Search

Your search keyword '"James S. Clark"' showing total 55 results
Start Over Author "James S. Clark" Topic 01 natural sciences
55 results on '"James S. Clark"'

1. Modeling spatially biased citizen science effort through the eBird database

Author

Becky Tang, Alan E. Gelfand, and James S. Clark

Subjects
Statistics and Probability, Database, Computer science, Sampling (statistics), 010501 environmental sciences, computer.software_genre, 01 natural sciences, 010104 statistics & probability, Citizen science, Preferential sampling, 0101 mathematics, Statistics, Probability and Uncertainty, Spatial dependence, Point process models, Scale (map), computer, 0105 earth and related environmental sciences, General Environmental Science, Spatial bias
Abstract

Citizen science databases are increasing in importance as sources of ecological information, but variability in effort across locations is inherent to such data. Spatially biased data—data not sampled uniformly across the study region—is expected. A further introduction of bias is variability in the level of sampling activity across locations. This motivates our work: with a spatial dataset of visited locations and sampling activity at those locations, we propose a model-based approach for assessing effort at these locations. Adjusting for potential spatial bias both in terms of sites visited and in terms of effort is crucial for developing reliable species distribution models (SDMs). Using data from eBird, a global citizen science database dedicated to avifauna, and illustrative regions in Pennsylvania and Germany, we model spatial dependence in both the observation locations and observed activity. We employ point process models to explain the observed locations in space, fit a geostatistical model to explain observation effort at locations, and explore the potential existence of preferential sampling, i.e., dependence between the two processes. Altogether, we offer a richer notion of sampling effort, combining information about location and activity. As SDMs are often used for their predictive capabilities, an important advantage of our approach is the ability to predict effort at unobserved locations and over regions. In this way, we can accommodate misalignment between point-referenced data and say, desired areal scale density. We briefly illustrate how our proposed methods can be applied to SDMs, with demonstrated improvement in prediction from models incorporating effort.

Published
2021
Full Text
View/download PDF

2. Continent-wide tree fecundity driven by indirect climate effects

Author

Robert Daley, Amanda M. Schwantes, Samantha Sutton, Cathryn H. Greenberg, William H. Schlesinger, Erin Shanahan, Jalene M. LaMontagne, Jonathan Myers, Andreas P. Wion, Shubhi Sharma, Michał Bogdziewicz, Jordan Luongo, Kristin Legg, Inés Ibáñez, Don C. Bragg, Adrian J. Das, Catherine A. Gehring, Christopher M. Moore, Eliot J. B. McIntire, C. Lane Scher, Michael Dietze, Ethan Ready, Jill F. Johnstone, James A. Lutz, Robert R. Parmenter, Robert A. Andrus, Diana Macias, Orrin Myers, Natalie L. Cleavitt, Michael A. Steele, Miranda D. Redmond, Jerry F. Franklin, James S. Clark, Yves Bergeron, Yassine Messaoud, Kai Zhu, Sam Pearse, Johannes M. H. Knops, Chase L. Nuñez, Roman Zlotin, Georges Kunstler, Thomas T. Veblen, Istem Fer, Walter D. Koenig, Thomas G. Whitham, Timothy J. Fahey, Dale G. Brockway, Janneke HilleRisLambers, Christopher L. Kilner, Gregory S. Gilbert, Benoît Courbaud, Renata Poulton-Kamakura, Scott M. Pearson, Nathan L. Stephenson, Kyle C. Rodman, Qinfeng Guo, Jennifer J. Swenson, Emily V. Moran, Susan L. Cohen, Margaret Swift, C. D. Reid, Mélaine Aubry-Kientz, Amy V. Whipple, Nicholas School of the Environment, Duke University [Durham], Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Colorado [Boulder], University of California [Merced], University of California, Université du Québec en Abitibi-Témiscamingue (UQAT), Adam Mickiewicz University in Poznań (UAM), USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), Cornell University [New York], Department Biostatistics University of North Carolina, University of North Carolina [Chapel Hill] (UNC), University of North Carolina System (UNC)-University of North Carolina System (UNC), National Park Service, United States Geological Survey (USGS), Boston University [Boston] (BU), Finnish Meteorological Institute (FMI), University of Washington [Seattle], Northern Arizona University [Flagstaff], University of California [Santa Cruz] (UCSC), Eastern Forest Environmental Threat Assessment Center, US Forest Service, University of Michigan System, University of Saskatchewan [Saskatoon] (U of S), Xi'an Jiaotong-Liverpool University [Suzhou], University of California [Berkeley], DePaul University [Chicago], Utah State University (USU), The University of New Mexico [Albuquerque], Pacific Forestry Centre, Natural Resources Canada (NRCan), University of Quebec (INRS-EMT), Colby College, Washington University in Saint Louis (WUSTL), Max Planck Society, United States Department of the Interior, Fort Collins Science Center, Mars Hill University, Colorado State University [Fort Collins] (CSU), University of Toronto, Wilkes University, Partenaires INRAE, Department of Geography, Bloomington, Russian and East European Institute, Bloomington, National Science Foundation (NSF) : DEB-1754443, Belmont Forum : 1854976, National Aeronautics & Space Administration (NASA) : AIST16-0052, AIST18-0063, and ANR-18-MPGA-0004,FORBIC,Prévision du changement de la biodiversité(2018)

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Climate Change, Science, Species distribution, General Physics and Astronomy, Climate change, Variation (game tree), Biology, 010603 evolutionary biology, 01 natural sciences, Article, General Biochemistry, Genetics and Molecular Biology, Climate effects, Trees, Theoretical, Models, Author Correction, 0105 earth and related environmental sciences, Multidisciplinary, Geography, Ecology, General Chemistry, Models, Theoretical, 15. Life on land, Fecundity, Climate Action, Tree (data structure), Fertility, 13. Climate action, North America, Seasons, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Tree species
Abstract

Indirect climate effects on tree fecundity that come through variation in size and growth (climate-condition interactions) are not currently part of models used to predict future forests. Trends in species abundances predicted from meta-analyses and species distribution models will be misleading if they depend on the conditions of individuals. Here we find from a synthesis of tree species in North America that climate-condition interactions dominate responses through two pathways, i) effects of growth that depend on climate, and ii) effects of climate that depend on tree size. Because tree fecundity first increases and then declines with size, climate change that stimulates growth promotes a shift of small trees to more fecund sizes, but the opposite can be true for large sizes. Change the depresses growth also affects fecundity. We find a biogeographic divide, with these interactions reducing fecundity in the West and increasing it in the East. Continental-scale responses of these forests are thus driven largely by indirect effects, recommending management for climate change that considers multiple demographic rates., Nature Communications, 12, ISSN:2041-1723

Published
2021
Full Text
View/download PDF

3. Is there tree senescence? The fecundity evidence

Author

Catherine A. Gehring, Tong Qiu, Kai Zhu, Richard K. Kobe, María Uriarte, James A. Lutz, Connie J. Clark, S. Joseph Wright, William Farfan-Rios, Sylvain Delzon, Thomas G. Whitham, Robert A. Andrus, Georges Kunstler, John R. Poulsen, Marie-Claire Aravena, Cathryn H. Greenberg, Andreas P. Wion, Ian S. Pearse, Amy V. Whipple, Miranda D. Redmond, Shubhi Sharma, Michał Bogdziewicz, Thomas A. Nagel, James S. Clark, Christopher L. Kilner, Kazuhiko Hoshizaki, Valentin Journé, Jalene M. LaMontagne, Margaret Swift, C. D. Reid, Jonathan Myers, Thomas T. Veblen, Benoît Courbaud, Walter D. Koenig, Kyle C. Rodman, Inés Ibáñez, Rafael Calama, Chase L. Nuñez, C. Lane Scher, Barbara Seget, Mateusz Ledwoń, Łukasz Piechnik, J. Julio Camarero, Qinfeng Guo, Thomas Boivin, Davide Ascoli, Janneke Hille Ris Lambers, Jennifer J. Swenson, Raúl Bonal, Sergio Calderón, Renata Poulton-Kamakura, Jess K. Zimmerman, Giorgio Vacchiano, Magdalena Żywiec, Miles R. Silman, Gregory S. Gilbert, Thomas Caignard, Harald Schmidt Van Marle, Roberta Berretti, Yves Bergeron, Renzo Motta, Nicholas School of the Environment, Duke University [Durham], Universidad de Chile, University of Colorado [Boulder], Department of Agriculture, Forest and Food Sciences, University of Torino, University of Quebec in Abitibi-Temiscamingue (UQAT), Adam Mickiewicz University in Poznań (UAM), Ecologie des Forêts Méditerranéennes (URFM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universidad Complutense de Madrid = Complutense University of Madrid [Madrid] (UCM), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centro de Investigacion Forestal (INIA-CIFOR), Instituto Nacional de Investigación y Tecnología Agraria y Alimentaria = National Institute for Agricultural and Food Research and Technology (INIA), Instituto Pirenaico de Ecologia (IPE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Missouri Botanical Garden, Northern Arizona University [Flagstaff], University of California [Santa Cruz] (UCSC), University of California, US DEPARTMENT OF AGRICULTURE FOREST SERVICE USA, Partenaires IRSTEA, Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA), Eastern Forest Environmental Threat Assessment Center, US Forest Service, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Akita University, University of Michigan [Ann Arbor], University of Michigan System, Michigan State University [East Lansing], Michigan State University System, University of California [Berkeley], DePaul University [Chicago], Polish Academy of Sciences (PAN), Department of Wildland Resources, Utah State University (USU), Washington University in Saint Louis (WUSTL), University of Ljubljana, Max Planck Institute of Animal Behavior, Fort Collins Science Center (FORT), US Geological Survey [Fort Collins], United States Geological Survey [Reston] (USGS)-United States Geological Survey [Reston] (USGS), W. Szafer Institute of Botany, Polska Akademia Nauk = Polish Academy of Sciences (PAN), Department of Forest and Rangeland Stewardship, Colorado State University [Fort Collins] (CSU), University of Wisconsin-Madison, Wake Forest University, Columbia University [New York], Department and Agricultural & Environmental Sciences, (DiSAA), University of Milan, Smithsonian Tropical Research Institute, University of Puerto Rico (UPR), National Science Foundation (NSF) : 1754443, Belmont Forum : 1854976, National Aeronautics and Space Administration (Advanced Information Systems Technology) : 16-0052 AIST18-0063, National Science Foundation (NSF) : DEB-1440409, W. Szafer Institute of Botany of the Polish Academy of Sciences, Foundation for Polish Science : 2019/33/B/NZ8/0134, National Science Foundation (NSF) : DEB 0963447 11222325 LTREB 1754647, Gordon and Betty Moore Foundation, United States Department of Agriculture (USDA)United States Forest Service, and ANR-18-MPGA-0004,FORBIC,Prévision du changement de la biodiversité(2018)

Subjects
0106 biological sciences, Senescence, Crown architecture, Biology, Forests, 010603 evolutionary biology, 01 natural sciences, Models, Biological, Trees, tree senescence, Tree life history, Models, Regeneration, Tree senescence, Architectural change, Allometric scaling, tree fecundity, Multidisciplinary, Ecology, crown architecture, Crown (botany), Regression analysis, 15. Life on land, Biological Sciences, Fecundity, Biological, Rate of increase, Fertility, Tree fecundity, Tree (set theory), Allometry, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, allometric scaling, 010606 plant biology & botany, tree life history
Abstract

International audience; Despite its importance for forest regeneration, food webs, and human economies, changes in tree fecundity with tree size and age remain largely unknown. The allometric increase with tree diameter assumed in ecological models would substantially overestimate seed contributions from large trees if fecundity eventually declines with size. Current estimates are dominated by overrepresentation of small trees in regression models. We combined global fecundity data, including a substantial representation of large trees. We compared size–fecundity relationships against traditional allometric scaling with diameter and two models based on crown architecture. All allometric models fail to describe the declining rate of increase in fecundity with diameter found for 80% of 597 species in our analysis. The strong evidence of declining fecundity, beyond what can be explained by crown architectural change, is consistent with physiological decline. A downward revision of projected fecundity of large trees can improve the next generation of forest dynamic models.

Published
2021
Full Text
View/download PDF

4. Spatiotemporal sensitivity of thermal stress for monitoring canopy hydrological stress in near real-time

Author

Bijan Seyednasrollah, James S. Clark, Jean-Christophe Domec, Department of Organismic and Evolutionary Biology, Harvard University [Cambridge], School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University [Flagstaff], Interactions Sol Plante Atmosphère (UMR ISPA), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro), Nicholas School of the Environment, and Duke University [Durham]

Subjects
0106 biological sciences, Canopy, Atmospheric Science, 010504 meteorology & atmospheric sciences, [SDV]Life Sciences [q-bio], evapotranspiration, Energy balance, Flux, Atmospheric sciences, 01 natural sciences, Stress (mechanics), remote sensing, Hydrology (agriculture), Evapotranspiration, 0105 earth and related environmental sciences, Global and Planetary Change, Forestry, Vegetation, 15. Life on land, thermal stress, 13. Climate action, [SDE]Environmental Sciences, Soil water, bayesian, hierarchical modeling, Agronomy and Crop Science, 010606 plant biology & botany
Abstract

International audience; Monitoring drought in real-time using minimal field data is a challenge for ecosystem management and conservation. Most methods require extensive data collection and in-situ calibration and accuracy is difficult to evaluate. Here, we demonstrated how the space-borne canopy "thermal stress", defined as surface-air temperature difference, provides a reliable surrogate for drought-induced water stress in vegetation. Using physics-based relationships that accommodate uncertainties, we showed how changes in canopy water flux from ground-based measurements relate to both the surface energy balance and remotely-sensed thermal stress. Field measurements of evapotranspiration in the southeastern and northwestern US verify this approach based on sensitivity of evapotranspiration to thermal stress in a large range of atmospheric and climate conditions. We found that a 1 degrees C change in the thermal stress is comparable to 1-1.2 mm day(-1) of evapotranspiration, depending on site and climate conditions. We quantified temporal and spatial sensitivity of evapotranspiration to the thermal stress and showed that it has the strongest relationship with evapotranspiration during warm and dry seasons, when monitoring drought is essential. Using only air and surface temperatures, we predicted the inter-annual anomaly in thermal stress across the contiguous United States over the course of 15 years and compared it with conventional drought indices. Among drought metrics that were considered in this study, the thermal stress had the highest correlation values. Our sensitivity results demonstrated that the thermal stress is a particularly strong indicator of water-use in warm seasons and regions. This simple metric can be used at varying time-scales to monitor surface evapotranspiration and drought in large spatial extents in near real-time.

Published
2019
Full Text
View/download PDF

5. On the interpretations of joint modelling in community ecology

Author

Wilfried Thuiller, Daria Bystrova, James S. Clark, Giovanni Poggiato, Julyan Arbel, Tamara Münkemüller, Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Nicholas School of the Environment, Duke University [Durham], Duke University, Department of Statistical Science, ERA-Net BiodivERsA -Belmont Forum, ANR-18-CE02-0025,GAMBAS,Nouvelles avancées dans la modélisation de la biodiversité et des services écosystémiques : améliorations statistiques et pertinences écologiques des modèles de distribution multi-espèces(2018), ANR-18-MPGA-0004,FORBIC,Prévision du changement de la biodiversité(2018), and ANR-18-EBI4-0009,FutureWeb,Climate and land use change threat to the vertebrate European food web structure and functioning(2018)

Subjects
0106 biological sciences, Community, Ecology, 010604 marine biology & hydrobiology, Ecology (disciplines), Climate, Rare species, Species distribution, Biodiversity, Biotic interactions, 15. Life on land, Joint Species Distribution Models, 010603 evolutionary biology, 01 natural sciences, Models, Biological, Field (geography), Community data, Geography, [SDE]Environmental Sciences, Joint (building), Biodiversity modelling, Ecology, Evolution, Behavior and Systematics, Environmental niche
Abstract

International audience; Explaining and modelling species communities is more than ever a central goal of ecology. Recently, joint species distribution models (JSDMs), which extend species distribution models (SDMs) by considering correlations among species, have been proposed to improve species community analyses and rare species predictions while potentially inferring species interactions. Here, we illustrate the mathematical links between SDMs and JSDMs and their ecological implications and demonstrate that JSDMs, just like SDMs, cannot separate environmental effects from biotic interactions. We provide a guide to the conditions under which JSDMs are (or are not) preferable to SDMs for species community modelling. More generally, we call for a better uptake and clarification of novel statistical developments in the field of biodiversity modelling.

Published
2021
Full Text
View/download PDF

6. Clustering Species With Residual Covariance Matrix in Joint Species Distribution Models

Author

Daria Bystrova, Giovanni Poggiato, Billur Bektaş, Julyan Arbel, James S. Clark, Alessandra Guglielmi, Wilfried Thuiller, Modèles statistiques bayésiens et des valeurs extrêmes pour données structurées et de grande dimension (STATIFY), Inria Grenoble - Rhône-Alpes, Institut National de Recherche en Informatique et en Automatique (Inria)-Institut National de Recherche en Informatique et en Automatique (Inria)-Laboratoire Jean Kuntzmann (LJK), Institut National de Recherche en Informatique et en Automatique (Inria)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA)-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA)-Institut polytechnique de Grenoble - Grenoble Institute of Technology (Grenoble INP ), Université Grenoble Alpes (UGA), Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Nicholas School of the Environment, Duke University [Durham], Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Dipartimento di Matematica, 'Francesco Brioschi', Politecnico di Milano [Milan] (POLIMI), ANR-18-CE02-0025,GAMBAS,Nouvelles avancées dans la modélisation de la biodiversité et des services écosystémiques : améliorations statistiques et pertinences écologiques des modèles de distribution multi-espèces(2018), ANR-15-IDEX-0002,UGA,IDEX UGA(2015), ANR-18-EBI4-0009,FutureWeb,Climate and land use change threat to the vertebrate European food web structure and functioning(2018), and ANR-19-P3IA-0003,MIAI,MIAI @ Grenoble Alpes(2019)

Subjects
0106 biological sciences, Computer science, dimension reduction, Species distribution, lcsh:Evolution, computer.software_genre, Residual, 010603 evolutionary biology, 01 natural sciences, Bayesian nonparametrics, 010104 statistics & probability, Dimension (vector space), lcsh:QH540-549.5, lcsh:QH359-425, 0101 mathematics, Cluster analysis, Ecology, Evolution, Behavior and Systematics, biodiversity modelling, Ecology, Covariance matrix, Dimensionality reduction, 15. Life on land, Visualization, joint species distribution model, plant communities, [STAT]Statistics [stat], Dirichlet process, [SDE]Environmental Sciences, Biodiversity modeling, Biodiversity modeling, dimension reduction, joint species distribution model, latent factors, Bayesian nonparametrics, plant communities, Data mining, latent factors, lcsh:Ecology, computer
Abstract

Modeling species distributions over space and time is one of the major research topics in both ecology and conservation biology. Joint Species Distribution models (JSDMs) have recently been introduced as a tool to better model community data, by inferring a residual covariance matrix between species, after accounting for species' response to the environment. However, these models are computationally demanding, even when latent factors, a common tool for dimension reduction, are used. To address this issue, Taylor-Rodriguez et al. (2017) proposed to use a Dirichlet process, a Bayesian nonparametric prior, to further reduce model dimension by clustering species in the residual covariance matrix. Here, we built on this approach to include a prior knowledge on the potential number of clusters, and instead used a Pitman–Yor process to address some critical limitations of the Dirichlet process. We therefore propose a framework that includes prior knowledge in the residual covariance matrix, providing a tool to analyze clusters of species that share the same residual associations with respect to other species. We applied our methodology to a case study of plant communities in a protected area of the French Alps (the Bauges Regional Park), and demonstrated that our extensions improve dimension reduction and reveal additional information from the residual covariance matrix, notably showing how the estimated clusters are compatible with plant traits, endorsing their importance in shaping communities.

Published
2021
Full Text
View/download PDF

7. Community Reorganization Response to Climate Change: Species Interactions, State-Space Modeling and Food Webs

Author

Amanda M. Schwantes, Lane Scher, Jennifer J. Swenson, Chase L. Nuñez, Christopher L. Kilner, James S. Clark, Tong Qui, and Shubham Sharma

Subjects
0106 biological sciences, Forest inventory, 010504 meteorology & atmospheric sciences, Environmental change, business.industry, Environmental resource management, Biodiversity, Climate change, 01 natural sciences, Breeding bird survey, Data modeling, Geography, Work (electrical), Habitat, business, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

Based on the data collected on the taxonomically diverse communities monitored in NEON (National Ecological Observatory Network), BBS (Breeding Bird Survey) and FIA (Forest Inventory & Analysis), we have forecasted community change and reorganization resulting from climate change across the coterminous USA. Predictive sensitivity analysis under climate change anticipates community reorganization and the habitats that will be most critical for new species assemblages. Our new semi-automated platform (pbgjam.org) enables revised forecasts as updated climate, remote sensing and biodiversity data come available. Our future work will build upon this modeling and platform by developing a dynamic, bio-physical framework to quantify the environment-species interactions that structure ecological communities and determine how they respond to environmental change.

Published
2020
Full Text
View/download PDF

8. Pervasive shifts in forest dynamics in a changing world

Author

Thomas A. M. Pugh, Craig D. Allen, Adam Hanbury-Brown, Ben Bond-Lamberty, Jeremy W. Lichstein, Daniel J. Johnson, Rupert Seidl, Louise Chini, James S. Clark, Nate G. McDowell, Lara M. Kueppers, Anthony P. Walker, Kristina J. Anderson-Teixeira, Charlotte Grossiord, María Uriarte, Monica G. Turner, Brian H. Aukema, Michael Dietze, Benjamin Poulter, George C. Hurtt, Kiona Ogle, Chonggang Xu, and Robert B. Jackson

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Acclimatization, Climate Change, Climate change, Forcing (mathematics), Forests, 010603 evolutionary biology, 01 natural sciences, Models, Biological, Trees, Biomass, 0105 earth and related environmental sciences, Biomass (ecology), Multidisciplinary, Land use, Forest dynamics, business.industry, Environmental resource management, Vegetation, 15. Life on land, Carbon Dioxide, Earth system science, Disturbance (ecology), 13. Climate action, Environmental science, business
Abstract

Shifting forest dynamics Forest dynamics are the processes of recruitment, growth, death, and turnover of the constituent tree species of the forest community. These processes are driven by disturbances both natural and anthropogenic. McDowell et al. review recent progress in understanding the drivers of forest dynamics and how these are interacting and changing in the context of global climate change. The authors show that shifts in forest dynamics are already occurring, and the emerging pattern is that global forests are tending toward younger stands with faster turnover as old-growth forest with stable dynamics are dwindling. Science , this issue p. eaaz9463

Published
2020
Full Text
View/download PDF

9. Joint Temporal Point Pattern Models for Proximate Species Occurrence in a Fixed Area Using Camera Trap Data

Author

Alan E. Gelfand, James S. Clark, Roland Kays, and Erin M. Schliep

Subjects
0106 biological sciences, Statistics and Probability, Multivariate statistics, Computer science, Applied Mathematics, Inference, Field of view, Interval (mathematics), 010603 evolutionary biology, 01 natural sciences, Agricultural and Biological Sciences (miscellaneous), Hierarchical database model, Cox process, 010104 statistics & probability, Statistics, Camera trap, 0101 mathematics, Statistics, Probability and Uncertainty, General Agricultural and Biological Sciences, Time complexity, General Environmental Science
Abstract

The distinction between an overlap in species daily activity patterns and proximate co-occurrence of species for a location and time due to behavioral attraction or avoidance is critical when addressing the question of species co-occurrence. We use data from a dense grid of camera traps in a forest in central North Carolina to inform about proximate co-occurrence. Camera trigger times are recorded when animals pass in front of the camera’s field of vision. We view the data as a point pattern over time for each species and model the intensities driving these patterns. These species-specific intensities are modeled jointly in linear time to preserve the notion of co-occurrence. We show that a multivariate log-Gaussian Cox process incorporating both circular and linear time provides a preferred choice for modeling occurrence of forest mammals based on daily activity rhythms. Model inference is obtained under a hierarchical Bayesian framework with an efficient Markov chain Monte Carlo sampling algorithm. After model fitting, we account for imperfect detection of individuals by the camera traps by incorporating species-specific detection probabilities that adjust estimates of occurrence and co-occurrence. We obtain rich inference including assessment of the probability of presence of one species in a particular time interval given presence of another species in the same or adjacent interval, enabling probabilities of proximate co-occurrence. Our results describe the ecology and interactions of four common mammals within this suburban forest including their daily rhythms, responses to temperature and rainfall, and effects of the presence of predator species. Supplementary materials accompanying this paper appear online.

Published
2018
Full Text
View/download PDF

10. Total C and N Pools and Fluxes Vary with Time, Soil Temperature, and Moisture Along an Elevation, Precipitation, and Vegetation Gradient in Southern Appalachian Forests

Author

James S. Clark, Craig R. See, James M. Vose, Chelcy Ford Miniat, and Jennifer D. Knoepp

Subjects
Biomass (ecology), 010504 meteorology & atmospheric sciences, Ecology, Growing season, Experimental forest, 04 agricultural and veterinary sciences, Vegetation, Plant litter, Atmospheric sciences, 01 natural sciences, Soil water, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Environmental Chemistry, Soil horizon, Environmental science, Precipitation, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences
Abstract

The interactions of terrestrial C pools and fluxes with spatial and temporal variation in climate are not well understood. We conducted this study in the southern Appalachian Mountains where complex topography provides variability in temperature, precipitation, and forest communities. In 1990, we established five large plots across an elevation gradient allowing us to study the regulation of C and N pools and cycling by temperature and water, in reference watersheds in Coweeta Hydrologic Laboratory, a USDA Forest Service Experimental Forest, in western NC, USA. Communities included mixed-oak pine, mixed-oak, cove hardwood, and northern hardwood. We examined 20-year changes in overstory productivity and biomass, leaf litterfall C and N fluxes, and total C and N pools in organic and surface mineral soil horizons, and coarse wood, and relationships with growing season soil temperature and precipitation. Productivity increased over time and with precipitation. Litterfall C and N flux increased over time and with increasing temperature and precipitation, respectively. Organic horizon C and N did not change over time and were not correlated to litterfall inputs. Mineral soil C and N did not change over time, and the negative effect of temperature on soil pools was evident across the gradient. Our data show that increasing temperature and variability in precipitation will result in altered aboveground productivity. Variation in surface soil C and N is related to topographic variation in temperature which is confounded with vegetation community. Data suggest that climatic changes will result in altered aboveground and soil C and N sequestration and fluxes.

Published
2018
Full Text
View/download PDF

11. Temporal coexistence mechanisms contribute to the latitudinal gradient in forest diversity

Author

Anthony R. Ives, James S. Clark, S. Joseph Wright, Nancy C. Garwood, Renato Valencia, Jill F. Johnstone, Jacob Usinowicz, Zhanqing Hao, Jess K. Zimmerman, I-Fang Sun, Margaret R. Metz, Yunyun Wang, Christine Fletcher, Chia-Hao Chang-Yang, Yu-Yun Chen, Yiching Lin, Tohru Nakashizuka, and Takashi Masaki

Subjects
0106 biological sciences, Tropical Climate, Time Factors, Multidisciplinary, Ecology, Reproduction, 010604 marine biology & hydrobiology, Niche differentiation, Biodiversity, Geographic Mapping, Forests, Biology, Storage effect, 010603 evolutionary biology, 01 natural sciences, Trees, Spatio-Temporal Analysis, Tropical climate, Temperate climate, Biological dispersal, Seasons, Ecosystem diversity, Temperate rainforest
Abstract

The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.

Published
2017
Full Text
View/download PDF

12. Dynamics of soil CO 2 efflux under varying atmospheric CO 2 concentrations reveal dominance of slow processes

Author

Dohyoung Kim, A. Christopher Oishi, Heather R. McCarthy, Kurt H. Johnsen, Ram Oren, James S. Clark, Chris A. Maier, and Sari Palmroth

Subjects
0106 biological sciences, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Co2 efflux, Biology, Photosynthesis, 01 natural sciences, Soil respiration, chemistry.chemical_compound, Animal science, chemistry, Co2 concentration, Botany, Carbon dioxide, Respiration, Environmental Chemistry, Dominance (ecology), Ecosystem, 010606 plant biology & botany, 0105 earth and related environmental sciences, General Environmental Science
Abstract

We evaluated the effect on soil CO2 efflux (FCO2) of sudden changes in photosynthetic rates by altering CO2 concentration in plots subjected to +200 ppmv for 15 years. Five-day intervals of exposure to elevated CO2 (eCO2) ranging 1.0–1.8 times ambient did not affect FCO2. FCO2 did not decrease until 4 months after termination of the long-term eCO2 treatment, longer than the 10 days observed for decrease of FCO2 after experimental blocking of C flow to belowground, but shorter than the ~13 months it took for increase of FCO2 following the initiation of eCO2. The reduction of FCO2 upon termination of enrichment (~35%) cannot be explained by the reduction of leaf area (~15%) and associated carbohydrate production and allocation, suggesting a disproportionate contraction of the belowground ecosystem components; this was consistent with the reductions in base respiration and FCO2-temperature sensitivity. These asymmetric responses pose a tractable challenge to process-based models attempting to isolate the effect of individual processes on FCO2.

Published
2017
Full Text
View/download PDF

13. Generalized joint attribute modeling for biodiversity analysis: median‐zero, multivariate, multifarious data

Author

Bijan Seyednasrollah, James S. Clark, Diana R. Nemergut, Phillip J. Turner, and Stacy Y. Zhang

Subjects
0106 biological sciences, Ordinal data, Multivariate statistics, Computer science, Ecology, Species distribution, Probabilistic logic, 010603 evolutionary biology, 01 natural sciences, Hierarchical database model, 010104 statistics & probability, Joint probability distribution, Statistics, Range (statistics), Quantitative Biology::Populations and Evolution, 0101 mathematics, Categorical variable, Ecology, Evolution, Behavior and Systematics
Abstract

Probabilistic forecasts of species distribution and abundance require models that accommodate the range of ecological data, including a joint distribution of multiple species based on combinations of continuous and discrete observations, mostly zeros. We develop a generalized joint attribute model (GJAM), a probabilistic framework that readily applies to data that are combinations of presence-absence, ordinal, continuous, discrete, composition, zero-inflated, and censored. It does so as a joint distribution over all species providing inference on sensitivity to input variables, correlations between species on the data scale, prediction, sensitivity analysis, definition of community structure, and missing data imputation. GJAM applications illustrate flexibility to the range of species-abundance data. Applications to forest inventories demonstrate species relationships responding as a community to environmental variables. It shows that the environment can be inverse predicted from the joint distribution of species. Application to microbiome data demonstrates how inverse prediction in the GJAM framework accelerates variable selection, by isolating effects of each input variable's influence across all species.

Published
2017
Full Text
View/download PDF

14. On the properties of the massive binary black hole merger GW170729

Author

Vivien Raymond, Bela Szilagyi, Andrea Taracchini, Gregorio Carullo, Mark Hannam, Juan Calderón Bustillo, Daniel A. Hemberger, Alejandro Bohé, R. Cotesta, Alyssa Garcia, Richard O'Shaughnessy, Lawrence E. Kidder, Manuela Campanelli, Michael Pürrer, Patricia Schmidt, Kevin Barkett, Alessandra Buonanno, Michael Boyle, Sebastian Khan, Pablo Laguna, Geoffrey Lovelace, Margaret Millhouse, Lionel London, Salvatore Vitale, Nousha Afshari, Carl-Johan Haster, Harald P. Pfeiffer, Katerina Chatziioannou, H. Fong, Yosef Zlochower, I. W. Harry, Ian Hinder, Prayush Kumar, Francesco Pannarale, Lijing Shao, Eric B. Flynn, James S. Clark, Deirdre Shoemaker, Matthew Giesler, M. Haney, Carlos O. Lousto, Frank Ohme, Stanislav Babak, S. Ghonge, Saul A. Teukolsky, Mark A. Scheel, Tony Chu, Bhavesh Khamersa, Ken K. Y. Ng, L. K. Nuttall, Tyson Littenberg, James Healy, J. S. Lange, Jonathan Blackman, Karan Jani, S. Ossokine, AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Centre National d'Études Spatiales [Toulouse] (CNES), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université de Paris (UP), Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Université Paris Cité (UPCité)

Subjects
gr-qc, ST/L000962/1, FOS: Physical sciences, alternative theories of gravity, Astophysics, General Relativity and Quantum Cosmology (gr-qc), spin, gravitational radiation: direct detection, 01 natural sciences, General Relativity and Quantum Cosmology, Gravitational waves, Binary black hole, Consistency (statistics), 0103 physical sciences, Prior probability, black hole, Waveform, ST/N000633/1, 010306 general physics, 10. No inequality, STFC, Spin-½, High Energy Astrophysical Phenomena (astro-ph.HE), Physics, astro-ph.HE, spin: precession, black holes, 010308 nuclear & particles physics, Gravitational wave, gravitational radiation, RCUK, Mass ratio, binary: compact, effect: higher-order, Computational physics, Black hole, General relativity, black hole: binary, gravitational radiation: emission, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], mass ratio, Astrophysics - High Energy Astrophysical Phenomena, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
Abstract

We present a detailed investigation into the properties of GW170729, the gravitational wave with the most massive and distant source confirmed to date. We employ an extensive set of waveform models, including new improved models that incorporate the effect of higher-order waveform modes which are particularly important for massive systems. We find no indication of spin-precession, but the inclusion of higher-order modes in the models results in an improved estimate for the mass ratio of $(0.3-0.8)$ at the 90\% credible level. Our updated measurement excludes equal masses at that level. We also find that models with higher-order modes lead to the data being more consistent with a smaller effective spin, with the probability that the effective spin is greater than zero being reduced from $99\%$ to $94\%$. The 90\% credible interval for the effective spin parameter is now $(-0.01-0.50)$. Additionally, the recovered signal-to-noise ratio increases by $\sim0.3$ units compared to analyses without higher-order modes. We study the effect of common spin priors on the derived spin and mass measurements, and observe small shifts in the spins, while the masses remain unaffected. We argue that our conclusions are robust against systematic errors in the waveform models. We also compare the above waveform-based analysis which employs compact-binary waveform models to a more flexible wavelet- and chirplet-based analysis. We find consistency between the two, with overlaps of $\sim 0.9$, typical of what is expected from simulations of signals similar to GW170729, confirming that the data are well-described by the existing waveform models. Finally, we study the possibility that the primary component of GW170729 was the remnant of a past merger of two black holes and find this scenario to be indistinguishable from the standard formation scenario., Comment: 14 pages, 8 figures, final published version, samples available at https://git.ligo.org/katerina.chatziioannou/gw170729hm_datarelease

Published
2019
Full Text
View/download PDF

15. Health of North Atlantic right whales Eubalaena glacialis over three decades: from individual health to demographic and population health trends

Author

Robert S. Schick, Scott D. Kraus, Heather M. Pettis, James S. Clark, Rosalind M. Rolland, Philip K. Hamilton, and Amy R. Knowlton

Subjects
0106 biological sciences, Ecology, 010604 marine biology & hydrobiology, media_common.quotation_subject, Population health, Aquatic Science, Biology, 010603 evolutionary biology, 01 natural sciences, Fishery, Individual health, Reproduction, Ecology, Evolution, Behavior and Systematics, Body condition, media_common
Published
2016
Full Text
View/download PDF

16. Seed predation and climate impacts on reproductive variation in temperate forests of the southeastern USA

Author

David M. Bell and James S. Clark

Subjects
0106 biological sciences, Insecta, Climate, media_common.quotation_subject, Rodentia, Forests, Biology, 010603 evolutionary biology, 01 natural sciences, Predation, Birds, Quercus, biology.animal, Temperate climate, Animals, Ecology, Evolution, Behavior and Systematics, media_common, Appalachian Region, Drupe, Ecology, Reproduction, food and beverages, Vertebrate, Feeding Behavior, Fecundity, Southeastern United States, Predatory Behavior, Seed predation, Seeds, Vertebrates, Temperate rainforest, 010606 plant biology & botany
Abstract

Climatic effects on tree recruitment will be determined by the interactive effects of fecundity and seed predation. Evaluating how insect and vertebrate seed predators mediate tree reproductive responses to climate depends on long-term studies of seed production, development, and predation. In this study, our objectives were to (1) assess the effects of interannual climate variation on seed abortion rates, (2) assess the impact of seed density on predation rates, and (3) examine the degree to which density-dependent seed predation would amplify or dampen interannual variation in fecundity associated with seed abortion. We used a 19-year study of seed abortion and pre-dispersal predation rates by insects and vertebrates (birds and rodents) for five temperate tree species across forest plots from the North Carolina Piedmont to the Southern Appalachian Mountains in the southeastern USA. We found that rates of seed abortion and predation increased reproductive variation for oaks (Quercus species). Probability of seed abortion was greatest during years with cool, dry springs. Responses of seed predation on Quercus species to current year's seed density varied by species, but exhibited positive density-dependence to previous year's seed density consistent with numerical responses of seed predators. Seed abortion and predation rates for two drupe species responded little to variation in climate or seed density, respectively. Given that predation increased interannual variation in seed availability and the negative density-dependence to previous year's seed density, our results indicate that consistent numerical responses of oak seed predators may amplify interannual variation due to climate-mediated processes like seed abortion.

Published
2016
Full Text
View/download PDF

17. Understanding the continuous phenological development at daily time step with a Bayesian hierarchical space-time model: impacts of climate change and extreme weather events

Author

Conghe Song, Tong Qiu, Nuvan Rathnayaka, James S. Clark, Junxiang Li, and Bijan Seyednasrollah

Subjects
010504 meteorology & atmospheric sciences, Phenology, 0208 environmental biotechnology, Soil Science, Climate change, Growing season, Geology, 02 engineering and technology, Vegetation, Land cover, 01 natural sciences, 020801 environmental engineering, Extreme weather, Climatology, Frost, Environmental science, Precipitation, Computers in Earth Sciences, 0105 earth and related environmental sciences, Remote sensing
Abstract

The impacts of climate change and extreme weather events (e.g. frost-, heat-, drought-, and heavy rainfall events) on the continuous phenological development over the entire seasonal cycle remained poorly understood. Previous studies mainly focused on modeling key phenological transition dates (e.g. discrete timing of spring bud-break and fall senescence) based on aggregated climate variables (e.g. mean temperature, growing-degree days). We developed and evaluated a Bayesian Hierarchical Space-Time model for Land Surface Phenology (BHST-LSP) to synthesize remotely sensed vegetation greenness with climate covariates at a daily temporal scale from 1981 to 2014 across the entire conterminous United States. The BHST-LSP model incorporated both temporal and spatial information and exhibited high predictive power in simulating daily phenological development with an overall out-of-sample R2 of 0.80 ± 0.17 and 0.72 ± 0.20 for spring and fall phenology, respectively. The overall out-of-sample normalized root mean square errors were 9.3% ± 6.1% and 9.9% ± 5.2% between the observed and predicted vegetation greenness for spring and fall phenology, respectively. We found that a fast increase of temperature can accelerate the speed of spring green-up while a slow decrease of temperature can lead to a decelerated fall brown-down. Increasing accumulated precipitation can benefit daily phenological development over an entire growing season, while extreme rainfall events can have the opposite effects. More frequent frost events could slow spring leaf expansion and accelerate fall leaf senescence. Impacts of extreme heat events were complex and depended on water availability. Cropland in the Midwest as well as evergreen needleleaf forest along the coastal regions showed relatively strong resistance to drought events compared to other land cover types. The BHST-LSP model can be used to forecast vegetation phenology given future climate projection, thus providing valuable information for adopting climate change adaptation and mitigation measures.

Published
2020
Full Text
View/download PDF

18. Leaf phenology paradox: Why warming matters most where it is already warm

Author

Bijan Seyednasrollah, James S. Clark, Jennifer J. Swenson, Jean-Christophe Domec, Department of Organismic and Evolutionary Biology, Harvard University [Cambridge], Nicholas School of the Environment, Duke University [Durham], School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University [Flagstaff], Interactions Sol Plante Atmosphère (UMR ISPA), and Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)

Subjects
0106 biological sciences, Canopy, green-up, 010504 meteorology & atmospheric sciences, warming, NDVI, multispectral, [SDV]Life Sciences [q-bio], Soil Science, Climate change, land surface temperature, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, phenology, forest, Ecosystem, Computers in Earth Sciences, 0105 earth and related environmental sciences, Remote sensing, spring, Phenology, Global warming, Geology, Vegetation, daily vegetation index, 15. Life on land, Evergreen, EVI, Deciduous, climate change, MODIS, 13. Climate action, [SDE]Environmental Sciences, bayesian, southeastern US, Environmental science, hierarchical modeling
Abstract

International audience; Interactions between climate and ecosystem properties that control phenological responses to climate warming and drought are poorly understood. To determine contributions from these interactions, we used space-borne remotely sensed vegetation indices to monitor leaf development across climate gradients and ecoregions in the southeastern United States. We quantified how air temperature, drought severity, and canopy thermal stress contribute to changes in leaf flushing from mountainous to coastal plain regions by developing a hierarchical state-space Bayesian model. We synthesized daily field climate data with daily vegetation indices and canopy surface temperature during spring green-up season at 59 sites in the southeastern United States between 2001 and 2012. Our results demonstrated strong interaction effects between ecosystem properties and climate variables across ecoregions. We found spring green-up is faster in the mountains, while coastal forests express a larger sensitivity to inter-annual temperature anomalies. Despite our detection of a decreasing trend in sensitivity to warming with temperature in all regions, we identified an ecosystem interaction: Deciduous dominated forests are less sensitive to warming than are those with fewer deciduous trees, likely due to the continuous presence of leaves in evergreen species throughout the season. Mountainous forest green-up is more susceptible to intensifying drought and moisture deficit, while coastal areas are relatively resilient. We found that with increasing canopy thermal stress, defined as canopy-air temperature difference, leaf development slows following dry years, and accelerates following wet years.

Published
2018
Full Text
View/download PDF

19. Joint Modeling of Climate Niches for Adult and Juvenile Trees

Author

Souparno Ghosh, Alan E. Gelfand, James S. Clark, and Kai Zhu

Subjects
0106 biological sciences, Statistics and Probability, Ecological niche, Forest inventory, 010504 meteorology & atmospheric sciences, Ecology, Applied Mathematics, Niche, Biology, 010603 evolutionary biology, 01 natural sciences, Agricultural and Biological Sciences (miscellaneous), Basal area, Abundance (ecology), Covariate, Spatial ecology, Statistics, Probability and Uncertainty, General Agricultural and Biological Sciences, Relative abundance distribution, 0105 earth and related environmental sciences, General Environmental Science
Abstract

Typical ecological gradient analysis for plant species considers variation in the response along a gradient of covariate values, for example, temperature or precipitation. Response is customarily modeled through the presence/absence or a suitable measure of abundance or both. Such analysis enables the creation of a climate niche or range limits for the species using this covariate. Interest often extends to two climate covariates, thus seeking a climate niche in two-dimensional space. It also seeks to learn whether the niche changes over life stages of the species. For instance, is the niche for juveniles different from that for adults? Across the climate domain, where are seedlings relatively more or less abundant than adults? Adult abundance is measured through basal area, juvenile abundance through seedling counts. Our contribution is to describe a coherent modeling approach to address the foregoing objectives. We construct a hierarchical stochastic specification that jointly models juveniles and adults with regard to their two-dimensional climate niches. Joint modeling of the abundance response surfaces is proposed because seedlings and adults are living jointly, competitively and is justified through exploratory analysis. Joint modeling can be challenging when one response is counts and the other is area. We model adult abundance and then juvenile abundance driven by adult abundance. Due to excess zeroes over our study plots, we employ zero-inflated models for both adult and seedling abundance. We demonstrate the benefits of the joint modeling through out-of-sample predictive performance. Our abundance data come from the USDA Forest Service’s Forest Inventory and Analysis dataset. Our climate data come from the 800 m resolution Parameter-elevation Regressions on Independent Slopes Model dataset. In order to extract a response to climate, we aggregate FIA plots to ecological subsections. At plot scale, micro-scale covariates explain variation in abundance; at a larger spatial scale, climate covariates can explain variation in abundance.

Published
2015
Full Text
View/download PDF

20. Modeling change in forest biomass across the eastern US

Author

Kai Zhu, Erin M. Schliep, James S. Clark, and Alan E. Gelfand

Subjects
0106 biological sciences, Statistics and Probability, Biomass (ecology), Forest inventory, 010504 meteorology & atmospheric sciences, Tree allometry, 010603 evolutionary biology, 01 natural sciences, Hierarchical database model, Statistics, Econometrics, Range (statistics), Quantitative Biology::Populations and Evolution, Bayesian hierarchical modeling, Allometry, Species richness, Statistics, Probability and Uncertainty, 0105 earth and related environmental sciences, General Environmental Science, Mathematics
Abstract

Predictions of above-ground biomass and the change in above-ground biomass require attachment of uncertainty due the range of reported predictions for forests. Because above-ground biomass is seldom measured, there have been no opportunities to obtain such uncertainty estimates. Standard methods involve applying an allometric equation to each individual tree on sample plots and summing the individual values. There is uncertainty in the allometry which leads to uncertainty in biomass at the tree level. Due to interdependence between competing trees, the uncertainty at the plot level that results from aggregating individual tree biomass in this way is expected to overestimate variability. That is, the variance at the plot level should be less than the sum of the individual variances. We offer a modeling strategy to learn about change in biomass at the plot level and model cumulative uncertainty to accommodate this dependence among neighboring trees. The plot-level variance is modeled using a parametric density-dependent asymptotic function. Plot-by-time covariate information is introduced to explain the change in biomass. These features are incorporated into a hierarchical model and inference is obtain within a Bayesian framework. We analyze data for the eastern United States from the Forest Inventory and Analysis (FIA) Program of the US Forest Service. This region contains roughly 25,000 FIA monitored plots from which there are measurements of approximately 1 million trees spanning more than 200 tree species. Due to the high species richness in the FIA data, we combine species into plant functional types. We present predictions of biomass and change in biomass for two plant functional types.

Published
2015
Full Text
View/download PDF

22. Joint Species Distribution Modeling: Dimension Reduction Using Dirichlet Processes

Author

Daniel Taylor-Rodriguez, Erin M. Schliep, James S. Clark, Alan E. Gelfand, and Kimberly Kaufeld

Subjects
0106 biological sciences, Statistics and Probability, abundance, latent variables, Applied Mathematics, Species distribution, presence–absence, Covariance, 010603 evolutionary biology, 01 natural sciences, Dirichlet distribution, Dirichlet process, 010104 statistics & probability, symbols.namesake, Markov chain Monte Carlo, Abundance (ecology), Statistics, Binary data, symbols, Econometrics, Dirichlet-multinomial distribution, hierarchical model, 0101 mathematics, Gibbs sampling, Mathematics
Abstract

Species distribution models are used to evaluate the variables that affect the distribution and abundance of species and to predict biodiversity. Historically, such models have been fitted to each species independently. While independent models can provide useful information regarding distribution and abundance, they ignore the fact that, after accounting for environmental covariates, residual interspecies dependence persists. With stacking of individual models, misleading behaviors, may arise. In particular, individual models often imply too many species per location. ¶ Recently developed joint species distribution models have application to presence–absence, continuous or discrete abundance, abundance with large numbers of zeros, and discrete, ordinal, and compositional data. Here, we deal with the challenge of joint modeling for a large number of species. To appreciate the challenge in the simplest way, with just presence/absence (binary) response and say, $S$ species, we have an $S$ -way contingency table with $2^{S}$ cell probabilities. Even if $S$ is as small as $100$ this is an enormous table, infeasible to work with without some structure to reduce dimension. ¶ We develop a computationally feasible approach to accommodate a large number of species (say order $10^{3}$ ) that allows us to: 1) assess the dependence structure across species; 2) identify clusters of species that have similar dependence patterns; and 3) jointly predict species distributions. To do so, we build hierarchical models capturing dependence between species at the first or “data” stage rather than at a second or “mean” stage. We employ the Dirichlet process for clustering in a novel way to reduce dimension in the joint covariance structure. This last step makes computation tractable. ¶ We use Forest Inventory Analysis (FIA) data in the eastern region of the United States to demonstrate our method. It consists of presence–absence measurements for 112 tree species, observed east of the Mississippi. As a proof of concept for our dimension reduction approach, we also include simulations using continuous and binary data.

Published
2017

23. Associations among arbuscular mycorrhizal fungi and seedlings are predicted to change with tree successional status

Author

Jess K. Zimmerman, María Uriarte, Jill Thompson, Jimena Forero-Montaña, Robert Muscarella, Nathan G. Swenson, Benedicte Bachelot, James S. Clark, and Krista L. McGuire

Subjects
0106 biological sciences, Specific leaf area, Tropical forests, Leaf damage, Arbuscular mycorrhizal fungi, Ecological succession, Biology, 010603 evolutionary biology, 01 natural sciences, Ecology and Environment, Trees, Abundance (ecology), Mycorrhizae, Succession, Ecology, Evolution, Behavior and Systematics, Soil Microbiology, Ecology, fungi, Puerto Rico, Fungi, food and beverages, Generalized joint attribute modeling, Seedlings, Trait, Luquillo Forest Dynamics Plot, Arbuscular mycorrhizal, Tree species, Functional traits, 010606 plant biology & botany
Abstract

Arbuscular mycorrhizal (AM) fungi in the soil may influence tropical tree dynamics and forest succession. The mechanisms are poorly understood, because the functional characteristics and abundances of tree species and AM fungi are likely to be codependent. We used generalized joint attribute modeling to evaluate if AM fungi are associated with three forest community metrics for a sub-tropical montane forest in Puerto Rico. The metrics chosen to reflect changes during forest succession are the abundance of seedlings of different successional status, the amount of foliar damage on seedlings of different successional status, and community-weighted mean functional trait values (adult specific leaf area [SLA], adult wood density, and seed mass). We used high-throughput DNA sequencing to identify fungal operational taxonomic units (OTUs) in the soil. Model predictions showed that seedlings of mid- and late-successional species had less leaf damage when the 12 most common AM fungi were abundant compared to when these fungi were absent. We also found that seedlings of mid-successional species were predicted to be more abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. In contrast, early-successional tree seedlings were predicted to be less abundant when the 12 most common AM fungi were abundant compared to when these fungi were absent. Finally, we showed that, among the 12 most common AM fungi, different AM fungi were correlated with functional trait characteristics of early- or late-successional species. Together, these results suggest that early-successional species might not rely as much as mid- and late-successional species on AM fungi, and AM fungi might accelerate forest succession.

Published
2017
Full Text
View/download PDF

24. Tree water balance drives temperate forest responses to drought

Author

Aaron B. Berdanier and James S. Clark

Subjects
0106 biological sciences, Ecophysiology, Biomass (ecology), 010504 meteorology & atmospheric sciences, Moisture, Ecology, Temperate forest, Water, Forests, 01 natural sciences, Droughts, Trees, Water balance, Tree (data structure), Environmental science, Biomass, Water content, Ecology, Evolution, Behavior and Systematics, Water use, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

Intensifying drought is increasingly linked to global forest diebacks. Improved understanding of drought impacts on individual trees has provided limited insight into drought vulnerability in part because tree moisture access and depletion is difficult to quantify. In forests, moisture reservoir depletion occurs through water use by the trees themselves. Here, we show that drought impacts on tree fitness and demographic performance can be predicted by tracking the moisture reservoir available to trees as a mass balance, estimated in a hierarchical state-space framework. We apply this model to multiple seasonal droughts with tree transpiration measurements to demonstrate how species and size differences modulate moisture availability across landscapes. The depletion of individual moisture reservoirs can be tracked over the course of droughts and linked to biomass growth and reproductive output. This mass balance approach can predict individual moisture deficit, tree demographic performance, and drought vulnerability throughout forest stands based on measurements from a sample of trees.

Published
2017

25. Biomass prediction using a density-dependent diameter distribution model

Author

James S. Clark, Alan E. Gelfand, Bradley J. Tomasek, and Erin M. Schliep

Subjects
hierarchical models, 0106 biological sciences, Statistics and Probability, Allometry, big O behavior, 010504 meteorology & atmospheric sciences, Scale (ratio), Tree allometry, Biomass, Regression analysis, Markov chain Monte Carlo, Poisson process, 010603 evolutionary biology, 01 natural sciences, Regression, symbols.namesake, Modeling and Simulation, Covariate, Statistics, symbols, Statistics, Probability and Uncertainty, 0105 earth and related environmental sciences, Mathematics
Abstract

Prediction of aboveground biomass, particularly at large spatial scales, is necessary for estimating global-scale carbon sequestration. Since biomass can be measured only by sacrificing trees, total biomass on plots is never observed. Rather, allometric equations are used to convert individual tree diameter to individual biomass, perhaps with noise. The values for all trees on a plot are then summed to obtain a derived total biomass for the plot. Then, with derived total biomasses for a collection of plots, regression models, using appropriate environmental covariates, are employed to attempt explanation and prediction. Not surprisingly, when out-of-sample validation is examined, such a model will predict total biomass well for holdout data because it is obtained using exactly the same derived approach. ¶ Apart from the somewhat circular nature of the regression approach, it also fails to employ the actual observed plot level response data. At each plot, we observe a random number of trees, each with an associated diameter, producing a sample of diameters. A model based on this random number of tree diameters provides understanding of how environmental regressors explain abundance of individuals, which in turn explains individual diameters. ¶ We incorporate density dependence because the distribution of tree diameters over a plot of fixed size depends upon the number of trees on the plot. After fitting this model, we can obtain predictive distributions for individual-level biomass and plot-level total biomass. We show that predictive distributions for plot-level biomass obtained from a density-dependent model for diameters will be much different from predictive distributions using the regression approach. Moreover, they can be more informative for capturing uncertainty than those obtained from modeling derived plot-level biomass directly. ¶ We develop a density-dependent diameter distribution model and illustrate with data from the national Forest Inventory and Analysis (FIA) database. We also describe how to scale predictions to larger spatial regions. Our predictions agree (in magnitude) with available wisdom on mean and variation in biomass at the hectare scale.

Published
2017
Full Text
View/download PDF

26. Divergent reproductive allocation trade‐offs with canopy exposure across tree species in temperate forests

Author

Aaron B. Berdanier and James S. Clark

Subjects
0106 biological sciences, Canopy, life history, media_common.quotation_subject, Biology, Trade-off, 010603 evolutionary biology, 01 natural sciences, Competition (biology), forest, allocation, lcsh:QH540-549.5, Life history, Ecology, Evolution, Behavior and Systematics, media_common, Biomass (ecology), Ecology, biomass, Agroforestry, Trade offs, lcsh:Ecology, light, Temperate rainforest, Tree species, competition, 010606 plant biology & botany
Abstract

Variation in tree reproduction can alter forest community dynamics, especially if reproductive output is costly for other functions like growth. However, empirical studies reach conflicting conclusions about the constraints on reproductive allocation relative to growth and how they vary through time, across species, and between environments. Here, we test the hypothesis that a critical resource, canopy exposure to light availability, limits reproductive allocation by comparing long‐term relationships between reproduction and growth for trees from 21 species in forests throughout the Southeastern United States. We found that species have divergent responses to light availability, with shade‐intolerant species experiencing an alleviation of trade‐offs at high light‐ and shade‐tolerant species showing no changes in reproductive output across light environments. Correlations between temporal variation in individual growth and reproduction were weak and generally insensitive to canopy exposure, but changed when considering time lags. The diversity of responses across species indicates that reproductive allocation for trees in these forests is strongly influenced by both species’ life history and environmental heterogeneity in space and time.

Published
2016

27. Multiyear drought-induced morbidity preceding tree death in southeastern U.S. forests

Author

James S. Clark and Aaron B. Berdanier

Subjects
0106 biological sciences, Moisture availability, Drought stress, Time Factors, 010504 meteorology & atmospheric sciences, Ecology, fungi, Drought tolerance, food and beverages, Inventory data, Biology, Forests, 01 natural sciences, Droughts, Trees, Species Specificity, parasitic diseases, Long term data, North Carolina, Ecosystem, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

Recent forest diebacks, combined with threats of future drought, focus attention on the extent to which tree death is caused by catastrophic events as opposed to chronic declines in health that accumulate over years. While recent attention has focused on large-scale diebacks, there is concern that increasing drought stress and chronic morbidity may have pervasive impacts on forest composition in many regions. Here we use long-term, whole-stand inventory data from southeastern U.S. forests to show that trees exposed to drought experience multiyear declines in growth prior to mortality. Following a severe, multiyear drought, 72% of trees that did not recover their pre-drought growth rates died within 10 yr. This pattern was mediated by local moisture availability. As an index of morbidity prior to death, we calculated the difference in cumulative growth after drought relative to surviving conspecifics. The strength of drought-induced morbidity varied among species and was correlated with drought tolerance. These findings support the ability of trees to avoid death during drought events but indicate shifts that could occur over decades. Tree mortality following drought is predictable in these ecosystems based on growth declines, highlighting an opportunity to address multiyear drought-induced morbidity in models, experiments, and management decisions.

Published
2016

28. Forest drought as an emerging research priority

Author

James S. Clark, Charles H. Luce, and James M. Vose

Subjects
0106 biological sciences, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Agroforestry, Research, Forests, 010603 evolutionary biology, 01 natural sciences, Droughts, Environmental Chemistry, Environmental science, 0105 earth and related environmental sciences, General Environmental Science
Published
2016

29. Why species tell more about traits than traits about species: predictive analysis

Author

James S. Clark

Subjects
0106 biological sciences, Forest inventory, Ecology, Species diversity, Biodiversity, Biology, Forests, Plants, 010603 evolutionary biology, 01 natural sciences, Variation (linguistics), Phenotype, Trait, Direct analysis, Probabilistic framework, Trait analysis, Ecology, Evolution, Behavior and Systematics, 010606 plant biology & botany, Diversity (business)
Abstract

Trait analysis aims to understand relationships between traits, species diversity, and the environment. Current methods could benefit from a model-based probabilistic framework that accommodates covariance between traits and quantifies contributions from inherent trait syndromes, species interactions, and responses to the environment. I develop a model-based approach that separates these effects on trait diversity. Application to USDA Forest Inventory and Analysis (FIA) data in the eastern United States demonstrates an apparent paradox, that the analysis of species better explains and predicts traits than does direct analysis of the traits themselves; trait data contain less, not more, information than species on environmental responses. Whereas variation in some traits is dominated by inherent syndromes (tendency for certain traits to be associated with others within an individual and species), others are strongly controlled by variation in species diversity. There is substantial variation in environmental control on trait patterns, between traits and regionally. In terms of environmental response traits do not aggregate into defined plant functional types, as would be desirable for models.

Published
2016

30. Effects of Model Formulation on Estimates of Health in Individual Right Whales (Eubalaena glacialis)

Author

Heather M. Pettis, Amy R. Knowlton, Robert S. Schick, James S. Clark, Len Thomas, Philip K. Hamilton, Scott D. Kraus, Rosalind M. Rolland, and John Harwood

Subjects
0106 biological sciences, 010604 marine biology & hydrobiology, Bayesian probability, Fishing, Statistical model, Variance (accounting), Missing data, 010603 evolutionary biology, 01 natural sciences, Process error, Individual health, Geography, Photo identification, Econometrics
Abstract

Right whales are vulnerable to many sources of anthropogenic disturbance including ship strikes, entanglement with fishing gear, and anthropogenic noise. The effect of these factors on individual health is unclear. A statistical model using photographic evidence of health was recently built to infer the true or hidden health of individual right whales. However, two important prior assumptions about the role of missing data and unexplained variance on the estimates were not previously assessed. Here we tested these factors by varying prior assumptions and model formulation. We found sensitivity to each assumption and used the output to make guidelines on future model formulation.

Published
2016
Full Text
View/download PDF

31. Inference on white dwarf binary systems using the first round Mock LISA Data Challenges data sets

Author

Alberto Vecchio, Alexander Stroeer, Martin Hendry, James S. Clark, C. Roever, Richard Umstaetter, Nelson Christensen, Graham Woan, Ed Bloomer, C. Messenger, Matthew Pitkin, Jennifer Toher, John Veitch, and Renate Meyer

Subjects
Physics, Source data, Physics and Astronomy (miscellaneous), 010308 nuclear & particles physics, Pipeline (computing), Astrophysics (astro-ph), FOS: Physical sciences, Inference, Binary number, Markov chain Monte Carlo, General Relativity and Quantum Cosmology (gr-qc), Astrophysics, Grid, 01 natural sciences, Signal, General Relativity and Quantum Cosmology, symbols.namesake, 0103 physical sciences, symbols, Detection theory, 010306 general physics, Algorithm
Abstract

We report on the analysis of selected single source data sets from the first round of the Mock LISA Data Challenges (MLDC) for white dwarf binaries. We implemented an end-to-end pipeline consisting of a grid-based coherent pre-processing unit for signal detection, and an automatic Markov Chain Monte Carlo post-processing unit for signal evaluation. We demonstrate that signal detection with our coherent approach is secure and accurate, and is increased in accuracy and supplemented with additional information on the signal parameters by our Markov Chain Monte Carlo approach. We also demonstrate that the Markov Chain Monte Carlo routine is additionally able to determine accurately the noise level in the frequency window of interest., Comment: GWDAW-11 proceeding, submitted to CQG, 10 pages, 3 figures, 1 table; revised values in table

Published
2007
Full Text
View/download PDF

32. Predictive models for radial sap flux variation in coniferous, diffuse-porous and ring-porous temperate trees

Author

Aaron B. Berdanier, James S. Clark, and Chelcy Ford Miniat

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Physiology, Ecology, Flux, Water, Soil science, Plant Transpiration, Plant Science, Variation (game tree), Models, Theoretical, 01 natural sciences, Trees, Data set, Tree (data structure), Calibration, Temperate climate, Range (statistics), Environmental science, Scaling, 010606 plant biology & botany, 0105 earth and related environmental sciences
Abstract

Accurately scaling sap flux observations to tree or stand levels requires accounting for variation in sap flux between wood types and by depth into the tree. However, existing models for radial variation in axial sap flux are rarely used because they are difficult to implement, there is uncertainty about their predictive ability and calibration measurements are often unavailable. Here we compare different models with a diverse sap flux data set to test the hypotheses that radial profiles differ by wood type and tree size. We show that radial variation in sap flux is dependent on wood type but independent of tree size for a range of temperate trees. The best-fitting model predicted out-of-sample sap flux observations and independent estimates of sapwood area with small errors, suggesting robustness in the new settings. We develop a method for predicting whole-tree water use with this model and include computer code for simple implementation in other studies.

Published
2015

33. The impacts of increasing drought on forest dynamics, structure, and biodiversity in the United States

Author

Stephen T. Jackson, Don C. Bragg, Christopher W. Woodall, Niklaus E. Zimmermann, Craig D. Allen, Neil Pederson, Anthony W. D'Amato, David M. Bell, Mark W. Schwartz, Michelle H. Hersh, Kristen M. Waring, Frank W. Davis, Louis R. Iverson, Inés Ibáñez, Matthew P. Peters, Stephen N. Matthews, and James S. Clark

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Range (biology), Life on Land, Forest management, Biodiversity, forest management, Climate change, drought, Forests, 010603 evolutionary biology, 01 natural sciences, Trees, Environmental Chemistry, Ecosystem, 0105 earth and related environmental sciences, General Environmental Science, Global and Planetary Change, Forest dynamics, Ecology, Agroforestry, Biological Sciences, United States, Droughts, Forest dieback, Geography, climate change, Habitat, forest dieback, Environmental Sciences
Abstract

© 2016 John Wiley & Sons Ltd. We synthesize insights from current understanding of drought impacts at stand-to-biogeographic scales, including management options, and we identify challenges to be addressed with new research. Large stand-level shifts underway in western forests already are showing the importance of interactions involving drought, insects, and fire. Diebacks, changes in composition and structure, and shifting range limits are widely observed. In the eastern US, the effects of increasing drought are becoming better understood at the level of individual trees, but this knowledge cannot yet be confidently translated to predictions of changing structure and diversity of forest stands. While eastern forests have not experienced the types of changes seen in western forests in recent decades, they too are vulnerable to drought and could experience significant changes with increased severity, frequency, or duration in drought. Throughout the continental United States, the combination of projected large climate-induced shifts in suitable habitat from modeling studies and limited potential for the rapid migration of tree populations suggests that changing tree and forest biogeography could substantially lag habitat shifts already underway. Forest management practices can partially ameliorate drought impacts through reductions in stand density, selection of drought-tolerant species and genotypes, artificial regeneration, and the development of multistructured stands. However, silvicultural treatments also could exacerbate drought impacts unless implemented with careful attention to site and stand characteristics. Gaps in our understanding should motivate new research on the effects of interactions involving climate and other species at the stand scale and how interactions and multiple responses are represented in models. This assessment indicates that, without a stronger empirical basis for drought impacts at the stand scale, more complex models may provide limited guidance.

Published
2015
Full Text
View/download PDF

34. Investigating Binary Black Hole Mergers with Principal Component Analysis

Author

Laura Cadonati, N. Mangini, James Healy, Ik Siong Heng, Lionel London, Larne Pekowsky, James S. Clark, Deirdre Shoemaker, and Josh Logue

Subjects
Coalescence (physics), Physics, 010308 nuclear & particles physics, Gravitational wave, Bayesian inference, 01 natural sciences, Numerical relativity, Binary black hole, 0103 physical sciences, Principal component analysis, Waveform, 010306 general physics, Algorithm, Spinning
Abstract

Despite recent progress in numerical simulations of the coalescence of binary black hole systems, highly asymmetric spinning systems and the construction of accurate physical templates remain challenging and computationally expensive. We explore the feasibility of a prompt and robust test of whether the signals exhibit evidence for generic features that can educate new simulations. We form catalogs of numerical relativity waveforms with distinct physical effects and compute the relative probability that a gravitational wave signal belongs to each catalog. We introduce an algorithm designed to perform this task for coalescence signals using principal component analysis of waveform catalogs and Bayesian model selection and demonstrate its effectiveness.

Published
2014
Full Text
View/download PDF

35. Search for gravitational wave ringdowns from perturbed intermediate mass black holes in LIGO-Virgo data from 2005?2010

Author

Li-Wei Wei, Kenneth A. Strain, Fabio Marchesoni, Kyungmin Kim, G. Quiroga, Yi Pan, K. E. Ramirez, Michael L. Gorodetsky, Michaela Pickenpack, Simon Stevenson, David Hammer, Joseph O'Dell, Hartmut Grote, G. Losurdo, Albrecht Ruediger, Neil J. Cornish, Peter Aufmuth, Jiayi Qin, Sammanani S. Premachandra, Jamie Scott, V. Re, Bruce Gendre, Robinjeet Singh, M. Yvert, T. D. Abbott, Jong H. Chow, Ludovico Carbone, P. Couvares, Benno Willke, J. Bauchrowitz, F. Garufi, Cristina Torres, Denis Martynov, S. G. Crowder, Federico Ferrini, Marco Colombini, A. F. Brooks, Q. Chu, Szymon Steplewski, Gerardo Moreno, Chunnong Zhao, J. Macarthur, Karen Roland, G. Vajente, David H. Shoemaker, M. Tse, D. M. Macleod, M. Meinders, W. D. Vousden, Gianpietro Cagnoli, L. Wallace, J. Poeld, R. Frey, Christophe Collette, Zhixing Yang, Evan Ochsner, Vicky Kalogera, Larry R. Price, Elaine Rhoades, Adrien Le Roux, Ajay Kumar, M. Leonardi, Carl Adams, C. Belczynski, M. A. Barton, Alessandra Buonanno, Brian O'Reilly, D. B. Kelley, Matteo Lorenzini, Linqing Wen, S. E. Zuraw, C. Palomba, R. Chakraborty, B. L. Swinkels, D. Verkindt, G. Kang, Christelle Buy, César A. Costa, Xing Zhu, S. Privitera, F. Vetrano, M. K. Haris, T. Vo, C. Bradaschia, P. Oppermann, Michele Vallisneri, M. S. Shahriar, Joris van Heijningen, Sascha Husa, Sonali Mohapatra, P. T. Beyersdorf, Andrew Lundgren, Eliu Huerta, Szabolcs Marka, Timothy A Welborn, M. T. Hartman, V. Kringel, Marica Branchesi, N. Straniero, Alessio Rocchi, D. R. Ingram, Ryan Fisher, Ivan Maksimovic, K. Siellez, A. Conte, Steffen Kaufer, Jo van den Brand, Daniel Amariutei, Saps Buchman, L. Sammut, A. Ain, D. Bersanetti, K. Mailand, K. A. Hodge, Marilyne Andersen, Mauro Tonelli, Kip S. Thorne, T. Chalermsongsak, Alessandro Bertolini, Duncan Meacher, B. Shapiro, Jonathan F. Stebbins, Heinz-Bernd Eggenstein, Zhihui Du, V. P. Mitrofanov, Sanjit Mitra, R. Mittleman, Sharad Gaonkar, Ik Siong Heng, Cyrus Reed, T. Z. Summerscales, Nelson Christensen, Sunil Susmithan, Oliver Puncken, Tyson Littenberg, D. Lodhia, Neil Gehrels, R. Lynch, V. Boschi, Hee Cho, Kasem Mossavi, Deepak Nanda Kumar, Grant David Meadors, R. Coyne, Haixing Miao, S. L. Danilishin, G. Bogaert, M. Shaltev, D. C. Coyne, J. Aasi, Jade Powell, David H. Reitze, Yi-Ming Hu, Sweta Shah, K. Izumi, D. Passuello, Nicolas Leroy, M. Barsuglia, E. O. Lebigot, Vuk Mandic, Alberto Di Lieto, Ignacio Santiago-Prieto, G. Vedovato, W. Katzman, S. E. Dwyer, David Keitel, Richard Gustafson, Suvadeep Bose, Z. Márka, Tomasz Bulik, Alexander Ivanov, C. Affeldt, P. Thomas, Jean-Pierre Zendri, Trevor Sidery, H. Heitmann, Ryan DeRosa, V. Loriette, Francesco Salemi, Pierre-François Cohadon, V. Litvine, Gurumurthy Rajalakshmi, O. Bock, István Rácz, K. L. Dooley, Sabrina D'Antonio, Joshua Yablon, Warren Anderson, Eric K. Gustafson, Sina Koehlenbeck, Jocelyn Read, F. Carbognani, J. Logue, H. J. Bulten, S. Gossler, David Kinzel, Almir Alemic, P. J. Veitch, Amber Stuver, Sanichiro Yoshida, Badri Krishnan, T. P. Bodiya, C. Vorvick, Marc Normandin, Ettore Majorana, Gary McIntyre, M. Edwards, Peter Wessels, Rosa Poggiani, Erik Katsavounidis, Namjun Kim, François Bondu, P. Leaci, A. Colla, Sean Morriss, M. Factourovich, P. Astone, J. Betzwieser, V. Kondrashov, Lisa Barsotti, Bala R. Iyer, Kieran Craig, Shaun Hooper, Valeria Malvezzi, Warren W. Johnson, Jay Marx, Antoine Heidmann, Piotr Jaranowski, Florent Robinet, P. Raffai, Kyle Ryan, Mark Barbet, Samuel Franco, Eric Thrane, Eric W. James, Manasadevi Thirugnanasamba, Sarah Caudill, E. Goetz, Scott Koranda, T. t. Fricke, J. B. Kanner, A. R. Wade, Rainer Weiss, Xu Chen, G. Bergmann, L. Matone, T. Dayanga, Martin van Beuzekom, Les Wade, Irene Di Palma, Young-Min Kim, Albert Lazzarini, Anthony Kremin, Fausto Acernese, Rajesh Kumar, R. J. G. Jonker, H. Overmier, Robert M. S. Schofield, Jessica McIver, Sang Oh, G. Mazzolo, G. Kuehn, D. Barker, K. Wette, F. Ricci, N. Mazumder, R. Quitzow-James, R. Day, Vladimir B. Braginsky, Maik Frede, C. C. Yancey, Giacomo Ciani, A. Mullavey, John J. Oh, D. Sellers, Alastair Grant, N. Morgado, H. Vahlbruch, A. Cumming, C. M. Mow-Lowry, H. Fehrmann, J. Meidam, Lisa M. Goggin, K. Riles, F. Ohme, S. J. Chamberlin, Sergey P. Vyatchanin, Calum Torrie, J. Hanks, J. Y. Vinet, Archana Pai, E. J. King, Hyun Lee, B. P. Abbott, Andrea Moggi, Jean-Daniel Fournier, Rory Smith, Hernan Daveloza, D. Sigg, S. W. Ballmer, Edwin J. Son, D. Ugolini, S. Vass, F. Paoletti, P. Ruggi, J. Eichholz, M. J. Cowart, Keiko Kokeyama, Riccardo Sturani, Andrzej Królak, Laurent Pinard, Fumiko Kawazoe, Tristan Briant, Benjamin William Allen, Stefan Hild, Y. Ma, E. Genin, N. D. Smith-Lefebvre, Graham Woan, Stuart Reid, Steven D. Penn, Yuri Minenkov, Laura Cadonati, Mohana Mageswaran, Veronica Lockett, N. Letendre, Karsten Danzmann, C. Aulbert, R. Cavalieri, Scott Dossa, H. Wittel, Walter Del Pozzo, Riccardo DeSalvo, C. Messenger, Bastian Schulz, R. Vincent-Finley, Jeffery Kline, H. Radkins, J. D. Lough, S. T. Countryman, S. H. Huttner, Fabrice Matichard, W. Kells, Jacob Scheuer, M. Jacobson, M. Weinert, P. Campsie, Michelle E. Walker, J. Birch, Katrin Dahl, A. Libson, M. Punturo, D. Hoak, D. Sentenac, Patrick Brady, Leopoldo Milano, Slawomir Gras, F. Fidecaro, S. Biscans, Fred Raab, Valentina D. Mangano, P. Baker, M. Mantovani, Andrew Melatos, E. Saracco, A. Brillet, Gary Hemming, Michail Agathos, A. Masserot, Santiago Caride, C. L. Mueller, B. Behnke, Matthew Heintze, Richard L. Savage, Alberto Vecchio, G. M. Harry, E. Oelker, K. Venkateswara, Benjamin Aylott, Daniel Kozak, Martina Neri, A. S. Bell, John Miller, T. Prestegard, Charles Celerier, Craig Lawrie, Lee Samuel Finn, Fafhan Feroz, Soma Mukherjee, R. L. McCarthy, Yuri Levin, Thanh Vinh Nguyen, David Blair, Vincenzo Dattilo, E. Coccia, C. Graef, B. A. Weaver, Dmitry Simakov, M. Brinkmann, L. Prokhorov, Will M. Farr, Elisabetta Cesarini, Troy Williams, Neil Gordon, Patrice Hello, Nancy Aggarwal, Robert Stone, Jordan Camp, James S. Clark, M. J. Hart, Richard O'Shaughnessy, B. Barr, Malik Rakhmanov, A. Pasqualetti, Roman Schnabel, J. G. Rollins, F. Y. Khalili, F. Travasso, Michał Bejger, Timo Denker, Luke Williams, J. C. Driggers, L. Austin, A. M. Gretarsson, A. R. Williamson, D. Feldbaum, S. Verma, A. Mytidis, J. E. Brau, L. Martinelli, Susan M. Scott, F. Marion, Efim A. Khazanov, Michael Thomas, A. Effler, Xiaoge Wang, Irene Fiori, G. Ballardin, Moritz Mehmet, David Stops, David Coward, Li Ju, Oleg Palashov, Daniel A. Shaddock, Adam Mercer, A. Basti, Philipp Moesta, Michael Rodruck, A. Allocca, Vincent Dolique, G. Valdes, Walter Winkler, Huan Yang, A. Perreca, M. Drago, B. Hughey, B. J. J. Slagmolen, Sheon Chua, M. Phelps, C. J. Guido, Paul Hopkins, Chiara M. F. Mingarelli, A. S. Markosyan, J. Hanson, Robert Taylor, B. C. Stephens, Mátyás Vasúth, Koji Arai, P. G. Murray, Cody Arceneaux, Fan Zhang, Brian Moe, Guenakh Mitselmakher, Vaibhav Tiwari, Shin Chung, E. Chassande-Mottin, Martin Mohan, Th. Bauer, Michael E Zucker, D. S. Rabeling, Ron Burman, Riccardo Bassiri, Joseph Gleason, V. Fafone, Guido Mueller, Tito Dal Canton, Christophe Michel, Sheila Rowan, Massimiliano Bitossi, Timothy MacDonald, Alan G. Wiseman, K. E. Gushwa, Fabien Kéfélian, E. Maros, J. H. Hough, Rocco Romano, Kendall Ackley, R. K. Nayak, Chad Hanna, M. Kasprzack, Paul Fulda, Ling Kuo, G. Debreczeni, S. E. Gossan, Shane L. Larson, F. Clara, Mary West, F. Magaña-Sandoval, J.-P. Coulon, M. Was, Susanne Milde, A. Staley, H. Vocca, Roy Williams, M. Tacca, Kipp Cannon, Carl-Johan Haster, A. Giazotto, E. Schreiber, Todd Adams, Roland Schilling, Matthew Evans, E. Cuoco, Douglas R. Cook, David Murphy, T. Isogai, R. S. Ottens, Ilaria Nardecchia, Michele Zanolin, S. Doravari, Ilya Mandel, Alex Nitz, Igor Neri, Jaclyn Sanders, J. S. Areeda, V. Sequino, Ruth A. Anderson, P. Kwee, Jeffrey Lewis, Fabrizio Barone, Jesper Munch, Leo Singer, Eugeniy E. Mikhailov, T. J. Massinger, R. Inta, R. W. P. Drever, C. Padilla, I. Ferrante, C. Mishra, J. K. Blackburn, Stephen S. Eikenberry, Innocenzo M. Pinto, J. Marque, Kat Grover, H. J. Jang, K. Haughian, S. Klimenko, Charlotte Bond, I. Kowalska, R. L. Ward, A. L. Lombardi, Corey Gray, M. Heurs, M. Boer, J. Steinlechner, A. S. Sengupta, P. Charlton, Gianluca Gemme, S. C. McGuire, Zsolt Frei, Marine Ducrot, G. D. Hammond, Anatoly Poteomkin, Angie Lin, M. Lormand, Máté Nagy, Sarah Recchia, R. Essick, D. Rosińska, S. P. Tarabrin, P. Puppo, D. Talukder, Nam Gyu Kim, M. Prijatelj, Jan Harms, R. Passaquieti, Marie-Anne Bizouard, G. Manca, Richard A. Matzner, S. Kandhasamy, B. Sorazu, Eric Quintero, J. C. Barayoga, R. Gouaty, Alexander Khalaidovski, E. Macdonald, Anthony Castiglia, Rosario DeRosa, H. Yamamoto, H. R. Paris, G. A. Prodi, John Worden, Alessandra Corsi, Viswanath Bavigadda, Nergis Mavalvala, Francisco Jimenez-Forteza, M. H. Wimmer, J. Greenhalgh, Chris Pankow, Junghyun Lee, F. Piergiovanni, Jerome Degallaix, Chang-Hwan Lee, Giancarlo Cella, A. Kutynia, C. Bogan, Tarun Souradeep, B. Mours, E. J. Daw, A. Gennai, A. Chiummo, F. Nocera, D. J. White, Alicia M. Sintes, Mark Lubinski, Igor Yakushin, M. Davier, J. Prasad, S. Grunewald, Kevin M. McLin, Nary-Catherine Man, Luca Gammaitoni, Andrea Chincarini, Steven Bloemen, Paolo Addesso, K. D. Giardina, M. Razzano, M. Born, D. Buskulic, Virginio Sannibale, David E. McClelland, C. Gill, Angela Di Virgilio, Jonathan R. Gair, Chris Van Den Broeck, N. A. Lockerbie, M. Damjanic, F. Martelli, Michael Smith, Kenneth G. Libbrecht, Husne Dereli, Harald Lueck, F. Cleva, S. Meshkov, S. Farinon, Tjonnie G. F. Li, Eric Howell, Huang-Wei Pan, Gijs Nelemans, T. B. Edo, Thomas Dent, Vladimir Dergachev, Eric D. Black, Jolien D. E. Creighton, Lindy Blackburn, S. Frasca, Michael Landry, James Whelan, P. Ajith, M. Cordier, N. A. Robertson, C. Lazzaro, K. Holt, Alan J. Weinstein, Chunglee Kim, I. A. Bilenko, S. Leavey, Stephen Fairhurst, Juan Calderón Bustillo, M. R. Abernathy, Kema Williams, Peter Fritschel, David J. Ottaway, G. Billingsley, David Hosken, L. Bosi, Peter Kalmus, B. Lantz, J. R. Leong, M. C. Díaz, Philip Graff, Tania Regimbau, Y. Ji, M. M. Hanke, C. Maglione, Ruslan Vaulin, Dirk Schuette, David B. Tanner, Stuart Anderson, T. P. Downes, M. Pedraza, K. Loew, Maria Alessandra Papa, F. Cavalier, M. Pichot, Collin Capano, Matthew Benacquista, Enrico Calloni, G. Traylor, Thomas Corbitt, Gabor Endroczi, Benjamin J. Owen, Gareth S. Davies, W. Z. Korth, Martin Hendry, Christopher Wipf, K. V. Tokmakov, Martin Hewitson, Junwei Cao, Alexander Corpuz, Bernard F. Whiting, Tobias Westphal, David Jones, Stan Whitcomb, Joseph A. Giaime, Marco Cavaglia, Patrick J. Sutton, F. Frasconi, C. R. Ramet, R. Flaminio, Odylio D. Aguiar, Abraham Singer, I. W. Martin, A. W. Heptonstall, Vivien Raymond, Peter R. Saulson, László Gondán, R. Abbott, Erik Luijten, David Nolting, M. C. Araya, Marie Huynh, V. Brisson, Emelie Harstad, Rana X. Adhikari, B. Machenschalk, F. Donovan, Phil Ehrens, L. Naticchioni, Salvatore Vitale, Ryan Goetz, A. L. Urban, Nick Mangini, C. J. Bell, K. Mason, Clive Tomlinson, Anna-Maria A. van Veggel, Sanjeev Dhurandhar, T. Huynh-Dinh, J. S. Kissel, Marc Favata, Roger Jones, R. M. Martin, D. D. Brown, Peter Shawhan, Xavier Siemens, K. Kawabe, S. M. Aston, F. Brückner, Michael W. Coughlin, Romain Bonnand, A. Viceré, T. Etzel, Yi Chen, Peter King, L. Bonelli, J. Slutsky, C. S. Unnikrishnan, Hyung-Mok Lee, Dan Moraru, Samuel Deléglise, Karoline Wiesner, Benjamin Canuel, P. M. Meyers, Sourav Ghosh, Scott Coughlin, J. H. Romie, Imre Bartos, Tom M. Evans, Barry C. Barish, Paul J. Groot, Marc van der Sluys, L. Cunningham, R. Douglas, John Veitch, V. Quetschke, Bangalore Suryanarayana Sathyaprakash, Martin M. Fejer, J. R. Smith, R. Bork, L. R. Cominsky, Axel Donath, Tobias Eberle, M. MacInnis, Gianluca Guidi, S. Raja, S. E. Strigin, Bruce Levine, G. M. Keiser, Benjamin Farr, Christian Cepeda, P. Rapagnani, Andreas Freise, Vincenzo Pierro, Alexander Sergeev, Paul D. Lasky, John Karlen, Joshua L. Willis, J. Zweizig, Carol Wilkinson, Laura Nuttall, G. Mendell, Matthew Pitkin, Liyuan Zhang, M. Wade, Sebastian Steinlechner, C. Osthelder, Karel E. Urbanek, D. O. Bridges, M. Granata, Prayush Kumar, G. P. Newton, M. Fyffe, Gabriela Gonzalez, I. W. Harry, Shiuh Chao, Gleb Romanov, Jim Batch, Adam Zadrozny, M. G. Beker, Qi Fang, V. Necula, Luciano Di Fiore, V. V. Frolov, V. Sandberg, K. A. Thorne, Benoit Sassolas, Stanislav Babak, M. Constancio, Duncan A. Brown, M. Wang, APC - Cosmologie, AstroParticule et Cosmologie (APC (UMR_7164)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Observatoire de Paris, Université Paris sciences et lettres (PSL), Laboratoire de l'Accélérateur Linéaire (LAL), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Astrophysique Relativiste Théories Expériences Métrologie Instrumentation Signaux (ARTEMIS), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Institut de Physique de Rennes (IPR), Université de Rennes (UR)-Centre National de la Recherche Scientifique (CNRS), Laboratoire des matériaux avancés (LMA), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), APC - Gravitation (APC-Gravitation), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Ecole Superieure de Physique et de Chimie Industrielles de la Ville de Paris (ESPCI Paris), Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria), IVC Lab, Lenovo Research, Lenovo, European Synchrotron Radiation Facility (ESRF), Physique Corpusculaire et Cosmologie - Collège de France ( PCC ), Collège de France ( CdF ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ) -Collège de France ( CdF ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Université Paris Diderot - Paris 7 ( UPD7 ) -Centre National de la Recherche Scientifique ( CNRS ) -AstroParticule et Cosmologie ( APC - UMR 7164 ), Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Observatoire de Paris-Université Paris Diderot - Paris 7 ( UPD7 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Centre National de la Recherche Scientifique ( CNRS ) -Observatoire de Paris-Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), Laboratoire de l'Accélérateur Linéaire ( LAL ), Université Paris-Sud - Paris 11 ( UP11 ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ), Astrophysique Relativiste Théories Expériences Métrologie Instrumentation Signaux ( ARTEMIS ), Université Nice Sophia Antipolis ( UNS ), Université Côte d'Azur ( UCA ) -Université Côte d'Azur ( UCA ) -Institut national des sciences de l'Univers ( INSU - CNRS ) -Observatoire de la Côte d'Azur, Université Côte d'Azur ( UCA ) -Centre National de la Recherche Scientifique ( CNRS ), Institut de Physique de Rennes ( IPR ), Université de Rennes 1 ( UR1 ), Université de Rennes ( UNIV-RENNES ) -Université de Rennes ( UNIV-RENNES ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire des matériaux avancés ( LMA ), Université Claude Bernard Lyon 1 ( UCBL ), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Centre National de la Recherche Scientifique ( CNRS ) -Centre National de la Recherche Scientifique ( CNRS ), Laboratoire d'Annecy de Physique des Particules ( LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules ), Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Université Savoie Mont Blanc ( USMB [Université de Savoie] [Université de Chambéry] ) -Centre National de la Recherche Scientifique ( CNRS ), AstroParticule et Cosmologie ( APC - UMR 7164 ), Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Observatoire de Paris-Université Paris Diderot - Paris 7 ( UPD7 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ), APC - Gravitation ( APC-Gravitation ), Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Observatoire de Paris-Université Paris Diderot - Paris 7 ( UPD7 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Centre National de la Recherche Scientifique ( CNRS ) -Institut National de Physique Nucléaire et de Physique des Particules du CNRS ( IN2P3 ) -Observatoire de Paris-Université Paris Diderot - Paris 7 ( UPD7 ) -Commissariat à l'énergie atomique et aux énergies alternatives ( CEA ) -Max-Planck-Institut für Gravitationsphysik (Albert-Einstein-Institut), Max-Planck-Institut-Max-Planck-Institut, ESPCI ParisTech, Universitá degli Studi dell’Insubria, European Synchrotron Radiation Facility ( ESRF ), Aasi, J., Abbott, B. P., Abbott, R., Abbott, T., Abernathy, M. R., Acernese, F., Ackley, K., Adams, C., Adams, T., Addesso, P., Adhikari, R. X., Affeldt, C., Agathos, M., Aggarwal, N., Aguiar, O. D., Ain, A., Ajith, P., Alemic, A., Allen, B., Allocca, A., Amariutei, D., Andersen, M., Anderson, R., Anderson, S. B., Anderson, W. G., Arai, K., Araya, M. C., Arceneaux, C., Areeda, J., Aston, S. M., Astone, P., Aufmuth, P., Aulbert, C., Austin, L., Aylott, B. E., Babak, S., Baker, P. T., Ballardin, G., Ballmer, S. W., Barayoga, J. C., Barbet, M., Barish, B. C., Barker, D., Barone, F., Barr, B., Barsotti, L., Barsuglia, M., Barton, M. A., Bartos, I., Bassiri, R., Basti, A., Batch, J. C., Bauchrowitz, J., Bauer, T. h. S., Bavigadda, V., Behnke, B., Bejger, M., Beker, M. G., Belczynski, C., Bell, A. S., Bell, C., Benacquista, M., Bergmann, G., Bersanetti, D., Bertolini, A., Betzwieser, J., Beyersdorf, P. T., Bilenko, I. A., Billingsley, G., Birch, J., Biscans, S., Bitossi, M., Bizouard, M. A., Black, E., Blackburn, J. K., Blackburn, L., Blair, D., Bloemen, S., Bock, O., Bodiya, T. P., Boer, M., Bogaert, G., Bogan, C., Bond, C., Bondu, F., Bonelli, L., Bonnand, R., Bork, R., Born, M., Boschi, V., Sukanta, Bose, Bosi, L., Bradaschia, C., Brady, P. R., Braginsky, V. B., Branchesi, M., Brau, J. E., Briant, T., Bridges, D. O., Brillet, A., Brinkmann, M., Brisson, V., Brooks, A. F., Brown, D. A., Brown, D. D., Brckner, F., Buchman, S., Bulik, T., Bulten, H. J., Buonanno, A., Burman, R., Buskulic, D., Buy, C., Cadonati, L., Cagnoli, G., Caldern Bustillo, J., Calloni, Enrico, Camp, J. B., Campsie, P., Cannon, K. C., Canuel, B., Cao, J., Capano, C. D., Carbognani, F., Carbone, L., Caride, S., Castiglia, A., Caudill, S., Cavagli, M., Cavalier, F., Cavalieri, R., Celerier, C., Cella, G., Cepeda, C., Cesarini, E., Chakraborty, R., Chalermsongsak, T., Chamberlin, S. J., Chao, S., Charlton, P., Chassande Mottin, E., Chen, X., Chen, Y., Chincarini, A., Chiummo, A., Cho, H. S., Chow, J., Christensen, N., Chu, Q., Chua, S. S. Y., Chung, S., Ciani, G., Clara, F., Clark, J. A., Cleva, F., Coccia, E., Cohadon, P. F., Colla, A., Collette, C., Colombini, M., Cominsky, L., Constancio, M., Conte, A., Cook, D., Corbitt, T. R., Cordier, M., Cornish, N., Corpuz, A., Corsi, A., Costa, C. A., Coughlin, M. W., Coughlin, S., Coulon, J. P., Countryman, S., Couvares, P., Coward, D. M., Cowart, M., Coyne, D. C., Coyne, R., Craig, K., Creighton, J. D. E., Crowder, S. G., Cumming, A., Cunningham, L., Cuoco, E., Dahl, K., Dal Canton, T., Damjanic, M., Danilishin, S. L., Dantonio, S., Danzmann, K., Dattilo, V., Daveloza, H., Davier, M., Davies, G. S., Daw, E. J., Day, R., Dayanga, T., Debreczeni, G., Degallaix, J., Delglise, S., Del Pozzo, W., Denker, T., Dent, T., Dereli, H., Dergachev, V., DE ROSA, Rosario, Derosa, R. T., Desalvo, R., Dhurandhar, S., Daz, M., Di Fiore, L., Di Lieto, A., Di Palma, I., Di Virgilio, A., Dolique, V., Donath, A., Donovan, F., Dooley, K. L., Doravari, S., Dossa, S., Douglas, R., Downes, T. P., Drago, M., Drever, R. W. P., Driggers, J. C., Du, Z., Ducrot, M., Dwyer, S., Eberle, T., Edo, T., Edwards, M., Effler, A., Eggenstein, H., Ehrens, P., Eichholz, J., Eikenberry, S. S., Endrczi, G., Essick, R., Etzel, T., Evans, M., Evans, T., Factourovich, M., Fafone, V., Fairhurst, S., Fang, Q., Farinon, S., Farr, B., Farr, W. M., Favata, M., Fehrmann, H., Fejer, M. M., Feldbaum, D., Feroz, F., Ferrante, I., Ferrini, F., Fidecaro, F., Finn, L. S., Fiori, I., Fisher, R. P., Flaminio, R., Fournier, J. D., Franco, S., Frasca, S., Frasconi, F., Frede, M., Frei, Z., Freise, A., Frey, R., Fricke, T. T., Fritschel, P., Frolov, V. V., Fulda, P., Fyffe, M., Gair, J., Gammaitoni, L., Gaonkar, S., Garufi, Fabio, Gehrels, N., Gemme, G., Gendre, B., Genin, E., Gennai, A., Ghosh, S., Giaime, J. A., Giardina, K. D., Giazotto, A., Gill, C., Gleason, J., Goetz, E., Goetz, R., Goggin, L. M., Gondan, L., Gonzlez, G., Gordon, N., Gorodetsky, M. L., Gossan, S., Goler, S., Gouaty, R., Grf, C., Graff, P. B., Granata, M., Grant, A., Gras, S., Gray, C., Greenhalgh, R. J. S., Gretarsson, A. M., Groot, P., Grote, H., Grover, K., Grunewald, S., Guidi, G. M., Guido, C., Gushwa, K., Gustafson, E. K., Gustafson, R., Hammer, D., Hammond, G., Hanke, M., Hanks, J., Hanna, C., Hanson, J., Harms, J., Harry, G. M., Harry, I. W., Harstad, E. D., Hart, M., Hartman, M. T., Haster, C. J., Haughian, K., Heidmann, A., Heintze, M., Heitmann, H., Hello, P., Hemming, G., Hendry, M., Heng, I. S., Heptonstall, A. W., Heurs, M., Hewitson, M., Hild, S., Hoak, D., Hodge, K. A., Holt, K., Hooper, S., Hopkins, P., Hosken, D. J., Hough, J., Howell, E. J., Hu, Y., Huerta, E., Hughey, B., Husa, S., Huttner, S. H., Huynh, M., Huynh Dinh, T., Ingram, D. R., Inta, R., Isogai, T., Ivanov, A., Iyer, B. R., Izumi, K., Jacobson, M., James, E., Jang, H., Jaranowski, P., Ji, Y., Jimnez Forteza, F., Johnson, W. W., Jones, D. I., Jones, R., Jonker, R. J. G., Ju, L., Haris, K, Kalmus, P., Kalogera, V., Kandhasamy, S., Kang, G., Kanner, J. B., Karlen, J., Kasprzack, M., Katsavounidis, E., Katzman, W., Kaufer, H., Kawabe, K., Kawazoe, F., Kflian, F., Keiser, G. M., Keitel, D., Kelley, D. B., Kells, W., Khalaidovski, A., Khalili, F. Y., Khazanov, E. A., Kim, C., Kim, K., Kim, N., Kim, N. G., Kim, Y. M., King, E. J., King, P. J., Kinzel, D. L., Kissel, J. S., Klimenko, S., Kline, J., Koehlenbeck, S., Kokeyama, K., Kondrashov, V., Koranda, S., Korth, W. Z., Kowalska, I., Kozak, D. B., Kremin, A., Kringel, V., Krishnan, B., Krlak, A., Kuehn, G., Kumar, A., Nanda Kumar, D., Kumar, P., Kumar, R., Kuo, L., Kutynia, A., Kwee, P., Landry, M., Lantz, B., Larson, S., Lasky, P. D., Lawrie, C., Lazzarini, A., Lazzaro, C., Leaci, P., Leavey, S., Lebigot, E. O., Lee, C. H., Lee, H. K., Lee, H. M., Lee, J., Leonardi, M., Leong, J. R., Le Roux, A., Leroy, N., Letendre, N., Levin, Y., Levine, B., Lewis, J., T. G. F., Li, Libbrecht, K., Libson, A., Lin, A. C., Littenberg, T. B., Litvine, V., Lockerbie, N. A., Lockett, V., Lodhia, D., Loew, K., Logue, J., Lombardi, A. L., Lorenzini, M., Loriette, V., Lormand, M., Losurdo, G., Lough, J., Lubinski, M. J., Lck, H., Luijten, E., Lundgren, A. P., Lynch, R., Ma, Y., Macarthur, J., Macdonald, E. P., Macdonald, T., Machenschalk, B., Macinnis, M., Macleod, D. M., Magana Sandoval, F., Mageswaran, M., Maglione, C., Mailand, K., Majorana, E., Maksimovic, I., Malvezzi, V., Man, N., Manca, G. M., Mandel, I., Mandic, V., Mangano, V., Mangini, N., Mantovani, M., Marchesoni, F., Marion, F., Mrka, S., Mrka, Z., Markosyan, A., Maros, E., Marque, J., Martelli, F., Martin, I. W., Martin, R. M., Martinelli, L., Martynov, D., Marx, J. N., Mason, K., Masserot, A., Massinger, T. J., Matichard, F., Matone, L., Matzner, R. A., Mavalvala, N., Mazumder, N., Mazzolo, G., Mccarthy, R., Mcclelland, D. E., Mcguire, S. C., Mcintyre, G., Mciver, J., Mclin, K., Meacher, D., Meadors, G. D., Mehmet, M., Meidam, J., Meinders, M., Melatos, A., Mendell, G., Mercer, R. A., Meshkov, S., Messenger, C., Meyers, P., Miao, H., Michel, C., Mikhailov, E. E., Milano, Leopoldo, Milde, S., Miller, J., Minenkov, Y., Mingarelli, C. M. F., Mishra, C., Mitra, S., Mitrofanov, V. P., Mitselmakher, G., Mittleman, R., Moe, B., Moesta, P., Moggi, A., Mohan, M., Mohapatra, S. R. P., Moraru, D., Moreno, G., Morgado, N., Morriss, S. R., Mossavi, K., Mours, B., Mow Lowry, C. M., Mueller, C. L., Mueller, G., Mukherjee, S., Mullavey, A., Munch, J., Murphy, D., Murray, P. G., Mytidis, A., Nagy, M. F., Nardecchia, I., Naticchioni, L., Nayak, R. K., Necula, V., Nelemans, G., Neri, I., Neri, M., Newton, G., Nguyen, T., Nitz, A., Nocera, F., Nolting, D., Normandin, M. E. N., Nuttall, L. K., Ochsner, E., Odell, J., Oelker, E., J. J., Oh, S. H., Oh, Ohme, F., Oppermann, P., Oreilly, B., Oshaughnessy, R., Osthelder, C., Ottaway, D. J., Ottens, R. S., Overmier, H., Owen, B. J., Padilla, C., Pai, A., Palashov, O., Palomba, C., Pan, H., Pan, Y., Pankow, C., Paoletti, F., Papa, M. A., Paris, H., Pasqualetti, A., Passaquieti, R., Passuello, D., Pedraza, M., Penn, S., Perreca, A., Phelps, M., Pichot, M., Pickenpack, M., Piergiovanni, F., Pierro, V., Pinard, L., Pinto, I. M., Pitkin, M., Poeld, J., Poggiani, R., Poteomkin, A., Powell, J., Prasad, J., Premachandra, S., Prestegard, T., Price, L. R., Prijatelj, M., Privitera, S., Prodi, G. A., Prokhorov, L., Puncken, O., Punturo, M., Puppo, P., Qin, J., Quetschke, V., Quintero, E., Quiroga, G., Quitzow James, R., Raab, F. J., Rabeling, D. S., Rcz, I., Radkins, H., Raffai, P., Raja, S., Rajalakshmi, G., Rakhmanov, M., Ramet, C., Ramirez, K., Rapagnani, P., Raymond, V., Razzano, M., Re, V., Read, J., Recchia, S., Reed, C. M., Regimbau, T., Reid, S., Reitze, D. H., Rhoades, E., Ricci, F., Riles, K., Robertson, N. A., Robinet, F., Rocchi, A., Rodruck, M., Rolland, L., Rollins, J. G., Romano, R., Romanov, G., Romie, J. H., Rosiska, D., Rowan, S., Rdiger, A., Ruggi, P., Ryan, K., Salemi, F., Sammut, L., Sandberg, V., Sanders, J. R., Sannibale, V., Santiago Prieto, I., Saracco, E., Sassolas, B., Sathyaprakash, B. S., Saulson, P. R., Savage, R., Scheuer, J., Schilling, R., Schnabel, R., Schofield, R. M. S., Schreiber, E., Schuette, D., Schutz, B. F., Scott, J., Scott, S. M., Sellers, D., Sengupta, A. S., Sentenac, D., Sequino, V., Sergeev, A., Shaddock, D., Shah, S., Shahriar, M. S., Shaltev, M., Shapiro, B., Shawhan, P., Shoemaker, D. H., Sidery, T. L., Siellez, K., Siemens, X., Sigg, D., Simakov, D., Singer, A., Singer, L., Singh, R., Sintes, A. M., Slagmolen, B. J. J., Slutsky, J., Smith, J. R., Smith, M., Smith, R. J. E., Smith Lefebvre, N. D., Son, E. J., Sorazu, B., Souradeep, T., Staley, A., Stebbins, J., Steinlechner, J., Steinlechner, S., Stephens, B. C., Steplewski, S., Stevenson, S., Stone, R., Stops, D., Strain, K. A., Straniero, N., Strigin, S., Sturani, R., Stuver, A. L., Summerscales, T. Z., Susmithan, S., Sutton, P. J., Swinkels, B., Tacca, M., Talukder, D., Tanner, D. B., Tarabrin, S. P., Taylor, R., Thirugnanasambandam, M. P., Thomas, M., Thomas, P., Thorne, K. A., Thorne, K. S., Thrane, E., Tiwari, V., Tokmakov, K. V., Tomlinson, C., Tonelli, M., Torres, C. V., Torrie, C. I., Travasso, F., Traylor, G., Tse, M., Ugolini, D., Unnikrishnan, C. S., Urban, A. L., Urbanek, K., Vahlbruch, H., Vajente, G., Valdes, G., Vallisneri, M., van Beuzekom, M., van den Brand, J. F. J., Van Den Broeck, C., van der Sluys, M. V., van Heijningen, J., van Veggel, A. A., Vass, S., Vasth, M., Vaulin, R., Vecchio, A., Vedovato, G., Veitch, J., Veitch, P. J., Venkateswara, K., Verkindt, D., Verma, S. S., Vetrano, F., Vicer, A., Vincent Finley, R., Vinet, J. Y., Vitale, S., Vo, T., Vocca, H., Vorvick, C., Vousden, W. D., Vyachanin, S. P., Wade, A., Wade, L., Wade, M., Walker, M., Wallace, L., Wang, M., Wang, X., Ward, R. L., Was, M., Weaver, B., Wei, L. W., Weinert, M., Weinstein, A. J., Weiss, R., Welborn, T., Wen, L., Wessels, P., West, M., Westphal, T., Wette, K., Whelan, J. T., Whitcomb, S. E., White, D. J., Whiting, B. F., Wiesner, K., Wilkinson, C., Williams, K., Williams, L., Williams, R., Williams, T., Williamson, A. R., Willis, J. L., Willke, B., Wimmer, M., Winkler, W., Wipf, C. C., Wiseman, A. G., Wittel, H., Woan, G., Worden, J., Yablon, J., Yakushin, I., Yamamoto, H., Yancey, C. C., Yang, H., Yang, Z., Yoshida, S., Yvert, M., Zadrony, A., Zanolin, M., Zendri, J. P., Fan, Zhang, Zhang, L., Zhao, C., Zhu, X. J., Zucker, M. E., Zuraw, S., Zweizig, J., Pinto, Innocenzo, Physique Corpusculaire et Cosmologie - Collège de France (PCC), Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Université Nice Sophia Antipolis (... - 2019) (UNS), Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Centre National de la Recherche Scientifique (CNRS), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules), PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), (Astro)-Particles Physics, The LIGO Scientific Collaboration, The Virgo Collaboration, LIGO, California Institute of Technology, Louisiana State University, INFN, Sezione di Napoli, Complesso Universitario di Monte S. Angelo, Università di Salerno, University of Florida, LIGO Livingston Observatory, Cardiff University, Albert-Einstein-Institut, Max-Planck-Institut für Gravitationsphysik, Nikhef, LIGO, Massachusetts Institute of Technology, Instituto Nacional de Pesquisas Espaciais, Inter-University Centre for Astronomy and Astrophysics, International Centre for Theoretical Sciences, Tata Institute of Fundamental Research, Syracuse University, University of Wisconsin-Milwaukee, Leibniz Universität Hannover, INFN, Sezione di Pisa, Università di Siena, Stanford University, University of Mississippi, California State University Fullerton, INFN, Sezione di Roma, University of Birmingham, Montana State University, European Gravitational Observatory (EGO), LIGO Hanford Observatory, SUPA, University of Glasgow, APC, AstroParticule et Cosmologie, Université Paris Diderot, CNRS/IN2P3, Columbia University, Università di Pisa, CAMK-PAN, Astronomical Observatory Warsaw University, University of Texas at Brownsville, INFN, Sezione Genova, Università Degli Studi di Genova, San Jose State University, Faculty of Physics, Lomonosov Moscow State University, LAL, Université Paris-Sud, IN2P3/CNRS, NASA/Goddard Space Flight Center, University of Western Australia, Université Nice-Sophia-Antipolis, CNRS, Observatoire de la Côte d'Azur, Institut de Physique de Rennes, CNRS, Université de Rennes 1, Laboratoire d'Annecy-le-Vieux de Physique des Particules (LAPP), Université de Savoie, CNRS/IN2P3, Washington State University, INFN, Sezione di Perugia, INFN, Sezione di Firenze, Università Degli Studi di Urbino Carlo Bo, University of Oregon, Laboratoire Kastler Brossel, ENS, Université Pierre et Marie Curie, VU University Amsterdam, University of Maryland, College Park, Maryland 20742, University of Massachusetts Amherst, Laboratoire des Matériaux Avancés (LMA), IN2P3/CNRS, Université de Lyon, Universitat de les Illes Balears, Università di Napoli 'Federico II', Complesso Universitario di Monte S. Angelo, Canadian Institute for Theoretical Astrophysics, University of Toronto, Tsinghua University, University of Michigan, Rochester Institute of Technology, INFN, Sezione di Roma Tor Vergata, National Tsing Hua University, Charles Sturt University, Caltech-CaRT, Pusan National University, Australian National University, Carleton College, INFN, Gran Sasso Science Institute, Università di Roma Tor Vergata, Università di Roma 'La Sapienza', University of Brussels, Sonoma State University, Embry-Riddle Aeronautical University, George Washington University, University of Cambridge, Northwestern University, University of Minnesota, University of Sheffield, Wigner RCP, RMKI, University of Sannio at Benevento, INFN, Gruppo Collegato di Trento, Università di Trento, Montclair State University, Pennsylvania State University, MTA Eötvös University, 'Lendulet' A. R. G., Università di Perugia, Accuray Inc., Rutherford Appleton Laboratory, HSIC, Perimeter Institute for Theoretical Physics, American University, University of Adelaide, Raman Research Institute, Korea Institute of Science and Technology Information, Białystok University, University of Southampton, IISER-TVM, CET Campus, Institute of Applied Physics, Seoul National University, Hanyang University, IM-PAN, NCBJ, Institute for Plasma Research, University of Melbourne, INFN, Sezione di Padova, Monash University, SUPA, University of Strathclyde, ESPCI, CNRS, Argentinian Gravitational Wave Group, Università di Camerino, Dipartimento di Fisica, University of Texas at Austin, Southern University and AandM College, College of William and Mary, IISER-Kolkata, National Institute for Mathematical Sciences, Hobart and William Smith Colleges, RRCAT, Tata Institute for Fundamental Research, SUPA, University of the West of Scotland, Institute of Astronomy, Indian Institute of Technology, Universidade Estadual Paulista (UNESP), Andrews University, Trinity University, University of Washington, Southeastern Louisiana University, Abilene Christian University, INFN, Sezione di Genova, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Centre National de la Recherche Scientifique (CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, and Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI)

Subjects
SPACE-TELESCOPE EVIDENCE, Physics and Astronomy (miscellaneous), Astronomy, Pacs number: 04.70.-s, Astrophysics, 01 natural sciences, Pacs number: 04.80.Nn, General Relativity and Quantum Cosmology, Gravitation, GLOBULAR-CLUSTER M15, Gravitational waves, black holes, interferometer, CORE, Quantum Cosmology, gravitational wave, 010303 astronomy & astrophysics, EQUATIONS, QC, QB, Physics, Pacs number: 07.05.Kf, Oscillation, Settore FIS/01 - Fisica Sperimentale, CANDIDATE, Nuclear and High Energy Physics, PERTURBATIONS, Pacs number: 95.85.Sz, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], Gravitational wave, General Relativity, Stellar mass, General relativity, MERGERS, Astrophysics::High Energy Astrophysical Phenomena, FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), Astrophysics::Cosmology and Extragalactic Astrophysics, [ PHYS.GRQC ] Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], Settore FIS/05 - Astronomia e Astrofisica, 0103 physical sciences, FIELD, COLLAPSE, Astrophysics::Galaxy Astrophysics, 010308 nuclear & particles physics, BINARY, Mass ratio, LIGO, 13. Climate action, Globular cluster, [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph]
Abstract

We report results from a search for gravitational waves produced by perturbed intermediate mass black holes (IMBH) in data collected by LIGO and Virgo between 2005 and 2010. The search was sensitive to astrophysical sources that produced damped sinusoid gravitational wave signals, also known as ringdowns, with frequency $50\le f_{0}/\mathrm{Hz} \le 2000$ and decay timescale $0.0001\lesssim \tau/\mathrm{s} \lesssim 0.1$ characteristic of those produced in mergers of IMBH pairs. No significant gravitational wave candidate was detected. We report upper limits on the astrophysical coalescence rates of IMBHs with total binary mass $50 \le M/\mathrm{M}_\odot \le 450$ and component mass ratios of either 1:1 or 4:1. For systems with total mass $100 \le M/\mathrm{M}_\odot \le 150$, we report a 90%-confidence upper limit on the rate of binary IMBH mergers with non-spinning and equal mass components of $6.9\times10^{-8}\,$Mpc$^{-3}$yr$^{-1}$. We also report a rate upper limit for ringdown waveforms from perturbed IMBHs, radiating 1% of their mass as gravitational waves in the fundamental, $\ell=m=2$, oscillation mode, that is nearly three orders of magnitude more stringent than previous results., Comment: for the science summary, see http://www.ligo.org/science/Publication-S5S6RD/index.php

Published
2014
Full Text
View/download PDF

36. Relationships between charcoal particles in air and sediments in west-central Siberia

Author

James S. Clark, Jason A. Lynch, Brian J. Stocks, and Johann G. Goldammer

Subjects
Hydrology, 010506 paleontology, Archeology, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Taiga, Geochemistry, Paleontology, Sediment, 01 natural sciences, Atmosphere, Deposition (aerosol physics), visual_art, visual_art.visual_art_medium, Russian federation, Charcoal, Fire history, Holocene, Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

Production and size of charred particles determine transport and deposition in lakes. Lack of such data is a principal obstacle to interpretation of past fire from charcoal profiles. Our two-part analysis includes a calibration study, to assess charred-particle production and transport during fire, and a study of charred particles in sediment. The calibration step establishes the magnitude and size distribution of particle accumulation from traps during a controlled burn of Pinus sylvewtris forest in west-central Siberia. This high-intensity fire consumed 3.71 kg m-2 of fuels and produced 0.0729 kg m-2 of airborne particles, for an emission factor of 0.02 kg kg-1. Particle flux to the ground was 1 to 3 mm2cm-2 yr-1 inside the burn; it declined sharply within 5 m of the burn edge, and it was variable but without trend to a distance of 60 m. Particle-size distributions were conservative, with a slope of 2 on plots of log frequency versus log diameter, and sediment data suggest this slope may steepen as sources bcome more remote and as large particles are progressively lost due to settling. Deposition from the plume is similar to accumulation rates in sediment, with apparent upward bias in sediments as expected from broad geographic patterns in charcoal distributions. During the mid-Holocene charred-particle accumulation in lake sediments (101 mm2 cm-2 yr-1 was greater than observed in particle traps within the experimental burn. Particles were larger, suggesting nearby sources. Rates decreased by 3800 BP to values lower than average rates in particle traps, and samples were depleted in large particles. Low rates and infrequent large particles indicate sources were distant. Accumulation rates and particle sizes were again high from 3400 to 2800 and from 1400 to 700 BP. Close correspondence between the accumulation rates during the experimental burn and in sediments and particle evidence for source area, as well as their agreement with particle-trap data from the experimental burn, suggest that, in this region, fire may have been more frequent and closer in the mid-Holocene than today. We cannot rule out the possibility, however, that changes in charred particle accumulation also reflect changes in supply of sediment to the core site.

Published
1998
Full Text
View/download PDF

37. Scaling Integral Projection Models for Analyzing Size Demography

Author

Alan E. Gelfand, James S. Clark, and Souparno Ghosh

Subjects
0106 biological sciences, Statistics and Probability, FOS: Computer and information sciences, General Mathematics, Population, Inference, log Gaussian Cox process, 010603 evolutionary biology, 01 natural sciences, Methodology (stat.ME), missing data, Applied mathematics, Projection (set theory), education, Scaling, Statistics - Methodology, Mathematics, education.field_of_study, 010601 ecology, Markov chain Monte Carlo, Distribution (mathematics), Iterated function, Kernel (statistics), Path (graph theory), Statistics, Probability and Uncertainty, Hierarchical model
Abstract

Historically, matrix projection models (MPMs) have been employed to study population dynamics with regard to size, age or structure. To work with continuous traits, in the past decade, integral projection models (IPMs) have been proposed. Following the path for MPMs, currently, IPMs are handled first with a fitting stage, then with a projection stage. Model fitting has, so far, been done only with individual-level transition data. These data are used in the fitting stage to estimate the demographic functions (survival, growth, fecundity) that comprise the kernel of the IPM specification. The estimated kernel is then iterated from an initial trait distribution to obtain what is interpreted as steady state population behavior. Such projection results in inference that does not align with observed temporal distributions. This might be expected; a model for population level projection should be fitted with population level transitions., Published in at http://dx.doi.org/10.1214/13-STS444 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)

Published
2013

38. The transient gravitational-wave sky

Author

Laura Cadonati, Rosalba Perna, Stefan Hild, Emanuele Berti, Shiho Kobayashi, Szabolcs Marka, James S. Clark, Deirdre Shoemaker, John M. Baker, Andrew MacFadyen, Luis Lehner, Harald P. Pfeiffer, Nils Andersson, Ilya Mandel, Carl L. Rodriguez, Christian Reisswig, Alicia M. Soderberg, S. Klimenko, Ulrich Sperhake, Steve Liebling, Antony C. Searle, Ik Siong Heng, Pablo Laguna, Jocelyn Read, Nathan K. Johnson-McDaniel, Zsuzsa Márka, Lee Samuel Finn, Janna Levin, Stan Whitcomb, Patrick J. Sutton, Pablo Cerdá-Durán, David Neilsen, Kostas D. Kokkotas, Peter Kalmus, M. Ruffert, Martin Hendry, José A. González, Nial R. Tanvir, Erik Schnetter, Bruno Giacomazzo, Peter Shawhan, Chris L. Fryer, P. T. O'Brien, M. Was, Marc Favata, Kris Belczynski, Sebastiano Bernuzzi, Nils, A, John, B, Krzystof, B, Sebastiano, B, Emanuele, B, Laura, C, Pablo Cerdá, D, James, C, Marc, F, Lee Samuel, F, Chris, F, Giacomazzo, B, Jose Antonio, G, Martin, H, Ik Siong, H, Stefan, H, Nathan Johnson, M, Peter, K, Sergei, K, Shiho, K, Kostas, K, Pablo, L, Luis, L, Janna, L, Steve, L, Andrew, M, Ilya, M, Szabolcs, M, Zsuzsa, M, David, N, Paul, O, Rosalba, P, Jocelyn, R, Christian, R, Carl, R, Max, R, Erik, S, Antony, S, Peter, S, Deirdre, S, Alicia, S, Ulrich, S, Patrick, S, Nial, T, Michal, W, and Stan, W

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), Physics and Astronomy (miscellaneous), Explosive material, media_common.quotation_subject, ELECTROMAGNETIC COUNTERPARTS, FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), 01 natural sciences, General Relativity and Quantum Cosmology, SPIN-DOWN LIMIT, 0103 physical sciences, PRESUPERNOVA EVOLUTION, CORE-COLLAPSE, 010306 general physics, 010303 astronomy & astrophysics, ARMED SPIRAL INSTABILITY, media_common, High Energy Astrophysical Phenomena (astro-ph.HE), Astroparticle physics, Physics, GAMMA-RAY BURSTS, NEUTRINO PAIR ANNIHILATION, Gravitational wave, Astronomy, MASS BLACK-HOLES, Universe, BAR-MODE INSTABILITY, Interferometry, Sky, Data analysis, Transient (oscillation), Astrophysics - High Energy Astrophysical Phenomena, DRIVEN SUPERNOVA, gravitational waves, neutron stars, black holes, Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

Interferometric detectors will very soon give us an unprecedented view of the gravitational-wave sky, and in particular of the explosive and transient Universe. Now is the time to challenge our theoretical understanding of short-duration gravitational-wave signatures from cataclysmic events, their connection to more traditional electromagnetic and particle astrophysics, and the data analysis techniques that will make the observations a reality. This paper summarizes the state of the art, future science opportunities, and current challenges in understanding gravitational-wave transients., 33 pages, 2 figures

Published
2013
Full Text
View/download PDF

39. The effects of elevated CO2 and nitrogen fertilization on stomatal conductance estimated from 11 years of scaled sap flux measurements at Duke FACE

Author

Jean-Christophe Domec, David M. Bell, Heather R. McCarthy, Eric J. Ward, James S. Clark, Hyun-Seok Kim, Ram Oren, Nicholas School of the Environment and Earth Sciences, Duke University [Durham], Duke University, National University of Singapore (NUS), Department of Forestry and Environmental Resources, North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC)-University of North Carolina System (UNC), Swedish University of Agricultural Sciences (SLU), University of Oklahoma (OU), Seoul National University [Seoul] (SNU), Transfert Sol-Plante et Cycle des Eléments Minéraux dans les Ecosystèmes Cultivés (TCEM), and Institut National de la Recherche Agronomique (INRA)-École Nationale d'Ingénieurs des Travaux Agricoles - Bordeaux (ENITAB)

Subjects
0106 biological sciences, Canopy, Time Factors, leaf area, Vapor Pressure, 010504 meteorology & atmospheric sciences, sapwood area, Physiology, hierarchical Bayes, [SDV]Life Sciences [q-bio], Liquidambar styraciflua, Flux, Plant Science, 01 natural sciences, Trees, Soil, Human fertilization, Liquidambar, Photosynthesis, Transpiration, biology, Chemistry, vapor pressure deficit, Pinus taeda, Wood, [SDE]Environmental Sciences, hydraulic architecture, Jarvis model, Stomatal conductance, Nitrogen, photosynthetic active radiation, Animal science, Botany, allometry, Fertilizers, Nitrogen cycle, 0105 earth and related environmental sciences, tree height, Water, Plant Transpiration, Carbon Dioxide, Models, Theoretical, biology.organism_classification, Plant Leaves, 13. Climate action, Plant Stomata, Allometry, soil moisture, 010606 plant biology & botany
Abstract

International audience; In this study, we employ a network of thermal dissipation probes (TDPs) monitoring sap flux density to estimate leaf-specific transpiration (E(L)) and stomatal conductance (G(S)) in Pinus taeda (L.) and Liquidambar styraciflua L. exposed to +200 ppm atmospheric CO(2) levels (eCO(2)) and nitrogen fertilization. Scaling half-hourly measurements from hundreds of sensors over 11 years, we found that P. taeda in eCO(2) intermittently (49% of monthly values) decreased stomatal conductance (G(S)) relative to the control, with a mean reduction of 13% in both total E(L) and mean daytime G(S). This intermittent response was related to changes in a hydraulic allometry index (A(H)), defined as sapwood area per unit leaf area per unit canopy height, which decreased a mean of 15% with eCO(2) over the course of the study, due mostly to a mean 19% increase in leaf area (A(L)). In contrast, L. styraciflua showed a consistent (76% of monthly values) reduction in G(S) with eCO(2) with a total reduction of 32% E(L), 31% G(S) and 23% A(H) (due to increased A(L) per sapwood area). For L. styraciflua, like P. taeda, the relationship between A(H) and G(S) at reference conditions suggested a decrease in G(S) across the range of A(H). Our findings suggest an indirect structural effect of eCO(2) on G(S) in P. taeda and a direct leaf level effect in L. styraciflua. In the initial year of fertilization, P. taeda in both CO(2) treatments, as well as L. styraciflua in eCO(2), exhibited higher G(S) with N(F) than expected from shifts in A(H), suggesting a transient direct effect on G(S). Whether treatment effects on mean leaf-specific G(S) are direct or indirect, this paper highlights that long-term treatment effects on G(S) are generally reflected in A(H) as well.

Published
2013
Full Text
View/download PDF

40. Gravitational-Wave Detection using Multivariate Analysis

Author

Patrick J. Sutton, Duncan Meacher, Gareth Jones, James S. Clark, T. Adams, and Ariana Minot

Subjects
Physics, Nuclear and High Energy Physics, 010308 nuclear & particles physics, Gravitational wave, business.industry, media_common.quotation_subject, Detector, FOS: Physical sciences, Pattern recognition, General Relativity and Quantum Cosmology (gr-qc), 01 natural sciences, General Relativity and Quantum Cosmology, Sky, 0103 physical sciences, Waveform, A priori and a posteriori, False alarm, Artificial intelligence, Gradient boosting, Gamma-ray burst, business, Astrophysics - Instrumentation and Methods for Astrophysics, 010303 astronomy & astrophysics, Instrumentation and Methods for Astrophysics (astro-ph.IM), media_common
Abstract

Searches for gravitational-wave bursts (transient signals, typically of unknown waveform) require identification of weak signals in background detector noise. The sensitivity of such searches is often critically limited by non-Gaussian noise fluctuations which are difficult to distinguish from real signals, posing a key problem for transient gravitational-wave astronomy. Current noise rejection tests are based on the analysis of a relatively small number of measured properties of the candidate signal, typically correlations between detectors. Multivariate analysis (MVA) techniques probe the full space of measured properties of events in an attempt to maximise the power to accurately classify events as signal or background. This is done by taking samples of known background events and (simulated) signal events to train the MVA classifier, which can then be applied to classify events of unknown type. We apply the boosted decision tree (BDT) MVA technique to the problem of detecting gravitational-wave bursts associated with gamma-ray bursts. We find that BDTs are able to increase the sensitive distance reach of the search by as much as 50%, corresponding to a factor of ~3 increase in sensitive volume. This improvement is robust against trigger sky position, large sky localisation error, poor data quality, and the simulated signal waveforms that are used. Critically, we find that the BDT analysis is able to detect signals that have different morphologies to those used in the classifier training and that this improvement extends to false alarm probabilities beyond the 3{\sigma} significance level. These findings indicate that MVA techniques may be used for the robust detection of gravitational-wave bursts with a priori unknown waveform., Comment: 14 pages, 12 figures

Published
2013
Full Text
View/download PDF

41. Estimating the mass flux of charcoal from sedimentary records: effects of particle size, morphology, and orientation

Author

Tristram C. Hussey and James S. Clark

Subjects
Mass flux, 010506 paleontology, Archeology, Global and Planetary Change, Morphology (linguistics), 010504 meteorology & atmospheric sciences, Ecology, Orientation (computer vision), Paleontology, Mineralogy, Estimator, 01 natural sciences, visual_art, visual_art.visual_art_medium, Particle, Sedimentary rock, Particle size, Charcoal, Geomorphology, Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

Reconstructing past fire requires ways to compare concentration estimates obtained by different charcoal analysis methods. These methods estimate concentrations from area measurements or particle counts on pollen slides, on sieves, and on thin sections, and they do so at different magnifications. Depending on particle properties, each method might give substantially different results. Image analysis of charred particles in thin sections of lake sediments is used to parameterize relationships among different concentration estimators. We determined distributions of particle size, shape, and orientation in undisturbed sediments and assessed how those distributions affect concentration estimates. Particle-diameter distributions were conservative across different magnifications. Particle shape was also conservative, with major:minor axis ratios near 2.5. Our derived relationships among estimators could be used to improve comparability for all but the smallest particle classes, which tended to be unpredictable in orientation. Simple equations with nomograms for necessary parameter values are provided. We derive a settling velocity index for composite samples that can be used to estimate relative differences in source region and dispersion. Comparisons of estimates from lakes in eastern North America showed geographic coherency, with highest values in the midwest and low values in the nor theast. A single exception to the eastwardly decline came from a sand plain site in New Hampshire, where fires were expected to be more common than in the prevailing northern hardwoods of the region. Application of our method to previous estimates of mass fluxes in eastern North America show values closer to those expected based on current understanding of fire behaviour than were previous, uncorrected estimates.

Published
1996
Full Text
View/download PDF

42. Quantifying global soil carbon losses in response to warming

Author

Peter B. Reich, Noah W. Sokol, Shibo Fang, Lifen Jiang, Yiqi Luo, Yolima Carrillo, James S. Clark, Jacqueline E. Mohan, Mark A. Bradford, Clara W. Rowe, John M. Blair, Andrew J. Burton, William R. Wieder, Josep Peñuelas, Bart R. Johnson, Pamela H. Templer, Jocelyn M. Lavallee, Christian Poll, Jeffrey M. Welker, Ji-Xun Guo, Elise Pendall, Megan B. Machmuller, Linna Ma, Sabine Reinsch, Shuli Niu, Lorien L. Reynolds, Thomas W. Crowther, Marc Estiarte, Klaus Steenberg Larsen, Kathleen K. Treseder, Inger Kappel Schmidt, Serita D. Frey, Steven D. Allison, Bridget A. Emmett, Massimo Lupascu, Aimée T. Classen, Katherine Todd-Brown, Bo Elberling, Sven Marhan, John Harte, Joanna C. Carey, Hjalmar Laudon, Scott D. Bridgham, György Kröel-Dulay, Guangsheng Zhou, L. Basten Snoek, Anders Michelsen, Seeta A. Sistla, Laurel Pfeifer-Meister, Feike A. Dijkstra, and Terrestrial Ecology (TE)

Subjects
Databases, Factual, 010504 meteorology & atmospheric sciences, General Science & Technology, Non-P.H.S, Climate change, Soil science, Atmospheric sciences, Research Support, 01 natural sciences, Global Warming, Carbon cycle, Carbon Cycle, Feedback, Databases, Soil, Models, Journal Article, Life Science, Ecosystem, Non-U.S. Gov't, Laboratorium voor Nematologie, Factual, 0105 earth and related environmental sciences, Models, Statistical, Multidisciplinary, Geography, Atmosphere, Global warming, Temperature, Soil chemistry, Biogeochemistry, Reproducibility of Results, 04 agricultural and veterinary sciences, Soil carbon, 15. Life on land, Statistical, PE&RC, Carbon, Agriculture and Soil Science, 13. Climate action, international, 040103 agronomy & agriculture, 0401 agriculture, forestry, and fisheries, Soil horizon, U.S. Gov't, Laboratory of Nematology
Abstract

© 2016 Macmillan Publishers Limited. All rights reserved. The majority of the Earth's terrestrial carbon is stored in the soil. If anthropogenic warming stimulates the loss of this carbon to the atmosphere, it could drive further planetary warming. Despite evidence that warming enhances carbon fluxes to and from the soil, the net global balance between these responses remains uncertain. Here we present a comprehensive analysis of warming-induced changes in soil carbon stocks by assembling data from 49 field experiments located across North America, Europe and Asia. We find that the effects of warming are contingent on the size of the initial soil carbon stock, with considerable losses occurring in high-latitude areas. By extrapolating this empirical relationship to the global scale, we provide estimates of soil carbon sensitivity to warming that may help to constrain Earth system model projections. Our empirical relationship suggests that global soil carbon stocks in the upper soil horizons will fall by 30 ± 30 petagrams of carbon to 203 ± 161 petagrams of carbon under one degree of warming, depending on the rate at which the effects of warming are realized. Under the conservative assumption that the response of soil carbon to warming occurs within a year, a business-as-usual climate scenario would drive the loss of 55 ± 50 petagrams of carbon from the upper soil horizons by 2050. This value is around 12-17 per cent of the expected anthropogenic emissions over this period. Despite the considerable uncertainty in our estimates, the direction of the global soil carbon response is consistent across all scenarios. This provides strong empirical support for the idea that rising temperatures will stimulate the net loss of soil carbon to the atmosphere, driving a positive land carbon-climate feedback that could accelerate climate change.

Published
2016
Full Text
View/download PDF

43. Climate and Indian effects on southern Ontario forests: a reply to Campbell and McAndrews

Author

James S. Clark

Subjects
010506 paleontology, Archeology, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Interpretation (philosophy), Ecology (disciplines), Paleontology, Climate change, Vegetation, Demise, 01 natural sciences, %22">Pinus , Taxon, Disturbance (ecology), Geology, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

Clark and Royall (1994) questioned the interpretation, drawn from a simulation model, that climatic cooling was responsible for the demise of typical northern hardwoods taxa and replacement with taxa that require fire or soil disturbance, Pinus and Quercus. Those questions were raised because the model predictions did not well describe the data, the ecology of the taxa is not consistent with the interpretation, the other sites in the region do not show the patterns consistent with climate cooling, and stratigraphic charcoal data support an alternative interpretation. Campbell and McAndrews (1995) challenged our questions, but made no effort to answer them. Rather, they questioned an alternative interpretation that Iroquois maize agriculture contributed to these transitions. The main discus sion here is devoted to the uses of historic evidence, models, and sedimentary data to interpret climate vs. cultural effects. I review the evidence for fire that pertains to this region, and I reanalyze regional data to show that climate change does not provide an explanation for observed changes. I conclude with the observation that the inter pretation that climate alone is responsible for the transitions at Crawford Lake is still in need of explanation.

Published
1995
Full Text
View/download PDF

44. Transformation of a northern hardwood forest by aboriginal (Iroquois) fire: charcoal evidence from Crawford Lake, Ontario, Canada

Author

P. D. Royall and James S. Clark

Subjects
010506 paleontology, Archeology, Global and Planetary Change, 010504 meteorology & atmospheric sciences, Ecology, Paleontology, Vegetation, medicine.disease_cause, 01 natural sciences, Archaeology, Hardwood forest, Geography, Pollen, visual_art, medicine, visual_art.visual_art_medium, Period (geology), Charcoal, 0105 earth and related environmental sciences, Earth-Surface Processes, Ontario canada
Abstract

Ecologists have long debated whether Indian burning had important impacts on presettlement forests. We obtained stratigraphic evidence for fire using charcoal analysis of southern Ontario lake sediments. The record spans a period of Iroquois occupation when cultivation coincides with pollen evidence for transition from northern hardwoods to white pine/oak forests. Charcoal data reveal that this transition was attended by increased charcoal accumulation, sufficiently high to suggest vegetation fires. Results support the notion that Indian burning is capable of producing dramatic changes in forest composition spanning centuries.

Published
1995
Full Text
View/download PDF

45. Particle-Size Evidence for Source Areas of Charcoal Accumulation in Late Holocene Sediments of Eastern North American Lakes

Author

James S. Clark and P. Dan Royall

Subjects
010506 paleontology, geography, Source area, geography.geographical_feature_category, 010504 meteorology & atmospheric sciences, Ecology, Drainage basin, Sediment, 01 natural sciences, Arts and Humanities (miscellaneous), visual_art, Fire protection, Temperate climate, visual_art.visual_art_medium, General Earth and Planetary Sciences, Particle size, Physical geography, Charcoal, Geology, Holocene sediments, 0105 earth and related environmental sciences, Earth-Surface Processes
Abstract

Two methods of analyzing charcoal in sediment reveal changes in charcoal accumulation across temperate eastern North America during the last several hundred years. In one method the analyst counts mostly small particles that reflect regional emissions; in the other, the analyst counts only larger particles derived mostly from such local sources as catchment fires. We used these methods to compare charcoal accumulation at 14 lakes from the prairie/forest border in Minnesota to eastern Maine. The two methods gave concordant accumulation rates for sediments of pre-1850 age at each of 4 lakes analyzed by both methods. This concordance is consistent with the interpretation that pre-1850 emissions were controlled by broad-scale factors, such as climatically controlled regional differences in fuels and moisture. Since 1900 large particles decreased greatly, and small particles decreased slightly, in Minnesota and Wisconsin. By contrast in the Northeast the large particle accumulation has remained at the low values measured in pre-1900 sediments at most sites, while small particles increased everywhere east of central New York and Pennsylvania. The observed patterns suggest that (1) large particles primarily reflect local fires that were common in the Midwest before fire suppression became effective, (2) large particles were rare in the Northeast, especially before extensive land clearance, (3) small particles reflect regional combustion that increased in the Northeast after extensive use of fire for land clearance and wood burning for industrial purposes of the 19th century, and (4) small particles remain abundant in the Midwest long after effective fire suppression, probably because these well-dispersed small particles have a large source area that extends beyond the local wildfires that account for large particles before European settlement.

Published
1995
Full Text
View/download PDF

46. Scientific objectives of Einstein Telescope

Author

V. Fafone, C. Kant Mishra, M. Doets, A. Cumming, M. Lorenzini, Tjonnie G. F. Li, B. Lagrange, M. R. Abernathy, J. H. Hough, Roman Schnabel, Michael Britzger, F. Brueckner, J. F. J. van den Brand, Martin Hendry, Adam Woodcraft, K. V. Tokmakov, Valeria Ferrari, J. Franc, Graham Woan, F. Richard, N. Beveridge, Bernard F. Schutz, A. Morgia, M. van Veggel, G. D. Hammond, C. Graef, Sascha Husa, Alberto Vecchio, S. Chelkowski, Ian Hawke, E. Chassande-Mottin, Kostas Glampedakis, Frédérique Marion, Rosa Poggiani, N. Lastzka, Sheila Rowan, Lucía Santamaría, R. O'. Shaughnessy, Paul Fulda, P. Weßels, B. Mours, Moritz Mehmet, D. J. A. McKechan, A. Colla, Henning Vahlbruch, Alicia M. Sintes, Benno Willke, Badri Krishnan, Hartmut Grote, Ronny Nawrodt, F. Y. Khalili, G. Losurdo, Mauro Tonelli, Loriano Storchi, C. Palomba, E. Genin, S. Van Der Putten, Fumiko Kawazoe, Christian D. Ott, K. Haughian, Tania Regimbau, H. Rehbein, S. P. Vyatchanin, S. L. Danilishin, Ilya Mandel, Ettore Majorana, Ik Siong Heng, Stefanie Kroker, C. Robinson, Paolo Falferi, M. Galimberti, D. Passuello, Y. Minenkov, M. Barsuglia, Benjamin William Allen, Karsten Danzmann, John Nelson, Riccardo Bassiri, S. Braccini, S. Reid, Bangalore Suryanarayana Sathyaprakash, G. M. Guidi, R. Vaccarone, Giancarlo Cella, Carlos F. Sopuerta, L. Moscatelli, C. Van Den Broeck, Mark Beker, V. Re, H. J. Bulten, P. G. Murray, A. Gennai, A. Pasqualetti, L. Naticchioni, G. Parguez, Kostas D. Kokkotas, Jonathan R. Gair, Jan Harms, Leor Barack, Pau Amaro-Seoane, C. N. Colacino, E. Chalkley, Kazuaki Kuroda, J. Dueck, L. Di Fiore, E. J. Daw, M. Punturo, E. Hennes, Daniel Friedrich, P. J. Sutton, R. Passaquieti, E. Coccia, M. A. Bizouard, Federico Ferrini, A. Viceré, A. Giazotto, Aiko Samblowski, B. Kley, Christine Michel, P. Ajith, Benjamin Taylor, G. A. Prodi, R. Flaminio, A. Rocchi, P. Astone, F. Vetrano, M. Di Paolo Emilio, F. Piergiovanni, Angela Delli Paoli, Rajesh Kumar, Massimo Bassan, P. Puppo, Craig A. Bond, L. Cunningham, J. M. Hallam, S. Márka, Kenneth A. Strain, C. Schwarz, F. Fidecaro, Nils Andersson, K. G. Arun, H. Lück, A. Thürin, B. Sorazu, Paul Campsie, Wolfango Plastino, Andrea Chincarini, John K. Scott, I. W. Martin, D. Heinert, F. Ricci, W. Del Pozzo, E. Cuoco, Vuk Mandic, M. V. Plissi, L. Bosi, S. E. Strigin, H. Tournefier, A. Corsi, Patricia Schmidt, Fiona C. Speirits, Benoit Sassolas, R. De Salvo, S. Mosca, John Veitch, Francesco Marin, S. H. Huttner, P. Popolizio, Laurent Pinard, Helge Müller-Ebhardt, Stefan Hild, Suvadeep Bose, R. Gouaty, Sofiane Aoudia, Enrico Calloni, G. T. Jones, P. Rapagnani, Andreas Freise, Kazuhiro Yamamoto, James S. Clark, Mirko Prato, J. Colas, M. Edwards, Matthew Pitkin, W. Graham, F. Frasconi, D. Mc. Leod, M. Granata, D. S. Rabeling, I. Kamaretsos, István Rácz, Jocelyn Read, R. Schilling, Rocco Romano, M. Perciballi, A. Di. Cintio, Marc Favata, J. Marque, L. Carbone, Tomasz Bulik, W. Winkler, V. Malvezzi, N. Morgado, Fabrizio Barone, T. Dent, R. De Rosa, Fausto Acernese, Kentaro Somiya, C. Bradaschia, D. I. Jones, Stephen Fairhurst, Edward K. Porter, B. Barr, Bala R. Iyer, A. Rüdiger, Oliver Burmeister, Gianluca Gemme, S. P. Tarabrin, Paul Seidel, Keiko Kokeyama, D. Huet, A. Dietz, Mark Hannam, S. Gossan, A. Di Virgilio, Astrophysique Relativiste Théories Expériences Métrologie Instrumentation Signaux (ARTEMIS), Centre National de la Recherche Scientifique (CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA), (Astro)-Particles Physics, Mathematical Analysis, Sathyaprakash, B, Abernathy, M, Acernese, F, Ajith, P, Allen, B, Amaro Seoane, P, Andersson, N, Aoudia, S, Arun, K, Astone, P, Krishnan, B, Barack, L, Barone, F, Barr, B, Barsuglia, M, Bassan, M, Bassiri, R, Beker, M, Beveridge, N, Bizouard, M, Bond, C, Bose, S, Bosi, L, Braccini, S, Bradaschia, C, Britzger, M, Brueckner, F, Bulik, T, Bulten, Hj, Burmeister, O, Calloni, E, Campsie, P, Carbone, L, Cella, G, Chalkley, E, Chassande Mottin, E, Chelkowski, S, Chincarini, A, Cintio, Ad, Clark, J, Coccia, E, Colacino, Cn, Colas, J, Colla, A, Corsi, A, Cumming, A, Cunningham, L, Cuoco, E, Danilishin, S, Danzmann, K, Daw, E, De Salvo, R, Pozzo, Wd, Dent, T, De Rosa, R, Fiore, Ld, Emilio, Mdp, Virgilio, Ad, Dietz, A, Doets, M, Dueck, J, Edwards, M, Fafone, V, Fairhurst, S, Falferi, P, Favata, M, Ferrari, V, Ferrini, F, Fidecaro, F, Flaminio, R, Franc, J, Frasconi, F, Freise, A, Friedrich, D, Fulda, P, Gair, J, Galimberti, M, Gemme, G, Genin, E, Gennai, A, Giazotto, A, Glampedakis, K, Gossan, S, Gouaty, R, Graef, C, Graham, W, Granata, M, Grote, H, Guidi, G, Hallam, J, Hammond, G, Hannam, M, Harms, J, Haughian, K, Hawke, I, Heinert, D, Hendry, M, Heng, I, Hennes, E, Hild, S, Hough, J, Huet, D, Husa, S, Huttner, S, Iyer, B, Jones, Di, Jones, G, Kamaretsos, I, Mishra, Ck, Kawazoe, F, Khalili, F, Kley, B, Kokeyama, K, Kokkotas, K, Kroker, S, Kumar, R, Kuroda, K, Lagrange, B, Lastzka, N, Li, Tgf, Lorenzini, M, Losurdo, G, Lück, H, Majorana, E, Malvezzi, V, Mandel, I, Mandic, V, Marka, S, Marin, F, Marion, F, Marque, J, Martin, I, Leod, Dm, Mckechan, D, Mehmet, M, Michel, C, Minenkov, Y, Morgado, N, Morgia, A, Mosca, S, Moscatelli, L, Mours, B, Müller Ebhardt, H, Murray, P, Naticchioni, L, Nawrodt, R, Nelson, J, Shaughnessy, Ro, Ott, Cd, Palomba, C, Paoli, A, Parguez, G, Pasqualetti, A, Passaquieti, R, Passuello, D, Perciballi, M, Piergiovanni, F, Pinard, L, Pitkin, M, Plastino, Wolfango, Plissi, M, Poggiani, R, Popolizio, P, Porter, E, Prato, M, Prodi, G, Punturo, M, Puppo, P, Rabeling, D, Racz, I, Rapagnani, P, Re, V, Read, J, Regimbau, T, Rehbein, H, Reid, S, Ricci, F, Richard, F, Robinson, C, Rocchi, A, Romano, R, Rowan, S, Rüdiger, A, Samblowski, A, Santamaría, L, Sassolas, B, Schilling, R, Schmidt, P, Schnabel, R, Schutz, B, Schwarz, C, Scott, J, Seidel, P, Sintes, Am, Somiya, K, Sopuerta, Cf, Sorazu, B, Speirits, F, Storchi, L, Strain, K, Strigin, S, Sutton, P, Tarabrin, S, Taylor, B, Thürin, A, Tokmakov, K, Tonelli, M, Tournefier, H, Vaccarone, R, Vahlbruch, H, Van Den Brand, Jfj, Van Den Broeck, C, Van Der Putten, S, Van Veggel, M, Vecchio, A, Veitch, J, Vetrano, F, Vicere, A, Vyatchanin, S, Weels, P, Willke, B, Winkler, W, Woan, G, Woodcraft, A, Yamamoto, K., B., Sathyaprakash, M., Abernathy, F., Acernese, P., Ajith, B., Allen, P., Amaro Seoane, N., Andersson, S., Aoudia, K., Arun, P., Astone, B., Krishnan, L., Barack, F., Barone, B., Barr, M., Barsuglia, M., Bassan, R., Bassiri, M., Beker, N., Beveridge, M., Bizouard, C., Bond, S., Bose, L., Bosi, S., Braccini, C., Bradaschia, M., Britzger, F., Brueckner, T., Bulik, H. J., Bulten, O., Burmeister, Calloni, Enrico, P., Campsie, L., Carbone, G., Cella, E., Chalkley, E., Chassande Mottin, S., Chelkowski, A., Chincarini, A., Di Cintio, J., Clark, E., Coccia, C. N., Colacino, J., Cola, A., Colla, A., Corsi, A., Cumming, L., Cunningham, E., Cuoco, S., Danilishin, K., Danzmann, E., Daw, R., De Salvo, W., Del Pozzo, T., Dent, DE ROSA, Rosario, L., Di Fiore, M., Di Paolo Emilio, A., Di Virgilio, A., Dietz, M., Doet, J., Dueck, M., Edward, V., Fafone, S., Fairhurst, P., Falferi, M., Favata, V., Ferrari, F., Ferrini, F., Fidecaro, R., Flaminio, J., Franc, F., Frasconi, A., Freise, D., Friedrich, P., Fulda, J., Gair, M., Galimberti, G., Gemme, E., Genin, A., Gennai, A., Giazotto, K., Glampedaki, S., Gossan, R., Gouaty, C., Graef, W., Graham, M., Granata, H., Grote, G., Guidi, J., Hallam, G., Hammond, M., Hannam, J., Harm, K., Haughian, I., Hawke, D., Heinert, M., Hendry, I., Heng, E., Henne, S., Hild, J., Hough, D., Huet, S., Husa, S., Huttner, B., Iyer, D. I., Jone, G., Jone, I., Kamaretso, C., Kant Mishra, F., Kawazoe, F., Khalili, B., Kley, K., Kokeyama, K., Kokkota, S., Kroker, R., Kumar, K., Kuroda, B., Lagrange, N., Lastzka, T. G. F., Li, M., Lorenzini, G., Losurdo, H., Lück, E., Majorana, V., Malvezzi, I., Mandel, V., Mandic, S., Marka, F., Marin, F., Marion, J., Marque, I., Martin, D., Mc Leod, D., Mckechan, M., Mehmet, C., Michel, Y., Minenkov, N., Morgado, A., Morgia, S., Mosca, L., Moscatelli, B., Mour, H., Müller Ebhardt, P., Murray, L., Naticchioni, R., Nawrodt, J., Nelson, R., O’ Shaughnessy, C. D., Ott, C., Palomba, A., Paoli, G., Parguez, A., Pasqualetti, R., Passaquieti, D., Passuello, M., Perciballi, F., Piergiovanni, L., Pinard, M., Pitkin, W., Plastino, M., Plissi, R., Poggiani, P., Popolizio, E., Porter, M., Prato, G., Prodi, M., Punturo, P., Puppo, D., Rabeling, I., Racz, P., Rapagnani, V., Re, J., Read, T., Regimbau, H., Rehbein, S., Reid, F., Ricci, F., Richard, C., Robinson, A., Rocchi, R., Romano, S., Rowan, A., Rüdiger, A., Samblowski, L., Santamaría, B., Sassola, R., Schilling, P., Schmidt, R., Schnabel, B., Schutz, C., Schwarz, J., Scott, P., Seidel, A. M., Sinte, K., Somiya, C. F., Sopuerta, B., Sorazu, F., Speirit, L., Storchi, K., Strain, S., Strigin, P., Sutton, S., Tarabrin, B., Taylor, A., Thürin, K., Tokmakov, M., Tonelli, H., Tournefier, R., Vaccarone, H., Vahlbruch, J. F. J., van den Brand, C., Van Den Broeck, S., van der Putten, M., van Veggel, A., Vecchio, J., Veitch, F., Vetrano, A., Vicere, S., Vyatchanin, P., Weßel, B., Willke, W., Winkler, G., Woan, A., Woodcraft, K., Yamamoto, AstroParticule et Cosmologie (APC (UMR_7164)), Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Laboratoire de l'Accélérateur Linéaire (LAL), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), Laboratoire des matériaux avancés (LMA), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), APC - Cosmologie, Physique Corpusculaire et Cosmologie - Collège de France (PCC), Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), APC - Gravitation (APC-Gravitation), PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Laboratoire d'Annecy de Physique des Particules (LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Centre National de la Recherche Scientifique (CNRS), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), and Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)

Subjects
Cosmology and Nongalactic Astrophysics (astro-ph.CO), Physics and Astronomy (miscellaneous), [SDU.ASTR.CO]Sciences of the Universe [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Physics::Instrumentation and Detectors, Interferometers, Gravitational waves detectors and experiments, Observatories and site testing, GRAVITATIONAL-WAVE OBSERVATIONS, FOS: Physical sciences, GAMMA-RAY BURSTS, BLACK-HOLE, PHYSICS, INTERMEDIATE, BINARIES, TAILS, General Relativity and Quantum Cosmology (gr-qc), onde gravitazionali, Astrophysics, 01 natural sciences, General Relativity and Quantum Cosmology, Cosmology, [PHYS.ASTR.CO]Physics [physics]/Astrophysics [astro-ph]/Cosmology and Extra-Galactic Astrophysics [astro-ph.CO], Observational astronomy, Settore FIS/05 - Astronomia e Astrofisica, antenne gravitazionali iterferometriche, gravitazione, 0103 physical sciences, 010306 general physics, ComputingMilieux_MISCELLANEOUS, [PHYS]Physics [physics], Physics, Detection of gravitational waves, Einstein Telescope, 010308 nuclear & particles physics, Detector, Settore FIS/01 - Fisica Sperimentale, Astrophysics::Instrumentation and Methods for Astrophysics, Astronomy, Cosmology and Extragalactic Astrophysics, BINARY, Interferometry, Fundamental physics, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], [PHYS.ASTR]Physics [physics]/Astrophysics [astro-ph], Astrophysics - Cosmology and Nongalactic Astrophysics
Abstract

The advanced interferometer network will herald a new era in observational astronomy. There is a very strong science case to go beyond the advanced detector network and build detectors that operate in a frequency range from 1 Hz-10 kHz, with sensitivity a factor ten better in amplitude. Such detectors will be able to probe a range of topics in nuclear physics, astronomy, cosmology and fundamental physics, providing insights into many unsolved problems in these areas., 18 pages, 4 figures, Plenary talk given at Amaldi Meeting, July 2011

Published
2012
Full Text
View/download PDF

47. Sensitivity Studies for Third-Generation Gravitational Wave Observatories

Author

E. Chassande Mottin, F. Ricci, Vuk Mandic, Angela Delli Paoli, Sheila Rowan, Nils Andersson, H. Lück, Kostas D. Kokkotas, S. H. Huttner, P. Popolizio, Y. Minenkov, M. Barsuglia, Roman Schnabel, M. van Veggel, Christian D. Ott, Alberto Vecchio, Laurent Pinard, E. Cuoco, L. Di Fiore, A. Giazotto, M. Doets, Mark Hannam, S. Braccini, P. G. Murray, Benno Willke, S. Mosca, C. Palomba, E. Coccia, Andre Thüring, D. Passuello, L. Bosi, Alicia M. Sintes, A. Di Virgilio, Mark Beker, J. H. Hough, F. Frasconi, C. Schwarz, Sascha Husa, F. Richard, S. Chelkowski, Christian Gräf, S. Reid, G. Parguez, J. Colas, C. Colacino, Ik Siong Heng, Karsten Danzmann, Jocelyn Read, Helge Müller-Ebhardt, M. Punturo, C. Van Den Broeck, A. Pasqualetti, John Nelson, G. D. Hammond, Enrico Calloni, Pau Amaro-Seoane, Kazuhiro Yamamoto, S. P. Vyatchanin, R. De Salvo, Kostas Glampedakis, D. Friedrich, A. Rocchi, Ronny Nawrodt, F. Y. Khalili, A. Gurkovsky, Stefan Hild, R. Passaquieti, Tania Regimbau, H. Rehbein, Rosa Poggiani, Hartmut Grote, Suvadeep Bose, F. Vetrano, P. Puppo, E. Hennes, Keiko Kokeyama, G. T. Jones, James S. Clark, R. Flaminio, Andreas Freise, Mirko Prato, I. W. Martin, S. L. Danilishin, Wolfango Plastino, A. Gennai, M. Granata, A. Viceré, Giancarlo Cella, P. J. Sutton, Jonathan R. Gair, L. Cunningham, Kenneth A. Strain, Badri Krishnan, Christine Michel, S. E. Strigin, D. Heinert, N. Beveridge, Paolo Falferi, D. S. Rabeling, Fiona C. Speirits, John Veitch, Paul Fulda, P. Rapagnani, E. Genin, Ilya Mandel, Lucía Santamaría, Benoit Sassolas, Bangalore Suryanarayana Sathyaprakash, G. M. Guidi, R. De Rosa, Fausto Acernese, M. Mantovani, Kentaro Somiya, C. Bradaschia, N. Morgado, Fabrizio Barone, T. Dent, Tomasz Bulik, B. Mours, Richard O'Shaughnessy, B. Barr, A. Rüdiger, Gianluca Gemme, S. P. Tarabrin, Paul Seidel, S. Birindelli, Ettore Majorana, K. G. Arun, Andrea Chincarini, J. F. J. van den Brand, Martin Hendry, J. Franc, V. Fafone, Tjonnie G. F. Li, M. R. Abernathy, Graham Woan, Jan Harms, A. Cumming, M. Lorenzini, Laboratoire de l'Accélérateur Linéaire (LAL), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Paris-Sud - Paris 11 (UP11), APC - Cosmologie, AstroParticule et Cosmologie (APC (UMR_7164)), Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3), Observatoire de la Côte d'Azur (OCA), Institut national des sciences de l'Univers (INSU - CNRS)-Centre National de la Recherche Scientifique (CNRS), APC - Gravitation (APC-Gravitation), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), Max-Planck-Gesellschaft-Max-Planck-Gesellschaft, Laboratoire des matériaux avancés (LMA), Centre National de la Recherche Scientifique (CNRS)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon, Laboratoire d'Annecy de Physique des Particules (LAPP), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS), S.Buchman , K.-X. Sun, Hild, S, Abernathy, M, Acernese, F, Amaro Seoane, P, Andersson, N, Arun, K, Barone, F, Barr, B, Barsuglia, M, Beker, M, Beveridge, N, Birindelli, S, Bose, S, Bosi, L, Braccini, S, Bradaschia, C, Bulik, T, Calloni, E, Cella, G, Mottin, Ec, Chelkowski, S, Chincarini, A, Clark, J, Coccia, E, Colacino, C, Colas, J, Cumming, A, Cunningham, L, Cuoco, E, Danilishin, S, Danzmann, K, De Salvo, R, Dent, T, De Rosa, R, Di Fiore, L, Di Virgilio, A, Doets, M, Fafone, V, Falferi, P, Flaminio, R, Franc, J, Frasconi, F, Freise, A, Friedrich, D, Fulda, P, Gair, J, Gemme, G, Genin, E, Gennai, A, Giazotto, A, Glampedakis, K, Graf, C, Granata, M, Grote, H, Guidi, G, Gurkovsky, A, Hammond, G, Hannam, M, Harms, J, Heinert, D, Hendry, M, Heng, I, Hennes, E, Hough, J, Husa, S, Huttner, S, Jones, G, Khalili, F, Kokeyama, K, Kokkotas, K, Krishnan, B, Li, Tgf, Lorenzini, M, Luck, H, Majorana, E, Mandel, I, Mandic, V, Mantovani, M, Martin, I, Michel, C, Minenkov, Y, Morgado, N, Mosca, S, Mours, B, Muller Ebhardt, H, Murray, P, Nawrodt, R, Nelson, J, Oshaughnessy, R, Ott, Cd, Palomba, C, Paoli, A, Parguez, G, Pasqualetti, A, Passaquieti, R, Passuello, D, Pinard, L, Plastino, Wolfango, Poggiani, R, Popolizio, P, Prato, M, Punturo, M, Puppo, P, Rabeling, D, Rapagnani, P, Read, J, Regimbau, T, Rehbein, H, Reid, S, Ricci, F, Richard, F, Rocchi, A, Rowan, S, Rudiger, A, Santamaria, L, Sassolas, B, Sathyaprakash, B, Schnabel, R, Schwarz, C, Seidel, P, Sintes, A, Somiya, K, Speirits, F, Strain, K, Strigin, S, Sutton, P, Tarabrin, S, Thuring, A, van den Brand, J, van Veggel, M, van den Broeck, C, Vecchio, A, Veitch, J, Vetrano, F, Vicere, A, Vyatchanin, S, Willke, B, Woan, G, Yamamoto, K., Université Paris-Sud - Paris 11 (UP11)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), Physique Corpusculaire et Cosmologie - Collège de France (PCC), Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Collège de France (CdF)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-AstroParticule et Cosmologie (APC (UMR_7164)), Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7), Centre National de la Recherche Scientifique (CNRS), PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Observatoire de Paris, PSL Research University (PSL)-PSL Research University (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS), Laboratoire d'Annecy de Physique des Particules (LAPP/Laboratoire d'Annecy-le-Vieux de Physique des Particules), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Observatoire de Paris, Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université Paris Diderot - Paris 7 (UPD7)-Centre National de la Recherche Scientifique (CNRS)-Max-Planck-Institut für Gravitationsphysik ( Albert-Einstein-Institut ) (AEI), Université de Lyon-Université de Lyon-Institut National de Physique Nucléaire et de Physique des Particules du CNRS (IN2P3)-Centre National de la Recherche Scientifique (CNRS), F., Acernese, F., Barone, Calloni, Enrico, DE ROSA, Rosario, L., Di Fiore, and S., Mosca

Subjects
Gravitational-wave observatory, Physics and Astronomy (miscellaneous), Field (physics), FOS: Physical sciences, General Relativity and Quantum Cosmology (gr-qc), 01 natural sciences, Gravitational-wave astronomy, 04.80.Nn, 95.75.Kk, General Relativity and Quantum Cosmology, Settore FIS/05 - Astronomia e Astrofisica, VIRGO SUPERATTENUATOR, 0103 physical sciences, DETECTORS, SILICA, 010303 astronomy & astrophysics, OPTICAL COATINGS, Physics, Einstein Telescope, 010308 nuclear & particles physics, Gravitational wave, SEISMIC NOISE, Settore FIS/01 - Fisica Sperimentale, Detector, PERFORMANCE, THERMAL NOISE, Computational physics, Radiation pressure, [PHYS.GRQC]Physics [physics]/General Relativity and Quantum Cosmology [gr-qc], Noise (radio)
Abstract

Advanced gravitational wave detectors, currently under construction, are expected to directly observe gravitational wave signals of astrophysical origin. The Einstein Telescope, a third-generation gravitational wave detector, has been proposed in order to fully open up the emerging field of gravitational wave astronomy. In this article we describe sensitivity models for the Einstein Telescope and investigate potential limits imposed by fundamental noise sources. A special focus is set on evaluating the frequency band below 10Hz where a complex mixture of seismic, gravity gradient, suspension thermal and radiation pressure noise dominates. We develop the most accurate sensitivity model, referred to as ET-D, for a third-generation detector so far, including the most relevant fundamental noise contributions., 13 pages, 7 pictures

Published
2010
Full Text
View/download PDF

48. Prospects for joint radio telescope and gravitational-wave searches for astrophysical transients

Author

Jonah Kanner, D. J. White, E. J. Daw, Graham Woan, Tania Regimbau, James S. Clark, P. J. Sutton, Alberto Vecchio, Stephen Fairhurst, Ik Siong Heng, X. Siemens, V. Predoi, P. Shawhan, Teviet Creighton, Cardiff University, The University of Texas at Brownsville and Texas Southmost College, University of Sheffield [Sheffield], University of Glasgow, University of Maryland [College Park], University of Maryland System, Astrophysique Relativiste Théories Expériences Métrologie Instrumentation Signaux (ARTEMIS), Université Nice Sophia Antipolis (... - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut national des sciences de l'Univers (INSU - CNRS)-Observatoire de la Côte d'Azur, Université Côte d'Azur (UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Université Côte d'Azur (UCA)-Centre National de la Recherche Scientifique (CNRS), University of Wisconsin - Milwaukee, and University of Birmingham [Birmingham]

Subjects
Physics, Physics and Astronomy (miscellaneous), Field (physics), 010308 nuclear & particles physics, Gravitational wave, FOS: Physical sciences, Binary number, Astronomy, General Relativity and Quantum Cosmology (gr-qc), 01 natural sciences, General Relativity and Quantum Cosmology, Radio telescope, Coincident, 0103 physical sciences, Physical Sciences, Joint (building), 010303 astronomy & astrophysics
Abstract

The radio skies remain mostly unobserved when it comes to transient phenomena. The direct detection of gravitational waves will mark a major milestone of modern astronomy, as an entirely new window will open on the universe. Two apparently independent phenomena can be brought together in a coincident effort that has the potential to boost both searches. In this paper we will outline the scientific case that stands behind these future joint observations and will describe the methods that might be used to conduct the searches and analyze the data. The targeted sources are binary systems of compact objects, known to be strong candidate sources for gravitational waves. Detection of transients coincident in these two channels would be a significant smoking gun for first direct detection of gravitational waves, and would open up a new field for characterization of astrophysical transients involving massive compact objects., 12 pages, Amaldi 8 Conference (New York, 2009) proceedings paper

Published
2010
Full Text
View/download PDF

49. Individual variability in tree allometry determines light resource allocation in forest ecosystems: a hierarchical Bayesian approach

Author

Georges Kunstler, Jean-François Dhôte, Ghislain Vieilledent, Benoît Courbaud, James S. Clark, Laboratoire d'Etudes des Ressources Forêt-Bois (LERFoB), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), and Duke University [Durham]

Subjects
0106 biological sciences, Time Factors, Light, [SDV]Life Sciences [q-bio], Phénotype, F62 - Physiologie végétale - Croissance et développement, Tree allometry, 01 natural sciences, Trees, Photosynthesis, Resource allocation, media_common, Propriété rhéologique, biology, U10 - Informatique, mathématiques et statistiques, Ecology, Phenotype, Succession écologique, Italy, Forêt, France, Interception, Modèle mathématique, Switzerland, Écosystème, F40 - Écologie végétale, media_common.quotation_subject, Lumière, Arbre, 010603 evolutionary biology, Intraspecific competition, Competition (biology), Variation génétique, Plasticité, Species Specificity, Forest ecology, Mesure, Hierarchical Bayes, Picea, Croissance, Succession, Ecology, Evolution, Behavior and Systematics, Ecosystem, Phenotypic plasticity, Picea abies, Bayes Theorem, 15. Life on land, Individual variability, biology.organism_classification, K10 - Production forestière, Allometry, 010606 plant biology & botany
Abstract

Tree species differences in crown size and shape are often highlighted as key characteristics determining light interception strategies and successional dynamics. The phenotypic plasticity of species in response to light and space availability suggests that intraspecific variability can have potential consequences on light interception and community dynamics. Species crown size varies depending on site characteristics and other factors at the individual level which differ from competition for light and space. These factors, such as individual genetic characteristics, past disturbances or environmental micro-site effects, combine with competition-related phenotypic plasticity to determine the individual variability in crown size. Site and individual variability are typically ignored when considering crown size and light interception by trees, and residual variability is relegated to a residual error term, which is then ignored when studying ecological processes. In the present study, we structured and quantified variability at the species, site, and individual levels for three frequently used tree allometric relations using fixed and random effects in a hierarchical Bayesian framework. We focused on two species: Abies alba (silver fir) and Picea abies (Norway spruce) in nine forest stands of the western Alps. We demonstrated that species had different allometric relations from site to site and that individual variability accounted for a large part of the variation in allometric relations. Using a spatially explicit radiation transmission model on real stands, we showed that individual variability in tree allometry had a substantial impact on light resource allocation in the forest. Individual variability in tree allometry modulates species' light-intercepting ability. It generates heterogeneous light conditions under the canopy, with high light micro-habitats that may promote the regeneration of light-demanding species and slow down successional dynamics.

Published
2010
Full Text
View/download PDF

50. Biases in the estimation of size-dependent mortality models: advantages of a semiparametric approach

Author

Benoît Courbaud, Georges Kunstler, Ghislain Vieilledent, James S. Clark, Jean-François Dhôte, Centre national du machinisme agricole, du génie rural, des eaux et forêts (CEMAGREF), Laboratoire d'Etudes des Ressources Forêt-Bois (LERFoB), AgroParisTech-Institut National de la Recherche Agronomique (INRA), Duke University [Durham], Institut National de la Recherche Agronomique (INRA)-AgroParisTech, Irstea Publications, Migration, Ecosystèmes montagnards (UR EMGR), Institut National de la Recherche Agronomique (INRA), DUKE UNIVERSITY DURHAM USA, Partenaires IRSTEA, and Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)-Institut national de recherche en sciences et technologies pour l'environnement et l'agriculture (IRSTEA)

Subjects
0106 biological sciences, [SDE] Environmental Sciences, Bark beetle, [SDV]Life Sciences [q-bio], F62 - Physiologie végétale - Croissance et développement, Mortalité, 010603 evolutionary biology, 01 natural sciences, Statistics, Shade tolerance, Mathematics, Estimation, Global and Planetary Change, Ecology, biology, U10 - Informatique, mathématiques et statistiques, Picea abies, Mortality rate, Size dependent, Forestry, 15. Life on land, biology.organism_classification, K10 - Production forestière, Abies alba, Mortality data, [SDE]Environmental Sciences, Modèle mathématique, 010606 plant biology & botany
Abstract

Mortality rate is thought to show a U-shape relationship to tree size. This shape could result from a decrease of competition-related mortality as diameter increases, followed by an increase of senescence and disturbance-related mortality for large trees. Modeling mortality rate as a function of diameter is nevertheless difficult, first because this relationship is strongly nonlinear, and second because data can be unbalanced, with few observations for large trees. Parametric functions, which are inflexible and sensitive to the distribution of observations, tend to introduce biases in mortality rate estimates. In this study we use mortality data for Abies alba Mill. and Picea abies (L.) Karst. to demonstrate that mortality rate estimates for extreme diameters were biased when using classical parametric functions. We then propose a semiparametric approach allowing a more flexible relationship between mortality and diameter. We show that the relatively shade tolerant A. alba has a lower annual mortality rate (2.75%) than P. abies (3.78%) for small trees (DBH

Published
2009
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results