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1. Disturbance sensitivity shapes patterns of tree species distribution in Afrotropical lowland rainforests more than climate or soil

Author: Chase L. Núñez, James S. Clark, and John R. Poulsen
Subjects: Anthropocene, biodiversity, climate change, joint species distribution modeling, plant traits, tropical forest, Ecology, QH540-549.5
Abstract: Abstract Understanding how tropical forests respond to abiotic environmental changes is critical for preserving biodiversity, mitigating climate change, and maintaining ecosystem services in the coming century. To evaluate the relative roles of the abiotic environment and human disturbance on Central African tree community composition, we employ tree inventory data, remotely sensed climatic data, and soil nutrient data collected from 30 1‐ha plots distributed across a large‐scale observational experiment in forests that had been differently impacted by logging and hunting in northern Republic of Congo. We show that the composition of Afrotropical plant communities at this scale responds to human disturbance more than to climate, with particular sensitivities to hunting and distance to the nearest village (a proxy for other human activities, including tree‐cutting and gathering). These findings contrast neotropical predictions, highlighting the unique ecological, evolutionary, and anthropogenic history of Afrotropical forests.
Published: 2024
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2. Learning from monitoring networks: Few-large vs. many-small plots and multi-scale analysis

Author: Becky Tang, Renata P. Kamakura, David T. Barnett, and James S. Clark
Subjects: aggregation, clustering, Forest Inventory and Analysis (FIA), parameter uncertainty, prediction performance, sample design, Evolution, QH359-425, Ecology, QH540-549.5
Abstract: In order to learn about broad scale ecological patterns, data from large-scale surveys must allow us to either estimate the correlations between the environment and an outcome and/or accurately predict ecological patterns. An important part of data collection is the sampling effort used to collect observations, which we decompose into two quantities: the number of observations or plots (n) and the per-observation/plot effort (E; e.g., area per plot). If we want to understand the relationships between predictors and a response variable, then lower model parameter uncertainty is desirable. If the goal is to predict a response variable, then lower prediction error is preferable. We aim to learn if and when aggregating data can help attain these goals. We find that a small sample size coupled with large observation effort coupled (few large) can yield better predictions when compared to a large number of observations with low observation effort (many small). We also show that the combination of the two values (n and E), rather than one alone, has an impact on parameter uncertainty. In an application to Forest Inventory and Analysis (FIA) data, we model the tree density of selected species at various amounts of aggregation using linear regression in order to compare the findings from simulated data to real data. The application supports the theoretical findings that increasing observational effort through aggregation can lead to improved predictions, conditional on the thoughtful aggregation of the observational plots. In particular, aggregations over extremely large and variable covariate space may lead to poor prediction and high parameter uncertainty. Analyses of large-range data can improve with aggregation, with implications for both model evaluation and sampling design: testing model prediction accuracy without an underlying knowledge of the datasets and the scale at which predictor variables operate can obscure meaningful results.
Published: 2023
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3. Limits to reproduction and seed size-number trade-offs that shape forest dominance and future recovery

Author: Tong Qiu, Robert Andrus, Marie-Claire Aravena, Davide Ascoli, Yves Bergeron, Roberta Berretti, Daniel Berveiller, Michal Bogdziewicz, Thomas Boivin, Raul Bonal, Don C. Bragg, Thomas Caignard, Rafael Calama, J. Julio Camarero, Chia-Hao Chang-Yang, Natalie L. Cleavitt, Benoit Courbaud, Francois Courbet, Thomas Curt, Adrian J. Das, Evangelia Daskalakou, Hendrik Davi, Nicolas Delpierre, Sylvain Delzon, Michael Dietze, Sergio Donoso Calderon, Laurent Dormont, Josep Espelta, Timothy J. Fahey, William Farfan-Rios, Catherine A. Gehring, Gregory S. Gilbert, Georg Gratzer, Cathryn H. Greenberg, Qinfeng Guo, Andrew Hacket-Pain, Arndt Hampe, Qingmin Han, Janneke Hille Ris Lambers, Kazuhiko Hoshizaki, Ines Ibanez, Jill F. Johnstone, Valentin Journé, Daisuke Kabeya, Christopher L. Kilner, Thomas Kitzberger, Johannes M. H. Knops, Richard K. Kobe, Georges Kunstler, Jonathan G. A. Lageard, Jalene M. LaMontagne, Mateusz Ledwon, Francois Lefevre, Theodor Leininger, Jean-Marc Limousin, James A. Lutz, Diana Macias, Eliot J. B. McIntire, Christopher M. Moore, Emily Moran, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Kyotaro Noguchi, Jean-Marc Ourcival, Robert Parmenter, Ian S. Pearse, Ignacio M. Perez-Ramos, Lukasz Piechnik, John Poulsen, Renata Poulton-Kamakura, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, Francisco Rodriguez-Sanchez, Javier D. Sanguinetti, C. Lane Scher, William H. Schlesinger, Harald Schmidt Van Marle, Barbara Seget, Shubhi Sharma, Miles Silman, Michael A. Steele, Nathan L. Stephenson, Jacob N. Straub, I-Fang Sun, Samantha Sutton, Jennifer J. Swenson, Margaret Swift, Peter A. Thomas, Maria Uriarte, Giorgio Vacchiano, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, Boyd Wright, S. Joseph Wright, Kai Zhu, Jess K. Zimmerman, Roman Zlotin, Magdalena Zywiec, and James S. Clark
Subjects: Science
Abstract: The relationships that control seed production in trees are key to understand evolutionary pressures that have shaped forests. A global synthesis of fecundity data reveals that while seed production is not constrained by a strict size-number trade-off, it is influenced by taxonomy and nutrient allocation.
Published: 2022
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4. Jointly modeling marine species to inform the effects of environmental change on an ecological community in the Northwest Atlantic

Author: Sarah M. Roberts, Patrick N. Halpin, and James S. Clark
Subjects: Medicine, Science
Abstract: Abstract Single species distribution models (SSDMs) are typically used to understand and predict the distribution and abundance of marine fish by fitting distribution models for each species independently to a combination of abiotic environmental variables. However, species abundances and distributions are influenced by abiotic environmental preferences as well as biotic dependencies such as interspecific competition and predation. When species interact, a joint species distribution model (JSDM) will allow for valid inference of environmental effects. We built a joint species distribution model of marine fish and invertebrates of the Northeast US Continental Shelf, providing evidence on species relationships with the environment as well as the likelihood of species to covary. Predictive performance is similar to SSDMs but the Bayesian joint modeling approach provides two main advantages over single species modeling: (1) the JSDM directly estimates the significance of environmental effects; and (2) predicted species richness accounts for species dependencies. An additional value of JSDMs is that the conditional prediction of species distributions can use not only the environmental associations of species, but also the presence and abundance of other species when forecasting future climatic associations.
Published: 2022
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5. Rethinking the nature of intraspecific variability and its consequences on species coexistence

Author: Camille Girard‐Tercieux, Isabelle Maréchaux, Adam T. Clark, James S. Clark, Benoît Courbaud, Claire Fortunel, Joannès Guillemot, Georges Künstler, Guerric leMaire, Raphaël Pélissier, Nadja Rüger, and Ghislain Vieilledent
Subjects: competition, environmental variation, high‐dimensional niche, individual variation, intraspecific variability, spatial autocorrelation, Ecology, QH540-549.5
Abstract: Abstract Intraspecific variability (IV) has been proposed to explain species coexistence in diverse communities. Assuming, sometimes implicitly, that conspecific individuals can perform differently in the same environment and that IV increases niche overlap, previous studies have found contrasting results regarding the effect of IV on species coexistence. We aim at showing that the large IV observed in data does not mean that conspecific individuals are necessarily different in their response to the environment and that the role of high‐dimensional environmental variation in determining IV has largely remained unexplored in forest plant communities. We first used a simulation experiment where an individual attribute is derived from a high‐dimensional model, representing “perfect knowledge” of individual response to the environment, to illustrate how large observed IV can result from “imperfect knowledge” of the environment. Second, using growth data from clonal Eucalyptus plantations in Brazil, we estimated a major contribution of the environment in determining individual growth. Third, using tree growth data from long‐term tropical forest inventories in French Guiana, Panama and India, we showed that tree growth in tropical forests is structured spatially and that despite a large observed IV at the population level, conspecific individuals perform more similarly locally than compared with heterospecific individuals. As the number of environmental dimensions that are well quantified at fine scale is generally lower than the actual number of dimensions influencing individual attributes, a great part of observed IV might be represented as random variation across individuals when in fact it is environmentally driven. This mis‐representation has important consequences for inference about community dynamics. We emphasize that observed IV does not necessarily impact species coexistence per se but can reveal species response to high‐dimensional environment, which is consistent with niche theory and the observation of the many differences between species in nature.
Published: 2023
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6. Fishing gear entanglement threatens recovery of critically endangered North Atlantic right whales

Author: Amy R. Knowlton, James S. Clark, Philip K. Hamilton, Scott D. Kraus, Heather M. Pettis, Rosalind M. Rolland, and Robert S. Schick
Subjects: entanglement, fixed fishing gear, health, injury severity, reproduction, survival, Ecology, QH540-549.5, General. Including nature conservation, geographical distribution, QH1-199.5
Abstract: Abstract North Atlantic right whales frequently become entangled in fishing gear, which can negatively affect their reproductive output and probability of survival. We estimated individual whale health from a hierarchical Bayesian model fit to photographic indices of health. We reviewed 696 whales sighted from 1980 to 2011 and assigned 1196 entanglement events to 573 individuals in six categories of increasing injury severity and estimated monthly median health scores (0–100 scale) for the duration of their life within the study period. We then quantified the relationship between entanglement injury events and their severity with survival, reproduction, and population health. Severe entanglements resulted in worse health for all whales—males and females with severe injuries were eight times more likely to die than males with minor injuries. Females with severe injuries that survived had the lowest birth rates. Though the relationship between entanglement and fecundity was complex, we found that as the health of reproductively active females declined, their calving intervals increased. Unimpacted whale health scores declined significantly over three decades, 1980s, 1990s, and 2000s, suggesting food limitations may be contributing to population‐wide health declines. Decadal health scores of entangled whales showed a more notable reduction in health suggesting a clear and perhaps synergistic effect.
Published: 2022
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7. Continent-wide tree fecundity driven by indirect climate effects

Author: James S. Clark, Robert Andrus, Melaine Aubry-Kientz, Yves Bergeron, Michal Bogdziewicz, Don C. Bragg, Dale Brockway, Natalie L. Cleavitt, Susan Cohen, Benoit Courbaud, Robert Daley, Adrian J. Das, Michael Dietze, Timothy J. Fahey, Istem Fer, Jerry F. Franklin, Catherine A. Gehring, Gregory S. Gilbert, Cathryn H. Greenberg, Qinfeng Guo, Janneke HilleRisLambers, Ines Ibanez, Jill Johnstone, Christopher L. Kilner, Johannes Knops, Walter D. Koenig, Georges Kunstler, Jalene M. LaMontagne, Kristin L. Legg, Jordan Luongo, James A. Lutz, Diana Macias, Eliot J. B. McIntire, Yassine Messaoud, Christopher M. Moore, Emily Moran, Jonathan A. Myers, Orrin B. Myers, Chase Nunez, Robert Parmenter, Sam Pearse, Scott Pearson, Renata Poulton-Kamakura, Ethan Ready, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, C. Lane Scher, William H. Schlesinger, Amanda M. Schwantes, Erin Shanahan, Shubhi Sharma, Michael A. Steele, Nathan L. Stephenson, Samantha Sutton, Jennifer J. Swenson, Margaret Swift, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, Kai Zhu, and Roman Zlotin
Subjects: Science
Abstract: Disentangling the various pathways by which climate change may drive community shifts in real-world ecosystems is challenging. Here the authors apply a trend attribution approach to a large dataset from the MASTIF database to assess the contribution of direct and indirect effects of climate on tree fecundity in North America, finding that the latter dominate trends by affecting tree growth and size and thereby fecundity.
Published: 2021
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8. Post-translational Modifications of the p53 Protein and the Impact in Alzheimer’s Disease: A Review of the Literature

Author: James S. Clark, Rakez Kayed, Giulia Abate, Daniela Uberti, Paul Kinnon, and Simona Piccirella
Subjects: p53, Alzheimer’s disease (AD), post translational modification (PTM), review, TP53, Neurosciences. Biological psychiatry. Neuropsychiatry, RC321-571
Abstract: Our understanding of Alzheimer’s disease (AD) pathogenesis has developed with several hypotheses over the last 40 years, including the Amyloid and Tau hypotheses. More recently, the p53 protein, well-known as a genome guardian, has gained attention for its potential role in the early evolution of AD. This is due to the central involvement of p53’s in the control of oxidative stress and potential involvement in the Amyloid and Tau pathways. p53 is commonly regulated by post-translational modifications (PTMs), which affect its conformation, increasing its capacity to adopt multiple structural and functional states, including those that can affect brain processes, thus contributing to AD development. The following review will explore the impact of p53 PTMs on its function and consequential involvement in AD pathogenesis. The greater understanding of the role of p53 in the pathogenesis of AD could result in more targeted therapies benefiting the many patients of this debilitating disease.
Published: 2022
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9. Distinct Community-Wide Responses to Forecasted Climate Change in Afrotropical Forests

Author: Chase L. Núñez, John R. Poulsen, Lee J. T. White, Vincent Medjibe, and James S. Clark
Subjects: afrotropics, Gabon, joint attribute modeling, biodiversity, community, Evolution, QH359-425, Ecology, QH540-549.5
Abstract: More refined knowledge of how tropical forests respond to changes in the abiotic environment is necessary to mitigate climate change, maintain biodiversity, and preserve ecosystem services. To evaluate the unique response of diverse Afrotropical forest communities to disturbances in the abiotic environment, we employ country-wide tree species inventories, remotely sensed climate data, and future climate predictions collected from 104 1-ha plots in the central African country of Gabon. We predict a 3–8% decrease in Afrotropical forest species richness by the end of the century, in contrast to the 30–50% loss of plant diversity predicted to occur with equivalent warming in the Neotropics. This work reveals that forecasts of community species composition are not generalizable across regions, and more representative studies are needed in understudied diverse biomes. This study serves as an important counterpoint to work done in the Neotropics by providing contrasting predictions for Afrotropical forests with substantially different ecological, evolutionary, and anthropogenic histories.
Published: 2022
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10. Niche Shifts From Trees to Fecundity to Recruitment That Determine Species Response to Climate Change

Author: Tong Qiu, Shubhi Sharma, Christopher W. Woodall, and James S. Clark
Subjects: climate change, regeneration niche, tree migration, life-history stages, seed production, Evolution, QH359-425, Ecology, QH540-549.5
Abstract: Anticipating the next generation of forests requires understanding of recruitment responses to habitat change. Tree distribution and abundance depend not only on climate, but also on habitat variables, such as soils and drainage, and on competition beneath a shaded canopy. Recent analyses show that North American tree species are migrating in response to climate change, which is exposing each population to novel climate-habitat interactions (CHI). Because CHI have not been estimated for either adult trees or regeneration (recruits per year per adult basal area), we cannot evaluate migration potential into the future. Using the Masting Inference and Forecasting (MASTIF) network of tree fecundity and new continent-wide observations of tree recruitment, we quantify impacts for redistribution across life stages from adults to fecundity to recruitment. We jointly modeled response of adult abundance and recruitment rate to climate/habitat conditions, combined with fecundity sensitivity, to evaluate if shifting CHI explain community reorganization. To compare climate effects with tree fecundity, which is estimated from trees and thus is "conditional" on tree presence, we demonstrate how to quantify this conditional status for regeneration. We found that fecundity was regulated by temperature to a greater degree than other stages, yet exhibited limited responses to moisture deficit. Recruitment rate expressed strong sensitivities to CHI, more like adults than fecundity, but still with substantial differences. Communities reorganized from adults to fecundity, but there was a re-coalescence of groups as seedling recruitment partially reverted to community structure similar to that of adults. Results provide the first estimates of continent-wide community sensitivity and their implications for reorganization across three life-history stages under climate change.
Published: 2021
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11. 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, and Wilfried Thuiller
Subjects: Biodiversity modeling, dimension reduction, joint species distribution model, latent factors, Bayesian nonparametrics, plant communities, Evolution, QH359-425, Ecology, QH540-549.5
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
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12. Author Correction: Continent-wide tree fecundity driven by indirect climate effects

Author: James S. Clark, Robert Andrus, Melaine Aubry-Kientz, Yves Bergeron, Michal Bogdziewicz, Don C. Bragg, Dale Brockway, Natalie L. Cleavitt, Susan Cohen, Benoit Courbaud, Robert Daley, Adrian J. Das, Michael Dietze, Timothy J. Fahey, Istem Fer, Jerry F. Franklin, Catherine A. Gehring, Gregory S. Gilbert, Cathryn H. Greenberg, Qinfeng Guo, Janneke HilleRisLambers, Ines Ibanez, Jill Johnstone, Christopher L. Kilner, Johannes Knops, Walter D. Koenig, Georges Kunstler, Jalene M. LaMontagne, Kristin L. Legg, Jordan Luongo, James A. Lutz, Diana Macias, Eliot J. B. McIntire, Yassine Messaoud, Christopher M. Moore, Emily Moran, Jonathan A. Myers, Orrin B. Myers, Chase Nunez, Robert Parmenter, Sam Pearse, Scott Pearson, Renata Poulton-Kamakura, Ethan Ready, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, C. Lane Scher, William H. Schlesinger, Amanda M. Schwantes, Erin Shanahan, Shubhi Sharma, Michael A. Steele, Nathan L. Stephenson, Samantha Sutton, Jennifer J. Swenson, Margaret Swift, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, Kai Zhu, and Roman Zlotin
Subjects: Science
Abstract: A Correction to this paper has been published: https://doi.org/10.1038/s41467-021-22025-2
Published: 2021
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13. Divergent reproductive allocation trade‐offs with canopy exposure across tree species in temperate forests

Author: Aaron B. Berdanier and James S. Clark
Subjects: allocation, biomass, competition, forest, life history, light, Ecology, QH540-549.5
Abstract: 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
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14. Habitat–trait interactions that control response to climate change: North American ground beetles (Carabidae)

Author: Tong Qiu, Aaron J. Bell, Jennifer J. Swenson, and James S. Clark
Published: 2023
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15. Community Reorganization Response to Climate Change: Species Interactions, State-Space Modeling and Food Webs.

Author: Jennifer J. Swenson, Tong Qui, Amanda M. Schwantes, Christopher Kilner, Chase Nuñez, Lane Scher, Shubham Sharma, and James S. Clark
Published: 2020
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16. Models for Ecological Data: An Introduction

Author: James S. Clark
Published: 2020

17. The emergent interactions that govern biodiversity change

Author: James S. Clark, C. Lane Scher, and Margaret Swift
Published: 2020
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18. North American tree migration paced by climate in the West, lagging in the East

Author: Shubhi Sharma, Robert Andrus, Yves Bergeron, Michal Bogdziewicz, Don C. Bragg, Dale Brockway, Natalie L. Cleavitt, Benoit Courbaud, Adrian J. Das, Michael Dietze, Timothy J. Fahey, Jerry F. Franklin, Gregory S. Gilbert, Cathryn H. Greenberg, Qinfeng Guo, Janneke Hille Ris Lambers, Ines Ibanez, Jill F. Johnstone, Christopher L. Kilner, Johannes M. H. Knops, Walter D. Koenig, Georges Kunstler, Jalene M. LaMontagne, Diana Macias, Emily Moran, Jonathan A. Myers, Robert Parmenter, Ian S. Pearse, Renata Poulton-Kamakura, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, C. Lane Scher, William H. Schlesinger, Michael A. Steele, Nathan L. Stephenson, Jennifer J. Swenson, Margaret Swift, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, Christopher W. Woodall, Roman Zlotin, and James S. Clark
Published: 2022
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19. Is there tree senescence? The fecundity evidence

Author: Tong Qiu, Marie-Claire Aravena, Robert Andrus, Davide Ascoli, Yves Bergeron, Roberta Berretti, Michal Bogdziewicz, Thomas Boivin, Raul Bonal, Thomas Caignard, Rafael Calama, J. Julio Camarero, Connie J. Clark, Benoit Courbaud, Sylvain Delzon, Sergio Donoso Calderon, William Farfan-Rios, Catherine A. Gehring, Gregory S. Gilbert, Cathryn H. Greenberg, Qinfeng Guo, Janneke Hille Ris Lambers, Kazuhiko Hoshizaki, Ines Ibanez, Valentin Journé, Christopher L. Kilner, Richard K. Kobe, Walter D. Koenig, Georges Kunstler, Jalene M. LaMontagne, Mateusz Ledwon, James A. Lutz, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Chase L. Nuñez, Ian S. Pearse, Łukasz Piechnik, John R. Poulsen, Renata Poulton-Kamakura, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, C. Lane Scher, Harald Schmidt Van Marle, Barbara Seget, Shubhi Sharma, Miles Silman, Jennifer J. Swenson, Margaret Swift, Maria Uriarte, Giorgio Vacchiano, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, S. Joseph Wright, Kai Zhu, Jess K. Zimmerman, Magdalena Żywiec, and James S. Clark
Published: 2021
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20. Modeling Community Dynamics Through Environmental Effects, Species Interactions and Movement

Author: Becky Tang, James S. Clark, Peter P. Marra, and Alan E. Gelfand
Subjects: Statistics and Probability, Applied Mathematics, Statistics, Probability and Uncertainty, General Agricultural and Biological Sciences, Agricultural and Biological Sciences (miscellaneous), General Environmental Science
Published: 2022
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21. Pervasive shifts in forest dynamics in a changing world

Author: Nate G. McDowell, Craig D. Allen, Kristina Anderson-Teixeira, Brian H. Aukema, Ben Bond-Lamberty, Louise Chini, James S. Clark, Michael Dietze, Charlotte Grossiord, Adam Hanbury-Brown, George C. Hurtt, Robert B. Jackson, Daniel J. Johnson, Lara Kueppers, Jeremy W. Lichstein, Kiona Ogle, Benjamin Poulter, Thomas A. M. Pugh, Rupert Seidl, Monica G. Turner, Maria Uriarte, Anthony P. Walker, and Chonggang Xu
Subjects: Earth Resources And Remote Sensing
Abstract: 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.
Published: 2020
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22. How to measure mast seeding?

Author: Michal Bogdziewicz, Rafael Calama, Benoit Courbaud, Josep M. Espelta, Andrew Hacket‐Pain, Valentin Journé, Georges Kunstler, Michael Steele, Tong Qiu, Magdalena Zywiec, James S. Clark, Polish National Agency for Academic Exchange, Bogdziewicz, Michal, Calama Sainz, Rafael Argimiro, Courbaud, Benoit, Espelta, Josep Maria, Hacket-Pain, Andrew, Journé, Valentin, Kunstler, Georges, Qiu, Tong, Zywiec, Magdalena, and Clark, James S.
Subjects: Masting breakdown, Seed production, Physiology, Phenotypic selection, Volatility, Plant Science, Reproductive variation
Abstract: 9 Pág., The periodic production of large seed crops, or masting, is a widespread phenomenon in perennial plants. This behavior can enhance the reproductive efficiency of plants, leading to increased fitness, and produce ripple effects on food webs. While variability from year to year is a defining characteristic of masting, the methods used to quantify this variability are highly debated. The commonly used coefficient of variation lacks the ability to account for the serial dependence in mast data and can be influenced by zeros, making it a less suitable choice for various applications based on individual-level observations, such as phenotypic selection, heritability, and climate change studies, which rely on individual-plant-level datasets that often contain numerous zeros. To address these limitations, we present three case studies and introduce volatility and periodicity, which account for the variance in the frequency domain by emphasizing the significance of long intervals in masting. By utilizing examples of Sorbus aucuparia, Pinus pinea, Quercus robur, Quercus pubescens, and Fagus sylvatica, we demonstrate how volatility captures the effects of variance at both high and low frequencies, even in the presence of zeros, leading to improved ecological interpretations of the results. The growing availability of long-term, individual-plant datasets promises significant advancements in the field, but requires appropriate tools for analysis, which the new metrics provide., The study was supported by the Polish National Agency for Academic Exchange Bekker program no. PPN/BEK/2020/1/00009/U/00001 and Polish National Science Centre grant no. 2019/35/D/NZ8/00050. RC's research is funded by National Project OLDPINE AGL-2017-83828-C2.1R.
Published: 2023
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23. The most abundant mammals on Earth

Author: James S. Clark
Subjects: Ecology, Evolution, Behavior and Systematics
Published: 2023
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24. Linking seed size and number to trait syndromes in trees

Author: Michal Bogdziewicz, Marie‐Claire Aravena Acuña, Robert Andrus, Davide Ascoli, Yves Bergeron, Daniel Brveiller, Thomas Boivin, Raul Bonal, Thomas Caignard, Maxime Cailleret, Rafael Calama, Sergio Donoso Calderon, J. Julio Camarero, Chia‐Hao Chang‐Yang, Jerome Chave, Francesco Chianucci, Natalie L. Cleavitt, Benoit Courbaud, Andrea Cutini, Thomas Curt, Adrian J. Das, Hendrik Davi, Nicolas Delpierre, Sylvain Delzon, Michael Dietze, Laurent Dormont, William Farfan‐Rios, Catherine A. Gehring, Gregory S. Gilbert, Georg Gratzer, Cathryn H. Greenberg, Arthur Guignabert, Qinfeng Guo, Andrew Hacket‐Pain, Arndt Hampe, Qingmin Han, Kazuhiko Hoshizaki, Ines Ibanez, Jill F. Johnstone, Valentin Journé, Thomas Kitzberger, Johannes M. H. Knops, Georges Kunstler, Richard Kobe, Jonathan G. A. Lageard, Jalene M. LaMontagne, Mateusz Ledwon, Theodor Leininger, Jean‐Marc Limousin, James A. Lutz, Diana Macias, Anders Marell, Eliot J. B. McIntire, Emily Moran, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Shoji Naoe, Mahoko Noguchi, Michio Oguro, Hiroko Kurokawa, Jean‐Marc Ourcival, Robert Parmenter, Ignacio M. Perez‐Ramos, Lukasz Piechnik, Tomasz Podgórski, John Poulsen, Tong Qiu, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, Pavel Šamonil, Jan Holik, C. Lane Scher, Harald Schmidt Van Marle, Barbara Seget, Mitsue Shibata, Shubhi Sharma, Miles Silman, Michael A. Steele, Jacob N. Straub, I‐Fang Sun, Samantha Sutton, Jennifer J. Swenson, Peter A. Thomas, Maria Uriarte, Giorgio Vacchiano, Thomas T. Veblen, Boyd Wright, S. Joseph Wright, Thomas G. Whitham, Kai Zhu, Jess K. Zimmerman, Magdalna Zywiec, James S. Clark, National Science Foundation (US), Belmont Forum, NASA Astrobiology Institute (US), Gordon and Betty Moore Foundation, National Science Centre (Poland), Polish National Agency for Academic Exchange, US Forest Service, Narodowe Centrum Nauki (Poland), Bogdziewicz, Michal, Aravena, Marie-Claire, Andrus, Robert, Ascoli, Davide, Bergeron, Yves, Bonal, Raul, Caignard, Thomas, Calama, Rafael, Calderon, Sergio Donoso, Camarero, J Julio, Chang-Yang, Chia-Hao, Cleavitt, Natalie L, Courbaud, Benoit, Curt, Thomas, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Dormont, Laurent, Farfan-Rios, William, Gehring, Catherine, Gilbert, Gregory S., Gratzer, Georg, Greenberg, Cathryn H., Guignabert, Arthur, Guo,Qinfeng, Hacket-Pain, Andrew, Hampe, Arndt, Han, Qingmin, Hoshizaki, Kazuhiko, Ibáñez, Inés, Johnstone, Jill F., Journé, Valentin, Kitzberger, Thomas, Knops, Johannes M. H., Kunstler, Georges, Kobe, Richard K., Lageard, Jonathan G. A., LaMontagne, Jalene M., Ledwon, Mateusz, Leininger, Theodor, Limousin, Jean-Marc, Lutz, James A., Moran, Emily, Motta, Renzo, Myers, Jonathan A., Nagel, Thomas A., Shoji, N., Michio Oguro, Mahoko Noguchi, Ourcival, Jean-Marc, Parmenter, Robert, Perez-Ramos, Ignacio M., Piechnik, Lukasz, Poulsen, John, Qiu, Tong, Redmond, Miranda D., Reid, Chantal D., Rodman, Kyle C., Scher, C. Lane, Seget, Barbara, Silman, Miles, Sun, I-Fang, Sutton, Samantha, Swenson, Jennifer J., Thomas, Peter A., Uriarte, Maria, Vacchiano, Giorgio, Veblen, Thomas T., Wright, Boyd, Wright, S. Joseph, Zhu, Kai, Zimmerman, Jess K., Zywiec, Magdalena, Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centro Austral de Investigaciones Científicas [Ushuaia] (CADIC), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), Ecosystèmes forestiers (UR EFNO), Università degli studi di Torino = University of Turin (UNITO), Université du Québec en Abitibi-Témiscamingue (UQAT), AgroParisTech, Ecologie des Forêts Méditerranéennes (URFM), 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), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Universidad de Chili / Departamento de Ciencias de la Computation, Instituto Pirenaico de Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC), National Kaohsiung Marine University [Taïwan] (NKMU), Evolution et Diversité Biologique (EDB), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Centre National de la Recherche Scientifique (CNRS), Department of Computer Science [Ithaca], Cornell University [New York], Centro di Viticoltura ed Enologia [CREA], Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA), California Sciences Institute, Ecologie Systématique et Evolution (ESE), Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Boston University [Boston] (BU), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), Saint Louis University (SLU), Northern Arizona University [Flagstaff], University of California (UC), Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), USDA Agricultural Research Service [Maricopa, AZ] (USDA), United States Department of Agriculture (USDA), Interactions Sol Plante Atmosphère (UMR ISPA), Ecole Nationale Supérieure des Sciences Agronomiques de Bordeaux-Aquitaine (Bordeaux Sciences Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of Liverpool, Forestry and Forest Products Research Institute (FFPRI), Akita University, University of Michigan [Dearborn], University of Michigan System, Nicholas School of the Environment, Duke University [Durham], Alabama Space Grant ConsortiumAIST16-0052AIST18-0063Belmont Forum1854976Polish National Agency for Academic Exchange (NAWA)PPN/BEK/2020/1/00009/U/00001National Science Centre, Poland2019/35/D/NZ8/00050National Science Foundation (NSF)DEB- 1754443, and ANR-18-MPGA-0004,FORBIC,Prévision du changement de la biodiversité(2018)
Subjects: Global and Planetary Change, Ecology, [SDV]Life Sciences [q-bio], fecundity, functional traits, leaf economics, life history strategies, size syndrome, tree recruitment, Life history strategie, Settore AGR/05 - Assestamento Forestale e Selvicoltura, Tree recruitmen, [SDE]Environmental Sciences, fecundity functional traits leaf economics life history strategies size syndrome, Ecology, Evolution, Behavior and Systematics
Abstract: 12 páginas.- 4 figuras.- referencias.- Additional supporting information can be found online in the Supporting Information section at the end of this article.- Full Access in https://onlinelibrary.wiley.com/doi/full/10.1111/geb.13652, Aim Our understanding of the mechanisms that maintain forest diversity under changing climate can benefit from knowledge about traits that are closely linked to fitness. We tested whether the link between traits and seed number and seed size is consistent with two hypotheses, termed the leaf economics spectrum and the plant size syndrome, or whether reproduction represents an independent dimension related to a seed size–seed number trade-off. Location Most of the data come from Europe, North and Central America and East Asia. A minority of the data come from South America, Africa and Australia. Time period 1960–2022. Major taxa studied Trees. Methods We gathered 12 million observations of the number of seeds produced in 784 tree species. We estimated the number of seeds produced by individual trees and scaled it up to the species level. Next, we used principal components analysis and generalized joint attribute modelling (GJAM) to map seed number and size on the tree traits spectrum. Results Incorporating seed size and number into trait analysis while controlling for environment and phylogeny with GJAM exposes relationships in trees that might otherwise remain hidden. Production of the large total biomass of seeds [product of seed number and seed size; hereafter, species seed productivity (SSP)] is associated with high leaf area, low foliar nitrogen, low specific leaf area (SLA) and dense wood. Production of high seed numbers is associated with small seeds produced by nutrient-demanding species with softwood, small leaves and high SLA. Trait covariation is consistent with opposing strategies: one fast-growing, early successional, with high dispersal, and the other slow-growing, stress-tolerant, that recruit in shaded conditions. Main conclusions Earth system models currently assume that reproductive allocation is indifferent among plant functional types. Easily measurable seed size is a strong predictor of the seed number and species seed productivity. The connection of SSP with the functional traits can form the first basis of improved fecundity prediction across global forests., The project has been funded by grants to J.S.C. from the National Science Foundation, most re-cently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052 and AIST18-0063) and the Programme d'Investissement d'Avenir under project FORBIC (18-MPGA-0004; Make Our Planet Great Again). Jerry Franklin's data remain acces-sible through NSF LTER DEB-1440409. Data from Hubbard Brook (New Hampshire) were funded through NSF-LTER. Puerto Rico data were funded by NSF grants, most recently DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF 727 LTREB 1754647. M.B. was supported by grant no. 2019/35/D/NZ8/00050 from the (Polish) National Science Centre and by Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. Research by the USDA Forest Service and the USGS was funded by these agencies. Any use of trade, firm or product names does not imply endorsement by the US Government. Any use of trade, firm, or product names is for descriptive purposes only and does not imply en -dorsement by the U.S. Government
Published: 2023
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25. Age-Related Changes in the Nasopharyngeal Microbiome Are Associated With Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) Infection and Symptoms Among Children, Adolescents, and Young Adults

Author: Jillian H Hurst, Alexander W McCumber, Jhoanna N Aquino, Javier Rodriguez, Sarah M Heston, Debra J Lugo, Alexandre T Rotta, Nicholas A Turner, Trevor S Pfeiffer, Thaddeus C Gurley, M Anthony Moody, Thomas N Denny, John F Rawls, James S Clark, Christopher W Woods, and Matthew S Kelly
Subjects: Microbiology (medical), Infectious Diseases
Abstract: Background Children are less susceptible to SARS-CoV-2 infection and typically have milder illness courses than adults, but the factors underlying these age-associated differences are not well understood. The upper respiratory microbiome undergoes substantial shifts during childhood and is increasingly recognized to influence host defense against respiratory pathogens. Thus, we sought to identify upper respiratory microbiome features associated with SARS-CoV-2 infection susceptibility and illness severity. Methods We collected clinical data and nasopharyngeal swabs from 285 children, adolescents, and young adults ( Results Nasopharyngeal microbiome composition varied with age (PERMANOVA, P Conclusions We identified interactive relationships between age and specific nasopharyngeal microbiome features that are associated with SARS-CoV-2 infection susceptibility and symptoms in children, adolescents, and young adults. Our data suggest that the upper respiratory microbiome may be a mechanism by which age influences SARS-CoV-2 susceptibility and illness severity.
Published: 2022
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26. Species traits and observer behaviors that bias data assimilation and how to accommodate them

Author: C. Lane Scher and James S. Clark
Subjects: Ecology
Published: 2023
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27. Foodwebs based on unreliable foundations: spatiotemporal masting merged with consumer movement, storage, and diet

Author: James S. Clark, Chase L. Nuñez, and Bradley Tomasek
Published: 2019
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28. Exploiting temporal coherence in forest dynamics simulation.

Author: Pankaj K. Agarwal, Thomas Mølhave, Hai Yu 0005, and James S. Clark
Published: 2011
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29. From Data Reverence to Data Relevance: Model-Mediated Wireless Sensing of the Physical Environment.

Author: Paul G. Flikkema, Pankaj K. Agarwal, James S. Clark, Carla Schlatter Ellis, Alan E. Gelfand, Kamesh Munagala, and Jun Yang 0001
Published: 2007
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30. Model-Driven Dynamic Control of Embedded Wireless Sensor Networks.

Author: Paul G. Flikkema, Pankaj K. Agarwal, James S. Clark, Carla Schlatter Ellis, Alan E. Gelfand, Kamesh Munagala, and Jun Yang 0001
Published: 2006
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31. 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
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32. Collagenase Clostridium Histolyticum-aaes for the Treatment of Cellulite in Women: Results From Two Phase 3 Randomized, Placebo-Controlled Trials

Author: Mitchel P. Goldman, Joel Schlessinger, David Hurley, John H Joseph, Saji Vijayan, Joely Kaufman-Janette, Lawrence S. Bass, V Leroy Young, James S. Clark, Matthew W. Davis, Michael H. Gold, Michael S. Kaminer, Bruce E. Katz, Kappa Peddy, Genzhou Liu, Michael Mclane, and Sabrina G. Fabi
Subjects: medicine.medical_specialty, Dermatology, Injections, Intralesional, Placebo, Gastroenterology, law.invention, Adult women, 030207 dermatology & venereal diseases, 03 medical and health sciences, 0302 clinical medicine, Collagenase clostridium histolyticum, Double-Blind Method, Randomized controlled trial, law, Internal medicine, medicine, Humans, Buttocks, Adverse effect, Cellulite, business.industry, General Medicine, Middle Aged, medicine.disease, Antibodies, Neutralizing, Injection Site Reaction, Clinical trial, Microbial Collagenase, Treatment Outcome, medicine.anatomical_structure, Patient Satisfaction, 030220 oncology & carcinogenesis, Original Article, Female, Surgery, business, medicine.drug
Abstract: BACKGROUND Fibrous septae play a role in contour alterations associated with cellulite. OBJECTIVE To assess collagenase clostridium histolyticum-aaes (CCH) for the treatment of cellulite. MATERIALS AND METHODS Two identically designed phase 3, double-blind, randomized studies (RELEASE-1 and RELEASE-2) were conducted. Adult women with moderate/severe cellulite (rating 3–4 on the Patient Reported Photonumeric Cellulite Severity Scale [PR-PCSS] and Clinician Reported PCSS [CR-PCSS]) on the buttocks received up to 3 treatment sessions of subcutaneous CCH 0.84 mg or placebo per treatment area. Composite response (≥2-level or ≥1-level improvement from baseline in both PR-PCSS and CR-PCSS) was determined at Day 71. RESULTS Eight hundred forty-three women received ≥1 injection (CCH vs placebo: RELEASE-1, n = 210 vs n = 213; RELEASE-2, n = 214 vs n = 206). Greater percentages of CCH-treated women were ≥2-level composite responders versus placebo in RELEASE-1 (7.6% vs 1.9%; p = .006) and RELEASE-2 (5.6% vs 0.5%; p = .002) and ≥1-level composite responders in RELEASE-1 (37.1% vs 17.8%; p < .001) and RELEASE-2 (41.6% vs 11.2%; p < .001). Most adverse events (AEs) in the CCH group were injection site related; few CCH-treated women discontinued because of an AE (≤4.3%). CONCLUSION Collagenase clostridium histolyticum-aaes significantly improved cellulite appearance and was generally well tolerated.
Published: 2021
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33. A scalable simulator for forest dynamics.

Author: Sathish Govindarajan, Mike Dietze, Pankaj K. Agarwal, and James S. Clark
Published: 2004
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34. Limits to reproduction and seed size-number tradeoffs that shape forest dominance and future recovery

Author: Tong Qiu, Robert Andrus, Marie-Claire Aravena, Davide Ascoli, Yves Bergeron, Roberta Berretti, Daniel Berveiller, Michal Bogdziewicz, Thomas Boivin, Raul Bonal, Don C. Bragg, Thomas Caignard, Rafael Calama, J. Julio Camarero, Chia-Hao Chang-Yang, Natalie L. Cleavitt, Benoit Courbaud, Francois Courbet, Thomas Curt, Adrian J. Das, Evangelia Daskalakou, Hendrik Davi, Nicolas Delpierre, Sylvain Delzon, Michael Dietze, Sergio Donoso Calderon, Laurent Dormont, Josep Espelta, Timothy J. Fahey, William Farfan-Rios, Catherine A. Gehring, Gregory S. Gilbert, Georg Gratzer, Cathryn H. Greenberg, Qinfeng Guo, Andrew Hacket-Pain, Arndt Hampe, Qingmin Han, Janneke Hille Ris Lambers, Kazuhiko Hoshizaki, Ines Ibanez, Jill F. Johnstone, Valentin Journé, Daisuke Kabeya, Christopher L. Kilner, Thomas Kitzberger, Johannes M. H. Knops, Richard K. Kobe, Georges Kunstler, Jonathan G. A. Lageard, Jalene M. LaMontagne, Mateusz Ledwon, Francois Lefevre, Theodor Leininger, Jean-Marc Limousin, James A. Lutz, Diana Macias, Eliot J. B. McIntire, Christopher M. Moore, Emily Moran, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Kyotaro Noguchi, Jean-Marc Ourcival, Robert Parmenter, Ian S. Pearse, Ignacio M. Perez-Ramos, Lukasz Piechnik, John Poulsen, Renata Poulton-Kamakura, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, Francisco Rodriguez-Sanchez, Javier D. Sanguinetti, C. Lane Scher, William H. Schlesinger, Harald Schmidt Van Marle, Barbara Seget, Shubhi Sharma, Miles Silman, Michael A. Steele, Nathan L. Stephenson, Jacob N. Straub, I-Fang Sun, Samantha Sutton, Jennifer J. Swenson, Margaret Swift, Peter A. Thomas, Maria Uriarte, Giorgio Vacchiano, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Andreas P. Wion, Boyd Wright, S. Joseph Wright, Kai Zhu, Jess K. Zimmerman, Roman Zlotin, Magdalena Zywiec, James S. Clark, National Science Foundation (US), Belmont Forum, NASA Specialized Center of Research and Training, Gordon and Betty Moore Foundation, W. Szafer Institute of Botany, Polish Academy of Sciences, National Science Centre (Poland), US Forest Service, Qiu, Tong, Andrus, Robert, Aravena, Marie-Claire, Ascoli, Davide, Bergeron, Yves, Berretti, Roberta 0000-0002-1944-8855], Berveiller, Daniel, Bogdziewicz, Michal, Bonal, Raul, Bragg, Don C, Caignard, Thomas, Calama, Rafael, Camarero, J Julio, Chang-Yang, Chia-Hao, Cleavitt, Natalie L, Courbaud, Benoit, Courbet, Francois, Curt, Thomas, Adrian, Das, Daskalakou, Evangelia, Davi, Hendrik, Delpierre, Nicolas, Delzon, Sylvain, Dietze, Michael, Calderon, Sergio Donoso, Dormont, Laurent, Espelta, Josep, Fahey, Timothy J, Farfan-Rios, William, Gehring, Catherine A, Gilbert, Gregory S, Gratzer, Georg, Greenberg, Cathryn H, Guo,Qinfeng, Hacket-Pain, Andrew, Hampe, Arndt, Han, Qingmin, Hoshizaki, Kazuhiko, Ibáñez, Inés, Johnstone, Jill F, Journé, Valentin, Kabeya, Daisuke, Kilner, Christopher L, Kitzberger, Thomas, Knops, Johannes M H, Kobe, Richard K, Kunstler, Georges, Lageard, Jonathan G A, LaMontagne, Jalene M, Ledwon, Mateusz, Lefèvre, François, Leininger, Theodor, Limousin, Jean-Marc, Lutz, James A, McIntire, Eliot J B, Moran, Emily, Motta, Renzo, Myers, Jonathan A, Nagel, Thomas A, Ourcival, Jean-Marc, Parmenter, Robert, Pearse, Ian S, Perez-Ramos, Ignacio M, Piechnik, Lukasz, Poulsen, John, Poulton-Kamakura, Renata, Redmond, Miranda D, Reid, Chantal D, Rodman, Kyle C, Rodriguez-Sanchez, Francisco, Schlesinger, William H, Seget, Barbara, Silman, Miles, Stephenson, Nathan L, Sun, I-Fang, Sutton, Samantha, Swenson, Jennifer J, Thomas, Peter A, Uriarte, Maria, Vacchiano, Giorgio, Veblen, Thomas T, Wion, Andreas P, Wright, Boyd, Wright, S Joseph, Zimmerman, Jess K, Zhu, Kai, Zywiec, Magdalena, Nicholas School of the Environment, Duke University [Durham], University of Colorado [Boulder], Universidad de Chile = University of Chile [Santiago] (UCHILE), Università degli studi di Torino = University of Turin (UNITO), Université du Québec en Abitibi-Témiscamingue (UQAT), Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), 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), USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), 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 Ecologìa = Pyrenean Institute of Ecology [Zaragoza] (IPE - CSIC), National Sun Yat-Sen University (NSYSU), Cornell University [New York], Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), United States Geological Survey (USGS), Boston University [Boston] (BU), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), CREAF - Centre for Ecological Research and Applied Forestries, Washington University in Saint Louis (WUSTL), Northern Arizona University [Flagstaff], University of California [Santa Cruz] (UC Santa Cruz), University of California (UC), Institute of Forest Ecology, Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), University of Liverpool, Forestry and Forest Products Research Institute (FFPRI), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Akita University, University of Michigan [Dearborn], University of Michigan System, University of Alaska [Anchorage], Universidad Nacional del Comahue [Neuquén] (UNCOMA), Xi'an Jiaotong University (Xjtu), Michigan State University [East Lansing], Michigan State University System, University of Manchester [Manchester], DePaul University [Chicago], Polish Academy of Sciences (PAN), The University of New Mexico [Albuquerque], Colby College, The project has been funded continuously since 1992 by NationalScience Foundation grants to J.S.C, most recently DEB-1754443, and by the BelmontForum (1854976), NASA (AIST16-0052, AIST18-0063), and the Programme d’Inves-tissement d’Avenir under project FORBIC (18-MPGA-0004)(Make Our Planet GreatAgain). Puerto Rico data were funded by NSF grants to M.U., most recently, DEB 0963447and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Groupwere funded by the Gordon and Betty Moore Foundation and NSF LTREB 1754647 toM.S. Additional funding to M.Z. came from the W.Szafer Institute of Botany of the PolishAcademy of Sciences and the Polish National Science Foundation (2019/33/B/NZ8/0134).M.B. was supported by the Polish National Science Centre grant no. 2019/35/D/NZ8/00050, and Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. J.M.L. was supported by NSF grant DEB 1745496. Jerry Franklin’sdata remain accessible through NSF LTER DEB-1440409. USDA Forest Service and USGSresearch was funded by those agencies, Qiu, Tong [0000-0003-4499-437X], Andrus, Robert [0000-0003-0968-8377], Aravena, Marie-Claire [0000-0002-4493-4396], Ascoli, Davide [0000-0002-0546-4467], Bergeron, Yves [0000-0003-3707-3687], Berretti, Roberta 0000-0002-1944-8855][, Berveiller, Daniel [0000-0001-7461-6420], Bogdziewicz, Michal [0000-0002-6777-9034], Bonal, Raul [0000-0002-6084-1771], Bragg, Don C [0000-0002-5207-8606], Caignard, Thomas [0000-0001-5009-4613], Calama, Rafael [0000-0002-2598-9594], Camarero, J Julio [0000-0003-2436-2922], Chang-Yang, Chia-Hao [0000-0003-3635-4946], Cleavitt, Natalie L [0000-0003-0425-2486], Courbaud, Benoit [0000-0002-3050-9559], Courbet, Francois [0000-0002-9438-6746], Curt, Thomas [0000-0002-2654-3009], Adrian, Das [0000-0002-3937-2616], Daskalakou, Evangelia [0000-0002-5190-1023], Davi, Hendrik [0000-0001-8828-3145], Delpierre, Nicolas [0000-0003-0906-9402], Delzon, Sylvain [0000-0003-3442-1711], Dietze, Michael [0000-0002-2324-2518], Calderon, Sergio Donoso [0000-0002-4599-4702], Dormont, Laurent [0000-0002-2021-0625], Espelta, Josep [0000-0002-0242-4988], Fahey, Timothy J [0000-0003-1283-1162], Farfan-Rios, William [0000-0002-3196-0317], Gehring, Catherine A [0000-0002-9393-9556], Gilbert, Gregory S [0000-0002-5195-9903], Gratzer, Georg [0000-0002-6355-6562], Greenberg, Cathryn H [0000-0002-2831-0989], Guo,Qinfeng [0000-0002-4375-4916], Hacket-Pain, Andrew [0000-0003-3676-1568], Hampe, Arndt [0000-0003-2551-9784], Han, Qingmin [0000-0001-6063-6068], Hoshizaki, Kazuhiko [0000-0001-7654-9129], Ibáñez, Inés[0000-0002-1054-0727], Johnstone, Jill F [0000-0001-6131-9339], Journé, Valentin [0000-0001-7324-7002], Kabeya, Daisuke [0000-0002-3420-199X], Kilner, Christopher L [0000-0001-8808-8868], Kitzberger, Thomas [0000-0002-9754-4121], Knops, Johannes M H [0000-0002-9647-9209], Kobe, Richard K [0000-0002-0943-9613], Kunstler, Georges [0000-0002-2544-1940], Lageard, Jonathan G A [0000-0001-8971-0444], LaMontagne, Jalene M [0000-0001-7713-8591], Ledwon, Mateusz [0000-0003-3017-6376], Lefèvre, François [0000-0003-2242-7251], Leininger, Theodor [0000-0002-4939-3656], Limousin, Jean-Marc [0000-0002-2734-2495], Lutz, James A [0000-0002-2560-0710], McIntire, Eliot J B [0000-0002-6914-8316], Moran, Emily [0000-0003-4624-1910], Motta, Renzo [0000-0002-1631-3840], Myers, Jonathan A [0000-0002-2058-8468], Nagel, Thomas A [0000-0002-4207-9218], Ourcival, Jean-Marc [0000-0002-3557-3496], Parmenter, Robert [0000-0002-2099-6824], Pearse, Ian S [0000-0001-7098-0495], Perez-Ramos, Ignacio M [0000-0003-2332-7818], Piechnik, Lukasz [0000-0002-3958-7393], Poulsen, John [0000-0002-1532-9808], Poulton-Kamakura, Renata [0000-0002-2516-8702], Redmond, Miranda D [0000-0002-4657-7943], Reid, Chantal D [0000-0002-3811-4076], Rodman, Kyle C [0000-0001-9538-8412], Rodriguez-Sanchez, Francisco [0000-0002-7981-1599], Schlesinger, William H [0000-0002-1391-0885], Seget, Barbara [0000-0002-7872-926X], Silman, Miles [0000-0003-4152-2844], Stephenson, Nathan L [0000-0003-0208-7229], Sun, I-Fang [0000-0001-9749-8324], Sutton, Samantha [0000-0002-1491-7763], Swenson, Jennifer J [0000-0002-2069-667X], Thomas, Peter A [0000-0003-3115-3301], Uriarte, Maria [0000-0002-0484-0758], Vacchiano, Giorgio [0000-0001-8100-0659], Veblen, Thomas T [0000-0002-3037-640X], Wion, Andreas P [0000-0002-0701-2843], Wright, Boyd [0000-0002-6322-4904], Wright, S Joseph [0000-0003-4260-5676], Zimmerman, Jess K [0000-0002-8179-0731], Zhu, Kai [0000-0003-1587-3317], and Zywiec, Magdalena [0000-0002-5992-4051]
Subjects: Physiology, [SDV]Life Sciences [q-bio], General Physics and Astronomy, Forests, Q1, General Biochemistry, Genetics and Molecular Biology, Trees, reproductive potential, Plant seed, Forest, pridelava semen, Plant ecology, SB, SD, Multidisciplinary, Reproduction, Contraception/Reproduction, Botánica, production control, food and beverages, General Chemistry, Biodiversity, Ecología, Fertility, natural disasters, nadzor pridelave, seed production, Seeds, reprodukcijski potencial, Forest ecology, udc:630*23, ujme, Tree
Abstract: 12 Pág., The relationships that control seed production in trees are fundamental to understanding the evolution of forest species and their capacity to recover from increasing losses to drought, fire, and harvest. A synthesis of fecundity data from 714 species worldwide allowed us to examine hypotheses that are central to quantifying reproduction, a foundation for assessing fitness in forest trees. Four major findings emerged. First, seed production is not constrained by a strict trade-off between seed size and numbers. Instead, seed numbers vary over ten orders of magnitude, with species that invest in large seeds producing more seeds than expected from the 1:1 trade-off. Second, gymnosperms have lower seed production than angiosperms, potentially due to their extra investments in protective woody cones. Third, nutrient-demanding species, indicated by high foliar phosphorus concentrations, have low seed production. Finally, sensitivity of individual species to soil fertility varies widely, limiting the response of community seed production to fertility gradients. In combination, these findings can inform models of forest response that need to incorporate reproductive potential., The project has been funded continuously since 1992 by National Science Foundation grants to J.S.C, most recently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052, AIST18-0063), and the Programme d’Investissement d’Avenir under project FORBIC (18-MPGA-0004)(Make Our Planet Great Again). Puerto Rico data were funded by NSF grants to M.U., most recently, DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF LTREB 1754647 to M.S. Additional funding to M.Z. came from the W.Szafer Institute of Botany of the Polish Academy of Sciences and the Polish National Science Foundation (2019/33/B/NZ8/0134). M.B. was supported by the Polish National Science Centre grant no. 2019/35/D/NZ8/00050, and Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. J.M.L. was supported by NSF grant DEB 1745496. Jerry Franklin’s data remain accessible through NSF LTER DEB-1440409. USDA Forest Service and USGS research was funded by those agencies.
Published: 2022
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35. Globally, tree fecundity exceeds productivity gradients

Author: Valentin Journé, Robert Andrus, Marie‐Claire Aravena, Davide Ascoli, Roberta Berretti, Daniel Berveiller, Michal Bogdziewicz, Thomas Boivin, Raul Bonal, Thomas Caignard, Rafael Calama, Jesús Julio Camarero, Chia‐Hao Chang‐Yang, Benoit Courbaud, Francois Courbet, Thomas Curt, Adrian J. Das, Evangelia Daskalakou, Hendrik Davi, Nicolas Delpierre, Sylvain Delzon, Michael Dietze, Sergio Donoso Calderon, Laurent Dormont, Josep Maria Espelta, Timothy J. Fahey, William Farfan‐Rios, Catherine A. Gehring, Gregory S. Gilbert, Georg Gratzer, Cathryn H. Greenberg, Qinfeng Guo, Andrew Hacket‐Pain, Arndt Hampe, Qingmin Han, Janneke Hille Ris Lambers, Kazuhiko Hoshizaki, Ines Ibanez, Jill F. Johnstone, Daisuke Kabeya, Roland Kays, Thomas Kitzberger, Johannes M. H. Knops, Richard K. Kobe, Georges Kunstler, Jonathan G. A. Lageard, Jalene M. LaMontagne, Theodor Leininger, Jean‐Marc Limousin, James A. Lutz, Diana Macias, Eliot J. B. McIntire, Christopher M. Moore, Emily Moran, Renzo Motta, Jonathan A. Myers, Thomas A. Nagel, Kyotaro Noguchi, Jean‐Marc Ourcival, Robert Parmenter, Ian S. Pearse, Ignacio M. Perez‐Ramos, Lukasz Piechnik, John Poulsen, Renata Poulton‐Kamakura, Tong Qiu, Miranda D. Redmond, Chantal D. Reid, Kyle C. Rodman, Francisco Rodriguez‐Sanchez, Javier D. Sanguinetti, C. Lane Scher, Harald Schmidt Van Marle, Barbara Seget, Shubhi Sharma, Miles Silman, Michael A. Steele, Nathan L. Stephenson, Jacob N. Straub, Jennifer J. Swenson, Margaret Swift, Peter A. Thomas, Maria Uriarte, Giorgio Vacchiano, Thomas T. Veblen, Amy V. Whipple, Thomas G. Whitham, Boyd Wright, S. Joseph Wright, Kai Zhu, Jess K. Zimmerman, Roman Zlotin, Magdalena Zywiec, James S. Clark, National Science Foundation (US), NASA Astrobiology Institute (US), Belmont Forum, Gordon and Betty Moore Foundation, Polish National Agency for Academic Exchange, Journé, Valentin [0000-0001-7324-7002], Camarero, Jesús Julio [0000-0003-2436-2922], Dietze, Michael [0000-0002-2324-2518], Espelta, Josep Maria [0000-0002-0242-4988], Kays, Roland [0000-0002-2947-6665], Hampe, Arndt [0000-0003-2551-9784], Kunstler, Georges [0000-0002-2544-1940], Ibáñez, Inés [0000-0002-1054-0727], Pérez-Ramos, Ignacio Manuel [0000-0003-2332-7818], Scher, C. Lane [0000-0003-3689-5769], Uriarte, María [0000-0002-0484-0758], Wright, S. Joseph [0000-0003-4260-5676], Zhu, Kai [0000-0003-1587-3317], Zywiec, Magdalena [0000-0002-5992-4051], Clark, James S. [0000-0002-5677-9733], Ecologie des Forêts Méditerranéennes (URFM), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Laboratoire des EcoSystèmes et des Sociétés en Montagne (UR LESSEM), University of Colorado [Boulder], Universidad de Chile = University of Chile [Santiago] (UCHILE), Università degli studi di Torino = University of Turin (UNITO), Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Adam Mickiewicz University in Poznań (UAM), 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), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), National Sun Yat-Sen University (NSYSU), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Western Ecological Research Center, Hellenic Agricultural Organization Demeter (HAO Demeter), Department of Earth and Environment [Boston], Boston University [Boston] (BU), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM), CREAF - Centre for Ecological Research and Applied Forestries, Cornell University [New York], Washington University in Saint Louis (WUSTL), Northern Arizona University [Flagstaff], University of California (UC), USDA Forest Service Rocky Mountain Forest and Range Experiment Station, United States Department of Agriculture (USDA), University of Liverpool, Forestry and Forest Products Research Institute (FFPRI), Departement Erdwissenschaften [ETH Zürich] (D-ERDW), Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Akita University, University of Michigan [Ann Arbor], University of Michigan System, University of Alaska [Fairbanks] (UAF), North Carolina State University [Raleigh] (NC State), University of North Carolina System (UNC), Universidad Nacional del Comahue [Neuquén] (UNCOMA), Xi'an Jiaotong-Liverpool University [Suzhou], Michigan State University [East Lansing], Michigan State University System, Manchester Metropolitan University (MMU), DePaul University [Chicago], USDA Forest Service, Southern Research Station, Utah State University (USU), The University of New Mexico [Albuquerque], Pacific Forestry Centre, Natural Resources Canada (NRCan), Colby College, University of California [Merced] (UC Merced), University of Ljubljana, National Park Service, United States Geological Survey (USGS), Instituto de Recursos Naturales y Agrobiología de Sevilla (IRNAS), Polish Academy of Sciences (PAN), Duke University [Durham], Colorado State University [Fort Collins] (CSU), University of Wisconsin-Madison, Universidad de Sevilla / University of Sevilla, Universidad de Santiago de Chile [Santiago] (USACH), Wake Forest University, Wilkes University, Partenaires INRAE, State University of New York (SUNY), Keele University [Keele], Columbia University [New York], Università degli Studi di Milano = University of Milan (UNIMI), University of New England (UNE), Smithsonian Tropical Research Institute, University of Puerto Rico (UPR), Indiana University [Bloomington], Indiana University System, National Science Foundation (NSF)DEB-1754443National Aeronautics & Space Administration (NASA)AIST16-0052AIST18-0063Belmont Forum1854976, ANR-18-MPGA-0004,FORBIC,Prévision du changement de la biodiversité(2018), Journé, Valentin, Camarero, Jesús Julio, Dietze, Michael, Espelta, Josep Maria, Kays, Roland, Hampe, Arndt, Kunstler, Georges, Ibáñez, Inés, Pérez-Ramos, Ignacio Manuel, Scher, C. Lane, Uriarte, María, Wright, S. Joseph, Zhu, Kai, Zywiec, Magdalena, Clark, James S., and McGlinn, Daniel
Subjects: S1, Climate, Forests, Regenerative Medicine, Forest regeneration, Trees, Seed consumption, Species interactions, climate, Ecology, Evolution, Behavior and Systematics, SD, tree fecundity, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Evolutionary Biology, species interactions, Ecology, competition, forest regeneration, seed consumption, Biodiversity, Fertility, Seeds, Competition, Ecological Applications, Tree fecundity
Abstract: 12 páginas.- 5 figuras.- 67 referencias.- Additional supporting information may be found in the online version of the article at the publisher’s website .- The peer review history for this article is available at https://publons.com/publon/10.1111/ele.14012 .- All data and code supporting our results are archived on the Zenodo Repository at the following link: https://doi.org/10.5281/zenodo.6381799, Lack of tree fecundity data across climatic gradients precludes the analysis of how seed supply contributes to global variation in forest regeneration and biotic interactions responsible for biodiversity. A global synthesis of raw seedproduction data shows a 250-fold increase in seed abundance from cold-dry to warm-wet climates, driven primarily by a 100-fold increase in seed production for a given tree size. The modest (threefold) increase in forest productivity across the same climate gradient cannot explain the magnitudes of these trends. The increase in seeds per tree can arise from adaptive evolution driven by intense species interactions or from the direct effects of a warm, moist climate on tree fecundity. Either way, the massive differences in seed supply ramify through food webs potentially explaining a disproportionate role for species interactions in the wet tropics., The project has been funded by grants to JSC from the National Science Foundation, most recently DEB-1754443, and by the Belmont Forum (1854976), NASA (AIST16-0052, AIST18-0063) and the Programme d’Investissement d’Avenir under project FORBIC (18-MPGA-0004) (Make Our Planet Great Again). Jerry Franklin’s data remain accessible through NSF LTER DEB-1440409. Puerto Rico data were funded by NSF grants, most recently, DEB 0963447 and LTREB 11222325. Data from the Andes Biodiversity and Ecosystem Research Group were funded by the Gordon and Betty Moore Foundation and NSF LTREB 1754647. MB was supported by grant no. 2019/35/D/NZ8/00050 from the (Polish) National Science Centre, and Polish National Agency for Academic Exchange Bekker programme PPN/BEK/2020/1/00009/U/00001. Research by the USDA Forest Service and the USGS was funded by these agencies. Any use of trade, firm or product names does not imply endorsement by the US Government.
Published: 2022
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36. A scalable algorithm for dispersing population.

Author: Sathish Govindarajan, Michael C. Dietze, Pankaj K. Agarwal, and James S. Clark
Published: 2007
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37. 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
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38. 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
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39. 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
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40. Carolina critters: a collection of camera‐trap data from wildlife surveys across North Carolina

Author: Casey G. Dukes, James S. Clark, Jacob S. Hill, Liz Kalies, Monica Lasky, Arielle W. Parsons, Staci Clark, George R. Hess, Roland Kays, Jonathan Shaw, Jessie Matthews, Colleen Olfenbuttel, Stephanie G. Schuttler, Jordan Siminitz, Ron Sutherland, and George Davis
Subjects: Mammals, education.field_of_study, Ecology, Species distribution, Population, Wildlife, Biodiversity, Animals, Wild, Geography, Habitat, North Carolina, Animals, Camera trap, Ecosystem, education, Ecology, Evolution, Behavior and Systematics, Global biodiversity
Abstract: Camera trap surveys are useful to understand animal species population trends, distribution, habitat preference, behavior, community dynamics, periods of activity, and species associations with environmental conditions. This information is ecologically important, because many species play important roles in local ecosystems as predators, herbivores, seed dispersers, and disease vectors. Additionally, many of the larger wildlife species detected by camera traps are economically important through hunting, trapping, or ecotourism. Here we present a data set of camera-trap surveys from 6,043 locations across all 100 counties of North Carolina, USA from 2009 to 2019. These data come from 26 survey initiatives and contain 215,108 records of 36 mammal species and three species of terrestrial birds. This large data set increases the geographical distribution data for these 39 mammal and bird species by >500% over what is available for North Carolina in the Global Biodiversity Information Facility (GBIF). These data can be used to conduct inquiries about species, populations, communities, or ecosystems, and to produce useful information on wildlife behavior, distribution, and interactions. There are no copyright restrictions. Please cite this paper when using the data for publication.
Published: 2021
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41. 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
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42. Improving the Modeling of Disease Data from the Government Surveillance System: A Case Study on Malaria in the Brazilian Amazon.

Author: Denis Valle and James S. Clark
Published: 2013
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43. Computation and Uncertainty in Ecological Forecasting.

Author: James S. Clark, Pankaj K. Agarwal, and Michael Lavin
Published: 2002

44. Models for Ecological Data

Author: James S. Clark
Published: 2020
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45. 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
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46. Where Resource‐Acquisitive Species Are Located: The Role of Habitat Heterogeneity

Author: James S. Clark and Bijan Seyednasrollah
Subjects: Geophysics, Resource (biology), Ecology, General Earth and Planetary Sciences, Environmental science, Foliar chemistry, Spatial heterogeneity
Published: 2020
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47. Contributors

Author: Taeryon Choi, James S. Clark, Erika Cunningham, Maria DeYoreo, J.-L. Dortet-Bernadet, Y. Fan, Michele Guindani, Maria Kalli, Nadja Klein, Thomas Kneib, Jeong Hwan Kook, Athanasios Kottas, Peter J. Lenk, Yadong Lu, Andrew A. Manderson, Giampiero Marra, Yinsen Miao, Kevin Murray, John T. Ormerod, Rosalba Radice, T. Rodrigues, Surya T. Tokdar, Berwin A. Turlach, and Marina Vannucci
Published: 2020
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48. A vignette on model-based quantile regression: analysing excess zero response

Author: Erika Cunningham, Surya T. Tokdar, and James S. Clark
Subjects: R package, Vignette, Econometrics, Tobit model, Regression analysis, Censoring (statistics), Mathematics, Zero (linguistics), Quantile regression, Quantile
Abstract: Quantile regression is widely seen as an ideal tool to understand complex predictor-response relations. Its biggest promise rests in its ability to quantify whether and how predictor effects vary across response quantile levels. But this promise has not been fully met due to a lack of statistical estimation methods that perform a rigorous, joint analysis of all quantile levels. This gap has been recently bridged by Yang and Tokdar [18] . Here we demonstrate how their joint quantile regression method, as encoded in the R package qrjoint , offers a comprehensive and model-based regression analysis framework. This chapter is an R vignette where we illustrate how to fit models, interpret coefficients, improve and compare models and obtain predictions under this framework. Our case study is an application to ecology where we analyse how the abundance of red maple trees depends on topographical and geographical features of the location. A complete absence of the species contributes excess zeros in the response data. We treat such excess zeros as left censoring in the spirit of a Tobit regression analysis. By utilising the generative nature of the joint quantile regression model, we not only adjust for censoring but also treat it as an object of independent scientific interest.
Published: 2020
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49. 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
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50. 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
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