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1. Defining model complexity: An ecological perspective

Author

Charlotte A. Malmborg, Alyssa M. Willson, L. M. Bradley, Meghan A. Beatty, David H. Klinges, Gerbrand Koren, Abigail S. L. Lewis, Kayode Oshinubi, and Whitney M. Woelmer

Subjects
ecology, evaluation, forecasting, model development, modelling, prediction, Meteorology. Climatology, QC851-999
Abstract

Abstract Models have become a key component of scientific hypothesis testing and climate and sustainability planning, as enabled by increased data availability and computing power. As a result, understanding how the perceived ‘complexity’ of a model corresponds to its accuracy and predictive power has become a prevalent research topic. However, a wide variety of definitions of model complexity have been proposed and used, leading to an imprecise understanding of what model complexity is and its consequences across research studies, study systems, and disciplines. Here, we propose a more explicit definition of model complexity, incorporating four facets—model class, model inputs, model parameters, and computational complexity—which are modulated by the complexity of the real‐world process being modelled. We illustrate these facets with several examples drawn from ecological literature. Overall, we argue that precise terminology and metrics of model complexity (e.g., number of parameters, number of inputs) may be necessary to characterize the emergent outcomes of complexity, including model comparison, model performance, model transferability and decision support.

Published
2024
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2. Winters are changing: snow effects on Arctic and alpine tundra ecosystems1

Author

Christian Rixen, Toke Thomas Høye, Petr Macek, Rien Aerts, Juha M. Alatalo, Jill T. Anderson, Pieter A. Arnold, Isabel C Barrio, Jarle W. Bjerke, Mats P. Björkman, Daan Blok, Gesche Blume-Werry, Julia Boike, Stef Bokhorst, Michele Carbognani, Casper T. Christiansen, Peter Convey, Elisabeth J. Cooper, J. Hans C. Cornelissen, Stephen J. Coulson, Ellen Dorrepaal, Bo Elberling, Sarah C. Elmendorf, Cassandra Elphinstone, T’ai G.W. Forte, Esther R. Frei, Sonya R. Geange, Friederike Gehrmann, Casey Gibson, Paul Grogan, Aud Helen Halbritter, John Harte, Gregory H.R. Henry, David W. Inouye, Rebecca E. Irwin, Gus Jespersen, Ingibjörg Svala Jónsdóttir, Ji Young Jung, David H. Klinges, Gaku Kudo, Juho Lämsä, Hanna Lee, Jonas J. Lembrechts, Signe Lett, Joshua Scott Lynn, Hjalte M.R. Mann, Mikhail Mastepanov, Jennifer Morse, Isla H. Myers-Smith, Johan Olofsson, Riku Paavola, Alessandro Petraglia, Gareth K. Phoenix, Philipp Semenchuk, Matthias B. Siewert, Rachel Slatyer, Marko J. Spasojevic, Katharine Suding, Patrick Sullivan, Kimberly L. Thompson, Maria Väisänen, Vigdis Vandvik, Susanna Venn, Josefine Walz, Robert Way, Jeffrey M. Welker, Sonja Wipf, and Shengwei Zong

Subjects
review, tundra, ground temperatures, snow experiments, ITEX, synthèse, Environmental sciences, GE1-350, Environmental engineering, TA170-171
Abstract

Snow is an important driver of ecosystem processes in cold biomes. Snow accumulation determines ground temperature, light conditions, and moisture availability during winter. It also affects the growing season’s start and end, and plant access to moisture and nutrients. Here, we review the current knowledge of the snow cover’s role for vegetation, plant-animal interactions, permafrost conditions, microbial processes, and biogeochemical cycling. We also compare studies of natural snow gradients with snow experimental manipulation studies to assess time scale difference of these approaches. The number of tundra snow studies has increased considerably in recent years, yet we still lack a comprehensive overview of how altered snow conditions will affect these ecosystems. Specifically, we found a mismatch in the timing of snowmelt when comparing studies of natural snow gradients with snow manipulations. We found that snowmelt timing achieved by snow addition and snow removal manipulations (average 7.9 days advance and 5.5 days delay, respectively) were substantially lower than the temporal variation over natural spatial gradients within a given year (mean range 56 days) or among years (mean range 32 days). Differences between snow study approaches need to be accounted for when projecting snow dynamics and their impact on ecosystems in future climates.

Published
2022
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3. Ten simple rules for training yourself in an emerging field

Author

Whitney M. Woelmer, L. M. Bradley, Lisa T. Haber, David H. Klinges, Abigail S. L. Lewis, Elizabeth J. Mohr, Christa L. Torrens, Kathryn I. Wheeler, and Alyssa M. Willson

Subjects
Biology (General), QH301-705.5
Abstract

The opportunity to participate in and contribute to emerging fields is increasingly prevalent in science. However, simply thinking about stepping outside of your academic silo can leave many students reeling from the uncertainty. Here, we describe 10 simple rules to successfully train yourself in an emerging field, based on our experience as students in the emerging field of ecological forecasting. Our advice begins with setting and revisiting specific goals to achieve your academic and career objectives and includes several useful rules for engaging with and contributing to an emerging field.

Published
2021

4. Vertical stratification patterns of tropical forest vertebrates: a meta‐analysis

Author

Edmund W. Basham, J. Alex Baecher, David H. Klinges, and Brett R. Scheffers

Subjects
General Agricultural and Biological Sciences, General Biochemistry, Genetics and Molecular Biology
Abstract

Tropical forests harbour the highest levels of terrestrial biodiversity and represent some of the most complex ecosystems on Earth, with a significant portion of this diversity above ground. Although the vertical dimension is a central aspect of the ecology of forest communities, there is little consensus as to prominence, evenness, and consistency of community-level stratification from ground to canopy. Here, we gather the results of 62 studies across the tropics to synthesise and assess broad patterns of vertical stratification of abundance and richness in vertebrates, the best studied taxonomic group for which results have not been collated previously. Our review of the literature yielded sufficient data for bats, small mammals, birds and amphibians. We show that variation in the stratification of abundance and richness exists within and among all taxa considered. Bat richness stratification was variable among studies, although bat abundance was weighted towards the canopy. Both bird richness and abundance stratification were variable, with no overriding pattern. On the contrary, both amphibians and small mammals showed consistent patterns of decline in abundance and richness towards the canopy. We descriptively characterise research trends in drivers of stratification cited or investigated within studies, finding local habitat structure and food distribution/foraging to be the most commonly attributed drivers. Further, we analyse the influence of macroecological variables on stratification patterns, finding latitude and elevation to be key predictors of bird stratification in particular. Prominent differences among taxa are likely due to taxon-specific interactions with local drivers such as vertical habitat structure, food distribution, and vertical climate gradients, which may vary considerably across macroecological gradients such as elevation and biogeographic realm. Our study showcases the complexity with which animal communities organise within tropical forest ecosystems, while demonstrating the canopy as a critical niche space for tropical vertebrates, thereby highlighting the inherent vulnerability of tropical vertebrate communities to forest loss and canopy disturbance. We recognise that analyses were constrained due to variation in study designs and methods which produced a variety of abundance and richness metrics recorded across different arrangements of vertical strata. We therefore suggest the application of best practices for data reporting and highlight the significant effort required to fill research gaps in terms of under-sampled regions, taxa, and environments.

Published
2022
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6. Biogeosciences

Author

Katherine E. O. Todd-Brown, Rose Z. Abramoff, Jeffrey Beem-Miller, Hava K. Blair, Stevan Earl, Kristen J. Frederick, Daniel R. Fuka, Mario Guevara Santamaria, Jennifer W. Harden, Katherine Heckman, Lillian J. Heran, James R. Holmquist, Alison M. Hoyt, David H. Klinges, David S. LeBauer, Avni Malhotra, Shelby C. McClelland, Lucas E. Nave, Katherine S. Rocci, Sean M. Schaeffer, Shane Stoner, Natasja van Gestel, Sophie F. von Fromm, Marisa L. Younger, Laboratoire des Sciences du Climat et de l'Environnement [Gif-sur-Yvette] (LSCE), Université de Versailles Saint-Quentin-en-Yvelines (UVSQ)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Institut national des sciences de l'Univers (INSU - CNRS)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), European Project: 834169,H2020,H2020-MSCA-IF-2018,FlexMod(2020), University of Zurich, and Todd-Brown, Katherine E O

Subjects
[SDU.OCEAN]Sciences of the Universe [physics]/Ocean, Atmosphere, Ecology, Evolution, communication, literature review, future prospect, 1904 Earth-Surface Processes, Earth, data set, 10122 Institute of Geography, 1105 Ecology, Evolution, Behavior and Systematics, Surface Processes, Behavior and Systematics, soil survey, 910 Geography & travel, soil analysis, soil management, [SDU.ENVI]Sciences of the Universe [physics]/Continental interfaces, environment, Ecology, Evolution, Behavior and Systematics, database, Earth-Surface Processes
Abstract

In the age of big data, soil data are more available and richer than ever, but-outside of a few large soil survey resources-they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century., Biogeosciences, 19 (14), ISSN:1726-4170

Published
2022
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7. Maintaining forest cover to enhance temperature buffering under future climate change

Author

Jonathan Lenoir, Kristoffer Hylander, Koenraad Van Meerbeek, Sanne Govaert, Miska Luoto, Florian Zellweger, Arndt Hampe, Karen De Pauw, Ditte M. Christiansen, Jérôme Ogée, David H. Klinges, Pieter Vangansbeke, Lander Baeten, Pieter Sanczuk, Pieter De Frenne, Stef Haesen, Emiel De Lombaerde, Camille Meeussen, Irena A. Koelemeijer, Thomas Vanneste, Brett R. Scheffers, Leen Depauw, Juha Aalto, Jonas J. Lembrechts, Francisco Rodríguez-Sánchez, and Caroline Greiser

Subjects
0106 biological sciences, DYNAMICS, Environmental Engineering, Temperature offsets, Climate Change, Microclimate, Biodiversity, Climate change, Forests, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, 03 medical and health sciences, Future climate projections, Temperate climate, Environmental Chemistry, Hindcast, MICROCLIMATE, Biology, Waste Management and Disposal, Ecosystem, 030304 developmental biology, 0303 health sciences, Temperature, Forest microclimate, Canopy, Understory, 15. Life on land, Pollution, Chemistry, PLANT-RESPONSES, Boreal, Habitat, 13. Climate action, Earth and Environmental Sciences, Environmental science, Paired sensor data
Abstract

Forest canopies buffer macroclimatic temperature fluctuations. However, we do not know if and how the capacity of canopies to buffer understorey temperature will change with accelerating climate change. Here we map the difference (offset) between temperatures inside and outside forests in the recent past and project these into the future in boreal, temperate and tropical forests. Using linear mixed-effect models, we combined a global database of 714 paired time series of temperatures (mean, minimum and maximum) measured inside forests vs. in nearby open habitats with maps of macroclimate, topography and forest cover to hindcast past (1970–2000) and to project future (2060–2080) temperature differences between free-air temperatures and sub-canopy microclimates. For all tested future climate scenarios, we project that the difference between maximum temperatures inside and outside forests across the globe will increase (i.e. result in stronger cooling in forests), on average during 2060–2080, by 0.27 ± 0.16 °C (RCP2.6) and 0.60 ± 0.14 °C (RCP8.5) due to macroclimate changes. This suggests that extremely hot temperatures under forest canopies will, on average, warm less than outside forests as macroclimate warms. This knowledge is of utmost importance as it suggests that forest microclimates will warm at a slower rate than non-forested areas, assuming that forest cover is maintained. Species adapted to colder growing conditions may thus find shelter and survive longer than anticipated at a given forest site. This highlights the potential role of forests as a whole as microrefugia for biodiversity under future climate change.

Published
2022
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8. Reviews and syntheses: The promise of big soil data, moving current practices towards future potential

Author

Katherine E. O. Todd-Brown, Rose Z. Abramoff, Jeffrey Beem-Miller, Hava K. Blair, Stevan Earl, Kristen J. Frederick, Daniel R. Fuka, Mario Guevara Santamaria, Jennifer W. Harden, Katherine Heckman, Lillian J. Heran, James R. Holmquist, Allison M. Hoyt, David H. Klinges, David S. LeBauer, Avni Malhotra, Shelby C. McClelland, Lucas E. Nave, Katherine S. Rocci, Sean M. Schaeffer, Shane Stoner, Natasja van Gestel, Sophie F. von Fromm, and Marisa L. Younger

Subjects
GeneralLiterature_MISCELLANEOUS
Abstract

In the age of big data, soil data are more available than ever, but -outside of a few large soil survey resources- remain largely unusable for informing soil management and understanding Earth system processes outside of the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for global relevance. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: data discovery, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century., Biogeosciences Discussions, ISSN:1810-6277, ISSN:1810-6285

Published
2021
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9. Ten simple rules for training yourself in an emerging field

Author

Christa L. Torrens, Lisa T. Haber, Kathryn I. Wheeler, L. M. Bradley, Abigail S. L. Lewis, David H. Klinges, Whitney M. Woelmer, Alyssa M. Willson, and Elizabeth J. Mohr

Subjects
Science and Technology Workforce, Computer science, Economics, Social Sciences, Careers in Research, 0302 clinical medicine, Learning and Memory, Mathematical and Statistical Techniques, Open Science, Sociology, Psychology, Biology (General), Simple (philosophy), 0303 health sciences, Textbooks, Career Choice, Careers, Ecology, Publications, Statistics, Professions, Editorial, Computational Theory and Mathematics, Community Ecology, Modeling and Simulation, Physical Sciences, Engineering ethics, Workshops, Goals, Human learning, Employment, Science Policy, QH301-705.5, Ecological forecasting, Theoretical ecology, Research and Analysis Methods, Training (civil), Education, 03 medical and health sciences, Cellular and Molecular Neuroscience, Human Learning, Genetics, Humans, Learning, Occupations, Statistical Methods, Students, Molecular Biology, Ecology, Evolution, Behavior and Systematics, 030304 developmental biology, Field (Bourdieu), Ecology and Environmental Sciences, Cognitive Psychology, Biology and Life Sciences, Labor Economics, People and Places, Cognitive Science, Scientists, Population Groupings, 030217 neurology & neurosurgery, Mathematics, Forecasting, Neuroscience
Abstract

The opportunity to participate in and contribute to emerging fields is increasingly prevalent in science. However, simply thinking about stepping outside of your academic silo can leave many students reeling from the uncertainty. Here, we describe 10 simple rules to successfully train yourself in an emerging field, based on our experience as students in the emerging field of ecological forecasting. Our advice begins with setting and revisiting specific goals to achieve your academic and career objectives and includes several useful rules for engaging with and contributing to an emerging field.

Published
2021

10. Microgeography, Not Just Latitude, Drives Climate Overlap on Mountains from Tropical to Polar Ecosystems

Author

Brett R. Scheffers and David H. Klinges

Subjects
0106 biological sciences, Tree canopy, Geography, Polar ecosystems, 010604 marine biology & hydrobiology, Biogeography, Altitude, Climate, Microclimate, Elevation, Temperature, Tropics, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Latitude, Environmental science, Biological dispersal, Ecology, Evolution, Behavior and Systematics, Ecosystem
Abstract

An extension of the climate variability hypothesis is that relatively stable climate, such as that of the tropics, induces distinct thermal bands across elevation that render dispersal over tropical mountains difficult compared with temperate mountains. Yet ecosystems are not thermally static in space-time, especially at small scales, which might render some mountains greater thermal isolators than others. Here we provide an extensive investigation of temperature drivers from fine to coarse scales, and we demonstrate that the degree of similarity in temperatures at high and low elevations on mountains is driven by more than just absolute mountain height and latitude. We compiled a database of 29 mountains spanning six continents to characterize thermal overlap by vertically stratified microhabitats and biomes and owing to seasonal changes in foliage, demonstrating via mixed effects modeling that micro- and mesogeography more strongly influence thermal overlap than macrogeography. Impressively, an increase of 1 m of vertical microhabitat height generates an increase in overlap equivalent to a 5.26° change in latitude. In addition, forested mountains have reduced thermal overlap-149% lower-relative to nonforested mountains. We provide evidence in support of a climate hypothesis that emphasizes microgeography as a determinant of dispersal, demographics, and behavior, thereby refining the classical theory of macroclimate variability as a prominent driver of biogeography.

Published
2021

11. Forest microclimates and climate change : importance, drivers and future research agenda

Author

Eva Gril, Arndt Hampe, Guillaume Decocq, Pieter De Frenne, Juha Aalto, Camille Meeussen, Jonathan Lenoir, Pieter Vangansbeke, Ronan Marrec, Michael B. Ashcroft, Caroline Greiser, Tommaso Jucker, Vilna Tyystjärvi, Jonas J. Lembrechts, Ditte M. Christiansen, Jérôme Ogée, Kristoffer Hylander, Florian Zellweger, David H. Klinges, Miska Luoto, Karen De Pauw, Sanne Govaert, Brett R. Scheffers, Irena A. Koelemeijer, Universiteit Gent = Ghent University [Belgium] (UGENT), Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Centre National de la Recherche Scientifique (CNRS)-Université de Picardie Jules Verne (UPJV), University of Helsinki, University of Florida [Gainesville] (UF), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, University of Wollongong [Australia], Department of Ecology, Environment and Plant Sciences [Stockholm], Stockholm University, Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), School of Biological Sciences [Bristol], University of Bristol [Bristol], Universiteit Antwerpen [Antwerpen], 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), ANR-19-CE32-0005,IMPRINT,IMpacts des PRocessus mIcroclimatiques sur la redistributioN de la biodiversiTé forestière en contexte de réchauffement du macroclimat(2019), and ANR-10-LABX-0045,COTE,COntinental To coastal Ecosystems: evolution, adaptability and governance(2010)

Subjects
0106 biological sciences, CANOPY STRUCTURE, 010504 meteorology & atmospheric sciences, Microclimate, Biodiversity, FINE-GRAIN, Forests, 01 natural sciences, Trees, Ecosystem services, forest, offset, BEHAVIORAL THERMOREGULATION, 11. Sustainability, General Environmental Science, biodiversity, Global and Planetary Change, Ecology, VERTICAL STRATIFICATION, Environmental resource management, buffering, Chemistry, Geography, climate change, [SDU.STU.CL]Sciences of the Universe [physics]/Earth Sciences/Climatology, TROPICAL FOREST, [SDE.MCG]Environmental Sciences/Global Changes, Climate change, 010603 evolutionary biology, LITTER DECOMPOSITION, future research, BOREAL FOREST, [SDV.EE.ECO]Life Sciences [q-bio]/Ecology, environment/Ecosystems, Forest ecology, ecosystem function, Environmental Chemistry, Ecosystem, PLANT-COMMUNITIES, Biology, 0105 earth and related environmental sciences, BIRDS NEST FERNS, business.industry, SPECIES DISTRIBUTION MODELS, 15. Life on land, 13. Climate action, Earth and Environmental Sciences, Sustainability, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, business, microclimate
Abstract

International audience; Forest microclimates contrast strongly with the climate outside forests. To fully understand and better predict how forests' biodiversity and functions relate to climate and climate change, microclimates need to be integrated into ecological research. Despite the potentially broad impact of microclimates on the response of forest ecosystems to global change, our understanding of how microclimates within and below tree canopies modulate biotic responses to global change at the species, community and ecosystem level is still limited. Here, we review how spatial and temporal variation in forest microclimates result from an interplay of forest features, local water balance, topography and landscape composition. We first stress and exemplify the importance of considering forest microclimates to understand variation in biodiversity and ecosystem functions across forest landscapes. Next, we explain how macroclimate warming (of the free atmosphere) can affect microclimates, and vice versa, via interactions with land-use changes across different biomes. Finally, we perform a priority ranking of future research avenues at the interface of microclimate ecology and global change biology, with a specific focus on three key themes: (1) disentangling the abiotic and biotic drivers and feedbacks of forest microclimates; (2) global and regional mapping and predictions of forest microclimates; and (3) the impacts of microclimate on forest biodiversity and ecosystem functioning in the face of climate change. The availability of microclimatic data will significantly increase in the coming decades, characterizing climate variability at unprecedented spatial and temporal scales relevant to biological processes in forests. This will revolutionize our understanding of the dynamics, drivers and implications of forest microclimates on biodiversity and ecological functions, and the impacts of global changes. In order to support the sustainable use of forests and to secure their biodiversity and ecosystem services for future generations, microclimates cannot be ignored.

Published
2021
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12. SoilTemp: A global database of near-surface temperature

Author

Juha M. Alatalo, Ilya M. D. Maclean, Ivan Nijs, Pascal Boeckx, Ronja E. M. Wedegärtner, Josefine Walz, Sergiy Medinets, Jonas Ardö, Martin Wilmking, Aníbal Pauchard, Onur Candan, Joseph Okello, Miguel Portillo-Estrada, Christian Rossi, Francesco Malfasi, Robert G. Björk, Tim Seipel, Pekka Niittynen, Kristoffer Hylander, Simone Cesarz, Michael B. Ashcroft, Dany Ghosn, T'Ai Gladys Whittingham Forte, Andrew D. Thomas, Nina Buchmann, Pavel Dan Turtureanu, Marcello Tomaselli, Martin Svátek, Luca Vitale, Christian Rixen, Valter Di Cecco, Pascal Vittoz, Jan Wild, Hans J. De Boeck, M. Rosa Fernández Calzado, Khatuna Gigauri, Haydn J.D. Thomas, Josef Brůna, Patrice Descombes, Robert Kanka, Roman Plichta, Julia Boike, Juan J. Jiménez, Mihai Pușcaș, James D. M. Speed, Tudor-Mihai Ursu, Maaike Y. Bader, Jian Zhang, Shengwei Zong, Marko Smiljanic, Ben Somers, Toke T. Høye, Martin Macek, Rebecca Finger Higgens, Jürgen Homeier, Fatih Fazlioglu, Ana Clara Mazzolari, Katja Tielbörger, Marek Čiliak, Sanne Govaert, Matěj Man, Loïc Pellissier, Bente J. Graae, Mana Gharun, Juan Lorite, Jhonatan Sallo Bravo, Thomas Scholten, Ian Klupar, Jonathan Lenoir, Martin Kopecký, Angela Stanisci, Joseph J. Bailey, Stuart W. Smith, Gergana N. Daskalova, Andrej Varlagin, Radim Matula, Meelis Pärtel, Ann Milbau, Peter Barančok, Jörg G. Stephan, Marijn Bauters, Jan Dick, Zuzana Sitková, Alistair S. Jump, Felix Gottschall, Fernando Moyano, Mario Trouillier, Filip Hrbáček, Eduardo Fuentes-Lillo, Nicoletta Cannone, Koenraad Van Meerbeek, Miska Luoto, Christopher Andrews, Charly Geron, Lisa J. Rew, Michael Stemkovski, Rafaella Canessa, Lucia Hederová, Peter Haase, Klaus Steinbauer, Keith W. Larson, Mats P. Björkman, Edoardo Cremonese, Lore T. Verryckt, Aud H. Halbritter, Jiri Dolezal, František Máliš, William D. Pearse, Zhaochen Zhang, Christian D. Larson, Sylvia Haider, Robert Weigel, Harald Pauli, Romina D. Dimarco, Nico Eisenhauer, Agustina Barros, Shyam S. Phartyal, Liesbeth van den Brink, Edmund W. Basham, Adrian V. Rocha, Mauro Guglielmin, Rafael A. García, Andrej Palaj, Josef Urban, Austin Koontz, Brett R. Scheffers, Mia Vedel Sørensen, Isla H. Myers-Smith, Camille Meeussen, Lena Muffler, Krystal Randall, Volodymyr I. Medinets, Sonia Merinero, Laurenz M. Teuber, Salvatore R. Curasi, José Luis Benito Alonso, Pieter De Frenne, Kamil Láska, Jonas Schmeddes, Martin A. Nuñez, Amanda Ratier Backes, Alessandro Petraglia, Miroslav Svoboda, Ellen Dorrepaal, Sonja Wipf, Juha Aalto, Masahito Ueyama, Benjamin Blonder, Jonas J. Lembrechts, Esther R. Frei, Lukas Siebicke, Bernard Heinesch, C. Johan Dahlberg, Juergen Kreyling, Camille Pitteloud, Florian Zellweger, Rebecca A. Senior, David H. Klinges, Miguel Ángel de Pablo, Elizabeth G. Simpson, George Kazakis, Jozef Kollár, Pallieter De Smedt, Olivier Roupsard, Jan Altman, Michele Carbognani, Julia Kemppinen, Manuela Winkler, Valeria Aschero, Pieter Vangansbeke, Andrea Lamprecht, Stef Haesen, University of Antwerp (UA), Finnish Meteorological Institute (FMI), Helsingin yliopisto = Helsingfors universitet = University of Helsinki, University of Wollongong [Australia], Australian Museum [Sydney], Universiteit Gent = Ghent University (UGENT), Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), Czech University of Life Sciences Prague (CZU), Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), University of Exeter, Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, 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), LMI IESOL Intensification Ecologique des Sols Cultivés en Afrique de l’Ouest [Dakar] (IESOL), Institut de recherche pour le développement (IRD [Sénégal]), Universidad de Concepción - University of Concepcion [Chile], Instituto de Ecología y Biodiversidad (IEB), Universidad Adventista de Chile - Adventist University of Chile (UNACH), Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Eidgenössische Technische Hochschule - Swiss Federal Institute of Technology [Zürich] (ETH Zürich), Qatar University, Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Nanyang Technological University [Singapour], University of Gothenburg (GU), Universität Greifswald - University of Greifswald, Georg-August-University = Georg-August-Universität Göttingen, Martin-Luther-University Halle-Wittenberg, German Centre for Integrative Biodiversity Research (iDiv), Leipzig University, Mountains of the Moon University, Laboratory of Applied Physical Chemistry - ISOFYS (Gent, Belgium), Mendel University in Brno (MENDELU), Siberian Federal University (SibFU), Nalanda University, Hemvati Nandan Bahuguna Garhwal University (HNBGU), Babes-Bolyai University [Cluj-Napoca] (UBB), A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences [Moscow] (RAS), Instituto de Investigaciones Forestales y Agropecuarias Bariloche (IFAB), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Instituto Nacional de Tecnología Agropecuaria (INTA), University of Stirling, Umeå University, Istituto per i Sistemi Agricoli e Forestali del Mediterraneo (ISAFOM), National Research Council of Italy | Consiglio Nazionale delle Ricerche (CNR), Dartmouth College [Hanover], University of Bergen (UiB), University of Notre Dame [Indiana] (UND), Utah State University (USU), Imperial College London, Arctic Research Centre [Aarhus] (ARC), Aarhus University [Aarhus], Universidad de Granada = University of Granada (UGR), Università degli studi di Parma = University of Parma (UNIPR), Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Stockholm University, University of South Bohemia, Aberystwyth University, York St John University, Centre International de Hautes Etudes Agronomiques Méditerranéennes - Institut Agronomique Méditerranéen de Chania (CIHEAM-IAMC), Centre International de Hautes Études Agronomiques Méditerranéennes (CIHEAM), Universidad de Alcalá - University of Alcalá (UAH), Montana State University (MSU), Lund University [Lund], Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria), Philipps Universität Marburg = Philipps University of Marburg, Università degli Studi del Molise = University of Molise (UNIMOL), Universidad Nacional de Cuyo [Mendoza] (UNCUYO), Instituto Argentino de Nivología, Glaciología y Ciencias Ambientales [Mendoza] (CONICET-IANIGLA), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional de Cuyo [Mendoza] (UNCUYO), Technical University in Zvolen (TUZVO), Georgian Institute of Public Affairs (GIPA), Austrian Academy of Sciences (OeAW), Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Osaka Prefecture University, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente [Bariloche] (INIBIOMA-CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), National Institute of Research and Development for Biological Sciences [Bucarest] (INCDSB), Université de Lausanne = University of Lausanne (UNIL), University of Tartu, Institute of Landscape Ecology of the Slovak Academy of Sciences, Slovak Academy of Sciences (SAS), Jolube Consultor Botánico, Northeast Normal University, Majella National Park - Parco Nazionale della Majella, National Forest Centre - Národné lesnícke centrum [Zvolen], University of Tübingen, County Administrative Board of Västra Götaland, Odessa National I.I.Mechnikov University, Research Institute for Nature and Forest (INBO), University of Edinburgh, University of California [Berkeley] (UC Berkeley), University of California (UC), Arizona State University [Tempe] (ASU), Swedish University of Agricultural Sciences (SLU), Gembloux Agro-Bio Tech [Gembloux], Université de Liège, Centre for Ecology and Hydrology [Bangor] (CEH), Natural Environment Research Council (NERC), Princeton University, Fundación Agencia Aragonesa para la Investigación y el Desarrollo (ARAID), Alfred Wegener Institute [Potsdam], Alfred-Wegener-Institut, Helmholtz-Zentrum für Polar- und Meeresforschung (AWI), Humboldt University Of Berlin, University of Florida [Gainesville] (UF), East China Normal University [Shangaï] (ECNU), Ordu University - Ordu Üniversitesi, Universidad Nacional de San Antonio Abad del Cusco (UNSAAC), Masaryk University [Brno] (MUNI), Aosta Valley Regional Environmental Protection Agency (ARPA), Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association, Universität Duisburg-Essen = University of Duisburg-Essen [Essen], Swiss National Park - Parc Naziunal Svizzer, Universität Zürich [Zürich] = University of Zurich (UZH), ANR-19-CE32-0005,IMPRINT,IMpacts des PRocessus mIcroclimatiques sur la redistributioN de la biodiversiTé forestière en contexte de réchauffement du macroclimat(2019), University of Helsinki, Universiteit Gent = Ghent University [Belgium] (UGENT), Centre National de la Recherche Scientifique (CNRS)-Université de Picardie Jules Verne (UPJV), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), 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)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Georg-August-University [Göttingen], Consiglio Nazionale delle Ricerche [Roma] (CNR), University of Granada [Granada], University of Parma = Università degli studi di Parma [Parme, Italie], Universitá degli Studi dell’Insubria, Philipps University of Marburg, Università degli Studi del Molise (Unimol), Universität für Bodenkultur Wien [Vienne, Autriche] (BOKU), University of Lausanne (UNIL), University of California [Berkeley], University of California, Humboldt-Universität zu Berlin, and University of Duisburg-Essen

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Biome, Biodiversity & Conservation, Microclimate, computer.software_genre, 01 natural sciences, topoclimate, Snow, HETEROGENEITY, SCALE, database, General Environmental Science, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, CLIMATE-CHANGE, Database, Ecology, Spatial database, Vegetation, Biological Sciences, Chemistry, soil climate, climate change, species distributions, Biodiversity Conservation, ecosystem processes, microclimate, temperature, Life Sciences & Biomedicine, Biologie, [SDE.MCG]Environmental Sciences/Global Changes, Climate change, Environmental Sciences & Ecology, [SDV.BID]Life Sciences [q-bio]/Biodiversity, MOISTURE, 010603 evolutionary biology, soil, LITTER DECOMPOSITION, species 19 distributions, Environmental Chemistry, DISTRIBUTIONS, SCALE SOIL, Biology, climate, Ecosystem, 0105 earth and related environmental sciences, Science & Technology, Global warming, SPECIES DISTRIBUTION MODELS, 15. Life on land, Radiative forcing, MACROCLIMATE, Agriculture and Soil Science, 13. Climate action, SNOW, Earth and Environmental Sciences, Environmental science, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, computer, Environmental Sciences
Abstract

Current analyses and predictions of spatially explicit patterns and processes in ecology most often rely on climate data interpolated from standardized weather stations. This interpolated climate data represents long-term average thermal conditions at coarse spatial resolutions only. Hence, many climate-forcing factors that operate at fine spatiotemporal resolutions are overlooked. This is particularly important in relation to effects of observation height (e.g. vegetation, snow and soil characteristics) and in habitats varying in their exposure to radiation, moisture and wind (e.g. topography, radiative forcing or cold-air pooling). Since organisms living close to the ground relate more strongly to these microclimatic conditions than to free-air temperatures, microclimatic ground and near-surface data are needed to provide realistic forecasts of the fate of such organisms under anthropogenic climate change, as well as of the functioning of the ecosystems they live in. To fill this critical gap, we highlight a call for temperature time series submissions to SoilTemp, a geospatial database initiative compiling soil and near-surface temperature data from all over the world. Currently, this database contains time series from 7,538 temperature sensors from 51 countries across all key biomes. The database will pave the way toward an improved global understanding of microclimate and bridge the gap between the available climate data and the climate at fine spatiotemporal resolutions relevant to most organisms and ecosystem processes. ispartof: GLOBAL CHANGE BIOLOGY vol:26 issue:11 pages:6616-6629 ispartof: location:England status: published

Published
2020
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13. Microclimc: A mechanistic model of above, below and within-canopy microclimate

Author

Ilya M. D. Maclean and David H. Klinges

Subjects
0106 biological sciences, Canopy, 010604 marine biology & hydrobiology, Ecological Modeling, Microclimate, Humidity, Ranging, Radiative forcing, Atmospheric sciences, 010603 evolutionary biology, 01 natural sciences, Data assimilation, Evapotranspiration, Transient (computer programming)
Abstract

Climate strongly influences ecological patterns and processes at scales ranging from local to global. Studies of ecological responses to climate usually rely on data derived from weather stations, where temperature and humidity may differ substantially from that in the microenvironments in which organisms reside. To help remedy this, we present a model that leverages first principles physics to predict microclimate above, within, and below the canopy in any terrestrial location on earth, made freely available as an R software package. The model can be run in one of two modes. In the first, heat and vapour exchange within and below canopy are modelled as transient processes, thus accounting for fine temporal-resolution changes. In the second, steady-state conditions are assumed, enabling conditions at hourly intervals or longer to be estimated with greater computational efficiency. We validated both modes of the model with empirical below-canopy thermal measurements from several locations globally, resulting in hourly predictions with mean absolute error of 2.77 °C and 2.79 °C for the transient and steady-state modes respectively. Alongside the microclimate model, several functions are provided to assist data assimilation, as well as different parameterizations to capture a variety of habitats, allowing flexible application even when little is known about the study location. The model's modular design in a programming language familiar to ecological researchers provides easy access to the modelling of site-specific climate forcing, in an attempt to more closely unify the fields of micrometeorology and ecology.

Published
2021
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