1
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Boonman CC, Huijbregts MA, Benítez‐López A, Schipper AM, Thuiller W, Santini L. Trait‐based projections of climate change effects on global biome distributions. DIVERS DISTRIB 2021. [DOI: 10.1111/ddi.13431] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022] Open
Affiliation(s)
- Coline C.F. Boonman
- Institute for Water and Wetland Research Department of Environmental Science Radboud University Nijmegen the Netherlands
- Institute for Water and Wetland Research Department of Aquatic Ecology & Environmental Biology Radboud University Nijmegen the Netherlands
| | - Mark A.J. Huijbregts
- Institute for Water and Wetland Research Department of Environmental Science Radboud University Nijmegen the Netherlands
| | - Ana Benítez‐López
- Institute for Water and Wetland Research Department of Environmental Science Radboud University Nijmegen the Netherlands
- Integrative Ecology Group Estación Biológica de Doñana (EBD‐CSIC) Sevilla Spain
| | - Aafke M. Schipper
- Institute for Water and Wetland Research Department of Environmental Science Radboud University Nijmegen the Netherlands
- PBL Netherlands Environmental Assessment Agency The Hague the Netherlands
| | - Wilfried Thuiller
- Laboratoire d'Écologie Alpine (LECA) CNRS LECA Univ. Grenoble AlpesUniv. Savoie Mont Blanc Grenoble France
| | - Luca Santini
- Institute for Water and Wetland Research Department of Environmental Science Radboud University Nijmegen the Netherlands
- Department of Biology and Biotechnologies “Charles Darwin” Sapienza University of Rome Rome Italy
- National Research Council Institute of Research on Terrestrial Ecosystems (CNR‐IRET)Monterotondo (Rome) Italy
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2
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Amini Tehrani N, Naimi B, Jaboyedoff M. Modeling current and future species distribution of breeding birds as regional essential biodiversity variables (SD EBVs): A bird perspective in Swiss Alps. Glob Ecol Conserv 2021. [DOI: 10.1016/j.gecco.2021.e01596] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022] Open
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3
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Chase JM, Jeliazkov A, Ladouceur E, Viana DS. Biodiversity conservation through the lens of metacommunity ecology. Ann N Y Acad Sci 2020; 1469:86-104. [PMID: 32406120 DOI: 10.1111/nyas.14378] [Citation(s) in RCA: 44] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2019] [Revised: 04/14/2020] [Accepted: 05/01/2020] [Indexed: 01/09/2023]
Abstract
Metacommunity ecology combines local (e.g., environmental filtering and biotic interactions) and regional (e.g., dispersal and heterogeneity) processes to understand patterns of species abundance, occurrence, composition, and diversity across scales of space and time. As such, it has a great potential to generalize and synthesize our understanding of many ecological problems. Here, we give an overview of how a metacommunity perspective can provide useful insights for conservation biology, which aims to understand and mitigate the effects of anthropogenic drivers that decrease population sizes, increase extinction probabilities, and threaten biodiversity. We review four general metacommunity processes-environmental filtering, biotic interactions, dispersal, and ecological drift-and discuss how key anthropogenic drivers (e.g., habitat loss and fragmentation, and nonnative species) can alter these processes. We next describe how the patterns of interest in metacommunities (abundance, occupancy, and diversity) map onto issues at the heart of conservation biology, and describe cases where conservation biology benefits by taking a scale-explicit metacommunity perspective. We conclude with some ways forward for including metacommunity perspectives into ideas of ecosystem functioning and services, as well as approaches to habitat management, preservation, and restoration.
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Affiliation(s)
- Jonathan M Chase
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.,Department of Computer Sciences, Martin Luther University, Halle-Wittenberg, Germany
| | - Alienor Jeliazkov
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.,Department of Computer Sciences, Martin Luther University, Halle-Wittenberg, Germany
| | - Emma Ladouceur
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.,Department of Computer Sciences, Martin Luther University, Halle-Wittenberg, Germany.,Department of Physiological Diversity, Helmholtz Centre for Environmental Research - UFZ, Leipzig, Germany
| | - Duarte S Viana
- German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Germany.,Leipzig University, Leipzig, Germany
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4
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Using macroecological constraints on spatial biodiversity predictions under climate change: the modelling method matters. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2018.10.023] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/23/2022]
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5
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Nieto‐Lugilde D, Maguire KC, Blois JL, Williams JW, Fitzpatrick MC. Multiresponse algorithms for community‐level modelling: Review of theory, applications, and comparison to species distribution models. Methods Ecol Evol 2017. [DOI: 10.1111/2041-210x.12936] [Citation(s) in RCA: 32] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Diego Nieto‐Lugilde
- Appalachian Laboratory University of Maryland Center for Environmental Science Frostburg MD USA
- Departamento de Botánica Ecología y Fisiología Vegetal Universidad de Córdoba Córdoba Spain
| | | | - Jessica L. Blois
- School of Natural Sciences University of California Merced CA USA
| | - John W. Williams
- Center for Climatic Research University of Wisconsin Madison WI USA
- Department of Geography University of Wisconsin Madison WI USA
| | - Matthew C. Fitzpatrick
- Appalachian Laboratory University of Maryland Center for Environmental Science Frostburg MD USA
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6
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Chen IC, Hsieh CH, Kondoh M, Lin HJ, Miki T, Nakamura M, Ohgushi T, Urabe J, Yoshida T. Filling the gaps in ecological studies of socioecological systems. Ecol Res 2017. [DOI: 10.1007/s11284-017-1521-9] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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7
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Schmitt S, Pouteau R, Justeau D, Boissieu F, Birnbaum P. ssdm
: An
r
package to predict distribution of species richness and composition based on stacked species distribution models. Methods Ecol Evol 2017. [DOI: 10.1111/2041-210x.12841] [Citation(s) in RCA: 85] [Impact Index Per Article: 12.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Sylvain Schmitt
- Botany and Applied Plant Ecology LaboratoryNew Caledonian Agronomic Institute (IAC) Nouméa New Caledonia
| | - Robin Pouteau
- Botany and Applied Plant Ecology LaboratoryNew Caledonian Agronomic Institute (IAC) Nouméa New Caledonia
| | - Dimitri Justeau
- Botany and Applied Plant Ecology LaboratoryNew Caledonian Agronomic Institute (IAC) Nouméa New Caledonia
| | - Florian Boissieu
- Institute for Sustainable Development (IRD) Noumea New Caledonia
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8
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Mateo RG, Mokany K, Guisan A. Biodiversity Models: What If Unsaturation Is the Rule? Trends Ecol Evol 2017; 32:556-566. [PMID: 28610851 PMCID: PMC5516772 DOI: 10.1016/j.tree.2017.05.003] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2016] [Revised: 05/10/2017] [Accepted: 05/12/2017] [Indexed: 11/26/2022]
Abstract
Improving biodiversity predictions is essential if we are to meet the challenges posed by global change. As knowledge is key to feed models, we need to evaluate how debated theory can affect models. An important ongoing debate is whether environmental constraints limit the number of species that can coexist in a community (saturation), with recent findings suggesting that species richness in many communities might be unsaturated. Here, we propose that biodiversity models could address this issue by accounting for a duality: considering communities as unsaturated but where species composition is constrained by different scale-dependent biodiversity drivers. We identify a variety of promising advances for incorporating this duality into commonly applied biodiversity modelling approaches and improving their spatial predictions. The majority of biodiversity modelling approaches do not explicitly address the question of saturation. Theoretical and methodological implications of saturation or unsaturation in biodiversity modelling. Addressing saturation or unsaturation is vital to produce more reliable conservation strategies. Integrative community modelling frameworks may be the way forward.
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Affiliation(s)
- Rubén G Mateo
- Department of Ecology and Evolution, University of Lausanne, Biophore, CH-1015, Lausanne, Switzerland; ETSI de Montes, Forestal y del Medio Natural, Universidad Politécnica de Madrid, Ciudad Universitaria s/n, 28040, Madrid, Spain.
| | | | - Antoine Guisan
- Department of Ecology and Evolution, University of Lausanne, Biophore, CH-1015, Lausanne, Switzerland; Institute of Earth Science Dynamics, University of Lausanne, Geopolis, CH-1015 Lausanne, Switzerland
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9
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Clark JS, Nemergut D, Seyednasrollah B, Turner PJ, Zhang S. Generalized joint attribute modeling for biodiversity analysis: median‐zero, multivariate, multifarious data. ECOL MONOGR 2017. [DOI: 10.1002/ecm.1241] [Citation(s) in RCA: 127] [Impact Index Per Article: 18.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Affiliation(s)
- James S. Clark
- Nicholas School of the Environment Duke University Durham North Carolina 27708 USA
- Department of Statistical Science Duke University Durham North Carolina 27708 USA
| | - Diana Nemergut
- Department of Biology Duke University Durham North Carolina 27708 USA
| | - Bijan Seyednasrollah
- Nicholas School of the Environment Duke University Durham North Carolina 27708 USA
| | - Phillip J. Turner
- Division of Marine Science and Conservation Nicholas School of the Environment Duke University Beaufort North Carolina 28516 USA
| | - Stacy Zhang
- Division of Marine Science and Conservation Nicholas School of the Environment Duke University Beaufort North Carolina 28516 USA
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10
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Evans MEK, Merow C, Record S, McMahon SM, Enquist BJ. Towards Process-based Range Modeling of Many Species. Trends Ecol Evol 2016; 31:860-871. [PMID: 27663835 DOI: 10.1016/j.tree.2016.08.005] [Citation(s) in RCA: 63] [Impact Index Per Article: 7.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2016] [Revised: 08/17/2016] [Accepted: 08/18/2016] [Indexed: 12/17/2022]
Abstract
Understanding and forecasting species' geographic distributions in the face of global change is a central priority in biodiversity science. The existing view is that one must choose between correlative models for many species versus process-based models for few species. We suggest that opportunities exist to produce process-based range models for many species, by using hierarchical and inverse modeling to borrow strength across species, fill data gaps, fuse diverse data sets, and model across biological and spatial scales. We review the statistical ecology and population and range modeling literature, illustrating these modeling strategies in action. A variety of large, coordinated ecological datasets that can feed into these modeling solutions already exist, and we highlight organisms that seem ripe for the challenge.
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Affiliation(s)
- Margaret E K Evans
- Laboratory of Tree-Ring Research, University of Arizona, Tucson, AZ 85721, USA; Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA.
| | - Cory Merow
- Department of Ecology and Evolutionary Biology, Yale University, New Haven, CT 06520, USA
| | - Sydne Record
- Department of Biology, Bryn Mawr College, Bryn Mawr, PA 19010, USA
| | - Sean M McMahon
- Smithsonian Environmental Research Center, Edgewater, MD 21307, USA
| | - Brian J Enquist
- Department of Ecology and Evolutionary Biology, University of Arizona, Tucson, AZ 85721, USA; The Santa Fe Institute, Santa Fe, NM 87501, USA; Center for Environmental Studies, Aspen, CO 81611, USA
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11
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Zurell D, Thuiller W, Pagel J, Cabral JS, Münkemüller T, Gravel D, Dullinger S, Normand S, Schiffers KH, Moore KA, Zimmermann NE. Benchmarking novel approaches for modelling species range dynamics. GLOBAL CHANGE BIOLOGY 2016; 22:2651-64. [PMID: 26872305 PMCID: PMC4972146 DOI: 10.1111/gcb.13251] [Citation(s) in RCA: 77] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/13/2015] [Revised: 01/28/2016] [Accepted: 02/04/2016] [Indexed: 05/22/2023]
Abstract
Increasing biodiversity loss due to climate change is one of the most vital challenges of the 21st century. To anticipate and mitigate biodiversity loss, models are needed that reliably project species' range dynamics and extinction risks. Recently, several new approaches to model range dynamics have been developed to supplement correlative species distribution models (SDMs), but applications clearly lag behind model development. Indeed, no comparative analysis has been performed to evaluate their performance. Here, we build on process-based, simulated data for benchmarking five range (dynamic) models of varying complexity including classical SDMs, SDMs coupled with simple dispersal or more complex population dynamic models (SDM hybrids), and a hierarchical Bayesian process-based dynamic range model (DRM). We specifically test the effects of demographic and community processes on model predictive performance. Under current climate, DRMs performed best, although only marginally. Under climate change, predictive performance varied considerably, with no clear winners. Yet, all range dynamic models improved predictions under climate change substantially compared to purely correlative SDMs, and the population dynamic models also predicted reasonable extinction risks for most scenarios. When benchmarking data were simulated with more complex demographic and community processes, simple SDM hybrids including only dispersal often proved most reliable. Finally, we found that structural decisions during model building can have great impact on model accuracy, but prior system knowledge on important processes can reduce these uncertainties considerably. Our results reassure the clear merit in using dynamic approaches for modelling species' response to climate change but also emphasize several needs for further model and data improvement. We propose and discuss perspectives for improving range projections through combination of multiple models and for making these approaches operational for large numbers of species.
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Affiliation(s)
- Damaris Zurell
- Dynamic Macroecology, Swiss Federal Research Institute WSL, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
| | - Wilfried Thuiller
- Univ. Grenoble Alpes, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
- CNRS, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
| | - Jörn Pagel
- Institute of Landscape and Plant Ecology, University of Hohenheim, August-v.Hartmann-Str. 3, D-70599 Stuttgart, Germany
| | - Juliano S Cabral
- Biodiversity, Macroecology and Conservation Biogeography, University Göttingen, Büsgenweg 2, D-37077, Goettingen, Germany
- Synthesis Centre of the German Centre for Integrative Biodiversity Research (iDiv), Deutscher Platz 5e, D-04103 Leipzig, Germany
| | - Tamara Münkemüller
- Univ. Grenoble Alpes, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
- CNRS, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
| | - Dominique Gravel
- Université de Québec à Rimouski, 300 Allée des Ursulines, Rimouski, Canada. G5L 3A1
| | - Stefan Dullinger
- Department of Botany and Biodiversity Research, University of Vienna, Rennweg 14, 1030 Vienna, Austria
| | - Signe Normand
- Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Ny Munkegade 114, DK-8000 Aarhus C, Denmark
| | - Katja H. Schiffers
- Univ. Grenoble Alpes, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
- CNRS, Laboratoire d’Écologie Alpine (LECA), UMR-CNRS 5553 Université J. Fourier BP 53, F-38000 Grenoble, France
- Senckenberg Biodiversity and Climate Research Centre (BiK-F), Georg Voigt-Straße 14-16, D-60325 Frankfurt (Main), Germany
| | - Kara A. Moore
- Center for Population Biology, University of California, Davis, One Shields Avenue, Davis, CA, 95616, USA
| | - Niklaus E. Zimmermann
- Dynamic Macroecology, Swiss Federal Research Institute WSL, Zürcherstrasse 111, CH-8903 Birmensdorf, Switzerland
- Department of Environmental Systems Science, Swiss Federal Institute of Technology ETH, CH-8092 Zurich, Switzerland
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12
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Zurell D, Zimmermann NE, Sattler T, Nobis MP, Schröder B. Effects of functional traits on the prediction accuracy of species richness models. DIVERS DISTRIB 2016. [DOI: 10.1111/ddi.12450] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Damaris Zurell
- Dynamic Macroecology; Landscape Dynamics; Swiss Federal Research Institute WSL; Zürcherstrasse 111 CH-8903 Birmensdorf Switzerland
| | - Niklaus E. Zimmermann
- Dynamic Macroecology; Landscape Dynamics; Swiss Federal Research Institute WSL; Zürcherstrasse 111 CH-8903 Birmensdorf Switzerland
- Department of Environmental Systems Science; Swiss Federal Institute of Technology ETH; CH-8092 Zürich Switzerland
| | - Thomas Sattler
- Swiss Ornithological Institute; Seerose 1 CH-6204 Sempach Switzerland
| | - Michael P. Nobis
- Dynamic Macroecology; Landscape Dynamics; Swiss Federal Research Institute WSL; Zürcherstrasse 111 CH-8903 Birmensdorf Switzerland
| | - Boris Schröder
- Environmental Systems Analysis; Institute of Geoecology; Technische Universität Braunschweig; Langer Kamp 19c D-38106 Braunschweig Germany
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB); D-14195 Berlin Germany
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13
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Burley HM, Mokany K, Ferrier S, Laffan SW, Williams KJ, Harwood TD. Macroecological scale effects of biodiversity on ecosystem functions under environmental change. Ecol Evol 2016; 6:2579-93. [PMID: 27066246 PMCID: PMC4798165 DOI: 10.1002/ece3.2036] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/11/2015] [Revised: 02/01/2016] [Accepted: 02/02/2016] [Indexed: 11/17/2022] Open
Abstract
Conserving different spatial and temporal dimensions of biological diversity is considered necessary for maintaining ecosystem functions under predicted global change scenarios. Recent work has shifted the focus from spatially local (α-diversity) to macroecological scales (β- and γ-diversity), emphasizing links between macroecological biodiversity and ecosystem functions (MB-EF relationships). However, before the outcomes of MB-EF analyses can be useful to real-world decisions, empirical modeling needs to be developed for natural ecosystems, incorporating a broader range of data inputs, environmental change scenarios, underlying mechanisms, and predictions. We outline the key conceptual and technical challenges currently faced in developing such models and in testing and calibrating the relationships assumed in these models using data from real ecosystems. These challenges are explored in relation to two potential MB-EF mechanisms: "macroecological complementarity" and "spatiotemporal compensation." Several regions have been sufficiently well studied over space and time to robustly test these mechanisms by combining cutting-edge spatiotemporal methods with remotely sensed data, including plant community data sets in Australia, Europe, and North America. Assessing empirical MB-EF relationships at broad spatiotemporal scales will be crucial in ensuring these macroecological processes can be adequately considered in the management of biodiversity and ecosystem functions under global change.
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Affiliation(s)
- Hugh M Burley
- Centre for Ecosystem Science School of Biological, Earth and Environmental Sciences University of New South Wales Sydney New South Wales 2052 Australia; CSIRO Land and Water Canberra Australian Capital Territory 2601 Australia
| | - Karel Mokany
- CSIRO Land and Water Canberra Australian Capital Territory 2601 Australia
| | - Simon Ferrier
- CSIRO Land and Water Canberra Australian Capital Territory 2601 Australia
| | - Shawn W Laffan
- Centre for Ecosystem Science School of Biological, Earth and Environmental Sciences University of New South Wales Sydney New South Wales 2052 Australia
| | - Kristen J Williams
- CSIRO Land and Water Canberra Australian Capital Territory 2601 Australia
| | - Tom D Harwood
- CSIRO Land and Water Canberra Australian Capital Territory 2601 Australia
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14
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Tayleur CM, Devictor V, Gaüzère P, Jonzén N, Smith HG, Lindström Å. Regional variation in climate change winners and losers highlights the rapid loss of cold-dwelling species. DIVERS DISTRIB 2016. [DOI: 10.1111/ddi.12412] [Citation(s) in RCA: 56] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022] Open
Affiliation(s)
- Catherine M. Tayleur
- Centre for Environmental and Climate Research; Lund University; S-223 62 Lund Sweden
- Conservation Science Group; Cambridge University; David Attenborough Building; Pembroke Street Cambridge CB2 3QZ
| | - Vincent Devictor
- Institut des Sciences de l'Evolution; Université Montpellier; CNRS; IRD; Place Eugéne Bataillon; 34095 Montpellier cedex 05 France
| | - Pierre Gaüzère
- Institut des Sciences de l'Evolution; Université Montpellier; CNRS; IRD; Place Eugéne Bataillon; 34095 Montpellier cedex 05 France
| | - Niclas Jonzén
- Department of Biology; Biodiversity Unit; Lund University; S-223 62 Lund Sweden
| | - Henrik G. Smith
- Centre for Environmental and Climate Research; Lund University; S-223 62 Lund Sweden
- Department of Biology; Biodiversity Unit; Lund University; S-223 62 Lund Sweden
| | - Åke Lindström
- Department of Biology; Biodiversity Unit; Lund University; S-223 62 Lund Sweden
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15
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Mokany K, Thomson JJ, Lynch JJ, Jordan GJ, Ferrier S. Linking changes in community composition and function under climate change. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2015; 25:2132-2141. [PMID: 26910944 DOI: 10.1890/14-2384.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
Climate change is expected to directly alter the composition of communities and the functioning of ecosystems across the globe. Improving our understanding of links between biodiversity and ecosystem functioning across large spatial scales and rapid global change is a major priority to help identify management responses that will retain diverse, functioning systems. Here we address this challenge by linking projected changes in plant community composition and functional attributes (height, leaf area, seed mass) under climate change across Tasmania, Australia. Using correlative community-level modeling, we found that projected changes in plant community composition were not consistently related to projected changes in community mean trait values. In contrast, we identified specific mechanisms through which alternative combinations of projected functional and compositional change across Tasmania could be realized, including loss/replacement of functionally similar species (lowland grasslands/grassy woodlands) and loss of a small number of functionally unique species (lowland forests). Importantly, we demonstrate how these linked projections of change in community composition and functional attributes can be utilized to inform specific management actions that may assist in maintaining diverse, functioning ecosystems under climate change.
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16
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Mokany K, Ferrier S, Connolly SR, Dunstan PK, Fulton EA, Harfoot MB, Harwood TD, Richardson AJ, Roxburgh SH, Scharlemann JPW, Tittensor DP, Westcott DA, Wintle BA. Integrating modelling of biodiversity composition and ecosystem function. OIKOS 2015. [DOI: 10.1111/oik.02792] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
| | | | - Sean R. Connolly
- School of Marine and Tropical Biology, James Cook University; Townsville QLD Australia
| | | | | | - Michael B. Harfoot
- United Nations Environment Programme World Conservation Monitoring Centre; Cambridge UK
- Computational Ecology and Environmental Science, Microsoft Research; Cambridge UK
| | | | - Anthony J. Richardson
- CSIRO; Brisbane QLD Australia
- Centre for Applications in Natural Resource Mathematics, School of Mathematics and Physics, The Univ. of Queensland; St Lucia QLD Australia
| | | | - Jörn P. W. Scharlemann
- United Nations Environment Programme World Conservation Monitoring Centre; Cambridge UK
- School of Life Sciences, Univ. of Sussex; Brighton UK
| | - Derek P. Tittensor
- United Nations Environment Programme World Conservation Monitoring Centre; Cambridge UK
- Computational Ecology and Environmental Science, Microsoft Research; Cambridge UK
- Dept of Biology; Dalhousie University; Halifax NS Canada
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17
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Souza DM, Teixeira RFM, Ostermann OP. Assessing biodiversity loss due to land use with Life Cycle Assessment: are we there yet? GLOBAL CHANGE BIOLOGY 2015; 21:32-47. [PMID: 25143302 PMCID: PMC4312853 DOI: 10.1111/gcb.12709] [Citation(s) in RCA: 29] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/07/2014] [Revised: 07/23/2014] [Accepted: 08/08/2014] [Indexed: 05/21/2023]
Abstract
Ecosystems are under increasing pressure from human activities, with land use and land-use change at the forefront of the drivers that provoke global and regional biodiversity loss. The first step in addressing the challenge of how to reverse the negative outlook for the coming years starts with measuring environmental loss rates and assigning responsibilities. Pinpointing the global pressures on biodiversity is a task best addressed using holistic models such as Life Cycle Assessment (LCA). LCA is the leading method for calculating cradle-to-grave environmental impacts of products and services; it is actively promoted by many public policies, and integrated as part of environmental information systems within private companies. LCA already deals with the potential biodiversity impacts of land use, but there are significant obstacles to overcome before its models grasp the full reach of the phenomena involved. In this review, we discuss some pressing issues that need to be addressed. LCA mainly introduces biodiversity as an endpoint category modeled as a loss in species richness due to the conversion and use of land over time and space. The functional and population effects on biodiversity are mostly absent due to the emphasis on species accumulation with limited geographic and taxonomical reach. Current land-use modeling activities that use biodiversity indicators tend to oversimplify the real dynamics and complexity of the interactions of species among each other and with their habitats. To identify the main areas for improvement, we systematically reviewed LCA studies on land use that had findings related to global change and conservation ecology. We provide suggestion as to how to address some of the issues raised. Our overall objective was to encourage companies to monitor and take concrete steps to address the impacts of land use on biodiversity on a broader geographical scale and along increasingly globalized supply chains.
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Affiliation(s)
- Danielle M Souza
- Institute for Environment and Sustainability, European Commission, Joint Research CentreVia Enrico Fermi 2749, TP270, Ispra, I-21027, Italy
- Department of Energy and Technology, Swedish University of Agricultural SciencesLennart Hjelms väg, 9, Uppsala, Sweden
| | - Ricardo FM Teixeira
- Department of Biology, Research Group of Plant and Vegetation Ecology, University of Antwerp, Campus Drie EikenUniversiteitsplein 1, Wilrijk, B-2610, Belgium
| | - Ole P Ostermann
- Institute for Environment and Sustainability, European Commission, Joint Research CentreVia Enrico Fermi 2749, TP270, Ispra, I-21027, Italy
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18
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Barker NKS, Slattery SM, Darveau M, Cumming SG. Modeling distribution and abundance of multiple species: Different pooling strategies produce similar results. Ecosphere 2014. [DOI: 10.1890/es14-00256.1] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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Clark JS, Gelfand AE, Woodall CW, Zhu K. More than the sum of the parts: forest climate response from joint species distribution models. ECOLOGICAL APPLICATIONS : A PUBLICATION OF THE ECOLOGICAL SOCIETY OF AMERICA 2014; 24:990-999. [PMID: 25154092 DOI: 10.1890/13-1015.1] [Citation(s) in RCA: 77] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/03/2023]
Abstract
The perceived threat of climate change is often evaluated from species distribution models that are fitted to many species independently and then added together. This approach ignores the fact that species are jointly distributed and limit one another. Species respond to the same underlying climatic variables, and the abundance of any one species can be constrained by competition; a large increase in one is inevitably linked to declines of others. Omitting this basic relationship explains why responses modeled independently do not agree with the species richness or basal areas of actual forests. We introduce a joint species distribution modeling approach (JSDM), which is unique in three ways, and apply it to forests of eastern North America. First, it accommodates the joint distribution of species. Second, this joint distribution includes both abundance and presence-absence data. We solve the common issue of large numbers of zeros in abundance data by accommodating zeros in both stem counts and basal area data, i.e., a new approach to zero inflation. Finally, inverse prediction can be applied to the joint distribution of predictions to integrate the role of climate risks across all species and identify geographic areas where communities will change most (in terms of changes in abundance) with climate change. Application to forests in the eastern United States shows that climate can have greatest impact in the Northeast, due to temperature, and in the Upper Midwest, due to temperature and precipitation. Thus, these are the regions experiencing the fastest warming and are also identified as most responsive at this scale.
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20
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Mokany K, Prasad S, Westcott DA. Loss of frugivore seed dispersal services under climate change. Nat Commun 2014; 5:3971. [DOI: 10.1038/ncomms4971] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2013] [Accepted: 04/28/2014] [Indexed: 11/09/2022] Open
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Moir ML, Hughes L, Vesk PA, Leng MC. Which host-dependent insects are most prone to coextinction under changed climates? Ecol Evol 2014; 4:1295-312. [PMID: 24834327 PMCID: PMC4020690 DOI: 10.1002/ece3.1021] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2014] [Revised: 02/13/2014] [Accepted: 02/13/2014] [Indexed: 11/09/2022] Open
Abstract
Coextinction (loss of dependent species with their host or partner species) presents a threat to untold numbers of organisms. Climate change may act synergistically to accelerate rates of coextinction. In this review, we present the first synthesis of the available literature and propose a novel schematic diagram that can be used when assessing the potential risk climate change represents for dependent species. We highlight traits that may increase the susceptibility of insect species to coextinction induced by climate change, suggest the most influential host characteristics, and identify regions where climate change may have the greatest impact on dependent species. The aim of this review was to provide a platform for future research, directing efforts toward taxa and habitats at greatest risk of species loss through coextinction accelerated by climate change.
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Affiliation(s)
- Melinda L Moir
- School of Plant Biology, University of Western Australia Crawley, Western Australia, 6009, Australia ; School of Botany, University of Melbourne Parkville, Victoria, 3010, Australia
| | - Lesley Hughes
- Department of Biological Sciences, Macquarie University North Ryde, New South Wales, 2109, Australia
| | - Peter A Vesk
- School of Botany, University of Melbourne Parkville, Victoria, 3010, Australia
| | - Mei Chen Leng
- School of Plant Biology, University of Western Australia Crawley, Western Australia, 6009, Australia
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22
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Mokany K, Westcott DA, Prasad S, Ford AJ, Metcalfe DJ. Identifying priority areas for conservation and management in diverse tropical forests. PLoS One 2014; 9:e89084. [PMID: 24551222 PMCID: PMC3925232 DOI: 10.1371/journal.pone.0089084] [Citation(s) in RCA: 19] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2013] [Accepted: 01/20/2014] [Indexed: 12/03/2022] Open
Abstract
The high concentration of the world’s species in tropical forests endows these systems with particular importance for retaining global biodiversity, yet it also presents significant challenges for ecology and conservation science. The vast number of rare and yet to be discovered species restricts the applicability of species-level modelling for tropical forests, while the capacity of community classification approaches to identify priorities for conservation and management is also limited. Here we assessed the degree to which macroecological modelling can overcome shortfalls in our knowledge of biodiversity in tropical forests and help identify priority areas for their conservation and management. We used 527 plant community survey plots in the Australian Wet Tropics to generate models and predictions of species richness, compositional dissimilarity, and community composition for all the 4,313 vascular plant species recorded across the region (>1.3 million communities (grid cells)). We then applied these predictions to identify areas of tropical forest likely to contain the greatest concentration of species, rare species, endemic species and primitive angiosperm families. Synthesising these alternative attributes of diversity into a single index of conservation value, we identified two areas within the Australian wet tropics that should be a high priority for future conservation actions: the Atherton Tablelands and Daintree rainforest. Our findings demonstrate the value of macroecological modelling in identifying priority areas for conservation and management actions within highly diverse systems, such as tropical forests.
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Affiliation(s)
- Karel Mokany
- Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT, Australia
- * E-mail:
| | - David A. Westcott
- Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation, Atherton, QLD, Australia
| | - Soumya Prasad
- Centre for Ecological Sciences, Indian Institute of Science, Bangalore, India
| | - Andrew J. Ford
- Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation, Atherton, QLD, Australia
| | - Daniel J. Metcalfe
- Ecosystem Sciences, Commonwealth Scientific and Industrial Research Organisation, Dutton Park, QLD, Australia
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β diversity contributes to ecosystem processes more than by simply summing the parts. Proc Natl Acad Sci U S A 2013; 110:E4057. [PMID: 24128765 DOI: 10.1073/pnas.1313429110] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
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24
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Blois JL, Zarnetske PL, Fitzpatrick MC, Finnegan S. Climate Change and the Past, Present, and Future of Biotic Interactions. Science 2013; 341:499-504. [PMID: 23908227 DOI: 10.1126/science.1237184] [Citation(s) in RCA: 317] [Impact Index Per Article: 28.8] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Affiliation(s)
- Jessica L Blois
- School of Natural Sciences, University of California, Merced, Merced, CA 95343, USA.
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Corlett RT, Westcott DA. Will plant movements keep up with climate change? Trends Ecol Evol 2013; 28:482-8. [PMID: 23721732 DOI: 10.1016/j.tree.2013.04.003] [Citation(s) in RCA: 302] [Impact Index Per Article: 27.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2012] [Revised: 04/16/2013] [Accepted: 04/25/2013] [Indexed: 11/16/2022]
Abstract
In the face of anthropogenic climate change, species must acclimate, adapt, move, or die. Although some species are moving already, their ability to keep up with the faster changes expected in the future is unclear. 'Migration lag' is a particular concern with plants, because it could threaten both biodiversity and carbon storage. Plant movements are not realistically represented in models currently used to predict future vegetation and carbon-cycle feedbacks, so there is an urgent need to understand how much of a problem failure to track climate change is likely to be. Therefore, in this review, we compare how fast plants need to move with how fast they can move; that is, the velocity of climate change with the velocity of plant movement.
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Affiliation(s)
- Richard T Corlett
- Center for Integrative Conservation, Xishuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Menglun, Mengla, Yunnan 666303, China.
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26
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Mokany K, Harwood TD, Ferrier S. Comparing habitat configuration strategies for retaining biodiversity under climate change. J Appl Ecol 2013. [DOI: 10.1111/1365-2664.12038] [Citation(s) in RCA: 21] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Karel Mokany
- CSIRO Ecosystem Sciences; Climate Adaptation Flagship; PO Box 1700 Canberra ACT 2601 Australia
| | - Thomas D. Harwood
- CSIRO Ecosystem Sciences; Climate Adaptation Flagship; PO Box 1700 Canberra ACT 2601 Australia
| | - Simon Ferrier
- CSIRO Ecosystem Sciences; Climate Adaptation Flagship; PO Box 1700 Canberra ACT 2601 Australia
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Jeltsch F, Bonte D, Pe'er G, Reineking B, Leimgruber P, Balkenhol N, Schröder B, Buchmann CM, Mueller T, Blaum N, Zurell D, Böhning-Gaese K, Wiegand T, Eccard JA, Hofer H, Reeg J, Eggers U, Bauer S. Integrating movement ecology with biodiversity research - exploring new avenues to address spatiotemporal biodiversity dynamics. MOVEMENT ECOLOGY 2013; 1:6. [PMID: 25709820 PMCID: PMC4337763 DOI: 10.1186/2051-3933-1-6] [Citation(s) in RCA: 107] [Impact Index Per Article: 9.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/11/2012] [Accepted: 06/03/2013] [Indexed: 05/03/2023]
Abstract
Movement of organisms is one of the key mechanisms shaping biodiversity, e.g. the distribution of genes, individuals and species in space and time. Recent technological and conceptual advances have improved our ability to assess the causes and consequences of individual movement, and led to the emergence of the new field of 'movement ecology'. Here, we outline how movement ecology can contribute to the broad field of biodiversity research, i.e. the study of processes and patterns of life among and across different scales, from genes to ecosystems, and we propose a conceptual framework linking these hitherto largely separated fields of research. Our framework builds on the concept of movement ecology for individuals, and demonstrates its importance for linking individual organismal movement with biodiversity. First, organismal movements can provide 'mobile links' between habitats or ecosystems, thereby connecting resources, genes, and processes among otherwise separate locations. Understanding these mobile links and their impact on biodiversity will be facilitated by movement ecology, because mobile links can be created by different modes of movement (i.e., foraging, dispersal, migration) that relate to different spatiotemporal scales and have differential effects on biodiversity. Second, organismal movements can also mediate coexistence in communities, through 'equalizing' and 'stabilizing' mechanisms. This novel integrated framework provides a conceptual starting point for a better understanding of biodiversity dynamics in light of individual movement and space-use behavior across spatiotemporal scales. By illustrating this framework with examples, we argue that the integration of movement ecology and biodiversity research will also enhance our ability to conserve diversity at the genetic, species, and ecosystem levels.
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Affiliation(s)
- Florian Jeltsch
- Department of Plant Ecology and Nature Conservation, Intitute of Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, 14469 Potsdam, Germany ; Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, D-14195 Germany
| | - Dries Bonte
- Department of Biology, Ghent University, K.L. Ledeganckstraat 35, Gent, 9000 Belgium
| | - Guy Pe'er
- Department of Conservation Biology, UFZ - Helmholtz Centre for Environmental Research, Permoserstr 15, Leipzig, 04318 Germany
| | - Björn Reineking
- Biogeographical Modelling, BayCEER, University of Bayreuth, Universitätsstr. 30, Bayreuth, 95447 Germany ; Irstea, UR EMGR Écosystèmes Montagnards, 2 rue de la Papeterie-BP 76, St-Martin-d'Hères, F-38402 France
| | - Peter Leimgruber
- National Zoological Park, Smithsonian, Conservation Biology Institute, 1500 Remount Road, Front Royal, VA 22630 USA
| | - Niko Balkenhol
- Department of Forest Zoology and Forest Conservation, University of Göttingen, Buesgenweg 3, Göttingen, 37077 Germany
| | - Boris Schröder
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, D-14195 Germany ; Landscape Ecology, Technische Universität München, Emil-Ramann-Str. 6, 85354 Freising-Weihenstephan, Germany ; Environmental Systems Analysis, Institute of Geoecology, Technical University of Braunschweig, Langer Kamp 19c, Braunschweig, 38106 Germany
| | - Carsten M Buchmann
- Department of Landscape Ecology, UFZ - Helmholtz Centre for Environmental Research, Permoserstr. 15, Leipzig, 04318 Germany
| | - Thomas Mueller
- National Zoological Park, Smithsonian, Conservation Biology Institute, 1500 Remount Road, Front Royal, VA 22630 USA ; Department of Biology, University of Maryland, College Park, MD 20742 USA
| | - Niels Blaum
- Department of Plant Ecology and Nature Conservation, Intitute of Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, 14469 Potsdam, Germany
| | - Damaris Zurell
- Department of Plant Ecology and Nature Conservation, Intitute of Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, 14469 Potsdam, Germany
| | - Katrin Böhning-Gaese
- Biodiversity and Climate Research Centre (BiK-F), Senckenberg Gesellschaft für Naturforschung, Senckenberganlage 25, Frankfurt (Main), 60325 Germany ; Department of Biological Sciences, Goethe Universität, Max-von-Laue-Straße 9, Frankfurt (Main), 60438 Germany
| | - Thorsten Wiegand
- Department of Ecological Modelling, Helmholz Centre for Environmental Research (UFZ), Permoserstr. 15, Leipzig, 04318 Germany
| | - Jana A Eccard
- Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, D-14195 Germany ; Department of Animal Ecology, Institute of Biochemistry and Biology, Universität Potsdam, Maulbeerallee 1, Potsdam, 14469 Germany
| | - Heribert Hofer
- Department of Evolutionary Ecology, Leibniz Institute for Zoo and Wildlife Research (IZW) in the Forschungsverbund Berlin e.V., Alfred-Kowalke-Str. 17, Berlin, 10315 Germany
| | - Jette Reeg
- Department of Plant Ecology and Nature Conservation, Intitute of Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, 14469 Potsdam, Germany
| | - Ute Eggers
- Department of Plant Ecology and Nature Conservation, Intitute of Biochemistry and Biology, University of Potsdam, Maulbeerallee 2, 14469 Potsdam, Germany
| | - Silke Bauer
- Department of Animal Ecology, Netherlands Institute of Ecology (NIOO-KNAW), P.O. Box 50, Wageningen, AB 6700 The Netherlands ; Swiss Ornithological Institute, Seerose 1, Sempach, 6204 Switzerland
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