Integrating the underlying structure of stochasticity into community ecology
Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on s...
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| Veröffentlicht in: | Ecology (Durham) Jg. 101; H. 2; S. 1 - 17 |
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| Hauptverfasser: | , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
United States
John Wiley and Sons, Inc
01.02.2020
Ecological Society of America John Wiley and Sons Inc |
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| ISSN: | 0012-9658, 1939-9170, 1939-9170 |
| Online-Zugang: | Volltext |
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| Abstract | Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics |
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| AbstractList | Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics. Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics.Stochasticity is a core component of ecology, as it underlies key processes that structure and create variability in nature. Despite its fundamental importance in ecological systems, the concept is often treated as synonymous with unpredictability in community ecology, and studies tend to focus on single forms of stochasticity rather than taking a more holistic view. This has led to multiple narratives for how stochasticity mediates community dynamics. Here, we present a framework that describes how different forms of stochasticity (notably demographic and environmental stochasticity) combine to provide underlying and predictable structure in diverse communities. This framework builds on the deep ecological understanding of stochastic processes acting at individual and population levels and in modules of a few interacting species. We support our framework with a mathematical model that we use to synthesize key literature, demonstrating that stochasticity is more than simple uncertainty. Rather, stochasticity has profound and predictable effects on community dynamics that are critical for understanding how diversity is maintained. We propose next steps that ecologists might use to explore the role of stochasticity for structuring communities in theoretical and empirical systems, and thereby enhance our understanding of community dynamics. |
| Author | Sullivan, Lauren L. Abbott, Karen C. Chase, Jonathan M. Shoemaker, Lauren G. Satterlee, Sean Yang, Qiang Wang, Xugao May, Felix Donohue, Ian Williams, Ryan J. Chu, Chengjin Huth, Andreas HilleRisLambers, Janneke James, Aubrie R. M. Taubert, Franziska Cabral, Juliano S. Wiegand, Thorsten Mayfield, Margaret M. Harpole, W. Stanley Muthukrishnan, Ranjan Kraft, Nathan J. B. |
| AuthorAffiliation | 22 CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology Chinese Academy of Sciences Shenyang 110016 China 21 Department of Ecology, Evolution, and Organismal Biology Iowa State University 251 Bessey Hall Ames Iowa 50011 USA 3 Department of Ecology and Evolutionary Biology University of Colorado 1900 Pleasant Street Boulder Colorado 80309 USA 10 Institute for Computer Science Martin Luther University Halle-Wittenberg Halle 06099 Germany 1 Department of Botany University of Wyoming 1000 E. University Ave. Laramie Wyoming 82017 USA 20 Department of Fisheries, Wildlife, and Conservation Biology University of Minnesota 2003 Upper Buford Circle St. Paul Minnesota 55108 USA 16 Department of Ecology and Evolutionary Biology Cornell University E145 Corson Hall Ithaca New York 14853 USA 6 Synthesis Centre of the German Centre for Integrative Biodiversity Research (sDiv) Halle-Jena-Leipzig Deutscher Platz 5e Leipzig 04103 Germany 7 Ecosystem Modeling, Center of Computation an |
| AuthorAffiliation_xml | – name: 20 Department of Fisheries, Wildlife, and Conservation Biology University of Minnesota 2003 Upper Buford Circle St. Paul Minnesota 55108 USA – name: 22 CAS Key Laboratory of Forest Ecology and Management, Institute of Applied Ecology Chinese Academy of Sciences Shenyang 110016 China – name: 17 Department of Ecology and Evolutionary Biology University of California, Los Angeles 621 Charles E. Young Drive East, P.O. Box 957246 Los Angeles CA 90095 USA – name: 19 Environmental Resilience Institute Indiana University 717 E 8th St Bloomington Indiana 47408 USA – name: 14 Institute of Environmental Research Systems University of Osnabrück P.O. Box 44 69,49069 Osnabrück Germany – name: 21 Department of Ecology, Evolution, and Organismal Biology Iowa State University 251 Bessey Hall Ames Iowa 50011 USA – name: 8 The University of Queensland School of Biological Sciences Goddard Building Brisbane Queensland 4072 Australia – name: 11 Department of Ecology, State Key Laboratory of Biocontrol and School of Life Sciences Sun Yat-sen University 510275 Guangzhou Guangdong China – name: 23 Department of Biology University of Konstanz Universitätsstraße 10 78464 Konstanz Germany – name: 9 German Centre for Integrative Biodiversity Research (iDiv) Deutscher Platz 5e Leipzig 04103 Germany – name: 15 Department of Biology University of Washington Box 351800 Seattle WA 98195 USA – name: 5 Department of Zoology, School of Natural Sciences Trinity College College Green Dublin 2 Ireland – name: 12 Helmholtz Center for Environmental Research–UFZ Permoserstrasse 15 04318 Leipzig Germany – name: 13 Institute of Biology Martin Luther University Halle-Wittenberg Am Kirchtor 1 06108 Halle (Saale) Germany – name: 6 Synthesis Centre of the German Centre for Integrative Biodiversity Research (sDiv) Halle-Jena-Leipzig Deutscher Platz 5e Leipzig 04103 Germany – name: 1 Department of Botany University of Wyoming 1000 E. University Ave. Laramie Wyoming 82017 USA – name: 24 Department of Biology Case Western Reserve University 10900 Euclid Avenue Cleveland OH 44106 USA – name: 2 Department of Ecology, Evolution, and Behavior University of Minnesota 1987 Upper Buford Circle Saint Paul Minnesota 55108 USA – name: 10 Institute for Computer Science Martin Luther University Halle-Wittenberg Halle 06099 Germany – name: 7 Ecosystem Modeling, Center of Computation and Theoretical Biology University of Würzburg Emil-Fischer-Strasse 32 97074 Würzburg Germany – name: 16 Department of Ecology and Evolutionary Biology Cornell University E145 Corson Hall Ithaca New York 14853 USA – name: 3 Department of Ecology and Evolutionary Biology University of Colorado 1900 Pleasant Street Boulder Colorado 80309 USA – name: 4 Division of Biological Sciences University of Missouri 105 Tucker Hall Columbia Missouri 65211 USA – name: 18 Center for Methodology Leuphana University Lüneburg Universitätsallee 1 D‐21335 Lüneburg Germany |
| Author_xml | – sequence: 1 givenname: Lauren G. surname: Shoemaker fullname: Shoemaker, Lauren G. – sequence: 2 givenname: Lauren L. surname: Sullivan fullname: Sullivan, Lauren L. – sequence: 3 givenname: Ian surname: Donohue fullname: Donohue, Ian – sequence: 4 givenname: Juliano S. surname: Cabral fullname: Cabral, Juliano S. – sequence: 5 givenname: Ryan J. surname: Williams fullname: Williams, Ryan J. – sequence: 6 givenname: Margaret M. surname: Mayfield fullname: Mayfield, Margaret M. – sequence: 7 givenname: Jonathan M. surname: Chase fullname: Chase, Jonathan M. – sequence: 8 givenname: Chengjin surname: Chu fullname: Chu, Chengjin – sequence: 9 givenname: W. Stanley surname: Harpole fullname: Harpole, W. Stanley – sequence: 10 givenname: Andreas surname: Huth fullname: Huth, Andreas – sequence: 11 givenname: Janneke surname: HilleRisLambers fullname: HilleRisLambers, Janneke – sequence: 12 givenname: Aubrie R. M. surname: James fullname: James, Aubrie R. M. – sequence: 13 givenname: Nathan J. B. surname: Kraft fullname: Kraft, Nathan J. B. – sequence: 14 givenname: Felix surname: May fullname: May, Felix – sequence: 15 givenname: Ranjan surname: Muthukrishnan fullname: Muthukrishnan, Ranjan – sequence: 16 givenname: Sean surname: Satterlee fullname: Satterlee, Sean – sequence: 17 givenname: Franziska surname: Taubert fullname: Taubert, Franziska – sequence: 18 givenname: Xugao surname: Wang fullname: Wang, Xugao – sequence: 19 givenname: Thorsten surname: Wiegand fullname: Wiegand, Thorsten – sequence: 20 givenname: Qiang surname: Yang fullname: Yang, Qiang – sequence: 21 givenname: Karen C. surname: Abbott fullname: Abbott, Karen C. |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/31652337$$D View this record in MEDLINE/PubMed |
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| Copyright | 2019 The Authors 2019 The Authors. published by Wiley Periodicals, Inc. on behalf of Ecological Society of America 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. 2019. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
| Copyright_xml | – notice: 2019 The Authors – notice: 2019 The Authors. published by Wiley Periodicals, Inc. on behalf of Ecological Society of America – notice: 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. – notice: 2019. This article is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. |
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| Keywords | diversity environmental stochasticity demographic stochasticity scale distribution uncertainty population dynamics autocorrelation |
| Language | English |
| License | Attribution 2019 The Authors. Ecology published by Wiley Periodicals, Inc. on behalf of Ecological Society of America. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited. |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Corresponding Editor: Tom E. X. Miller. |
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| SubjectTerms | autocorrelation Community ecology CONCEPTS & SYNTHESIS demographic stochasticity Demographics distribution diversity Ecological monitoring Ecology Ecosystem environmental stochasticity Mathematical models Models, Biological Models, Theoretical Population Dynamics Population levels scale Stochastic Processes Stochasticity uncertainty |
| Title | Integrating the underlying structure of stochasticity into community ecology |
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