Craig R. Allen
Current Organizations / Institutes
The organizations/institutes from the scholar's latest article
Previous Organizations / Institutes
The organizations / institutes from the scholar's other articles in the past ten years
Research Subjects
Craig R. Allen has a total of 49 co-authors. Here are the top co-authors by number of shared publications:
- Ahjond S. Garmestani
United States Environmental Protection Agency
14 shared publications - David G. Angeler
Consejo Superior de Investigaciones Científicas, Museo Nacional de Ciencias Naturales (MNCN‐CSIC) Madrid Spain
5 shared publications - Hannah E. Birge
Nebraska Cooperative Fish and Wildlife Research Unit, and School of Natural Resources, University of Nebraska, Lincoln, NE 68583, USA
4 shared publications - Lance Gunderson
Department of Environmental Sciences, Emory University, Atlanta, GA, USA
3 shared publications - Barbara Cosens
University of Idaho
2 shared publications - Craig A. Stow
Great Lakes Environmental Research Laboratory National Oceanic and Atmospheric Administration Ann Arbor MI USA
2 shared publications
Latest Publications
- 20 December 2016
- Published by Springer Nature in Biological Invasions
- Vol. 19 (2) , 713-722
The invasive ant, Solenopsis invicta, reduces herpetofauna richness and abundance
- 20 December 2016
- Published by Springer Nature in Biological Invasions
- Vol. 19 (2) , 713-722
The invasive ant, Solenopsis invicta, reduces herpetofauna richness and abundance
- Open Access
- 20 December 2016
- Published by Wiley in Ecology Letters
- Vol. 20 (1) , 19-32
Detecting spatial regimes in ecosystems
Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory‐based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.
- 20 December 2016
- Published by Wiley in Ecology Letters
- Vol. 20 (1) , 19-32
Open AccessDetecting spatial regimes in ecosystems
Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory‐based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.
- 1 December 2016
- Published by Elsevier in Journal of Environmental Management
- Vol. 183, 343-352
Adaptive management for ecosystem services
- 1 December 2016
- Published by Elsevier in Journal of Environmental Management
- Vol. 183, 343-352
Adaptive management for ecosystem services
- Open Access
- 26 August 2016
- Published by MDPI AG in Sustainability
- Vol. 8 (9) , 844
Avoiding Decline: Fostering Resilience and Sustainability in Midsize Cities
Eighty-five percent of United States citizens live in urban areas. However, research surrounding the resilience and sustainability of complex urban systems focuses largely on coastal megacities (>1 million people). Midsize cities differ from their larger counterparts due to tight urban-rural feedbacks with their immediate natural environments that result from heavy reliance and close management of local ecosystem services. They also may be less path-dependent than larger cities due to shorter average connection length among system components, contributing to higher responsiveness among social, infrastructural, and ecological feedbacks. These distinct midsize city features call for a framework that organizes information and concepts concerning the sustainability of midsize cities specifically. We argue that an integrative approach is necessary to capture properties emergent from the complex interactions of the social, infrastructural, and ecological subsystems that comprise a city system. We suggest approaches to estimate the relative resilience of midsize cities, and include an example assessment to illustrate one such estimation approach. Resilience assessments of a midsize city can be used to examine why some cities end up on sustainable paths while others diverge to unsustainable paths, and which feedbacks may be partially responsible. They also provide insight into how city planners and decision makers can use information about the resilience of midsize cities undergoing growth or shrinkage relative to their larger and smaller counterparts, to transform them into long-term, sustainable social-ecological systems.
- 26 August 2016
- Published by MDPI AG in Sustainability
- Vol. 8 (9) , 844
Open AccessAvoiding Decline: Fostering Resilience and Sustainability in Midsize Cities
Eighty-five percent of United States citizens live in urban areas. However, research surrounding the resilience and sustainability of complex urban systems focuses largely on coastal megacities (>1 million people). Midsize cities differ from their larger counterparts due to tight urban-rural feedbacks with their immediate natural environments that result from heavy reliance and close management of local ecosystem services. They also may be less path-dependent than larger cities due to shorter average connection length among system components, contributing to higher responsiveness among social, infrastructural, and ecological feedbacks. These distinct midsize city features call for a framework that organizes information and concepts concerning the sustainability of midsize cities specifically. We argue that an integrative approach is necessary to capture properties emergent from the complex interactions of the social, infrastructural, and ecological subsystems that comprise a city system. We suggest approaches to estimate the relative resilience of midsize cities, and include an example assessment to illustrate one such estimation approach. Resilience assessments of a midsize city can be used to examine why some cities end up on sustainable paths while others diverge to unsustainable paths, and which feedbacks may be partially responsible. They also provide insight into how city planners and decision makers can use information about the resilience of midsize cities undergoing growth or shrinkage relative to their larger and smaller counterparts, to transform them into long-term, sustainable social-ecological systems.
- 13 May 2016
- Published by Wiley in Journal of Applied Ecology
- Vol. 53 (3) , 625-635
Quantifying spatial resilience
Summary: Anthropogenic stressors affect the ecosystems upon which humanity relies. In some cases when resilience is exceeded, relatively small linear changes in stressors can cause relatively abrupt and nonlinear changes in ecosystems. Ecological regime shifts occur when resilience is exceeded and ecosystems enter a new local equilibrium that differs in its structure and function from the previous state. Ecological resilience, the amount of disturbance that a system can withstand before it shifts into an alternative stability domain, is an important framework for understanding and managing ecological systems subject to collapse and reorganization. Recently, interest in the influence of spatial characteristics of landscapes on resilience has increased. Understanding how spatial structure and variation in relevant variables in landscapes affects resilience to disturbance will assist with resilience quantification, and with local and regional management. Synthesis and applications. We review the history and current status of spatial resilience in the research literature, expand upon existing literature to develop a more operational definition of spatial resilience, introduce additional elements of a spatial analytical approach to understanding resilience, present a framework for resilience operationalization and provide an overview of critical knowledge and technology gaps that should be addressed for the advancement of spatial resilience theory and its applications to management and conservation.
- 13 May 2016
- Published by Wiley in Journal of Applied Ecology
- Vol. 53 (3) , 625-635
Quantifying spatial resilience
Summary: Anthropogenic stressors affect the ecosystems upon which humanity relies. In some cases when resilience is exceeded, relatively small linear changes in stressors can cause relatively abrupt and nonlinear changes in ecosystems. Ecological regime shifts occur when resilience is exceeded and ecosystems enter a new local equilibrium that differs in its structure and function from the previous state. Ecological resilience, the amount of disturbance that a system can withstand before it shifts into an alternative stability domain, is an important framework for understanding and managing ecological systems subject to collapse and reorganization. Recently, interest in the influence of spatial characteristics of landscapes on resilience has increased. Understanding how spatial structure and variation in relevant variables in landscapes affects resilience to disturbance will assist with resilience quantification, and with local and regional management. Synthesis and applications. We review the history and current status of spatial resilience in the research literature, expand upon existing literature to develop a more operational definition of spatial resilience, introduce additional elements of a spatial analytical approach to understanding resilience, present a framework for resilience operationalization and provide an overview of critical knowledge and technology gaps that should be addressed for the advancement of spatial resilience theory and its applications to management and conservation.
- 25 April 2015
- Published by Springer Nature
- p. 255-262
Adaptive Management of Social-Ecological Systems: The Path Forward
- 25 April 2015
- Published by Springer Nature
- p. 255-262
Adaptive Management of Social-Ecological Systems: The Path Forward
- 31 December 2014
- Published by Columbia University Press
- p. 1-14
Introduction. Social-Ecological Resilience and Law
- 31 December 2014
- Published by Columbia University Press
- p. 1-14
Introduction. Social-Ecological Resilience and Law
- Open Access
- 2 October 2014
- Published by MDPI AG in Sustainability
- Vol. 6 (10) , 6925-6948
Transdisciplinary Application of Cross-Scale Resilience
The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlying discontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/ anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems.
- 2 October 2014
- Published by MDPI AG in Sustainability
- Vol. 6 (10) , 6925-6948
Open AccessTransdisciplinary Application of Cross-Scale Resilience
The cross-scale resilience model was developed in ecology to explain the emergence of resilience from the distribution of ecological functions within and across scales, and as a tool to assess resilience. We propose that the model and the underlying discontinuity hypothesis are relevant to other complex adaptive systems, and can be used to identify and track changes in system parameters related to resilience. We explain the theory behind the cross-scale resilience model, review the cases where it has been applied to non-ecological systems, and discuss some examples of social-ecological, archaeological/ anthropological, and economic systems where a cross-scale resilience analysis could add a quantitative dimension to our current understanding of system dynamics and resilience. We argue that the scaling and diversity parameters suitable for a resilience analysis of ecological systems are appropriate for a broad suite of systems where non-normative quantitative assessments of resilience are desired. Our planet is currently characterized by fast environmental and social change, and the cross-scale resilience model has the potential to quantify resilience across many types of complex adaptive systems.