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Isolation predicts compositional change after discrete disturbances in a global meta-study

Isolation predicts compositional change after discrete disturbances in a global meta-study
Isolation predicts compositional change after discrete disturbances in a global meta-study
Globally, anthropogenic disturbances are occurring at unprecedented rates and over extensive spatial and temporal scales. Human activities also affect natural disturbances, prompting shifts in their timing and intensities. Thus, there is an urgent need to understand and predict the response of ecosystems to disturbance. In this study, we investigated whether there are general determinants of community response to disturbance across different community types, locations, and disturbance events. We compiled 14 case studies of community response to disturbance from four continents, twelve aquatic and terrestrial ecosystem types, and eight different types of disturbance. We used community compositional differences and species richness to indicate community response. We used mixed-effects modeling to test the relationship between each of these response metrics and four potential explanatory factors: regional species pool size, isolation, number of generations passed, and relative disturbance intensity. We found that compositional similarity was higher between pre- and post-disturbance communities when the disturbed community was connected to adjacent undisturbed habitat. The number of generations that had passed since the disturbance event was a significant, but weak, predictor of community compositional change; two communities were responsible for the observed relationship. We found no significant relationships between the factors we tested and changes in species richness. To our knowledge, this is the first attempt to search for general drivers of community resilience from a diverse set of case studies. The strength of the relationship between compositional change and isolation suggests that it may be informative in resilience research and biodiversity management.
0906-7590
1-11
Shackelford, Nancy
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Starzomski, Brian M.
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Banning, Natasha C.
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Battaglia, Loretta L.
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Becker, Alistair
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Bellingham, Peter J.
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Bestelmeyer, Brandon
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Catford, Jane A.
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Dwyer, John M.
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Dynesius, Mats
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Gilmour, James
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Hallett, Lauren M.
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Hobbs, Richard J.
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Price, Jodi
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Sasaki, Takehiro
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Tanner, Edmund V.J.
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Standish, Rachel J.
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Shackelford, Nancy
29b017cf-8072-4e3d-a4c7-bac3260f9569
Starzomski, Brian M.
c2adcb13-2c6d-4f9a-b0b2-43439b54d1b7
Banning, Natasha C.
de3331ca-9775-4c6f-8a2e-605aa627101b
Battaglia, Loretta L.
e96e6fa8-0d9d-4a69-b070-734149549660
Becker, Alistair
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Bellingham, Peter J.
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Bestelmeyer, Brandon
ce222117-36e4-45f6-bbdf-b3305b141d8e
Catford, Jane A.
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Dwyer, John M.
048e25d0-e7b2-4296-907d-3091aaecb602
Dynesius, Mats
67a0fd3d-3038-474e-be9a-4e2bf7483c8c
Gilmour, James
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Hallett, Lauren M.
f5132a52-0054-4029-96a6-a8afca6ccc76
Hobbs, Richard J.
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Price, Jodi
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Sasaki, Takehiro
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Tanner, Edmund V.J.
deddb2dd-b63b-4cd5-95e6-604d211ab5b8
Standish, Rachel J.
c900e3c1-e482-4486-927d-476a71f26314

Shackelford, Nancy, Starzomski, Brian M., Banning, Natasha C., Battaglia, Loretta L., Becker, Alistair, Bellingham, Peter J., Bestelmeyer, Brandon, Catford, Jane A., Dwyer, John M., Dynesius, Mats, Gilmour, James, Hallett, Lauren M., Hobbs, Richard J., Price, Jodi, Sasaki, Takehiro, Tanner, Edmund V.J. and Standish, Rachel J. (2017) Isolation predicts compositional change after discrete disturbances in a global meta-study. Ecography, 1-11. (doi:10.1111/ecog.02383).

Record type: Article

Abstract

Globally, anthropogenic disturbances are occurring at unprecedented rates and over extensive spatial and temporal scales. Human activities also affect natural disturbances, prompting shifts in their timing and intensities. Thus, there is an urgent need to understand and predict the response of ecosystems to disturbance. In this study, we investigated whether there are general determinants of community response to disturbance across different community types, locations, and disturbance events. We compiled 14 case studies of community response to disturbance from four continents, twelve aquatic and terrestrial ecosystem types, and eight different types of disturbance. We used community compositional differences and species richness to indicate community response. We used mixed-effects modeling to test the relationship between each of these response metrics and four potential explanatory factors: regional species pool size, isolation, number of generations passed, and relative disturbance intensity. We found that compositional similarity was higher between pre- and post-disturbance communities when the disturbed community was connected to adjacent undisturbed habitat. The number of generations that had passed since the disturbance event was a significant, but weak, predictor of community compositional change; two communities were responsible for the observed relationship. We found no significant relationships between the factors we tested and changes in species richness. To our knowledge, this is the first attempt to search for general drivers of community resilience from a diverse set of case studies. The strength of the relationship between compositional change and isolation suggests that it may be informative in resilience research and biodiversity management.

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Accepted/In Press date: 17 October 2016
e-pub ahead of print date: 19 January 2017
Organisations: Environmental

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Local EPrints ID: 404671
URI: http://eprints.soton.ac.uk/id/eprint/404671
ISSN: 0906-7590
PURE UUID: 3ff7c977-d084-46e6-996f-47a07b25b3b8
ORCID for Jane A. Catford: ORCID iD orcid.org/0000-0003-0582-5960

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Date deposited: 19 Jan 2017 15:17
Last modified: 15 Mar 2024 06:13

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Contributors

Author: Nancy Shackelford
Author: Brian M. Starzomski
Author: Natasha C. Banning
Author: Loretta L. Battaglia
Author: Alistair Becker
Author: Peter J. Bellingham
Author: Brandon Bestelmeyer
Author: Jane A. Catford ORCID iD
Author: John M. Dwyer
Author: Mats Dynesius
Author: James Gilmour
Author: Lauren M. Hallett
Author: Richard J. Hobbs
Author: Jodi Price
Author: Takehiro Sasaki
Author: Edmund V.J. Tanner
Author: Rachel J. Standish

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