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Predicting community persistence based on different methods of species ranking.

Michael Fowler, Mike Fowler Orcid Logo

Annales Zoologici Fennici, Volume: 42, Pages: 533 - 543

Swansea University Author: Mike Fowler Orcid Logo

Abstract

Different species in a community can be ranked according to the strength of their effect on the dynamics of the entire community. Despite a considerable research effort on community structure and the “keystone” species concept, there are still unresolved issues in this area. This work addresses the...

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Published in: Annales Zoologici Fennici
Published: 2005
URI: https://cronfa.swan.ac.uk/Record/cronfa19659
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first_indexed 2014-12-02T02:57:38Z
last_indexed 2018-02-09T04:55:27Z
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spelling 2014-12-01T10:24:07.0998912 v2 19659 2014-12-01 Predicting community persistence based on different methods of species ranking. a3a29027498d4b43a3f082a0a5ba16b4 0000-0003-1544-0407 Mike Fowler Mike Fowler true false 2014-12-01 SBI Different species in a community can be ranked according to the strength of their effect on the dynamics of the entire community. Despite a considerable research effort on community structure and the “keystone” species concept, there are still unresolved issues in this area. This work addresses the suitability of different methods of characterising community members, either by relative abundance, or different measures of competitive ability. Multi-species competitive communities were simulated to allow comparison of methods that rank community members by either their abundance or competitive ability. Results indicate that characterising species according to their relative density, rather than competitive ability, provides a more refined measure of the importance of each community member. The analysis is extended by assessing which species are most likely to be involved with cascading extinction events, showing that the species with the lowest abundance is most likely to face extinction. Here it is also shown that removal of the most abundant species, i.e. that with the greatest relative density within the community, leads to the highest probability of community collapse, with further loss of community members through cascading extinctions. The asymmetry and non-linearity of between species interactions mean that species’ ranking can change unexpectedly following species loss. These results can lead to practical recommendations in management decisions for conservation and other species managementproblems, e.g. harvesting in marine food-webs, where it may be difficult to assess relative competitive ability between species in the ecosystem Journal Article Annales Zoologici Fennici 42 533 543 31 12 2005 2005-12-31 COLLEGE NANME Biosciences COLLEGE CODE SBI Swansea University 2014-12-01T10:24:07.0998912 2014-12-01T10:24:07.0998912 Faculty of Science and Engineering School of Biosciences, Geography and Physics - Biosciences Michael Fowler 1 Mike Fowler 0000-0003-1544-0407 2
title Predicting community persistence based on different methods of species ranking.
spellingShingle Predicting community persistence based on different methods of species ranking.
Mike Fowler
title_short Predicting community persistence based on different methods of species ranking.
title_full Predicting community persistence based on different methods of species ranking.
title_fullStr Predicting community persistence based on different methods of species ranking.
title_full_unstemmed Predicting community persistence based on different methods of species ranking.
title_sort Predicting community persistence based on different methods of species ranking.
author_id_str_mv a3a29027498d4b43a3f082a0a5ba16b4
author_id_fullname_str_mv a3a29027498d4b43a3f082a0a5ba16b4_***_Mike Fowler
author Mike Fowler
author2 Michael Fowler
Mike Fowler
format Journal article
container_title Annales Zoologici Fennici
container_volume 42
container_start_page 533
publishDate 2005
institution Swansea University
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Biosciences, Geography and Physics - Biosciences{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Biosciences, Geography and Physics - Biosciences
document_store_str 0
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description Different species in a community can be ranked according to the strength of their effect on the dynamics of the entire community. Despite a considerable research effort on community structure and the “keystone” species concept, there are still unresolved issues in this area. This work addresses the suitability of different methods of characterising community members, either by relative abundance, or different measures of competitive ability. Multi-species competitive communities were simulated to allow comparison of methods that rank community members by either their abundance or competitive ability. Results indicate that characterising species according to their relative density, rather than competitive ability, provides a more refined measure of the importance of each community member. The analysis is extended by assessing which species are most likely to be involved with cascading extinction events, showing that the species with the lowest abundance is most likely to face extinction. Here it is also shown that removal of the most abundant species, i.e. that with the greatest relative density within the community, leads to the highest probability of community collapse, with further loss of community members through cascading extinctions. The asymmetry and non-linearity of between species interactions mean that species’ ranking can change unexpectedly following species loss. These results can lead to practical recommendations in management decisions for conservation and other species managementproblems, e.g. harvesting in marine food-webs, where it may be difficult to assess relative competitive ability between species in the ecosystem
published_date 2005-12-31T03:23:08Z
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