Applied Functional Biology: Linking Ecological Morphology to Conservation and Management
Author(s) -
Eric J. McElroy,
Diego Sustaita,
Lance D. McBrayer
Publication year - 2020
Publication title -
integrative and comparative biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.328
H-Index - 123
eISSN - 1557-7023
pISSN - 1540-7063
DOI - 10.1093/icb/icaa076
Subject(s) - wildlife , functional ecology , ecology , conservation biology , wildlife management , wildlife conservation , biology , environmental resource management , natural (archaeology) , geography , ecosystem , paleontology , environmental science
Synopsis Many researchers work at the interface of organisms and environment. Too often, the insights that organismal, or functional, biologists can bring to the understanding of natural history, ecology, and conservation of species are overlooked. Likewise, natural resource managers are frequently focused on the management of populations and communities, while ignoring key functional traits that might explain variation in abundance and shifts in species composition at these ecological levels. Our intention for this symposium is two-fold: (1) to bring to light current and future research in functional and ecological morphology applicable to concerns and goals of wildlife management and conservation and (2) to show how such studies can result in measurable benchmarks useful to regulatory agencies. Symposium topics reveal past, present, and future collaborations between functional morphologists/biomechanists and conservation/wildlife biologists. During the SICB 2020 Annual Meeting, symposium participants demonstrated how data gathered to address fundamental questions regarding the causes and consequences of organismal form and function can also help address issues of conservation and wildlife management. Here we review how these, and other, studies of functional morphology, biomechanics, ecological development morphology and performance can inform wildlife conservation and management, principally by identifying candidate functional traits that have clear fitness consequences and population level implications.
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