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Elevational trends in life histories: revising the pace‐of‐life framework
Author(s) -
Hille Sabine M.,
Cooper Caren B.
Publication year - 2015
Publication title -
biological reviews
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 4.993
H-Index - 165
eISSN - 1469-185X
pISSN - 1464-7931
DOI - 10.1111/brv.12106
Subject(s) - pace , biology , life history theory , trait , reproduction , ecology , trade off , evolutionary biology , economic geography , life history , geography , geodesy , computer science , programming language
Life‐history traits in birds, such as lifespan, age at maturity, and rate of reproduction, vary across environments and in combinations imposed by trade‐offs and limitations of physiological mechanisms. A plethora of studies have described the diversity of traits and hypothesized selection pressures shaping components of the survival–reproduction trade‐off. Life‐history variation appears to fall along a slow–fast continuum, with slow pace characterized by higher investment in survival over reproduction and fast pace characterized by higher investment in reproduction over survival. The Pace‐of‐Life Syndrome ( POLS ) is a framework to describe the slow–fast axis of variation in life‐history traits and physiological traits. The POLS corresponds to latitudinal gradients, with tropical birds exhibiting a slow pace of life. We examined four possible ways that the traits of high‐elevation birds might correspond to the POLS continuum: ( i ) rapid pace, ( ii ) tropical slow pace, ( iii ) novel elevational pace, or ( iv ) constrained pace. Recent studies reveal that birds breeding at high elevations in temperate zones exhibit a combination of traits creating a unique elevational pace of life with a central trade‐off similar to a slow pace but physiological trade‐offs more similar to a fast pace. A paucity of studies prevents consideration of the possibility of a constrained pace of life. We propose extending the POLS framework to include trait variation of elevational clines to help to investigate complexity in global geographic patterns.

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