Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies. (12th May 2019)
- Record Type:
- Journal Article
- Title:
- Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies. (12th May 2019)
- Main Title:
- Multidimensional ecological analyses demonstrate how interactions between functional traits shape fitness and life history strategies
- Authors:
- Pistón, Nuria
de Bello, Francesco
Dias, André T. C.
Götzenberger, Lars
Rosado, Bruno H. P.
de Mattos, Eduardo A.
Salguero‐Gómez, Roberto
Carmona, Carlos P. - Editors:
- Cornelissen, Hans
- Abstract:
- Abstract: Traditionally, trait‐based studies have explored single‐trait‐fitness relationships. However, this approximation in the study of fitness components is often too simplistic, given that fitness is determined by the interplay of multiple traits, which could even lead to multiple functional strategies with comparable fitness (i.e. alternative designs). Here we suggest that an analytical framework using boosted regression trees (BRT) can prove more informative to test hypotheses on trait combinations compared to standard linear models. We use two published datasets for comparisons: a botanical garden dataset with 557 plant species (Herben, 2012, Journal of Ecology, 100, 1522) and an observational dataset with 83 plant species (Adler, 2014, Proceedings of the National Academy of Sciences, 111, 740). Using the observational dataset, we found that BRTs predict the role of traits on the relative importance of survival, growth and reproduction for population growth rate better than linear models do. Moreover, we split species cultivated in different habitats within the botanical garden and observed that seed and vegetative reproduction depended on trait combinations in most habitats. Our analyses suggest that, while not all traits impact fitness components to the same degree, it is crucial to consider traits that represent different ecological dimensions. Synthesis . The analysis of trait combinations, and corresponding alternative designs via BRTs, represent a promisingAbstract: Traditionally, trait‐based studies have explored single‐trait‐fitness relationships. However, this approximation in the study of fitness components is often too simplistic, given that fitness is determined by the interplay of multiple traits, which could even lead to multiple functional strategies with comparable fitness (i.e. alternative designs). Here we suggest that an analytical framework using boosted regression trees (BRT) can prove more informative to test hypotheses on trait combinations compared to standard linear models. We use two published datasets for comparisons: a botanical garden dataset with 557 plant species (Herben, 2012, Journal of Ecology, 100, 1522) and an observational dataset with 83 plant species (Adler, 2014, Proceedings of the National Academy of Sciences, 111, 740). Using the observational dataset, we found that BRTs predict the role of traits on the relative importance of survival, growth and reproduction for population growth rate better than linear models do. Moreover, we split species cultivated in different habitats within the botanical garden and observed that seed and vegetative reproduction depended on trait combinations in most habitats. Our analyses suggest that, while not all traits impact fitness components to the same degree, it is crucial to consider traits that represent different ecological dimensions. Synthesis . The analysis of trait combinations, and corresponding alternative designs via BRTs, represent a promising approach for understanding and managing functional changes in vegetation composition through measurement of suites of relatively easily measurable traits. Abstract : The analysis of trait combinations, and corresponding alternative designs via BRTs, represent a promising approach for understanding and managing functional changes in vegetation composition through measurement of suites of relatively easily measurable traits. … (more)
- Is Part Of:
- Journal of ecology. Volume 107:Number 5(2019:Sep.)
- Journal:
- Journal of ecology
- Issue:
- Volume 107:Number 5(2019:Sep.)
- Issue Display:
- Volume 107, Issue 5 (2019)
- Year:
- 2019
- Volume:
- 107
- Issue:
- 5
- Issue Sort Value:
- 2019-0107-0005-0000
- Page Start:
- 2317
- Page End:
- 2328
- Publication Date:
- 2019-05-12
- Subjects:
- alternative design -- boosted regression tree (BRT) -- elasticity -- fitness -- functional trait -- population growth rate -- trade‐off -- vegetative reproduction
Plant ecology -- Periodicals
577.05 - Journal URLs:
- http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2745 ↗
http://onlinelibrary.wiley.com/ ↗ - DOI:
- 10.1111/1365-2745.13190 ↗
- Languages:
- English
- ISSNs:
- 0022-0477
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4972.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 25937.xml