B. Yguel, H. Jactel, I. Pearse, D. Moen, M. Winter, J. Hortal, M. Helmus, I. Kühn, S. Pavoine, O. Purschke, E. Weiher, C. Violle, W. Ozinga, M. Brändle, I. Bartish, A. Prinzing
{"title":"The Evolutionary Legacy of Diversification Predicts Ecosystem Function","authors":"B. Yguel, H. Jactel, I. Pearse, D. Moen, M. Winter, J. Hortal, M. Helmus, I. Kühn, S. Pavoine, O. Purschke, E. Weiher, C. Violle, W. Ozinga, M. Brändle, I. Bartish, A. Prinzing","doi":"10.1086/687964","DOIUrl":null,"url":null,"abstract":"Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the “ELDERness surfaces.” These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning.","PeriodicalId":90979,"journal":{"name":"","volume":"28 1","pages":"398 - 410"},"PeriodicalIF":0.0,"publicationDate":"2016-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"13","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1086/687964","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 13
Abstract
Theory suggests that the structure of evolutionary history represented in a species community may affect its functioning, but phylogenetic diversity metrics do not allow for the identification of major differences in this structure. Here we propose a new metric, ELDERness (for Evolutionary Legacy of DivERsity) to estimate evolutionary branching patterns within communities by fitting a polynomial function to lineage-through-time (LTT) plots. We illustrate how real and simulated community branching patterns can be more correctly described by ELDERness and can successfully predict ecosystem functioning. In particular, the evolutionary history of branching patterns can be encapsulated by the parameters of third-order polynomial functions and further measured through only two parameters, the “ELDERness surfaces.” These parameters captured variation in productivity of a grassland community better than existing phylogenetic diversity or diversification metrics and independent of species richness or presence of nitrogen fixers. Specifically, communities with small ELDERness surfaces (constant accumulation of lineages through time in LTT plots) were more productive, consistent with increased productivity resulting from complementary lineages combined with niche filling within lineages. Overall, while existing phylogenetic diversity metrics remain useful in many contexts, we suggest that our ELDERness approach better enables testing hypotheses that relate complex patterns of macroevolutionary history represented in local communities to ecosystem functioning.