Phylogenetic diversity and the functioning of ecosystems

There is an increasing interest in measuring loss of phylogenetic diversity and evolutionary distinctiveness which together depict the evolutionary history of conservation interest. Those losses are assessed through the evolutionary relationships between species and species threat status or extinction probabilities. Yet, available information is not always sufficient to quantify the threat status of species that are then classified as data deficient. Data‐deficient species are a crucial issue as they cause incomplete assessments of the loss of phylogenetic diversity and evolutionary distinctiveness. We aimed to explore the potential bias caused by data‐deficient species in estimating four widely used indices: HEDGE, EDGE, PDloss, and Expected PDloss. Second, we tested four different widely applicable and multitaxa imputation methods and their potential to minimize the bias for those four indices. Two methods are based on a best‐ vs. worst‐case extinction scenarios, one is based on the frequency distribution of threat status within a taxonomic group and one is based on correlates of extinction risks. We showed that data‐deficient species led to important bias in predictions of evolutionary history loss (especially high underestimation when they were removed). This issue was particularly important when data‐deficient species tended to be clustered in the tree of life. The imputation method based on correlates of extinction risks, especially geographic range size, had the best performance and enabled us to improve risk assessments. Solving threat status of DD species can fundamentally change our understanding of loss of phylogenetic diversity. We found that this loss could be substantially higher than previously found in amphibians, squamate reptiles, and carnivores. We also identified species that are of high priority for the conservation of evolutionary distinctiveness.

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“…2008; Srivastava et al. 2012). On the contrary if DD species are safe, they could protect some deep branches in the tree.…”

Section: Introductionmentioning

confidence: 99%

Integrating data‐deficient species in analyses of evolutionary history loss

Véron

Penone²,

Clergeau

et al. 2016

Ecology and Evolution

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“…In the frequentist statistical framework, phylogenetic signals generate bias in ecological analysis, increasing type I error, because the differences in ecological traits among species pairs cannot be used as primary information given the phylogenetic dependence among species (Martins & Housworth, 2002). More current analytical methods are working toward using the information available in the phylogeny to measure evolutionary diversity (Tucker et al., 2017) and to model ecosystem functionality (Srivastava et al., 2012). …”

Section: Introductionmentioning

confidence: 99%

When phylogeny and ecology meet: Modeling the occurrence of Trichoptera with environmental and phylogenetic data

Godoy

Camargos

Lodi

2018

Ecology and Evolution

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Ecological studies are increasingly considering phylogenetic relationships among species. The phylogeny is used as a proxy or filter to improve statistical tests and retain evolutionary elements, such as niche conservation. We used the phylogenetic topology to improve the model for occurrence of Trichoptera genera in Cerrado (Brazilian Savanna) streams. We tested whether parameters generated by logistic models of occurrence, using phylogenetic signals, are better than models generated without phylogenetic information. We used a model with Bayesian updating to examine the influence of stream water pH and phylogenetic relationship among genera on the occurrence of Trichoptera genera. Then, we compared this model with the logistic model for each Trichoptera genus. The probability of occurrence of most genera increased with water pH, and the phylogeny‐based explicit logistic model improved the parameters estimated for observed genera. The inferred relationship between genera occurrence and stream pH improved, indicating that phylogeny adds relevant information when estimating ecological responses of organisms. Water with elevated acidity (low pH values) may be restrictive for the occurrence of Trichoptera larvae, especially if the regional streams exhibit neutral to alkaline water, as is observed in the Cerrado region. Using phylogeny‐based modeling to predict species occurrence is a prominent opportunity to extend our current statistical framework based on environmental conditions, as it enables a more precise estimation of ecological parameters.

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“…This may be due to the lower evolutionary distances among animal taxa, which translates into smaller community niche space and more similar functions compared with plants (Srivastava et al 2012), or to the overwhelming effect of external factors (food) over internal ones (physiology, metabolism, etc. ) in determining the isotopic characteristics of animal tissues (see below).…”

Section: Evolutionary Controlmentioning

confidence: 99%

“…However, historical evolutionary explanations for nutrient cycles do not appear to be incompatible with environmental determinism because the tolerance to local physical/ecological conditions is an evolved property of populations and clades (Ricklefs 2004). Importantly, clades and their intrinsic functional roles are not distributed randomly along environmental gradients (Srivastava et al 2012). Thus, focusing on present drivers without considering evolutionary history may limit the mechanistic interpretation of ecosystem responses.…”

Section: Introductionmentioning

confidence: 99%

Abiotic, Biotic, and Evolutionary Control of the Distribution of C and N Isotopes in Food Webs

Laiolo

Illera

Meléndez

et al. 2015

The American Naturalist

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Online enhancement: appendix. Dryad data: http://dx.doi.org/10.5061/dryad.g4p92.abstract: Ecosystem functioning depends on nutrient cycles and their responses to abiotic and biotic determinants, with the influence of evolutionary legacies being generally overlooked in ecosystem ecology. Along a broad elevation gradient characterized by shifting climatic and grazing environments, we addressed clines of plant N and C : N content and of d 13 C and d 15 N in producers (herbs) and in primary (grasshoppers) and secondary (birds) consumers, both within and between species in phylogenetically controlled scenarios. We found parallel and significant intra-and interspecific trends of isotopic variation with elevation in the three groups. In primary producers, nutrient and isotope distributions had a detectable phylogenetic signal that constrained their variation along the environmental gradient. The influence of the environment could not be ascribed to any single factor, and both grazing and climate had an effect on leaf stoichiometry and, thus, on the resources available to consumers. Trends in consumers matched those in plants but often became nonsignificant after controlling for isotopic values of their direct resources, revealing direct bottom-up control and little phylogenetic dependence. By integrating ecosystem and mechanistic perspectives, we found that nutrient dynamics in food webs are governed at the base by the complex interaction between local determinants and evolutionary factors.

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Phylogenetic diversity and the functioning of ecosystems

Cited by 494 publications

References 83 publications

Integrating data‐deficient species in analyses of evolutionary history loss

Integrating data‐deficient species in analyses of evolutionary history loss

When phylogeny and ecology meet: Modeling the occurrence of Trichoptera with environmental and phylogenetic data

Abiotic, Biotic, and Evolutionary Control of the Distribution of C and N Isotopes in Food Webs

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