Phylogenetic scale in ecology and evolution Graham, Catherine H.; Storch, David; Machac, Antonin
Global ecology and biogeography,
February 2018, Letnik:
27, Številka:
1/2
Journal Article
Recenzirano
Odprti dostop
Aim: Many important patterns and processes vary across the phylogeny and depend on phylogenetic scale. Nonetheless, phylogenetic scale has never been formally conceptualized, and its potential ...remains largely unexplored. Here, we formalize the concept of phylogenetic scale, review how phylogenetic scale has been considered across multiple fields and provide practical guidelines for the use of phylogenetic scale to address a range of biological questions. Innovation: We summarize how phylogenetic scale has been treated in macroevolution, community ecology, biogeography and macroecology, illustrating how it can inform, and possibly resolve, some of the longstanding controversies in these fields. To promote the concept empirically, we define phylogenetic grain and extent, scale dependence, scaling and the domains of phylogenetic scale. We illustrate how existing phylogenetic data and statistical tools can be used to investigate the effects of scale on a variety of well-known patterns and processes, including diversification rates, community structure, niche conservatism or species-abundance distributions. Main conclusions: Explicit consideration of phylogenetic scale can provide new and more complete insight into many longstanding questions across multiple fields (macroevolution, community ecology, biogeography and macroecology). Building on the existing resources and isolated efforts across fields, future research centred on phylogenetic scale might enrich our understanding of the processes that together, but over different scales, shape the diversity of life.
Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species' environmental requirements from ...localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species' physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21 000 years before present) and a future climate projection (double preindustrial CO₂ conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.
Understanding the processes that drive the dramatic changes in biodiversity along the productivity gradient remains a major challenge. Insight from simple, bivariate relationships so far has been ...limited. We combined >11,000 community plots in the French Alps with a molecular phylogeny and trait information for >1200 plant species to simultaneously investigate the relationships between all major biodiversity dimensions and satellite-sensed productivity. Using an approach that tests for differential effects of species dominance, species similarity and the interplay between phylogeny and traits, we demonstrate that unimodal productivity-biodiversity relationships only dominate for taxonomic diversity. In forests, trait and phylogenetic diversity typically increase with productivity, while in grasslands, relationships shift from unimodal to declining with greater land-use intensity. High productivity may increase trait/phylogenetic diversity in ecosystems with few external constraints (forests) by promoting complementary strategies, but under external constraints (managed grasslands) successful strategies are similar and thus the best competitors may be selected.
Conservation priorities that are based on species distribution, endemism, and vulnerability may underrepresent biologically unique species as well as their functional roles and evolutionary ...histories. To ensure that priorities are biologically comprehensive, multiple dimensions of diversity must be considered. Further, understanding how the different dimensions relate to one another spatially is important for conservation prioritization, but the relationship remains poorly understood. Here, we use spatial conservation planning to (i) identify and compare priority regions for global mammal conservation across three key dimensions of biodiversity—taxonomic, phylogenetic, and traits—and (ii) determine the overlap of these regions with the locations of threatened species and existing protected areas. We show that priority areas for mammal conservation exhibit low overlap across the three dimensions, highlighting the need for an integrative approach for biodiversity conservation. Additionally, currently protected areas poorly represent the three dimensions of mammalian biodiversity. We identify areas of high conservation priority among and across the dimensions that should receive special attention for expanding the global protected area network. These highpriority areas, combined with areas of high priority for other taxonomic groups and with social, economic, and political considerations, provide a biological foundation for future conservation planning efforts.
Trophic ecosystem functions between consumer and resource species have been explored either using functional trait diversity or interaction networks.However, these approaches miss a critical element ...that has not been addressed yet: traits only impact trophic ecosystem functions when species interact.Understanding the mechanisms shaping trophic ecosystem functions requires the integration of functional and network ecology into a single trait-based framework.Based on previous developments of functional diversity and interactions networks, we present the interaction functional space (IFS) as an integrative framework to analyze how the traits of interacting species build up a combined functional space that underpins trophic ecosystem functions.The IFS can be applied to a broad range of trophic functions to understand how they emerge and change under global change.
Quantifying the vulnerability of ecosystems to global change requires a better understanding of how trophic ecosystem functions emerge. So far, trophic ecosystem functions have been studied from the perspective of either functional diversity or network ecology. To integrate these two perspectives, we propose the interaction functional space (IFS) a conceptual framework to simultaneously analyze the effects of traits and interactions on trophic functions. We exemplify the added value of our framework for seed dispersal and wood decomposition and show how species interactions influence the relationship between functional trait diversity and trophic functions. We propose future applications for a range of functions where the IFS can help to elucidate mechanisms underpinning trophic functions and facilitate understanding of functional changes in ecosystems amidst global change.
Most methods for modeling species distributions from occurrence records require additional data representing the range of environmental conditions in the modeled region. These data, called background ...or pseudo-absence data, are usually drawn at random from the entire region, whereas occurrence collection is often spatially biased toward easily accessed areas. Since the spatial bias generally results in environmental bias, the difference between occurrence collection and background sampling may lead to inaccurate models. To correct the estimation, we propose choosing background data with the same bias as occurrence data. We investigate theoretical and practical implications of this approach. Accurate information about spatial bias is usually lacking, so explicit biased sampling of background sites may not be possible. However, it is likely that an entire target group of species observed by similar methods will share similar bias. We therefore explore the use of all occurrences within a target group as biased background data. We compare model performance using target-group background and randomly sampled background on a comprehensive collection of data for 226 species from diverse regions of the world. We find that target-group background improves average performance for all the modeling methods we consider, with the choice of background data having as large an effect on predictive performance as the choice of modeling method. The performance improvement due to target-group background is greatest when there is strong bias in the target-group presence records. Our approach applies to regression-based modeling methods that have been adapted for use with occurrence data, such as generalized linear or additive models and boosted regression trees, and to Maxent, a probability density estimation method. We argue that increased awareness of the implications of spatial bias in surveys, and possible modeling remedies, will substantially improve predictions of species distributions.
The latitudinal diversity gradient (LDG) is one of the most widely studied patterns in ecology, yet no consensus has been reached about its underlying causes. We argue that the reasons for this are ...the verbal nature of existing hypotheses, the failure to mechanistically link interacting ecological and evolutionary processes to the LDG, and the fact that empirical patterns are often consistent with multiple explanations. To address this issue, we synthesize current LDG hypotheses, uncovering their eco-evolutionary mechanisms, hidden assumptions, and commonalities. Furthermore, we propose mechanistic eco-evolutionary modeling and an inferential approach that makes use of geographic, phylogenetic, and trait-based patterns to assess the relative importance of different processes for generating the LDG.
The latitudinal diversity gradient (LDG) is one of the most widely debated patterns in ecology and evolution, associated with hundreds of papers, dozens of hypotheses, and disagreements about its underlying processes.
The lack of agreement stems from: (i) the verbal nature of existing hypotheses, (ii) the failure to mechanistically integrate all relevant ecological and evolutionary processes to the LDG, and (iii) the degree to which many empirical patterns are consistent with multiple LDG explanations.
We show how mapping LDG hypotheses to a set of key ecological and evolutionary processes leads to a better understanding of the internal logic of those hypotheses. The codification of those processes within a mechanistic eco-evolutionary model is essential for contrasting support for hypotheses and for understanding the relative importance of the processes themselves.
Niche conservatism is the tendency of species to retain ancestral ecological characteristics. In the recent literature, a debate has emerged as to whether niches are conserved. We suggest that simply ...testing whether niches are conserved is not by itself particularly helpful or interesting and that a more useful focus is on the patterns that niche conservatism may (or may not) create. We focus specifically on how niche conservatism in climatic tolerances may limit geographic range expansion and how this one type of niche conservatism may be important in (a) allopatric speciation, (b) historical biogeography, (c) patterns of species richness, (d) community structure, (e) the spread of invasive, human-introduced species, (f) responses of species to global climate change, and (g) human history, from 13,000 years ago to the present. We describe how these effects of niche conservatism can be examined with new tools for ecological niche modeling.
By specialising on specific resources, species evolve advantageous morphologies to increase the efficiency of nutrient acquisition. However, many specialists face variation in resource availability ...and composition. Whether specialists respond to these changes depends on the composition of the resource pulses, the cost of foraging on poorly matched resources, and the strength of interspecific competition. We studied hummingbird bill and plant corolla matching during seasonal variation in flower availability and morphology. Using a hierarchical Bayesian model, we accounted for the detectability and spatial overlap of hummingbird‐plant interactions. We found that despite seasonal pulses of flowers with short‐corollas, hummingbirds consistently foraged on well‐matched flowers, leading to low niche overlap. This behaviour suggests that the costs of searching for rare and more specialised resources are lower than the benefit of switching to super‐abundant resources. Our results highlight the trade‐off between foraging efficiency and interspecific competition, and underline niche partitioning in maintaining tropical diversity.
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