Phylogenetic turnover in tropical tree communities: impact of environmental filtering, biogeography and mesoclimatic niche conservatism

Hardy, Olivier J.; Couteron, Pierre; Munoz, François; Ramesh, B. R.; Pélissier, Raphaël

doi:10.1111/j.1466-8238.2011.00742.x

Cited by 96 publications

(134 citation statements)

References 31 publications

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“…We tested for phylogenetic signal to determine whether we could use phylogenetic turnover to make ecological inferences in our system, and to determine the most appropriate metric of phylogenetic turnover. We found significant phylogenetic signal, but only across relatively short phylogenetic distances (Figure 2), consistent with previous work (Andersson et al, 2010;Diniz-Filho et al, 2010;Hardy et al, 2012;Stegen et al, 2012). It is therefore most appropriate to quantify phylogenetic turnover among closest relatives (Stegen et al, 2012).…”

Section: Analytical Framework Developmentsupporting

confidence: 91%

Quantifying community assembly processes and identifying features that impose them

et al. 2013

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Spatial turnover in the composition of biological communities is governed by (ecological) Drift, Selection and Dispersal. Commonly applied statistical tools cannot quantitatively estimate these processes, nor identify abiotic features that impose these processes. For interrogation of subsurface microbial communities distributed across two geologically distinct formations of the unconfined aquifer underlying the Hanford Site in southeastern Washington State, we developed an analytical framework that advances ecological understanding in two primary ways. First, we quantitatively estimate influences of Drift, Selection and Dispersal. Second, ecological patterns are used to characterize measured and unmeasured abiotic variables that impose Selection or that result in low levels of Dispersal. We find that (i) Drift alone consistently governs B25% of spatial turnover in community composition; (ii) in deeper, finer-grained sediments, Selection is strong (governing B60% of turnover), being imposed by an unmeasured but spatially structured environmental variable; (iii) in shallower, coarser-grained sediments, Selection is weaker (governing B30% of turnover), being imposed by vertically and horizontally structured hydrological factors; (iv) low levels of Dispersal can govern nearly 30% of turnover and be caused primarily by spatial isolation resulting from limited exchange between finer and coarser-grain sediments; and (v) highly permeable sediments are associated with high levels of Dispersal that homogenize community composition and govern over 20% of turnover. We further show that our framework provides inferences that cannot be achieved using preexisting approaches, and suggest that their broad application will facilitate a unified understanding of microbial communities.

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Section: Analytical Framework Developmentsupporting

confidence: 91%

Quantifying community assembly processes and identifying features that impose them

et al. 2013

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“…The analogous procedure was used to estimate OTU niche values for water elevation. The niche values estimate the depth and the water elevation where each OTU is most abundant, thereby characterizing two axes of each OTU's niche in terms of the habitats where it occurs (for similar approaches in plant and microbial ecology, see Andersson et al, 2010;Pei et al, 2011;Hardy et al, 2012). For each niche axis, between-OTU niche differences were related to between-OTU phylogenetic distances.…”

Section: Phylogenetic Signalmentioning

confidence: 99%

“…Drawing on established evolutionary theory (specifically Haldane, 1932;Wiedenbeck and Cohan, 2011), we predicted that a positive relationship between bacterial ecological differences and phylogenetic distances should only occur among close relatives. Our results and previous work in bacterial systems are consistent with this expectation: beyond B13-15% of the maximum phylogenetic distance observed between any two OTUs, there was no systematic relationship between ecological difference and phylogenetic distance (Figure 3).…”

Section: Phylogenetic Signal In Ecological Nichesmentioning

confidence: 99%

“…Across more distant relatives, however, there was effectively no relationship between ecological differences and phylogenetic distances. Ecological niches of bacteria have therefore evolved in a Brownian-like manner across recent evolutionary time, but in a phylogenetically random manner across deeper evolutionary time (see also Andersson et al, 2010;Diniz-Filho et al, 2010;Hardy et al, 2012). Kembel (2009) found that phylogenetic community composition provides robust inferences of ecological processes for systems like ours, where (i) phylogenetic signal is consistent with Brownian evolution; (ii) the environment is heterogeneous; and (iii) more than one aspect of organismal physiology determines OTU relative performance across environmental conditions, which we assume to be true.…”

Section: Phylogenetic Signal In Ecological Nichesmentioning

confidence: 99%

“…On the other hand, horizontal gene transfer can move ecological attributes among bacteria (Doolittle, 1999a,b;Welch et al, 2002). Wiedenbeck and Cohan (2011) draw from Haldane's (1932) classical work to demonstrate that horizontal gene transfer does not, however, 'scramble' ecological niches among taxa (see also Cohan and Koeppel, 2008;Philippot et al, 2010). Horizontal gene transfer should instead improve the performance of recipients (Cohan and Koeppel, 2008;Wiedenbeck and Cohan, 2011).…”

Section: Introductionmentioning

confidence: 99%

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Stochastic and deterministic assembly processes in subsurface microbial communities

et al. 2012

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A major goal of microbial community ecology is to understand the forces that structure community composition. Deterministic selection by specific environmental factors is sometimes important, but in other cases stochastic or ecologically neutral processes dominate. Lacking is a unified conceptual framework aiming to understand why deterministic processes dominate in some contexts but not others. Here we work toward such a framework. By testing predictions derived from general ecological theory we aim to uncover factors that govern the relative influences of deterministic and stochastic processes. We couple spatiotemporal data on subsurface microbial communities and environmental parameters with metrics and null models of within and between community phylogenetic composition. Testing for phylogenetic signal in organismal niches showed that more closely related taxa have more similar habitat associations. Community phylogenetic analyses further showed that ecologically similar taxa coexist to a greater degree than expected by chance. Environmental filtering thus deterministically governs subsurface microbial community composition. More importantly, the influence of deterministic environmental filtering relative to stochastic factors was maximized at both ends of an environmental variation gradient. A stronger role of stochastic factors was, however, supported through analyses of phylogenetic temporal turnover. Although phylogenetic turnover was on average faster than expected, most pairwise comparisons were not themselves significantly non-random. The relative influence of deterministic environmental filtering over community dynamics was elevated, however, in the most temporally and spatially variable environments. Our results point to general rules governing the relative influences of stochastic and deterministic processes across micro-and macro-organisms.

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Environment shapes the spatial organization of tree diversity in fragmented forests across a human‐modified landscape

Krishnadas

Osuri

2020

Ecological Applications

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Biodiversity patterns are shaped by the combination of dispersal, environment, and stochasticity, but how the influence of these drivers changes in fragmented habitats remains poorly understood. We examined patterns and relationships among total (γ) and site‐level (α) diversity, and site‐to‐site variation in composition (β‐diversity) of tree communities in structurally contiguous and fragmented tropical rainforests within a human‐modified landscape in India's Western Ghats. First, for the entire landscape, we assessed the extent to which habitat type (fragment or contiguous forest), space and environment explained variation in α‐diversity and composition. Next, within fragments and contiguous forest, we assessed the relative contribution of spatial proximity, environmental similarity, and their joint effects in explaining β‐diversity. We repeated these assessments with β‐diversity values corrected for the confounding effects of α‐ and γ‐diversity using null models (β‐deviation). Lower γ‐diversity of fragments resulted from both lower α‐ and β‐diversity compared to contiguous forests. However, β‐deviation did not differ between contiguous forests and fragments. Fragmented and contiguous forest clearly diverged in floristic composition, which was attributable to β‐diversity being driven by differences in elevation and MAP. Within fragmented forest, neither space nor environment explained β‐diversity, but β‐deviation increased with greater elevational differences. In contiguous forests by comparison, environment alone (mainly elevation) explained the most variation in β‐diversity and β‐deviation of both species' occurrences and abundances. Spatial gradients in environmental conditions played a larger role than dispersal limitation in shaping diversity and composition of tree communities across forest fragments. Thus, location of remnant patches at different elevations was a key factor underlying site‐to‐site variability in species abundances across fragments. Understanding the environmental characteristics of remnant forests in human‐modified landscapes, combined with knowledge of species–environment relationships across different functional groups, would therefore be important considerations for management and restoration planning in human‐modified landscapes.

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Phylogenetic turnover in tropical tree communities: impact of environmental filtering, biogeography and mesoclimatic niche conservatism

Cited by 96 publications

References 31 publications

Quantifying community assembly processes and identifying features that impose them

Quantifying community assembly processes and identifying features that impose them

Stochastic and deterministic assembly processes in subsurface microbial communities

Environment shapes the spatial organization of tree diversity in fragmented forests across a human‐modified landscape

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