Scaling from Traits to Ecosystems

Enquist, Brian J.; Norberg, Jon; Bonser, Stephen P.; Violle, Cyrille; Webb, Colleen T.; Henderson, Amanda; Sloat, Lindsey L.; Savage, Van M.

doi:10.1016/bs.aecr.2015.02.001

Cited by 300 publications

(141 citation statements)

References 145 publications

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“…High values of kurtosis mean that the distribution is peaked and that the abundance of traits is unevenly distributed, indicating the dominance of a few trait values. In contrast, low values of kurtosis mean that the distribution of traits is flat and that the abundance of traits is evenly distributed, indicating low dominance (Enquist et al., ; Le Bagousse‐Pinguet et al., ). High values of skewness mean that the distribution is asymmetric and that the abundance of traits is biased towards one direction (low or high trait values), indicating the presence of extreme trait values (Enquist et al., ; Le Bagousse‐Pinguet et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…To estimate the community trait distributions, we subsampled individuals (i.e., observations) in species trait distributions (Enquist et al., ). We assumed that the distribution X ijk of trait i of species j in a particular community k follows a normal distribution of mean μ ijk and SD σ ijk (Equation ).…”

Section: Methodsmentioning

confidence: 99%

“…Based on the values of μ ijk and σ ijk estimated from the data in each community, trait values were sampled in this distribution for n individuals per species, where the number of individuals was determined by the total number of individuals observed in the community ( N ) weighted by the relative cover of the species in the community. The advantages of this approach are that it allows more realistic trait distributions by using most of the information contained in the trait measurements and takes into account intra‐specific trait variations (Enquist et al., ).…”

Section: Methodsmentioning

confidence: 99%

“…While previous studies have shown that using a trait‐based approach may help to understand the outcomes of competitive and facilitative interactions between species, very few have examined how direct and indirect facilitative interactions impact the community structure as a whole (Gross et al., ). Thus, how facilitation shapes plant functional diversity and community structure constitutes a substantial research gap in community ecology (Enquist et al., ; Violle et al., ).…”

Section: Introductionmentioning

confidence: 99%

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Effects of indirect facilitation on functional diversity, dominance and niche differentiation in tropical alpine communities

Danet

Anthelme

Gross

et al. 2018

J Vegetation Science

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Question Positive interactions between plants have well‐known effects on community species richness and biomass via micro‐environment improvements. However, the effects of indirect facilitation performed by a nurse on an associated plant community, occurring e.g., through protection against grazing, have not attracted much attention in the literature so far, in particular regarding the functional traits of the associated plant communities. Because characteristics of trait distributions can reveal selective pressures at play, they offer valuable information for the study of grazing pressure. Here, we tested the extent to which indirect facilitation affects the amount of distinct trait combinations (H1), trait dominance (H2) and niche differentiation between species (H3) of associated plant communities living under nurse plants. Location Tropical alpine peatlands, Cordillera Real, Bolivia. Methods We set up a grazing exclusion experiment over two dominant nurse cushion species: one providing indirect facilitation under grazing pressure and the other not. We measured three functional traits in the associated communities, which are known to vary depending on the grazing level: LDMC, leaf thickness and maximum height. We assessed the amount of distinct trait combinations by computing the volume of the phenotypic space (H1). The variation in trait dominance was quantified with kurtosis and skewness of the trait distributions (H2). The variation in niche differentiation was evaluated using mean intra‐population trait variance relative to intra‐community trait variance (H3). Results We did not find a significant effect of grazing and indirect facilitation on the volume of the phenotypic space (H1). However, our study revealed a significant effect of indirect facilitation on dominance in the associated communities by maintaining the evenness of the trait distributions (maximum height and leaf thickness) in grazed compared to ungrazed plots (H2), and on niche differentiation by maintaining trait overlaps (LDMC and maximum height) between species in grazed compared to ungrazed contexts (H3). Conclusion Our results suggest that indirect facilitation promotes the co‐existence of contrasting functional strategies (H2) and species niches (H3) in associated plant communities subject to grazing. These results reflect the buffering effect of indirect facilitation on the grazing selective pressures exerted on associated plant communities living under the protection of nurses.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Effects of indirect facilitation on functional diversity, dominance and niche differentiation in tropical alpine communities

Danet

Anthelme

Gross

et al. 2018

J Vegetation Science

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“…We also include an approach to allow for weighting of data and variation/uncertainty within data. This approach can be used for example to account for abundance of species and/or intraspecific trait variation in community‐level functional diversity analyses (Enquist et al., ). The weight_data function can be applied before running any of the hypervolume algorithms.…”

Section: Other New Functionalitymentioning

confidence: 99%

New approaches for delineating n‐dimensional hypervolumes

et al. 2017

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Hutchinson's n‐dimensional hypervolume concept underlies many applications in contemporary ecology and evolutionary biology. Estimating hypervolumes from sampled data has been an ongoing challenge due to conceptual and computational issues. We present new algorithms for delineating the boundaries and probability density within n‐dimensional hypervolumes. The methods produce smooth boundaries that can fit data either more loosely (Gaussian kernel density estimation) or more tightly (one‐classification via support vector machine). Further, the algorithms can accept abundance‐weighted data, and the resulting hypervolumes can be given a probabilistic interpretation and projected into geographic space. We demonstrate the properties of these methods on a large dataset that characterises the functional traits and geographic distribution of thousands of plants. The methods are available in version ≥2.0.7 of the hypervolume r package. These new algorithms provide: (i) a more robust approach for delineating the shape and density of n‐dimensional hypervolumes; (ii) more efficient performance on large and high‐dimensional datasets; and (iii) improved measures of functional diversity and environmental niche breadth.

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Explicitly representing soil microbial processes in Earth system models

Wieder

Allison

Davidson

et al. 2015

Global Biogeochemical Cycles

331

304

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Microbes influence soil organic matter decomposition and the long‐term stabilization of carbon (C) in soils. We contend that by revising the representation of microbial processes and their interactions with the physicochemical soil environment, Earth system models (ESMs) will make more realistic global C cycle projections. Explicit representation of microbial processes presents considerable challenges due to the scale at which these processes occur. Thus, applying microbial theory in ESMs requires a framework to link micro‐scale process‐level understanding and measurements to macro‐scale models used to make decadal‐ to century‐long projections. Here we review the diversity, advantages, and pitfalls of simulating soil biogeochemical cycles using microbial‐explicit modeling approaches. We present a roadmap for how to begin building, applying, and evaluating reliable microbial‐explicit model formulations that can be applied in ESMs. Drawing from experience with traditional decomposition models, we suggest the following: (1) guidelines for common model parameters and output that can facilitate future model intercomparisons; (2) development of benchmarking and model‐data integration frameworks that can be used to effectively guide, inform, and evaluate model parameterizations with data from well‐curated repositories; and (3) the application of scaling methods to integrate microbial‐explicit soil biogeochemistry modules within ESMs. With contributions across scientific disciplines, we feel this roadmap can advance our fundamental understanding of soil biogeochemical dynamics and more realistically project likely soil C response to environmental change at global scales.

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Scaling from Traits to Ecosystems

Cited by 300 publications

References 145 publications

Effects of indirect facilitation on functional diversity, dominance and niche differentiation in tropical alpine communities

Effects of indirect facilitation on functional diversity, dominance and niche differentiation in tropical alpine communities

New approaches for delineating n‐dimensional hypervolumes

Explicitly representing soil microbial processes in Earth system models

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