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Biotic homogenization destabilizes ecosystem functioning by decreasing spatial asynchrony.

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TLDR
In this article, the effects of local biodiversity loss on ecosystem stability are well documented, but the consequences of biodiversity changes at larger spatial scales, in particular biotic homogenization, that is, reduced species turnover across space (β diversity), remain poorly known.
Abstract
Our planet is facing significant changes of biodiversity across spatial scales. Although the negative effects of local biodiversity (α diversity) loss on ecosystem stability are well documented, the consequences of biodiversity changes at larger spatial scales, in particular biotic homogenization, that is, reduced species turnover across space (β diversity), remain poorly known. Using data from 39 grassland biodiversity experiments, we examine the effects of β diversity on the stability of simulated landscapes while controlling for potentially confounding biotic and abiotic factors. Our results show that higher β diversity generates more asynchronous dynamics among local communities and thereby contributes to the stability of ecosystem productivity at larger spatial scales. We further quantify the relative contributions of α and β diversity to ecosystem stability and find a relatively stronger effect of α diversity, possibly due to the limited spatial scale of our experiments. The stabilizing effects of both α and β diversity lead to a positive diversity-stability relationship at the landscape scale. Our findings demonstrate the destabilizing effect of biotic homogenization and suggest that biodiversity should be conserved at multiple spatial scales to maintain the stability of ecosystem functions and services.

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Citations
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Journal ArticleDOI

Grazing-induced biodiversity loss impairs grassland ecosystem stability at multiple scales.

TL;DR: This study provides the first evidence for the scale dependence of grazing effects on grassland stability through biodiversity, and suggests that ecosystem management should strive to maintain biodiversity across scales to achieve sustainability of grassland ecosystem functions and services.
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Decoupled responses of above‐ and below‐ground stability of productivity to nitrogen addition at the local and larger spatial scale

TL;DR: In this paper , the authors used experimental N addition in a grassland and found different responses of ANPP and BNPP stability to N addition at the local scale and that these responses propagated to the larger spatial scale.
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Spatial asynchrony matters more than alpha stability in stabilizing ecosystem productivity in a large temperate forest region

TL;DR: In this article , the authors evaluated biodiversity-stability effects from local to larger spatial scales in a large temperate forest region, considering a range of environmental conditions and environmental heterogeneity.
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Consistent stabilizing effects of plant diversity across spatial scales and climatic gradients

TL;DR: The authors investigated the relationship between biodiversity and community stability in natural plant communities from quadrat (1 m2) to plot (400 m2), and regional (5−214 km2) scales and across broad climatic conditions, using an extensive plant community dataset from the National Ecological Observatory Network.
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Nutrients and herbivores impact grassland stability across spatial scales through different pathways

TL;DR: It is found that both nutrient addition and herbivore exclusion alone reduced stability at the larger spatial scale (aggregated local communities; gamma stability), but through different pathways, and that disentangling the processes operating at different spatial scales may improve conservation and management.
References
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Journal ArticleDOI

A general and simple method for obtaining R2 from generalized linear mixed-effects models

TL;DR: In this article, the authors make a case for the importance of reporting variance explained (R2) as a relevant summarizing statistic of mixed-effects models, which is rare, even though R2 is routinely reported for linear models and also generalized linear models (GLM).
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Evolution and measurement of species diversity

Robert H. Whittaker
- 01 May 1972 - 
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piecewiseSEM: Piecewise structural equation modelling in r for ecology, evolution, and systematics

TL;DR: In this paper, the authors present an open-source implementation of structural equation models (SEM), a form of path analysis that resolves complex multivariate relationships among a suite of interrelated variables.
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