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Developing a macroecology for human‐altered ecosystems

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Although anthropogenically‐induced ecological disruptions are fundamentally important in defining ecosystem properties, they are largely overlooked by macroecological theory. Anthropogenic disruptions and their effects are generally not comparable to one another, nor to disturbances that are part of natural disturbance regimes. To address this gap, we consider distributions of species diversity, abundance, and spatial clustering in carefully matched paired sites: sites anthropogenically exposed to ‘pack stock use' (intensive spot foraging by non‐native horses and mules), and control sites with no modern history of pack stock use. We examine ecological disruption in plant communities in 18 field plots arranged over two moisture levels, arrayed within 6 paired meadows in the high Sierra Nevada, in California, USA. Multiple hypotheses, including predictions from the maximum entropy theory of ecology (METE), were evaluated against plot‐level data. METE, an information‐theoretic framework of interrelated macroecological predictions, has demonstrated broad applicability across a variety of ecosystems and taxa, but has failed in systems with natural disturbance and ecological succession. We find that the shape of the species abundance distributions in plots are not by themselves good discriminants of anthropogenic disruption, and all models tested overestimate the number of ‘rare' species (those with ≤ 10 individuals). A measure of by‐species spatial clustering from METE fits empirical patterns from anthropogenically disrupted and control sites better than other models. Ultimately, arrays of small‐scale macroecological scaling plots in field studies might provide a way to capture landscape heterogeneity across altered landscapes, and be used to assess how mathematically interrelated biodiversity distributions change together under various stressors, both natural and anthropogenic in origin. Though more testing is needed to make generally applicable statements for human‐altered systems, we find that the METE predictions are robust to the level of anthropogenic disruption at these sites, and patterns from disrupted sites do not resemble patterns from natural disturbances.
Title: Developing a macroecology for human‐altered ecosystems
Description:
Although anthropogenically‐induced ecological disruptions are fundamentally important in defining ecosystem properties, they are largely overlooked by macroecological theory.
Anthropogenic disruptions and their effects are generally not comparable to one another, nor to disturbances that are part of natural disturbance regimes.
To address this gap, we consider distributions of species diversity, abundance, and spatial clustering in carefully matched paired sites: sites anthropogenically exposed to ‘pack stock use' (intensive spot foraging by non‐native horses and mules), and control sites with no modern history of pack stock use.
We examine ecological disruption in plant communities in 18 field plots arranged over two moisture levels, arrayed within 6 paired meadows in the high Sierra Nevada, in California, USA.
Multiple hypotheses, including predictions from the maximum entropy theory of ecology (METE), were evaluated against plot‐level data.
METE, an information‐theoretic framework of interrelated macroecological predictions, has demonstrated broad applicability across a variety of ecosystems and taxa, but has failed in systems with natural disturbance and ecological succession.
We find that the shape of the species abundance distributions in plots are not by themselves good discriminants of anthropogenic disruption, and all models tested overestimate the number of ‘rare' species (those with ≤ 10 individuals).
A measure of by‐species spatial clustering from METE fits empirical patterns from anthropogenically disrupted and control sites better than other models.
Ultimately, arrays of small‐scale macroecological scaling plots in field studies might provide a way to capture landscape heterogeneity across altered landscapes, and be used to assess how mathematically interrelated biodiversity distributions change together under various stressors, both natural and anthropogenic in origin.
Though more testing is needed to make generally applicable statements for human‐altered systems, we find that the METE predictions are robust to the level of anthropogenic disruption at these sites, and patterns from disrupted sites do not resemble patterns from natural disturbances.

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