Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level

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Dataset information

Country of origin
Updated
2022.03.11 00:00
Created
2022.01.01
Available languages
English
Keywords
Community ecology, Multiple stressors, Recovery, Food web, Composition
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Dataset description

Abstract Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply for the first time quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrients enrichment and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified post-disturbance interaction strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticides interactions to be significant in the long term only when both interactions strength and food web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery. Significance Statement Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food web analysis to assess the influence of species interactions on community recovery. We found species interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species interaction strength and food web architecture change significantly. Please see the "readme" sheet in the datafile for a description of the file structure and treatments abreviations.
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