Mitigating the impacts of global anthropogenic change on species is conservation’s greatest challenge. Forecasting the effects of actions to mitigate threats is hampered by incomplete information on species’ responses. We develop an approach to predict community restructuring under threat management, which combines models of responses to threats with network analyses of species co-occurrence. We discover that contributions by species to network co-occurrence predict their recovery under reduction of multiple threats. Highly connected species are likely to benefit more from threat management than poorly connected species. Importantly, we show that information from a few species on co-occurrence and expected responses to alternative threat management actions can be used to train a response model for an entire community. We use a unique management dataset for a threatened bird community to validate our predictions and, in doing so, demonstrate positive feedbacks in occurrence and co-occurrence resulting from shared threat management responses during ecosystem recovery.
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D.B.L. is supported by an ARC Laureate Fellowship. A.I.T.T. is funded by the Australian Research Council Centre of Excellence for Environmental Decisions (CEED). The monitoring program was coordinated by D. Florance from The Australian National University (ANU) and approved by the Australian National University Animal Ethics Committee, and field staff from ANU and volunteers from the Canberra Ornithologists Group assisted with surveys. We thank M. Westgate and P. Lane for valuable discussions on methodology.
The authors declare no competing financial interests.
Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Supplementary Figures 1–3, Supplementary Tables 1–7, Supplementary References
Step 1 input ‘threats present’ species by site data for analysis of community of 88 bird species in Grassy Box Woodlands from 2011–2013
Step 1 output ‘threats present’ co-occurrence results: significant species pairs for 88 spp
Step 1 output ‘threats present’ co-occurrence results: pairwise effect size matrix for 88 spp
Step 2 output ‘threats present’ expected threat management responses: predicted changes in colonization rates for 37 species under 7 management strategies
Step 3 input ‘threats present’ pairwise data on co-occurrence (results from step 1) and species’ expected responses to threat reduction (results from step 2) for models predicting expected outcomes of 7 management strategies
Step 3 output ‘threats present’ pairwise data from model predicting expected outcomes of managing 3 threats (input for step 4)
Step 4 output ‘threats present’ species-level data on predicted change in colonization when managing 3 threats to all 88 species
Step 5/6 input ‘threats managed’ site by species data to calculate change in site occupancy, with sites categorized as 0, 1, 2 or 3 threats remaining
Step 5/6 input ‘threats managed’ species-level data for validation of change in site occupancy after management
Step 5/6 input ‘threats managed’ pairwise-level data for validation of predicted ‘increasers’ and ‘decreasers’
Input for Matlab matrix manipulation: an excel version of step 1 output pairwise effect size matrix for 88 spp
Input for Matlab matrix manipulation: an excel version of step 1 output significant species pairs for 88 spp
R code for the conceptual framework of predicting community responses
Matlab code for co-occurrence matrix manipulation
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