Back

Multi-trophic metacommunity responses to habitatnfragmentation in the Brazilian Atlantic Forest

Souto Martins Teixeira, T.; Khalilur Rahman, O.; Cirtwill, A.; Speer, K.; Hemprich-Bennett, D. R.; Brown, A.; Perkins, S.; Simmons, N. B.; Rossiter, S.; Claudia Delciellos, A.; Vieira, M. V.; Clare, E.

2025-10-04 ecology
10.1101/2025.10.03.680099 bioRxiv
Show abstract

The structure of ecological communities is profoundly altered by anthropogenic disturbance to landscapes. However, most reported impacts rely on the quantification of diversity estimates for single trophic levels or impacts on key species of interest. In this analysis we integrate measures of community structure, comparisons of interaction networks and measures of {beta}-diversity across four trophic levels: plants, bats, bat ectoparasites and bacteria within the ectoparasites. Our data show that bat, bat fly, and bacterial communities are significantly nested across forest fragments, with specialist consumers in all groups being found in fewer fragments than generalists. We found substantial {beta}-diversity in both species richness and interaction richness across fragments but no decline in interaction redundancy with decreasing fragment size, likely because even intact forest networks had very low redundancy in our dataset. Despite the loss of species and interactions, our data provide support for the conservation value of even the smallest and most disturbed forest fragments where essential seed dispersal services are potentially maintained by Artibeus, Carollia and Sturnira and distinct sets of taxa and interactions are supported. These species may be key in the potential recovery of these habitats, but our data highlight the fragility of these communities which have contracted around these disturbance-tolerant species.

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.