Back

Forest bird decline and community change over 19 years in long-isolated South Asian tropical rainforest fragments

Surendra, A.; Raman, T. R. S.

2022-10-24 ecology
10.1101/2022.10.22.513365 bioRxiv
Show abstract

Recent evidence of forest bird declines worldwide is attributed to climate change and its interactive effects with recent land-use changes such as forest loss and fragmentation, and avian life-history traits. In Asian tropical forests, such effects are poorly understood as long-term data are lacking from fragments that are long-isolated rather than recently fragmented. Here, we use data from ~2000 point-counts from bird surveys carried out between 2000 - 2005 and 2019 in 19 long-isolated (~80 y) South Asian tropical rainforest fragments to examine changes in bird species richness, density, and composition in relation to fragment area (0.7 - 4310 ha), habitat structure, and time. Over the 19 y timespan, despite stable fragment areas, we uncovered a 29% decline in rainforest bird density and 7% decline in individual-rarefied species richness of rainforest birds, while density and richness of open-country birds remained stable. With increasing fragment area, rainforest bird species richness (jackknife estimate) increased, while open country bird richness (individual-rarefied) and density decreased. Larger fragments housed more compositionally stable bird communities, while poorer habitat was associated with lower diversity of rainforest birds but higher diversity, density, and compositional variation of open-country birds. Threshold analysis however indicated relatively small area thresholds (~20 ha) for rainforest bird species abundance. Besides identifying alarming declines in rainforest birds, the study confirms some but not all predictions for bird diversity in long-isolated forest fragments with stable forest-matrix boundaries, indicating that small fragments and habitat quality also matter.

Matching journals

The top 8 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.