Large‐scale impacts of selective logging on canopy tree beta‐diversity in the Brazilian Amazon

Selective logging is one of the largest drivers of tropical forest degradation. While logged forests often retain high alpha-diversity of tropical trees at local spatial scales, understanding how selective logging impacts tree beta-diversity and community composition across far larger spatial scales remains a key unresolved question. We leverage large datasets of more than 155,000 adult trees over 35 cm DBH covering 3100 ha of Amazonian rainforest to inform simulations of selective logging harvests across a gradient of logging intensity (0–40 m3 ha−1). These simulations incorporate real world price data, account for all forest damage throughout the harvest process and assume preferential harvest of the most valuable stems. We use the simulations to assess how selective logging affects canopy tree beta-diversity and composition across large spatial scales, whether nestedness or turnover of species best explains variation in communities across space, and how the spatial scale of sampling influences observed beta-diversity effects. Selective logging had minimal impacts on beta-diversity across the canopy tree community, but caused substantial subtractive heterogenization in community composition for larger trees, in particular very large trees over 110 cm DBH. Turnover is the dominant component of tree beta-diversity in unlogged and logged forests. Increasing the spatial grain of sampling reduced the observed importance of logging in explaining patterns of beta-diversity in very large tree communities. Synthesis and applications. Minimal impacts on tree beta-diversity across large spatial scales points towards the retention of substantial conservation value in logged tropical forests. Strong subtractive heterogenization in very large trees indicates the breakdown of broad scale patterns of composition with potential negative consequences for recruitment processes, fauna reliant upon emergent trees, and other ecosystem functions and services. Avoiding large-scale erosion of very large tree community composition in the Amazon requires stronger conservation policies, including enforced retention or maximum cutting diameters.