Vegetation structure has emerged as a key determinant of terrestrial biodiversity based on studies using randomly placed sampling grids. The resultant grid cells often contain substantial heterogeneity in ecological conditions that are highly relevant for the taxa of interest, potentially undermining our ability to detect relevant drivers of diversity. Here we use 12 structural metrics measured using a ground-based light detection and ranging (lidar) scanner to model mammalian diversity at 58 sampling locations across seven distinct tropical forest types in Indonesian Borneo. We conducted analyses at four spatial scales using over five years of camera trap data. Models predicting mammal diversity based on ecologically defined scales (i.e., forest type boundaries) outperformed models using a grid scale of comparable resolution. Our results highlight the importance of incorporating ecologically meaningful spatial scales in biodiversity studies and underscore the value of lidar in capturing forest structural metrics relevant to mammals. Ecologically informed spatial units improve predictions of mammal diversity in tropical forests by better capturing variation in forest structure, revealing scale-dependent relationships between terrestrial LiDAR-derived metrics and community diversity that are obscured by grid-based approaches.
Estrada et al. (2026) studied this question.