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Updated: Jan 22, 2026

Scalable, Flexible, and Cost-Effective Seedling Grafting
Published on: January 6, 2023
Neighborhood effects explain increasing asynchronous seedling survival in a subtropical forest
Lei Chen1,2, Yunquan Wang1,3, Xiangcheng Mi1
1State Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, 100093, China.
Abstract:
Biotic interactions play a critical role in mediating community responses to temporal environmental variation, but the importance of these effects relative to the direct effects of environmental change remains poorly understood, particularly in diverse forest communities. Here we combine a neighborhood modeling approach with insights from coexistence theory to assess the effects of temporal variation in species interactions and environmental conditions (e.g., precipitation, temperature, and understory light availability) on seedling survival over nine census years in a subtropical forest. We find significant temporal shifts in the magnitude of neighborhood effects on both community-wide and species-level seedling survival (statistically significant random effects of neighborhood × year and neighborhood × species × year interactions). These results are consistent with the idea that environmental change will play a fundamental role on forest regeneration dynamics by altering biotic interactions at the neighborhood scale. Moreover, differences among species in response to neighbors over time contribute to a pattern of temporal decoupling of seedling survival between species, which can help to promote diversity in certain contexts. In separate analyses of multiple regression on distance matrices (MRM), altered interactions with neighbors are much stronger predictors of asynchronous seedling survival among species than the pure effects of climate and plant functional traits, explaining twice as much variation (43.9% vs. 22.2%). In sum, these results reveal that divergent species responses to interannual environmental variability detected are driven primarily by indirect effects mediated by changing biotic environments. This highlights the importance of including indirect effects from local biotic (neighborhood) interactions in forecasts of forest community responses to global change.
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