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Neighborhood effects explain increasing asynchronous seedling survival in a subtropical forest

作 者:Chen L, Wang YQ, Mi XC, Liu XJ, Ren HB, Chen JH, Ma KP*, Kraft NJB
影响因子: 4.285
刊物名称: Ecology
出版年份: 2019
卷:   期:    页码: DOI: 10.1002/ecy.2821

文章摘要 : 

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 communitywide and specieslevel 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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