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Forest dynamics and its driving forces of sub-tropical forest in South China.

ABSTRACT: Tree mortality and recruitment are key factors influencing forest dynamics, but the driving mechanisms of these processes remain unclear. To better understand these driving mechanisms, we studied forest dynamics over a 5-year period in a 20-ha sub-tropical forest in the Dinghushan Nature Reserve, South China. The goal was to identify determinants of tree mortality/recruitment at the local scale using neighborhood analyses on some locally dominant tree species. Results show that the study plot was more dynamic than some temperate and tropical forests in a comparison to large, long-term forest dynamics plots. Over the 5-year period, mortality rates ranged from 1.67 to 12.33% per year while recruitment rates ranged from 0 to 20.26% per year. Tree size had the most consistent effect on mortality across species. Recruitment into the ≥1-cm size class consistently occurred where local con-specific density was high. This suggests that recruitment may be limited by seed dispersal. Hetero-specific individuals also influenced recruitment significantly for some species. Canopy species had low recruitment into the ≥1-cm size class over the 5-year period. In conclusion, tree mortality and recruitment for sixteen species in this plot was likely limited by seed dispersal and density-dependence.

SUBMITTER: Ma L

PROVIDER: S-EPMC4778038 | biostudies-other | 2016 Mar

REPOSITORIES: biostudies-other

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Project description:Our aims were to quantify and map the plant sub regions of the the Caatinga, that covers 844,453 km2 and is the largest block of seasonally dry forest in South America. We performed spatial analyses of the largest dataset of woody plant distributions in this region assembled to date (of 2,666 shrub and tree species; 260 localities), compared these distributions with the current phytogeographic regionalizations, and investigated the potential environmental drivers of the floristic patterns in these sub regions. Phytogeographical regions were identified using quantitative analyses of species turnover calculated as Simpson dissimilarity index. We applied an interpolation method to map NMDS axes of compositional variation over the entire extent of the Caatinga, and then classified the compositional dissimilarity according to the number of biogeographical sub regions identified a priori using k-means analysis. We used multinomial logistic regression models to investigate the influence of contemporary climatic productivity, topographic complexity, soil characteristics, climate stability since the last glacial maximum, and the human footprint in explaining the identified sub regions. We identified nine spatially cohesive biogeographical sub regions. Current productivity, as indicated by an aridity index, was the only explanatory variable retained in the best model, explaining nearly half of the floristic variability between sub regions. The highest rates of endemism within the Caatinga were in the Core and Periphery Chapada Diamantina sub regions. Our findings suggest that the topographic complexity, soil variation, and human footprint in the Caatinga act on woody plant distributions at local scales and not as determinants of broad floristic patterns. The lack of effect of climatic stability since the last glacial maximum probably results from the fact that a single measure of climatic stability does not adequately capture the highly dynamic climatic shifts the region suffered during the Pleistocene. There was limited overlap between our results and previous Caatinga classifications.

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Forest dynamics and its driving forces of sub-tropical forest in South China.

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