Understanding global warming effects on forest ecosystems will help policy-makers and forest managers design forest management and biodiversity conservation strategies. We examined the change in woody plant structural diversity in response to topography-associated thermal gradients in a subtropical forest with diverse abundance patterns. We found that energy distribution in a warming trend across slopes had significant effects on woody plant structural diversity. Except for total basal area of the adult trees, plant structural diversity significantly decreased with the increase of heat load. Heat load is significantly and negatively correlated with number of stems, number of species, and the number of stems of the most abundant species (Nmax) for seedlings, saplings, and individuals of all sizes. For the adult trees, heat load is significantly and positively correlated with number of stems and Nmax, and negatively but not significantly with number of species, indicating that large trees may not be as sensitive as seedlings and saplings to warming. Partial correlation analysis, having controlled for elevation, strengthened those relations in most cases. Our results reveal that warming will increase community productivity by enhancing the growth of large trees, but decrease species diversity and inhibit the regeneration of tree seedlings and saplings.

The impacts of climate change on forest community composition are still not well known. Although directional trends in climate change and community composition change were reported in recent years, further quantitative analyses are urgently needed. Previous studies focused on measuring population growth rates in a single time period, neglecting the development of the populations. Here we aimed to compose a method for calculating the community composition change, and to testify the impacts of climate change on community composition change within a relatively short period (several decades) based on long-term monitoring data from two plots—Dinghushan Biosphere Reserve, China (DBR) and Barro Colorado Island, Panama (BCI)—that are located in tropical and subtropical regions. We proposed a relatively more concise index, Slnλ, which refers to an overall population growth rate based on the dominant species in a community. The results indicated that the population growth rate of a majority of populations has decreased over the past few decades. This decrease was mainly caused by population development. The increasing temperature had a positive effect on population growth rates and community change rates. Our results promote understanding and explaining variations in population growth rates and community composition rates, and are helpful to predict population dynamics and population responses to climate change.

Conventional models for predicting species distribution under global warming scenarios often treat one species as a homogeneous whole. In the present study, we selected Cunninghamia lanceolata (C. lanceolata), a widely distributed species in China, to investigate the physio-ecological responses of five populations under different temperature regimes. The results demonstrate that increased mean temperatures induce increased growth performance among northern populations, which exhibited the greatest germination capacity and largest increase in the overlap between the growth curve and the monthly average temperature. However,tolerance of the southern population to extremely high temperatures was stronger than among the population from the northern region,shown by the best growth and the most stable photosynthetic system of the southern population under extremely high temperature. This result indicates that the growth advantage among northern populations due to increased mean temperatures may be weakened by lower tolerance to extremely high temperatures. This finding is antithetical to the predicted results. The theoretical coupling model constructed here illustrates that the difference in growth between populations at high and low latitudes and altitudes under global warming will decrease because of the frequent occurrence of extremely high temperatures.

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