The relationship between species diversity and biomass/productivity is a major scientific question in ecology. Exploring this relationship is essential to understanding the mechanisms underpinning the maintenance of biodiversity. Positive, negative, and neutral relationships have been identified in controlled experiments and observational research. However, increasing evidence suggests that the effects of species diversity on aboveground biomass and productivity are influenced by biotic and abiotic factors, but it remains unclear whether scale-dependent effects affect aboveground biomass and productivity. Herein, we used a generalized linear regression model and a structural equation model to explore relationships between species diversity and productivity/aboveground biomass under different scales and to investigate the effects of topographical factors and species diversity on ecosystem functioning. The results revealed a positive relationship between biodiversity and ecosystem functioning based on species diversity and aboveground biomass. Different sampling scales may impact the relationship between species diversity and ecosystem functioning. A positive relationship was found between species richness and productivity at medium and large scales; however, ambiguous relationships were found in productivity and other species diversity indices. Elevation was a key factor affecting both biomass and productivity. These results suggest that species diversity is not the only factor affecting biomass and productivity, and the positive correlation between species diversity and ecosystem functioning is mediated by abiotic factors.

The growth and survival of individual trees determine the physical structure of a forest with important consequences for forest function. However, given the diversity of tree species and forest biomes, quantifying the multitude of demographic strategies within and across forests and the way that they translate into forest structure and function remains a significant challenge. Here, we quantify the demographic rates of 1961 tree species from temperate and tropical forests and evaluate how demographic diversity (DD) and demographic composition (DC) differ across forests, and how these differences in demography relate to species richness, aboveground biomass (AGB), and carbon residence time. We find wide variation in DD and DC across forest plots, patterns that are not explained by species richness or climate variables alone. There is no evidence that DD has an effect on either AGB or carbon residence time. Rather, the DC of forests, specifically the relative abundance of large statured species, predicted both biomass and carbon residence time. Our results demonstrate the distinct DCs of globally distributed forests, reflecting biogeography, recent history, and current plot conditions. Linking the DC of forests to resilience or vulnerability to climate change, will improve the precision and accuracy of predictions of future forest composition, structure, and function.

Quercus wutaishansea populations on the Loess Plateau are currently becoming more dominant in natural secondary forests, whereas Pinus tabulaeformis is declining. In the present paper, the diameter class (instead of age) was used to classify the different growth stages as juvenile, subadult, or adult, and the univariate function g(r) was used to analyze the dynamic changes in spatial patterns and interspecific associations in three 1-ha tree permanent plots on the Loess Plateau, NW China. Our results suggested that the niche breadth changed with the development stage. The diameter distribution curve was consistent with the inverted \"J\" type, indicating that natural regeneration was common in all three plots. There was a close relationship between the spatial pattern and scale, which showed significant aggregation at small distances, and became more random as distance increased, but in the Pinus + Quercus mixed forests, the whole species were aggregated at distances up to 50 m. The degree of spatial clumping decreased from juvenile to subadult and from subadult to adult. The spatial pattern also differed at different growth stages, likely due to strong intraspecific competition. Associations among different growth stages were positively correlated at small scales. Our study is important to the understanding of the development of the Q. wutaishansea forests; thus, the spatial dynamic change features should be received greater attention when planning forest management and developing restoration strategies on the Loess Plateau.

Intra-specific negative density dependence promotes species coexistence by regulating population sizes. Patterns consistent with such density dependence are frequently reported in diverse tropical tree communities. Empirical evidence demonstrating whether intra-specific variation is related to these patterns, however, is lacking. The present study addresses this important knowledge gap by genotyping all individuals of a tropical tree in a long-term forest dynamics plot in tropical China. We show that related individuals are often spatially clustered, but having closely related neighbours reduces the growth performance of focal trees. We infer from the evidence that dispersal limitation and negative density dependence are operating simultaneously to impact the spatial distributions of genotypes in a natural population. Furthermore, dispersal limitation decreases local intra-specific genetic diversity and increases negative density dependence thereby promoting niche differences and species coexistence as predicted by theory.

To learn the forest dynamics and evaluate the ecosystem services of forest effectively, a timely acquisition of spatial and quantitative information of forestland is very necessary. Here, a new method was proposed for mapping forest cover changes by combining multi-scale satellite remote-sensing imagery with time series data. Using time series Normalized Difference Vegetation Index products derived from the Moderate Resolution Imaging Spectroradiometer images (MODIS-NDVI) and Landsat Thematic Mapper/Enhanced Thematic Mapper Plus (TM/ETM+) images as data source, a hierarchy stepwise analysis from coarse scale to fine scale was developed for detecting the forest change area. At the coarse scale, MODIS-NDVI data with 1-km resolution were used to detect the changes in land cover types and a land cover change map was constructed using NDVI values at vegetation growing seasons. At the fine scale, based on the results at the coarse scale, Landsat TM/ETM+ data with 30-m resolution were used to precisely detect the forest change location and forest change trend by analyzing time series forest vegetation indices (IFZ). The method was tested using the data for Hubei Province, China. The MODIS-NDVI data from 2001 to 2012 were used to detect the land cover changes, and the overall accuracy was 94.02 % at the coarse scale. At the fine scale, the available TM/ETM+ images at vegetation growing seasons between 2001 and 2012 were used to locate and verify forest changes in the Three Gorges Reservoir Area, and the overall accuracy was 94.53 %. The accuracy of the two layer hierarchical monitoring results indicated that the multi-scale monitoring method is feasible and reliable.