Tongqing Song

Biogeographical patterns of biomass allocation in leaves, stems, and roots in China’s forests

To test whether there are general patterns in biomass partitioning in relation to environmental variation when stand biomass is considered, we investigated biomass allocation in leaves, stems, and roots in China’s forests using both the national forest inventory data (2004–2008) and our field measurements (2011–2012). Distribution patterns of leaf, stem, and root biomass showed significantly different trends according to latitude, longitude, and altitude, and were positively and significantly correlated with stand age and mean annual precipitation. Trade-offs among leaves, stems, and roots varied with forest type and origin and were mainly explained by stand biomass. Based on the constraints of stand biomass, biomass allocation was also influenced by forest type, origin, stand age, stand density, mean annual temperature, precipitation, and maximum temperature in the growing season. Therefore, after stand biomass was accounted for, the residual variation in biomass allocation could be partially explained by stand characteristics and environmental factors, which may aid in quantifying carbon cycling in forest ecosystems and assessing the impacts of climate change on forest carbon dynamics in China.

Biogeographical patterns of forest biomass allocation vary by climate, soil and forest characteristics in China

To explore whether the large-scale patterns of biomass allocation vary by climate, soil, and forest characteristics in terrestrial ecosystems, on the basis of the national forest inventory data (2004?2008) and our previous field measurements (2011?2012), we investigated the variation of four biomass allocation fractions (BAFs), and their relationship with environmental factors (e.g. climate and soil chemistry) and forest characteristics (e.g. stand age and stand density) across 11 of China?s forest types. Our results revealed that BAFs have significant latitudinal, longitudinal and altitudinal trends. Stepwise multiple regression models that involve the climate, soil and forest stand properties account for a part of the biogeographical variation in BAFs, and the stand age, stand density and mean growing season temperature mainly explain these variations. Reduced major axis regression models showed that BAFs differ in their sensitivity (slope of their response to environmental gradients) to climate, soil and forest characteristics among different forest types. The results of the current study do not support the isometric allocation hypothesis, which suggests that component biomass scales equivalently as total biomass across different plant species along environmental gradients.

Spatial Heterogeneity of Soil Mineral Oxide Components in Depression Between Karst Hills, Southwest China

In karst regions, the spatial heterogeneity of soil mineral oxides and environmental variables is still not clear. We investigated the spatial heterogeneity of SiO2, Al2O3, Fe2O3, CaO, MgO, P2O5, K2O, and MnO contents in the soils of slope land, plantation forest, secondary forest, and primary forest, as well as their relationships with environmental variables in a karst region of Southwest China. Geostatistics, principal component analysis (PCA), and canonical correlation analysis (CCA) were applied to analyze the field data. The results show that SiO2 was the predominant mineral in the soils (45.02%–67.33%), followed by Al2O3 and Fe2O3. Most soil mineral oxide components had a strong spatial dependence, except for CaO, MgO, and P2O5 in the plantation forest, MgO and P2O5 in the secondary forest, and CaO in the slope land. Dimensionality reduction in PCA was not appropriate due to the strong spatial heterogeneity in the ecosystems. Soil mineral oxide components, the main factors in all ecosystems, had greater influences on vegetation than those of conventional soil properties. There were close relationships between soil mineral oxide components and vegetation, topography, and conventional soil properties. Mineral oxide components affected species diversity, organic matter and nitrogen levels.

Responses of soil nutrients and microbial communities to three restoration strategies in a karst area, southwest China

Ecological restoration is widespread in the karst region, southwest China, but the impacts of different restoration strategies on soil fertility indices have rarely been compared. Here soil nutrients and microbial communities were measured 16 years after agricultural abandonment in a karst area, southwest China. Three restoration strategies were included, i.e., i) restoration with an economic tree species Toona sinensis (TS), ii) restoration with Guimu-1 hybrid elephant grass (GG), iii) restoration with a combination of Zenia insignis and Guimu-1 hybrid elephant grass (ZG). Cropland under maize-soybean rotation (CR) was used as reference. Soil organic carbon level was more than doubled in TS, and that in GG and ZG was elevated by about 50% relative to CR. Soil total nitrogen concentration in GG was not significantly different from CR, but that in TS and ZG was increased by 93% and 55% relative to CR. Similar to nitrogen, soil total phosphorus concentration in GG was not changed relative to CR, but that in TS and ZG were significantly increased. Microbial biomass carbon and nitrogen concentrations were significantly increased in TS and GG by 124% and 82%, respectively, compared to CR, but those in ZG and CR were similar. The abundance of total PLFAs (phospholipid fatty acids) was significantly increased by 55-69% following agricultural abandonment, and there was no significant difference among the three restoration strategies. The patterns of the other microbial groups and the ratio of fungal to bacterial (F:B) PLFAs were largely similar to that of total PLFAs. Soil organic carbon was identified as the primary factor affecting the abundance of soil microbial communities. Our findings suggest that the three restoration strategies, particularly TS are efficient in improving soil fertility.

Spatial distribution of tree species in evergreen-deciduous broadleaf karst forests in southwest China

Understanding the spatial distribution of tree species in subtropical evergreen-deciduous broadleaf karst forest is fundamental to studying species coexistence and karst species diversity. Here, complete spatial randomness and heterogeneous Poisson process models were used to analyze the spatial distribution patterns of 146 species with at least one individual per ha in a 25-ha plot in southwest China. We used canonical correspondence analysis (CCA) and the torus-translation test (TTT) to explain the distributions of observed species. Our results show that an aggregated distribution was the dominant pattern in Mulun karst forests; the percentage and intensity of aggregated decreased with increasing spatial scale, abundance, mean diameter at breast height (DBH), and maximum DBH. Rare species were more aggregated than intermediately abundant and abundant species. However, functional traits (e.g., growth form and phenological guild) had no significant effects on the distributions of species. The CCA revealed that the four analyzed topographic variables (elevation, slope, aspect, and convexity) had significant influences on species distributions. The TTT showed that not all species have habitat preferences and that 68.5% (100 out of 146 species) show a strongly positive or negative association with at least one habitat. Most species were inclined to grow on slopes and hilltops.

Plant community characteristics and their relationships with soil properties in a karst region of southwest China

In this study, we analyzed plant community characteristics and the relationship between plant and soil properties based on forest successional stages in depressions between karst hills. The secondary forests showed the maximum number of species, genera, and families with important values >5 and the highest species diversity, and primary forest was the optimal community structure. The arboreal layer played a dominant role in determining fragile karst ecosystem status, followed by shrubs, Al2O3, and Fe2O3. A close relationship existed between species diversity and soil organic C, total N, total P, Fe2O3, MnO, microbial biomass C, and microbial biomass P. Plant characteristics could be explained by the soil nutrient factors (21.6%), soil microbes (17.1%), soil mineral components (10.2%), and interactions among these variables (29.3%).