A comparison of metric scoring and health status classification methods to evaluate benthic macroinvertebrate-based index of biotic integrity performance in Poyang Lake wetland.

Methods for metric scoring and health status classification in development of index of biotic integrity (IBI) vary considerably across published studies. The difference between ecosystem health assessment results from these alternative methods for scoring and classification has rarely been studied systematically. Poyang Lake in China has experienced severe degradation over recent decades. Here, we aimed to develop a benthic macroinvertebrate-based index of biotic integrity (B-IBI) to assess the wetland health of Poyang Lake, and to evaluate the difference in assessment results using different methods of scoring and classification. Data on benthic macroinvertebrate assemblages, water quality and human-induced disturbances were collected at 30 sampling sites. Forty-nine attributes of macroinvertebrate assemblages were tested, and only the attributes that were significantly correlated with disturbance gradients or showed strong discriminatory power between reference and impaired sites were selected as the B-IBI metrics. Two scoring, two thresholding and three classification methods were applied for metric scoring and health status classification. Five assemblage attributes, i.e. the number of taxa, Shannon-Wiener diversity index, % Diptera, ASPT index and the number of predator taxa, were selected as the B-IBI metrics. Health status assessments varied considerably among the various metric scoring and classification methods, suggesting the importance of standardizing the methods for scoring and classification to be able to compare assessment results across different areas and time periods. The wetland health of Poyang Lake was rated as fair, which indicates that the wetland has experienced anthropogenic pressure and substantial changes in macroinvertebrate assemblage structure. Further, sample sites adjacent to tributary river mouths were in poor or very poor condition, suggesting that pollutant input by rivers has strong negative impacts on wetland health. Effective management of the entire lake basin and its watershed is therefore important for the wetland conservation.

Taxonomic bias in occurrence information of angiosperm species in China.

Taxonomic bias is a well-known shortcoming of species occurrence databases. Understanding the causes of taxonomic bias facilitates future biological surveys and addresses current knowledge gaps. Here, we investigate the main drivers of taxonomic bias in occurrence data of angiosperm species in China. We used a database including 5,936,768 records for 28,968 angiosperm species derived from herbarium specimens and literature sources. Generalized additive models (GAMs) were applied to investigate explanatory powers of 17 variables on the variation in record numbers of species. Five explanatory variables were selected for a multi-predictor GAM that explained 69% of the variation in record numbers: plant height, range size, elevational range, numbers of scientific publications and web pages. Range size was the most important predictor in the model and positively correlated with number of records. Morphological and phenological traits and social-economic factors including economic values and conservation status had weak explanatory powers on record numbers of plant species, which differs from the findings in animals, suggesting that causes of taxonomic bias in occurrence databases may vary between taxonomic groups. Our results suggest that future floristic surveys in China should more focus on range-restricted and socially or scientifically less "interesting" species.

[Effects of Land Use Types at Different Spatial Scales on Water Quality in Poyang Lake Wetland].

Water is a crucial environmental element that affects various ecological processes in wetlands. Poyang Lake is the largest freshwater lake in China, where seasonal variation in water level generates a unique landscape of wetland in the dry season-a critical habitat for Siberian migratory birds. Nevertheless, the water quality of the Poyang Lake wetland has not been systematically and rigorously studied. In this study, we analyzed the spatial pattern of water quality in the Poyang Lake wetland based on four key physicochemical parameters[i.e. chlorophyll-a (Chl-a), chemical oxygen demand using permanganate index, total nitrogen (TN), total phosphorus (TP)] at 30 randomly selected sample sites. We also investigated the relationships between water quality parameters and land use types at different spatial scales. We found that water quality at the sample sites varied from level III (fair) to level V (very poor), with an average of level IV (poor). TN and TP were the main pollutants in the water of Poyang Lake wetland, while Chl-a content and permanganate index were comparatively low. There were significant correlations between water quality parameters and land use types at different spatial scales. Land use types within a 500 m buffer zone had the strongest explanatory power on the spatial variation of permanganate index, while those within a 1 km buffer zone had the strongest relationships with Chl-a, TN, TP, and the overall water quality. Land use types in buffer zones exhibited stronger explanatory power than those at watershed scales. Built-up land was positively correlated with all water quality parameters, while farmland had positive relationships with TN and TP. Rivers within a 200 m buffer zone were positively correlated with TN and TP, indicating that the river input might be an important source of nitrogen and phosphorus in Poyang Lake. The percentage of lake area had negative relationships with Chl-a, TN, and TP, suggesting that wetland was a source of pollutants compared with the main region of Poyang Lake. Our study shows that controlling the land use patterns within small spatial scales (≤ 1 km), especially minimizing the area of built-up land and farmland, is important for the protection of water resources in the Poyang Lake wetland.

Effects of land use, topography, climate and socio-economic factors on geographical variation pattern of inland surface water quality in China.

The deterioration of water quality has become a primary environmental concern worldwide. Understanding the status of water quality and identifying the influencing factors are important for water resources management. However, reported analyses have mostly been conducted in small and focused areas. It is still unclear if factors driving spatial variation in water quality would be different in extended spatial scales. In this paper, we analyzed spatial pattern of inland surface water quality in China using a dataset with four water quality parameters (i.e., pH, DO, NH4+-N and CODMn) and the water quality level. We tested the effects of anthropogenic (i.e., land use and socio-economic) and natural (i.e., climatic and topographic) factors on spatial variation in water quality. The study concluded that the overall inland surface water quality in China was at level III (fair). Water quality level was strongly correlated with CODMn and NH4+-N concentration. In contrast to reported studies that suggested land use patterns were the determinants of inland surface water quality, this study revealed that both anthropogenic and natural factors played important roles in explaining spatial variation of inland surface water quality in China. Among the tested explanatory variables, mean elevation within watershed appeared as the best predictor for pH, while annual precipitation and mean air temperature were the most important explanatory variables for CODMn and DO, respectively. NH4+-N concentration and water quality level were most strongly correlated with the percent of forest cover in watershed. Compared to studies at smaller spatial scales, this study found different influencing factors of surface water quality, suggesting that factors may play different roles at different spatial scales of consideration. Therefore management policies and measures in water quality control must be established and implemented accordingly. Since currently adopted parameters for monitoring of inland surface water quality in China are largely influenced by natural variables, additional physicochemical and biological indicators are needed for a robust assessment of human impacts on water quality.