Modeling potential wetland distributions in China based on geographic big data and machine learning algorithms

Climate change and human activities have reduced the area and degraded the functions and services of wetlands in China.To protect and restore wetlands,it is urgent to predict the spatial distribution of potential wetlands.In this study,the distribution of potential wetlands in China was simulated by integrating the advantages of Google Earth Engine with geographic big data and machine learning algorithms.Based on a potential wetland database with 46,000 samples and an indicator system of 30 hydrologic,soil,vegetation,and topographic factors,a simulation model was constructed by machine learning algorithms.The accuracy of the random forest model for simulating the distribution of potential wetlands in China was good,with an area under the receiver operating characteristic curve value of 0.851.The area of potential wetlands was 332,702 km^(2),with 39.0%of potential wetlands in Northeast China.Geographic features were notable,and potential wetlands were mainly concentrated in areas with 400-600 mm precipitation,semi-hydric and hydric soils,meadow and marsh vegetation,altitude less than 700 m,and slope less than 3°.The results provide an important reference for wetland remote sensing mapping and a scientific basis for wetland management in China.

Effects of Wetland Utilization Change on Spatial Distribution of Soil Nematodes in Heihe River Basin, Northwest China

The first account of the effects of wetland reclamation on soil nematode assemblages were provided, three sites in Heihe River Basin of Northwest China, that is grass wetland(GW), Tamarix chinensis wetland(TW) and crop wetland(CW) treatments, were compared. Results showed that the majority of soil nematodes were presented in the 0–20 cm soil layers in CW treatments, followed by in the 20–40 cm and 40–60 cm layers in GW treatments. Plant-feeding nametodes were the most abundant trophic groups in each treatment, where GW(91.0%) > TW(88.1%) > CW(53.5%). Generic richness(GR) was lower in the TW(16) than that in GW(23) and CW(25). The combination of enrichment index(EI) and structure index(SI) showed that the soil food web in GW was more structured, and those in TW was stressed, while the enrichment soil food web was presented in the CW treatment. Several ecological indices which reflected soil community structure, diversity, Shannon-Weaver diversity(H′), Evenness(J′), Richness(GR) and modified maturity index(MMI) were found to be effective for assessing the response of soil namatode communities to soil of saline wetland reclamation. Furthermore, saline wetland reclamation also exerted great influence on the soil physical and chemical properties(p H, Electric conductivity(EC), Total organic carbon(TOC), Total nitrogen(Total-N) and Nitrate Nitrogen(N-NO3–)). These results indicated that the wetland reclamation had significantly effects on soil nematode community structure and soil properties in this study.

WETLANDS IN CHINA: FEATURE, VALUE AND PROTECTION

The estimated total area of wetland in China is more than 25.9 million hectares including about 11.9 million hectares of marshes and bogs, 9.1 million hectares of lake and about 2.2 million hectares of coastal salt marshes and mudflats. The area of wetland is equivalent to 2.7％ of the land surface. China also has 2.7 million hectares of shallow sea water (less 5m in depth at low tide). Marshes and bogs are equivalent 1.3％ of the land surface. Only three provinces(regions)— Qinghai, Xizang (Tibet)and Heilongjiang— have a larger total area of marsh and bog. According to the structure, type and development of wetland in different river basins, wetland can be classified nine main regions. The experiments indicate that the coefficient of the marsh to regulate flood is similar to that of lakes. Wetlands occupy 17.8％ of the Sanjiang Plain area, the annual carbon contribution is 0.78× 104t. Carbon released from marsh soil return into atmosphere is 3.95× 106t/a. At present there is a sharp contradiction between population growth and natural resources shortage, causing wetland to be exerted with huge pressures and serious threats.

Suitability mapping of global wetland areas and validation with remotely sensed data

With increasing urbanization and agricultural expansion, large tracts of wetlands have been either disturbed or converted to other uses. To protect wetlands, accurate distribution maps are needed. However, because of the dramatic diversity of wetlands and difficulties in field work, wetland mapping on a large spatial scale is very difficult to do. Until recently there were only a few high resolution global wetland distribution datasets developed for wetland protection and restoration. In this paper, we used hydrologic and climatic variables in combination with Compound Topographic Index （CTI） data in modeling the average annual water table depth at 30 arc-second grids over the continental areas of the world except for Antarctica. The water table depth data were modeled without considering influences of anthropogenic activities. We adopted a relationship between poten- tial wetland distribution and water table depth to develop the global wetland suitability distribution dataset. The modeling re- suits showed that the total area of global wetland reached 3.316× 10^7 km^2. Remote-sensing-based validation based on a compi- lation of wetland areas from multiple sources indicates that the overall accuracy of our product is 83.7%. This result can be used as the basis for mapping the actual global wetland distribution. Because the modeling process did not account for the im- pact of anthropogenic water management such as irrigation and reservoir construction over suitable wetland areas, our result represents the upper bound of wetland areas when compared with some other global wetland datasets. Our method requires relatively fewer datasets and has a higher accuracy than a recently developed global wetland dataset.