Study On Evaluation Method Of Soil Ecosystem Services In Cultivated Land

As the most predominant agricultural production data in the Earth's life system,cultivated land is not only a powerful guarantee for soil safety,but also a key area for exploring the mechanism and energy cycle of ecosystems.It is of important theoretical and practical significance to study the composition and distribution of soil ecosystem services in arable areas,and complete accurate quantitative assessments for discovering the problems existing in the spatial distribution and management of soil resources as well as providing sustainable construction of soil ecological environment.Soil ecosystem services in cultivated areas have strong spatial heterogeneity and spatial autocorrelation.Their spatial patterns are influenced by geographical location,scale effects and soil formation factors.The coupling effects of different services in different regions are different.Therefore,it is necessary to combine digital soil mapping method to realize the visual expression and evaluation of soil ecosystem services in cultivated areas.In order to establish a set of applicable,scientific and systematic evaluation methods and indicators systems for soil ecosystem services in cultivated areas,this paper took the theory of soil ecosystem services and its classification as the basis.Using digital soil mapping methods as tools,the study selected soil ecosystem services and environmental variables in cultivated areas of Xiangyang City.Identifying the best evaluation method for each soil ecosystem service,and also assessing the trade-offs and synergies between them in the region.The research had initially achieved the following results:(1)The ecosystem services which were based on the main soil ecological functions in the study area were soil carbon sequestration function service,soil erosion regulation service as well as soil grain supply service.Among the acquired multi-source collaborative environmental information data,there were 21 indicators that can be used as pre-selected indicators for soil carbon sequestration service,9 indicators for participating in soil erosion mediation service,and 2 main indicators for participating in soil grain supply service.These indicators mainly came from topographical,biological,and climatic factors,and also included soil properties,land use types,and statistical yearbook data.(2)When evaluating and analyzing the soil carbon sequestration function service,the SOC content of all samples in the study area were between 2.376 g/kg and 26.088g/kg,which showed medium variation intensity.The nugget/sill ratio of the trend term residuals of each evaluation method showed strong spatial correlation,indicating that the local variation of SOC that may be covered by spatial non-stationarity in prediction was mainly affected by structural factors.Finally,the spatial distribution of soil carbon sequestration services assessed by Regression Kriging,Geographically Weighted Regression Kriging,Partial Least Squares Regression Kriging,Artificial Neural Network Kriging and Support Vector Machine Kriging methods which using trend and residual terms tended to be consistent.The prediction accuracy of Artificial Neural Network Kriging was increased by 28.718%,which was selected as the best evaluation method for soil carbon sequestration function service in the study area;The Revised Universal Soil Loss Equation model was selected as the evaluation framework of soil erosion regulation service.The Wischmeier formula,EPIC model,Renard formula,curve model as well as land use type assignment method were used to generate rainfall erosivity factor R,soil erodibility factor K,slope length and its steepness factor LS,vegetation cover factor C,soil and water conservation measure factor P,respectively.Then accumulating them as the potential soil erosion modulus A value in the study area,which ranging from 0.000 t/(hm~2·a)to 14.528 t/(hm~2·a).The whole area was dominated by slight erosion degree,and there was only slight erosion at some local locations;In the process of searching the spatial distribution features of soil grain yield,the county harvest index of 0.357 t·m~2/(kg·C)~1.334 t·m~2/(kg·C)was calculated by converting the total NPP of each county and the corresponding grain yield.The final evaluation results of food supply services in the study area ranging from 0.000 t to 1.088 t.The amount of grain production was also related to the classification of agricultural land,and high-quality areas produced more food.(3)The detection result of the GeoDetector in the study area was that the interpretation rate of spatial distribution of each single soil ecosystem service to others was 2.22%~21.05%.If the interaction between the two services happened,the interpretation rate can be increased from 10.42%to 28.03%,the three services were not decisive factors for each other.The global spatial autocorrelation analysis showed that the overall spatial distributions of the soil ecosystem services were highly synergistic,with strong spatial clustering phenomenon.The results of local spatial autocorrelation showed that the patches of the single soil ecosystem service synergy area were more than the trade-off area,while the patches of the synergy area between the two soil ecosystem services were generally less than the trade-off area.The spatial distribution characteristics of trade-offs and synergies between services are closely related to the results of previous soil ecosystem service evaluations.