Local singularity and S–A methods for analyzing ore-producing anomalies in the Jianbiannongchang area of Heilongjiang,China

The Heilongjiang Jianbiannongchang area is located at the confluence of the Great and Lesser Xing’an Ranges.This area has a complex magmatic and tectonic evolutionary history that has resulted in a complex and diverse geological background for mineralization.In this study,isometric logarithmic ratio(ILR)transformations of Au,Cu,Pb,Zn,and Sb contents were performed in the1:50,000 soil geochemical data of the Jianbiannongchang area.Robust principal component analysis(RPCA)was conducted based on ILR transformation.The local singularity and spectrum-area(S-A)methods were used to extract information on mineralogic anomalies.The results showed that:(1)the transformed data eliminated the influence of the original data closure effect,and the PC1and PC2 information obtained by applying RPCA reflected ore-producing element anomalies dominated by Au and Cu.(2)The local singularity method can enhance the information of the local strong and weak slow anomalies.After performing local singularity analysis on PC1 and PC2,the obtained local anomalies reflected the local singularity spatial anomaly patterns related to Cu and Au mineralization in this area,which is an effective method for trapping ore-producing anomalies.(3)Furthermore,the composite anomaly decomposition of PC1 and PC2 was performed using the S-A method,and the screened anomalous and background fields reflect the ore-producing anomalies related to Cu and Au mineralization.This information is in agreement with known Cu and Au mineralization.(4)The geochemical anomalies with mineralization potential were obtained outside the known mineralization sites by integrating the information of oreproducing anomalies extracted by the local singularity and S-A methods,providing the theoretical basis and exploration direction for future exploration in the study area.

Relationship between diversity of forest plant and community dynamics in eastern mountain area of Heilongjiang Province, China

The biodiversity was studied in 26 communities with different structures in Maoershan National Park and Liangshui Natural Reserve of Northeast Forestry University in Heilongjiang Province, China. Composition index （CI） was taken as a parameter to quantify the community dynamics, which can nicely describe forest community dynamics, meanwhile, the relationship between diversity and community dynamics were also investigated and analyzed. Results showed that the total number species of community, richness, evenness, and Shannon-Wiener diversity index were obviously different in every community. The richness decreased with the increasing CI of every community, which means richness was in inverse proportion to community dynamics. The Shannon-Wiener index of every community increased from the initial stage to the middle stage of succession, and then decreased in the climax stage. The coverage weighted foliage-height diversity index increased along with the increase of CI, which was similar as the oattem diversity.