We analyzed the spatial local accuracy of land cover (LC) datasets for the Qiangtang Plateau, High Asia, incorporating 923 field sampling points and seven LC compilations including the International Geosphere Biosphere Programme Data and Information System (IGBPDIS), Global Land cover mapping at 30 m resolution (GlobeLand30), MODIS Land Cover Type product (MCD12Q1), Climate Change Initiative Land Cover (CCI-LC), Global Land Cover 2000 (GLC2000), University of Maryland (UMD), and GlobCover 2009 (Glob-Cover). We initially compared resultant similarities and differences in both area and spatial patterns and analyzed inherent relationships with data sources. We then applied a geographically weighted regression (GWR) approach to predict local accuracy variation. The results of this study reveal that distinct differences, even inverse time series trends, in LC data between CCI-LC and MCD12Q1 were present between 2001 and 2015, with the exception of category areal discordance between the seven datasets. We also show a series of evident discrepancies amongst the LC datasets sampled here in terms of spatial patterns, that is, high spatial congruence is mainly seen in the homogeneous southeastern region of the study area while a low degree of spatial congruence is widely distributed across heterogeneous northwestern and northeastern regions. The overall combined spatial accuracy of the seven LC datasets considered here is less than 70%, and the GlobeLand30 and CCI-LC datasets exhibit higher local accuracy than their counterparts, yielding maximum overall accuracy (OA) values of 77.39% and 61.43%, respectively. Finally, 5.63% of this area is characterized by both high assessment and accuracy (HH) values, mainly located in central and eastern regions of the Qiangtang Plateau, while most low accuracy regions are found in northern, northeastern, and western regions.
Non-crop habitats have been suggested to impact local biodiversity significantly in agricultural landscapes. However, there have been few studies of the effects of less-focused non-crop habitats(orchard, wetland, pit and ditch) on variation of spider abundance. In this study, spiders in 30 woodlands were captured using pitfall traps in Fengqiu County, China, and the effects of local and landscape variations at different scales(50 m, 100 m, 200 m, 350 m and 500 m) on spider abundance were analysed. The most important variation that influenced spider abundance at the 500 m scale was the less-focused non-crop habitat(LNH) cover, and 10% was an appropriate proportion of LNH cover to sustain high level of spider diversity in the investigated landscape. Non-metric multidimensional scaling analyses revealed that there were significant differences in the spider composition among the high, medium and low LNH coverage. Based on indicator species analysis, different spider species were associated with landscapes with different levels of LNH cover. Lycosidae, which accounted for 48% of the total specimens, preferred woodland habitats neighbouring areas with high LNH cover. Compared with woodland habitats, LNH provided more diverse food sources and habitat to sustain more spider species in the study area. Furthermore, linear elements composed of vegetation, such as pits and ditches, may prevent agricultural intensification by enhancing landscape connectivity and providing habitats for different spiders. Our findings may provide a theoretical basis for biodiversity conservation in agro-ecosystems and top-down control of pests. 相似文献
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