Identifying the spatial drivers of net primary productivity: A case study in the Bailong River Basin, China

Net primary productivity (NPP) is an important indicator of regional vegetation growth status and ecosystem health. In the ecologically fragile Bailong River Basin (BRB) of China, particularly in its arid valley (AV) region, vegetation is extremely sensitive to anthropogenic interferences and natural influences. Therefore, there is an urgent need to identify NPP drivers in this region. Human activities shape the landscape and affect NPP dynamics. In addition, other factors including climate, soil, and topography play pivotal roles in NPP dynamics. Hence, identifying the interactions among these variables is essential for environmental management. Here, we aimed to identify the key drivers of spatial variation in NPP and evaluate the associations among these variables. We calculated the NPP based on moderate resolution imaging spectrometer data from 2018. Redundancy analysis and variation partitioning were used to identify the key drivers and to determine the unique, shared, and total explanatory variables of these sets of variables in the BRB and AV. The spatial heterogeneity of vegetation NPP was evident, and NPP in the north was lower than that in the south. Moreover, the natural and social factors of various townships in the two regions synergistically controlled vegetation growth. In the BRB, the first four axes explained 83.4% of the total variation in NPP across all townships. Meanwhile, in the AV, the first four axes explained only 80.06% of the total variation in NPP. Mean annual temperature, solar radiation, elevation, and slope were identified as the key drivers of NPP. Variation partitioning revealed complex inter-relationships among all sets of variables, with most explanatory variables being unique or shared; as such, climate factors was important explanatory variables of NPP in the BRB. In the AV, NPP was the most affected by topographic factors. Our results may aid the policymakers and planners in implementing sustainable vegetation restoration and conservation programs.