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Unmanned aerial vehicle (UAV) remote sensing technology is gradually playing a role alternative to traditional field survey methods in monitoring plant functional traits of forest ecology. Few studies focused on monitoring functional trait ecology of underground forests of inaccessible negative terrain with UAV. The underground forests of tiankeng were discovered and are known as the inaccessible precious ecological refugia of extreme negative terrain. The aim of this research proposal is to explore the suitability of UAV technology for extracting the stand parameters of underground forests’ functional traits in karst tiankeng. Based on the multi-scale segmentation algorithm and object-oriented classification method, the canopy parameters (crown width and densities) of underground forests in degraded karst tiankeng were extracted by UAV remote sensing image data and appropriate features collection. First, a multi-scale segmentation algorithm was applied to attain the optimal segmentation scale to obtain the single wood canopy. Second, feature space optimization was used to construct the optimal feature space set for the image and then the k-nearest neighbor(k-NN) classifier was used to classify the image features. The features were classified into five types: canopy, grassland, road, gap, and bare land. Finally, both the crown densities and average crown width of the trees were calculated, and their accuracy were verified. The results showed that overall accuracy of object-oriented image feature classification was 85.60%, with 0.72 of kappa coefficient. The accuracy of tree canopy density extraction was 82.34%, for which kappa coefficient reached 0.91. The average canopy width of trees in the samples from the tiankeng-inside was 5.38 m, while that of the outside samples was 4.83 m. In conclusion, the canopy parameters in karst tiankeng were higher than those outside the tiankeng. Stand parameters extraction of karst tiankeng underground forests based on UAV remote sensing was relatively satisfactory. Thus, UAV technology provides a new approach to explore forest resources in inaccessible negative terrain such as karst tiankengs. In the future, we need to consider UAVs with more bands of cameras to extract more plant functional traits to promote the application of UAV for underground forest ecology research of more inaccessible negative terrain.

During the past several decades, the carbon budget in the dryland ecosystem has experienced great variation under the joint impact of climate change and anthropogenic interference. How the net ecosystem productivity (NEP) responds to climate change and human interference in the Qilian Mountains (QLM), Northwest China, remains unclear. To fill these gaps, we first estimated the NEP in the QLM and then quantified the independent and interactive influences of natural environment factors, climatic factors, and human activity intensity on the NEP change from 2000 to 2020 by linking the Geodetector and structural equation models. The NEP of the QLM showed a significant increase during the recent 20 years, and 78.93% of the QLM experienced a significant increase in NEP; while only 4.83% of the area in the QLM experienced a decreasing trend, which is dominantly located on the southeast edge, surrounding the Qinghai Lake, and the midland of the QLM. The area percentage of the carbon sink region increased from 47% in 2000 to 62% in 2020. The natural environment factors (e.g., altitude and soil type) and climate factors (e.g., temperature and precipitation) were the dominant factors that determine the spatial distribution of NEP. Compared with a single factor, the interaction of pairs of factors enhanced the influence strength on NEP. The natural environment factors indirectly affected NEP change through influencing human activities intensity and climatic factors. Human activities intensity played a medium indirectly negative effect on NEP, while climatic factors exerted strong direct and indirect positive influences on NEP. The contributions of human activity intensity, climatic factors, and natural environment on NEP change in the QLM were 33.5%, 62.3%, and 38.3%, respectively. Overall, warming and wetting shifts in meteorological conditions offset the negative impact of human activities on NEP in the QLM, and the QLM has acted as a growing carbon sink in the past 20 years.