/* DATA DESCRIPTION: Citation: Zhi, Shuqi; Lou, Ruitao; Zhang, Ke; Chen, Xianglin; Ren, Yan; Liu, Ying: A Meta-Analysis Dataset on the Effects of Mixed-Species Transformation on Plantation Ecosystem Functions [dataset]. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.992528 (dataset in review) Abstract: This database presents a comprehensive collection of soil and climatic variables associated with the ecological functioning of pure and mixed forest ecosystems across China. It is designed to support comparative analyses and modeling studies on forest management, biodiversity, and ecosystem services.The dataset encompasses key soil properties—including soil organic carbon, pH, bulk density, and moisture content—alongside critical climate variables such as mean annual temperature, precipitation, and seasonal climatic extremes. Data were compiled from field surveys, national forest inventories, and meteorological monitoring networks, standardized and georeferenced for consistent spatial analysis. Focusing on the contrast between pure-species plantations and multi-species mixed forests, this resource enables researchers to examine how forest composition influences soil health, nutrient cycling, water regulation, and carbon sequestration under varying climatic conditions. The database is particularly valuable for studies on sustainable forestry, climate change resilience, and ecological restoration. All data have undergone quality control and harmonization, with metadata provided for traceability. The dataset is available in structured tabular format and can be accessed for non-commercial research purposes to advance understanding of forest ecosystem responses to environmental and management drivers. Keyword(s): Climate data; ecosystem functioning; mixed forest; soil properties Source: Abbas, Fakher; Zhu, Zhaolong; An, Shaoshan (2021): Evaluating aggregate stability of soils under different plant species in Ziwuling Mountain area using three renowned methods. CATENA, 207, 105616, https://doi.org/10.1016/j.catena.2021.105616 (Dataset reference ID 18) Bai, Xiu-mei; Han, You-zhi; Guo, Han-qing (2014): Study on Soil Anti erodibility of Different Vegetation Restoration Types in Guandi Mountain. (in Chinese with English abstract), Journal of Soil and Water Conservation, 28(02), 79-84, https://doi.org/10.13870/j.cnki.stbcxb.2014.02.015 (Dataset reference ID 28) Bai, Xuejuan; Wang, Baorong; An, Shaoshan; Zeng, Quanchao; Zhang, Haixin (2019): Response of forest species to C:N:P in the plant-litter-soil system and stoichiometric homeostasis of plant tissues during afforestation on the Loess Plateau, China. CATENA, 183, 104186, https://doi.org/10.1016/j.catena.2019.104186 (Dataset reference ID 19) Cao, Yu-chao; Lu, Jinping; Ma, Jiejiao; Wei, Haoliang (2025): Effects of different vegetation restoration models on soil nutrient content in stony mountain of Yanshan. (in Chinese), Forestry and Ecological Sciences, 40(02), 189-196, https://doi.org/10.13320/j.cnki.hjfor.2025.0022 (Dataset reference ID 115) Chen, Guoping; Gao, Zhangying; Zu, Lihong; Tang, Lili; Yang, Tong; Feng, Xiaomei; Zhao, Tiejian; Shi, Fuchen (2017): Soil aggregate characteristics and stability of soil carbon stocks in a Pinus tabulaeformis plantation. New Forests, 48(6), 837-853, https://doi.org/10.1007/s11056-017-9600-x (Dataset reference ID 17) Chen, Hai; Zhu, Dayun; Chen, Hu (2021): Effects of land-use patterns on soil aggregate stability and organic carbon in rocky desertification areas. (in Chinese with English abstract), Carsologica Sinica, 40(02), 346-354, https://doi.org/10.11932/karst20210211 (2021a, Dataset reference ID 56) Chen, Jia; Chen, Hong-Song; Feng, Teng; Wang, Ke-Lin; Zhang, Wei (2012): Anti-soil erodibility of different land use types in Northwest Guangxi Karst Regions. (in Chinese with English abstract), Chinese Journal of Eco-Agriculture, 20(1), 105-110, https://doi.org/10.3724/SP.J.1011.2012.00105 (Dataset reference ID 65) Chen, Qiang; Chang, En-fu; Bi, Bo; Li, Pin-rong; Yin, Ai-ping; Liu, Yong-guo; Nong, Shi-zhen (2006): Study on Conservation of Soil and Water in Three Different Forestation Modes in Karst Area of Southeastern of Yunnan. (in Chinese), Journal of Soil and Water Conservation, 5, 1-4+33, https://doi.org/10.13870/j.cnki.stbcxb.2006.05.001 (Dataset reference ID 30) Chen, Rui; Cheng, Ke; Guo, Yanhui; Yang, Xitian; Wang, Teng; Xiao, Yang; Feng, Zhipei (2025): Spatial distribution characteristics of leaf-eating pestdamage in Quercus variabilis forest and its environmental driving factors. (in Chinese), Journal of Henan Agricultural University, 1-12, https://doi.org/10.16445/j.cnki.1000-2340.20250416.001 (Dataset reference ID 79) Chen, Shiqi; Zhang, Guanghui; Zhu, Pingzong; Wang, Chengshu; Wan, Yuanqiang (2023): Impact of land use type on soil erodibility in a small watershed of rolling hill northeast China. Soil & Tillage Research, 227, 105597, https://doi.org/10.1016/j.still.2022.105597 (Dataset reference ID 14) Chen, Tao; Zhou, Lijun; Qi, Shi; Sun, Baoping; Nie, Zexu (2021): Soil aggregate stability and anti-erodibility of typical forest stands in Huaying mountain area. (in Chinese with English abstract), Journal of Zhejiang A&F University, 38(06), 1161-1169, https://doi.org/10.11833/j.issn.2095-0756.20210142 (2021b, Dataset reference ID 37) Chen, Ying; Wei, Xingping; Lei, Shan (2020): Analysis on soil erodibility of different land use types in the Qingmuguan karst valley. (in Chinese with English abstract), 39(6), 836-844, https://doi.org/10.11932/karst20200604 (Dataset reference ID 66) Chen, Yuanqi; Zhang, Yu; Yu, Shiqin; Li, Feng; Liu, Suping; Zhou, Lixia; Fu, Shenglei (2021): Responses of soil labile organic carbon and water-stable aggregates to reforestation in southern subtropical China. Journal of Plant Ecology, 14(2), 191-201, https://doi.org/10.1093/jpe/rtaa087 (2021c, Dataset reference ID 38) Chen, Yuxuan; Ren, Kang; Wei, Tianxing; Sha, Guoliang; Yu, Huan; Fan, Dehui; Zhou, Wenjie; Ding, Xuewei; Feng, Huancheng (2024): Response of understory plant species diversity to plant mixture on the Loess Plateau: A case study of Hippophae rhamnoides. Land Degradation & Development, 35(6), 2201-2213, https://doi.org/10.1002/ldr.5054 (Dataset reference ID 23) Chu, Xiao-yuan; Wang, Yu-jie; Liu, Nan; Qi, Na; Yang, Xiao-mei; Shen, Yan-ke (2009): Micro-aggregates Characteristics Analysis in the Soil of Typical Forests in Jinyun Mountain in Chongqing City. (in Chinese), Chinese Journal of Soil Science, 40(06), 1240-1244, https://doi.org/10.19336/j.cnki.trtb.2009.06.002 (Dataset reference ID 43) Deng, Wangang; Wu, Weidong; Wang, Hailong; Luo, Wei; Kimberley, Mark O (2009): Temporal dynamics of iron-rich, tropical soil organic carbon pools after land-use change from forest to sugarcane. Journal of Soils and Sediments, 9(2), 112-120, https://doi.org/10.1007/s11368-008-0053-x (Dataset reference ID 70) Dong, Lingbo; Tang, Yaru; Tian, Dongyuan; Liu, Zhaogang; Lin, Xueying (2023): Evaluating the structure complexity of different forest types in the central part of the Greater Khingan Mountains. Journal of Nanjing Forestry University (Natural Sciences Edition), 47(05), 147-155, https://doi.org/10.12302/j.issn.1000-2006.202112016 (Dataset reference ID 121) Dou, Yanxing; Yang, Yang; An, Shaoshan; Zhu, Zhaolong (2020): Effects of different vegetation restoration measures on soil aggregate stability and erodibility on the Loess Plateau, China. CATENA, 185, 104294, https://doi.org/10.1016/j.catena.2019.104294 (Dataset reference ID 11) Du, Jianping (2023): Study on Stand Growth and Vegetation Characteristics of Larix gmelinii-Pinus strobus L. Mixed Forest in Eastern Liaoning Mountainous Area. (in Chinese), Journal of Anhui Agricultural Sciences, 50(18), 127-130 (Dataset reference ID 108) Fan, Chuan; Zhou, Yigui; Li, Xianwei; Zhang, Jian; Liao, Hongliu; Li, Fengting; Feng, Maosong (2014): Comparison of Soil Anti-Erodibility of Different Modes for Reforming Low Efficiency Stands of Cupressus funebris. (in Chinese with English abstract), Scientia Silvae Sinicae, 50(06), 107-114 (Dataset reference ID 62) Fan, Rong-yuan; Ye, Shao-ming; Zhang, Qian-chun; He, Ya-qin; Deng, Jia-zhen (2023): Characteristics of Active Organic Carbon Components in Soil Aggregates of Pure Plantation of C.lanceolata and Its Mixed Forest. (in Chinese), Journal of Northwest Forestry University, 38(06), 20-28+37 (Dataset reference ID 104) Fang, Wei; Fan, Tao (2020): Differences in Soil Aggregate Stability of Different Species of Pinus Yunnanensis inKarst Mountain Area of Eastern Yunnan Province. (in Chinese), Bulletin of Soil and Water Conservation, 40(03), 95-102+132, https://doi.org/10.13961/j.cnki.stbctb.2020.03.014 (Dataset reference ID 60) Gao, Guannv; Huang, Xueman; Xu, Haocheng; Wang, Yi; Shen, Weijun; Zhang, Wen; Yan, Jinliu; Su, Xiaoyan; Liao, Shushou; You, Yeming (2022): Conversion of pure Chinese fir plantation to multi-layered mixed plantation enhances the soil aggregate stability by regulating microbial communities in subtropical China. Forest Ecosystems, 9, 100078, https://doi.org/10.1016/j.fecs.2022.100078 (Dataset reference ID 63) Gong, Shihao; Zhang, Xiaoxia; Zhang, Hengshuo; Gao, Lianwei; Zha, Tonggang (2025): Nitrogen addition promotes the coupling of deep soil carbon and nitrogen under different vegetation restoration types in the Chinese Loess Plateau. Geoderma, 455, 117236, https://doi.org/10.1016/j.geoderma.2025.117236 (Dataset reference ID 20) Guo, Geng; Li, Xiao; Zhu, Xi; Xu, Yanyin; Dai, Qiao; Zeng, Guangruo; Lin, Jie (2021): Effect of Forest Management Operations on Aggregate-Associated SOC Dynamics Using a 137Cs Tracing Method. Forests, 12(7), 859, https://doi.org/10.3390/f12070859 (Dataset reference ID 7) Guo, Mingming; Wang, Wenlong; Kang, Hongliang; Yang, Bo (2018): Changes in soil properties and erodibility of gully heads induced by vegetation restoration on the Loess Plateau, China. Journal of Arid Land, 10(5), 712-725, https://doi.org/10.1007/s40333-018-0121-z (Dataset reference ID 4) He, Ming-xia; Huang, Xue-man; You, Ye-ming; Wang, Bo; Tong, Hui; Yang, Xin-ran; Ming, Ang-ang; Zhao, Li-jun; Luan, Jun-wei (2025): Regulatory mechanism of root-mycelial-microorganism interactions on soil phosphorus transformation of Pinus massoniana plantation under mixed renovation. (in Chinese), Journal of Beijing Forestry University, 47(3), 83-94, https://doi.org/10.12171/j.1000-1522.20240322 (Dataset reference ID 80) He, Yuxuan; He, Jienan; Gao, Ling (2024): Study on Understory Vegetation Diversity of Cunninghamia lanceolata Mixed Forest. (in Chinese), Green Science and Technology, 26(04), 89-95, https://doi.org/10.16663/j.cnki.lskj.2024.04.018 (Dataset reference ID 102) Hong, Yicong (2017): Soil Fertility and Water Conservation of Different-aged Compound Storied Castanopsis fissa and Cunninghamia lanceolata Plantations. (in Chinese), Journal of Northeast Forestry University, 45(11), 65-71, https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 (Dataset reference ID 33) Hou, Yiyang; Ye, Shaoming; Wang, Shengqiang (2025): Study on Zymometric Properties of Soil Aggregates in Pure and Mixed Eucalyptus Forest. (in Chinese), Journal of Southwest Forestry University (Natural Sciences), 45(05), 110-119 (Dataset reference ID 88) Hu, Hai-qing; Liu, Yang; Sun, Long; Cai, Ti-jiu; Song, Li-chen (2008): Effect of Fire on Soil Hydro-physical Properties under Different Types of Forest Land. Journal of Soil and Water Conservation, (02), 162-165, https://doi.org/10.13870/j.cnki.stbcxb.2008.02.045 (Dataset reference ID 126) Hu, Wanliang; Tan, Xueren; Ding, Guoquan; Ding, Lei; Jin, Xin (2012): Ecological and Economic Benefits of Water Conservation Forests in Eastern Mountainous Region of Liaoning Province After Different Types of Alteration. (in Chinese), Journal of Northeast Forestry University, 40(02), 50-53+92, https://doi.org/10.13759/j.cnki.dlxb.2012.02.008 (Dataset reference ID 58) Huang, X L (2023): Effects of Mixed Planting of Eucalyptus grandis and Fokienia hodginsii on Forest Growth and Soil Nutrients. (in Chinese), Anhui Agricultural Science Bulletin, 29(19), 43-46, https://doi.org/10.16377/j.cnki.issn1007-7731.2023.19.008 (Dataset reference ID 106) Huang, Zhigang; Ouyang, Zhiyun; Li, Fengrui; Zheng, Hua; Wang, Xiaoke (2010): Response of runoff and soil loss to reforestation and rainfall type in red soil region of southern China. Journal of Environmental Sciences, 22(11), 1765-1773, https://doi.org/10.1016/S1001-0742(09)60317-X (Dataset reference ID 41) Jia, K D; Wang, Y Q; Gao, Y; Zhou, Z Y (2024): Variability of Soil Organic Carbon Pool in Different Coniferous Pure Forests and Mixed Forests in Taiyue Mountain，Shanxi Province. (in Chinese), Journal of Northeast Forestry University, 52(03), 112-118, https://doi.org/10.13759/j.cnki.dlxb.2024.03.008 (Dataset reference ID 103) Jiang, Lu; Zhang, Pifang; Wang, Jun; Qin, Xiaopeng; Wang, Hailun; Zhou, Shixing; Huang, Congde (2024): Effects of constructing mixed forests on understory shrub and herbs pecies diversity after clear-cutting of Eucalyptus grandis pure forest [webpage]. (in Chinese), Chinese Journal of Applied and Environmental Biology, 30(03), 477-484, https://doi.org/10.19675/j.cnki.1006-687x.2023.06021 (2024a, Dataset reference ID 100) Jiang, Nianchun; Qiu, Yongbin; Zhang, Nengjun; Xuan, Lingjuan; Zheng, Weijian; Huang, Gan; Hu, Weiming (2024): Characteristics of Litter and Soil Nutrient Content and Stoichiometric Ratio in Mixed Forest Cunninghamia lanceolata and Broadleaved Trees. (in Chinese), Journal of Zhejiang Forestry Science and Technology, 44(04), 1-6, https://doi.org/10.3969/j.issn.1001-3776.2024.04.001 (2024b, Dataset reference ID 96) Kong, Tongwei; Liu, Binhui; Henderson, Mark; Zhou, Wanying; Su, Yuanhang; Wang, Shuai; Wang, Ligang; Wang, Guibin (2022): Effects of Shelterbelt Transformation on Soil Aggregates Characterization and Erodibility in China Black Soil Farmland. Agriculture, 12(11), 1917, https://doi.org/10.3390/agriculture12111917 (Dataset reference ID 10) Li, Changzhun; Wang, Qingcheng; Wu, Huirong; Zhang, Yong; Ma, Shuangjiao; Xu, Liqing (2024): Effects of tree species composition in plantation forest on soil aggregate stability and organic carbon pools in northeastern China. Geoderma Regional, 39, e00899, https://doi.org/10.1016/j.geodrs.2024.e00899 (Dataset reference ID 52) Li, Dan; Yang, Liping; Jia, Chengzhen (2021): Characteristics of Ground Surface Dead Fuel Moisture Content for Different Stand Types in Great Xing'an Mountains and Relevant Affecting Factors. (in Chinese), Journal of Arid Meteorology, 39(01), 144-150 (Dataset reference ID 123) Li, Peng; Yang, Zhangqi; Yan, Peidong; Wu, Dongshan (2022): Quality evaluation of mixed plantations of Pinus massoniana and Castanopsis hystrix based on the soil erosion characteristics and soil physical and chemical properties. (in Chinese), Journal of Central South University of Forestry & Technology, 42(04), 104-116, https://doi.org/10.14067/j.cnki.1673-923x.2022.04.012 (Dataset reference ID 42) Li, Qian; Sun, Hanyu; Yang, Yanfen; Deng, Hanxiao; Cao, Zetao; Bian, He (2025): Characteristics of Understory Herbaceous Vegetation in Mixed Plantations andTheir Effects on Herbaceous Interception in Loess Hilly Areas. (in Chinese), Journal of Soil and Water Conservation, 39(03), 163-171, https://doi.org/10.13870/j.cnki.stbcxb.2025.03.008 (Dataset reference ID 77) Liang, Bo; Nie, Xiaogang; Wan, Dan; Yu, Wu; Sun, Qiwu; Zhao, Wei (2018): Impacts of Forest Typical of the Southern Piedmont of the Himalaya Mountains on Soil Physicochemical Properties and Erodibility K. (in Chinese), Acta Pedologica Sinica, 55(06), 1377-1388 (Dataset reference ID 46) Liang, Hao; Wu, Huifeng; Wen, Xin; Su, Mengbai; Han, Hairong; Cheng, Xiaoqin; Tang, Yuanhang (2025): Soil stoichiometric characteristics and their relationship with tree growth of Larix principis-rupprechtii in Qilaotu Mountain. (in Chinese), Chinese Journal of Applied and Environmental Biology, 31(03), 383-393, https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 (Dataset reference ID 92) Liu, Daquan; Chen, Mingwan; Liu, Hong; Qi, Jincun; Yang, Jiwei; Lv, Meng; Li, Chen; Li, Changjiang; Li, Changzhen (2025): The conversion of tropical natural forests alters soil carbon fractions in aggregates and reduces aggregates stability. Journal of Environmental Management, 376, 124455, https://doi.org/10.1016/j.jenvman.2025.124455 (Dataset reference ID 27) Liu, Jing; Tian, Yaowu; Zhang, Qiaoming (2016): Characteristics of Soil Organic Carbon Content and Mineralization in Soil Aggregates under Different Land Use Patterns in the Loess Hilly Area of Henan. (in Chinese), Journal of Soil and Water Conservation, 30(03), 255-261, https://doi.org/10.13870/j.cnki.stbcxb.2016.03.044 (Dataset reference ID 5) Liu, Linxin; Wang, Jian; Yang, Xiaojie; Liu, Chuanzhao; Wang, Xiuwen (2018): Forest plant community and soil organic carbondensity in Da Xing'an Mountains. (in Chinese), Ecology and Environmental Sciences, 27(09), 1610-1616, https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 (Dataset reference ID 124) Liu, Shuting; Lin, Zhe; Duan, Xiaoqian; Deng, Yusong (2024): Effects of soil microorganisms on aggregate stability during vegetation recovery in degraded granitic red soil areas. Applied Soil Ecology, 204, 105734, https://doi.org/10.1016/j.apsoil.2024.105734 (2024a, Dataset reference ID 55) Liu, Xiaojun; Zhang, Yi; Li, Peng (2020): Spatial Variation Characteristics of Soil Erodibility in the Yingwugou Watershed of the Middle Dan River, China. International Journal of Environmental Research and Public Health, 17(10), 3568, https://doi.org/10.3390/ijerph17103568 (Dataset reference ID 71) Liu, Xinghua (2025): Analysis of Water Conservation Effects of Planted Forests in the Arid Region of Fuxin. (in Chinese), Technical Supervision in Water Resources, 6, 151-154, https://doi.org/10.3969/j.issn.1008-1305.2025.06.041 (Dataset reference ID 78) Liu, Yanan; Sui, Xin; Hua, Henian; Liu, Xu; Chang, Qiuyang; Xu, Ruiting; Li, Mengsha; Mu, Liqiang (2024): Soil Aggregate Stability and Organic Carbon Content among Different Forest Types in Temperate Ecosystems in Northeastern China. Forests, 15(2), 279, https://doi.org/10.3390/f15020279 (2024b, Dataset reference ID 36) Liu, Yingying; Luo, Wenmin; Wen, Ximei; Mu, Guiting; Wu, Xianliang; Zhang, Zhenming (2022): Eco-Stoichiometric Characteristics of Rhizosphere and Bulk Soils of Smilax china L. along Vertical Zone Spectrum of Fanjing Mountain. International Journal of Environmental Research and Public Health, 19(14), 8693, https://doi.org/10.3390/ijerph19148693 (Dataset reference ID 82) Liu, Yun; Wu, Tong; Luo, Hualong; Mei, Yang (2023): Characteristies and Changes of Soil Carbon, Nitrogen and Phosphorus Nutrientsin Pure and Mixed Pinus massoniana Plantations. (in Chinese), Green Science and Technology, 25(18), 20-24, https://doi.org/10.16663/j.cnki.lskj.2023.18.005 (Dataset reference ID 107) Liu, Ziqiang; Wang, Xiaodi; Jia, Guodong; Jiang, Jiang; Liao, Bin (2024): Introduction of broadleaf tree species can promote the resource use efficiency and gross primary productivity of pure forests. Plant Cell and Environment, 47(12), 5252-5264, https://doi.org/10.1111/pce.15096 (2024c, Dataset reference ID 45) Liying, Sun; Fengting, Yang; Jingyuan, Wang; Haiyan, Fang; Junyu, Qi (2015): Impacts of forest types on soil C, N and DOC loss in runoff in the laterite hilly region of southern China. Environmental Earth Sciences, 74(2), 1391-1402, https://doi.org/10.1007/s12665-015-4129-9 (Dataset reference ID 47) Lu, Weiyong; Ye, Jiayi; Fu, Jun; Chen, Zhenhua; Guo, Fei; Xiang, Zaifang; Li, Yuan; Zhou, Yanling; Chen, Hu; Li, Peng; Li, Xuetuan (2023): Study on Soil Physical and Chemical Properties of Pure and Mixed Forest of Pinus massoniana and Castanopsis hystrix. (in Chinese), Green Science and Technology, 25(13), 119-124, https://doi.org/10.16663/j.cnki.lskj.2023.13.014 (2023a, Dataset reference ID 109) Lu, Weiyong; Ye, Jiayi; Li, Xuetuan; Fu, Jun; Guo, Fei; He, Bin (2023): Water conservation capacity of litter and soil of pure and mixed-forest of Pinus massoniana and Castanopsis hystrix. Subtropical Agriculture Research, 19(02), 83-90, https://doi.org/10.13321/j.cnki.subtrop.agric.res.2023.02.002 (2023b, Dataset reference ID 111) Luo, Yi; Deng, Houyin; WANG, Runhui; Huang, Rong; Yan, Shu; Wei, Rupin; Zheng, Huiquan (2024): Diversity analysis of understory plants in different mixed forests of Cunninghamia lanceolata and broad-leaved trees in Northern Guangdong Province, China. (in Chinese), South China Forestry Science, 52(05), 45-51, https://doi.org/10.16259/j.cnki.36-1342/s.2024.05.008 (Dataset reference ID 93) Lv, Jiao; Wang, Wei (2010): Study on Function of Soil and Water Conservation of Six Vegetation Arrangement Patterns in Middle Taihang Mt. (in Chinese), Chinese Journal of Soil Science, 41(05), 1146-1152, https://doi.org/10.19336/j.cnki.trtb.2010.05.026 (Dataset reference ID 29) Ma, Xi-jun; Cheng, Jin-hua; Zhang, Hong-jiang; Lu, Xiao-yu; Zhang, Jun-su; Sun, Long; Wang, Bin-yan (2012): Analysis of soil anti-erodibility of five different plantation lands in Zhongyang,Shanxi. (in Chinese), Journal of Northwest A & F University (Natural Science Edition), 40(07), https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 (Dataset reference ID 1) Ma, Ying; Wu, Huifeng; Hu, Baoan; Cheng, Xiaoqin; Kang, Fengfeng; Han, Hairong (2023): Effects of Betula platyphylla invasion in North China on soil aggregate stability, soil organic carbon and active carbon composition of larch plantation. Plant and Soil, 486(1-2), 337-359, https://doi.org/10.1007/s11104-023-05873-3 (Dataset reference ID 9) Mo, X J; Ye, Y L; Mo, B P (2023): Study on the Growth Amount and Soil Fertilityof the Same Age Mixed Forest of Castanopsis hystrix and Acacia crassicarpa. (in Chinese), Agricultural Technology & Equipment, 5, 122-124 (Dataset reference ID 112) Niu, Yajie; Li, Xin; Han, Youzhi; Liang, Wenjun; Wang, Chuanxu; Wang, Zhuo (2025): Soil bacterial beta diversity and its environmental interpretation inpure and mixed stands of Larix principis-rupprechtii. (in Chinese), Journal of Forest and Environment, 45(03), 235-245, https://doi.org/10.13324/j.cnki.jfcf.202411001 (Dataset reference ID 83) Peng, X; Zhang, B; Zhao, Q; Horn, R; Hallett, P D (2003): Influence of types of restorative vegetation on the wetting properties of aggregates in a severely degraded clayey Ultisol in subtropical China. Geoderma, 115(3-4), 313-324, https://doi.org/10.1016/S0016-7061(03)00085-5 (Dataset reference ID 75) Peng, Xiaoyu; Liu, Jiaxin; Duan, Xingwu; Yang, Hua; Huang, Yong (2023): Key Soil Physicochemical Properties Regulating Microbial Community Structure under Vegetation Restoration in a Karst Region of China. Ecosystem Health and Sustainability, 9, 0031, https://doi.org/10.34133/ehs.0031 (Dataset reference ID 44) Qiao, Leilei; Chen, Wenjing; Wu, Yang; Liu, Hongfei; Zhang, Jiaoyang; Liu, Guobin; Xue, Sha (2019): Rehabilitation time has greater influences on soil mechanical composition and erodibility than does rehabilitation land type in the hilly-gully region of the Loess Plateau, China. PeerJ, 7, e8090, https://doi.org/10.7717/peerj.8090 (Dataset reference ID 72) Shen, H; Jiang, F Q; Du, X J; Lu, T G (2000): Evaluation on soil anti-erodibility of soil and water conservation forest. (in Chinese), Chinese Journal of Applied Ecology, 3, 345-348, https://doi.org/10.13287/j.1001-9332.2000.0088 (Dataset reference ID 13) Shen, Yafei; Cheng, Ruimei; Xiao, Wenfa; Yang, Shao (2021): Effects of understory removal and thinning on soil aggregation, and organic carbon distribution in Pinus massoniana plantations in the three Gorges Reservoir area. Ecological Indicators, 123, 107323, https://doi.org/10.1016/j.ecolind.2020.107323 (Dataset reference ID 51) Shi, J L; Wang, C; Sa, R L; Hai, L; Liu, L; Li, F Z; Liu, Q Y (2025): Evaluation on the Stability of Different Afforestation Models in the Southern Margin of Horqin Sandy Land. (in Chinese), Journal of Temperate Forestry Research, 8(02), 17-23, https://doi.org/10.3969/j.issn.2096-4900.2025.02.003 (Dataset reference ID 116) Shi, Qin; Lu, Zhiguo; Xu, Ming; Zhang, Rui; Hua, Jianfeng; Chen, Changren (2022): Soil Anti erosion Effects Under Different Vegetation Types for Hongze Lake Embankment. (in Chinese), Bulletin of Soil and Water Conservation, 42(01), 42-48, https://doi.org/10.13961/j.cnki.stbctb.20211126.002 (Dataset reference ID 34) Song, Q L; Dong, X B (2023): Comprehensive Evaluation of Forest Community Stability of Different Types of Low-Quality Forest Stands in the Greater Higgnan Mountains. (in Chinese), Scientia Silvae Sinicae, 50(06), 10-17 (Dataset reference ID 127) Sun, Chenchen; Wang, Ziqiang; Pan, Chang; Song, Yaqi; Yu, Yuanchun (2023): Effects of Cunninghamia lanceolata and Schima superba Mixed Forest on Soil Nutrients and Enzyme Activities. (in Chinese), Acta Agriculturae Universitatis Jiangxiensis, 45(03), 517-525, https://doi.org/10.13836/j.jjau.2023049 (Dataset reference ID 114) Sun, Wanyi; Yu, Xinxiao; Ju, Guodong; Wang, Xu; Meng, Jun; Niu, Yunming (2024): Correlation Between Soil Factors and Understory Plant Diversity in Different Plantations in Semi-Arid Regions of Inner Mongolia. (in Chinese), Journal of Northeast Forestry University, 52(07, 51-57, https://doi.org/10.13759/j.cnki.dlxb.2024.07.011 (Dataset reference ID 98) Wan, Pan; He, Ruirui (2020): Soil microbial community characteristics under different vegetation types at the national nature reserve of Xiaolongshan Mountains, Northwest China. Ecological Informatics, 55, 101020, https://doi.org/10.1016/j.ecoinf.2019.101020 (Dataset reference ID 105) Wang, Bing; Xue, Sha; Liu, Guo Bin; Zhang, Guang Hui; Li, Gary; Ren, Zong Ping (2012): Changes in soil nutrient and enzyme activities under different vegetations in the Loess Plateau area, Northwest China. CATENA, 92, 186-195, https://doi.org/10.1016/j.catena.2011.12.004 (Dataset reference ID 3) Wang, Hao; Zhang, Guang-hui; Li, Ning-ning; Zhang, Bao-jun; Yang, Han-yue (2019): Variation in soil erodibility under five typical land uses in a small watershed on the Loess Plateau, China. CATENA, 174, 24-35, https://doi.org/10.1016/j.catena.2018.11.003 (Dataset reference ID 69) Wang, Haodong; Cheng, Meng; Yuan, Congjun; He, Shuang; Ding, Fangjun; Yang, Rui (2024): The short-term effects of converting pure Pinus massoniana forests into mixed broadleaved forests on soil carbon and nitrogen sequestration [webpage]. (in Chinese), Journal of Central South University of Forestry & Technology, 44(10), 126-137, https://doi.org/10.14067/j.cnki.1673-923x.2024.10.013 (2024a, Dataset reference ID 97) Wang, Hui; Mu, Chunheng; Li, Jiaqi; Sun, Lin; Wang, Gailing (2025): Impacts of the Ecosystem Transformation in Red Jujube Commercial Forests on the Soil Organic Carbon Sources and Stability in the Lvliang Mountains. Land Degradation & Development, 36(7), 2234-2246, https://doi.org/10.1002/ldr.5492 (2025a, Dataset reference ID 21) Wang, J Y; Gong, W; Hu, T X; Gong, Y B; Ran, H (2007): Water conservation in a natural evergreen broadleaf forest and three plantations in southern Sichuan Province. (in Chinese), Journal of Zhejiang A&F University, 5, 569-574 (Dataset reference ID 25) Wang, Man; Jiang, Yongmeng; Zhang, Shiliang; Zhang, Jinxiu; Zheng, Linmin; Zeng, Zhiwei; Lyu, Maokui; Xie, Jinsheng (2024): Effects of Mixing Tree Species on Soil Enzyme Activity and Carbon-Use Efficiency in Eroded Masson Pine Forest. (in Chinese), Journal of Soil and Water Conservation, 38(06), 264-272, https://doi.org/10.13870/j.cnki.stbcxb.2024.06.030 (2024b, Dataset reference ID 91) Wang, Miaoqian; Xu, Xiaoming; Wang, Haojia; Xue, Fan; Zou, Yadong; Lü, Du; He, Jie; Tian, Qilong; Yi, Haijie; He, Liang; Zhang, Xiaoping (2023): Dynamic characterization of soil aggregates during secondary forest vegetation succession in the Loess Plateau. (in Chinese), Journal of Northwest A & F University (Natural Science Edition), 51(10), 107-117, https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 (2023a, Dataset reference ID 6) Wang, Ningjie; Lv, Ting; Wang, Lu; Chen, Shuifei; Xie, Lei; Fang, Yanming; Ding, Hui (2024): Leaf functional traits and ecological strategies of common plant species in evergreen broad-leaved forests on Huangshan Mountain. Journal of Forestry Research, 35(1), 130, https://doi.org/10.1007/s11676-024-01780-0 (2024c, Dataset reference ID 85) Wang, Run; Xu, Ming; Yang, Zue; Tian, Yue; Zhang, Jian (2025): Community Structure Diversity and Spatial Distribution Characteristics of Different Pinus massoniana Conifer-broadleaf Mixed Forests in Central Guizhou. (in Chinese), Journal of Mountain Agriculture and Biology, 44(02), 87-92, https://doi.org/10.15958/j.cnki.sdnyswxb.2025.02.013 (2025b, Dataset reference ID 81) Wang, S S; Bi, H X; Cui, Y H; Yun, H Y; Ma, X Z; Zhao, D Y; Hou, G R (2022): Key indexes and characteristics of soil anti-erodibility of Robinia pseudoacacia with different densities in loess region of western Shanxi Province, northern China. (in Chinese), Journal of Beijing Forestry University, 44(05), 94-104 (Dataset reference ID 74) Wang, Y; Qi, L; Zhou, L; Zhou, W M; Mao, R C; Zhu, Q; Zhao, F Q (2021): A study on the influencing factors of Larix gmelinii post-fire seed germination. (in Chinese), Acta Ecologica Sinica, 41(07), 2835-2844 (Dataset reference ID 119) Wang, Yafei; Chen, Lixin; Qu, Meixue; Duan, Wenbiao; Wang, Zhizhen; Tian, Zhen; Yang, Wen (2023): Response of Soil Aggregate Composition and Stability to Secondary Succession and Plantation of a Broad-Leaved Korean Pine Forest after Clear-Cutting and Its Causes. Forests, 14(10), 2010, https://doi.org/10.3390/f14102010 (2023b, Dataset reference ID 39) Wen, Li-li; Wang, Jin-yue; Deng, Yu-song; Duan, Xiao-qian (2023): Fragmentation process of soil aggregates under concentrated water flow in red soil hilly region with different land use patterns. Journal of Mountain Science, 20(11), 3233-3249, https://doi.org/10.1007/s11629-023-8154-y (Dataset reference ID 49) Wu, Jin-xia; Chen, Qi-bo; Wang, Ke-qin; Zhao, Yang-yi; Tong, Zhi-long (2015): Soil and water conservation benefits and their impacts on soil organiccarbon of different vegetation. (in Chinese), Journal of Northwest A & F University (Natural Science Edition), 43(04), 141-148, https://doi.org/10.13207/j.cnki.jnwafu.2015.04.010 (Dataset reference ID 35) Wu, Wenxiang; Zhou, Xiaoguo; Wen, Yuanguang; Zhu, Hongguang; You, Yeming; Qin, Zhiwei; Li, Yunchou; Huang, Xueman; Yan, Li; Li, Haiyan; Li, Xiaoqiong (2019): Coniferous-Broadleaf Mixture Increases Soil Microbial Biomass and Functions Accompanied by Improved Stand Biomass and Litter Production in Subtropical China. Forests, 10(10), 879, https://doi.org/10.3390/f10100879 (Dataset reference ID 84) Xiao, R H; Man, X L; Ding, L Z (2019): Soil nitrogen mineralization characteristics of the natural coniferous forest in Northern Daxing'an Mountains,Northeast China. (in Chinese), Acta Ecologica Sinica, 39(08), 2762-2771 (Dataset reference ID 122) Xiao, Zhirou; Teng, Jinqian; Qin, Jiaqi; Liang, Zeli; He, Jiang; Qin, Lin (2024): Differential Responses of Soil Carbon, Nitrogen and PhosphorusEco-stoichiometric Ratio to Monoculture and Mixed Coniferous-Broadleaved Plantations. (in Chinese), Journal of West China Forestry Science, 53(02), 56-63, https://doi.org/10.16473/j.cnki.xblykx1972.2024.02.008 (Dataset reference ID 99) Yan, S Y; Wang, J Y; Gong, W; Luo, J Y; Su, L M; Shu, L M; Zhao, C P; Cai, Y (2016): Effects of forest change on soil physical properties and anti-erodibility in southern Sichuan mountains. (in Chinese), Resources and Environment in the Yangtze Basin, 25(07), 1112-1120 (Dataset reference ID 57) Yan, Yu; Cui, Yuhong; Fan, Rongyuan; Pan, Cailing; Jiang, Chenyang; Hao, Jingwei; Ye, Shaoming (2023): Soil aggregate stability and distribution characteristics of organic nitrogen components in Eucalyptus pure and mixed forests. (in Chinese), Forest Research, 43(07), 149-158, https://doi.org/10.14067/j.cnki.1673-923x.2023.07.015 (Dataset reference ID 110) Yang, Hong-bin; Xiao, Yi-hua; Xu, Han; Huang, Zi-jun; Guo, Xiao-min; You, Hui-min (2022): Distribution and Stability of Soil Aggregates in Different Forest Types Under an Urban-rural Gradient. (in Chinese), Forest Research, 35(03), 82-92, https://doi.org/10.13275/j.cnki.lykxyj.2022.03.010 (Dataset reference ID 59) Yang, S Y; Wang, J R; Zhu, Y Y; Yi, L T; Liu, M H (2024): Effects of Mixed Plantation of Cunninghamia lanceolata and Phoebe chekiangensis on Root Exudates and Community Structure of Arbuscular Mycorrhizal Fungi. (in Chinese), Scientia Silvae Sinicae, 60(09), 59-68 (Dataset reference ID 94) Yang, Senlin; Mao, Kangshan; Yang, Hao; Wang, Yujie; Feng, Qiuhong; Wang, Shiyang; Miao, Ning (2023): Stand characteristics and ecological benefits of Chinese Fir, Chinese Cedar, and mixed plantations in the mountainous areas of the Sichuan Basin. Forest Ecology and Management, 544, 121168, https://doi.org/10.1016/j.foreco.2023.121168 (Dataset reference ID 31) Yang, Yahui; Zhao, Wenhui; Abla, Murat; Lin, Pengfei; Yu, Yipeng; Chen, Lili; Zhang, Xiaoping (2016): Impacts of Vegetation Cover on Soil Physic-chemical Properties -A Case Study in Wangdonggou Watershed. (in Chinese), Bulletin of Soil and Water Conservation, 36(01), 249-252, https://doi.org/10.13961/j.cnki.stbctb.2016.01.044 (Dataset reference ID 15) Yi, Caili; Zhao, Xinyu; Feng, Yingjie; Zhang, Qianmei; Zhang, Weiqiang; Gan, Xianhua; Njoroge, Brian; Liu, Xiaodong (2024): Regional climax forest has a better water conservation function than pine plantation: A comparative study in humid subtropical China. CATENA, 239, 107935, https://doi.org/10.1016/j.catena.2024.107935 (Dataset reference ID 40) You, Yuyu; Xiang, Wenhua; Ouyang, Shuai; Zhao, Zhonghui; Chen, Liang; Zeng, Yelin; Lei, Pifeng; Deng, Xiangwen; Wang, Jiurong; Wang, Keling (2020): Hydrological fluxes of dissolved organic carbon and total dissolved nitrogen in subtropical forests at three restoration stages in southern China. Journal of Hydrology, 583, 124656, https://doi.org/10.1016/j.jhydrol.2020.124656 (Dataset reference ID 48) Yu, Zhen; Zhou, Guoyi; Liu, Shirong; Sun, Pengsen; Agathokleous, Evgenios (2020): Impacts of forest management intensity on carbon accumulation of China's forest plantations. Forest Ecology and Management, 472, 118252, https://doi.org/10.1016/j.foreco.2020.118252 (Dataset reference ID 86) Zhang, Bao-jun; Xiong, Dong-hong; Liu, Lin; Tang, Yong-fa (2022): Wind erodibility indices of aeolian sandy soils impacted by different vegetation restoration: a case study from the Shannan valley of the Yarlung Zangbo River. Journal of Mountain Science, 19(10), 2830-2845, https://doi.org/10.1007/s11629-022-7305-x (2022a, Dataset reference ID 68) Zhang, Bin; Deng, Huan; Wang, Hui-li; Yin, Rui; Hallett, P D; Griffiths, Bryan S; Daniell, Tim J (2010): Does microbial habitat or community structure drive the functional stability of microbes to stresses following re-vegetation of a severely degraded soil? Soil Biology and Biochemistry, 42(5), 850-859, https://doi.org/10.1016/j.soilbio.2010.02.004 (Dataset reference ID 76) Zhang, G L; Sheng, H; Zhou, Q; Duan, L X; Wu, Y Y (2022): Erodibility of Red Soil in Subtropical Hilly Region in Response to Land Use Change. (in Chinese), Journal of Changjiang River Scientific Research Institute, 39(02), 63-69 (2022b, Dataset reference ID 50) Zhang, Guowei; Xue, Jianhui; Ma, Jie; Wang, Hankun (2024): Soil nutrients and enzyme activities in different types of forest plantations in karst degraded mountainous sites [webpage]. (in Chinese), Chinese Journal of Ecology, 43(03), 616-622, https://doi.org/10.13292/j.1000-4890.202403.035 (2024a, Dataset reference ID 113) Zhang, Luan; Zhao, Lihua (2018): Effects of Different Revegetation Patterns on Soil and Water Conservation in Sandy-hilly Region of Northern Shanxi Province. (in Chinese), Journal of Soil and Water Conservation, 32(06), 107-111, https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 (Dataset reference ID 12) Zhang, Min; Dong, Liguo; Wang, Ying; Bai, Xiaoxiong; Ma, Zitong; Yu, Xuan; Zhao, Zhong (2021): The response of soil microbial communities to soil erodibility depends on the plant and soil properties in semiarid regions. Land Degradation & Development, 32(11), 3180-3193, https://doi.org/10.1002/ldr.3887 (Dataset reference ID 26) Zhang, Shuyu; Zhao, Guangju; Fan, Junjian; Yang, Mingyue; Tian, Peng; Mu, Xingmin; Geng, Ren (2024): Variations of soil infiltration in response to vegetation restoration and its influencing factors on the Loess Plateau. Journal of Environmental Management, 372, 123356, https://doi.org/10.1016/j.jenvman.2024.123356 (2024b, Dataset reference ID 24) Zhang, T; Yang, D R; Mao, C; Zhu, Y L; Pang, W C; Yang, M (2025): Impact of Pinus caribaea Coniferous and Broad-leaved Mixed Forest Early Transformation on Understory Vegetation Diversity and Soil Physicochemical Property. (in Chinese), Journal of Beihua University (Natural Science), 26(01), 84-92 (2025a, Dataset reference ID 87) Zhang, Tingting; Zhou, Weichaoqi; Tang, Lianbo; Gao, Chengjie (2024): Characteristies of Nutrient Transfer in Leaves of Azadirachta Indica Under Different Restoration Patterns in Dry-Hot Valley. (in Chinese), Green Science and Technology, 26(23), 104-109+115, https://doi.org/10.16663/j.cnki.lskj.2024.23.038 (2024c, Dataset reference ID 89) Zhang, Wen; Li, Jiajun; Xiang, Mingzhu; Huang, Haimei; Li, Changhang; Yan, Jinliu; Gao, Guannu; Su, Xiaoyan; You, Yeming; Huang, Xueman (2024): Effects of nitrogen-Fixing tree species Acacia mangium on particle size and stability of soil aggregates in Eucalyptus grandis X urphylla plantations. (in Chinese with English abstract), Guihaia, 44(07), 1245-1256, https://doi.org/10.11931/guihaia.gxzw202210071 (2024d, Dataset reference ID 54) Zhang, Xiaoping; Li, Mingchao; Bi, Yinli; Li, Xin (2024): Accumulation effect of soil aggregate organic carbon in mixed forest in open-pit coal mine. (in Chinese with English abstract), Coal Science and Technology, 52(12), 324-338, https://doi.org/10.12438/cst.2023-1532 (2024e, Dataset reference ID 101) Zhang, Xue; Tian, Lihui; Yang, Zongyu; Li, Shikai; Fan, Mingyan; Yang, Shuai (2025): Characteristics of water uses of trees in plantations with different configuration patterns in Xining City. (in Chinese), Acta Ecologica Sinica, 45(13), 6390-6405, https://doi.org/10.20103/j.stxb.202407111626 (2025b, Dataset reference ID 117) Zhang, Yi; Lin, Yiyan; Jia, Guodong; Yu, Xianxiao; Wang, Yusong; Lei, Ziran (2022): Soil Saturated Hydraulic Conductivity and Its Influencing Factors of Typical Vegetation Types in Beiiing Mountainous Area. (in Chinese), Journal of Soil and Water Conservation, 36(06), 171-178, https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 (2022c, Dataset reference ID 32) Zhang, Yuncheng (2024): Analysis of soil physical characteristics of different forest types at Longfeng Mountain Scenic Area of Kazuo County in the west of Liaoning Province. (in Chinese), Inner Mongolia Forestry Science and Technology, 50(04), 12-18 (Dataset reference ID 90) Zhang, Zeyu; Zha, Tonggang; Yu, Yang; Zhang, Xiaoxia; Smith, Pete; Rodrigo-Comino, Jesús (2022): Evaluating indices of soil organic carbon stability. A case study for forest restoration projects near Beijing, China. Ecological Indicators, 142, 109222, https://doi.org/10.1016/j.ecolind.2022.109222 (2022d, Dataset reference ID 8) Zhang, Zhen-guo; Huang, Jian-cheng; Jiao, Ju-ying; Bai, Wen-juan (2008): Analysis on Erosion Resistance of Different Vegetation Communities in Abandoned Lands in Anʾsai Hilly-gully Loess Region. (in Chinese with English abstract), Research of Soil and Water Conservation, 15(01), 28-31 (Dataset reference ID 2) Zhang, Ziji; Wang, Qixin; Zhao, Zhenyu; Lu, Yue; Liu, Wenjing; Gao, Fanglei; Xia, Jiangbao (2024): Soil Improvement Effect of Different Economic Forest Planting Modes in South-central Shandong Province. (in Chinese), Research of Soil and Water Conservation, 31(05), 102-111, https://doi.org/10.13869/j.cnki.rswc.2024.05.021 (2024f, Dataset reference ID 95) Zhao, Yan; Zhao, Huixue; Kang, Long; Li, Ming; Zhang, Guangqi; Cao, Yang (2024): Beyond monocultures: Optimizing soil carbon sequestration with diverse planting strategies on the Loess Plateau. CATENA, 246, 108447, https://doi.org/10.1016/j.catena.2024.108447 (Dataset reference ID 22) Zheng, Xin; Cong, Ri-zheng; Wang, Jian-nan; Zhang, Ji-li (2023): Effects of Forest Fire Disturbance on Soil Nutrients and Soil Enzyme Activities of Different Forests in Cold Temperate Zone. (in Chinese with English abstract), Forest Engineering, 39(05), 74-84 (2023a, Dataset reference ID 120) Zheng, Yonglin; Wang, Yunqi; Zhang, Yuxuan; Zhang, Jialiang; Wang, Yujie; Zhu, Junlin (2023): Broadleaf Trees Increase Soil Aggregate Stability in Mixed Forest Stands of Southwest China. Forests, 14(12), 2402, https://doi.org/10.3390/f14122402 (2023b, Dataset reference ID 64) Zhu, Dayun; Yang, Qian; Zhao, Yingshan; Cao, Zhen; Han, Yurong; Li, Ronghan; Ni, Ju; Wu, Zhigao (2023): Afforestation Influences Soil Aggregate Stability by Regulating Aggregate Transformation in Karst Rocky Desertification Areas. Forests, 14(7), 1356, https://doi.org/10.3390/f14071356 (2023a, Dataset reference ID 67) Zhu, Guangyu; Shangguan, Zhouping; Deng, Lei (2021): Dynamics of water-stable aggregates associated organic carbon assessed from delta C-13 changes following temperate natural forest development in China. Soil & Tillage Research, 205, 104782, https://doi.org/10.1016/j.still.2020.104782 (Dataset reference ID 61) Zhu, Meifei; Cheng, Jinhua; Shi, Xueqi; Shi, Dewei; Ma, Siwen (2023): Characteristics of forest structure and carbon sequestration of typical artificial shelterbelts in Three Gorges Reservoir Area. (in Chinese), Science of Soil and Water Conservation, 21(03), 119-127, https://doi.org/10.16843/j.sswc.2023.03.015 (2023b, Dataset reference ID 118) Zhu, Pingzong; Zhang, Guanghui; Wang, Hongxiao; Zhang, Baojun; Wang, Xue (2020): Land surface roughness affected by vegetation restoration age and types on the Loess Plateau of China. Geoderma, 366, 114240, https://doi.org/10.1016/j.geoderma.2020.114240 (2020b, Dataset reference ID 16) Zhu, Yuanhao; Huang, Yun; Sheng, Chuwang; Ai, Biao; Xie, Zeyang; Huang, Qiongyao; Zheng, Bofu; Zhu, Jinqi (2020): Effects of Planting Economic Forest on Soil Aggregates and Organic Carbon in Southern Jiangxi Province. (in Chinese), Environmental Science & Technology, 43(05), 213-220, https://doi.org/10.19672/j.cnki.1003-6504.2020.05.029 (2020a, Dataset reference ID 53) Zou, Li; Tang, Qingming; Wang, Yi (2010): Ecological Distribution of Soil Microorganism in Pure and Mixed Forests of Pinus sylvestris var. mongolica and Larix gmelini. (in Chinese), Journal of Northeast Forestry University, 38(11), 63-64+79, https://doi.org/10.13759/j.cnki.dlxb.2010.11.029 (Dataset reference ID 125) Zou, Li-Qun; Chen, Fu-Sheng; Duncan, David S; Fang, Xiang-Min; Wang, Huimin (2015): Reforestation and slope-position effects on nitrogen, phosphorus pools, and carbon stability of various soil aggregates in a red soil hilly land of subtropical China. Canadian Journal of Forest Research, 45(1), 26-35, https://doi.org/10.1139/cjfr-2014-0275 (Dataset reference ID 73) Funding: National Natural Science Foundation of China (NSFC) (URI: https://www.nsfc.gov.cn/english/site_1/index.html), grant/award no. 42130717 National Natural Science Foundation of China (NSFC) (URI: https://www.nsfc.gov.cn/english/site_1/index.html), grant/award no. 42577397 Coverage: MEDIAN LATITUDE: 33.900655 * MEDIAN LONGITUDE: 112.701052 * SOUTH-BOUND LATITUDE: 18.625000 * WEST-BOUND LONGITUDE: 93.083000 * NORTH-BOUND LATITUDE: 53.433000 * EAST-BOUND LONGITUDE: 129.030000 MINIMUM ELEVATION: 12.00 m a.s.l. * MAXIMUM ELEVATION: 2553.00 m a.s.l. Event(s): 1_Forest_function_China * LATITUDE: 37.182000 * LONGITUDE: 111.005000 * ELEVATION START: 1424.0 m * ELEVATION END: 1446.0 m 2_Forest_function_China * LATITUDE: 36.458000 * LONGITUDE: 107.650000 * ELEVATION: 1364.0 m 3_Forest_function_China * LATITUDE: 36.776000 * LONGITUDE: 109.248000 * ELEVATION START: 1129.0 m * ELEVATION END: 1185.0 m 4_Forest_function_China * LATITUDE: 35.725000 * LONGITUDE: 107.558000 * ELEVATION START: 1260.0 m * ELEVATION END: 1278.0 m 5_Forest_function_China * LATITUDE: 34.358000 * LONGITUDE: 111.475000 * ELEVATION START: 365.0 m * ELEVATION END: 410.0 m 6_Forest_function_China * LATITUDE: 35.841000 * LONGITUDE: 109.039000 * ELEVATION START: 1081.0 m * ELEVATION END: 1203.0 m 7_Forest_function_China * LATITUDE: 35.011000 * LONGITUDE: 118.965000 * ELEVATION: 277.2 m 8_Forest_function_China * LATITUDE: 39.530000 * LONGITUDE: 116.250000 * ELEVATION: 30.0 m 9_Forest_function_China * LATITUDE: 37.300000 * LONGITUDE: 112.070000 * ELEVATION START: 2122.0 m * ELEVATION END: 2258.0 m 10_Forest_function_China * LATITUDE: 48.220000 * LONGITUDE: 123.700000 * ELEVATION: 175.0 m 11_Forest_function_China * LATITUDE START: 36.750000 * LONGITUDE START: 109.250000 * LATITUDE END: 36.750000 * LONGITUDE END: 109.260000 * ELEVATION START: 1318.0 m * ELEVATION END: 1325.0 m 12_Forest_function_China * LATITUDE: 40.020000 * LONGITUDE: 112.450000 * ELEVATION: 1439.0 m 13_Forest_function_China * LATITUDE: 41.580000 * LONGITUDE: 120.440000 * ELEVATION: 360.0 m 14_Forest_function_China * LATITUDE: 49.000000 * LONGITUDE: 126.560000 * ELEVATION: 445.0 m 15_Forest_function_China * LATITUDE: 35.230000 * LONGITUDE: 107.680000 * ELEVATION: 1150.0 m 16_Forest_function_China * LATITUDE START: 36.760000 * LONGITUDE START: 109.270000 * LATITUDE END: 36.770000 * LONGITUDE END: 109.270000 * ELEVATION START: 1140.0 m * ELEVATION END: 1207.0 m 17_Forest_function_China * LATITUDE: 40.180000 * LONGITUDE: 117.560000 * ELEVATION START: 400.0 m * ELEVATION END: 410.0 m 18_Forest_function_China * LATITUDE START: 36.050000 * LONGITUDE START: 109.140000 * LATITUDE END: 36.090000 * LONGITUDE END: 109.190000 * ELEVATION START: 1110.0 m * ELEVATION END: 1298.0 m 19_Forest_function_China * LATITUDE START: 36.080000 * LONGITUDE START: 109.150000 * LATITUDE END: 36.760000 * LONGITUDE END: 109.170000 * ELEVATION START: 1174.6 m * ELEVATION END: 1273.3 m 20_Forest_function_China * LATITUDE: 36.270000 * LONGITUDE: 110.730000 * ELEVATION START: 1059.0 m * ELEVATION END: 1166.0 m 21_Forest_function_China * LATITUDE START: 37.540000 * LONGITUDE START: 110.540000 * LATITUDE END: 38.100000 * LONGITUDE END: 110.910000 * ELEVATION START: 843.4 m * ELEVATION END: 937.4 m 22_Forest_function_China * LATITUDE: 36.776000 * LONGITUDE: 109.248472 * ELEVATION START: 1090.0 m * ELEVATION END: 1202.0 m 23_Forest_function_China * LATITUDE START: 36.890000 * LONGITUDE START: 108.160000 * LATITUDE END: 36.930000 * LONGITUDE END: 108.230000 * ELEVATION START: 1345.0 m * ELEVATION END: 1528.0 m 24_Forest_function_China * LATITUDE START: 35.700000 * LONGITUDE START: 107.553000 * LATITUDE END: 35.707000 * LONGITUDE END: 107.565000 * ELEVATION START: 1203.0 m * ELEVATION END: 1278.0 m 25_Forest_function_China * LATITUDE: 28.691700 * LONGITUDE: 103.800000 * ELEVATION: 1325.0 m 26_Forest_function_China * LATITUDE: 36.215250 * LONGITUDE: 107.555000 * ELEVATION START: 1350.0 m * ELEVATION END: 1370.0 m 27_Forest_function_China * LATITUDE: 18.625000 * LONGITUDE: 108.841500 * ELEVATION: 763.0 m 28_Forest_function_China * LATITUDE: 37.867000 * LONGITUDE: 111.483300 * ELEVATION START: 1720.0 m * ELEVATION END: 1800.0 m 29_Forest_function_China * LATITUDE: 36.224800 * LONGITUDE: 113.395000 * ELEVATION: 1253.5 m 30_Forest_function_China * LATITUDE: 23.220000 * LONGITUDE: 104.680000 * ELEVATION: 1730.0 m 31_Forest_function_China * LATITUDE: 31.080000 * LONGITUDE: 103.940000 * ELEVATION START: 1153.0 m * ELEVATION END: 1215.5 m 32_Forest_function_China * LATITUDE: 39.900000 * LONGITUDE: 116.467000 * ELEVATION: 809.0 m 33_Forest_function_China * LATITUDE: 26.883000 * LONGITUDE: 118.266500 * ELEVATION: 500.0 m 34_Forest_function_China * LATITUDE: 32.130000 * LONGITUDE: 118.490000 * ELEVATION: 12.0 m 35_Forest_function_China * LATITUDE: 24.580000 * LONGITUDE: 102.828000 * ELEVATION: 1780.0 m 36_Forest_function_China * LATITUDE START: 50.701000 * LONGITUDE START: 125.930000 * LATITUDE END: 50.802000 * LONGITUDE END: 125.935000 * ELEVATION START: 508.0 m * ELEVATION END: 525.0 m 37_Forest_function_China * LATITUDE START: 30.301700 * LONGITUDE START: 106.795800 * LATITUDE END: 30.437500 * LONGITUDE END: 106.846400 * ELEVATION START: 518.0 m * ELEVATION END: 1409.0 m 38_Forest_function_China * LATITUDE: 22.567000 * LONGITUDE: 112.833000 * ELEVATION: 175.0 m 39_Forest_function_China * LATITUDE START: 47.143000 * LONGITUDE START: 113.909000 * LATITUDE END: 47.176000 * LONGITUDE END: 128.910000 * ELEVATION START: 361.0 m * ELEVATION END: 498.0 m 40_Forest_function_China * LATITUDE: 23.167000 * LONGITUDE: 121.517000 * ELEVATION: 255.0 m 41_Forest_function_China * LATITUDE: 29.433000 * LONGITUDE: 111.217000 * ELEVATION: 564.0 m 42_Forest_function_China * LATITUDE: 23.587000 * LONGITUDE: 107.506000 * ELEVATION START: 298.0 m * ELEVATION END: 374.0 m 43_Forest_function_China * LATITUDE: 29.750000 * LONGITUDE: 106.367000 * ELEVATION START: 760.0 m * ELEVATION END: 825.0 m 44_Forest_function_China * LATITUDE: 23.730000 * LONGITUDE: 103.380000 * ELEVATION: 1050.0 m 45_Forest_function_China * LATITUDE: 27.083000 * LONGITUDE: 115.608000 * ELEVATION: 43.5 m 46_Forest_function_China * LATITUDE: 28.683000 * LONGITUDE: 93.083000 * ELEVATION: 1200.0 m 47_Forest_function_China * LATITUDE: 26.733000 * LONGITUDE: 115.067000 * ELEVATION: 100.0 m 48_Forest_function_China * LATITUDE: 28.406000 * LONGITUDE: 113.300000 * ELEVATION: 136.2 m 49_Forest_function_China * LATITUDE: 24.742000 * LONGITUDE: 109.842000 * ELEVATION: 300.0 m 50_Forest_function_China * LATITUDE: 28.400000 * LONGITUDE: 114.117000 * ELEVATION: 160.0 m 51_Forest_function_China * LATITUDE: 28.792000 * LONGITUDE: 110.225000 * ELEVATION: 650.0 m 52_Forest_function_China * LATITUDE: 43.817000 * LONGITUDE: 129.030000 * ELEVATION: 900.0 m 53_Forest_function_China * LATITUDE: 25.658000 * LONGITUDE: 114.275000 * ELEVATION START: 170.0 m * ELEVATION END: 210.0 m 54_Forest_function_China * LATITUDE: 22.050000 * LONGITUDE: 106.933000 * ELEVATION: 225.5 m 55_Forest_function_China * LATITUDE: 23.800000 * LONGITUDE: 111.542000 * ELEVATION: 386.0 m 56_Forest_function_China * LATITUDE START: 27.178000 * LONGITUDE START: 105.099000 * LATITUDE END: 27.248000 * LONGITUDE END: 105.112000 * ELEVATION START: 1761.0 m * ELEVATION END: 1897.0 m 57_Forest_function_China * LATITUDE: 28.692000 * LONGITUDE: 103.800000 * ELEVATION: 1325.0 m 58_Forest_function_China * LATITUDE: 41.575000 * LONGITUDE: 124.083000 * ELEVATION: 350.0 m 59_Forest_function_China * LATITUDE START: 23.188000 * LONGITUDE START: 113.228000 * LATITUDE END: 25.303000 * LONGITUDE END: 113.840000 * ELEVATION START: 36.3 m * ELEVATION END: 627.3 m 60_Forest_function_China * LATITUDE START: 25.724000 * LONGITUDE START: 103.564000 * LATITUDE END: 25.784000 * LONGITUDE END: 103.636000 * ELEVATION START: 1990.8 m * ELEVATION END: 2087.6 m 61_Forest_function_China * LATITUDE START: 36.033000 * LONGITUDE START: 108.517000 * LATITUDE END: 36.050000 * LONGITUDE END: 108.533000 * ELEVATION START: 1437.0 m * ELEVATION END: 1450.0 m 62_Forest_function_China * LATITUDE: 31.167000 * LONGITUDE: 104.417000 * ELEVATION: 510.0 m 63_Forest_function_China * LATITUDE: 22.133000 * LONGITUDE: 106.817000 * ELEVATION: 596.0 m 64_Forest_function_China * LATITUDE: 29.783000 * LONGITUDE: 106.333000 * ELEVATION: 560.0 m 65_Forest_function_China * LATITUDE: 24.833000 * LONGITUDE: 107.917000 * ELEVATION: 596.0 m 66_Forest_function_China * LATITUDE: 29.560000 * LONGITUDE: 106.460000 * ELEVATION: 550.0 m 67_Forest_function_China * LATITUDE START: 27.229000 * LONGITUDE START: 105.104000 * LATITUDE END: 27.242000 * LONGITUDE END: 105.108000 * ELEVATION START: 1751.0 m * ELEVATION END: 1892.0 m 68_Forest_function_China * LATITUDE: 29.613000 * LONGITUDE: 94.937000 * ELEVATION: 1498.0 m 69_Forest_function_China * LATITUDE: 36.776000 * LONGITUDE: 109.248500 * ELEVATION: 1160.0 m 70_Forest_function_China * LATITUDE: 19.350000 * LONGITUDE: 109.917000 * ELEVATION: 150.0 m 71_Forest_function_China * LATITUDE: 33.531500 * LONGITUDE: 110.898000 * ELEVATION: 532.0 m 72_Forest_function_China * LATITUDE: 36.929000 * LONGITUDE: 108.862000 * ELEVATION START: 1237.0 m * ELEVATION END: 1561.0 m 73_Forest_function_China * LATITUDE: 26.730000 * LONGITUDE: 115.017000 * ELEVATION: 126.0 m 74_Forest_function_China * LATITUDE START: 36.206000 * LONGITUDE START: 110.723000 * LATITUDE END: 36.276000 * LONGITUDE END: 110.770000 * ELEVATION START: 1070.0 m * ELEVATION END: 1145.0 m 75_Forest_function_China * LATITUDE: 28.092000 * LONGITUDE: 116.092000 * ELEVATION: 34.0 m 76_Forest_function_China * LATITUDE: 28.250000 * LONGITUDE: 116.917000 * ELEVATION: 140.0 m 77_Forest_function_China * LATITUDE START: 36.891000 * LONGITUDE START: 108.131000 * LATITUDE END: 36.928000 * LONGITUDE END: 108.217000 * ELEVATION START: 1480.3 m * ELEVATION END: 1510.2 m 78_Forest_function_China * LATITUDE: 42.470000 * LONGITUDE: 121.600000 * ELEVATION: 724.5 m 79_Forest_function_China * LATITUDE: 34.492000 * LONGITUDE: 112.908000 * ELEVATION: 636.5 m 80_Forest_function_China * LATITUDE: 22.133000 * LONGITUDE: 103.817000 * ELEVATION: 22.1 m 81_Forest_function_China * LATITUDE: 27.083000 * LONGITUDE: 107.017000 * ELEVATION: 1104.0 m 82_Forest_function_China * LATITUDE: 26.200000 * LONGITUDE: 111.583000 * ELEVATION: 196.0 m 83_Forest_function_China * LATITUDE START: 37.854000 * LONGITUDE START: 111.545000 * LATITUDE END: 37.917000 * LONGITUDE END: 111.598000 * ELEVATION START: 1720.0 m * ELEVATION END: 2250.0 m 84_Forest_function_China * LATITUDE: 37.017000 * LONGITUDE: 112.017000 * ELEVATION START: 1828.0 m * ELEVATION END: 1906.0 m 85_Forest_function_China * LATITUDE START: 37.278000 * LONGITUDE START: 106.282000 * LATITUDE END: 37.353000 * LONGITUDE END: 106.399000 * ELEVATION START: 2096.0 m * ELEVATION END: 2553.0 m 86_Forest_function_China * LATITUDE: 28.017000 * LONGITUDE: 119.058000 * ELEVATION START: 1390.0 m * ELEVATION END: 1432.0 m 87_Forest_function_China * LATITUDE: 22.675000 * LONGITUDE: 108.208000 * ELEVATION START: 180.0 m * ELEVATION END: 190.0 m 88_Forest_function_China * LATITUDE: 24.108000 * LONGITUDE: 111.625000 * ELEVATION: 400.0 m 89_Forest_function_China * LATITUDE: 25.700000 * LONGITUDE: 101.850000 * ELEVATION: 1120.0 m 90_Forest_function_China * LATITUDE: 41.108000 * LONGITUDE: 119.975000 * ELEVATION: 865.0 m 91_Forest_function_China * LATITUDE: 25.667000 * LONGITUDE: 116.333000 * ELEVATION: 500.0 m 92_Forest_function_China * LATITUDE: 41.500000 * LONGITUDE: 108.400000 * ELEVATION START: 1196.0 m * ELEVATION END: 1219.0 m 93_Forest_function_China * LATITUDE: 24.790000 * LONGITUDE: 113.610000 * ELEVATION START: 160.0 m * ELEVATION END: 270.0 m 94_Forest_function_China * LATITUDE: 29.917000 * LONGITUDE: 116.867000 * ELEVATION: 122.0 m 95_Forest_function_China * LATITUDE: 35.573000 * LONGITUDE: 118.205000 * ELEVATION: 210.9 m 96_Forest_function_China * LATITUDE: 29.150000 * LONGITUDE: 118.417000 * ELEVATION START: 196.0 m * ELEVATION END: 207.0 m 97_Forest_function_China * LATITUDE: 25.440000 * LONGITUDE: 107.300000 * ELEVATION: 975.0 m 98_Forest_function_China * LATITUDE START: 41.069000 * LONGITUDE START: 116.979000 * LATITUDE END: 45.925000 * LONGITUDE END: 120.444000 * ELEVATION START: 549.0 m * ELEVATION END: 591.0 m 99_Forest_function_China * LATITUDE: 22.173000 * LONGITUDE: 106.711000 * ELEVATION START: 195.0 m * ELEVATION END: 215.0 m 100_Forest_function_China * LATITUDE: 29.433000 * LONGITUDE: 103.583000 * ELEVATION START: 425.0 m * ELEVATION END: 451.0 m 101_Forest_function_China * LATITUDE: 39.767000 * LONGITUDE: 111.267000 * ELEVATION: 1163.5 m 102_Forest_function_China * LATITUDE: 27.700000 * LONGITUDE: 112.542000 * ELEVATION: 193.0 m 103_Forest_function_China * LATITUDE: 36.667000 * LONGITUDE: 112.074000 * ELEVATION START: 1213.0 m * ELEVATION END: 1275.0 m 104_Forest_function_China * LATITUDE: 22.100000 * LONGITUDE: 106.833000 * ELEVATION START: 725.0 m * ELEVATION END: 730.0 m 105_Forest_function_China * LATITUDE START: 30.717000 * LONGITUDE START: 110.789000 * LATITUDE END: 30.898000 * LONGITUDE END: 110.829000 * ELEVATION START: 534.0 m * ELEVATION END: 921.0 m 106_Forest_function_China * LATITUDE: 25.327000 * LONGITUDE: 117.494000 * ELEVATION: 407.0 m 107_Forest_function_China * LATITUDE: 22.600000 * LONGITUDE: 108.150000 * ELEVATION: 286.0 m 108_Forest_function_China * LATITUDE: 41.013000 * LONGITUDE: 124.799000 * ELEVATION: 300.0 m 109_Forest_function_China * LATITUDE: 21.875000 * LONGITUDE: 106.875000 * ELEVATION: 210.0 m 110_Forest_function_China * LATITUDE: 22.133000 * LONGITUDE: 106.817000 * ELEVATION START: 245.0 m * ELEVATION END: 255.0 m 111_Forest_function_China * LATITUDE: 22.417000 * LONGITUDE: 107.117000 * ELEVATION: 385.0 m 112_Forest_function_China * LATITUDE: 22.900000 * LONGITUDE: 108.349000 * ELEVATION: 155.0 m 113_Forest_function_China * LATITUDE: 23.342000 * LONGITUDE: 105.708000 * ELEVATION START: 1410.0 m * ELEVATION END: 1480.0 m 114_Forest_function_China * LATITUDE: 27.029000 * LONGITUDE: 118.413000 * ELEVATION START: 209.0 m * ELEVATION END: 239.0 m 115_Forest_function_China * LATITUDE: 42.125000 * LONGITUDE: 117.383300 * ELEVATION: 1409.0 m 116_Forest_function_China * LATITUDE START: 42.589000 * LONGITUDE START: 120.400000 * LATITUDE END: 43.441000 * LONGITUDE END: 120.925000 * ELEVATION START: 285.0 m * ELEVATION END: 464.0 m 117_Forest_function_China * LATITUDE: 35.483500 * LONGITUDE: 96.325000 * ELEVATION: 2261.0 m 118_Forest_function_China * LATITUDE: 28.570000 * LONGITUDE: 106.437500 * ELEVATION: 1105.0 m 119_Forest_function_China * LATITUDE: 52.970300 * LONGITUDE: 122.454500 * ELEVATION: 521.0 m 120_Forest_function_China * LATITUDE: 51.825000 * LONGITUDE: 123.500000 * ELEVATION: 981.0 m 121_Forest_function_China * LATITUDE: 52.033000 * LONGITUDE: 124.183000 * ELEVATION: 638.0 m 122_Forest_function_China * LATITUDE: 53.433000 * LONGITUDE: 122.283000 * ELEVATION: 332.0 m 123_Forest_function_China * LATITUDE START: 50.517000 * LONGITUDE START: 119.930000 * LATITUDE END: 50.700000 * LONGITUDE END: 123.750000 * ELEVATION START: 433.0 m * ELEVATION END: 1184.0 m 124_Forest_function_China * LATITUDE: 51.830500 * LONGITUDE: 123.504000 * ELEVATION: 812.0 m 125_Forest_function_China * LATITUDE: 50.641500 * LONGITUDE: 124.908500 * ELEVATION: 800.0 m 126_Forest_function_China * LATITUDE: 50.000000 * LONGITUDE: 123.250000 * ELEVATION: 900.0 m 127_Forest_function_China * LATITUDE START: 50.460600 * LONGITUDE START: 124.252500 * LATITUDE END: 50.572400 * LONGITUDE END: 124.403350 * ELEVATION START: 475.0 m * ELEVATION END: 475.0 m Parameter(s): Event label (Event) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) Identification (ID) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) Reference/source (Reference) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) Uniform resource locator/link to reference (URL ref) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) Area/locality (Area) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) Year of observation [a AD] (Year obs) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Number of measurements [#] (n) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: measurements reported in the original studies LONGITUDE (Longitude) * GEOCODE * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based LATITUDE (Latitude) * GEOCODE * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based ELEVATION [m a.s.l.] (Elevation) * GEOCODE * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Precipitation, annual mean [mm] (MAP) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Temperature, annual mean [°C] (MAT) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Stand age [a] (Stand age) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Slope angle [deg] (Slope angle) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Trees, canopy cover [%] (Canopy cover) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Shannon Diversity Index (H') * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Shannon Diversity Index, standard deviation [±] (H' std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Clay [%] (Clay) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Clay, standard deviation [±] (Clay std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Silt [%] (Silt) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Silt, standard deviation [±] (Silt std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Sand [%] (Sand) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Sand, standard deviation [±] (Sand std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Density, dry bulk [g/cm**3] (DBD) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Soil water content [%] (SWC) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Soil water content, standard deviation [±] (SWC std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Nitrogen, total [g/kg] (TN) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Carbon, organic, soil [g/kg] (SOC) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Carbon, organic, soil, standard deviation [±] (SOC std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based pH (pH) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: soil Mean weight diameter [mm] (MWD) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based Soil erodibility [(t*ha*h)/(MJ*mm*ha)] (K factor) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based * COMMENT: mean Soil erodibility, standard deviation [±] (K factor std dev) * PI: Zhi, Shuqi (https://orcid.org/0009-0000-5785-2579, zhishuqi24@mails.ucas.ac.cn) * METHOD/DEVICE: Literature based License: Creative Commons Attribution 4.0 International (CC-BY-4.0) (URI: https://creativecommons.org/licenses/by/4.0/) (License comes into effect after moratorium ends) Status: Curation Level: Enhanced curation (URI: https://wiki.pangaea.de/wiki/Curation_levels) Size: 11909 data points */ Event ID Reference URL ref Area Year obs [a AD] n [#] Longitude Latitude Elevation [m a.s.l.] MAP [mm] MAT [°C] Stand age [a] Slope angle [deg] Canopy cover [%] H' H' std dev [±] Clay [%] Clay std dev [±] Silt [%] Silt std dev [±] Sand [%] Sand std dev [±] DBD [g/cm**3] SWC [%] SWC std dev [±] TN [g/kg] SOC [g/kg] SOC std dev [±] pH MWD [mm] K factor [(t*ha*h)/(MJ*mm*ha)] K factor std dev [±] 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1446.00 518.16 6.00 9.00 7.00 0.300 10.410 0.611 58.370 3.091 17.490 0.889 1.200 1.890 9.287 0.455 0.019 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1446.00 518.16 6.00 9.00 7.00 0.300 10.200 0.599 26.120 1.383 50.240 2.554 1.360 1.540 8.770 0.429 0.014 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1424.00 518.16 6.00 9.00 20.00 0.700 13.470 0.791 40.000 2.118 38.100 1.937 1.040 1.800 9.954 0.487 0.016 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1424.00 518.16 6.00 9.00 20.00 0.700 9.390 0.551 27.760 1.470 48.390 2.460 1.330 1.080 6.183 0.303 0.015 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1443.00 518.16 6.00 9.00 30.00 0.500 8.570 0.503 30.410 1.610 44.450 2.260 1.060 1.870 8.208 0.402 0.015 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1443.00 518.16 6.00 9.00 30.00 0.500 6.840 0.402 50.000 2.647 19.410 0.987 1.160 1.470 5.748 0.281 0.018 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1438.00 518.16 6.00 9.00 0.00 0.550 11.220 0.659 46.730 2.474 34.160 1.737 1.080 2.830 10.771 0.527 0.017 0.000 1_Forest_function_China 1 Ma et al. (2012) https://doi.org/10.13207/j.cnki.jnwafu.2012.07.015 Zhongyang,Shanxi 2010 30 111.005000 37.18200 1438.00 518.16 6.00 9.00 0.00 0.550 11.220 0.659 31.630 1.675 46.220 2.350 1.140 0.750 9.907 0.485 0.015 0.000 2_Forest_function_China 2 Zhang et al. (2008) Ansai,Shaanxi 2006 10 107.650000 36.45800 1364.00 500.00 8.90 35.00 12.300 0.602 2_Forest_function_China 2 Zhang et al. (2008) Ansai,Shaanxi 2006 10 107.650000 36.45800 1364.00 500.00 8.90 35.00 12.300 0.602 2_Forest_function_China 2 Zhang et al. (2008) Ansai,Shaanxi 2006 10 107.650000 36.45800 1364.00 500.00 8.90 25.00 17.700 0.867 2_Forest_function_China 2 Zhang et al. (2008) Ansai,Shaanxi 2006 10 107.650000 36.45800 1364.00 500.00 8.90 20.00 19.400 0.950 3_Forest_function_China 3 Wang et al. (2012) https://doi.org/10.1016/j.catena.2011.12.004 Ansai,Shaanxi 2005 3 109.248000 36.77600 1129.00 549.10 8.80 32.00 12.000 0.705 24.000 1.271 64.000 3.254 0.700 5.900 0.289 8.740 0.013 0.000 3_Forest_function_China 3 Wang et al. (2012) https://doi.org/10.1016/j.catena.2011.12.004 Ansai,Shaanxi 2005 3 109.248000 36.77600 1166.00 549.10 8.80 27.00 12.000 0.705 24.000 1.271 64.000 3.254 0.800 6.800 0.160 8.740 0.013 0.000 3_Forest_function_China 3 Wang et al. (2012) https://doi.org/10.1016/j.catena.2011.12.004 Ansai,Shaanxi 2005 3 109.248000 36.77600 1142.00 549.10 8.80 24.00 12.000 0.705 24.000 1.271 64.000 3.254 0.700 6.400 0.068 8.730 0.013 0.000 3_Forest_function_China 3 Wang et al. (2012) https://doi.org/10.1016/j.catena.2011.12.004 Ansai,Shaanxi 2005 3 109.248000 36.77600 1185.00 549.10 8.80 27.00 12.000 0.705 24.000 1.271 64.000 3.254 0.900 9.200 0.027 8.620 0.013 0.000 4_Forest_function_China 4 Guo et al. (2018) https://doi.org/10.1007/s40333-018-0121-z Xifeng Research Station of Soil and Water Conservation 2016 3 107.558000 35.72500 1278.00 523.00 10.00 0.11 14.030 0.824 72.690 3.849 13.280 0.675 1.350 1.100 0.031 0.000 4_Forest_function_China 4 Guo et al. (2018) https://doi.org/10.1007/s40333-018-0121-z Xifeng Research Station of Soil and Water Conservation 2016 3 107.558000 35.72500 1273.00 523.00 10.00 0.09 13.620 0.800 68.860 3.646 17.520 0.891 1.180 1.300 0.029 0.000 4_Forest_function_China 4 Guo et al. (2018) https://doi.org/10.1007/s40333-018-0121-z Xifeng Research Station of Soil and Water Conservation 2016 3 107.558000 35.72500 1260.00 523.00 10.00 5.93 12.340 0.725 70.140 3.714 17.520 0.891 1.210 1.300 0.029 0.000 5_Forest_function_China 5 Liu et al. (2016) https://doi.org/10.13870/j.cnki.stbcxb.2016.03.044 Luoning,Henan 2013 6 111.475000 34.35800 410.00 1150.00 13.70 30.00 34.540 2.028 51.860 2.746 15.600 0.793 1.060 1.630 32.904 2.730 7.240 5_Forest_function_China 5 Liu et al. (2016) https://doi.org/10.13870/j.cnki.stbcxb.2016.03.044 Luoning,Henan 2013 6 111.475000 34.35800 365.00 1150.00 13.70 10.00 23.00 34.230 2.010 49.620 2.627 16.150 0.821 1.120 1.370 31.033 4.150 7.270 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 6 109.039000 35.84100 1081.00 587.00 7.40 70.00 24.50 0.670 63.995 3.133 5.685 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 6 109.039000 35.84100 1081.00 587.00 7.40 70.00 24.50 0.670 13.827 0.677 2.240 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 5 109.039000 35.84100 1109.00 587.00 7.40 120.00 24.00 0.810 76.677 3.754 4.936 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 5 109.039000 35.84100 1109.00 587.00 7.40 120.00 24.00 0.810 12.052 0.590 2.085 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 3 109.039000 35.84100 1193.00 587.00 7.40 150.00 18.00 0.770 69.882 3.422 4.430 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 3 109.039000 35.84100 1193.00 587.00 7.40 150.00 18.00 0.770 11.200 0.548 1.661 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 3 109.039000 35.84100 1203.00 587.00 7.40 135.00 24.00 0.810 57.581 2.819 4.072 6_Forest_function_China 6 Wang et al. (2023a) https://doi.org/10.13207/j.cnki.jnwafu.2023.10.012 ziwuling,Shaanxi 2020 3 109.039000 35.84100 1203.00 587.00 7.40 135.00 24.00 0.810 11.401 0.558 1.892 7_Forest_function_China 7 Guo et al. (2021) https://doi.org/10.3390/f12070859 Lianyungang, Jiangsu 2016 3 118.965000 35.01100 277.20 976.60 13.90 25.00 13.00 3.200 0.710 60.210 12.055 36.590 13.042 1.440 2.570 30.860 8.435 5.670 4.100 0.060 0.001 7_Forest_function_China 7 Guo et al. (2021) https://doi.org/10.3390/f12070859 Lianyungang, Jiangsu 2016 3 118.965000 35.01100 277.20 976.60 13.90 13.00 11.00 3.770 0.312 64.660 11.535 31.570 13.562 1.430 1.350 18.870 2.598 5.950 4.000 0.070 0.001 7_Forest_function_China 7 Guo et al. (2021) https://doi.org/10.3390/f12070859 Lianyungang, Jiangsu 2016 3 118.965000 35.01100 277.20 976.60 13.90 10.00 13.00 2.290 0.398 56.630 7.552 41.070 14.982 1.470 1.210 11.550 3.776 5.480 3.300 0.080 0.001 7_Forest_function_China 7 Guo et al. (2021) https://doi.org/10.3390/f12070859 Lianyungang, Jiangsu 2016 3 118.965000 35.01100 277.20 976.60 13.90 11.00 15.00 4.160 0.624 65.000 9.751 30.840 8.747 1.420 1.520 13.830 3.083 5.670 3.350 0.080 0.001 8_Forest_function_China 8 Zhang et al. (2022d) https://doi.org/10.1016/j.ecolind.2022.109222 Ding River, Daxing District, Beijing / 3 116.250000 39.53000 30.00 600.00 9.00 13.00 3.00 0.050 0.000 / / 1.800 0.030 1.410 0.240 3.960 0.290 8.000 8_Forest_function_China 8 Zhang et al. (2022d) https://doi.org/10.1016/j.ecolind.2022.109222 Ding River, Daxing District, Beijing / 3 116.250000 39.53000 30.00 600.00 9.00 13.00 3.00 0.040 0.000 / / 1.650 0.050 1.410 0.140 1.510 0.140 8.130 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2250.00 653.00 8.60 25.00 32.00 1.600 0.060 20.730 2.962 28.580 2.650 50.690 2.546 1.380 2.250 35.814 1.395 6.580 1.731 0.015 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2250.00 653.00 8.60 25.00 32.00 1.600 0.060 21.630 1.593 30.910 2.096 47.460 4.139 1.230 1.560 29.884 2.163 6.760 1.801 0.015 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2250.00 653.00 8.60 25.00 32.00 1.600 0.060 22.160 1.230 31.890 2.459 45.950 3.741 1.170 1.380 21.488 0.484 7.090 1.854 0.015 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2258.00 653.00 8.60 26.00 28.00 1.790 0.050 18.950 1.074 27.570 3.273 53.480 4.330 1.250 2.510 45.349 1.628 6.620 1.807 0.014 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2258.00 653.00 8.60 26.00 28.00 1.790 0.050 20.070 2.304 29.270 2.286 50.660 2.685 1.160 1.690 31.698 1.605 6.900 1.851 0.015 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2258.00 653.00 8.60 26.00 28.00 1.790 0.050 21.690 1.697 29.050 2.529 49.260 3.256 1.100 1.430 22.084 0.335 7.040 1.896 0.015 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2122.00 653.00 8.60 23.00 23.00 1.880 0.230 16.580 2.130 27.990 3.758 55.420 1.663 1.240 2.610 47.209 2.209 7.150 1.893 0.014 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2122.00 653.00 8.60 23.00 23.00 1.880 0.230 17.380 1.472 29.020 1.974 53.610 1.230 1.090 1.970 36.163 1.256 7.280 1.935 0.014 0.000 9_Forest_function_China 9 Ma et al. (2023) https://doi.org/10.1007/s11104-023-05873-3 The eastern region of the middle segment of Taiyue Mountain in central Shanxi Province 2020 3 112.070000 37.30000 2122.00 653.00 8.60 23.00 23.00 1.880 0.230 21.380 2.165 27.170 2.338 51.450 1.801 1.060 1.440 24.837 1.488 7.330 2.011 0.014 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 28.00 25.837 2.493 15.656 2.310 58.590 2.700 1.413 1.670 32.789 3.851 2.979 0.012 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 28.00 25.297 2.964 17.504 4.448 57.346 6.632 1.408 1.165 20.544 3.501 2.729 0.013 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 29.00 28.061 1.942 13.786 1.123 58.173 2.535 1.507 1.996 35.085 5.395 2.486 0.012 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 29.00 27.761 1.782 17.193 1.522 54.783 2.342 1.513 1.202 20.374 4.719 1.657 0.013 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 28.00 34.661 2.235 21.372 1.189 43.810 2.257 1.323 1.612 31.412 5.012 3.143 0.014 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 28.00 27.101 2.586 27.231 3.359 45.744 2.511 1.371 0.995 18.878 3.333 2.329 0.015 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 45.00 21.823 7.883 10.569 2.042 69.177 3.352 1.472 1.618 29.269 4.876 2.521 0.010 0.000 10_Forest_function_China 10 Kong et al. (2022) https://doi.org/10.3390/agriculture12111917 Gannan County, Qiqihar City, Heilongjiang Province 2021 21 123.700000 48.22000 175.00 438.10 4.40 45.00 20.289 2.695 11.790 2.054 68.081 4.410 1.508 0.915 15.748 2.547 2.036 0.011 0.000 11_Forest_function_China 11 Dou et al. (2020) https://doi.org/10.1016/j.catena.2019.104294 The northern Shaanxi Province Zhifanggou watershed 2016 3 109.260000 36.75000 1325.00 549.10 8.80 28.80 1.040 0.270 6.090 0.540 8.240 1.079 0.024 0.002 11_Forest_function_China 11 Dou et al. (2020) https://doi.org/10.1016/j.catena.2019.104294 The northern Shaanxi Province Zhifanggou watershed 2016 3 109.260000 36.75000 1325.00 549.10 8.80 28.80 1.210 0.160 4.410 0.570 8.230 0.971 0.025 0.005 11_Forest_function_China 11 Dou et al. (2020) https://doi.org/10.1016/j.catena.2019.104294 The northern Shaanxi Province Zhifanggou watershed 2016 3 109.250000 36.75000 1318.00 549.10 8.80 20.56 1.110 0.200 5.820 0.490 8.310 1.804 0.020 0.003 11_Forest_function_China 11 Dou et al. (2020) https://doi.org/10.1016/j.catena.2019.104294 The northern Shaanxi Province Zhifanggou watershed 2016 3 109.250000 36.75000 1318.00 549.10 8.80 20.56 1.160 0.160 3.840 0.410 8.280 1.709 0.019 0.003 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 21.00 12.00 1.250 0.050 29.710 0.490 68.940 0.660 1.390 5.420 0.970 18.109 1.788 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 21.00 12.00 1.330 6.800 0.450 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 21.00 12.00 1.340 7.520 2.330 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 21.00 12.00 1.340 6.920 1.420 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 21.00 12.00 1.400 6.360 1.370 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 18.00 10.00 1.320 0.100 28.420 0.490 70.250 1.830 1.300 5.810 2.540 17.254 4.663 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 18.00 10.00 1.280 7.720 1.960 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 18.00 10.00 1.300 7.090 0.870 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 18.00 10.00 1.320 6.830 0.830 12_Forest_function_China 12 Zhang and Zhao (2018) https://doi.org/10.13870/j.cnki.stbcxb.2018.06.016 Jiajiaoyao gentle slope hills in Youyu County, Shanxi Province 2016 3 112.450000 40.02000 1439.00 420.00 4.00 18.00 10.00 1.360 5.170 0.750 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 16.00 10.00 8.256 0.404 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 16.00 6.00 15.484 0.758 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 16.00 10.00 6.774 0.332 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 16.00 2.00 9.326 0.457 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 16.00 3.00 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 8.00 10.00 8.124 0.398 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 15.00 11.00 4.488 0.220 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 15.00 11.00 4.383 0.215 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 28.00 9.00 5.414 0.265 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 28.00 9.00 2.750 0.135 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 48.00 12.00 8.765 0.429 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 48.00 12.00 4.297 0.210 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 13.00 5.00 13_Forest_function_China 13 Shen et al. (2000) https://doi.org/10.13287/j.1001-9332.2000.0088 Chaoyang,Liaoning 3 120.440000 41.58000 360.00 550.00 8.50 13.00 8.00 14_Forest_function_China 14 Chen et al. (2023) https://doi.org/10.1016/j.still.2022.105597 Heshang farm,nengjiang,Heilongjiang 2021 8 126.560000 49.00000 445.00 461.00 0.00 7.830 0.080 81.000 0.250 11.170 0.320 1.297 34.840 2.559 2.271 0.046 0.004 14_Forest_function_China 14 Chen et al. 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(2021) https://doi.org/10.1016/j.catena.2021.105616 Ziwuling in Fuxian County, Shaanxi Province 2019 3 109.140000 36.08000 1269.00 588.70 9.20 14.00 19.810 1.770 34.080 3.190 46.110 4.050 10.040 0.880 2.210 19.470 0.560 8.110 2.671 0.015 0.000 18_Forest_function_China 18 Abbas et al. (2021) https://doi.org/10.1016/j.catena.2021.105616 Ziwuling in Fuxian County, Shaanxi Province 2019 3 109.140000 36.08000 1269.00 588.70 9.20 14.00 17.200 0.010 29.470 0.010 53.350 0.020 10.270 0.880 2.100 15.460 1.760 8.160 2.118 0.014 0.000 18_Forest_function_China 18 Abbas et al. (2021) https://doi.org/10.1016/j.catena.2021.105616 Ziwuling in Fuxian County, Shaanxi Province 2019 3 109.150000 36.09000 1240.00 588.70 9.20 12.00 19.810 1.770 34.080 3.190 46.110 4.050 10.040 0.880 2.210 19.470 0.560 8.110 2.671 0.015 0.000 18_Forest_function_China 18 Abbas et al. 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(2025) https://doi.org/10.1016/j.geoderma.2025.117236 Caijiachuan,Shanxi 2024 4 110.730000 36.27000 1059.00 568.60 10.00 27.00 12.760 1.470 8.323 0.721 8.130 20_Forest_function_China 20 Gong et al. (2025) https://doi.org/10.1016/j.geoderma.2025.117236 Caijiachuan,Shanxi 2024 4 110.730000 36.27000 1059.00 568.60 10.00 27.00 12.760 1.470 8.323 0.721 8.130 20_Forest_function_China 20 Gong et al. (2025) https://doi.org/10.1016/j.geoderma.2025.117236 Caijiachuan,Shanxi 2024 4 110.730000 36.27000 1059.00 568.60 10.00 27.00 11.080 0.730 3.294 0.719 8.520 20_Forest_function_China 20 Gong et al. (2025) https://doi.org/10.1016/j.geoderma.2025.117236 Caijiachuan,Shanxi 2024 4 110.730000 36.27000 1059.00 568.60 10.00 27.00 11.080 0.730 3.294 0.719 8.520 21_Forest_function_China 21 Wang et al. (2025a) https://doi.org/10.1002/ldr.5492 Lvliang Mountain,Shanxi Province 3 110.580000 38.10000 893.64 518.80 8.80 12.00 9.910 0.582 42.500 2.250 26.580 1.351 1.350 7.040 0.790 0.310 1.220 0.080 0.020 0.000 21_Forest_function_China 21 Wang et al. (2025a) https://doi.org/10.1002/ldr.5492 Lvliang Mountain,Shanxi Province 3 110.540000 38.09000 937.38 518.80 8.80 13.50 9.910 0.582 42.500 2.250 26.580 1.351 1.260 10.590 0.450 0.450 3.600 0.100 0.017 0.000 21_Forest_function_China 21 Wang et al. (2025a) https://doi.org/10.1002/ldr.5492 Lvliang Mountain,Shanxi Province 3 110.790000 37.54000 843.40 518.80 8.80 10.00 9.910 0.582 42.500 2.250 26.580 1.351 1.240 12.270 1.840 0.480 4.320 0.070 0.017 0.000 21_Forest_function_China 21 Wang et al. (2025a) https://doi.org/10.1002/ldr.5492 Lvliang Mountain,Shanxi Province 3 110.910000 37.74000 912.20 518.80 8.80 12.00 9.910 0.582 42.500 2.250 26.580 1.351 1.220 10.380 1.730 0.360 3.160 0.050 0.017 0.000 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1090.00 504.00 8.90 20.00 1.360 0.234 1.242 12.047 1.309 0.788 5.216 0.305 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1090.00 504.00 8.90 20.00 1.360 0.234 1.316 8.259 1.187 0.471 2.644 0.227 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1090.00 504.00 8.90 20.00 1.360 0.234 1.382 5.327 0.925 0.308 1.787 0.162 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1150.00 504.00 8.90 30.00 1.855 0.169 1.123 15.923 0.908 0.813 6.320 0.286 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1150.00 504.00 8.90 30.00 1.855 0.169 1.252 11.663 1.222 0.497 3.797 0.197 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1150.00 504.00 8.90 30.00 1.855 0.169 1.321 6.147 0.855 0.281 2.618 0.239 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1202.00 504.00 8.90 23.00 1.503 0.172 1.183 13.042 0.978 0.729 5.600 0.383 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1202.00 504.00 8.90 23.00 1.503 0.172 1.255 8.190 1.047 0.464 2.608 0.229 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1202.00 504.00 8.90 23.00 1.503 0.172 1.324 5.658 0.838 0.254 1.917 0.169 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1145.00 504.00 8.90 16.00 1.567 0.244 1.198 14.614 1.344 0.974 7.006 0.379 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1145.00 504.00 8.90 16.00 1.567 0.244 1.313 10.197 1.344 0.646 3.736 0.175 22_Forest_function_China 22 Zhao et al. (2024) https://doi.org/10.1016/j.catena.2024.108447 Zhifanggou watershed,Shaanxi Province, 10 109.248472 36.77600 1145.00 504.00 8.90 16.00 1.567 0.244 1.368 6.444 1.170 0.425 1.873 0.164 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.200000 36.89000 1468.00 483.40 7.80 30.00 2.299 0.385 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.230000 36.89000 1351.00 483.40 7.80 10.00 2.050 0.419 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.180000 36.91000 1351.00 483.40 7.80 15.00 2.322 0.385 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.180000 36.90000 1435.00 483.40 7.80 13.00 2.073 0.215 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.180000 36.90000 1452.00 483.40 7.80 23.00 1.688 0.283 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.180000 36.90000 1528.00 483.40 7.80 18.00 1.778 0.510 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.160000 36.92000 1494.00 483.40 7.80 23.00 2.107 0.442 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.160000 36.92000 1488.00 483.40 7.80 6.00 2.118 0.227 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.190000 36.91000 1468.00 483.40 7.80 25.00 2.288 0.113 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.190000 36.91000 1345.00 483.40 7.80 22.00 2.245 0.034 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.190000 36.93000 1468.00 483.40 7.80 19.00 1.971 0.147 23_Forest_function_China 23 Chen et al. (2024) https://doi.org/10.1002/ldr.5054 Wuqi County, Shaanxi Province 2019 25 108.180000 36.92000 1426.00 483.40 7.80 23.00 2.084 0.170 24_Forest_function_China 24 Zhang et al. (2024b) https://doi.org/10.1016/j.jenvman.2024.123356 Nanxiaohegou watershed ,situated near Qingyang City, Gansu 2022 3 107.563000 35.70600 1203.00 556.00 9.30 24.00 7.710 0.453 79.400 4.204 12.890 0.655 1.340 9.220 1.166 5.270 0.477 1.270 0.020 0.000 24_Forest_function_China 24 Zhang et al. (2024b) https://doi.org/10.1016/j.jenvman.2024.123356 Nanxiaohegou watershed ,situated near Qingyang City, Gansu 2022 3 107.565000 35.70000 1210.00 556.00 9.30 20.00 7.730 0.454 78.410 4.152 13.860 0.705 1.260 9.180 1.161 5.680 0.514 1.560 0.020 0.000 24_Forest_function_China 24 Zhang et al. (2024b) https://doi.org/10.1016/j.jenvman.2024.123356 Nanxiaohegou watershed ,situated near Qingyang City, Gansu 2022 3 107.553000 35.70700 1278.00 556.00 9.30 23.00 6.490 0.381 73.170 3.874 20.340 1.034 1.030 21.860 2.766 10.140 0.918 1.680 0.019 0.000 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 0.480 77.204 4.467 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 0.590 42.869 3.267 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 36.00 0.750 59.470 4.000 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 36.00 0.780 20.601 3.467 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 34.00 0.920 34.668 2.000 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 34.00 1.270 11.867 2.933 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 32.00 0.710 50.069 4.867 25_Forest_function_China 25 Wang et al. (2007) Sichuan 2004 15 103.800000 28.69170 1325.00 331.60 12.80 32.00 0.840 25.468 3.934 26_Forest_function_China 26 Zhang et al. (2021) https://doi.org/10.1002/ldr.3887 Loess Plateau 2018 9 107.555000 36.21525 1350.00 550.00 8.90 35.00 1.280 0.020 1.060 10.820 0.050 8.510 2.260 0.027 0.000 26_Forest_function_China 26 Zhang et al. (2021) https://doi.org/10.1002/ldr.3887 Loess Plateau, 2018 9 107.555000 36.21525 1370.00 550.00 8.90 21.00 1.090 0.210 0.900 9.990 0.100 8.500 2.450 0.026 0.000 26_Forest_function_China 26 Zhang et al. (2021) https://doi.org/10.1002/ldr.3887 Loess Plateau, 2018 9 107.555000 36.21525 1350.00 550.00 8.90 43.00 1.390 0.080 1.300 13.980 0.100 8.290 1.550 0.028 0.000 26_Forest_function_China 26 Zhang et al. (2021) https://doi.org/10.1002/ldr.3887 Loess Plateau, 2018 9 107.555000 36.21525 1360.00 550.00 8.90 36.00 1.080 0.150 0.930 8.230 0.270 8.490 1.630 0.030 0.000 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 1.023 20.407 1.949 35.468 3.468 4.782 3.298 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 1.067 23.897 1.299 17.404 2.277 4.451 3.184 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 0.821 24.257 1.240 26.064 2.702 4.403 2.529 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 0.910 14.459 1.240 19.851 2.468 4.767 2.253 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 1.020 18.512 1.780 25.149 3.787 5.042 3.403 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 1.287 25.132 2.312 15.787 4.596 4.593 3.517 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 0.972 18.759 1.770 20.553 3.106 4.734 2.795 27_Forest_function_China 27 Liu et al. (2025) https://doi.org/10.1016/j.jenvman.2025.124455 Park-Jianfengling,Hainan 2022 15 108.841500 18.62500 763.00 880.00 14.30 1.008 14.985 1.369 13.830 3.021 4.827 2.433 28_Forest_function_China 28 Bai et al. (2014) https://doi.org/10.13870/j.cnki.stbcxb.2014.02.015 Lvliang Mountain,Shanxi Province 2012 5 111.483300 37.86700 1780.00 822.60 4.30 34.00 17.00 1.230 12.360 1.001 0.860 28_Forest_function_China 28 Bai et al. (2014) https://doi.org/10.13870/j.cnki.stbcxb.2014.02.015 Lvliang Mountain,Shanxi Province 2012 5 111.483300 37.86700 1720.00 822.60 4.30 55.00 15.00 1.180 15.780 1.278 1.040 28_Forest_function_China 28 Bai et al. (2014) https://doi.org/10.13870/j.cnki.stbcxb.2014.02.015 Lvliang Mountain,Shanxi Province 2012 5 111.483300 37.86700 1800.00 822.60 4.30 60.00 16.00 1.140 19.720 1.597 1.280 29_Forest_function_China 29 Lv and Wang (2010) https://doi.org/10.19336/j.cnki.trtb.2010.05.026 Shunping,Shanxi 2007 3 113.395000 36.22480 1253.50 608.30 9.10 25.00 1.150 29_Forest_function_China 29 Lv and Wang (2010) https://doi.org/10.19336/j.cnki.trtb.2010.05.026 Shunping,Shanxi 2007 3 113.395000 36.22480 1253.50 608.30 9.10 25.00 0.980 29_Forest_function_China 29 Lv and Wang (2010) https://doi.org/10.19336/j.cnki.trtb.2010.05.026 Shunping,Shanxi 2007 3 113.395000 36.22480 1253.50 608.30 9.10 25.00 1.020 30_Forest_function_China 30 Chen et al. (2006) https://doi.org/10.13870/j.cnki.stbcxb.2006.05.001 Xichou,Yunnan 2002 3 104.680000 23.22000 1730.00 1345.50 16.20 14.640 1.185 6.660 30_Forest_function_China 30 Chen et al. (2006) https://doi.org/10.13870/j.cnki.stbcxb.2006.05.001 Xichou,Yunnan 2002 3 104.680000 23.22000 1730.00 1345.50 16.20 26.032 2.108 6.930 30_Forest_function_China 30 Chen et al. (2006) https://doi.org/10.13870/j.cnki.stbcxb.2006.05.001 Xichou,Yunnan 2002 3 104.680000 23.22000 1730.00 1345.50 16.20 20.560 1.665 6.480 30_Forest_function_China 30 Chen et al. (2006) https://doi.org/10.13870/j.cnki.stbcxb.2006.05.001 Xichou,Yunnan 2002 3 104.680000 23.22000 1730.00 1345.50 16.20 22.160 1.794 7.030 31_Forest_function_China 31 Yang et al. (2023) https://doi.org/10.1016/j.foreco.2023.121168 Pengzhou City, Sichuan Province 2018 13 103.940000 31.08000 1153.00 1265.00 15.70 31.00 2.520 0.070 19.329 0.591 6.980 3.660 0.970 4.630 31_Forest_function_China 31 Yang et al. (2023) https://doi.org/10.1016/j.foreco.2023.121168 Pengzhou City, Sichuan Province 2018 13 103.940000 31.08000 1215.50 1265.00 15.70 33.00 2.100 0.090 16.215 0.537 3.040 4.260 1.630 4.610 31_Forest_function_China 31 Yang et al. (2023) https://doi.org/10.1016/j.foreco.2023.121168 Pengzhou City, Sichuan Province 2018 13 103.940000 31.08000 1196.00 1265.00 15.70 30.00 2.250 0.110 22.980 0.698 3.000 4.380 0.990 4.590 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.300 19.595 1.465 44.900 1.810 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.470 16.590 2.290 23.950 0.330 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.560 9.770 1.175 16.200 0.325 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.440 17.035 2.580 54.440 2.430 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.470 13.035 1.730 41.550 1.000 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.530 13.330 0.870 28.330 0.925 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.370 14.555 1.110 29.020 0.855 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.430 14.095 1.390 18.710 0.650 32_Forest_function_China 32 Zhang et al. (2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.500 14.510 1.280 16.400 0.325 32_Forest_function_China 32 Zhang et al. 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(2022c) https://doi.org/10.13870/j.cnki.stbcxb.2022.06.022 Beijing 2021 9 116.467000 39.90000 809.00 630.00 12.50 1.630 10.825 1.135 22.890 0.805 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.113 18.150 0.060 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.237 17.760 0.500 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.036 19.280 0.050 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.163 18.620 0.600 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.086 18.910 0.070 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.196 18.370 0.700 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.105 18.560 0.050 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.223 17.950 0.500 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.145 17.550 0.060 33_Forest_function_China 33 Hong (2017) https://doi.org/10.13759/j.cnki.dlxb.2017.11.013 Gaosha,Fujian 2016 5 118.266500 26.88300 500.00 1887.00 19.70 28.00 1.271 17.270 0.060 34_Forest_function_China 34 Shi et al. 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(2012) Guangxi 3 107.917000 24.83300 596.00 1529.20 18.50 26.873 10.787 65_Forest_function_China 65 Chen et al. (2012) Guangxi 3 107.917000 24.83300 596.00 1529.20 18.50 76.289 22.771 65_Forest_function_China 65 Chen et al. (2012) Guangxi 3 107.917000 24.83300 596.00 1529.20 18.50 94.145 36.556 66_Forest_function_China 66 Chen et al. (2020) Chong Qing 2019 5 106.460000 29.56000 550.00 1104.90 18.00 0.043 0.003 66_Forest_function_China 66 Chen et al. (2020) Chong Qing 2019 5 106.460000 29.56000 550.00 1104.90 18.00 0.047 0.001 66_Forest_function_China 66 Chen et al. (2020) Chong Qing 2019 5 106.460000 29.56000 550.00 1104.90 18.00 0.048 0.001 67_Forest_function_China 67 Zhu et al. (2023a) https://doi.org/10.3390/f14071356 Southwest China s karst region 10 105.108000 27.24200 1892.00 984.00 12.70 19.00 2.555 66.521 5.412 1.736 0.049 0.011 67_Forest_function_China 67 Zhu et al. 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(2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.439 73_Forest_function_China 73 Zou et al. (2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.373 73_Forest_function_China 73 Zou et al. (2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.285 73_Forest_function_China 73 Zou et al. (2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.301 73_Forest_function_China 73 Zou et al. (2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.345 73_Forest_function_China 73 Zou et al. (2015) https://doi.org/10.1139/cjfr-2014-0275 Taihe County, Jiangxi 2010 3 115.017000 26.73000 126.00 1500.00 17.90 1.350 73_Forest_function_China 73 Zou et al. 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(2025) https://doi.org/10.13870/j.cnki.stbcxb.2025.03.008 Shanxi, China 3 108.217000 36.89100 1505.50 466.36 7.80 23.00 1.410 0.138 78_Forest_function_China 78 Liu (2025) China 15 121.600000 42.47000 724.50 478.00 7.10 28.000 3.071 78_Forest_function_China 78 Liu (2025) China 15 121.600000 42.47000 724.50 478.00 7.10 29.000 3.180 78_Forest_function_China 78 Liu (2025) China 15 121.600000 42.47000 724.50 478.00 7.10 26.000 2.851 78_Forest_function_China 78 Liu (2025) China 15 121.600000 42.47000 724.50 478.00 7.10 24.000 2.632 79_Forest_function_China 79 Chen et al. (2025) https://doi.org/10.16445/j.cnki.1000-2340.20250416.001 Henan, China 35 112.908000 34.49200 636.50 614.00 14.20 1.040 0.270 79_Forest_function_China 79 Chen et al. (2025) https://doi.org/10.16445/j.cnki.1000-2340.20250416.001 Henan, China 35 112.908000 34.49200 636.50 614.00 14.20 1.310 0.260 80_Forest_function_China 80 He et al. (2025) Guangxi 4 103.817000 22.13300 22.05 1350.00 22.50 0.155 0.023 0.976 22.426 2.779 80_Forest_function_China 80 He et al. (2025) Guangxi 4 103.817000 22.13300 22.05 1350.00 22.50 0.203 0.010 1.286 34.644 4.024 80_Forest_function_China 80 He et al. (2025) Guangxi 4 103.817000 22.13300 22.05 1350.00 22.50 0.201 0.040 1.700 32.550 5.885 81_Forest_function_China 81 Wang et al. (2025b) https://doi.org/10.15958/j.cnki.sdnyswxb.2025.02.013 Guizhou 16 107.017000 27.08300 1104.00 1258.00 13.50 1.800 0.176 81_Forest_function_China 81 Wang et al. (2025b) https://doi.org/10.15958/j.cnki.sdnyswxb.2025.02.013 Guizhou 16 107.017000 27.08300 1104.00 1258.00 13.50 1.480 0.144 81_Forest_function_China 81 Wang et al. (2025b) https://doi.org/10.15958/j.cnki.sdnyswxb.2025.02.013 Guizhou 16 107.017000 27.08300 1104.00 1258.00 13.50 2.270 0.221 82_Forest_function_China 82 Liu et al. (2022) https://doi.org/10.3390/ijerph19148693 Hunan 6 111.583000 26.20000 196.00 1272.00 18.00 10.00 1.360 17.140 0.120 3.630 44.590 0.680 4.380 82_Forest_function_China 82 Liu et al. (2022) https://doi.org/10.3390/ijerph19148693 Hunan 6 111.583000 26.20000 196.00 1272.00 18.00 10.00 1.440 17.860 0.080 1.870 15.700 0.860 4.600 82_Forest_function_China 82 Liu et al. (2022) https://doi.org/10.3390/ijerph19148693 Hunan 6 111.583000 26.20000 196.00 1272.00 18.00 10.00 1.540 18.610 0.150 2.530 26.940 3.600 4.670 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.545000 37.85500 1720.00 820.00 4.30 1.350 9.850 2.520 2.565 10.860 1.060 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.554000 37.87600 1850.00 820.00 4.30 1.525 10.835 2.565 1.235 10.040 0.890 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.560000 37.88900 1950.00 820.00 4.30 1.465 17.365 2.875 1.865 11.765 1.240 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.570000 37.89600 2050.00 820.00 4.30 1.370 16.760 2.230 1.485 12.435 0.900 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.584000 37.90700 2150.00 820.00 4.30 1.260 15.245 2.085 1.050 13.865 1.125 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.598000 37.91700 2250.00 820.00 4.30 1.200 13.955 1.950 1.910 16.805 0.985 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.548000 37.85400 1720.00 820.00 4.30 1.370 13.685 1.230 2.050 10.410 1.440 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.559000 37.87500 1850.00 820.00 4.30 1.385 13.970 1.070 2.655 10.150 1.405 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.558000 37.88700 1950.00 820.00 4.30 1.505 13.320 1.135 1.375 12.330 1.420 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.569000 37.89800 2050.00 820.00 4.30 1.490 10.035 1.090 1.690 15.260 1.710 83_Forest_function_China 83 Niu et al. (2025) https://doi.org/10.13324/j.cnki.jfcf.202411001 Shanxi, China 2021 9 111.580000 37.91000 2150.00 820.00 4.30 1.415 13.575 2.060 1.135 21.150 2.060 84_Forest_function_China 84 Wu et al. (2019) https://doi.org/10.3390/f10100879 Shanxi, China 2022 15 112.017000 37.01700 1906.00 600.00 10.80 24.00 23.050 4.275 1.730 20.520 2.260 6.910 84_Forest_function_China 84 Wu et al. (2019) https://doi.org/10.3390/f10100879 Shanxi, China 2022 15 112.017000 37.01700 1906.00 600.00 10.80 24.00 22.320 4.270 1.320 15.570 1.530 6.950 84_Forest_function_China 84 Wu et al. (2019) https://doi.org/10.3390/f10100879 Shanxi, China 2022 15 112.017000 37.01700 1828.00 600.00 10.80 25.00 26.565 5.460 1.900 24.370 6.710 5.835 84_Forest_function_China 84 Wu et al. (2019) https://doi.org/10.3390/f10100879 Shanxi, China 2022 15 112.017000 37.01700 1828.00 600.00 10.80 25.00 20.370 3.490 1.510 18.680 7.260 6.220 85_Forest_function_China 85 Wang et al. (2024c) https://doi.org/10.1007/s11676-024-01780-0 Ningxia, China 2023 3 106.283000 37.30500 2553.00 259.00 8.70 34.00 1.032 0.471 85_Forest_function_China 85 Wang et al. (2024c) https://doi.org/10.1007/s11676-024-01780-0 Ningxia, China 2023 3 106.302000 37.31100 2096.00 259.00 8.70 21.00 3.122 0.220 85_Forest_function_China 85 Wang et al. (2024c) https://doi.org/10.1007/s11676-024-01780-0 Ningxia, China 2023 3 106.399000 37.35300 2187.00 259.00 8.70 24.00 2.827 0.224 85_Forest_function_China 85 Wang et al. (2024c) https://doi.org/10.1007/s11676-024-01780-0 Ningxia, China 2023 3 106.282000 37.27800 2267.00 259.00 8.70 35.00 3.100 0.220 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1432.00 1048.80 16.30 16.00 3.091 42.532 4.557 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1432.00 1048.80 16.30 16.00 1.435 15.696 2.279 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1432.00 1048.80 16.30 16.00 1.009 9.620 2.785 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1390.00 1048.80 16.30 14.00 3.785 61.013 10.127 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1390.00 1048.80 16.30 14.00 1.956 26.329 2.532 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1390.00 1048.80 16.30 14.00 1.341 15.696 1.772 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1420.00 1048.80 16.30 22.00 3.233 45.570 11.139 86_Forest_function_China 86 Yu et al. (2020) https://doi.org/10.1016/j.foreco.2020.118252 Sichuan 3 119.058000 28.01700 1420.00 1048.80 16.30 22.00 1.719 21.519 2.025 86_Forest_function_China 86 Yu et al. 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(2025a) Guangxi 6 108.208000 22.67500 180.00 1300.00 21.60 25.00 2.172 0.108 1.190 20.570 4.010 2.440 10.870 0.480 4.700 87_Forest_function_China 87 Zhang et al. (2025a) Guangxi 6 108.208000 22.67500 190.00 1300.00 21.60 23.00 2.860 0.043 1.130 33.510 2.880 4.490 20.550 0.760 4.590 87_Forest_function_China 87 Zhang et al. (2025a) Guangxi 6 108.208000 22.67500 190.00 1300.00 21.60 23.00 2.860 0.043 1.230 30.720 5.430 2.450 20.360 0.650 4.800 88_Forest_function_China 88 Hou et al. (2025) Guangxi 2021 15 111.625000 24.10800 400.00 2056.00 19.30 0.626 13.348 0.313 4.242 1.670 88_Forest_function_China 88 Hou et al. (2025) Guangxi 2021 15 111.625000 24.10800 400.00 2056.00 19.30 0.720 15.478 0.288 4.654 1.880 88_Forest_function_China 88 Hou et al. (2025) Guangxi 2021 15 111.625000 24.10800 400.00 2056.00 19.30 0.854 16.781 0.253 4.741 2.150 89_Forest_function_China 89 Zhang et al. 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(2024c) https://doi.org/10.16663/j.cnki.lskj.2024.23.038 Yunnan, China 9 101.850000 25.70000 1120.00 634.00 21.90 1.620 4.790 0.525 0.430 7.800 0.979 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.075 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.440 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.210 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.350 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 48.00 1.325 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 48.00 1.390 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.260 90_Forest_function_China 90 Zhang (2024) Liaoning, China 2023 9 119.975000 41.10800 865.00 507.30 8.50 50.00 1.370 91_Forest_function_China 91 Wang et al. (2024b) https://doi.org/10.13870/j.cnki.stbcxb.2024.06.030 Fuzhou, China 2020 20 116.333000 25.66700 500.00 1700.00 18.30 19.00 1.030 16.370 2.650 4.380 91_Forest_function_China 91 Wang et al. (2024b) https://doi.org/10.13870/j.cnki.stbcxb.2024.06.030 Fuzhou, China 2020 20 116.333000 25.66700 500.00 1700.00 18.30 19.00 0.940 15.470 2.080 4.000 91_Forest_function_China 91 Wang et al. (2024b) https://doi.org/10.13870/j.cnki.stbcxb.2024.06.030 Fuzhou, China 2020 20 116.333000 25.66700 500.00 1700.00 18.30 39.00 0.670 11.830 1.440 4.240 91_Forest_function_China 91 Wang et al. (2024b) https://doi.org/10.13870/j.cnki.stbcxb.2024.06.030 Fuzhou, China 2020 20 116.333000 25.66700 500.00 1700.00 18.30 39.00 1.340 22.900 0.120 4.200 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1196.00 625.00 9.10 45.00 20.30 1.727 15.418 2.423 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1202.00 625.00 9.10 45.00 20.50 1.339 10.793 1.542 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1219.00 625.00 9.10 44.00 19.00 0.846 8.040 1.652 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1209.00 625.00 9.10 25.00 22.50 2.626 20.374 2.643 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1209.00 625.00 9.10 26.00 19.80 2.044 16.740 2.974 92_Forest_function_China 92 Liang et al. (2025) https://doi.org/10.19675/j.cnki.1006-687x.2024.05002 Neimenggu, China 2023 6 108.400000 41.50000 1210.00 625.00 9.10 27.00 20.30 1.427 11.894 2.643 93_Forest_function_China 93 Luo et al. 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(2023) Guangxi 2020 25 106.833000 22.10000 730.00 1350.00 20.50 27.00 1.270 12.300 2.270 4.320 3.190 104_Forest_function_China 104 Fan et al. (2023) Guangxi 2020 25 106.833000 22.10000 730.00 1350.00 20.50 27.00 10.320 1.350 2.835 104_Forest_function_China 104 Fan et al. (2023) Guangxi 2020 25 106.833000 22.10000 725.00 1350.00 20.50 23.00 1.250 33.180 2.760 4.290 3.366 104_Forest_function_China 104 Fan et al. (2023) Guangxi 2020 25 106.833000 22.10000 725.00 1350.00 20.50 23.00 17.120 2.760 3.224 104_Forest_function_China 104 Fan et al. (2023) Guangxi 2020 25 106.833000 22.10000 728.00 1350.00 20.50 32.00 1.320 20.770 1.230 4.390 2.885 104_Forest_function_China 104 Fan et al. 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(2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 34.00 3.740 0.140 58.940 0.390 38.320 0.210 0.940 63.150 0.040 3.552 0.387 0.056 0.017 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 34.00 10.750 0.170 66.130 0.330 23.120 0.200 1.040 57.750 0.040 1.903 0.207 0.055 0.019 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 34.00 13.570 0.430 70.170 0.400 16.260 0.170 1.450 52.010 0.040 1.622 0.177 0.058 0.020 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 29.00 4.960 0.330 52.190 0.350 42.850 0.540 1.110 72.160 0.060 4.966 0.541 0.045 0.017 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 29.00 9.960 0.280 59.150 0.390 30.890 0.100 1.350 66.440 0.070 3.332 0.363 0.060 0.017 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 29.00 13.190 0.280 62.390 0.350 24.420 0.230 1.510 48.290 0.020 1.683 0.184 0.055 0.019 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 36.00 4.130 0.190 59.070 0.280 36.800 0.220 1.150 61.350 0.050 5.252 0.573 0.053 0.017 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 36.00 9.320 0.230 69.070 0.210 21.610 0.340 1.390 58.370 0.040 3.333 0.363 0.047 0.018 118_Forest_function_China 118 Zhu et al. (2023b) https://doi.org/10.16843/j.sswc.2023.03.015 Chongqing,jiangjing 9 106.437500 28.57000 1105.00 1522.30 13.70 15.00 36.00 13.530 0.260 72.660 0.270 13.810 0.080 1.530 50.950 0.010 0.842 0.092 0.060 0.025 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.200 0.001 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.200 0.001 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.200 0.001 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.030 0.240 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.030 0.240 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.030 0.240 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.460 0.320 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.460 0.320 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.460 0.320 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.810 0.260 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.810 0.260 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.810 0.260 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.910 0.210 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.910 0.210 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.910 0.210 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.710 0.530 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.710 0.530 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.710 0.530 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.480 0.270 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.480 0.270 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.480 0.270 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.530 0.070 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.530 0.070 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.530 0.070 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.290 0.230 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.390 0.350 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.270 0.300 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.090 0.230 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.390 0.350 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 1.270 0.300 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.850 0.360 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.470 0.580 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 1.190 0.200 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 1.300 0.350 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 1.300 0.350 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 36.00 5.94 0.700 0.820 0.350 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.570 0.440 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.210 0.250 119_Forest_function_China 119 Wang et al. (2021) Daxinganling 16 122.454500 52.97030 521.00 425.00 -4.20 37.00 9.88 0.700 0.560 0.360 120_Forest_function_China 120 Zheng et al. (2023a) Daxinganling 9 123.500000 51.82500 981.00 425.00 -4.30 2.780 37.380 8.200 120_Forest_function_China 120 Zheng et al. (2023a) Daxinganling 9 123.500000 51.82500 981.00 425.00 -4.30 15.00 5.050 50.390 6.560 120_Forest_function_China 120 Zheng et al. (2023a) Daxinganling 9 123.500000 51.82500 981.00 425.00 -4.30 15.00 3.670 64.870 7.750 120_Forest_function_China 120 Zheng et al. (2023a) Daxinganling 9 123.500000 51.82500 981.00 425.00 -4.30 4.00 7.210 107.900 13.230 121_Forest_function_China 121 Dong et al. (2023) Daxinganling 50 124.183000 52.03300 638.00 500.00 4.50 42.20 1.150 0.190 121_Forest_function_China 121 Dong et al. (2023) Daxinganling 50 124.183000 52.03300 638.00 500.00 4.50 62.60 1.540 0.200 121_Forest_function_China 121 Dong et al. (2023) Daxinganling 50 124.183000 52.03300 638.00 500.00 4.50 52.40 1.690 0.180 122_Forest_function_China 122 Xiao et al. (2019) Daxinganling 9 122.283000 53.43300 332.00 425.00 -4.90 6.340 27.010 2.951 122_Forest_function_China 122 Xiao et al. (2019) Daxinganling 9 122.283000 53.43300 332.00 425.00 -4.90 4.730 36.820 2.913 122_Forest_function_China 122 Xiao et al. (2019) Daxinganling 9 122.283000 53.43300 332.00 425.00 -4.90 4.160 27.960 2.919 123_Forest_function_China 123 Li et al. (2021) Daxinganling 6 121.400000 50.51700 433.00 375.00 -3.50 34.091 1.349 123_Forest_function_China 123 Li et al. (2021) Daxinganling 6 121.400000 50.51700 433.00 375.00 -3.50 66.761 4.048 123_Forest_function_China 123 Li et al. (2021) Daxinganling 6 123.750000 50.70000 732.00 375.00 -3.50 50.426 3.977 123_Forest_function_China 123 Li et al. (2021) Daxinganling 6 119.930000 50.60900 1184.00 375.00 -3.50 41.193 5.114 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.418 0.031 29.050 2.030 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.531 0.052 31.010 3.260 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.691 0.062 36.070 2.140 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.418 0.031 25.130 1.560 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.531 0.052 26.350 2.540 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.691 0.062 32.060 2.140 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.418 0.031 20.740 1.850 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.531 0.052 21.170 1.580 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.691 0.062 26.580 2.010 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.418 0.031 15.320 1.360 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.531 0.052 18.790 1.690 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 1.691 0.062 21.490 1.590 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 0.871 0.072 19.615 2.060 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 0.871 0.072 17.630 2.140 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 0.871 0.072 12.810 1.980 124_Forest_function_China 124 Liu et al. (2018) https://doi.org/10.16258/j.cnki.1674-5906.2018.09.004 Daxinganling 20 123.504000 51.83050 812.00 425.00 4.70 0.871 0.072 11.585 1.060 125_Forest_function_China 125 Zou et al. (2010) https://doi.org/10.13759/j.cnki.dlxb.2010.11.029 Daxinganling 15 124.908500 50.64150 800.00 500.00 -1.30 35.00 10.00 0.750 26.890 2.782 125_Forest_function_China 125 Zou et al. (2010) https://doi.org/10.13759/j.cnki.dlxb.2010.11.029 Daxinganling 15 124.908500 50.64150 800.00 500.00 -1.30 35.00 10.00 0.750 11.290 1.168 125_Forest_function_China 125 Zou et al. (2010) https://doi.org/10.13759/j.cnki.dlxb.2010.11.029 Daxinganling 15 124.908500 50.64150 800.00 500.00 -1.30 22.00 10.00 0.750 35.400 3.533 126_Forest_function_China 126 Hu et al. (2008) https://doi.org/10.13870/j.cnki.stbcxb.2008.02.045 Daxinganling 9 123.250000 50.00000 900.00 450.00 -3.50 59.795 6.186 126_Forest_function_China 126 Hu et al. (2008) https://doi.org/10.13870/j.cnki.stbcxb.2008.02.045 Daxinganling 9 123.250000 50.00000 900.00 450.00 -3.50 68.035 7.038 126_Forest_function_China 126 Hu et al. (2008) https://doi.org/10.13870/j.cnki.stbcxb.2008.02.045 Daxinganling 9 123.250000 50.00000 900.00 450.00 -3.50 22.198 2.216 127_Forest_function_China 127 Song and Dong (2014) Daxinganling 15 124.252500 50.51695 475.00 450.00 -1.20 6.00 0.400 1.060 0.090 36.310 2.580 6.690 19.490 1.070 127_Forest_function_China 127 Song and Dong (2014) Daxinganling 15 124.252500 50.51695 475.00 450.00 -1.20 6.00 1.020 0.080 78.570 5.140 5.240 18.780 1.030 127_Forest_function_China 127 Song and Dong (2014) Daxinganling 15 124.264000 50.46060 475.00 450.00 -1.20 8.00 1.350 0.150 82.750 6.340 6.340 17.160 0.980 127_Forest_function_China 127 Song and Dong (2014) Daxinganling 15 124.264000 50.46060 475.00 450.00 -1.20 8.00 1.210 0.110 76.160 4.280 6.590 21.060 1.280 127_Forest_function_China 127 Song and Dong (2014) Daxinganling 15 124.403350 50.57240 475.00 450.00 -1.20 7.00 1.060 0.090 43.390 3.250 8.730 20.010 1.540