2000－2021年桂西南峰丛洼地流域植被净初级生产力演变特征及其归因

王栋华; 田义超; 张强; 张亚丽; 林俊良; 陶进; 黄亮亮

doi:10.11932/karst20240204

2000－2021年桂西南峰丛洼地流域植被净初级生产力演变特征及其归因

doi: 10.11932/karst20240204

王栋华^{1, 2,},
田义超^{1, 2, ,},
张强¹,
张亚丽¹,
林俊良¹,
陶进¹,
黄亮亮²

1.
北部湾大学资源与环境学院, 北部湾海洋地理信息资源开发利用重点实验室, 广西钦州 535011
2.
桂林理工大学环境科学与工程学院, 广西桂林 541004

基金项目: 国家自然科学基金资助项目(42061020)；广西基地和人才项目(2019AC20088)；广西自然科学基金联合培育项目(2018JJA150135)；广西创新驱动发展专项(AA18118038)；北部湾大学高层次人才引进项目(2019KYQD28)；2021年度广西高校中青年教师科研基础能力提升项目(2021KY0431)

详细信息

作者简介:
王栋华（1996－），女，硕士研究生，研究方向：喀斯特生态系统服务。E-mail: dhua0521@hotmail.com

通讯作者:
田义超（1986－），男，博士，教授，研究方向：资源环境遥感与海岸带生态环境监测。E-mail: tianyichao1314@yeah.net。

中图分类号: Q948.1
计量
- 文章访问数: 42
- HTML浏览量: 9
- PDF下载量: 21
- 被引次数: 0
出版历程
- 收稿日期: 2022-09-14
- 网络出版日期: 2024-07-10
- 刊出日期: 2024-04-30

Evolution and attribution of net primary productivity of vegetation in the peak-cluster depression basin of Southwest Guangxi from 2000 to 2021

1.
School of Resources and Environment, Key Laboratory of Marine Geographic Information Resources Development and Utilization in the Beibu Gulf, Beibu Gulf University, Qinzhou, Guangxi 535011, China
2.
College of Environmental Science and Engineering, Guilin University of Technology, Guilin, Guangxi 541004, China

摘要

摘要: 监测植被净初级生产力的演变特征及其驱动力机制，对于深入了解陆地碳循环机制和促进生态环境可持续发展有着及其重要的作用。文章基于MOD17A3数据集植被净初级生产力（NPP）产品评估了 2000—2021年桂西南典型喀斯特峰丛洼地流域植被净初级生产力的时空演变，并借助 Theil-Sen Median 趋势分析、Mann-Kendall 检验方法、 Hurst 指数以及地理探测器等，研究区域内植被净初级生产力的空间分布、未来趋势、可持续性及驱动机制。结果表明：(1) 2000—2021年研究区植被NPP均值为945.23 gC∙m⁻²∙a⁻¹，呈现出上升趋势，增加速率为3.5596 gC∙m⁻²∙a⁻¹。喀斯特区域(4.5148 gC∙m⁻²∙a⁻¹) > 研究区域(3.5596 gC∙m⁻²∙a⁻¹) > 非喀斯特区域(2.7219 gC∙m⁻²∙a⁻¹)；(2) 植被NPP高值区域在防城港市周边，值皆大于1 200 gC∙m⁻²∙a⁻¹；低值区散布于水文线附近；(3) Sen变化趋势显示，研究区22年间植被NPP增加区域面积(77.98%)显著大于减少区域面积(22.02%)。Hurst指数显示，区域植被NPP介于0~1之间，平均值为0.65，呈现出向负偏态分布；(4)土地利用/覆被、植被覆盖度与高程因子是本研究区植被NPP的显著控制因子，其次为坡度及土壤类型。
- 植被净初级生产力 /
- MOD17A3 /
- 地理探测器 /
- 时空变化 /
- 桂西南峰丛洼地
Abstract: China has about 3.44×10⁶ km² of karst area, and the most typical karst landscape—one of the largest in the world—is distributed in Southwest China, covering an area of 4.26×10⁵ km². The karst area in Southwest China has a total population of more than 100 million in 48 ethnic minorities. Meanwhile, it is the major poverty-stricken area in China, with nearly half of the country's poor population. The peak-cluster depression basin in Guangxi is located in the southwest of Guangxi Zhuang Autonomous Region, including most parts of 3 prefecture-level cities—Baise, Wenshan and Chongzuo, as well as some areas of Nanning City and Fangchenggang City. The peak-cluster depression basin in southwest Guangxi is an old revolutionary base area and autonomous region for ethnic minorities along China's land boundary. It is not only an essential ecological barrier of the Pearl river basin, but also an important area for water conservation and biodiversity protection in China. However, this peak-cluster depression basin is subject to severe rock desertification and the scarcity of vegetation, because this basin is extensively developed with karst landscape, characterized by unique double-layer hydrogeological structures and shallow soil layer with severe soil erosion. This basin falls under the zone of southern subtropical climate, which is subdivided into the central subtropical climate zone (southern Guangxi climate zone), including Fangchenggang and Nanning, and the western subtropical climate zone (southwestern Guangxi climate zone), mainly including Baise, Pingxiang and Chongzuo. Due to the unique geography and fragile ecological environment of this basin, monitoring and analyzing the evolution and driving mechanism of the net primary productivity (NPP) of vegetation plays an important role in insight into the terrestrial carbon cycle mechanism and in sustainable development of the ecological environment.This study assessed the spatial and temporal evolution of NPP in the typical karst peak-cluster depression basin in southwestern Guangxi from 2000 to 2021, based on the MOD17A3 dataset NPP products, and investigated the spatial distribution, future trends, sustainability and driving mechanisms of NPP in this region with Theil-Sen Median trend analysis, Mann-Kendall test method, Hurst index and geodetector. The results show: (1) From 2000 to 2021, the average value of NPP in the study area was 945.23 gC∙m⁻²∙a⁻¹, with an increase rate of 3.5596 gC∙m⁻²∙a⁻¹. The increase rate can be ranked as: 4.5148 gC∙m⁻²∙a⁻¹ in the karst area >3.5596 gC∙m⁻²∙a⁻¹ in the study area >2.7219 gC∙m⁻²∙a⁻¹ in the non-karst area. (2) The areas with high NPP values (all greater than 1,200 gC∙m⁻²∙a⁻¹) were situated around Fangchenggang City; the areas with low values were scattered along the hydrological line. (3) The trend of Sen showed that the area with an increase of vegetation NPP (77.98%) was significantly larger than the area with a decrease of NPP (22.02%) during 22 years in the study area. Hurst index showed that the regional vegetation NPP values ranged from 0 to 1, averaging 0.65, with a negative skew distribution. (4) The quantitative attribution results of geodetector showed that land use/cover, vegetation coverage and elevation factors were the significant control factors of NPP in the study area, followed by slope and soil type.
- net primary productivity /
- MOD17A3 /
- geodetector /
- temporal and spatial changes /
- the peak-cluster depression in southwest Guangxi

HTML

图 1 桂西南峰丛洼地流域地理位置

Figure 1. Geographical location of the peak-cluster depression basin in southwest Guangxi

下载: 全尺寸图片幻灯片

图 2 研究区年均 NPP 时间变化趋势

Figure 2. Temporal trend of annual average NPP in the study area

下载: 全尺寸图片幻灯片

图 3 研究区 NPP 多年平均值 (a) 与 Sen 空间变化趋势 (b)

Figure 3. Annual average value of NPP (a) and spatial change of Sen (b) in the study area

下载: 全尺寸图片幻灯片

图 4 研究区 Hurst 指数空间分布 (a) 及其正态分布图 (b)

Figure 4. Spatial distribution of Hurst index (a) and its normal distribution (b) in the study area

下载: 全尺寸图片幻灯片

图 5 研究区 NPP 空间分异单因素解释度 ( q 值)

Figure 5. Single-factor explanatory degree (q-value) of spatial variation of NPP in the study area

下载: 全尺寸图片幻灯片

图 6 研究区土地利用转移桑基图 (a) 与2000—2020年土地利用类型变化过程中植被NPP的损益量 (b)

Figure 6. Sankey diagram of land use transfer (a) and the gain and loss of NPP in the process of change of land use types (b) in the study area from 2000 to 2020

下载: 全尺寸图片幻灯片

图 7 研究区不同海拔地带 NPP 统计图 (a) 与不同岩性类型区 NPP 统计图 (b)

Figure 7. NPP statistics at different elevations (a) and in different lithology types (b) in the study area

下载: 全尺寸图片幻灯片

图 8 研究区不同土壤类型 NPP 统计图

Figure 8. NPP statistics for different soil types in the study area

下载: 全尺寸图片幻灯片

表 1 Sen趋势值及其显著性检验分级

Table 1. Sen trend value and grading of its significance test

植被NPP类型	植被NPP变化趋势		面积/km²	百分比/%
植被NPP类型	Sen趋势	显著性检验	面积/km²	百分比/%
极显著增加	S>0	P<0.01	22 550.40	36.84
显著增加	S>0	0.01≤P<0.05	8 977.13	14.66
无明显变化	S<0或S>0	P≥0.05	24 809.70	40.53
显著减少	S<0	0.01≤P<0.05	1 998.56	3.26
极显著减少	S<0	P<0.01	2 878.88	4.70

下载: 导出CSV

表 2 不同气候类型区气象数据情况

Table 2. Meteorological data of different climate zones

气候区	降水量/mm∙a⁻¹	蒸散量/mm∙a⁻¹	太阳辐射量/MJ∙m⁻²∙a⁻¹	温度/ ℃
中亚热带西南部气候区	1 067.61	1 030.44	4 912.45	18.50
南亚热带西部气候区	1 471.11	1 047.11	4 653.11	21.03
南亚热带中部气候区	1 391.55	1 106.43	4 472.20	21.90

下载: 导出CSV

表 3 不同气候类型区植被NPP均值 (gC∙m⁻²)

Table 3. Mean values of NPP of different climate zones (gC∙m⁻²)

气候区	2000年	2005年	2010年	2015年	2020年
中亚热带西南部气候区	945.15	960.28	948.84	1 070.59	1 069.58
南亚热带西部气候区	918.10	849.36	941.46	969.77	974.89
南亚热带中部气候区	789.22	683.01	824.26	832.10	841.57

下载: 导出CSV

参考文献(47)

[1]	Field Christopher B, Behrenfeld Michael J, Randerson James T, Falkowski Paul. Primary production of the biosphere: Integrating terrestrial and oceanic components[J]. Science, 1998, 281(5374): 237-240.
[2]	Kwa Chunglin. Local ecologies and global science: Discourses and strategies of the International Geosphere-Biosphere Programme[J]. Social Studies of Science, 2005, 35(6): 923-950. doi: 10.1177/0306312705052100
[3]	Janssen Marco A, Schoon Michael L, Ke Weimao, Börner Katy. Scholarly networks on resilience, vulnerability and adaptation within the human dimensions of global environmental change[J]. Global Environmental Change, 2006, 16(3): 240-252.
[4]	Schiffer Robert A, Rossow William B. The International Satellite Cloud Climatology Project (ISCCP): The first project of the world climate research programme[J]. Bulletin of the American Meteorological Society, 1983, 64(7): 779-784. doi: 10.1175/1520-0477-64.7.779
[5]	Grace John. Understanding and managing the global carbon cycle[J]. Journal of Ecology, 2004, 92(2): 189-202. doi: 10.1111/j.0022-0477.2004.00874.x
[6]	Canadell Josep G, Pataki Diane E, Pitelka Louis F. Terrestrial ecosystems in a changing world[M]. Heidelberg: Springer Science & Business Media, 2007.
[7]	宋冰, 牛书丽. 全球变化与陆地生态系统碳循环研究进展[J]. 西南民族大学学报(自然科学版), 2016, 42(1):14-23. SONG Bing, NIU Shuli. Global change and terrestrial carbon cycle: A review[J]. Journal of Southwest Minzu University (Natural Science Edition), 2016, 42(1): 14-23.
[8]	左丽媛, 高江波. 基于地理探测器的喀斯特植被NPP定量归因[J]. 生态环境学报, 2020, 29(4):686-694. ZUO Liyuan, GAO Jiangbo. Quantitative attribution analysis of NPP in karst peak cluster depression based on geographical detector[J]. Ecology and Environmental Sciences, 2020, 29(4): 686-694.
[9]	闫妍, 覃金华, 房磊, 胡宝清, 伊坤朋, 陈龙池. 湖南省植被净初级生产力时空动态及其与气候因素的关系[J]. 生态学杂志, 2022, 41(8):1535-1544. YAN Yan, QIN Jinhua, FANG Lei, HU Baoqing, YI Kunpeng, CHEN Longchi. Spatiotemporal dynamics of vegetation net primary productivity and its relationships with climatic factors in Hunan Province[J]. Chinese Journal of Ecology, 2022, 41(8): 1535-1544.
[10]	朱思佳, 冯徽徽, 邹滨, 叶书朝. 2000—2019年洞庭湖流域植被NPP时空特征及驱动因素分析[J]. 自然资源遥感, 2022, 34(3):196-206. ZHU Sijia, FENG Huihui, ZOU Bin, YE Shuchao. Spatial-temporal characteristics of 2000–2019 vegetation NPP of the Dongting lake basin and their driving factors[J]. Remote Sensing for Natural Resources, 2022, 34(3): 196-206.
[11]	Kolby Smith W, Reed Sasha C, Cleveland Cory C, Ballantyne Ashley P, Anderegg William R L, Wieder William R, Liu Yi Y, Running Steven W. Large divergence of satellite and earth system model estimates of global terrestrial CO₂ fertilization[J]. Nature Climate Change, 2015, 6(3): 306-310.
[12]	Robinson Nathaniel P, Allred Brady W, Smith William K, Jones Matthew O, Moreno Alvaro, Erickson Tyler A, Naugle David E, Running Steven W, Pettorelli Nathalie, Paruelo Jose. Terrestrial primary production for the conterminous United States derived from Landsat 30 m and MODIS 250 m[J]. Remote Sensing in Ecology and Conservation, 2018, 4(3): 264-280.
[13]	Park Jin Han, Gan Jianbang, Park Chan. Discrepancies between global forest net primary productivity estimates derived from MODIS and forest inventory data and underlying factors[J]. Remote Sensing, 2021, 13(8): 1441. doi: 10.3390/rs13081441
[14]	Mngadi M, Odindi J, Mutanga O, Sibanda M. Estimating aboveground net primary productivity of reforested trees in an urban landscape using biophysical variables and remotely sensed data[J]. Science of the Total Environment, 2022, 802: 149958.
[15]	Oliva Gabriel, Paredes Paula, Ferrante Daniela, Cepeda Carla, Rabinovich Jorge, Root Bernstein Meredith. Remotely sensed primary productivity shows that domestic and native herbivores combined are overgrazing Patagonia[J]. Journal of Applied Ecology, 2019, 56(7): 1575-1584. doi: 10.1111/1365-2664.13408
[16]	Jaafar Hadi H, Ahmad Farah A. Crop yield prediction from remotely sensed vegetation indices and primary productivity in arid and semi-arid lands[J]. International Journal of Remote Sensing, 2015, 36(18): 4570-4589. doi: 10.1080/01431161.2015.1084434
[17]	Yu Tao, Sun Rui, Xiao Zhiqiang, Zhang Qiang, Liu Gang, Cui Tianxiang, Wang Juanmin. Estimation of global vegetation productivity from global land surface satellite data[J]. Remote Sensing, 2018, 10(2): 327. doi: 10.3390/rs10020327
[18]	李登科, 王钊. 基于MOD17A3的中国陆地植被NPP变化特征分析[J]. 生态环境学报, 2018, 27(3):397-405. LI Dengke, WANG Zhao. The characteristics of NPP of terrestrial vegetation in China based on MOD17A3 data[J]. Ecology and Environmental Sciences, 2018, 27(3): 397-405.
[19]	车风, 黄国清, 刘韬, 田艳红, 徐庆华, 邹秀琼, 聂荔. 2004—2015年湖北省植被NPP时空分布特征及其与气候因素关系[J]. 水土保持研究, 2019, 26(6):198-204, 225. CHE Feng, HUANG Guoqing, LIU Tao, TIAN Yanhong, XU Qinghua, ZOU Xiuqiong, NIE Li. Spatiotemporal distribution of net primary productivity and its correlation with meteorological factors in Hubei Province from 2004 to 2015[J]. Research of Soil and Water Conservation, 2019, 26(6): 198-204, 225.
[20]	何国兴, 柳小妮, 张德罡, 杜月红, 李强, 刘志刚, 关文昊, 杨军银, 韩天虎, 孙斌, 潘冬荣. 甘肃省草地NPP时空变化及对气候因子的响应[J]. 草地学报, 2021, 29(4):788-797. HE Guoxing, LIU Xiaoni, ZHANG Degang, DU Yuehong, LI Qiang, LIU Zhigang, GUAN Wenhao, YANG Junyin, HAN Tianhu, SUN Bin, PAN Dongrong. Spatio-temporal variation of NPP and its response to climate factors in grassland, Gansu Province[J]. Acta Agrestia Sinica, 2021, 29(4): 788-797.
[21]	李登科, 范建忠, 王娟. 基于MOD17A3的陕西省植被NPP变化特征[J]. 生态学杂志, 2011, 30(12):2776-2782. LI Dengke, FAN Jianzhong, WANG Juan. Variation characteristics of vegetation net primary productivity in Shaanxi Province based on MO17A3[J]. Chinese Journal of Ecology, 2011, 30(12): 2776-2782.
[22]	Zhang Yulong, Song Conghe, Zhang Kerong, Cheng Xiaoli, Zhang Quanfa. Spatial-temporal variability of terrestrial vegetation productivity in the Yangtze River Basin during 2000–2009[J]. Journal of Plant Ecology, 2013, 7(1): 10-23.
[23]	胡砚霞, 王长青. 汉江流域耕地生产力变化趋势与持续性分析[J]. 长江流域资源与环境, 2022, 31(6):1249-1261. HU Yanxia, WANG Changqing. Change trend and sustainability analysis of farmland productivity in the Han river basin[J]. Resources and Environment in the Yangtze Basin, 2022, 31(6): 1249-1261.
[24]	何宏昌, 马炳鑫, 靖娟利, 徐勇, 窦世卿, 刘兵. 近20年西南喀斯特地区植被NPP时空变化及自然因素地理探测[J]. 水土保持研究, 2022, 29(3):172-178, 188. doi: 10.3969/j.issn.1005-3409.2022.3.stbcyj202203024 HE Hongchang, MA Bingxin, JING Juanli, XU Yong, DOU Shiqing, LIU Bing. Spatiotemporal changes of NPP and natural factors in the southwestern karst areas from 2000 to 2019[J]. Research of Soil and Water Conservation, 2022, 29(3): 172-178, 188. doi: 10.3969/j.issn.1005-3409.2022.3.stbcyj202203024
[25]	洪辛茜, 黄勇, 孙涛. 我国西南喀斯特地区2001—2018年植被净初级生产力时空演变[J]. 生态学报, 2021, 41(24):9836-9846. HONG Xinqian, HUANG Yong, SUN Tao. Spatiotemporal evolution of vegetation net primary productivity in the karst region of Southwest China from 2001 to 2018[J]. Acta Ecologica Sinica, 2021, 41(24): 9836-9846.
[26]	Zhang Mengyu, Zhang Li, Ren Xiaoli, He Honglin, Lyu Yan, Wang Junbang, Yan Huimin. Effect of land use and land cover change on the changes in net primary productivity in karst areas of Southwest China: A case study of Huanjiang Maonan Autonomous County[J]. Journal of Resources and Ecology, 2020, 11(6): 606-616.
[27]	孙治娟, 谢世友. 基于地理探测器的云南省净初级生产力时空演变及因子探测[J]. 生态学杂志, 2021, 40(12):3836-3848. SUN Zhijuan, XIE Shiyou. Spatiotemporal variation in net primary productivity and factor detection in Yunnan Province based on geodetector[J]. Chinese Journal of Ecology, 2021, 40(12): 3836-3848.
[28]	王世杰, 张信宝, 白晓永. 中国南方喀斯特地貌分区纲要[J]. 山地学报, 2015, 33(6):641-648. WANG Shijie, ZHANG Xinbao, BAI Xiaoyong. An outline of karst geomorphology zoning in the karst areas of Southern China[J]. Mountain Research, 2015, 33(6): 641-648.
[29]	田义超, 杨棠, 徐欣. 北部湾典型入海流域植被净初级生产力时空分布特征及其影响因素[J]. 生态环境学报, 2021, 30(5):938-948. TIAN Yichao, YANG Tang, XU Xin. Temporal and spatial distribution characteristics and influencing factors of net primary productivity of vegetation in typical basin entering the sea in Beibu Gulf[J]. Ecology and Environmental Sciences, 2021, 30(5): 938-948.
[30]	王劲峰, 徐成东. 地理探测器:原理与展望[J]. 地理学报, 2017, 72(1):116-134. doi: 10.11821/dlxb201701010 WANG Jinfeng, XU Chengdong. Geodetector: Principle and prospective[J]. Acta Geographica Sinica, 2017, 72(1): 116-134. doi: 10.11821/dlxb201701010
[31]	刘垚燚, 曾鹏, 张然, 孙凤云, 车越. 基于GEE和BRT的1984—2019年长三角生态绿色一体化发展示范区植被覆盖度变化[J]. 应用生态学报, 2021, 32(3):1033-1044. LIU Yaoyi, ZENG Peng, ZHANG Ran, SUN Fengyun, CHE Yue. Vegetation coverage change of the demonstration area of ecologically friendly development in the Yangtze River Delta, China based on GEE and BRT during 1984–2019[J]. Chinese Journal of Applied Ecology, 2021, 32(3): 1033-1044.
[32]	李燕丽, 潘贤章, 王昌昆, 刘娅, 赵其国. 2000—2011年广西植被净初级生产力时空分布特征及其驱动因素[J]. 生态学报, 2014, 34(18):5220-5228. LI Yanli, PAN Xianzhang, WANG Changkun, LIU Ya, ZHAO Qiguo. Changes of vegetation net primary productivity and its driving factors from 2000 to 2011 in Guangxi, China[J]. Acta Ecologica Sinica, 2014, 34(18): 5220-5228.
[33]	廖春贵, 熊小菊, 胡宝清, 陈依兰, 陈月连, 贺同鑫. 广西不同岩性植被覆盖变化及对人类活动的响应[J]. 生态经济, 2018, 34(6):168-173. LIAO Chungui, XIONG Xiaoju, HU Baoqing, CHEN Yilan, CHEN Yuelian, HE Tongxin. Variation of vegetation cover on various lithology and its response to human activities in Guangxi[J]. Ecological Economy, 2018, 34(6): 168-173.
[34]	Taelman Sue Ellen, Schaubroeck Thomas, De Meester Steven, Boone Lieselot, Dewulf Jo. Accounting for land use in life cycle assessment: The value of NPP as a proxy indicator to assess land use impacts on ecosystems[J]. Science of the Total Environment, 2016, 550: 143-156. doi: 10.1016/j.scitotenv.2016.01.055
[35]	王茜, 赵筱青, 普军伟, 李思楠, 苗培培. 滇东南喀斯特区域石漠化时空格局演变研究:以广南县为例[J]. 中国岩溶, 2021, 40(4):707-717. WANG Qian, ZHAO Xiaoqing, PU Junwei, LI Sinan, MIAO Peipei. Study on temporal and spatial pattern evolution of karst rocky desertification region of southeast Yunnan: A case study of Guangnan county[J]. Carsologica Sinica, 2021, 40(4): 707-717.
[36]	黄龙, 包维楷, 李芳兰, 胡慧. 土壤结构和植被对土壤微生物群落的影响[J]. 应用与环境生物学报, 2021, 27(6):1725-1731. HUANG Long, BAO Weikai, LI Fanglan, HU Hui. Effects of soil structure and vegetation on microbial communities[J]. Chinese Journal of Applied and Environmental Biology, 2021, 27(6): 1725-1731.
[37]	李珊, 张浩, 李启权, 顾会战, 王昌全, 李冰, 蒋欣烨. 广元植烟土壤有效态微量元素的空间变异特征及影响因素[J]. 核农学报, 2017, 31(8):1618-1625. doi: 10.11869/j.issn.100-8551.2017.08.1618 LI Shan, ZHANG Hao, LI Qiquan, GU Huizhan, WANG Changquan, LI Bing, JIANG Xinye. Spatial variability of soil available microelement contents and their influencing factors in tobacco growing area in Guangyuan City[J]. Journal of Nuclear Agricultural Sciences, 2017, 31(8): 1618-1625. doi: 10.11869/j.issn.100-8551.2017.08.1618
[38]	况雪源, 苏志, 涂方旭. 广西气候区划[J]. 广西科学, 2007, 14(3):278-283. doi: 10.3969/j.issn.1005-9164.2007.03.024 KUANG Xueyuan, SU Zhi, TU Fangxu. Climate regionalization of Guangxi[J]. Guangxi Sciences, 2007, 14(3): 278-283. doi: 10.3969/j.issn.1005-9164.2007.03.024
[39]	田义超, 黄远林, 张强, 陶进, 张亚丽, 黄鹄, 周国清. 北部湾南流江流域植被净初级生产力时空分布及其驱动因素[J]. 生态学报, 2019, 39(21):8156-8171. TIAN Yichao, HUANG Yuanlin, ZHANG Qiang, TAO Jin, ZHANG Yali, HUANG Hu, ZHOU Guoqing. Spatiotemporal distribution of net primary productivity and its driving factors in the Nanliu river basin in the Beibu Gulf[J]. Acta Ecologica Sinica, 2019, 39(21): 8156-8171.
[40]	匡昭敏, 朱伟军, 杨鑫, 黄永璘, 何立, 孙涵. 基于MODIS数据的广西旱区干旱指数模型研究[J]. 大气科学学报, 2007, 30(3):352-358. doi: 10.3969/j.issn.1674-7097.2007.03.009 KUANG Zhaomin, ZHU Weijun, YANG Xin, HUANG Yonglin, HE Li, SUN Han. Study on drought index model of arid area in central Guangxi based on MODIS data[J]. Transactions of Atmospheric Sciences, 2007, 30(3): 352-358. doi: 10.3969/j.issn.1674-7097.2007.03.009
[41]	陈彦君, 赵筱青, 普军伟, 石小倩, 冯严, 周世杰. 滇东南喀斯特山区石漠化程度与坡位因子的关联机制研究[J/OL]. 中国岩溶, 2024,43(2): 1-15. http://kns.cnki.net/kcms/detail/45.1157.P.20220414.1805.002.html. CHEN Yanjun, ZHAO Xiaoqing, PU Junwei, SHI Xiaoqian, FENG Yan, ZHOU Shijie. Study on correlation mechanism between rocky desertification degree and slope position factors in karst mountainous area of southeast Yunnan[J/OL]. Carsologica Sinica, 2024,43(2): 1-15. http://kns.cnki.net/kcms/detail/45.1157.P.20220414.1805.002.html.
[42]	许尔琪. 基于CiteSpace的喀斯特石漠化国际研究进展[J]. 中国岩溶, 2021, 40(4):728-738. XU Erqi. Progress of international research of karst rocky desertification based on CiteSpace[J]. Carsologica Sinica, 2021, 40(4): 728-738.
[43]	曹建华, 袁道先, 杨慧, 黄芬, 朱同彬, 梁建宏, 周孟霞, 罗劬侃, 吴夏. 岩溶生态系统中的植物[J]. 中国岩溶, 2022, 41(3):365-377. doi: 10.11932/karst20220304 CAO Jianhua, YUAN Daoxian, YANG Hui, HUANG Fen, ZHU Tongbin, LIANG Jianhong, ZHOU Mengxia, LUO Qukan, WU Xia. Karst ecosystem and its plants[J]. Carsologica Sinica, 2022, 41(3): 365-377. doi: 10.11932/karst20220304
[44]	刘鸿雁, 蒋子涵, 戴景钰, 吴秀臣, 彭建, 王红亚, Jeroen Meersmans, Sophie M Green, Timothy A Quine. 岩石裂隙决定喀斯特关键带地表木本与草本植物覆盖[J]. 中国科学:地球科学, 2019, 49(12):1974-1981. LIU Hongyan, JIANG Zihan, DAI Jingyu, WU Xiuchen, PENG Jian, WANG Hongya, Jeroen Meersmans, Sophie M Green, Timothy A Quine. Rock crevices determine woody and herbaceous plant cover in the karst critical zone[J]. Scientia Sinica Terrae, 2019, 49(12): 1974-1981.
[45]	茆杨, 蒋勇军, 张彩云, 乔伊娜, 吕同汝, 邱菊. 近20年来西南地区植被净初级生产力时空变化与影响因素及其对生态工程响应[J]. 生态学报, 2022, 42(7):2878-2890. MAO Yang, JIANG Yongjun, ZHANG Caiyun, QIAO Yina, LYU Tongru, QIU Ju. Spatio-temporal changes and influencing factors of vegetation net primary productivity in Southwest China in the past 20 years and its response to ecological engineering[J]. Acta Ecologica Sinica, 2022, 42(7): 2878-2890.
[46]	潘洪义, 黄佩, 徐婕. 基于地理探测器的岷江中下游地区植被NPP时空格局演变及其驱动力研究[J]. 生态学报, 2019, 39(20):7621-7631. PAN Hongyi, HUANG Pei, XU Jie. The spatial and temporal pattern evolution of vegetation NPP and its driving forces in middle-lower areas of the Min river based on geographical detector analyses[J]. Acta Ecologica Sinica, 2019, 39(20): 7621-7631.
[47]	刘洁, 孟宝平, 葛静, 高金龙, 殷建鹏, 侯蒙京, 冯琦胜, 梁天刚. 基于CASA模型和MODIS数据的甘南草地NPP时空动态变化研究[J]. 草业学报, 2019, 28(6):19-32. doi: 10.11686/cyxb2018320 LIU Jie, MENG Baoping, GE Jing, GAO Jinlong, YIN Jianpeng, HOU Mengjing, FENG Qisheng, LIANG Tiangang. Spatio-temporal dynamic changes of grassland NPP in Gannan Prefecture, as determined by the CASA model[J]. Acta Prataculturae Sinica, 2019, 28(6): 19-32. doi: 10.11686/cyxb2018320