Impacts of climate change on key soil ecosystem services and interactions in Central Asia

被引:10
作者
Li J. [1 ,2 ]
Chen H. [1 ,2 ]
Zhang C. [3 ,4 ]
机构
[1] State Key Laboratory of Desert and Oasis Ecology, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, Urumqi
[2] University of Chinese Academy of Sciences, Beijing
[3] Shandong Provincial Key Laboratory of Water and Soil Conservation and Environmental Protection, College of Resources and Environment, Linyi University, Linyi
[4] Research Center for Ecology and Environment of Central Asia, Chinese Academy of Sciences, Urumqi
来源
Zhang, Chi (zc@ms.xjb.ac.cn) | 1600年 / Elsevier B.V., Netherlands卷 / 116期
关键词
Central Asia; Climate change; Net primary productivity; Sand fixation; Soil conservation;
D O I
10.1016/j.ecolind.2020.106490
中图分类号
学科分类号
摘要
In Central Asia (CA), climate change influences soil ecosystem services (ESs) that are essential for the sustainable management of natural resources and development of social economies. Based on the Revised Universal Soil Equation (RUSLE), Revised Wind Erosion Equation (RWEQ) and Carnegie-Ames-Stanford Approach (CASA), we simulated the three key ESs, including soil conservation (SC), sand fixation (SF) and net primary productivity (NPP), in CA for two future periods (2030s and 2050s) using a climate projection for two representative concentration pathway (RCP) scenarios: RCP 2.6 and RCP 8.5. Based on the Inter-sectoral Impact Model Inter-comparison Project (ISIMIP2b) climate model, a consensus was found using the two RCP scenarios, and it indicated that an increase in temperature (average: 1.48 °C–3.59 °C) and increase in rainfall (average: 5.07 mm–33.79 mm) would occur among the four climatic subregions under future climate changes. The SC and SF were projected to increase by 4.85%–29.14% and 35.14%–161.25% under RCP 2.6 and RCP 8.5, respectively. The results indicated that the non-phreatophyte shrubland distributed in the central arid desert shrub area would decrease by 5.2 g C/m2–15.94 g C/m2. Correlation analysis indicated a positive relationship between the difference in SC and NPP (R = 0.54–0.64), except in the humid and cold forest-meadow area in Tianshan, where negative correlations existed between the difference in SF and NPP (R = −0.07 to −0.58)/SC (R = −0.21 to −0.48) from 1986 to 2060. Climatic changes are the major drivers of ecosystem service fluctuations. A correlation analysis showed that the decrease in precipitation significantly hindered SC (R = 0.37–0.69) and NPP (R = 0.45–0.74), while the increases in wind speed (R = 0.45–0.85) and temperature (R = 0.29–0.69) exerted obvious positive influences on SF. Our research results show that risks of vegetation degradation will occur in the middle arid desert shrub area, and ecological restoration projects (e.g. ecological reserve) should be established to improve soil ESs efficiency. © 2020 Elsevier Ltd
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共 91 条
  • [71] Su C., Liu H., Wang S., A process-based framework for soil ecosystem services study and management, Sci. Total Environ., 627, pp. 282-289, (2018)
  • [72] Teng H., Liang Z., Chen S., Liu Y., Viscarra Rossel R.A., Chappell A., Et al., Current and future assessments of soil erosion by water on the Tibetan Plateau based on RUSLE and CMIP5 climate models, Sci. Total Environ., 635, pp. 673-686, (2018)
  • [73] van Vuuren D.P., Lucas P.L., Hilderink H., Downscaling drivers of global environmental change: enabling use of global SRES scenarios at the national and grid levels, Glob. Environ. Change, 17, pp. 114-130, (2007)
  • [74] van Vuuren D.P., Stehfest E., den Elzen M.G.J., van Vliet J., Isaac M., Exploring IMAGE model scenarios that keep greenhouse gas radiative forcing below 3W/m2 in 2100, Energy Econ., 32, pp. 1105-1120, (2010)
  • [75] Wang C., Han X., Xing X., Effects of grazing exclusion on soil net nitrogen mineralization and nitrogen availability in a temperate steppe in northern China, J. Arid Environ., 74, pp. 1287-1293, (2010)
  • [76] Wang X., Cheng C., Yin L., Feng X., Wei X., Spatial-temporal changes and trade-offs and synergies relationship of ecosystem services in Xinjiang, Chin. J. Ecol., pp. 1-14, (2019)
  • [77] Watanabe M., Suzuki T., Oishi R., Komuro Y., Watanabe S., Emori S., Et al., Improved climate simulation by MIROC5: mean states, variability, and climate sensitivity, J. Clim., 23, pp. 6312-6335, (2010)
  • [78] Wieder W., Regridded Harmonized World Soil Database v1.2, (2014)
  • [79] Wischmeier W.H., Smith D.D., Predicting Rainfall Erosion Losses: A Guide to Conservation Planning [USA], (1978)
  • [80] Wu H., Huang A., He Q., Zhao Y., Projection of the spatial and temporal variation characteristics of precipitation over Central Asia of 10 CMIP5 models in the next 50 years, Arid Land Geogr., 36, pp. 669-679, (2013)