Productivity and phenological responses of natural vegetation to present and future inter-annual climate variability across semi-arid river basins in Chile

被引:0
作者
Francisco E. Glade
Marcelo D. Miranda
Francisco J. Meza
Willem J. D. van Leeuwen
机构
[1] Pontificia Universidad Católica de Chile,Department of Ecosystem and Environment
[2] Pontificia Universidad Católica de Chile,Center of Applied Ecology & Sustainability (CAPES)
[3] Pontificia Universidad Católica de Chile,Centro Interdisciplinario de Cambio Global
[4] The University of Arizona,School of Natural Resources and the Environment, Office of Arid Lands Studies, Arizona Remote Sensing Center
[5] The University of Arizona,School of Geography and Development
来源
Environmental Monitoring and Assessment | 2016年 / 188卷
关键词
Vegetation productivity; Phenology trends; Monitoring land degradation; Climate change; Semi-arid region;
D O I
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中图分类号
学科分类号
摘要
Time series of vegetation indices and remotely sensed phenological data offer insights about the patterns in vegetation dynamics. Both are useful sources of information for analyzing and monitoring ecosystem responses to environmental variations caused by natural and anthropogenic drivers. In the semi-arid region of Chile, climate variability and recent severe droughts in addition to land-use changes pose threats to the stability of local ecosystems. Normalized difference vegetation index time series (2000–2013) data from the moderate resolution imaging spectroradiometer (MODIS) was processed to monitor the trends and patterns of vegetation productivity and phenology observed over the last decade. An analysis of the relationship between (i) vegetation productivity and (ii) precipitation and temperature data for representative natural land-use cover classes was made. Using these data and ground measurements, productivity estimates were projected for two climate change scenarios (RCP2.6 and RCP8.5) at two altitudinal levels. Results showed negative trends of vegetation productivity below 2000 m a.s.l. and positive trends for higher elevations. Phenology analysis suggested that mountainous ecosystems were starting their growing period earlier in the season, coinciding with a decreased productivity peak during the growing season. The coastal shrubland/grassland land cover class had a significant positive relation with rainfall and a significant negative relation with temperature, suggesting that these ecosystems are vulnerable to climate change. Future productivity projections indicate that under an RCP8.5 climate change scenario, productivity could decline by 12% in the period of 2060–2100, leading to a severe vegetation degradation at lower altitudes and in drier areas.
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[1]  
Anyamba A(2005)Analysis of Sahelian vegetation dynamics using NOAA-AVHRR NDVI data from 1981–2003 Journal of Arid Environments 63 596-614
[2]  
Tucker CJ(2008)Long-term satellite NDVI data sets: evaluating their ability to detect ecosystem functional changes in South America Sensors 8 5397-5425
[3]  
Baldi G(2008)Grazing effect on NDVI across an aridity gradient in Argentina Journal of Arid Environments 72 764-776
[4]  
Nosetto MD(1999)Phenological changes reflect climate change in Wisconsin Proceedings of the National Academy of Sciences of the United States of America 96 9701-9704
[5]  
Aragón R(2012)Temperature and precipitation controls over leaf-and ecosystem-level CO2 flux along a woody plant encroachment gradient Global Change Biology 18 1389-1400
[6]  
Aversa F(2015)Evaluation of TRMM multi-satellite precipitation analysis (TMPA) in a mountainous region of the central Andes range with a Mediterranean climate Hydrology Research 46 89-105
[7]  
Paruelo JM(2014)Modelling vegetation water-use and groundwater recharge as affected by climate variability in an arid-zone Acacia savanna woodland Journal of Hydrology 519 1084-1096
[8]  
Jobbágy EG(2007)A summary of the PRUDENCE model projections of changes in European climate by the end of this century Climatic Change 81 7-30
[9]  
Blanco LJ(2013)Increasing drought under global warming in observations and models Nature Climate Change 3 52-58
[10]  
Aguilera MO(2015)Trend analysis of MODIS NDVI time series for detecting land degradation and regeneration in Mongolia Journal of Arid Environments 113 16-28