Periodic Reporting for period 1 - CROSSGRASS (Cross-border analysis of grassland greenness in Asia: Climate variations, grazing pressure, and land policy change)
Reporting period: 2018-04-01 to 2020-03-31
To reduce land degradation and secure the livelihoods of rural populations for the Dryland Asia. The overall goal of project “CROSSGRASS” is to analyse the drivers and extent of the changes in grassland greenness, a proxy for plant growth, for the Dryland Asia’s grassland biome. We derived these insights from the combination of remote sensing data, agricultural statistics, and climate data with high spatial and temporal resolution. Using insights from past changes, we forecasted potential future developments under various alternative climate change scenarios. A better understanding of these relationships will allow the carving out of both management options and policy solutions that will help reduce the risk of land degradation and secure the livelihoods for rural populations. The specific objectives of CROSSGRASS include: (1) comparing different remote sensing resources; (2) mapping dynamics of grassland greenness; (2) analysing the drivers of changes in grassland greenness; (3) exploring future scenarios of grassland greenness; (4) dissemination and training. Due to the delayed progress in collection work of the animal data in the five central Asia countries, we have adapted our work plan and decided to firstly conduct our research in the Mongolian Plateau, and we promise that when the data is ready, we will update the results accordingly for the whole dryland Asia including Mongolian Plateau, North-western China and the central Asia.
In order to realize the listed objectives as written in the proposal, we have performed scientific works accordingly, including (1) We assessed temporal changes in grassland biomass and investigate whether the response of vegetation biomass to animal grazing across the different datasets, we used NDVI integrals derived from NDVI data for the whole Mongolian Plateau from 2000 to 2015 from the two widely used sensor systems, including the AVHRR (Advanced Very High Resolution Radiometer) NDVI3g from the GIMMS (Global Inventory Modelling and Mapping Studies) group (GIMMS NDVI3g) and two MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI products, i.e. the MODIS NDVI at a spatial resolution of 1km and 5km, respectively. (2) We employed the breaks for additive season and trend algorithm (BFAST) to detect the changes in grassland greenness in NDVI from 1982 to 2015. (3) Assessing the determinants of grassland greenness on the Mongolian Plateau, covering the province of Inner Mongolia in China and Mongolia. We used spatial panel regressions to disentangle the influence of precipitation, temperature, radiation, and the intensity of livestock grazing on the changes of normalized difference vegetation indices (NDVI) from 1982 to 2015 at the county level. (4) exploring future scenarios of grassland greenness, we projected the climate change and climate extremes (e.g. drought) over the dryland Asia, via climate observations from Climatic Research Unit (CRU) Time Series (TS) version 4.03 and climate simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) Earth system models. (5) The results have been disseminated to the public, especially the academic communities, by attending seminars, workshops, conferences, and publishing papers on academic media, and introducing MSCA projects as MSCA ambassador.
To effectively disseminate the research results of this project to the academic community and the broad audiences, we have attended several academic conferences that related to land use and climate change. We presented our project result by oral presentations and posters. The research results have been published or submitted for publications timely, which include a paper titled “Higher precipitation resulted in the grasslands greening on the Mongolian Plateau despite higher grazing intensity” that has been under review on Land degradation & development, a paper titled “Are overgrazing and climate change threatening the steppes of the Mongolian Plateau” that has been published on IAMO annuals and a paper on “Future drought in the dryland Asia under 1.5 ℃ and 2 ℃ warming scenario” that has been published in Earth’s Future. Discussions were organized every week in the host institute to discuss and solve problems that appear during conducting the project, with the main supervisor PD. Dr. Daniel Mueller and the advisor Dr. Zhanli Sun. During the past two years, we have also carried out tight collaborations with Prof. Dr. Patrick Hostert from Humboldt University in Berlin, and we have visited each other several times for detailed collaborations.
To effectively disseminate the research results of this project to the academic community and the broad audiences, we have attended several academic conferences that related to land use and climate change. We presented our project result by oral presentations and posters. The research results have been published or submitted for publications timely, which include a paper titled “Higher precipitation resulted in the grasslands greening on the Mongolian Plateau despite higher grazing intensity” that has been under review on Land degradation & development, a paper titled “Are overgrazing and climate change threatening the steppes of the Mongolian Plateau” that has been published on IAMO annuals and a paper on “Future drought in the dryland Asia under 1.5 ℃ and 2 ℃ warming scenario” that has been published in Earth’s Future. Discussions were organized every week in the host institute to discuss and solve problems that appear during conducting the project, with the main supervisor PD. Dr. Daniel Mueller and the advisor Dr. Zhanli Sun. During the past two years, we have also carried out tight collaborations with Prof. Dr. Patrick Hostert from Humboldt University in Berlin, and we have visited each other several times for detailed collaborations.
Changes in land management and climate alter vegetation dynamics, but the determinants of vegetation changes often remain elusive, especially in global drylands. Here, we assess the determinants of grassland greenness on the Mongolian Plateau, which is one of the world’s largest grassland biomes, covering the province of Inner Mongolia in China and Mongolia. We use spatial panel regressions to quantify the influence of precipitation, temperature, radiation, and the intensity of livestock grazing on the normalized difference vegetation indices (NDVI) from 1982 to 2015 at the county level. The results suggest that the Mongolian Plateau experienced vegetation greening during the growing season from 1982 to 2015. Precipitation and temperature were the most influential in contributing to higher grassland NDVI values for Inner Mongolia, while a higher grazing intensity and precipitation dominated in Mongolia. Our results highlight the dominant effect of climate variability, especially that of precipitation, on the grassland greenness in global drylands and challenge the common belief that a higher grazing pressure is principally associated with land degradation. The analysis exemplifies how representative wall-to-wall results can be attained from examining space-time data via recently developed software options.
To avoid the negative impacts of climate warming, the Paris Agreement aims to pursue efforts to maintain the global warming increase at well below 1.5℃ and even 2.0℃ until the end of the century. Questions have been raised regarding the climate extremes in dryland Asia. Will drought issues become more severe under the context of global warming? Are the existing drought indices able to quantify and characterize the drought intensity and arid area in this region? Answers to these questions are crucial for the livelihood of millions of individuals, as these people rely on grassland biomass to feed both animals and farmers; however, the answers remain unclear. Here, we found that the projected drought severity and arid area will persistently increase under both the 1.5°C and 2.0°C global warming scenarios. We also found that the drought conditions under the 2.0℃ warming scenario will be mitigated relative to those under the 1.5℃ warming scenario due to the beneficial effect of adequate precipitation under RCP4.5. Kazakhstan and Northwest China might be severely affected by drought. Therefore, understanding future changes in drought conditions in dryland Asia is critical for developing adaptation measures to cope with the challenges of rapid climate change.
To avoid the negative impacts of climate warming, the Paris Agreement aims to pursue efforts to maintain the global warming increase at well below 1.5℃ and even 2.0℃ until the end of the century. Questions have been raised regarding the climate extremes in dryland Asia. Will drought issues become more severe under the context of global warming? Are the existing drought indices able to quantify and characterize the drought intensity and arid area in this region? Answers to these questions are crucial for the livelihood of millions of individuals, as these people rely on grassland biomass to feed both animals and farmers; however, the answers remain unclear. Here, we found that the projected drought severity and arid area will persistently increase under both the 1.5°C and 2.0°C global warming scenarios. We also found that the drought conditions under the 2.0℃ warming scenario will be mitigated relative to those under the 1.5℃ warming scenario due to the beneficial effect of adequate precipitation under RCP4.5. Kazakhstan and Northwest China might be severely affected by drought. Therefore, understanding future changes in drought conditions in dryland Asia is critical for developing adaptation measures to cope with the challenges of rapid climate change.