气候变化领域集成服务门户(CCPortal): Annual Landsat time series reveal post-Soviet changes in grazing pressure

CCPortal

DOI	10.1016/j.rse.2020.111667
	Annual Landsat time series reveal post-Soviet changes in grazing pressure
	Dara A.; Baumann M.; Freitag M.; Hölzel N.; Hostert P.; Kamp J.; Müller D.; Prishchepov A.V.; Kuemmerle T.
发表日期	2020
ISSN	00344257
卷号	239
英文摘要	Temperate grasslands are globally widespread, play an important role as carbon storage, and harbor unique biodiversity. Livestock grazing is the most widespread land use in temperate grasslands, and understanding the impact of grazing on grassland ecosystems is therefore important. However, monitoring grazing pressure and how it changes is hampered by a lack of adequate tools. The Eurasian steppe belt, extending from Eastern Europe to China has experienced marked changes in grazing pressure. Most notably, livestock numbers in the steppes of Kazakhstan and Russia declined by up to 80% after the breakdown of the Soviet Union in 1991, yet how this impacted spatial patterns of grazing pressure is unclear. To address this research gap, we used all available Landsat data from 1985 to 2017 together with extensive ground reference data on grazing pressure to evaluate a broad range of spectral-temporal metrics regarding their ability to capture grazing pressure. While Tasseled Cap-based disturbance indices performed best, combining all spectral-temporal metrics in a binary random forest classification yielded a grazing class membership probability that strongly outperformed all individual metrics. This new index of grazing pressure correlated well with a range of field-based grazing indicators (e.g., number of dung piles, herbaceous biomass) and yielded highly plausible spatial patterns of grazing pressure. We used this index to reconstruct annual changes in grazing pressure across our 360,000 km2 study region, and used LandTrendr time series segmentation to identify trends in grazing pressure. Aggregated grazing pressure followed closely known trends in total livestock numbers over the time period we studied. The spatial footprint of heavy grazing was very large before 1991, but decreased by 73 (±2) % until 2017. This now leaves large areas virtually ungrazed, even in close vicinity to settlements and agricultural areas, and despite a recent recovery of livestock numbers. Our analyses uncovered previously unknown hot-spots of heavy grazing during Soviet times (e.g., around watering points). Our findings suggest potential for a further revival of the livestock sector as well as for the restoration of steppe ecosystems. More broadly, our study highlights how the Landsat archive, in combination with field data on grazing, can be used to map grazing pressure reliably across large areas and over long time spans. © 2020 Elsevier Inc.
英文关键词	Class probabilities; Eurasian steppes; Grazing pressure; Land-use change; Landsat time series; LandTrendr; Random forests
语种	英语
scopus关键词	Biodiversity; Decision trees; Digital storage; Forestry; Land use; Time series; Class probabilities; Eurasian steppes; Grazing pressure; Land-use change; Landsat time series; LandTrendr; Random forests; Ecosystems; algorithm; annual variation; grassland; grazing pressure; land use change; Landsat; probability; satellite data; steppe; terrestrial ecosystem; time series; China; Eastern Europe; Kazakhstan; Russian Federation; USSR
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179437
作者单位	Geography Department, Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany; Leibniz Institute for Agricultural Development in Transition Economies (IAMO), Theodor-Lieser-Str. 2, Halle (Saale), 06120, Germany; Integrative Research Institute on Transformations of Human-Environment Systems (IRI THESys), Humboldt-Universität zu Berlin, Unter den Linden 6, Berlin, 10099, Germany; Institute of Landscape Ecology, University Münster, Heisenbergstr. 2, Münster, 48149, Germany; Department of Geosciences and Natural Resource Management (IGN), University of Copenhagen, Copenhagen, 1350, Denmark
推荐引用方式 GB/T 7714	Dara A.,Baumann M.,Freitag M.,et al. Annual Landsat time series reveal post-Soviet changes in grazing pressure[J],2020,239.
APA	Dara A..,Baumann M..,Freitag M..,Hölzel N..,Hostert P..,...&Kuemmerle T..(2020).Annual Landsat time series reveal post-Soviet changes in grazing pressure.Remote Sensing of Environment,239.
MLA	Dara A.,et al."Annual Landsat time series reveal post-Soviet changes in grazing pressure".Remote Sensing of Environment 239(2020).