Satellite observed widespread decline in Mongolian grasslands largely due to overgrazing

Abstract

The Mongolian Steppe is one of the largest remaining grassland ecosystems. Recent studies have reported widespread decline of vegetation across the steppe and about 70% of this ecosystem is now considered degraded. Among the scientific community there has been an active debate about whether the observed degradation is related to climate, or over-grazing, or both. Here, we employ a new atmospheric correction and cloud screening algorithm (MAIAC) to investigate trends in satellite observed vegetation phenology. We relate these trends to changes in climate and domestic animal populations. A series of harmonic functions is fitted to Moderate Resolution Imaging Spectroradiometer (MODIS) observed phenological curves to quantify seasonal and inter-annual changes in vegetation. Our results show a widespread decline (of about 12% on average) in MODIS observed normalized difference vegetation index (NDVI) across the country but particularly in the transition zone between grassland and the Gobi desert, where recent decline was as much as 40% below the 2002 mean NDVI. While we found considerable regional differences in the causes of landscape degradation, about 80% of the decline in NDVI could be attributed to increase in livestock. Changes in precipitation were able to explain about 30% of degradation across the country as a whole but up to 50% in areas with denser vegetation cover (P < 0.05). Temperature changes, while significant, played only a minor role (r(2) = 0.10, P < 0.05). Our results suggest that the cumulative effect of overgrazing is a primary contributor to the degradation of the Mongolian steppe and is at least partially responsible for desertification reported in previous studies.

Spatio-temporal patterns of herbage availability and livestock movements: A cross-border analysis in the Chinese-Mongolian Altay

“…However, the non-compliance with administratively prescribed arrival and departure dates for pasture sites by most of the herders (own data, unpublished) disclosed the limited reach of strict regulation in a highly fragile environment (Banks et al 2003;Campbell et al 2006;Lee et al 2015). Mongolian pastures, in contrast, are currently subjected to rising grazing pressure due to increasing livestock numbers (especially before the 2009/2010 dzud) and particularly increasing numbers of cashmere goats, as well as possibly reduced livestock mobility (Saizen et al 2010;Hilker et al 2014). These phenomena were also observed in Bulgan county (personal communication, Bulgan sum governor), where from 1999 to 2014 the goat and sheep population in the Mongolian study region increased by 51 % and 9 %, with peaks of 114 % and 14 %, respectively, reached in the pre-dzud year 2008 (Appendix).…”

“…While the topographic conditions of the Altay-Dzungarian region are similar on both sides of the Mountain range, the social and economic context of Chinese and Mongolian pastoralists could hardly be more different. This reflects the different historicalcultural background as well as the significant political and economic transformation processes of the last decades, which severely challenge the transhumance system in both countries (Angerer et al 2008;Liu et al 2013;Hilker et al 2014;Liao et al 2014b;Martin et al 2014).…”

“…Recent rangeland studies in both countries mainly focused on different interacting drivers of declining herbage yields and herbage quality such as increasing livestock numbers, changes in livestock species, reduction of livestock mobility, reduction of affordable and good quality winter fodder, privatization of rangeland, alteration of traditional rangeland management, rural labour outmigration to cities and changing climate either in China or in Mongolia (Glindemann et al 2009;Kakinuma et al 2013;Liu et al 2013;Bruegger et al 2014;Hilker et al 2014;Ma et al 2014;Khishigbayar et al 2015). Despite marked differences between China and Mongolia, both countries struggle with designing effective rangeland strategies, policies and programmes that allow to sustain rangeland productivity on the basis of fine-tuned pasture management and planning for disaster mitigation (Addison et al 2012;Sasaki et al 2012;Schönbach et al 2012;Kreutzmann 2013a;Wang et al 2013;Hilker et al 2014;Khishigbayar et al 2015).…”

“…Despite marked differences between China and Mongolia, both countries struggle with designing effective rangeland strategies, policies and programmes that allow to sustain rangeland productivity on the basis of fine-tuned pasture management and planning for disaster mitigation (Addison et al 2012;Sasaki et al 2012;Schönbach et al 2012;Kreutzmann 2013a;Wang et al 2013;Hilker et al 2014;Khishigbayar et al 2015).…”

Object-Based Classification of Grasslands from High Resolution Satellite Image Time Series Using Gaussian Mean Map Kernels

“…Using satellite remote sensing images, grasslands have been much studied at a regional scale with medium spatial resolution sensors (i.e., MODIS, 250 m/pixel [17,18,32]), where the Minimum Mapping Unit (MMU) is at least of hundreds of meters. This scale is suitable for large, extensive, homogeneous and contiguous regions like steppes [33], but not for fragmented landscapes, which are usually found in Europe and in France particularly [34,35].…”