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Spatial Patterns in Relative Primary Productivity and Gazelle Migration in the Eastern Steppes of Mongolia

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Spatial Patterns in Relative Primary Productivity and Gazelle Migration in the Eastern Steppes of Mongolia Biological Conservation 102 (2001) 205–212 www.elsevier.com/locate/biocon Spatial patterns in relative primary productivity and gazelle migration in the Eastern Steppes of Mongolia Peter Leimgruber a,*, William J. McShea a, Christopher J. Brookes b, Lhamsuren Bolor-Erdene b, Chris Wemmer a, Chris Larson a aNational Zoological Park, Conservation and Research Center, 1500 Remount Road, Front Royal, VA 22630, USA bEastern Steppes Biodiversity Project, PO Box 350, Choibalsan, Dornod, Mongolia Received 19 May 2000; received in revised form 20 December 2000; accepted 3 January 2001 Abstract The Mongolian gazelle (Procapra gutturosa) of the Eastern Steppes of Mongolia shows seasonal migrations to traditional winter and calving grounds with diffuse movements during the intervening periods. We used a normalized difference vegetation index (NDVI), derived from coarse-resolution satellite imagery, to map relative primary productivity of steppes between April 1992 and December 1995. Productivity peaks were variable between years, but winter and calving grounds had highest NDVI scores during periods of use by gazelles. Gazelle movements to these areas track shifts in primary productivity across the steppe. Diffuse move- ments in summer were not matched to peaks in productivity. Productivity ‘hotspots’ utilized by gazelles during critical periods in their life cycle should be first priority for conservation and the impact of livestock grazing on these areas should be evaluated. # 2001 Elsevier Science Ltd. All rights reserved. Keywords: Mongolian gazelle; Ungulate migration; Primary productivity; Steppe; NDVI 1. Introduction and a short birthing season, usually sometime between mid-June and mid-July (Lushchekina, 1990, in Lhagva- Zeer, as Mongolian gazelles (Procapra gutturosa) are suren and Milner-Gulland, 1997). The onset of the cal- locally known, are the dominant and characteristic fea- ving period is very variable and may depend on climatic ture of one of the last remaining temperate grasslands — conditions during the previous year (Lhagvasuren and the Eastern Steppes of Mongolia. The zeer is especially Milner-Gulland, 1997). During calving periods, groups noted for its annual migrations, during which herds of up to 40,000 females can be observed in areas of ranging in size from 35,000 to 80,000 animals can be about 35 km2, during an approximately 2-week period observed (Lhagvasuren and Milner-Gulland, 1997). (Lushchekina et al., 1985). Up to 90% of the females in Migrations of the gazelles do not follow a clear north/ a group may give birth within a period of 4 days south axis, but rather are characterized by herd move- (Lushchekina, 1990 in Lhagvasuren and Milner-Gul- ments between winter and calving grounds that are land, 1997). scattered throughout the steppes (Lushchekina et al., Aggregations of zeer also occur during the winter 1985; Jiang et al., 1998). (Lhagvasuren and Milner-Gulland, 1997; Wang et al., Zeer have been described as ‘permanent migrants’, 1997; Jiang et al., 1998). These aggregations appear to with only females pausing in their movements during be driven by a search for snow-free areas. The number the brief calving season (Lhagvasuren and Milner-Gul- of congregated animals appears to fluctuate with the land, 1997). Zeer are seasonal breeders with a rutting severity of the winter (Lhagvasuren and Milner-Gul- season that lasts from mid-November to early February land, 1997; Wang et al., 1997). In recent years, there has been increasing concern about declines in geographic range and population * Corresponding author. Tel.: +1-540-635-6578. numbers of zeer (Lhagvasuren and Milner-Gulland, E-mail address: [email protected] (P. Leimgruber). 1997; Reading et al., 1998). Until as recently as the 1950s, 0006-3207/01/$ - see front matter # 2001 Elsevier Science Ltd. All rights reserved. PII: S0006-3207(01)00041-6 206 P. Leimgruber et al. / Biological Conservation 102 (2001) 205–212 zeer were commonly found throughout most of Mon- gazelles assume a severe population decline for the spe- golia and adjacent regions belonging to Kazakhstan, the cies (Lushchenkina et al., 1985; Lushchekina, 1990 in Russian Federation, and China — an area of approxi- Lhagvasuren and Milner-Guland, 1997; Lhagvasuren mately 1.2 million km2 (Fig. 1). Now, the species is and Milner-Gulland, 1997; Reading et al., 1998). restricted to <400,000 km2 — the eastern portion of the The declines in both numbers and range appear to be original range (Fig. 1; Lushchenkina et al., 1985; Lhag- caused by overharvesting, poaching, and the over- vasuren and Milner-Gulland, 1997; Reading et al., 1998). stocking of livestock (Lhagvasuren and Milner-Gul- Zeer population numbers also declined in the last half land, 1997; Jiang et al., 1998; Reading et al., 1998). The of the 20th century. Zeer were abundant throughout selection of optimal protected areas for zeer conserva- the 1940s with a total population size estimated at tion is challenging because of the lack of basic data on 1,000,000 animals (Bannikov, 1954, in Lhagvasuren and habitat needs. However, areas where animals aggregate Milner-Gulland, 1997). By the 1970s, these numbers (i.e. winter and calving grounds) and corridors between had dropped sharply to as few as 170,000–180,000 ani- these areas should be of particular importance to the mals (Lushchekina, 1990, in Lhagvasuren and Milner- species. We hypothesized that zeer migrations are driven Guland, 1997; Tsagaan, 1978, in Lhagvasuren and Mil- by a search for forage and that calving grounds, espe- ner-Guland, 1997). The population recovered somewhat cially, should exhibit an abundance of green grasses to in the 1980s and 1990s, with population estimates support large numbers of female zeer. between 300,000 and 400,000 animals for the 1980s To evaluate our hypothesis, we explored the useful- (Lushchekina et al., 1985) and at least 400,000 animals ness of satellite imagery and Geographic Information in the 1990s (Lhagvasuren and Milner-Gulland, 1997). Systems (GIS) for linking seasonal patterns in primary Based on these estimates the total population has been productivity to migratory patterns in gazelles. If such a reduced by half during only 50 years. system works, identification of important areas for Zeer population estimates are admittedly crude and gazelle conservation in the vast Eastern Steppes could vary widely depending on the source of the estimate. be significantly aided by satellite imagery, remote sen- There is good reason to credit more the lower estimates. sing and GIS technology. For example, current estimates range from 400,000 to Satellite imagery and remote sensing technology 2,000,000 animals (Lhagvasuren and Milner-Gulland, commonly have been used to assess habitat extent and 1997). The larger number would mean the population quality in ungulate studies (e.g. Unsworth et al., 1998; has doubled since the 1940s even as its range collapsed Bowyer et al., 1999; McShea et al., 1999). For rangeland to an area less than 1/3 of its original size. This is very ungulates, aboveground net primary productivity unlikely and most recent publications on Mongolian (ANPP) is strongly correlated with habitat quality Fig. 1. Historic and present geographic distribution of Mongolian gazelles (Procapra gutturosa). P. Leimgruber et al. / Biological Conservation 102 (2001) 205–212 207 (McNaughton, 1985; Frank and McNaughton, 1992; NDVI images for Mongolia are available for the per- McNaughton, 1993). It is possible to use the normalized iod from 1 April, 1992 to 30 September, 1993, and 1 difference vegetation index (NDVI; Lillesand and Kie- February, 1995 to 31 December, 1995. We downloaded fer, 1999) calculated from Advanced Very High Reso- all images and, using visual inspection, chose the best lution Radiometer (AVHRR) satellite imagery as an image for each month for our analyses. Despite the fact index for relative ANPP. The NDVI represents the dif- that using 10-composites of AVHRR imagery for the cal- ference in reflection between the near-infrared and the culation of NDVI significantly reduces cloud contamina- red parts of the electromagnetic spectrum (Eidenshink tion of pixels, we could not find acceptable NDVI and Faundeen, 1994) and works well to measure pro- images with cloud cover <30% for December 1992. ductivity because healthy green vegetation reflects We delineated three types of habitat within the zeer strongly in the near-infrared but absorbs most light in range (i.e. winter, summer, and calving grounds) using a the red. There are good statistical relationships between combination of maps from the literature (Fig. 2; Lush- the NDVI and biomass or ANPP (Cilhar et al., 1991; chenkina et al., 1985; Lhagvasuren and Milner-Gulland, Paruelo and Laurenroth, 1995; Paruelo et al., 1997), 1997) and expert knowledge of staff members of the and NDVI has been used to estimate herbivore stocking Eastern Steppes Biodiversity Project (ESBP) funded by rates for the rangelands of Argentina (Oesterheld et al., the United Nations (UN) Global Environment Facility 1998). We used the NDVI derived from AVHRR data (GEF). Because calving occurs during a very short time to test our hypothesis that zeer migrations are corre- period and at variable dates, and because zeer migrate over lated with shifts in primary productivity. very large areas, it is unlikely that all calving grounds are currently known. However, if our analysis demon- strates a close link between primary productivity, mea- 2. Methods sured by satellite sensors, and known seasonal gazelle movements, the technique could be used in the future to Our study focused on the current range of the predict where unknown calving areas might be located. remaining zeer populations in the Eastern Steppes of All areas known to be used by the gazelles as winter, Mongolia (Lhagvasuren and Milner-Gulland, 1997). summer, and calving grounds were entered into a GIS The NDVI was calculated from AVHRR imagery by by digitizing the outlines on-screen and using data from using channel 1 (visible, VIS) and channel 2 (near- the Digital Charts of the World (DCW; ESRI, 1993) as infrared, NIR) in the equation: a back-drop.
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