Population estimates of Endangered Mongolian saiga Saiga tatarica mongolica: implications for effective monitoring and population recovery
Julie K. Young1, Kim M. Murray1, Samantha Strindberg2, Bayarbaatar Buuveibaatar3, Joel Berger1
1Wildlife Conservation Society, Northern Rockies Field Office, University of Montana, Missoula, Montana, USA. E-mail email@example.com
2Wildlife Conservation Society, Bronx, New York, USA.
3Institute of Biology, Mongolian Academy of Sciences, Ulaanbaatar, Mongolia.
The global population of saiga Saiga tatarica, categorized as Critically Endangered on the IUCN Red List, declined by .95% at the end of the 20th century, resulting in several conservation initiatives to protect the species. Previously used methods to monitor population trends were inadequate to properly assess numbers of saiga. We report findings from the first survey for Mongolian saiga S. tatarica mongolica to utilize statistically rigorous methodology, using line transect distance sampling in 2006 and 2007 to obtain population estimates in and around the Sharga Nature Reserve, the southern part of the species current range. We estimate a density of 0.54 and 0.78 saiga km-2 in 2006 and 2007, respectively. Our best models suggest that 4,938 (95% confidence interval, CI52,762–8,828) saiga occupied the 4,524- km2 study area in 2006 and 7,221 (95%CI54,380–11,903) the 4,678-km2 study area in 2007. Although these estimates, with their large confidence intervals, preclude an assessment of the impacts of conservation initiatives on population trends, they suggest that the Mongolian saiga population is larger than previous reports based on minimum counts, and adequate to support in situ population recovery. Modifications to the survey protocol hold promise for improving the precision of future estimates. Distance sampling may be a useful, scientifically defensible method for monitoring saiga population trends and assessing the effectiveness of conservation efforts to stabilize and recover populations.
Keyword: Antelope,distance sampling,endangered species,line transects,Mongolia,population estimate,Saiga tatarica
Estimates of population size are vital for understanding species ecology, providing information on fluctuations in size and enabling monitoring of population trends. For threatened species population estimates are crucial for developing conservation strategies and assessing their effectiveness but obtaining estimates of species that occur at low numbers and inhabit large geographical areas is logistically difficult. Consequently, information on population size is often lacking for such species.
Saiga Saiga tatarica is a nomadic, sexually dimorphic species that was formerly widespread across the Central Asian steppe (Bekenov et al., 1998; Schaller, 1998). S. tatarica tatarica occurs in Kazakhstan, Russia, Uzbekistan and Turkmenistan, and Mongolian saiga S. tatarica mongolica, categorized as Endangered on the IUCN Red List (Mallon, 2008), is now only found in Mongolia. The Mongolian subspecies is ecologically, phenotypically and behaviourally distinct (Bannikov et al., 1961; Kholodova et al., 2001). Because of overharvesting, saiga suffered a global population decline of c. 95% in ,15 years (Milner-Gulland et al., 2001). This severe decline led to the signing of a Memorandum of Understanding (MOU) among range states, under the Convention of Migratory Species (CMS, 2006), which established the need to adopt a standardized monitoring protocol to regularly assess population numbers. The MOU emphasized the need to evaluate the impact of natural and human-induced threats on saiga populations. Although the Mongolian saiga is not officially included in the MOU, the decline and resulting CMS raised awareness of the paucity of information on the population status and distribution of this subspecies (Lushchekina et al., 1999). Varied but consistent counts suggest that ,5,000 Mongolian saiga remain in the wild (Clark & Javzansuren, 2006; Chimeddorj et al., 2009).
Methods used previously for estimating population sizes of Mongolian saiga provided only a measure of relative abundance, with no corresponding measure of uncertainty, precluding statistical comparisons (Chimeddorj et al., 2009). An absolute estimate of abundance, and its associated estimate of variance, is required to properly assess and monitor population size. Methods should be accurate, repeatable and statistically rigorous. We therefore used distance sampling (Buckland et al., 2001) because it is a well-developed methodology that has been successfully applied to many ungulate species (Biswas & Sankar, 2002; Koenen et al., 2002; Seddon et al., 2003; Whittaker et al., 2003; Focardi et al., 2005). Distance sampling methods are flexible and efficient for sampling sparse populations distributed over large regions (Olson et al., 2005), factors important for adoption of a technique to estimate population size throughout saiga range states.
In line-transect distance sampling observers traverse a series of transects and record perpendicular distance to detected groups. The group is used as the unit of observation when there is dependence among individuals in species that aggregate, and group size is recorded. Radial distance and angle are measured to calculate the perpendicular distance between the transect line and centre of the group. The probability of detecting a group is modelled as a function of the observed perpendicular distances and then combined with the estimated group encounter rate and estimated expected group size to calculate the density of individuals in the study area; abundance is also calculated if the total area of the study region is known (Buckland et al., 2001). Estimating the probability of detecting a group corrects for the number of animals undetected and provides absolute density and abundance estimates. Estimates are considered valid if four assumptions are met: (1) all individuals or groups on the transect line are detected with certainty, (2) animals are detected at their original location, (3) measurements are exact, and (4) transects are randomly placed with respect to animal or group distribution (Buckland et al., 2001).
We report population estimates of Mongolian saiga based on 2 years of distance sampling surveys, and discuss implications for in situ recovery of Mongolian saiga. We discuss the challenges in meeting the first two assumptions for estimating population density of saiga and suggest modifications to survey methodology that could improve the precision of estimates, making the technique suitable for range-wide adoption as a standardized monitoring protocol.
The study was conducted in and around the Sharga Nature Reserve (Gobi-Altai Aimag) in western Mongolia (Fig. 1). Clark & Javzansuren (2006) suggest that c. 90% of the Mongolian saiga population occurs within or near the Reserve. Our study area included c. 35% of the current range of Mongolian saiga (L. Amgalan, pers. comm.). Mean total annual precipitation is c. 50mm year-1, with much of it from winter snow. Annual temperatures are -30 to +30C. The area is semi-desert and the predominant vegetation includes Allium, Stipa, Anabasis and Salsola. The only other ungulate to occupy the area is goitered gazelle Gazella subgutturosa. Altitudes are 1,300–2,100 m.
Material and Methods
We established 24 15-km transects (Fig. 1), placed systematically to provide complete coverage of the study area. Although the starting point for the first transect was not selected randomly it was chosen without prior information regarding habitat, terrain, or other ecological characteristics. Cardinal directions for travel were selected so that transects traversed the numerous ravines that extended along the slopes of the valley because saiga often used these ravines as cover from wind and sun when resting during the day. Transects were spaced $5 km apart to avoid double counting, which could occur if saiga were displaced by observers from one transect to the next. Distance sampling was conducted in , 2 weeks in September 2006 and 2007, with 1–5 transects completed each day. Most observers were different between the two surveys. Some transects could not be completed in their entirety because of difficult terrain and mechanical failures of the vehicles. Therefore, the length of transects varied slightly between years and two of the transects were not used in 2006. This resulted in differences in sampling effort and size of the study area between years (Table 1). Transects were driven during daylight hours using a global positioning system for orientation. When saiga were detected group size, radial distance (r) and sighting angle (Ө) were recorded, using a compass, binoculars, spotting scope and rangefinder. Saiga often began to run after we detected them and, in these cases, we used a landscape feature at the point of detection to measure r and h. From these data we calculated perpendicular distance as x 5 r sin (Ө). Density of saiga groups within the area surveyed (Dg) was then estimated as:
We observed 241 saiga in 93 groups in 2006 and 421 saiga in 121 groups in 2007 (Table 1). The survey area (Table 1) was smaller in 2006 because we were unable to complete two transects in that year (Fig. 1). Group sizes were 1–14 and 1–35 in 2006 and 2007, respectively (Table 2). For both years the size bias regression was significant (P , 0.01), and thus the expected group size (Table 2) was used to estimate density. Encounter rate (n/L) was considerably lower in 2006 than in 2007 but with a similar percentage coefficient of variation (Table 3).
Saigas were typically far from observers when first detected (577.7 – SE 28.7 m) but were detected as close as 80 m. Detection and the effective strip width were estimated separately for each year (Table 4) because we had sufficient data per year and suspected that detectability varied between the two years because of difference in the amount of rainfall and resulting greenness of the vegetation: 2006 was dry and the vegetation was brown during the sampling periods, whereas 2007 was wet and green, resulting in a greater contrast between saiga coat colour and vegetation. In addition, although all observers were trained, the use of some different observers between years may have confounded comparisons.
Our population estimates for Mongolian saiga in the Sharga Nature Reserve and surrounding area are considerably larger than previous estimates, based on minimum counts, of the entire Mongolian saiga population (Lushchekina et al., 1999; Amgalan et al., 2008). Our results suggest that, with adequate protection, sufficient numbers exist to facilitate in situ population recovery. To date, the international conservation strategy for saiga has often been based around an apparent need to establish a captive herd and breeding programme. Captive breeding of Mongolian saiga was identified as a priority within the CMS Medium Term Work Programme (CMS, 2006). However, this need was identified based on minimum counts that estimated only c. 1,800 saiga remained in the wild (Amgalan et al., 2008). Our estimates were conducted in the autumn so that saiga would be widely distributed in small groups, to facilitate distance sampling, and at this time the observable population was probably at its highest for the year. Saiga, especially calves, may suffer high levels of mortality during periodically harsh Mongolian winters, known as dzuds (Bekenov et al., 1998). Previous counts were conducted in January (Amgalan et al., 2008), and differences between our results and Amgalan et al. (2008) may reflect overwinter mortality. Yet, no dzuds were reported during the sampling years for either study. Rather, it is likely that previous survey techniques resulted in underestimates of saiga populations. Underestimates of population size based on minimum counts probably resulted from the failure to estimate and correct for detection probability, as well as the exclusion of potentially suitable habitat for saiga from the survey area (e.g. minimum counts excluded canyons, to increase efficiency; Amgalan et al., 2008).
Similarly, line transect estimates of ecologically equivalent North American pronghorn Antilocapra americana that did not account for detectability underestimated population abundance (Pojar & Guenzel, 1999). Although our estimates are substantially larger than minimum counts (Lushchekina et al., 1999; Amgalan et al., 2008), it is unclear whether the Mongolian saiga population is increasing. Saiga move according to vegetation, water and climactic conditions. Because these conditions may vary between years it is possible that the higher density in 2007 was a result of saiga movement into our study area rather than to an actual increase in the population. In addition, two estimates of population size are insufficient to evaluate long-term trends.
Population size is an important predictor of population persistence (Berger, 1990; Shaffer et al., 2000; Reed et al., 2003), although human threats can have profound and unpredictable impacts even on large populations (Ceballos & Ehrlich, 2002; Altizer et al., 2003). For saiga, overharvesting and poaching resulted in their rapid and dramatic population decline (Milner-Gulland et al., 2001). Yet, as with pronghorn in North America (Byers & Moodie, 1990; Byers, 1997), saiga demonstrate great recovery potential because females exhibit high fecundity and regular rates of twinning (KuЁhl et al., 2007). In addition, c. 90% of female saiga may reproduce within their first year (Fadeev & Sludskii, 1982).
We are indebted to L. Amgalan, B. Lkhagvasuren, A. Fine and P. Zahler for assistance with this project. We thank staff at the Institute of Biology of the Mongolian Academy of Sciences and at the Wildlife Conservation Society, Mongolia Country Program Office for their logistical support. D. Chin-Unen and many others assisted with fieldwork and at the camp. H. Weaver and B. Hudgens commented on earlier drafts of this article. The project was funded by a grant from the National Geographic Society.
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