Aim Long-distance migrations of terrestrial animals, driven by needs such as food, water and escaping predators and harsh climatic conditions, are widely known phenomena. The saiga antelope (Saiga tatarica tatarica) migrates over long distances in the semi-arid rangelands of Central Asia. Both the saiga’s range and its populations have been severely affected by socio-political and land use changes over the last century, related to the formation and dissolution of the Soviet Union. We identified ecological drivers of saiga migration, compared four populations in terms of differences in the geographical characteristics of their ranges and the factors affecting habitat selection within the seasonal ranges.
Location Kazakhstan and pre-Caspian Russia.
Methods Using 40 years of direct observations, we tested for differences between the four saiga populations’ ranges in terms of precipitation, seasonal productivity and topographical variables using discriminant analyses. We tested hypotheses concerning the drivers of migration to their seasonal ranges and assessed the impact of peak and average values and the predictability of drivers of habitat use within the seasonal ranges using logistic regressions.
Results Three of the four populations migrate in a similar way, following a latitudinal gradient driven by seasonal changes in productivity, which is closely related to broad-scale differences in precipitation. Intermediate productivity and its low interannual variability determine habitat selection within the seasonal ranges of all the populations.
Main conclusions Migration of all four populations is driven by productivity and precipitation. The migrations in Kazakhstan are still intact despite major recent disruption to the populations, whereas their status in the pre-Caspian region is unknown. All four populations are under severe threat from habitat loss, poaching, lack of protection and gaps in ecological knowledge. A better understanding of the drivers of saiga migration at multiple scales is a key step towards addressing these threats.
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