Search
The main aim of this study was to identify saiga distribution in Kalmykia during winter and spring, based on data from a participatory monitoring programme. Models were produced to identify the drivers of distribution and predict likely areas of saiga occupancy.
The data collated from participatory monitoring is evaluated and
analysed alongside data from wildlife rangers in the region and an
annual aerial survey using a maximum entropy habitat suitability
modelling approach. Improvements to the monitoring techniques
covered are discussed. Participatory monitoring is found to be an
effective tool for monitoring the saiga antelope.
The presence data collated from the participatory monitoring is evaluated and analysed alongside presence data from wildlife rangers in the region and an annual aerial survey using maximum entropy habitat suitability modelling approach.
The participatory monitoring data performs well with an improved model fit than the ranger data and of similar fit to the aerial survey data. Additionally the deterministic value of the environmental variables impacting saiga habitat selection, are analysed. The normalized difference vegetation index (NDVI) is shown to have the greatest effect on saiga habitat selection. Human factors and distance to water are also demonstrated to have deterministic value.…
Анализ изменения растительности показал, что на пастбищах
существенно возросла доля злаков, уменьшилось участие разнотравья,
что отрицательно отразилось на питании и состоянии сайгаков.
Установлено, что современные степные пастбища с господством злаков
мало или совсем не пригодны для устойчивого существования популяции
сайгаков.