Modeling the Spatial Distribution of Plateau Pika (Ochotona curzoniae) in the Qinghai Lake Basin, China.

Abstract

Simple SummaryThe plateau pika (Ochotona curzoniae) is a keystone species on the Qinghai–Tibetan Plateau (QTP). We identified key factors affecting its distribution and predicted it in Qinghai Lake basin by the maximum entropy (Maxent) model at 1-km spatial resolution. Our results showed that the suitable area for plateau pika in Qinghai Lake basin is approximately 3982 km2, which occupies 15.8% of the land area in the whole watershed. The distance to road emerged as the most important predictor of distribution patterns of plateau pika, while the soil type was of ancillary importance. With the constraint of human factors, the presence probability of plateau pika in about 1661 km2 will increase. These findings indicate that human factors have significant importance for plateau pika’s distribution, and provide evidence to guide plateau pika control in this and other similar regions. The plateau pika (Ochotona curzoniae) is a keystone species in the alpine rangeland ecosystem of the Qinghai–Tibetan Plateau. Most previous studies of habitat selection by plateau pika have been conducted at a local microhabitat scale; however, little is known about the relationship between the distribution of plateau pika and macrohabitat factors at broad spatial scales. Using a presence-only ecological niche model (maximum entropy, Maxent), we predicted the distribution of plateau pika in the Qinghai Lake basin based on a set of environmental and anthropogenic variables at 1-km spatial resolution, and identified key macrohabitat factors that contribute to the predictive performance. Our results showed suitable area for plateau pika in the Qinghai Lake basin being approximately 3982 km2, which is 15.8% of the land area in the whole watershed. The distance to road emerged as the most important predictor of the distribution patterns of plateau pika, while the soil type was of ancillary importance. Mean air temperature of wettest quarter, distance to resident site and altitude also produced high gains in defining plateau pika’s distribution. A higher predictive accuracy was achieved by the model that combined environmental and anthropogenic variables. With the constraint of human factors, the presence probability of plateau pika in about 1661 km2 will increase. These findings demonstrate the impact of human activities on the distribution of plateau pika, and the importance of vegetation reservation for plateau pika control.