We investigated application of MaxEnt, a one-class classifier, in mapping the spatial distribution of Colophospermum mopane, Dichrostachys cinerea and Salvadora persica using drainage, elevation, slope, soil and Normalised Difference Vegetation Index as environmental variables. Model performance was evaluated based on the area under the ROC curve (AUC), Kappa and Total Skills Statistic. The AUC results demonstrated the high predictive power of MaxEnt as test data values of all species, respectively, were 0.694, 0.754 and 0.998 (p < 0.05). Elevation contributed the most in explaining spatial distributions of all species. Results also indicated that several one-class species maps can be integrated into one species distribution map. We showed that C. mopane is likely to co-occur with D. cinerea and S. persica, whereas S. persica is likely to co-occur with D. cinerea. However, there was no habitat suitable for co-occurrence of all species. One-class species mapping can therefore be successful in heterogeneous agricultural landscapes.

中文翻译：

---

在异构农业景观中映射关键浏览资源

我们研究了 MaxEnt（一种单级分类器）在使用排水、海拔、坡度、土壤和归一化差异植被指数作为环境变量绘制 Colophospermum mopane、Dichrostachys cinerea 和 Salvadora persica 的空间分布中的应用。根据 ROC 曲线下面积 (AUC)、Kappa 和总技能统计量评估模型性能。AUC 结果表明 MaxEnt 具有很高的预测能力，因为所有物种的测试数据值分别为 0.694、0.754 和 0.998（p < 0.05）。海拔在解释所有物种的空间分布方面贡献最大。结果还表明，可以将多个一类物种图整合为一个物种分布图。我们发现 C. mopane 可能与 D. cinerea 和 S. persica 共存，而 S. persica 很可能与 D. cinerea 共同发生。然而，没有适合所有物种共生的栖息地。因此，一类物种制图可以在异质农业景观中取得成功。