Data from: Development and field validation of a regional, management-scale habitat model: a koala Phascolarctos cinereus case study

Species distribution models have great potential to efficiently guide management for threatened species, especially for those that are rare or cryptic. We used MaxEnt to develop a regional-scale model for the koala Phascolarctos cinereus at a resolution (250 m) that could be used to guide management. To ensure the model was fit for purpose, we placed emphasis on validating the model using independently-collected field data. We reduced substantial spatial clustering of records in coastal urban areas using a 2-km spatial filter and by modeling separately two subregions separated by the 500-m elevational contour. A bias file was prepared that accounted for variable survey effort. Frequency of wildfire, soil type, floristics and elevation had the highest relative contribution to the model, while a number of other variables made minor contributions. The model was effective in discriminating different habitat suitability classes when compared with koala records not used in modeling. We validated the MaxEnt model at 65 ground-truth sites using independent data on koala occupancy (acoustic sampling) and habitat quality (browse tree availability). Koala bellows (n = 276) were analyzed in an occupancy modeling framework, while site habitat quality was indexed based on browse trees. Field validation demonstrated a linear increase in koala occupancy with higher modeled habitat suitability at ground-truth sites. Similarly, a site habitat quality index at ground-truth sites was correlated positively with modeled habitat suitability. The MaxEnt model provided a better fit to estimated koala occupancy than the site-based habitat quality index, probably because many variables were considered simultaneously by the model rather than just browse species. The positive relationship of the model with both site occupancy and habitat quality indicates that the model is fit for application at relevant management scales. Field-validated models of similar resolution would assist in guiding management of conservation-dependent species.物种分布模型（Species Distribution Models）在高效指导受威胁物种的管理工作中具备巨大潜力，尤其适用于稀有或隐秘的受威胁物种。本研究采用最大熵模型（MaxEnt），以250米的空间分辨率构建了针对考拉（*Phascolarctos cinereus*）的区域尺度模型，可用于指导相关管理实践。为确保模型满足应用需求，我们重点采用独立采集的野外数据对模型进行验证。为消除沿海城市区域内记录的显著空间聚类问题，我们通过2千米空间过滤，并以500米海拔等高线为界将研究区划分为两个子区域分别开展建模。我们制备了可反映可变调查强度的偏差文件（bias file）。野火发生频率、土壤类型、植物区系组成与海拔对模型的相对贡献最高，其余诸多变量的贡献则相对较小。相较于建模过程中未纳入的考拉观测记录，该模型可有效区分不同的生境适宜性等级。我们基于65个实地验证样点（ground-truth sites）的独立数据对最大熵模型进行验证：数据涵盖考拉生境占用情况（通过声学采样（acoustic sampling）获取）与生境质量（基于可食用树叶的树木可得性评估）。我们在占用模型框架内分析了276次考拉鸣叫声记录，同时基于可食用树种对样地生境质量进行指数化赋值。野外验证结果显示，实地验证样点的考拉生境占用率随模拟生境适宜性提升呈线性增长趋势。类似地，实地验证样点的生境质量指数与模拟生境适宜性呈显著正相关。相较于基于样地的生境质量指数，最大熵模型对考拉生境占用率的拟合效果更优，这可能是因为该模型同时考量了多个变量，而非仅聚焦于可食用树种。该模型与样地生境占用率及生境质量均呈正相关关系，表明其适用于相应管理尺度下的应用。具备相似分辨率的野外验证模型，将有助于指导依赖保护物种的管理工作。