Data from: Evaluating citizen vs. professional data for modelling distributions of a rare squirrel

To realize the potential of citizens to contribute to conservation efforts through the acquisition of data for broad-scale species distribution models, scientists need to understand and minimize the influences of commonly observed sample selection bias on model performance. Yet evaluating these data with independent, planned surveys is rare, even though such evaluation is necessary for understanding and applying data to conservation decisions.
We used the state-listed fox squirrel Sciurus niger in Florida, USA, to interpret the performance of models created with opportunistic observations from citizens and professionals by validating models with independent, planned surveys.
Data from both citizens and professionals showed sample selection bias with more observations within 50 m of a road. While these groups showed similar sample selection bias in reference to roads, there were clear differences in the spatial coverage of the groups, with citizens observing fox squirrels more frequently in developed areas.
Based on predictions at planned field surveys sites, models developed from citizens generally performed similarly to those developed with data collected by professionals. Accounting for potential sample selection bias in models, either through the use of covariates or via aggregating data into home range size grids, provided only slight increases in model performance.
Synthesis and applications. Despite sample selection biases, over a broad spatial scale opportunistic citizen data provided reliable predictions and estimates of habitat relationships needed to advance conservation efforts. Our results suggest that the use of professionals may not be needed in volunteer programmes used to determine the distribution of species of conservation interest across broad spatial scales.

为挖掘公民通过采集数据助力大范围物种分布模型构建以参与保护工作的潜力，科研人员需明晰并尽可能削弱常见抽样选择偏差对模型性能的影响。然而，即便此类评估对理解数据并将其应用于保护决策至关重要，采用独立规划调查对这类数据进行验证的研究仍较为罕见。
本研究以美国佛罗里达州的州列保护物种东部狐松鼠（Sciurus niger）为研究对象，通过独立规划调查对模型进行验证，以此解析由公民与专业人员的偶发观测数据构建的物种分布模型性能。
公民与专业人员的观测数据均表现出抽样选择偏差：二者的观测点均更集中于道路50米范围内。尽管两类群体在道路相关的抽样选择偏差特征上表现相似，但二者的空间覆盖范围存在显著差异——公民观测到的东部狐松鼠更多集中于开发区域。
基于规划野外调查点位的预测结果，由公民观测数据构建的模型整体性能与专业人员采集数据构建的模型相当。在模型中校正潜在抽样选择偏差（如通过引入协变量，或按家域尺度网格聚合数据）仅能小幅提升模型性能。
综合与应用：尽管存在抽样选择偏差，但在大空间尺度下，公民偶发观测数据仍可提供可靠的预测结果以及助力推进保护工作所需的栖息地关系评估。本研究结果表明，在用于大空间尺度内确定具有保护价值物种分布的志愿监测项目中，或许无需依赖专业人员采集数据。