Species distribution models (SDMs) are increasingly used in conservation and land-use planning as inputs to describe biodiversity patterns. These models can be built in different ways, and decisions about data preparation, selection of predictor variables, model fitting, and evaluation all alter the resulting predictions. Commonly, the true distribution of species is unknown and independent data to verify which SDM variant to choose are lacking. Such model uncertainty is of concern to planners. We analyzed how 11 routine decisions about model complexity, predictors, bias treatment, and setting thresholds for predicted values altered conservation priority patterns across 25 species. Models were created with MaxEnt and run through Zonation to determine the priority rank of sites. Although all SDM variants performed well (area under the curve >0.7), they produced spatially different predictions for species and different conservation priority solutions. Priorities were most strongly altered by decisions to not address bias or to apply binary thresholds to predicted values; on average 40% and 35%, respectively, of all grid cells received an opposite priority ranking. Forcing high model complexity altered conservation solutions less than forcing simplicity (14% and 24% of cells with opposite rank values, respectively). Use of fewer species records to build models or choosing alternative bias treatments had intermediate effects (25% and 23%, respectively). Depending on modeling choices, priority areas overlapped as little as 10–20% with the baseline solution, affecting top and bottom priorities differently. Our results demonstrate the extent of model-based uncertainty and quantify the relative impacts of SDM building decisions. When it is uncertain what the best SDM approach and conservation plan is, solving uncertainty or considering alterative options is most important for those decisions that change plans the most.

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关于拟合物种分布模型的决定如何影响保护结果

物种分布模型 (SDM) 越来越多地用于保护和土地利用规划，作为描述生物多样性模式的输入。这些模型可以以不同的方式构建，关于数据准备、预测变量选择、模型拟合和评估的决策都会改变结果预测。通常，物种的真实分布是未知的，并且缺乏用于验证选择哪个 SDM 变体的独立数据。这种模型的不确定性是规划者所关心的。我们分析了 11 个关于模型复杂性、预测因子、偏差处理和设置预测值阈值的常规决策如何改变 25 个物种的保护优先模式。模型是用 MaxEnt 创建的，并通过 Zonation 运行以确定站点的优先级。尽管所有 SDM 变体都表现良好（曲线下面积 > 0. 7），他们对物种和不同的保护优先解决方案产生了空间上不同的预测。决定不解决偏见或对预测值应用二元阈值的决定最强烈地改变了优先级；平均而言，所有网格单元中分别有 40% 和 35% 获得了相反的优先级排名。强制高模型复杂性改变的保护解决方案少于强制简单性（分别为 14% 和 24% 的具有相反秩值的单元格）。使用较少的物种记录来构建模型或选择替代偏差处理具有中间效果（分别为 25% 和 23%）。根据建模选择，优先领域与基线解决方案的重叠率低至 10-20%，对最高优先级和最低优先级的影响不同。我们的结果证明了基于模型的不确定性的程度，并量化了 SDM 建筑决策的相对影响。当不确定最佳 SDM 方法和保护计划是什么时，解决不确定性或考虑替代选项对于那些最能改变计划的决策来说是最重要的。