Consensus forecasting of species distributions: the effects of niche model performance and niche properties.
Consensus forecasting of species distributions: the effects of niche model performance and niche properties.
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物种分布的共识预测：生态位模型性能和生态位特性的影响。
DOI：
10.1371/journal.pone.0120056
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发表时间：
2015
期刊：
影响因子：
3.7
通讯作者：
Wang L
中科院分区：
文献类型：
--
作者：
Zhang L;Liu S;Sun P;Wang T;Wang G;Zhang X;Wang L
集合预测被认为是减少物种分布模型(SDM)中不确定性的一种方法。这是因为它有望平衡SDM模型的准确性和稳健性。然而，关于由不同共识方法生成的组合分布图的空间相似性的可用数据很少。利用8个生态位模型、9个分裂样本校正回合(或9个随机模型训练子集)和9个气候变化情景，模拟了当前和未来气候条件下中国地区32种森林树种的分布。使用三种简单的共识方法(平均值、频率和中位数[PCA])将预测集合组合在一起，以确定目标物种的最终共识预测图。物种的地理范围因气候变化而改变(面积变化和移动距离)，但三个共识预测在多大程度上或在哪个方向上没有显著差异，但它们确实在三个共识预测的空间相似性方面存在差异。不一致的区域主要在物种范围的边缘观察到。多元逐步回归模型显示，三个因素(生态位的边际性和专门化，以及生态位模型的准确性)与观察到的共识方法之间共识预测图的差异有关。当生态位模型精度较高、边缘和专门化程度较低时，预测地图之间的空间对应程度最高。空间预测的差异表明，在根据地图输出做出关于专业物种的任何决定之前，应更多地关注空间不确定性的范围。利基属性和单模型预测性能提供了有前景的见解，可能会进一步理解SDM中的不确定性。
Ensemble forecasting is advocated as a way of reducing uncertainty in species distribution modeling (SDM). This is because it is expected to balance accuracy and robustness of SDM models. However, there are little available data regarding the spatial similarity of the combined distribution maps generated by different consensus approaches. Here, using eight niche-based models, nine split-sample calibration bouts (or nine random model-training subsets), and nine climate change scenarios, the distributions of 32 forest tree species in China were simulated under current and future climate conditions. The forecasting ensembles were combined to determine final consensual prediction maps for target species using three simple consensus approaches (average, frequency, and median [PCA]). Species’ geographic ranges changed (area change and shifting distance) in response to climate change, but the three consensual projections did not differ significantly with respect to how much or in which direction, but they did differ with respect to the spatial similarity of the three consensual predictions. Incongruent areas were observed primarily at the edges of species’ ranges. Multiple stepwise regression models showed the three factors (niche marginality and specialization, and niche model accuracy) to be related to the observed variations in consensual prediction maps among consensus approaches. Spatial correspondence among prediction maps was the highest when niche model accuracy was high and marginality and specialization were low. The difference in spatial predictions suggested that more attention should be paid to the range of spatial uncertainty before any decisions regarding specialist species can be made based on map outputs. The niche properties and single-model predictive performance provide promising insights that may further understanding of uncertainties in SDM.
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影响因子：
3.1
作者：
Crimmins, Shawn M.;Dobrowski, Solomon Z.;Mynsberge, Alison R.
通讯作者：
Mynsberge, Alison R.
影响因子：
14.4
作者：
Granitto, PM;Verdes, PF;Ceccatto, HA
通讯作者：
Ceccatto, HA
影响因子：
3.7
作者：
Iverson, Louis R.;Prasad, Anantha M.;Peters, Matthew
通讯作者：
Peters, Matthew
影响因子：
5.9
作者：
Grenouillet, Gael;Buisson, Laetitia;Lek, Sovan
通讯作者：
Lek, Sovan
影响因子：
4.8
作者：
Dixon, PM;Ellison, AM;Gotelli, NJ
通讯作者：
Gotelli, NJ