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通过区域模型可转移性和数据效率改进加拿大猞猁分布预测。

Improved prediction of Canada lynx distribution through regional model transferability and data efficiency.

作者信息

Olson Lucretia E, Bjornlie Nichole, Hanvey Gary, Holbrook Joseph D, Ivan Jacob S, Jackson Scott, Kertson Brian, King Travis, Lucid Michael, Murray Dennis, Naney Robert, Rohrer John, Scully Arthur, Thornton Daniel, Walker Zachary, Squires John R

机构信息

Rocky Mountain Research Station United States Forest Service Missoula MT USA.

Wyoming Game and Fish Department Lander WY USA.

出版信息

Ecol Evol. 2021 Jan 24;11(4):1667-1690. doi: 10.1002/ece3.7157. eCollection 2021 Feb.

Abstract

The application of species distribution models (SDMs) to areas outside of where a model was created allows informed decisions across large spatial scales, yet transferability remains a challenge in ecological modeling. We examined how regional variation in animal-environment relationships influenced model transferability for Canada lynx (), with an additional conservation aim of modeling lynx habitat across the northwestern United States. Simultaneously, we explored the effect of sample size from GPS data on SDM model performance and transferability. We used data from three geographically distinct Canada lynx populations in Washington ( = 17 individuals), Montana ( = 66), and Wyoming ( = 10) from 1996 to 2015. We assessed regional variation in lynx-environment relationships between these three populations using principal components analysis (PCA). We used ensemble modeling to develop SDMs for each population and all populations combined and assessed model prediction and transferability for each model scenario using withheld data and an extensive independent dataset ( = 650). Finally, we examined GPS data efficiency by testing models created with sample sizes of 5%-100% of the original datasets. PCA results indicated some differences in environmental characteristics between populations; models created from individual populations showed differential transferability based on the populations' similarity in PCA space. Despite population differences, a single model created from all populations performed as well, or better, than each individual population. Model performance was mostly insensitive to GPS sample size, with a plateau in predictive ability reached at ~30% of the total GPS dataset when initial sample size was large. Based on these results, we generated well-validated spatial predictions of Canada lynx distribution across a large portion of the species' southern range, with precipitation and temperature the primary environmental predictors in the model. We also demonstrated substantial redundancy in our large GPS dataset, with predictive performance insensitive to sample sizes above 30% of the original.

摘要

将物种分布模型(SDMs)应用于模型创建区域之外的地区,有助于在大空间尺度上做出明智决策,但在生态建模中,模型的可转移性仍是一项挑战。我们研究了动物与环境关系的区域差异如何影响加拿大猞猁(Lynx canadensis)模型的可转移性,另外还有一个保护目标是对美国西北部的猞猁栖息地进行建模。同时,我们探讨了来自GPS数据的样本量对SDM模型性能和可转移性的影响。我们使用了1996年至2015年来自华盛顿(n = 17只个体)、蒙大拿(n = 66)和怀俄明(n = 10)三个地理上不同的加拿大猞猁种群的数据。我们使用主成分分析(PCA)评估了这三个种群之间猞猁与环境关系的区域差异。我们使用集成建模为每个种群以及所有种群组合开发了SDM,并使用预留数据和一个广泛的独立数据集(n = 650)评估了每个模型情景的模型预测和可转移性。最后,我们通过测试使用原始数据集5% - 100%的样本量创建的模型来检验GPS数据效率。PCA结果表明种群之间在环境特征上存在一些差异;从单个种群创建的模型根据种群在PCA空间中的相似性表现出不同的可转移性。尽管种群存在差异,但从所有种群创建的单个模型表现与每个单个种群相同或更好。模型性能大多对GPS样本量不敏感,当初始样本量较大时,在约占GPS数据集总量30%时预测能力达到平稳状态。基于这些结果,我们生成了经过充分验证的加拿大猞猁在该物种南部大部分分布区域的空间预测,模型中降水和温度是主要的环境预测因子。我们还证明了我们的大型GPS数据集中存在大量冗余,当样本量超过原始量的30%时,预测性能对样本量不敏感。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/739c/7882975/847ffcf0ef5e/ECE3-11-1667-g001.jpg

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