当前位置: X-MOL 学术Methods Ecol. Evol. › 论文详情
Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)
Defining and evaluating predictions of joint species distribution models
Methods in Ecology and Evolution ( IF 6.6 ) Pub Date : 2020-10-28 , DOI: 10.1111/2041-210x.13518
David P. Wilkinson 1 , Nick Golding 1, 2, 3 , Gurutzeta Guillera‐Arroita 1 , Reid Tingley 4 , Michael A. McCarthy 1
Affiliation  

  1. Joint species distribution models (JSDMs) simultaneously model the distributions of multiple species, while accounting for residual co‐occurrence patterns. Despite increasing adoption of JSDMs in the literature, the question of how to define and evaluate JSDM predictions has only begun to be explored.
  2. We define four different JSDM prediction types that correspond to different aspects of species distribution and community assemblage processes. Marginal predictions are environment‐only predictions akin to predictions from single‐species models; joint predictions simultaneously predict entire community assemblages; and conditional marginal and conditional joint predictions are made at the species or assemblage level, conditional on the known occurrence state of one or more species at a site. We define five different classes of metrics that can be used to evaluate these types of predictions: threshold‐dependent, threshold‐independent, community dissimilarity, species richness and likelihood metrics.
  3. We illustrate different prediction types and evaluation metrics using a case study in which we fit a JSDM to a frog occurrence dataset collected in Melbourne, Australia.
  4. Joint species distribution models present opportunities to investigate the facets of species distribution and community assemblage processes that are not possible to explore with single‐species models. We show that there are a variety of different metrics available to evaluate JSDM predictions, and that choice of prediction type and evaluation metric should closely match the questions being investigated.


中文翻译:

定义和评估联合物种分布模型的预测

  1. 联合物种分布模型(JSDM)同时为多种物种的分布建模,同时考虑了残留的共现模式。尽管文献中越来越多地采用JSDM,但是如何定义和评估JSDM预测的问题才刚刚开始探讨。
  2. 我们定义了四种不同的JSDM预测类型,它们分别对应于物种分布和社区聚集过程的不同方面。边际预测是仅针对环境的预测,类似于单物种模型的预测。联合预测同时预测整个社区的聚集;并在物种或集合水平进行条件边际条件联合预测,条件是某个地点的一个或多个物种的已知发生状态。我们定义了五类不同的度量标准,可用于评估这些类型的预测:阈值依赖性,阈值无关性,群落差异性,物种丰富度和似然性度量。
  3. 我们使用案例研究说明了不同的预测类型和评估指标,在案例研究中,我们将JSDM拟合到在澳大利亚墨尔本收集的青蛙发生数据集。
  4. 联合物种分布模型为调查物种分布和社区集合过程的各个方面提供了机会,而单物种模型则无法探索这些方面。我们表明,有多种不同的指标可用于评估JSDM预测,并且预测类型和评估指标的选择应与正在调查的问题紧密匹配。
更新日期:2020-10-28
down
wechat
bug