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首页> 外文期刊>ICES Journal of Marine Science >Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales
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Predictions for an invaded world: a strategy to predict the distribution of native and non-indigenous species at multiple scales

机译：对入侵世界的预测：一种以多种尺度预测本地和非本地物种分布的策略

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摘要

Habitat models can be used to predict the distributions of marine and estuarine non-indigenous species (NIS) over several spatial scales. At an estuary scale, our goal is to predict the estuaries most likely to be invaded, but at a habitat scale, the goal is to predict the specific locations within an estuary that are most vulnerable to invasion. As an initial step in evaluating several habitat models, model performance for a suite of benthic species with reasonably well-known distributions on the Pacific coast of the US needs to be compared. We discuss the utility of non-parametric multiplicative regression (NPMR) for predicting habitat- and estuary-scale distributions of native and NIS. NPMR incorporates interactions among variables, allows qualitative and categorical variables, and utilizes data on absence as well as presence. Preliminary results indicate that NPMR generally performs well at both spatial scales and that distributions of NIS are predicted as well as those of native species. For most species, latitude was the single best predictor, although similar model performance could be obtained at both spatial scales with combinations of other habitat variables. Errors of commission were more frequent at a habitat scale, with omission and commission errors approximately equal at an estuary scale.
机译：栖息地模型可用于预测海洋和河口非本地物种（NIS）在几个空间尺度上的分布。在河口尺度上，我们的目标是预测最有可能入侵的河口，但在栖息地尺度上，目标是预测在河口内最容易受到入侵的特定位置。作为评估几种栖息地模型的第一步，需要比较一套在美国太平洋海岸具有相当知名的底栖物种的模型性能。我们讨论了非参数乘法回归（NPMR）的功能，可用于预测自然和NIS的栖息地和河口规模分布。 NPMR包含变量之间的交互作用，允许定性和分类变量，并利用缺少和存在的数据。初步结果表明，NPMR通常在两个空间尺度上都表现良好，并且可以预测NIS的分布以及本地物种的分布。对于大多数物种而言，纬度是唯一的最佳预测因子，尽管在两个空间尺度上都可以通过结合其他栖息地变量获得相似的模型性能。在栖息地规模上，佣金错误更为常见，在河口规模上，遗漏和佣金错误大致相等。

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