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首页> 外文期刊>Marine ecology progress series >Estimating circumpolar distributions of lanternfish using 2D and 3D ecological niche models
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Estimating circumpolar distributions of lanternfish using 2D and 3D ecological niche models

机译：使用2D和3D生态利基模型估算灯笼的Circumpolar分布

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Ecological niche models (ENMs) can be a practical approach for investigating distributions and habitat characteristics of pelagic species. In principle, to reflect the ecological niche of a species well, ENMs should incorporate environmental predictors that consider its full vertical habitat, yet examples of such models are rare. Here we present the first application of '3D' ENMs to 10 Southern Ocean lanternfish species. This 3D approach incorporates depth-specific environmental predictor data to identify the distribution of suitable habitat across multiple depth levels. Results were compared to those from the more common '2D' approach, which uses only environmental data from the sea surface. Measures of model discriminatory ability and overfitting indicated that 2D models often outperform 3D methods, even when accounting for reduced available sample size in the 3D models. Nevertheless, models for species with a known affinity for deeper habitat benefitted from the 3D approach, and our results suggest that species can track their ecological niche in latitude and depth leading to equatorward or poleward range extensions beyond that expected from incorporating only surface data. However, since 3D models require comprehensive depth-specific data, both data availability and the need for depth-specific model outputs must be considered when choosing the appropriate modelling approach. We advocate increased effort to include depth-resolved environmental parameters within marine ENMs. This will require collection of mesopelagic species occurrence data using appropriate temporal and depth-stratified methods, and inclusion of accurate depth information when occurrence records are submitted to global biodiversity databases.
机译：生态利基模型（ENMS）可以是调查皮埃古物种分布和栖息地特征的实用方法。原则上，为了反映物种的生态利基，恩姆姆应包含考虑其全垂直栖息地的环境预测因子，但这种模型的例子很少见。在这里，我们将“3D”enmms的第一次应用于10个南海灯笼类。该3D方法包括深度特定的环境预测数据，以识别跨多个深度水平的合适栖息地的分布。将结果与来自较常见的'2D'方法的结果进行比较，其仅使用来自海面的环境数据。模型歧视能力和过度措施的测量表明，2D模型往往优于3D方法，即使在3D模型中的可用样本量降低时也是如此。尽管如此，具有已知亲和力的物种的模型与3D方法有益于更深的栖息地，我们的结果表明，物种可以在纬度和深度中跟踪其生态利基，导致超出额定或极端的范围扩展，这些延伸范围仅包括所需的表面数据。然而，由于3D模型需要全面的深度特定数据，因此在选择适当的建模方法时，必须考虑数据可用性和对深度特定模型输出的需求。我们提倡增加努力，包括在海洋脑内的深度解决环境参数。这将需要使用适当的时间和深度分层方法集合中断物种的数据，并且当发生记录提交给全球生物多样性数据库时，将准确的深度信息包含在一起。

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