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首页> 外文期刊>Journal of Biogeography >Do community-level models describe community variation effectively?
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Do community-level models describe community variation effectively?

机译：社区级模型是否有效地描述了社区差异？

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Aim The aim of community-level modelling is to improve the performance of species distributional models by taking patterns of co-occurrence among species into account. Here, we test this expectation by examining how well three community-level modelling strategies ('assemble first, predict later', 'predict first, assemble later', and 'assemble and predict together') spatially project the observed composition of species assemblages.Location Europe.Methods Variation in the composition of European tree assemblages and its spatial and environmental correlates were examined with cluster analysis and constrained analysis of principal coordinates. Results were used to benchmark spatial projections from three community-based strategies: (1) assemble first, predict later (cluster analysis first, then generalized linear models, GLMs); (2) predict first, assemble later (GLMs first, then cluster analysis); and (3) assemble and predict together (constrained quadratic ordination).Results None of the community-level modelling strategies was able to accurately model the observed distribution of tree assemblages in Europe. Uncertainty was particularly high in southern Europe, where modelled assemblages were markedly different from observed ones. Assembling first and predicting later led to distribution models with the simultaneous occurrence of several types of assemblages in southern Europe that do not co-occur, and the remaining strategies yielded models with the presence of non-analogue assemblages that presently do not exist and that are much more strongly correlated with environmental gradients than with the real assemblages.Main conclusions Community-level models were unable to characterize the distribution of European tree assemblages effectively. Models accounting for co-occurrence patterns along environmental gradients did not outperform methods that assume individual responses of species to climate. Unrealistic assemblages were generated because of the models' inability to capture fundamental processes causing patterns of covariation among species. The usefulness of these forms of community-based models thus remains uncertain and further research is required to demonstrate their utility.
机译：目的社区级建模的目的是通过考虑物种间共现的模式来提高物种分布模型的性能。在这里，我们通过检查三种社区级别的建模策略（“先组装，后预测”，“先预测，后组装”以及“先组装后预测”）在空间上对所观察到的物种集合组成的预测程度，来检验这种期望。定位欧洲。方法通过聚类分析和主坐标约束分析，研究欧洲树木组合的组成及其空间和环境相关性的变化。结果被用于从三种基于社区的策略中对空间投影进行基准测试：（1）首先进行组装，然后进行预测（首先进行集群分析，然后进行广义线性模型GLM）; （2）先进行预测，再进行组装（先进行GLM，然后进行聚类分析）;结果（3）组合和预测（约束的二次排序）。结果在欧洲，没有一种社区级建模策略能够准确地对观察到的树木组合分布进行建模。在欧洲南部，不确定性特别高，那里的组合模型与观察到的组合明显不同。首先进行组装，然后进行预测，导致分布模型同时在欧洲南部同时出现，但并没有同时出现，而其余的策略则产生了具有非类似组合的模型，这些模型目前不存在，并且存在主要结论与社区梯度模型相比，与环境梯度之间的相关性要强得多。主要结论社区一级的模型无法有效地描述欧洲树木组合的分布。解释沿环境梯度共现模式的模型并没有超过假设物种对气候的个体反应的方法。由于模型无法捕获导致物种间协变模式的基本过程，因此产生了不切实际的组合。因此，这些形式的基于社区的模型的有用性仍不确定，因此需要进一步研究以证明其实用性。

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