Although the species-urban green area relationship (SARu) has been analyzed worldwide, the global consistency of its parameters, such as the fit and the slope of models, remains unexplored. Moreover, the SARu can be explained by 20 different models. Therefore, our objective was to evaluate which models provide a better explanation of SARus and, focusing on the power model, to evaluate the global heterogeneity in its fit and slope. We tested the performance of multiple statistical models in accounting for the way in which species richness increases with area, and examined whether variability in model form was associated with various methodological and environmental factors. Focusing on the power model, we analyzed the global heterogeneity in the fit and slope of the models through a meta-analysis. Among 20 analyzed models, the linear model provided the best fit to the most datasets, was the top ranked model according to our efficiency criterion, and was the top overall ranked model. The Kobayashi and power models were the second and third overall ranked models, respectively. The number of green areas and the minimum number of species within a green area were the only significant variables explaining the variation in model form and performance, accounting for less than 10% of the variation. Based on the power model, there was a consistent overall fit (r2 = 0.50) and positive slope of 0.20 for the species richness increase with area worldwide. The good fit of the linear model to our SARu datasets contrasts with the non-linear SAR frequently found in true and non-urban habitat island systems; however, this finding may be a result of the small sample size of many SARu datasets. The overall power model slope of 0.20 suggests low levels of isolation among urban green patches, or alternatively that habitat specialist and area sensitive species have already been extirpated from urban green areas.

中文翻译：

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全球城市绿地面积对鸟类丰富度的一致的积极影响

尽管已经在全球范围内分析了物种与城市绿地之间的关系（SARu），但仍未探索其参数（例如模型的拟合度和斜率）的全局一致性。而且，SARu可以用20种不同的模型来解释。因此，我们的目标是评估哪些模型可以更好地解释SARus，并着重于幂模型，评估其拟合度和斜率的整体异质性。我们测试了多种统计模型的性能，以说明物种丰富度随面积增加的方式，并检查模型形式的可变性是否与各种方法和环境因素相关。围绕功效模型，我们通过荟萃分析分析了模型拟合和斜率中的全局异质性。在20种分析模型中，线性模型最适合大多数数据集，根据我们的效率标准是排名最高的模型，也是整体排名最高的模型。小林和功率模型分别是第二和第三名。绿地的数量和绿地内物种的最少数量是解释模型形式和性能变化的唯一重要变量，占不到变化的10％。基于幂模型，物种丰富度随世界范围的增加存在一致的总体拟合（r2 = 0.50）和正斜率为0.20。线性模型与SARu数据集的良好拟合与真实和非城市栖息地岛屿系统中经常发现的非线性SAR形成对比。然而，这一发现可能是许多SARu数据集样本量较小的结果。总体功率模型斜率为0.20，表明城市绿地之间的隔离度较低，或者表示已经从城市绿地中淘汰了栖息地专家和对区域敏感的物种。