Department of Biology, University of Texas at Arlington, Arlington, TX, USA.
Washington State Department of Ecology, Environmental Assessment Program, Lacey, WA, USA.
Sci Total Environ. 2024 May 20;926:171618. doi: 10.1016/j.scitotenv.2024.171618. Epub 2024 Mar 11.
Influential ecological research in the 1980s, elucidating that local biodiversity (LB) is a function of local ecological factors and the size of the regional species pool (γ-diversity), has prompted numerous investigations on the local and regional origins of LB. These investigations, however, have been mostly limited to single scales and target groups and centered exclusively on γ-diversity. Here we developed a unified framework including scale, environmental factors (heterogeneity and ambient levels), and metacommunity properties (intraspecific spatial aggregation, regional evenness, and γ-diversity) as hierarchical predictors of LB. We tested this framework with variance partitioning and structural equation modeling using subcontinental data on stream diatoms, insects, and fish as well as local physicochemistry, climate, and land use. Pure aggregation + regional evenness outperformed pure γ-diversity in explaining LB across groups. The covariance of the environment with aggregation + regional evenness rather than with γ-diversity generally explained a much greater proportion of the variance in diatom and insect LB, especially at smaller scales. Thus, disregarding aggregation and regional evenness, as commonly done, may lead to gross underestimation of the pure metacommunity effects and the indirect environmental effects on LB. We examined the shape of the local-regional species richness relationship, which has been widely used to infer local vs. regional effects on LB. We showed that this shape has an ecological basis, but its interpretation is not straightforward. Therefore, we advocate that the variance partitioning analysis under the proposed framework is adopted instead. In diatoms, metacommunity properties had the greatest total effects on LB, while in insects and fish, it was the environment, suggesting that larger organisms are more strongly controlled by the environment. Broader use of our framework may lead to novel biogeographical insights into the drivers of LB and improved projections of its trends along current and future environmental gradients.
20 世纪 80 年代具有影响力的生态学研究阐明，本地生物多样性（LB）是本地生态因素和区域物种库（γ-多样性）大小的函数，这促使人们对 LB 的本地和区域起源进行了大量研究。然而，这些研究大多仅限于单一尺度和目标群体，并且完全集中在 γ-多样性上。在这里，我们开发了一个统一的框架，将尺度、环境因素（异质性和环境水平）和集合群落属性（种内空间聚集、区域均匀度和 γ-多样性）作为 LB 的分层预测因子。我们使用亚大陆的溪流硅藻、昆虫和鱼类以及本地物理化学、气候和土地利用数据，通过方差分解和结构方程模型来测试这个框架。纯聚集+区域均匀度在跨组解释 LB 方面优于纯γ-多样性。环境与聚集+区域均匀度的协方差通常比与γ-多样性的协方差更能解释硅藻和昆虫 LB 方差的更大比例，尤其是在较小的尺度上。因此，像通常那样忽略聚集和区域均匀度可能会导致对纯集合群落效应和环境对 LB 的间接影响的严重低估。我们检查了本地-区域物种丰富度关系的形状，该关系已被广泛用于推断 LB 上的本地和区域效应。我们表明，这种形状具有生态基础，但解释并不直接。因此，我们主张采用所提出框架下的方差分解分析。在硅藻中，集合群落属性对 LB 的总效应最大，而在昆虫和鱼类中，是环境，这表明较大的生物体受环境的控制更强。更广泛地使用我们的框架可能会对 LB 的驱动因素产生新的生物地理见解，并改善对其在当前和未来环境梯度下趋势的预测。
