Laboratório de Biogeografia e Ecologia Aquática (Bioecol), Universidade Estadual de Goiás, Anápolis, Goiás, Brazil.
Departamento de Ecologia, Universidade de Brasília, Distrito Federal, Brasília, Brazil.
PLoS One. 2020 May 26;15(5):e0233733. doi: 10.1371/journal.pone.0233733. eCollection 2020.
Understanding how assemblages are structured in space and the factors promoting their distributions is one of the main goals in Ecology, however, studies regarding the distribution of organisms at larger scales remain biased towards terrestrial groups. We attempt to understand if the structure of stream fish metacommunities across a Neotropical ecoregion (Upper Paraná-drainage area of 820,000 km2) are affected by environmental variables, describing natural environmental gradient, anthropogenic impacts and spatial predictors. For this, we obtained 586 sampling points of fish assemblages in the ecoregion and data on environmental and spatial predictors that potentially affect fish assemblages. We calculated the local beta diversity (Local Contribution to Beta Diversity, LCBD) and alpha diversity from the species list, to be used as response variables in the partial regression models, while the anthropogenic impacts, environmental gradient and spatial factors were used as predictors. We found a high total beta diversity for the ecoregion (0.41) where the greatest values for each site sampled were located at the edges of the ecoregion, while richer communities were found more centrally. All sets of predictors explained the LCBD and alpha diversity, but the most important was dispersal variables, followed by the natural environmental gradient and anthropogenic impact. However, we found an increase in the models' prediction power through the shared effect. Results suggest that environmental filters (i.e. environmental variables such as climate, hydrology and anthropogenic impact) and dispersal limitation together shape fish assemblages of the Upper Paraná ecoregion, showing the importance of using multiple sets of predictors to understand the processes structuring biodiversity distribution.
理解组合在空间上的结构以及促进其分布的因素是生态学的主要目标之一,然而,关于较大尺度上生物分布的研究仍然偏向于陆地群体。我们试图了解在一个新热带生态区(上巴拉那流域面积 820,000 平方公里)中,溪流鱼类元群落的结构是否受到环境变量的影响,这些变量描述了自然环境梯度、人为影响和空间预测因子。为此,我们在该生态区获得了 586 个鱼类组合样本点的数据,以及可能影响鱼类组合的环境和空间预测因子的数据。我们从物种列表中计算了局部 beta 多样性(局部对 beta 多样性的贡献,LCBD)和 alpha 多样性,作为偏回归模型的响应变量,而人为影响、环境梯度和空间因素则作为预测因子。我们发现该生态区的总 beta 多样性很高(0.41),每个采样点的最大值都位于生态区的边缘,而较丰富的群落则位于中心位置。所有预测因子集都解释了 LCBD 和 alpha 多样性,但最重要的是扩散变量,其次是自然环境梯度和人为影响。然而,我们发现通过共享效应可以提高模型的预测能力。结果表明,环境过滤器(即气候、水文学和人为影响等环境变量)和扩散限制共同塑造了上巴拉那生态区的鱼类组合,这表明使用多组预测因子来理解生物多样性分布结构过程的重要性。