A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.
A comparative analysis reveals weak relationships between ecological factors and beta diversity of stream insect metacommunities at two spatial levels.
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DOI：
10.1002/ece3.1439
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发表时间：
2015-03
影响因子：
2.6
通讯作者：
Townsend, Colin R.
中科院分区：
文献类型：
--
作者：
Heino, Jani;Melo, Adriano S.;Bini, Luis Mauricio;Altermatt, Florian;Al-Shami, Salman A.;Angeler, David G.;Bonada, Nuria;Brand, Cecilia;Callisto, Marcos;Cottenie, Karl;Dangles, Olivier;Dudgeon, David;Encalada, Andrea;Goethe, Emma;Groenroos, Mira;Hamada, Neusa;Jacobsen, Dean;Landeiro, Victor L.;Ligeiro, Raphael;Martins, Renato T.;Miserendino, Maria Laura;Rawi, Che Salmah Md;Rodrigues, Marciel E.;Roque, Fabio de Oliveira;Sandin, Leonard;Schmera, Denes;Sgarbi, Luciano F.;Simaika, John P.;Siqueira, Tadeu;Thompson, Ross M.;Townsend, Colin R.
关键词：
β多样性应该随着纬度的降低而增加，随着区域空间范围的增加而增加的假设很少基于多个数据集的比较分析进行测试，并且没有这样的研究集中在溪流昆虫上。我们首先评估了如何预测的昆虫组，纬度，空间范围，海拔范围和数据集属性在世界各地的多个流域流域的流昆虫metacperitics的β多样性的变化。其次，我们评估了环境和空间因素在驱动每个流域内的组合组成的变化的相对作用。我们的分析是基于一个数据集的95流昆虫metaceritics从31个流域分布在世界各地。我们使用基于差异性的指数来量化每个元生态系统的β多样性，随后，回归β多样性对昆虫群，纬度，空间范围，海拔范围和数据集属性（例如，网站数量和存在的百分比）。在每个元群落中，我们结合使用空间本征函数分析和部分冗余分析将聚集结构的变化划分为环境部分、共享部分、空间部分和无法解释的部分。我们发现，在多个流域，数据集属性比生态和地理因素更重要的预测β多样性。在流域内的分析，环境和空间变量一般较差的组合组成的变化预测。我们的研究结果显示偏离一般的生物多样性模式，因为β多样性并没有表现出预期的下降趋势与纬度。我们的研究结果还呼吁重新考虑如何可预测的流组合是沿着生态梯度，与环境评估和保护决策的影响。我们的研究结果也可能适用于其他动态系统的可预测性低。
The hypotheses that beta diversity should increase with decreasing latitude and increase with spatial extent of a region have rarely been tested based on a comparative analysis of multiple datasets, and no such study has focused on stream insects. We first assessed how well variability in beta diversity of stream insect metacommunities is predicted by insect group, latitude, spatial extent, altitudinal range, and dataset properties across multiple drainage basins throughout the world. Second, we assessed the relative roles of environmental and spatial factors in driving variation in assemblage composition within each drainage basin. Our analyses were based on a dataset of 95 stream insect metacommunities from 31 drainage basins distributed around the world. We used dissimilarity-based indices to quantify beta diversity for each metacommunity and, subsequently, regressed beta diversity on insect group, latitude, spatial extent, altitudinal range, and dataset properties (e.g., number of sites and percentage of presences). Within each metacommunity, we used a combination of spatial eigenfunction analyses and partial redundancy analysis to partition variation in assemblage structure into environmental, shared, spatial, and unexplained fractions. We found that dataset properties were more important predictors of beta diversity than ecological and geographical factors across multiple drainage basins. In the within-basin analyses, environmental and spatial variables were generally poor predictors of variation in assemblage composition. Our results revealed deviation from general biodiversity patterns because beta diversity did not show the expected decreasing trend with latitude. Our results also call for reconsideration of just how predictable stream assemblages are along ecological gradients, with implications for environmental assessment and conservation decisions. Our findings may also be applicable to other dynamic systems where predictability is low.
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