Environmental factors and river network position allow prediction of benthic community assemblies: A model of nematode metacommunities

Abstract

The field of metacommunity studies is growing rapidly, including recent applications to river networks. Most of these studies have targeted a single river network but whether their findings are relevant to other river systems is unknown. This study investigated the influence of environmental, spatial and temporal parameters on the community structure of nematodes in the river networks of the Elbe and Rhine. We asked whether the variance in community structure was better explained by spatial variables representing the watercourse than by overland distances. After determining the patterns in the Elbe river network, we tested whether they also explained the Rhine data. The Elbe data were evaluated using a boosted regression tree analysis. The predictive ability of the model was then assessed using the Rhine data. In addition to strong temporal dynamics, environmental factors were more important than spatial factors in structuring riverine nematode communities. Community structure was more strongly influenced by watercourse than by Euclidean distances. Application of the model’s predictions to the Rhine data correlated significantly with field observations. Our model shows that the consequences of changes in environmental factors or habitat connectivity for aquatic communities across different river networks are quantifiable.

The influence of environmental and spatial factors on benthic invertebrate metacommunities differing in size and dispersal mode

“…In addition, the oviposition of flying insects is seasonally restricted. Thus, the relative impact of the investigated factors may change during the course of the year, consistent with the strong temporal component shown to characterize nematode metacommunities (Gansfort and Traunspurger 2019). Furthermore, although our study included a direct comparison between meio-and macrobenthic taxa, investigations of other meiobenthic groups, such as rotifers and other microcrustaceans, are needed to provide a complete understanding of the processes affecting invertebrate biodiversity in lotic systems.…”

The ability to get everywhere: dispersal modes of free-living, aquatic nematodes

“…Dispersal also ultimately affects the distribution and composition of benthic invertebrates (Grönroos et al, 2013;Kärnä et al, 2015;Tonkin et al, 2018;Tornero et al, 2018;Gansfort & Traunspurger, 2019). However, these organisms are inhabitants of aquatic islands that are often not directly connected to similar habitats but are instead surrounded by a ''dry ocean'' (Incagnone et al, 2015).…”

Assessing forest degradation using multivariate and machine‐learning methods in the Patagonian temperate rain forest

“…To determine the optimal number of trees used in the BRT, we used a k-fold cross-validation method that minimizes the hold-out residual deviance (Hastie and Tibshirani 2016). When fitting the BRT models, we followed Elith et al's (2008) indications, including a Gaussian family of relationships, a random seed of 7, a tree depth or complexity of 2 given the relatively small number of plots (Gansfort and Traunspurger 2019), a learning rate of 0.001 to reach at least 1,000 trees in each model, 10fold cross-validation with a bagging rate of two-thirds to avoid overfitting, an initial number of trees to fit of 50, a maximum number of trees to fit of 10,000, where the other parameters were used as defaults following the custom code written by Leathwick and Elith based on the R/ GBM package (Elith et al 2008). Interactions between predictors were revised using the methodology developed by Elith et al (2008) (including the code mentioned earlier).…”