Spatial Scaling of Environmental Variables Improves Species-Habitat Models of Fishes in a Small, Sand-Bed Lowland River

PLoS One. 2015 Nov 16;10(11):e0142813. doi: 10.1371/journal.pone.0142813. eCollection 2015.

Abstract

Habitat suitability and the distinct mobility of species depict fundamental keys for explaining and understanding the distribution of river fishes. In recent years, comprehensive data on river hydromorphology has been mapped at spatial scales down to 100 m, potentially serving high resolution species-habitat models, e.g., for fish. However, the relative importance of specific hydromorphological and in-stream habitat variables and their spatial scales of influence is poorly understood. Applying boosted regression trees, we developed species-habitat models for 13 fish species in a sand-bed lowland river based on river morphological and in-stream habitat data. First, we calculated mean values for the predictor variables in five distance classes (from the sampling site up to 4000 m up- and downstream) to identify the spatial scale that best predicts the presence of fish species. Second, we compared the suitability of measured variables and assessment scores related to natural reference conditions. Third, we identified variables which best explained the presence of fish species. The mean model quality (AUC = 0.78, area under the receiver operating characteristic curve) significantly increased when information on the habitat conditions up- and downstream of a sampling site (maximum AUC at 2500 m distance class, +0.049) and topological variables (e.g., stream order) were included (AUC = +0.014). Both measured and assessed variables were similarly well suited to predict species' presence. Stream order variables and measured cross section features (e.g., width, depth, velocity) were best-suited predictors. In addition, measured channel-bed characteristics (e.g., substrate types) and assessed longitudinal channel features (e.g., naturalness of river planform) were also good predictors. These findings demonstrate (i) the applicability of high resolution river morphological and instream-habitat data (measured and assessed variables) to predict fish presence, (ii) the importance of considering habitat at spatial scales larger than the sampling site, and (iii) that the importance of (river morphological) habitat characteristics differs depending on the spatial scale.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Area Under Curve
  • Ecosystem*
  • Fishes / physiology*
  • Geography
  • Germany
  • Linear Models
  • Models, Theoretical*
  • Reproducibility of Results
  • Rivers*
  • Species Specificity

Grants and funding

This project has been carried out with financial support from the Commission of the European Communities, specifically the RTD programme “IWRMNET”. It does not necessarily reflect its views and in no way anticipates the Commission’s future policy in this area. The authors have been funded by the German Federal Ministry for Education and Research (grant number 02WM1134). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.