Modeling and mapping fish abundance across wadeable streams of Illinois, USA, based on landscape-level environmental variables

Abstract

To effectively conserve and restore stream ecosystems, we need to better understand the distribution and abundance of individual fish species in relation to natural environments and anthropological stressors. In this study, we modeled the abundance of 97 fish species in small wadeable streams of Illinois, USA, based on random forests regression and landscape-level environmental variables. Model R2 values for intermediately common species were higher than for common species, but highly variable among rare ones. Models for 50 species reached R2 of 0.2–0.70 and were tested with a separate set of samples and applied to unsampled wadeable reaches to show the population hotspots of each species across the state. Furthermore, we evaluated the importance of individual environmental variables to a given fish species as well as the directional responses of each species to top 10 key predictors. Climate and land use were the best predictors for most species, followed by topography, geology, and soil permeability. Spatial connection of a stream also was associated with a large number of species. These findings improved our understanding of the relationships between fish species and landscape environments. The distribution maps could guide resource management, restoration, and monitoring of stream fish assemblages.

A Synopsis of Global Mapping of Freshwater Habitats and Biodiversity: Implications for Conservation

“…For the US, a comparable dataset is the NHD plus system (1:24K scale), which provides climate, hydrology, and land-use information summarized within the entire upstream network above each stream reach. Many freshwater species distribution modeling efforts have utilized the NHDplus data (1:24k) and architecture because of topological connectivity and habitat predictors offered by the resource [102][103][104][105][106][107] ( Figure 11). Although NHDplus is a convenient database to support freshwater species distribution modeling, it does not adequately represent 1st order streams, the majority of which provide habitat for freshwater taxa (Figure 11).…”

State‐Level Freshwater Mussel Programs: Current Status and a Research Framework to Aid in Mussel Management and Conservation

“…The presence of host fish species is another important factor to consider at broad scales that can be included using fish distribution data or distribution modeling efforts (Vaughn and Taylor ; Cao et al. ). In instances of information gaps, interagency collaboration may facilitate data collection of identified information needs.…”

“…For assessments at broader scales, the inclusion of controlling variables that vary across a region or province, such as climate, water chemistry, and stream size may improve the niche model. The presence of host fish species is another important factor to consider at broad scales that can be included using fish distribution data or distribution modeling efforts (Vaughn and Taylor 2000;Cao et al 2016). In instances of information gaps, interagency collaboration may facilitate data collection of identified information needs.…”

Fisheries Volume 43 Number 8 August 2018

“…For assessments at broader scales, the inclusion of controlling variables that vary across a region or province, such as climate, water chemistry, and stream size may improve the niche model. The presence of host fi sh species is another important factor to consider at broad scales that can be included using fi sh distribution data or distribution modeling efforts (Vaughn and Taylor 2000 ;Cao et al 2016 ). In instances of information gaps, interagency collaboration may facilitate data collection of identifi ed information needs.…”