Local‐Habitat, Watershed, and Biotic Features Associated with Bull Trout Occurrence in Montana Streams

Abstract

Abstract.-We evaluated the association of local-habitat features, large-scale watershed factors, the presence of nonnative brook trout Salvelinus fontinalis, and connectivity to neighboring populations with patterns of occurrence of threatened bull trout S. confluentus in 112 first-order to fourthorder streams in the Bitterroot River drainage in western Montana. Species presence or absence was estimated via single-pass electrofishing, local-habitat features were measured in 500-m sampling reaches, watershed variables were obtained from topographic maps, and potential demographic support from nearby bull trout populations occupying larger main-stem streams was estimated from electrofishing data records. We defined a set of nine candidate models that represented various combinations of these four main factors and used an information-theoretic approach to evaluate the relative plausibility of competing models. Models combining local habitat (width, gradient, and woody debris) with brook trout presence and the main-stem abundance of bull trout and a global model (all variables) were the best approximating models. In contrast, watershed models based on elevation, basin area, and tributary slope and models with local-habitat or biotic variables alone were poor predictors of bull trout occurrence. Bull trout occurrence was positively associated with channel width, large woody debris, and the presence of a ''strong'' neighboring main-stem population and negatively associated with channel gradient and the presence of brook trout. Our findings suggest that bull trout have increased resistance to invasion by brook trout in streams with high habitat complexity and connectivity. Consideration of abiotic and biotic factors at multiple scales, along with a means for ranking their relative importance, is needed to perform more comprehensive assessments of landscape and local influences on species distribution patterns.

Habitat Associations of Fish Species of Greatest Conservation Need at Multiple Spatial Scales in Wadeable Iowa Streams

“…Small-scale models Multiple-scale models regression analysis is a common multivariate approach for predicting the binary response of fish species presence or absence (e.g., Porter et al 2000;Rich et al 2003;Rashleigh et al 2005). Using retained variables (i.e., the 5 large-scale variables and 13 small-scale variables), candidate multiple logistic regression models were created for all possible combinations of variables measured at a large scale, a small scale, and multiple scales (i.e., both large-scale and small-scale variables).…”

“…Furthermore, an understanding of species-habitat relationships can provide insight into the effects of land use practices, habitat alterations, and climate change on species distributions (Wang et al 2003;Wall et al 2004;Lyons et al 2010). Modeling of species distributions is an important tool for addressing many issues in conservation (Guisan and Thuiller 2005), and the use of predictive occurrence models to further the understanding of fish species' relationships with habitat features in freshwater systems is common (e.g., Olden and Jackson 2001;Rich et al 2003;Steen et al 2008). As habitat loss and degradation continue to threaten fish biodiversity in North America (Miller et al 1989;Richter et al 1997;Jelks et al 2008), species distribution models are playing an increasingly important role in conservation.…”

“…Additionally, the modeling of species occurrences with large-scale habitat variables is economical because such variables are easily measured with a GIS, thereby reducing the need for costly field sampling (Oakes et al 2005;Steen et al 2008). However, in other regions, large-scale habitat variables such as land use may not effectively explain variation in fish assemblage structure (Rich et al 2003;Heitke et al 2006) or may only do so indirectly (Rowe et al 2009a).…”

“…Identification of the factors and spatial scales influencing fish species occurrences remains a central focus of fisheries ecologists (e.g., Porter et al 2000;Rich et al 2003;Pont et al 2005). Biotic communities are influenced by a hierarchical system of constraints in which large-scale processes constrain smallerscale processes (Tonn 1990;Poff 1997;Quist et al 2005).…”

“…This is especially evident for stream habitats, which are hierarchically organized within catchments, segments, reaches, macrohabitats, and microhabitats (Frissel et al 1986). Thus, species occurrence models that account for effects measured at multiple spatial scales may provide more predictive power and transferability than models that incorporate variables measured at a single spatial scale (Leftwich et al 1997;Rich et al 2003;Pont et al 2005).…”