Shifting climate conditions affect recruitment in Midwestern stream trout, but depend on seasonal and spatial context

Abstract

Climate change is a complex threat to freshwater ecosystems. Effects on aquatic species will likely differ among populations depending on seasonal and spatial context, which makes a detailed understanding of population responses to shifting climate conditions key to guiding strategic decision‐making. However, few empirical studies have tested for such context dependency on distinct populations across seasons or at large spatial scales. We used 26 years of standardized survey data on recreationally and economically important brook trout (Salvelinus fontinalis) and brown trout (Salmo trutta) in Wisconsin, USA to assess short‐ and long‐term variability in population trends, and quantify the influence of seasonal and spatial climate variability (air temperatures and precipitation) on annual recruitment strength (as indexed by young‐of‐year [YOY] relative abundance in summer). Some short‐term population fluctuations were spatially consistent across the state, indicative of broadscale environmental forcing. Over the longer term, average YOY and age 1 and older brook trout relative abundance has declined since 2006, especially for YOY, while brown trout abundance has substantially increased. The effects of climate conditions on recruitment varied by species, season, and latitude. Increasing maximum summer temperatures were associated with lower brook trout recruitment, but higher brown trout recruitment. The effect for both species was stronger at lower latitudes. Spring temperatures were positively related to brown trout recruitment at lower latitudes; in mid‐latitude and northern streams, they were related to increasing recruitment up to about 1 standard deviation, above which recruitment declined. High and low winter and spring precipitation were associated with precipitous declines in recruitment for both species. By contrast, summer precipitation was positively related to recruitment in northern streams for brook trout and southern streams for brown trout. Our results demonstrate that shifts in climate can affect recruitment in similar species differently depending on temporal (seasonal) and spatial (warm, southern regions compared with cool, northern regions) context. Given trout population trends in Wisconsin and climate projections for the Midwestern United States, location‐ and species‐specific management actions are needed that account for this context dependency. Management should aim to maximize the resiliency of populations to extreme climate conditions by buffering negative influences on recruitment.

Microgeographic variation in demography and thermal regimes stabilize regional abundance of a widespread freshwater fish

“…While some connected populations within drainages exhibited similar trends in recruitment (e.g., MC and UC, LO and UO; Figure 2b), asynchrony prevailed nonetheless (Appendix S1, Section S2), similar to observations from recent research on salmonids (Donadi et al, 2023) and other organisms (Moore & Schindler, 2022; Rowland et al, 2022). However, these results differ from previous studies of brook trout elsewhere in North America (Kanno et al, 2016; Maitland & Latzka, 2022; Sweka & Wagner, 2022; Warren et al, 2009; Zorn & Nuhfer, 2007), and other stream‐dwelling salmonids in Europe (Alonso et al, 2011; Bret et al, 2016; Cattanéo et al, 2003), which generally report synchronized population dynamics at larger scales than the current study. This synchrony is often attributed to the Moran effects, where one or more environmental variables are spatially autocorrelated and consistently influence recruitment across the study area (Moran, 1953).…”

“…Models were compared using the corrected Akaike information criterion (AIC c ), and the model with the lowest AIC c by two or more units was selected as the best fit (Johnson & Omland, 2004). To ensure that temperature and precipitation extremes did not have stronger effects on recruitment or growth (Maitland & Latzka, 2022), we repeated our DFA model selection procedure with maximum values instead of means.…”

Cold-water habitats, climate refugia, and their utility for conserving salmonid fishes

“…Stimulating discussions about thermal controls on salmonid populations in recent decades, of course, has been anthropogenic climate change that is increasing water temperatures globally (McCullough et al 2009;van Vliet et al 2013;O'Reilly et al 2015;Isaak et al 2018) and exacerbating habitat losses and productivity declines among salmonids and other aquatic species where warm conditions are limiting (Lynch et al 2016;Gallagher et al 2022). The potential for climate change to reduce the geographic extent occupied by salmonids was first recognized in late 20th-century bioclimatic assessments (Meisner 1990;Keleher and Rahel 1996;Nakano et al 1996), which spawned many similar studies (reviewed by ) and, more recently, case histories that document species distribution shifts consistent with model predictions (Hari et al 2006;Winfield et al 2010;Almodóvar et al 2012;Lemoine et al 2020;Bell et al 2021;Maitland and Latzka 2022;Svenning et al 2022). Although climate-related extirpations of local populations in southern ranges are yet infrequent and may ultimately be limited in comparison to the historical losses already suffered by many species (Gustafson et al 2007), projections of warming for the next several decades or longer (IPCC 2021) suggest that further population declines, range contractions, and occasional extirpations could become commonplace.…”

Spatial asynchrony and cross‐scale climate interactions in populations of a coldwater stream fish

“…Second, we tested whether spatial synchrony was explained by a set of seasonal climate variables and whether the importance of seasonal climate variables differed between and within northern and southern sub‐regions. Because we studied a sensitive coldwater species at its southern range limit, we predicted that temperature would be a stronger driver of synchrony in southern populations compared to northern populations (Maitland & Latzka, 2022). Furthermore, we predicted that winter and spring stream flow would be a stronger driver of synchrony in the young‐of‐the‐year (YOY) (juvenile) stage versus adult stage of this fall spawner due to the diminished ability to withstand bed‐scouring high flows of the younger stage (Kanno et al., 2016; Kovach et al., 2016).…”