Stream Temperature, Density Dependence, Catchment Size, and Physical Habitat: Understanding Salmonid Size Variation Across Small Streams

Abstract

The average body size (fork length) of juvenile salmonids in small streams varies across landscapes and can be influenced by stream temperature, density dependence, catchment size, and physical habitat. In this study, we compared sets of 16 mixed-effects linear models representing these four potentially influencing indicators for three species/age classes to assess the relative importance of their influences on body size. The global model containing all indicators was the most parsimonious model for juvenile coho salmon (Oncorhynchus kisutch; R²m = 0.4581, R²c = 0.5859), age-0 trout (R²m = 0.4117, R²c = 0.5968), and age-1 or older coastal cutthroat trout (O. clarkii; R²m = 0.2407, R²c = 0.5188). Contrary to expectations, salmonid density, catchment size, and physical habitat metrics contributed more to the top models for both coho salmon and age-1 or older cutthroat trout than stream temperature metrics. However, a stream temperature metric, accumulated degree days, had the only significant relationship (positive) of the indicators with body size in age-0 trout (95% CI 1.58 to 23.04). Our analysis identifies complex relationships between salmonid body size and environmental influences, such as the importance of physical habitat such as pool size and boulders. However, management or restoration actions aimed at improving or preventing anticipated declines in physical habitat such as adding instream wood or actions that may lead to increasing pool area have potential to ensure a natural range of salmonid body sizes across watersheds.

1. Introduction

The size of fish at any point in time is determined by its history of growth, which varies by species [1] and environmental conditions [2,3]. Fish size is known to influence behavior, physical performance, thermal tolerance, and survival [4,5,6,7]. Variation in individual juvenile salmonid responses, such as growth, to environmental variability can reduce extirpation risk to populations [8]; however, the factors driving variation remain poorly understood. Within species or life history stages, juvenile salmonid body size can be shaped by stream temperatures, density dependence, and food availability [9,10]. These factors often interact, leading to substantial spatial variation in body size among streams. This variability may enhance local diversity and population resilience, forming a portfolio effect that buffers salmonid populations against environmental changes [9,11].

Understanding the drivers of body size variation is increasingly important in the context of stream and habitat alterations caused by both the legacy of forest harvest and climate change. Arismendi et al. [12] documented a 6–13% decline in coastal cutthroat trout body size over thirty years in Oregon, which they partially attributed to both climate change and the legacy forest harvest influences. Historical riparian logging has degraded stream habitat [13,14], and these impacts are likely to persist—or even intensify—in the near future [15,16], potentially influencing salmonid body size. Additionally, climate change may influence body size by increasing stream temperatures and reducing the size of streams [17,18]. A deeper understanding of how environmental indicators influence fish growth and body size is essential for guiding effective management and restoration efforts, predicting ecological responses to changing conditions, and supporting the long-term viability of salmonid populations.

Juvenile salmonid body size plays a pivotal role in shaping life history trajectories and survival, including the timing of migration. For instance, Peven et al. [19] suggested that body size thresholds may trigger anadromous salmonid migrations. Later work has shown that such threshold size can vary based on other factors such as growth, age-class, and reproductive state and that individuals may follow different developmental pathways to reach similar stages [20,21,22,23,24]. The possibility of migration thresholds combined with variation in growth rate among streams may help to explain variations in the age of smolts and the duration of freshwater residency among salmonids that spend a portion of their life histories in freshwater before migrating to the ocean (e.g., coho salmon Oncorhynchus kisutch, steelhead O. mykiss, coastal cutthroat trout O. clarkii, stream-type Chinook salmon O. tshawytscha) [25]. For example, Hall et al. [26] documented steelhead migration across different ages, lengths, and seasons (i.e., age-0 fall; <86 mm, age-1 spring and fall; 87–132 mm, age-2 spring and fall; >132 mm, and age-3 spring and fall), with only fish older than age-0 surviving to return as adults. Similarly, Roni et al. [7] found that coho salmon had successful adult returns from both fall and spring migrations but larger individuals were more likely to survive and migrate in the spring. These studies reveal a nuanced process wherein juvenile salmon migrate at various ages, lengths, or seasons. While the “bigger-is-better” hypothesis has generally been theorized for ocean survival [27,28], research has uncovered contradictions, with studies on ocean survival yielding mixed results [28,29,30,31]. Although some studies support the “bigger is better” hypothesis [7,32], a diverse range of body sizes across a landscape may facilitate a bet-hedging strategy (an evolutionary strategy where organisms diversify traits to increase long-term population viability) [11].

Stream temperature is often thought to be one of the primary indicators influencing body size of juvenile salmonids. Metabolic theory outlines how temperature influences organism size through biological metabolism [33], with direct implications for cold-water ectothermic salmonids. Coho salmon, for instance, achieve optimal growth within an average weekly temperature range of 12–17 °C [1,34,35]. However, greater variation in growth among fish within the same species has been found at lower temperatures within the range than at higher temperatures. For example, Lusardi et al. [1] reported a sixfold increase in juvenile coho salmon growth at 16.6 °C compared to 13 °C and found that growth remained high at their highest studied temperature of 18.1 °C. The ability of salmonids to maintain high levels of growth in the upper end of their temperature growth range has been attributed to the consumption of higher amounts of prey [1]. However, if stream temperatures exceed optimal ranges, fish growth will slow down or stop, resulting in reduced body size [1,36]. This variability in optimal stream temperature for growth supports the notion that adaptation and acclimation lead to varying ranges of maximum growth among salmonid populations [1].

Density is another well-documented driver of juvenile salmonid body size [37,38,39]. In general, juvenile salmonid body size decreases with increased densities, often following a negative power curve [40,41,42]. Imer et al. [41] theorized that the density responses observed at relatively low densities may be due to exploitative competition for stream drift. Furthermore, Amundsen [43] found that intraspecific competition for food led to increased food intake and a subsequent improvement in growth rate at lower densities. In a meta-analysis, Grant and Imre [37] reported that increased abundance significantly reduced growth in 15 of the 19 stream populations studied, suggesting widespread density-dependent regulation of body size. Walters et al. [39] proposed several mechanisms for the relationship between density and growth including limited rearing habitat, relatively consistent spawning locations, and the trade-off juvenile fish must make between foraging and avoiding predators. However, density effects may shift from impacting body size at lower densities to increasing mortality and migration at higher densities [37].

Stream physical characteristics, including habitat complexity and riparian vegetation, influence prey type, and abundance [44,45,46,47]. In general, greater habitat heterogeneity has been linked to richer and denser macroinvertebrate communities—key prey for salmonids [48,49,50]. Moreover, Wipfli [51] emphasized the influence of riparian vegetation on aquatic food webs and suggested that diverse and dense plant communities may foster more diverse and productive terrestrial insect communities—an important component of salmonid diets. Furthermore, physical habitat structure influences carrying capacity and may mediate the influences of density dependence [46,52,53]. To some degree, all these factors and likely others influence fish growth and ultimately the body size of fish.

Despite insights from laboratory and modeling studies [54,55], there remains a limited understanding of how these indicators interact to influence juvenile salmonid body size under natural field conditions. Field studies are essential to assess the real-world implications of environmental variation and restoration efforts. In this study, we evaluated juvenile salmonid body size across a range of sites on Washington’s Olympic Peninsula, USA. Our objective was to determine the relative importance of stream temperature, density dependence, catchment size, and physical habitat (e.g., instream wood key piece density and % boulders) on salmonid body size. We hypothesized that stream temperature would have the strongest influence on body size, with streams closer to the upper limits of a species’ optimal growth range supporting larger fish. Specifically, we predicted that stream temperature metrics (daily temperature range, degree days) would explain more variation in body size than salmonid density (density dependence), watershed area (catchment size), or physical habitat (e.g., the density of key pieces of instream wood). We conclude by discussing the implications of our findings for climate change adaptation, habitat restoration, and riparian management strategies.

2. Material and Methods

2.1. Study Area

The Washington Department of Natural Resources’ (WDNR) Olympic Experimental State Forest (OESF) on Washington’s western Olympic Peninsula has been designated as a place for both research/monitoring and commodity production (primarily timber harvest). The OESF encompasses approximately 110,000 hectares of state lands within boundaries extending along the crest of the Olympic Mountains, following the watersheds of West Twin Creek and Lake Crescent to the east, the Strait of Juan de Fuca to the north, the Pacific Ocean to the west, and the Quinault River Watershed to the south (Figure 1). Elevations within the OESF vary from sea level to 1155 m, and the region is characterized by a coastal rainforest climate with substantial precipitation, ranging from 203 to 355 cm annually, with the majority occurring during the winter months. The catchments in this study are forested with a mosaic of standages, the majority of which are second-growth conifer forests, though they also contain third-growth and some stand that have never been harvested.

The OESF contains over 4300 km of streams including portions of several major rivers such as the Queets, Clearwater, Hoh, Bogachiel, Calawah, Sol Duc, Dickey, Hoko, and Clallam. Based on the long-term monitoring of 50 of the small streams in this study, the average 7-day average daily maximum temperature was 14.4 °C; the highest average 7-day average daily maximum temperature for any of these monitored streams was 16.4 °C [56]. While only two salmonid species (i.e., Lake Ozette sockeye salmon O. nerka and bull trout Salvelinus confluentus) are listed under the Endangered Species Act, salmonid populations in the region are largely reduced from historical levels [57,58,59]. The small streams that are the focus of this study (stream order 1st–3rd) [60] typically contain some combination of juvenile coho salmon, rainbow trout/steelhead (O. mykiss), coastal cutthroat trout, lampreys (Lampetra and Entosphenus spp.), and/or sculpins (Cottus spp.). Juvenile coho salmon typically spend one year in freshwater, while coastal cutthroat trout and steelhead can spend anywhere from a year to a lifetime in freshwater [61]. However, larger fish (>150 mm) are relatively rare in these small streams.

2.2. Monitoring Programs

Data from three monitoring efforts were used for this analysis. Fish data were collected through the WDNR’s Validation Monitoring and the T3 Watershed Experiment. Habitat variables and water temperature data were obtained from the WDNR’s Status and Trends program, Validation Monitoring, and the T3 Watershed Experiment. The Status and Trends and Validation Monitoring programs operate within the same reaches and complement each other. The T3 Watershed Experiment follows a similar protocol, combining the approaches used in the Status and Trends and Validation Monitoring programs.

The Status and Trends and Validation Monitoring catchments (n = 44) were selected using a stratified random design [62]. Validation Monitoring samples a single stream reach near the outlet of each catchment. The program samples 20 catchments annually and samples the remaining 24 catchments on a two-year rotation (12 each in even and odd years), as per Martens [63]. This sampling regimen is ongoing; however, data in this analysis were collected from 2016 to 2022. In contrast, the T3 Watershed Experiment sampled two stream reaches within each of 16 catchments annually from 2019 to 2022. As a result, all streams have been sampled at least three times.

2.3. Fish Surveys and Sampling Data Alignment

Fish sampling took place from mid-July to mid-October, a timeframe carefully selected to coincide with the period when age-0 spring spawning salmonids (i.e., steelhead and coastal cutthroat trout; hereafter referred to as age-0 trout) could be safely sampled, while avoiding complications caused by the accumulation of leaves in the block nets during the fall. Juvenile fish surveys were conducted using a multiple-pass removal electrofishing technique. In the T3 Watershed Experiment catchments, sample reaches were 100 m in length, while, in the Validation Monitoring catchments, sample reaches ranged from 100 to 120 m. Prior to sampling, seine nets were strategically positioned at the top and bottom of each reach to prevent fish movement. Once a reach was effectively blocked, a Smith–Root model 24b backpack electrofisher (Smith- Root, Vancouver, WA, USA) was employed to collect fish moving from the downstream net to the upstream net and then turning around and fishing downstream to the bottom net. Typically, electrofishing operated at a frequency of 60 hertz with a 25 percent duty cycle and voltage levels ranging from 300 to 600 volts. Fish sampling employed a variable-pass approach, varying between three to six passes, as determined by the Connolly [64] charts and utilized as described in Martens and Connolly [65].

Following electrofishing, all salmonids underwent anesthesia with MS-222, followed by identification and measured for fork length (from the fish nose to the fork in the tail) and weighed, before being released back into the stream. Field crews could not reliably determine the identity of juvenile coastal cutthroat trout and steelhead under 80 mm (young of the year) at this stage of their development, so they were combined under the designation “age-0 trout”, while all other fish were identified to species in the field. However, it should be noted that most of these fish were coastal cutthroat trout, as steelhead occurred at lower densities and in fewer streams within the study area. Due to the limited body size range in age-1 or older coastal cutthroat trout, variations between streams, and limited numbers of fish within each stream, all coastal cutthroat trout over 80 mm were combined into a single group for this analysis: age-1 or older coastal cutthroat trout.

After each field season, the length frequencies of age-0 trout were compared with those of age-1 or older coastal cutthroat trout and plotted together. An experienced reviewer then visually confirmed or adjusted the dividing point in fork length (initially 80 mm) between age-0 trout and age-1 or older coastal cutthroat. The dividing point was determined by identifying the low point in the bimodal distribution of small and larger fish. For each survey (i.e., each year × site combination), average fork length was calculated for each species (and age-class in the case of juvenile trout). Any sites with fewer than three fish per species or age-class per year were removed from further analysis. This three-fish threshold was a compromise that sought to reduce the influence of outlier fish lengths on average length at sites with very low densities while recognizing the value of data from low-fish-density sites that have been found to be important for identifying density dependence [40,41].

The total number of surveys having at least three fish were 84 for coho salmon, 140 for age-0 trout, and 154 for age-1 or older coastal cutthroat trout.

2.4. Habitat Data Collection

Water temperature was monitored year-round at 60-min intervals throughout the study at each of the stream sample reaches using Tidbit v2 temperature data loggers (HOBO^® Data Loggers, Bourne, MA, USA). Average daily temperature range (from 1 June through 31 August) was calculated for each reach in each year. Water degree days were summed from 1 January to 31 July for each reach in each year.

Immediately following each fish survey, habitat units (e.g., pools, riffles, runs) within each of the sample reaches were delineated based on the methodology of Bisson et al. [66] and Pleus et al. [67]. The surface area of each habitat unit was calculated based on length and the average of three wetted-width measurements. The mean and maximum water depth of each habitat unit was measured to the nearest cm. Within each sample reach, key pieces of instream wood (defined as pieces > 45 cm diameter at the midpoint and >2 m long) were counted.

In each sample reach, five to six equally spaced cross-sections were established. At each cross-section, stream bankfull width was measured, and streambed substrate particle size was measured using a gravelometer at a minimum of 20 equally spaced sample locations. For each reach, median particle size was calculated, as was the percentage of particles classified as boulders (251 to 3999 mm diameter).

Canopy shade was measured using hemispherical photos taken at stream-center at each of the five or size cross sections. Photos were analyzed using Hemisfer software version 2.2 [68] to calculate the percentage of shaded pixels, defined as those for which vegetation obstructed open sky, using an 82.7-degree field of view (the equivalent view of a spherical densiometer) [69].

Catchment area was calculated using GIS (ArcMap version 10.6, ESRI, Redlands, CA, USA).

2.5. Data Analysis

Juvenile coho salmon (the vast majority of coho salmon were age-0 fish, with only an occasional age-1 fish collected), age-0 trout, and age-1 or older coastal cutthroat trout were used for this analysis because they were the most common species/age-classes found in the study area. Variables hypothesized to influence the average body size (fork length) of these salmonids were organized into four potential indicators: density, temperature, catchment size, and physical habitat. Variables were selected based on data availability, the probability of detecting a response based on relevant research, and the desire to look at a range of different types of variables. Salmonid density (fish per square meter of stream surface area) was used as the metric for the density indicator (Density;

Table 1. Variables assessed in the analysis of salmonid body size (Fork Length, mm).

Variable	Indicator a	Unit	Min	Max	Mean	SD
Julian day of the year		Days	198	287	237	21.25
Year		Year	2015	2022
Salmonid density	Density	Fish per m2	0.0069	3.1152	0.3401	0.3502
Degree days	Temperature	Celsius	1263.1	2083.2	1746.8	142.4
Daily stream temperature range	Temperature	Celsius	0.3300	2.4495	1.0426	0.3802
Catchment area	Catchment	Hectares	31.09	1076.3	253.52	202.25
Pool area	Habitat	Percent	0	73	28	15
Stream depth	Habitat	Centimeters	3.17	30.00	12.84	5.66
Boulders	Habitat	Percent	0	27.67	8.33	8.28
Key pieces of instream wood	Habitat	Pieces > 45 cm/meter	0	0.1954	0.0652	0.0437
Canopy shade	Habitat	Percent	85.3	99.7	92.65	2.91

^a Julian Day of the Year was used to account for time between sampling events and was not grouped in a category. Year was used to account for interannual variation that was not explained by any of the other variables.

). Steam temperature (Temperature) metrics included cumulative degree days (January through July) and average daily temperature range in the summer. Beyond the common metric of degree days for stream temperature, the range of daily stream variation was added since daily stream variation has been found to influence salmonids [70] and may be important for determining body size. We used catchment area as a metric to represent catchment size. Finaly, physical habitat (Habitat) metrics were percent pool area, average stream depth (excluding pools), boulders (as a percentage of total substrate), the density of key pieces of instream wood (pieces over 2 m length and >45 cm diameter), and percent canopy shade.

Initially, all potential variables were analyzed using Pearson correlations in the program SigmaPlot (Version 13.0, Systat Software, Inc., San Jose, CA, USA). When any two potential variables showed a correlation coefficient above 0.70, one of the variables was removed from the analysis. Bankfull width and catchment area, average substrate size and percent boulders, salmonid density (per m²) and salmonid biomass (per m²), and degree days and elevation were found to be highly correlated. From these pairs, we opted to use catchment area, percent boulders, salmonid density, and degree days in our analysis because these variables were deemed to be more informative after initial examination. All models included the variable Julian day of the year and year. Julian day was added to account for any fish growth over time between sampling events over the summer field season (July-mid-October). Year was added to account for interannual variation in body size that was not explained by other variables (e.g., interannual variation in degree days). All variables except year were standardized between 0 and 1 in the program R (R Foundation for Statistical Computing, Vienna, Austria) using the package scales (version 1.4.0) [71].

The data underwent analysis using linear mixed-effect models within the R package, lme4 (version 1.1-37) [72]. Sixteen models for each of the three species/age classes (coho salmon, age-0 trout, and age-1 or older coastal cutthroat trout) were constructed using combinations of variables based on the four indicators (Density, Temperature, Catchment, and Habitat) along with a global model and a null model. When an indicator had multiple metrics (for example, degree days and daily stream range for the Temperature indicator), all metrics were included in the model. Additionally, site names were incorporated as a random effect in all models since sites were sampled between three and seven times. The global model encompassed all four indicators and included all 11 variables.

Average fish body size = Julian day of the year + Year + Salmonid density + Degree days + Daily stream temperature range + Catchment area + Pool area + Stream depth + Percent boulders + Key piece density + Canopy shade + (1|Site)

Assessments of the linear model assumptions for the global models were conducted to ensure compliance with key assumptions. Normality was assessed using the R package performance (version 0.15.0) [73], and the homogeneity of variance was tested using Levene’s Test in the R package car (3.1-3) [74].

Model ranking was then conducted using Akiaki’s Information Criterion (AICc) corrected for small sample sizes with the R package AICcmodavg (version 2.3-4) [75]. Models were ranked based on Delta AICc with models within 2 delta AICc units considered to have substantial support compared to the top model [76]. Since the top models in our analysis garnered most of the weight (0.96–0.59) and no other model was within 2 Delta AICc units of a top model (

Table 2. Model selection results for models of average juvenile coho salmon body size in OESF streams from 2015 to 2022. Variables within each indicator were: Density = salmonid density; Temperature = degree days, and daily stream temperature range; Catchment = catchment area; and Habitat = pool area, stream depth, boulders, key piece density, and canopy shade. All models also included year and Julian day of the year as a fixed effect and site name as a random effect. K = the number of parameters, WT = weight, and LL = log-likelihood of the model.

Model	K	AICc	Delta AICc	WT	LL
Coho Salmon
Density + Temperature + Catchment + Habitat	20	499.65	0	0.75	−223.16
Density + Temperature + Habitat	19	502.21	2.56	0.21	−226.17
Temperature + Catchment + Habitat	19	506.16	6.51	0.03	−228.14
Density + Catchment + Habitat	18	509.34	9.69	0.01	−231.41
Temperature + Habitat	18	509.37	9.72	0.01	−231.43
Density + Habitat	17	511.85	12.20	0.00	−234.29
Catchment + Habitat	17	513.34	13.70	0.00	−235.04
Habitat	16	516.39	16.74	0.00	−238.13
Density + Temperature + Catchment	15	517.49	17.84	0.00	−240.22
Density + Temperature	14	520.92	21.27	0.00	−243.41
Temperature + Catchment	14	524.72	25.07	0.00	−245.32
Density + Catchment	13	532.37	32.72	0.00	−250.59
Temperature	12	533.33	33.68	0.00	−252.47
Catchment	12	535.67	36.02	0.00	−253.64
Density	12	536.07	36.42	0.00	−253.84
Null	3	576.12	76.47	0.00	−284.91

,

Table 3. Model selection results for models of average age-0 trout body size in OESF streams from 2015 to 2022. Variables within each indicator were: Density = salmonid density; Temperature = degree days, and daily stream temperature range; Catchment = catchment area; and Habitat = pool area, stream depth, boulders, key piece density, and canopy shade. All models also included year and Julian day of the year as a fixed effect and site name as a random effect. K = the number of parameters, WT = weight, and LL = log-likelihood of the model.

Model	K	AICc	Delta AICc	WT	LL
Age-0 Trout
Density + Temperature + Catchment + Habitat	19	907.94	0	0.59	−431.80
Temperature + Catchment + Habitat	18	910.30	2.36	0.18	−434.32
Density + Temperature + Habitat	18	910.34	2.39	0.18	−434.34
Temperature + Habitat	17	912.81	4.87	0.05	−436.90
Density + Catchment + Habitat	17	919.06	11.12	0	−440.02
Catchment + Habitat	16	921.52	13.58	0	−442.55
Density + Habitat	16	923.16	15.21	0	−443.37
Habitat	15	925.86	17.92	0	−445.99
Density + Temperature + Catchment	14	926.93	18.99	0	−447.78
Density + Temperature	13	929.70	21.76	0	−450.41
Temperature + Catchment	13	929.92	21.98	0	−450.52
Density + Catchment	12	936.38	28.44	0	−454.96
Temperature	11	938.86	30.92	0	−457.40
Catchment	11	939.29	31.35	0	−457.61
Density	11	941.28	33.34	0	−458.61
Null	3	1011.89	103.95	0	−502.86

and

Table 4. Model selection results for models of average age-1 or older coastal cutthroat trout body size in OESF streams from 2015 to 2022. Variables within each indicator were: Density = salmonid density; Temperature = degree days, and daily stream temperature range; Catchment = catchment area; and Habitat = pool area, stream depth, boulders, key piece density, and canopy shade. All models also included year and Julian day of the year as a fixed effect and site name as a random effect. K = the number of parameters, WT = weight, and LL = log-likelihood of the model.

Model	K	AICc	Delta AICc	WT	LL
Age-1 or older Coastal Cutthroat Trout
Density + Temperature + Catchment + Habitat	19	1055.41	0	0.96	−505.83
Temperature + Catchment + Habitat	18	1062.23	6.82	0.03	−510.54
Density + Temperature + Habitat	18	1065.01	9.60	0.01	−511.94
Temperature + Habitat	17	1071.72	16.31	0	−516.58
Density + Temperature + Catchment	14	1074.33	18.92	0	−521.63
Temperature + Catchment	13	1080.00	24.59	0	−525.68
Density + Catchment + Habitat	13	1088.76	33.34	0	−525.13
Density + Temperature	13	1096.49	35.28	0	−531.03
Catchment + Habitat	16	1094.31	38.90	0	−529.17
Density + Habitat	16	1096.49	41.08	0	−530.26
Temperature	11	1100.32	44.90	0	−538.21
Habitat	15	1102.06	46.65	0	−534.29
Density + Catchment	12	1108.03	52.62	0	−540.91
Catchment	11	1112.66	57.26	0	−544.40
Density	11	1123.64	68.22	0	−549.89
Null	3	1148.14	92.73	0	−570.99

), the contributions of the fixed-effect variables from the top models were additionally assessed through hierarchical partitioning using the R package glmmhp (version 0.1-8) [77] rather than using model averaging. Additionally, the direction of the relationship of the fixed effects were determined through 95% confidence intervals with variables considered significant if the entire confidence interval was positive or negative.

3. Results

Juvenile coho salmon average body size ranged from 47 mm to 97 mm among sites, with an overall mean of 65 mm and standard deviation of 8 mm. The average body size was 59 mm in July and 72 mm in October (Figure 2). For age-0 trout, average body size ranged from 25 mm to 80 mm among sites, with an overall mean of 56 mm and standard deviation of 9 mm. Age-0 trout had mean body sizes of 49 mm in July and 64 mm in October. Age-1 or older coastal cutthroat trout had an average body size ranging from 84 mm to 152 mm among sites, with a mean of 106 mm and standard deviation of 11 mm. In July, age-1 or older coastal cutthroat trout averaged 103 mm, increasing slightly to 107 mm in October.

The global model (Density + Temperature + Catchment + Habitat) emerged as the top model for coho salmon, age-0 trout, and age-1 or older coastal cutthroat trout. Specifically, for coho salmon, the top model (R²m = 0.4581, R²c = 0.5859) was 3.6 times more parsimonious than the next closest model (Density + Temperature + Habitat; Table 2). In the top model, Julian day of the year (β = 14.87, 95% CI = 9.20 to 19.84), salmonid density (β = −9.25, 95% CI = −16.12 to −2.79), daily mean temperature range (β = 10.62, 95% CI = 1.85 to 19.12), and boulders (β = 8.33, 95% CI = 2.02 to 14.41) exhibited significant relationships with average coho salmon body size; Figure 3; Appendix A 

Table A1. Fixed effects from global model of coho salmon. Significant effects are in bold.

Fixed Effects	Estimate	Std Error	T-Value	DF	LCI	UCI
Intercept	67.99	11.26	6.04	44.14	49.32	88.26
Julian day	14.87	3.03	4.91	65.49	9.20	19.85
Salmonid density	−9.25	3.99	−2.32	48.66	−16.12	−2.79
Degree days	−11.44	7.16	−1.60	42.58	−24.27	0.28
Temp. range	10.62	5.15	2.06	47.64	1.85	19.12
Year-2016	−0.15	6.42	−0.02	53.44	−1.12	11.91
Year-2017	−9.73	8.44	−1.15	65.91	−24.62	4.35
Year-2018	−4.14	6.89	−0.60	61.05	−16.29	7.77
Year-2019	−5.15	7.45	−0.69	64.30	−18.69	7.35
Year-2020	−1.40	7.64	−0.18	64.73	−15.17	11.41
Year-2021	−2.63	6.94	−0.38	61.06	−15.10	9.21
Year-2022	−3.21	8.36	−0.38	65.55	−18.33	10.84
Catchment area	4.76	5.86	0.81	48.02	−5.04	14.77
Pool Area	−1.44	4.67	−0.31	64.61	−9.39	6.39
Stream depth	−3.77	4.97	−0.76	65.94	−12.03	5.42
Boulders	8.33	3.64	2.29	22.92	2.02	14.41
Key piece density	3.72	3.84	0.97	37.11	−2.77	9.98
Canopy shade	−4.66	7.37	−0.63	32.46	−17.12	7.67

).

For age-0 trout, the top model (R²m = 0.4117, R²c = 0.5968) was 3.3 times more parsimonious than the next closest model (Temperature + Catchment + Habitat; Table 3). Within the top model, Julian day of the year (β = 16.12, 95% CI = 10.80 to 21.23) and degree days (β = 12.38. 95% CI = 1.58 to 23.04) had significant positive relationships with average age-0 trout body size (Figure 3; Appendix A 

Table A2. Fixed effects from global model of age-0 trout. Significant effects are in bold.

Fixed Effects	Estimate	Std Eror	T-Value	DF	LCI	UCI
Intercept	36.48	8.44	4.32	66.28	21.20	51.70
Julian day	16.12	2.85	5.65	119.83	10.80	21.23
Salmonid density	−2.91	3.63	−0.80	98.24	−9.39	3.65
Degree days	12.38	5.91	2.09	61.20	1.58	23.04
Temp. range	4.48	4.96	0.90	105.45	−4.44	13.58
Year-2017	3.27	3.77	0.87	122.54	−3.69	10.16
Year-2018	2.48	2.98	0.83	110.8	−3.01	8.00
Year-2019	8.22	3.10	2.65	114.27	2.40	13.88
Year-2020	0.64	3.09	0.21	118.08	−5.16	6.25
Year-2021	3.14	2.99	1.05	113.65	−2.42	8.60
Year-2022	0.95	3.80	0.25	120.23	−6.03	7.81
Catchment area	2.39	4.38	0.55	66.87	−5.50	10.43
Pool area	−3.45	3.69	−0.93	117.92	−10.16	3.25
Stream depth	2.83	4.41	0.64	122.78	−5.12	10.97
Boulders	3.47	3.18	1.09	49.32	−2.34	9.22
Key piece density	6.03	3.62	1.67	121.07	−0.45	12.83
Canopy shade	−3.13	6.25	−0.50	39.13	−14.44	8.20

).

The top model for age-1 or older coastal cutthroat trout (R²m = 0.2407, R²c = 0.5188) was 30.3 times more parsimonious than the next closest model (Temperature + Catchment + Habitat; Table 4). Within the top model, catchment area (β = 14.97, 95% CI 4.43 to 25.53) and pool area (β = 9.26, 95% CI 1.05 to 17.56) had significant positive relationships with average body size (Figure 3; Appendix A 

Table A3. Fixed effects from global model of age-1 or older coastal cutthroat trout. Significant effects are in bold.

Fixed Effects	Estimate	Std Eror	T-Value	DF	LCI	UCI
Intercept	120.13	12.14	9.90	123.71	97.78	142.33
Julian day	5.70	3.86	1.48	134.85	−1.37	12.77
Salmonid density	−9.38	4.34	−2.16	118.39	−17.36	−1.45
Degree days	−10.81	7.72	−1.40	69.16	−25.11	3.44
Temp. range	−0.29	5.76	−0.05	126.05	−10.89	10.25
Year-2017	−2.50	4.85	−0.52	134.94	−11.42	6.48
Year-2018	−2.88	3.64	−0.79	122.94	−9.59	3.90
Year-2019	−3.35	3.94	−0.85	132.22	−10.63	3.91
Year-2020	−4.06	3.88	−1.05	133.19	−11.22	3.09
Year-2021	−3.65	3.56	−1.03	129.84	−10.21	2.91
Year-2022	−5.67	5.02	−1.13	131.96	−14.88	3.57
Catchment area	14.97	5.69	2.63	75.09	4.43	25.53
Pool area	9.26	4.50	2.06	134.02	1.05	17.56
Stream depth	−0.79	5.22	−0.15	134.81	−10.37	9.05
Boulders	2.39	4.15	0.58	60.64	−5.25	10.04
Key piece density	−3.22	4.55	−0.71	130.72	−11.52	5.17
Canopy shade	−11.48	8.95	−1.28	130.66	−27.83	4.99

).

Julian day of the year emerged as the most important variable in models of average body size at sites in both the coho salmon and age-0 trout top models, with over 35% of individual contributions, but was among the least important variables for age-1 or older coastal cutthroat trout, only contributing 6.2% (Figure 4). Coho salmon had five variables (Julian day of the year = 35.7%, boulders = 19.1%, stream depth = 11.0%, salmonid density = 9.8%, and catchment area = 6.8%) collectively making up over 82% of the total individual contributions. Age-0 trout exhibited six variables (Julian day of the year = 42.1%, year = 22.0%, stream depth = 10.5%, degree days = 7.6%, and Key piece density = 5.3%) which constituted 88% of the total individual contributions. Age-1 or older coastal cutthroat trout had five predictors (catchment area = 43.0%, pool area = 13.0%, salmonid density = 11.8%, Julian day of the year = 6.2%, and year = 6.1%), comprising 80% of the total individual contributions.

4. Discussion

Our findings highlight the complex interplay of multiple indicators that determine the average body size of juvenile salmonids in natural environments. The best models for coho salmon, age-0 trout, and age-1 or older coastal cutthroat trout included significant variables from all four indicators: Density, Temperature, Catchment, and Habitat. Additionally, hierarchal partitioning revealed that each indicator had at least one variable contributing over 9% of the individual explanatory power of the models. Contrary to our hypothesis that stream temperature would have the greatest influence on fish body size, density had a greater influence than stream temperature on both coho salmon (9.8% for density compared to 3.3% for daily stream temperature range) and age-1 or older cutthroat trout (11.8% for salmonoid density compared to 5.2% for degree days). Additionally, both Catchment and Habitat indicators had metrics that were more important for coho salmon than stream temperature (6.8% for catchment area and 19.1% for boulders compared to 3.3% for daily stream temperature range) and age 1 or older cutthroat (43% for catchment area and 13% for pool area compared to 5.2% for degree days). However, the stream temperature metric degree days (95% CI 1.58 to 23.04) was the only significant variables outside of Julian day of the year in the age-0 trout model, providing some support for our hypothesis. Altogether, the overall support for the global model suggests that no single indicator dictates body size across sites. Other potentially important indicators such as nutrient concentration [78], prey availability [79], and current velocities [80] were unavailable for this analysis, and future studies that incorporate these indicators could provide additional insights about how these factors influence fish body size.

While the variable Julian day of the year was primarily used to account for the timing of surveys, it was by far the most important variable for two of our subjects, with significant relationships to average body size (coho salmon 9.20 to 19.85 95% CI and age-0 trout 10.80 to 21.23 95% CI) and the greatest individual influence (contributing 17–21% more than the next most important variable). In contrast, for age-1 or older coastal cutthroat trout, Julian day of the year was not significant (95% CI = −1.37 to 12.77) and contributed less than 6% to the top model. This may show that these larger fish have slower growth rates over the summer [81], or it may be the result of grouping multiple age classes of fish into one category. Additionally, sites with age-1 or older coastal cutthroat trout had relatively few large individuals (only 1% > 170 mm), also suggesting slow growth, the lack of older fish in these populations and increased juvenile migration, or the higher mortality of older individuals.

4.1. Catchment Size

Catchment area—positively correlated with bankfull width, a general measure of stream size—emerged as a key variable for age-1 or older coastal cutthroat trout, with 43.0% of the individual contribution to the top model. In contrast, it was relatively unimportant for age-0 trout (2.7%) and coho salmon (6.8%). This may be partially due to the larger size or longer freshwater resident times of age-1 or older cutthroat. Al-Chokhachy et al. [82] also identified a positive relationship between body size and stream size, attributing it to factors such as shorter growing season in typically colder headwater streams, increased foraging opportunities in larger streams, and reduced predator refuge in smaller streams. While our study’s narrower range in stream sizes may have limited the variation in growing season length between sites, differences in foraging opportunities and predator refuge may help to explain these patterns. Berger and Gresswell [83] reported a weak negative relationship between survival and body size in headwater streams, whereas Penaluna et al. [84] found that larger fish were more likely to survive avian threats than smaller fish in semi-natural modified stream channels. Fish movement from smaller to larger streams could also influence the average body size at the study sites. Additionally, small streams often have less instream shelter, and Penaluna et al. [85] observed that fish emigration increased with reduced cover. Reinhardt [86] found that higher predation risk can result in smaller fish. Larger streams also receive more light, potentially enhancing productivity and food availability [87]. However, in our models, canopy shade had only a 3–4% individual contribution under hierarchical partitioning and was not significant for any species or age-class.

The mechanisms linking catchment area and fish body size remain only partially understood and warrant further investigation. However, our findings suggest that reductions in stream width caused by the lower summer flows expected under climate change [17,18] may lead to smaller body sizes in age-1 or older cutthroat trout.

4.2. Density

Evidence for density dependence was apparent in coho salmon and age-1 or older cutthroat trout, with significant negative relationships between salmonid density and body size (95% CI = −16.12 to −2.79 and 95% CI = −17.36 to −1.45, respectively). Our findings align with Arismendi et al. [12], who also observed a negative relationship in coastal cutthroat trout. Density influences on fish body size are thought to be expressed in lower-density sites, whereas, in higher-density sites, density influences are thought to be expressed through mortality and migration [37]. Since our study focused on a class of streams designated as having “a moderate or slight fish” [88] use, the influences of density may be more pronounced in these streams because smaller streams within this designation are likely only marginally capable of supporting fish. Furthermore, historical timber harvest in these catchments has reduced fish habitat [13,89], potentially lowering the carrying capacity of streams and increasing the chances of density-dependent regulation of body size. The simplification of habitat resulting from the legacy influences of mid-20th century forest harvest as well as reduced summer flows associated with climate change could result in smaller, less complex streams and ultimately a high proportion of streams with lower densities and larger fish. These relationships highlight the complicated nature of fish growth with potentially competing influences, where we predicted both that reduced stream size would decrease body size and where lower densities in smaller streams may increase body size for age-1 or older cutthroat salmon. However, in our analysis the catchment area had a much larger influence than density (43.0% of the contribution from catchment area and 11.8% from salmonid density) on the age-1 or older cutthroat with a positive relationship between body size and catchment area (95% CI = −17.36 to −1.45), so, based on the more influential contribution of catchment area, we would expect an overall net decrease in fish size with reduced stream size for age-1 or older cutthroat trout. Restoration efforts targeting these streams may enhance their capacity and thus alleviate some of the impact of density dependence.

4.3. Stream Temperature

Stream temperature showed significant relationships with body size in juvenile coho salmon (daily stream temperature range; 95% CI = 1.85 to 19.12) and age-0 trout (degree days; 95% CI = 1.57 to 23.04), with positive associations with degree days, and stream temperature range. However, stream temperature had no significant relationships with age-1 or older coastal cutthroat trout body size. This may be due to the higher growth rates in young-of-year fish (age-0 trout and coho salmon) compared to older/larger fish [90]. These findings suggest that increasing stream temperature and variability could enhance body size in coho salmon and age-0 trout, highlighting potential influences of climate change. Juvenile coho salmon and age-0 trout may currently be more sensitive to stream temperature than age-1 or older coastal cutthroat trout, and their growth and body size likely to increase under warmer summer conditions projected with climate change [17,18].

Although stream temperature was not a significant factor for age-1 or older cutthroat trout, influences during earlier life stages could carry over as the fish matures. It is also possible that the apparent lack of significance for age-1 or older cutthroat or coho salmon was due to the limited range of stream temperatures in our study. Most sites were located in small streams within predominantly second-growth forests with dense canopy cover, where stream temperatures were generally within the optimal growth range of these species [56,69].

4.4. Physical Habitat

Habitat-related metrics significantly influenced body size in coho salmon and age-1 or older cutthroat trout, though specific metrics differed. Coho salmon body size showed a positive relationship with percent boulders (95% CI = 2.02 to 14.41), while age-1 or older coastal cutthroat body size had a positive relationship with pool area (95% CI = 1.05 to 17.56). Habitat showed less influence on age-0 trout; the highest contributing metric was stream depth, which contributed 10.5% to the top model and was not significant (95% CI = −5.12 to 10.97). This may be due to age-0 trout habitat preferences for shallow, low-velocity stream margins [91], potentially making them more responsive to factors like stream temperature.

Among habitat variables, the most surprising finding was the positive association between coho salmon body size and boulders (95% CI = 2.02 to 14.41). Boulders are typically more common in higher-gradient streams [92], which coho salmon are thought to avoid due to their preference for lower-gradient streams [93,94]. However, a study using boulder weirs for stream restoration showed that they could increase coho salmon abundance [95]. The authors cautioned that while boulders are a good starting point for stream restoration, long-term restoration would require the addition of instream wood from riparian areas. They attributed this positive influence from boulders to the role of boulders in increasing pool area. Boulders, similarly to pieces of instream wood, can create a diversity of flow velocities, creating areas for juvenile fish feeding and resting that could be beneficial for fish growth [96]. Boulders may partially substitute for some wood functions, such as providing fish cover, enhancing habitat and flow complexity, and storing water and sediment [92].

Thus, increasing pool habitat and fish cover with instream wood may more effectively address habitat degradation. It is possible that, within the more restricted range of coho salmon in our study (lower gradient streams) [97], the range of key pieces of wood and resulting pool area were so limited across all sites [69] that the importance of instream wood and pool area was not detected in our coho salmon models. Given coho salmon habitat preferences [98,99] and distribution [89] and the current conditions of these second growth forests [69], the recruitment and accumulation of large instream wood would likely support a more natural range of coho salmon body sizes. Nonetheless, our findings emphasize the value of boulders for coho salmon habitat in areas where they are naturally present.

5. Conclusions

Fish body size across streams is regulated by complex interactions among density, stream temperature, catchment size, and physical habitat. Contrary to our hypothesis that stream temperature would be the primary driver of fish size, density, catchment size, and physical habitat played a more significant role in shaping body size in coho salmon and age-1 or older cutthroat trout. However, stream temperature was a key driver for age-0 trout. Our findings highlight that both climate change and habitat degradation—particularly from the legacy impacts of historical timber harvest—may alter the natural range of body size variation across landscapes. These changes could have potentially cascading consequences for salmonid populations by influencing migration timing and reducing life history diversity. This, in turn, may impair the bet-hedging capacity of salmonid populations and their long-term viability.

Our results also emphasize the importance of physical habitat in regulating salmonid body size and suggest that management efforts should prioritize the preservation of key habitat features and the restoration of degraded ones, such as pools and instream wood. Restoration efforts that improve physical habitat—such as reconnecting floodplains, re-aggrading incised channels, or adding instream wood—can lower stream temperatures and expand pool area [100,101], potentially helping to mitigate reductions in fish body size. A deeper understanding of local habitat conditions in small streams will aid restoration efforts and support population resilience in the face of the dual challenges posed by climate change and habitat degradation.