In Alaska, the coho salmon undergoes a typical two-year rearing process in streams, which potentially renders them more vulnerable to fluctuations in hydrologic patterns compared to other Pacific salmon populations. The primary factors that directly impact coho salmon are anticipated to be increased water temperatures and alterations in flow patterns. Deviations from the historically observed range of variability during the freshwater life stages can have detrimental effects on the productivity of these salmon. The aim of this study was to predict the potential impact of climate-induced alterations in streamflow and temperatures during the early stages of freshwater life on a population of coho salmon in the Chuitna watershed in southcentral Alaska. Furthermore, the study aimed to determine how these changes would influence smolt production over a period of 20 years.
“Fig 1. Map of the Chuitna watershed (Alaska, USA) showing the location of three subwatersheds within the study area (thick black lines) and Chuitna streams (thin grey lines) as well as the location of the watershed in south central Alaska”.
To incorporate climate change scenarios into the coho salmon life-cycle model for the Chuitna Watershed, the authors utilized historical data and five future climate scenarios. These scenarios were based on information obtained from an integrated hydrologic model specific to the watershed. Climate change projections for Alaska were derived from a collection of 21 general circulation models that employed the A1B emissions scenario, reflecting medium to low cumulative carbon dioxide emissions, as outlined in the IPCC's Fourth Assessment Report. The selected scenarios considered the maximum and minimum predicted changes in air temperature (Tmax, Tmin) and precipitation (Pmax, Pmin), as well as the median changes in both (T50/P50).
To evaluate the response of salmon populations to hydrological changes, they required a flexible population model framework capable of incorporating subwatershed-scale hydrologic model output, future climate scenarios, specific habitat requirements, and stream habitat measurements. Following an existing framework established (by Scheuerell et al. (2006) and Battin et al. (2007)), the authors constructed a model using the R statistical platform that was specifically parameterized for the life cycles of Alaskan coho salmon. The model was run for a 20-year period spanning the end of the century (2080-2100), allowing them to track changes in smolt abundance. This final freshwater life stage integrates mortality across the entire freshwater period.
“Fig 2. The Chuitna coho life-cycle model flow diagram showing the possible life histories. Solid gray circles represent life stages modeled, dashed gray circles represent intermediate life stages not modeled and black arrow signifies the different individual pathways”.
In the model above, the authors accounted for individuals existing in seven life stages (refer to Fig. 2.)
Eggs: Individuals present in the gravel from October 1st to April 30th.
Fry 0.x: Individuals in freshwater from May 1st of year 1 to May 31st of year 2.
Parr 1.x: Individuals transitioning to parr stage after one year in freshwater.
Smolt 1.x and 2.x: Individuals that undergo smolting after one or two years in freshwater.
Jack 1.0 and 2.0: Precocious males that return to spawn in the same year as smolting after one or two years in freshwater.
Adult 1.1 and 2.1: Individuals that spend one full year at sea after one or two years in freshwater.
Spawners: Individuals that return to freshwater between July 15th and September 30th.
In order to determine the flow volume that triggered the movement of streambed materials and resulted in a decrease in egg-to-fry survival, we utilized Alaska-specific techniques for estimating 2-year peak streamflow values for each subwatershed, even in ungauged watersheds. As an illustration, in the middle creek subwatershed, the egg-to-fry survival rate reached its highest value (0.65) when the flow remained below 7.16 m³/s (2-year peak streamflow). However, as the flow increased, the survival rate declined linearly, reaching a minimum of 0.01 when flows exceeded 24.45 m³/s (100-year peak streamflow).
Survival values for various life stages were obtained or calculated using available data from southeast Alaskan coho populations and southcentral Alaska-based studies. For survival values not estimated through functional relationships, existing data were utilized. Exploitation rates were averaged from four streams over the period of 1982-2010 (Skannes et al., 2012). Long-term marine survival rates were estimated using data from seven wild stocks spanning from 1982 to 2007 (Shaul et al., 1991, 2008). Fry survival rates were estimated based on a 3-year period (Crone & Bond, 1976).
Smolt 1.x survival was calculated by back calculating the required number of smolts and fry from a specific cohort of returning adults using the provided information. The number of smolts was divided by the number of fry to obtain a survival value (Eqn S5). Parr 1.x survival was calculated by dividing the calculated smolt 1.x survival by the ratio of average juvenile-to-Ocean 1 survival to smolt-to-Ocean 1 survival (Eqn S7). Smolt 2.x survival was calculated using juvenile-to-adult survival rates (Shaul et al., 1991) and smolt-to-adult survival rates for southeast Alaska (Shaul et al., 2008). Survival rates for Jack, adult 1.1, and adult 2.1 were estimated using long-term marine survival rates from various watersheds in southeast Alaska (Shaul et al., 2008), adjusting the rates based on the duration of time spent at sea.
Capacity values for adult and juvenile life stages were estimated based on site-specific relationships between habitat area and juvenile coho density estimates, following the approach of Nickelson et al. (1992) as described by Bartz et al. (2006). Egg capacity was estimated using escapement values from 2008 (Nemeth et al., 2009), assuming that approximately 50% of escapement represents females and each female contributes to one redd. To calculate capacities for fry, parr, and smolt, the area (length × wetted width) of pool, riffle, and glide habitats within the entire subwatershed was estimated, multiplied by habitat-specific rearing densities (Nickelson et al., 1992). In accounting for the inverse relationship between territory and fish length (Grant & Kramer, 1990), density values previously estimated (Nickelson et al., 1992) were assigned to the respective juvenile life stages (parr 1.x and parr 2.x)
Furthermore, a sensitivity analysis was conducted to assess the impact of changes in input parameters on the predicted number of smolts and spawners. Survival or capacity for different life stages (spawner, egg, fry, parr, smolt, and adult) were systematically modified by two percent while keeping other variables constant
The findings from the model indicate that elevated peak flows during the incubation period of salmon eggs could have a significant detrimental effect on egg survival and, consequently, smolt production. This observation aligns with the identification of increased peak flows during incubation as a key factor contributing to projected declines in Chinook salmon populations as well. High peak flows have the potential to physically disrupt salmon redds, leading to the crushing or displacement of eggs. However, the impact of such flows depends on factors like egg pocket depth and spawning substrate. This long-term effect is particularly noteworthy because, unlike temperature changes that can be mitigated through behavioral responses or natural selection, salmon may have limited ability to evade or adapt to widespread and unpredictable physical disturbances due to their specific requirements for spawning habitat.
In Alaska, the coho salmon undergoes a typical two-year rearing process in streams, which potentially renders them more vulnerable to fluctuations in hydrologic patterns compared to other Pacific salmon populations. The primary factors that directly impact coho salmon are anticipated to be increased water temperatures and alterations in flow patterns. Deviations from the historically observed range of variability during the freshwater life stages can have detrimental effects on the productivity of these salmon. The aim of this study was to predict the potential impact of climate-induced alterations in streamflow and temperatures during the early stages of freshwater life on a population of coho salmon in the Chuitna watershed in southcentral Alaska. Furthermore, the study aimed to determine how these changes would influence smolt production over a period of 20 years.
“Fig 1. Map of the Chuitna watershed (Alaska, USA) showing the location of three subwatersheds within the study area (thick black lines) and Chuitna streams (thin grey lines) as well as the location of the watershed in south central Alaska”.
To incorporate climate change scenarios into the coho salmon life-cycle model for the Chuitna Watershed, the authors utilized historical data and five future climate scenarios. These scenarios were based on information obtained from an integrated hydrologic model specific to the watershed. Climate change projections for Alaska were derived from a collection of 21 general circulation models that employed the A1B emissions scenario, reflecting medium to low cumulative carbon dioxide emissions, as outlined in the IPCC's Fourth Assessment Report. The selected scenarios considered the maximum and minimum predicted changes in air temperature (Tmax, Tmin) and precipitation (Pmax, Pmin), as well as the median changes in both (T50/P50).
To evaluate the response of salmon populations to hydrological changes, they required a flexible population model framework capable of incorporating subwatershed-scale hydrologic model output, future climate scenarios, specific habitat requirements, and stream habitat measurements. Following an existing framework established (by Scheuerell et al. (2006) and Battin et al. (2007)), the authors constructed a model using the R statistical platform that was specifically parameterized for the life cycles of Alaskan coho salmon. The model was run for a 20-year period spanning the end of the century (2080-2100), allowing them to track changes in smolt abundance. This final freshwater life stage integrates mortality across the entire freshwater period.
“Fig 2. The Chuitna coho life-cycle model flow diagram showing the possible life histories. Solid gray circles represent life stages modeled, dashed gray circles represent intermediate life stages not modeled and black arrow signifies the different individual pathways”.
In the model above, the authors accounted for individuals existing in seven life stages (refer to Fig. 2.)
Eggs: Individuals present in the gravel from October 1st to April 30th. Fry 0.x: Individuals in freshwater from May 1st of year 1 to May 31st of year 2. Parr 1.x: Individuals transitioning to parr stage after one year in freshwater. Smolt 1.x and 2.x: Individuals that undergo smolting after one or two years in freshwater. Jack 1.0 and 2.0: Precocious males that return to spawn in the same year as smolting after one or two years in freshwater. Adult 1.1 and 2.1: Individuals that spend one full year at sea after one or two years in freshwater. Spawners: Individuals that return to freshwater between July 15th and September 30th.
In order to determine the flow volume that triggered the movement of streambed materials and resulted in a decrease in egg-to-fry survival, we utilized Alaska-specific techniques for estimating 2-year peak streamflow values for each subwatershed, even in ungauged watersheds. As an illustration, in the middle creek subwatershed, the egg-to-fry survival rate reached its highest value (0.65) when the flow remained below 7.16 m³/s (2-year peak streamflow). However, as the flow increased, the survival rate declined linearly, reaching a minimum of 0.01 when flows exceeded 24.45 m³/s (100-year peak streamflow).
Survival values for various life stages were obtained or calculated using available data from southeast Alaskan coho populations and southcentral Alaska-based studies. For survival values not estimated through functional relationships, existing data were utilized. Exploitation rates were averaged from four streams over the period of 1982-2010 (Skannes et al., 2012). Long-term marine survival rates were estimated using data from seven wild stocks spanning from 1982 to 2007 (Shaul et al., 1991, 2008). Fry survival rates were estimated based on a 3-year period (Crone & Bond, 1976). Smolt 1.x survival was calculated by back calculating the required number of smolts and fry from a specific cohort of returning adults using the provided information. The number of smolts was divided by the number of fry to obtain a survival value (Eqn S5). Parr 1.x survival was calculated by dividing the calculated smolt 1.x survival by the ratio of average juvenile-to-Ocean 1 survival to smolt-to-Ocean 1 survival (Eqn S7). Smolt 2.x survival was calculated using juvenile-to-adult survival rates (Shaul et al., 1991) and smolt-to-adult survival rates for southeast Alaska (Shaul et al., 2008). Survival rates for Jack, adult 1.1, and adult 2.1 were estimated using long-term marine survival rates from various watersheds in southeast Alaska (Shaul et al., 2008), adjusting the rates based on the duration of time spent at sea. Capacity values for adult and juvenile life stages were estimated based on site-specific relationships between habitat area and juvenile coho density estimates, following the approach of Nickelson et al. (1992) as described by Bartz et al. (2006). Egg capacity was estimated using escapement values from 2008 (Nemeth et al., 2009), assuming that approximately 50% of escapement represents females and each female contributes to one redd. To calculate capacities for fry, parr, and smolt, the area (length × wetted width) of pool, riffle, and glide habitats within the entire subwatershed was estimated, multiplied by habitat-specific rearing densities (Nickelson et al., 1992). In accounting for the inverse relationship between territory and fish length (Grant & Kramer, 1990), density values previously estimated (Nickelson et al., 1992) were assigned to the respective juvenile life stages (parr 1.x and parr 2.x) Furthermore, a sensitivity analysis was conducted to assess the impact of changes in input parameters on the predicted number of smolts and spawners. Survival or capacity for different life stages (spawner, egg, fry, parr, smolt, and adult) were systematically modified by two percent while keeping other variables constant
The findings from the model indicate that elevated peak flows during the incubation period of salmon eggs could have a significant detrimental effect on egg survival and, consequently, smolt production. This observation aligns with the identification of increased peak flows during incubation as a key factor contributing to projected declines in Chinook salmon populations as well. High peak flows have the potential to physically disrupt salmon redds, leading to the crushing or displacement of eggs. However, the impact of such flows depends on factors like egg pocket depth and spawning substrate. This long-term effect is particularly noteworthy because, unlike temperature changes that can be mitigated through behavioral responses or natural selection, salmon may have limited ability to evade or adapt to widespread and unpredictable physical disturbances due to their specific requirements for spawning habitat.