Periodic Reporting for period 2 - SAL-MOVE (Migration timing genotype as a predictor of salmon vulnerability to environmental change)
Okres sprawozdawczy: 2024-04-01 do 2025-03-31
As the climate changes, species increasingly experience mismatches between seasonally timed movements and conditions encountered. How and whether they can adjust their timing to overcome this mismatch depends on how it is shaped by genetics. The long-distance ocean and river migrations of Atlantic salmon (Salmo salar) are an example of such movements. Salmon spend the first part of their life in freshwater, then migrate out to the ocean where they feed and grow before returning to their home river to breed. To successfully complete this life cycle they need to match timing of their juvenile migration out to the ocean and their adult migration back to the river with conditions that enable their survival and reproductive success. By combining genetics, climate change projections and machine-learning, project SAL-MOVE aimed to predict how Atlantic salmon populations will be globally impacted by human-induced changes through their migration.
Results from this project can help manage and conserve populations of Atlantic salmon that are declining across their range, ensuring the sustainability of fisheries that support indigenous communities and local economies through tourism and fishing. The societal importance also extends to addressing complex environmental challenges through international collaboration, contributing to the preservation of biodiversity in a rapidly changing environment.
The three inter-related objectives of SAL-MOVE were:
O1: To identify the environmental correlates of Atlantic salmon run timing throughout the species’ range
O2: To characterise the genomic architecture of run timing throughout the species’ range
O3: To combine the outcomes of O1 and O2 in a modelling framework to predict the migration-mediated vulnerability of Atlantic salmon populations to future environmental change
To achieve these objectives, SAL-MOVE created a large network of Atlantic salmon researchers and biologists from 8 countries: Norway, Canada, Iceland, France, Finland, Ireland and the UK. This collaboration shared scientific resources, including genetic samples and data on migration timing for young salmon (smolts) and adults.
Results from this project can help manage and conserve populations of Atlantic salmon that are declining across their range, ensuring the sustainability of fisheries that support indigenous communities and local economies through tourism and fishing. The societal importance also extends to addressing complex environmental challenges through international collaboration, contributing to the preservation of biodiversity in a rapidly changing environment.
The three inter-related objectives of SAL-MOVE were:
O1: To identify the environmental correlates of Atlantic salmon run timing throughout the species’ range
O2: To characterise the genomic architecture of run timing throughout the species’ range
O3: To combine the outcomes of O1 and O2 in a modelling framework to predict the migration-mediated vulnerability of Atlantic salmon populations to future environmental change
To achieve these objectives, SAL-MOVE created a large network of Atlantic salmon researchers and biologists from 8 countries: Norway, Canada, Iceland, France, Finland, Ireland and the UK. This collaboration shared scientific resources, including genetic samples and data on migration timing for young salmon (smolts) and adults.
O1: Identifying the environmental correlates of Atlantic salmon run timing throughout the species’ range
Our results show that adult salmon migration timing or ‘run timing’ in North America have started occurring earlier over the past 29 years (1993-2021). Worryingly, the population that migrates the earliest is now at record low numbers.
We used climate data from the WorldClim database for each population and combined it with genetic findings from O2 to predict how vulnerable different salmon populations are to climate change (see O3).
O2: Characterising the genomic architecture of run timing throughout the species’ range
Although we had long-term records of when adult salmon returned, we did not have genetic samples for most of these fish. To overcome this, we used population-level return timing and linked it to population-level genetic differences. We did this for 11 North American salmon populations using a SNP array that scanned over 220,000 genetic markers.
We found many genes associated with migration timing. Some were already known from studies of European salmon, showing shared genetic traits across continents. Our findings also suggest that historical mixing between EU and North American populations at the end of the last Ice Age may have shaped these traits.
We then took a closer look at genetic differences using low-coverage whole genome sequencing on salmon from 7 North American populations. This more detailed analysis revealed a new genomic region strongly linked to migration timing. Interestingly, this region includes genes also associated with long-distance migration in birds, hinting at shared biological processes across species.
We also studied the genetics of “smolt migration” — the journey of young salmon from river to ocean. Thanks to our collaborators, we collected smolt samples from 10 rivers across 7 countries and recorded their migration dates. We genotyped the earliest and latest migrants using a 60K SNP chip to look for associations between genes and migration timing.
Given differences between North American and EU salmon, we analysed the continents separately. In EU populations, one genomic region stood out as being strongly linked to smolt migration and also linked to adult return timing. Early findings from North America suggest Ice Age population mixing may also have influenced smolt migration genetics.
O3: combining the outcomes of O1 and O2 in a modelling framework to predict the migration-mediated vulnerability of Atlantic salmon populations to future environmental change
Once we knew which genes influence migration timing and how this timing is shaped by the environment, we used machine-learning models to forecast how future climate conditions could threaten salmon. We calculated a "genomic offset", which is the gap between a population’s current genetic makeup and the genetic changes it would need to stay in sync with a changing climate.
In North America, we found no clear environmental link for early-migrating adults. But late-migrating and multi-peak populations showed strong genetic-environment links. Our models revealed that northern populations face the largest genomic mismatch, meaning they may struggle most to keep pace with climate change.
For smolts, we found no clear environmental link to their migration genes, so genomic offsets were not applied.
Our results show that adult salmon migration timing or ‘run timing’ in North America have started occurring earlier over the past 29 years (1993-2021). Worryingly, the population that migrates the earliest is now at record low numbers.
We used climate data from the WorldClim database for each population and combined it with genetic findings from O2 to predict how vulnerable different salmon populations are to climate change (see O3).
O2: Characterising the genomic architecture of run timing throughout the species’ range
Although we had long-term records of when adult salmon returned, we did not have genetic samples for most of these fish. To overcome this, we used population-level return timing and linked it to population-level genetic differences. We did this for 11 North American salmon populations using a SNP array that scanned over 220,000 genetic markers.
We found many genes associated with migration timing. Some were already known from studies of European salmon, showing shared genetic traits across continents. Our findings also suggest that historical mixing between EU and North American populations at the end of the last Ice Age may have shaped these traits.
We then took a closer look at genetic differences using low-coverage whole genome sequencing on salmon from 7 North American populations. This more detailed analysis revealed a new genomic region strongly linked to migration timing. Interestingly, this region includes genes also associated with long-distance migration in birds, hinting at shared biological processes across species.
We also studied the genetics of “smolt migration” — the journey of young salmon from river to ocean. Thanks to our collaborators, we collected smolt samples from 10 rivers across 7 countries and recorded their migration dates. We genotyped the earliest and latest migrants using a 60K SNP chip to look for associations between genes and migration timing.
Given differences between North American and EU salmon, we analysed the continents separately. In EU populations, one genomic region stood out as being strongly linked to smolt migration and also linked to adult return timing. Early findings from North America suggest Ice Age population mixing may also have influenced smolt migration genetics.
O3: combining the outcomes of O1 and O2 in a modelling framework to predict the migration-mediated vulnerability of Atlantic salmon populations to future environmental change
Once we knew which genes influence migration timing and how this timing is shaped by the environment, we used machine-learning models to forecast how future climate conditions could threaten salmon. We calculated a "genomic offset", which is the gap between a population’s current genetic makeup and the genetic changes it would need to stay in sync with a changing climate.
In North America, we found no clear environmental link for early-migrating adults. But late-migrating and multi-peak populations showed strong genetic-environment links. Our models revealed that northern populations face the largest genomic mismatch, meaning they may struggle most to keep pace with climate change.
For smolts, we found no clear environmental link to their migration genes, so genomic offsets were not applied.
This study is the first to uncover the genetic connections not only to the timing of the adult Atlantic salmon migration in North America, but also to smolt outmigration across their entire range. Using advanced genetic tools, we pinpointed key regions of the genome that underlie these important behaviours. For adults, we found genes also known to influence migration in birds—an unexpected discovery that sheds light on migration across vertebrates. For smolts, we uncovered the first ever genetic link to migration timing, offering new insight into how smolt migration begins.
This genetic knowledge allows us to predict how salmon populations might respond to climate change. Our models show that northern populations may be at highest risk. This is crucial information for conservation, helping us prioritise which populations need the most support.
The project’s findings are already informing conservation and fisheries management. They help protect local economies and deepen our understanding of how climate change impacts migratory patterns. Our discovery that smolt migration timing has a genetic basis also means that adjusting to climate change may not be easy for these fish.
We have also made major strides in public engagement. A public seminar about SAL-MOVE drew strong interest—543 people expressed interest, 86 registered, and 42 attended live. The session was recorded and shared on our university’s website, making it accessible to many more. This response highlights the public’s interest in salmon conservation and the importance of including people in conservation efforts.
Overall, our research has broad implications for understanding and addressing the challenges of climate change. By fostering interdisciplinary research and innovative ideas, we will continue to work with stakeholders to develop effective strategies for adapting to a changing environment.
This genetic knowledge allows us to predict how salmon populations might respond to climate change. Our models show that northern populations may be at highest risk. This is crucial information for conservation, helping us prioritise which populations need the most support.
The project’s findings are already informing conservation and fisheries management. They help protect local economies and deepen our understanding of how climate change impacts migratory patterns. Our discovery that smolt migration timing has a genetic basis also means that adjusting to climate change may not be easy for these fish.
We have also made major strides in public engagement. A public seminar about SAL-MOVE drew strong interest—543 people expressed interest, 86 registered, and 42 attended live. The session was recorded and shared on our university’s website, making it accessible to many more. This response highlights the public’s interest in salmon conservation and the importance of including people in conservation efforts.
Overall, our research has broad implications for understanding and addressing the challenges of climate change. By fostering interdisciplinary research and innovative ideas, we will continue to work with stakeholders to develop effective strategies for adapting to a changing environment.