Predicting the roles of anadromy and freshwater carry-over effects in the sustainability of threatened brown trout Salmo trutta populations

This PhD is based on developing new understandings on the ecology and conservation of brown/sea trout Salmo trutta. This is because human activities in freshwaters are driving major and unsustainable declines in freshwater biodiversity, with population reductions of over 80% since the 1970s. These declines in freshwater biodiversity are most apparent in species with complex lifecycles, especially diadromous fishes (lifecycles involving movements between freshwater and marine environments), with all 16 European mid- and long-distance migratory fishes suffering substantial population declines in recent decades. Returning populations of these species back to sustainable levels is thus a high conservation priority globally – but is highly challenging. However, developments in fish telemetry technologies now enable the tracking of migrations of individual fishes across key lifetime events. We are using brown/sea trout as our study specie because they are a strong example of an anadromous fish species experiencing recent and rapid population declines. A major impediment to

understandings of their declines is that their populations consist of both freshwater resident (non-migratory) and migratory (anadromous ‘sea trout’) forms, with the drivers of this divergent life history strategy remaining unclear. Whilst it is considered that anadromous females provide a greater reproductive contribution to the next generation than freshwater residents, but with trade-offs involving considerably higher energetic costs and mortality risks, why some individuals migrate when others remain river-resident remains a major knowledge gap. Although brown/sea trout population declines are considered to be strongly driven by reduced survival during the marine phase of their life cycle, freshwater carry-over effects could be strongly influencing subsequent marine survival. Developing new knowledge on how carry-over effects influence the ecology and population dynamics of brown/sea trout should strongly inform conservation actions in the river that could substantially improve marine survival rates. The aim of the PhD is to assess how key factors in the juvenile stages of brown trout in the river influence their subsequent life history strategy (e.g. non-migratory or anadromous), and the implications at individual levels for growth, behaviour, migrations (as timings (‘phenology’) and distances), and survival probability to spawning. It will use a long-term brown/sea trout dataset on the River Frome, Dorset, where in the last decade, juvenile trout at multiple sites across the catchment have been implanted with passive integrated transponder (PIT) tags and their movements tracked over their lifecycle using recapture events (non-migratory fish) and PIT tag detection systems in the lower river (migratory forms, detecting smolt emigration and adult immigration). Objectives include: (1) quantifying the age and length structure of the river-resident and anadromous components of the trout populations and assess the extent of their migratory behaviours (as phenology of emigration and return, duration of marine sojourn, and marine return rates); and (2) developing predictive models for simulating juvenile trout production, growth and

survival according to abiotic and biotic factors (and interactions), including the probability of individuals remaining river resident versus developing anadromy. The Frome dataset is comprised of over 30,000 juvenile trout that have been captured, measured, weighed, and PIT tagged across the catchment, with these fish subsequently recaptured in sampling events and/or detected on the PIT tag detectors as they migrate to sea as smolts in spring. Those fish that do emigrate as smolts spend between 30 days to several years in the marine environment before returning to the river where they are once more detected on the detectors. As PIT tagging enables individual identification, all data are at the individual fish level and the data previously collected (that will also be added to within the studentship) allow each objective to develop a series of relevant hypotheses that are tested through the development of powerful, multivariate models.