IAP-25-079

Modelling effects of climate change on future kelp habitats and associated commercial fisheries

Kelp habitats are among the most productive marine ecosystems, providing critical ecological functions globally (Duarte 2017). They support high biodiversity and serve as nurseries for many ecologically and commercially important species (Jayathilake & Costello, 2021; Smale et al., 2013). Many fisheries depend on these habitats for the recruitment and survival of key species such as lobsters, crabs, and finfish, which in turn sustain coastal communities (Kemp 2023). However, kelp ecosystems face growing threats from climate change, including ocean warming, acidification, and storms, as well as local pressures like pollution and coastal development (Farrugia Drakard et al., 2023; Wear et al., 2023).

In the United Kingdom, substantial kelp habitats occur on shallow rocky reefs across all countries, particularly around the Scottish isles, the northeast and southwest coasts of England, and southwest Wales, all of which support fisheries for commercially important species (Smale 2022). Future climate scenarios are expected to drive significant shifts in the global distribution of kelp species and widespread regional reorganisation of kelp communities (Assis et al., 2024). However, little research in the UK has examined where fisheries associations are strongest, where they break down, and what ecological thresholds may signal the risk of fishery decline. This lack of evidence limits the ability of current management to safeguard both kelp ecosystems and the fisheries that depend on them (Hamilton 2022).

Species Distribution Models (SDMs) are widely used to predict the distribution of marine species and are increasingly applied to estimate population density. SDMs can predict future distributions under different climate scenarios, offering critical insights into how distributions and abundance may respond to environmental change (Zelli et al., 2025). They are powerful tools for informing policy, management, and evaluating fisheries health. However, their reliability depends on the availability of high-quality observational data and associated environmental variables (Elith and Leathwick, 2009). While fisheries data are available and offer some insight into species distributions, they are typically aggregated at broad spatial scales that encompass multiple habitats and are also influenced by species life history traits, fishing effort and location (Smale et al 2022).

This project aims to fill important gaps in our understanding of kelp associated fishery responses to climate change by: 1) developing SDMs to model kelp associated commercially important invertebrate and fish taxa; 2) validating and refining these models using fishery independent data, which will be collected from study sites around the UK; 3) exploring the responses of kelp habitats and associated fisheries to predicted climate changes.

By collecting high quality data and subsequent statistical modelling the student will work to develop the understanding on commercial marine species and kelp associations. A strong partner network of end-users will ensure the relevance of the study and generate real-world impact from the work.

The student will identify UK wide substrate data, and assemble species data focussing on data for presence and absence (and where available, abundance) of relevant kelp species on rocky reef habitats from e.g. Fish Glob (Maureaud 2021), the NBN Atlas (https://nbnatlas.org/); the UK Archive for Marine Species and Habitats Data (DASSH) (https://www.dassh.ac.uk/); the UK Joint Nature Conservation Committee (JNCC) Marine Nature Conservation Review (MNCR, 1977-1998); Seasearch surveys (https://www.seasearch.org.uk/); and other camera or dive surveys collected by organisations including the Centre for Environment, Fisheries and Aquaculture Science (CEFAS), universities, and non-departmental public bodies (e.g. NatureScot, Natural England).

They will produce preliminary SDMs of kelp-associated, commercially important invertebrate and fish taxa. The number of study taxa will depend on data availability, but a range of species that associate with kelp at different life stages and/or in different ways (e.g. for predation, shelter, or movement) will be selected to explore the varying relationships and potential impacts of kelp loss or degradation. Taxa likely to have sufficient data and representing different types of kelp habitat associations include: Cod (Gadus morhua), Pollack (Pollachius pollachius), Ballan wrasse (Labrus bergylta), Spiny dogfish (Squalus acanthias), European clawed lobster (Homarus gammarus), Brown crab (Cancer pagurus), and Sea urchin (Echinus esculentus).An experimental design for the in-situ observations will then identify data poor regions (based on data points and the spatial patterns of uncertainty from the SDMs) and select sites that allow the team to target kelp density gradients (no kelp (control), sparse, intermediate, dense). The student will explore associated invertebrate and fish communities, collecting e.g. species diversity and abundance data, and kelp quality and extent data. This will involve undertaking surveys along the proposed kelp density gradients, using scuba, drop down cameras and/or baited remote underwater video (BRUV) systems. Kelp quality and extent will be mapped using acoustic methods developed in conjunction with the CASE partner. To investigate the impacts on abundance seasonal studies will be undertaken.

Once these data gaps are filled, SDMs will be refined and predictions of distribution and abundance for the target taxa will be undertaken under several climate scenarios . Climate scenarios will follow the IPCC’s Shared Socioeconomic Pathways (SSPs), using SSP2-4.5 to represent a moderate “middle-of-the-road” trajectory (~2.7 °C warming by 2100) and SSP5-8.5 to represent an extreme, high-emissions scenario (~4.4 °C warming by 2100). The SDMs will include the biotic association of kelp density to improve predictive performance; an approach shown to significantly enhance model accuracy and explanatory power (Stephenson et al., 2022). Incorporating this relationship will be critical for developing “conditional” predictions under future climate scenarios; that is, assessing how species distributions may change in response to environmental variables (e.g. water temperature) and associated shifts in kelp density or distribution. This novel approach will provide more accurate and holistic predictions of changes in commercially important taxa under future environmental conditions.

There will also be options for the student to develop the project, depending on the research interests of the successful candidate, to potentially include economic impacts on associated commercial fisheries, scaling up the results using modelling approaches to European or Global kelp habitats, exploring future fishing scenarios etc.

Year 1

The first 6 months will be used to conduct a desk study to collate the available data on kelp and commercial fisheries associations nationwide, with the overall aim of publishing a literature review.

The following 6 months of the PhD will draw on the desk study, working to collect data to populate SDMs and identify data poor areas, using these to drive a detailed experimental design. The student will likely focus on collecting data on the continuum of kelp habitat quality and species associations as described above.

Year 2

Year 2 will focus on data collection and the delivery of scuba, drop-down camera or BRUV surveys to validate and refine the SDMs. This will allow fine scale models to be developed.

Four sites at data poor regions around the UK will be surveyed. Each site will be surveyed once in July or August, and again once in winter.

Once collected diversity and abundance data will be used to improve modelling of the associations and distributions of commercially important species and kelp habitats across the UK. These models will be used to generate distribution and density estimates for publication. Additional fieldwork may be undertaken to supplement data-poor regions.

Year 3

During the first six months of Year 3, the student will prepare a publication based on data from Years 1 and 2, before developing future scenarios, which may include modelling the effects of climate change and/or no-take zones on kelp-associated commercial species. The second half of the year will be devoted to drafting a policy document for a specific species, using model outputs to evaluate the feasibility of management measures.

Year 3.5

The final 6 months of the PhD will involve completing the thesis and preparing the remaining papers for publication.

The student will receive training in the analysis of spatial data, statistical analysis, modelling, experimental design and field and laboratory techniques. In addition, they will develop skills in project management, communication to a varied audience, teamwork and networking.