IAP-26-112

Depth Effects on Functional Homogenisation, Turnover, and Network Connectivity of Coral Reef Fish

Marine heatwaves and shallow habitat degradation are reshaping coral reef fish communities. As species and traits are lost or replaced, functional structure and the trophic links between species erode, driving functional homogenisation and network decomposition that undermine the ecosystem functions reefs support (Richardson et al. 2018). Potential rescue effects, including through deeper mesophotic reefs (~30–120 m) acting as refuges (Bongaerts et al. 2010), require functional and network connectivity between assemblages. Yet depth is itself a strong filter: mesophotic fish assemblages are ecologically distinct and assembled by different rules (Rocha et al. 2018; Pinheiro et al. 2023). Whether deep reefs can buffer shallow-water change, or instead mirror or amplify it, depends on how functional structure and trophic links are organised along the depth gradient and across ocean basins. These questions have not been addressed beyond single locations or time points.

Developed in concert with a UKRI NERC Independent Research Fellowship, this PhD asks whether depth can rescue reef function, working through time, across space and through food webs, and drawing on two rare resources: a depth-stratified baseline of reef fish and benthos from the surface to 40 m at eleven reefs in Kimbe Bay, Papua New Guinea, surveyed three times since 2013 before repeated marine heatwaves (MacDonald et al. 2016; Versteeg et al. 2025); and the Multi-Gradient reef Fish Abundance (MGFA) dataset — >150,000 fishes of 885 species, 0–120 m, at >70 sites spanning 25,000 km from the Western Pacific to the Eastern Atlantic.

Objective 1 — Does heatwave-driven functional homogenisation attenuate with depth? Three competing hypotheses: depth refuge — homogenisation weakens as coral loss and thermal stress attenuate with depth; fragile deep — low functional redundancy leaves deep assemblages equally vulnerable despite less habitat change; redistribution — shallow functional entities shift deeper, eroding distinctness among depths rather than within them.

Objective 2 — Does depth interact with longitude to shape distance decay of functional structure? We predict flatter distance decay of functional dissimilarity among mesophotic than shallow assemblages, reflecting convergent filtering at depth, and stronger functional turnover between depths near the Indo-Australian biodiversity centre, where rich species pools support depth specialists, weakening towards depauperate peripheries. Pilot MGFA analyses already show divergent assembly along interacting depth and longitude gradients.

Objective 3 — Are reef fish food webs robust to species loss along the depth gradient? Marine food webs appear globally connected (Albouy et al. 2019) but have never been resolved across depth, where species and trophic groups are replaced. We predict greater modularity, discontinuities between shallow and mesophotic networks, and lower robustness of deep networks to species loss.

Dr Chancey MacDonald (Newcastle) will provide training in mesophotic field methods, scientific diving, functional ecology and Bayesian modelling, with co-supervision by Prof. Anne Magurran (St Andrews), a world expert in biodiversity research. Further collaborators will provide training in network analysis.

The project combines SCUBA surveys with global-scale analyses in R; two objectives use existing data, protecting the thesis against field disruption.

Objective 1.
Based at Mahonia Na Dari Research and Conservation Centre, the student will resurvey the Kimbe Bay sites in a single field season in Year 1 using the published video-transect protocol and paired benthic categories (MacDonald et al. 2016). With 2027/28 post-heatwave surveys, this gives a five-point time series resolving whether change is continuing or recovering. Species will be assigned to functional entities from six traits (body size, diet, water-column position, mobility, schooling, activity). Functional richness, redundancy and vulnerability (Mouillot et al. 2014), and temporal functional beta diversity within and among depths, will be modelled against measured benthic change in Bayesian hierarchical models, testing mechanism rather than inferring it from depth.

Objective 2.
Using the MGFA dataset and existing multiply-imputed trait data, the student will calculate pairwise functional dissimilarity among assemblages within and across depth zones (0–30, 30–60, 60–120 m), partitioned into turnover and nestedness components (Baselga 2010; Villéger et al. 2013) Distance-decay relationships will be modelled with Bayesian mixed models (brms) including interactions between geographic distance, depth and longitudinal position, with null models separating functional from taxonomic turnover.

Objective 3.
Trophic interactions among MGFA species will be inferred from phylogenetic and body-size models (Parravicini et al. 2020), validated against gut-content DNA metabarcoding of fishes collected at 18–90 m in Moorea within the Fellowship. The student will quantify connectance, nestedness and modularity of every assemblage food web along depth, latitude and longitude, identifying distance decay and discontinuities. Robustness will be tested by simulated extinctions (Dunne et al. 2002) — fishing-targeted, narrowest thermal niche and random species — and by reassembly under climate-driven vertical and poleward shifts. Species losses observed in Kimbe Bay provide an empirical test of these simulations. Should imputation perform poorly at depth, MGFA co-occurrence networks provide a fallback needing no new data.

Year 1

Literature review of functional homogenisation and the deep reef refuge hypothesis (manuscript 1).
• Training in scientific diving, reef fish identification and video survey methods; field season in Kimbe Bay, PNG.
• Training in functional diversity and Bayesian modelling; begin Objective 2 analyses on the MGFA dataset.
• Video and benthic analysis from the field season.

Year 2

• Complete Objective 1 analyses of the full Kimbe Bay time series (manuscript 2).
• Complete Objective 2 analyses (manuscript 3); present at a national conference.
• Training in ecological network analysis; build depth-explicit food webs (Objective 3).

Year 3

• Objective 3 network structure and robustness simulations; present at an international conference.

Year 3.5

• Preparation of manuscript 4 (Objective 3).
• Thesis completion.

The student will train in scientific diving to 40 m within Newcastle University’s diving programme, overseen by the primary supervisor as University Diving Officer — nitrox and twin-cylinder diving, dive planning, risk assessment and emergency oxygen — alongside underwater video surveys and identification of one of the richest reef fish faunas on Earth.

Analytical training covers functional diversity, beta-diversity partitioning, network analysis, Bayesian hierarchical modelling (brms/Stan) and reproducible workflows on high-performance computing — skills in demand across consultancy, conservation and data science. Newcastle’s postgraduate workshops, scientific writing, presentation, peer mentoring and an international collaborator network complete the training.

Theoretical skills will be mentored in biodiversity assembly, trait abundance distributions and network composition as tools for understanding disturbance effects and community assembly.

In Papua New Guinea the student will help deliver Mahonia Na Dari’s education programme for local school children and report results to the Kobognade Locally Managed Marine Area, whose customary tenure covers the survey reefs.