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A novel approach to using seabed geomorphology as a predictor of habitat use in highly mobile marine predators : implications for ecology and conservation

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Date
19/04/2022
Author
Wyles, Hannah Maria Elizabeth
Boehme, Lars
Russell, Debbie JF
Carter, Matt I. D.
Funder
NERC
NERC
Grant ID
NE/R015007/1
NE/T010614/1
Keywords
Hidden Markov models (HMMs)
Movement ecology
North Sea
Geomorphons
Grey seal (Halichoerus grypus)
Satellite telemetry and tracking
GC Oceanography
NDAS
SDG 14 - Life Below Water
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Abstract
Understanding how marine predators find patchily distributed prey resources in a dynamic environment is key to identifying important ecological areas for ecosystem-level conservation management. However, the mechanisms underpinning important foraging areas often result from complex interactions between static and dynamic covariates (e.g. topography and currents). Modelling habitat associations with hydrodynamic processes is rarely useful when attempting to identify and characterise foraging areas across an individual’s foraging range. Investigating the influence of static habitat features on predator behaviour can provide a more tractable baseline understanding of habitat associations, upon which additional complexity can be added. Seabed gradient covariates (e.g. slope and aspect) are often used, yet such metrics are computed at singular user-defined resolutions, and provide limited ecological insight when used in isolation. Instead, categorising the seabed into geomorphological features may provide better characterisation of seabed structure. Here we explore the utility of a pattern recognition algorithm to delineate whole geomorphological features (“geomorphons”) on the seabed (e.g. valleys, ridges, footslopes) from bathymetry data, and examine the influence of geomorphology on marine predator habitat use. We demonstrate the potential application of this approach in a case study, examining the influence of geomorphons on the at-sea behaviour of a highly mobile predator inhabiting shelf seas: the grey seal (Halichoerus grypus). We analyse GPS tracking data from three seals tagged in the southern North Sea, an area with heterogeneous geomorphology. We use hidden Markov models (HMMs) to infer foraging and travelling behaviour and model the effect of different feature types on the probability of switching between states. All three seals showed an increased probability of transitioning from travelling to foraging when encountering slopes, footslopes and hollows, and foraging activity was concentrated at slopes on the fringes of the Dogger Bank. We hypothesise that such features may host prey aggregations, or lead to increased prey capture success. The results suggest the importance of such areas for grey seals in the southern North Sea, a region undergoing rapid and widespread anthropogenic habitat change. This method could be incorporated into future species distribution models to improve estimates of predator distribution, informing conservation management and marine spatial planning.
Citation
Wyles , H M E , Boehme , L , Russell , D JF & Carter , M I D 2022 , ' A novel approach to using seabed geomorphology as a predictor of habitat use in highly mobile marine predators : implications for ecology and conservation ' , Frontiers in Marine Science . https://doi.org/10.3389/fmars.2022.818635
Publication
Frontiers in Marine Science
Status
Peer reviewed
DOI
https://doi.org/10.3389/fmars.2022.818635
ISSN
2296-7745
Type
Journal article
Rights
Copyright © 2022 Wyles, Boehme, Russell and Carter. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Description
Department for Business, Energy, and Industrial Strategy (BEIS, formerly DECC) Offshore Energy Strategic Environmental Assessment programme funded the purchase of the tags and their deployment (OESEA-14-47) and supported HMEW (OESEA-20-118). DJFR was supported by NERC National Public Good- National Capability funding to SMRU (NE/R015007/1). MIDC was supported by project EcoSTAR, funded under NERC INSITE Phase II (grant no. NE/T010614/1). Funds for open access publication fees were from the research grants of supervisors at University of St Andrews.
Collections
  • University of St Andrews Research
URI
http://hdl.handle.net/10023/25209

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