Increasing numbers of harbour seals and grey seals in the Solent
Creators: name: Marley, Sarah
name: Castles, Robyne
name: Woods, Fiona
name: Hughes, Peter
name: Arnott, John
name: MacCallum, Louise
Publisher: name: Zenodo
Year: 2022
Subjects: marine biology
harbour seals
grey seal
photo-identification

description: Harbour seals (<i>Phoca vitulina</i>) and grey seals (<i>Halichoerus grypus</i>) both occur within the UK, but display regional contrasting population trends. Whilst grey seals are typically increasing in number, harbour seals have shown varying trends in recent decades following repeated pandemics. There is a need for monitoring of regional and local populations to understand overall trends. This study utilised a 20-year dataset of seal counts from two neighbouring harbours in the Solent region of south England. Generalised additive models showed a significant increase in the numbers of harbour (mean 5.3 to 30.5) and grey seals (mean 0 to 12.0) utilising Chichester Harbour. Conversely, in Langstone Harbour there has been a slight decrease in the number of harbour seals (mean 5.3 to 4.0). Accompanying photographic data from 2016-18 supports the increase in seal numbers within Chichester Harbour, with a total of 68 harbour and 8 grey seals identified. These data also show evidence of site fidelity of harbour seals in this area, with almost a quarter of animals resighted within the past three years. Overall, this long-term study indicates an increasing number of both harbour and grey seals within the Solent. However, more research is required to identify the drivers of this trend.
description: <i>"AllSealCounts.csv"</i> contains counts of harbour and grey seals collected during visual surveys in Chichester and Langstone Harbours, UK. <i>"SolentSeals.html"</i> presents the data exploration and analysis, with an extended example of applying GAMs to harbour seal counts in Chichester Harbour. <em>"SolenSeals.Rmd" </em>presents the RMarkdown code used to prepare SolentSeals.html "<i>SolentSealCatalogue.pdf</i>" contains photographs of all the individual seals recorded in this study, along with their sex (if known) and first sighting date.
description: <i>Study Area</i> The Solent is a sheltered channel system, separated from the English Channel by the Isle of Wight and stretching along the coastline of Hampshire and West Sussex (Figure 1). It includes numerous estuaries and natural harbours, the largest of which are Portsmouth, Langstone, and Chichester Harbours, which form a series of connected basins comprised of extensive intertidal mud and sand banks. Previous studies have confirmed that harbour seals utilise haul-outs in both Chichester and Langstone Harbours, moving between these sites via both the sea and a network of tidal channels (Chesworth et al., 2010). Grey seals have previously only been reported in a single sighting located within Chichester Harbour (Chesworth et al., 2010). <i>Data Collection</i> Visual surveys were undertaken in Chichester Harbour from 1999 to 2012 and 2015 to 2019, with surveys in Langstone Harbour from 2009 to 2017 and 2019 (Appendix 1). Surveys approximately overlapped with low tide, when the tidal mud flats were at their maximum availability for seal haul-outs. However, in some cases surveys were limited by poor weather. Pre-2015, data was collected on a monthly basis using a combination of boat- and land-based surveys and did not include estimates of seal age. Post-2015, field protocols at both sites were standardised to ensure the same methodology was consistently applied. This included: moving surveys to an entirely boat-based platform; conducting surveys concurrently at both harbours to remove the chance of individuals being counted twice; undertaking surveys at least once a month between May and September to capture the harbour seal pupping season (with additional months surveyed on an opportunistic basis); and recording the approximate age of individuals (adult, sub-adult/juvenile, or pup) where possible. It can be challenging to assign an age cohort from observation alone (except for newborn pups), especially for harbour seals; despite females having lower overall lengths at maturity, they display higher early growth rates than males (Hall et al., 2019). Hence sub-adults and juveniles were combined into one category. Regardless, age/sex data were not used in the present analyses beyond observation of pup numbers. Note that it was not possible to collect count data in Langstone Harbour during 2018. Additionally, boat-based photo-ID using a digital SLR camera and appropriate zoom lens was undertaken in Chichester Harbour from 2016 to 2018. Photo processing followed standard protocols (Yochem et al., 1990; Mackey et al. 2007; Hastings et al., 2008; Cunningham, et al., 2009; Cordes et al., 2015). In brief, photos were sorted by survey and allocated ratings based on their quality (i.e., clear focus, good lighting, head visible) for identifying pelage markings: Grade 1 (good quality), Grade 2 (sufficient), or Grade 3 (poor). Only Grade 1 and 2 photos were retained. Four independent reviewers manually compared images to identify individual seals based on unique pelage markings. 'New' individuals were allocated a sequential identification number and added to the catalogue. When individuals were resighted, the date was noted in a separate spreadsheet. <i>Data Analysis</i> Seal count data were analysed in R (R Core Team, 2019) for each species and site using Generalised Additive Models (GAMs, <i>mgcv </i>package, Wood, 2011) to allow smooth functions to be fitted to temporal covariates (Month and Year) based on results from exploratory analyses. Cyclic cubic splines were used for Month to ensure there was no discontinuity between January and December. To account for overdispersion, GAMs were fitted with a Tweedie distribution (Miller et al., 2013). Restricted maximum likelihood (REML) was used to minimise over-fitting (Wood, 2011). The best model was selected using Akaike's Information Criterion for small sample sizes (AICc; <i>MuMIn</i> package, Barton, 2020). Model assumptions were checked by producing standard residual diagnostic plots and an acf function was used to check for temporal autocorrelation (Zuur and Ieno, 2016). See 'Data Accessibility' section for a link to code used in these analyses.