National Marine Monitoring Scheme
In order to better monitor inshore biodiversity the an effort based monitoring scheme – Adopt-a-Site was launched in 2016. The Scheme consists of 17 sites monitored once a month over 5 months (May-September) and to the end of 2017 has collected 2,652 records of 209 species. The Adopt a Site scheme is aimed at clubs, dive centres and individual divers and training is organised locally on request. For more information on organising an Adopt a Site training session for your club or local dive group email NMMSIrl@gmail.com.
Rationale for Adopt-a-Site: A problem with the Seasearch Ireland data?
Seasearch data is useful in terms of atlas projects, for monitoring distribution of rare but relatively simple to identify species across Ireland and provides a baseline for species distribution and abundance of a large number of species that are not monitored through any other means. However in its current format the Seasearch data cannot be used detect trends in the status of individual species or map true distribution as absence is difficult to quantify due to differences in sampling effort.
Atlas projects are dependent on the quality and quantity of data received and, while statistical analyses can compensate for some of the problems arising from a lack of standardisation in sampling effort (Robertson et al. 2010), a more robust sampling framework would benefit the collection of Seasearch data.
In particular, the issue arises that data providers range from professional marine biologists, (some of whom are experts in specific taxonomic groups), to absolute novices who can identify a small range of relatively common species. Thus any analysis of the Seasearch Ireland data set requires a large amount of filtering of records on an already limited data set.
4 sources of variation in recording effort were identified by Isaac et al. (2014):
- Uneven recording intensity over time (number of visits per site per year).
- Uneven spatial coverage.
- Uneven sampling effort per visit.
- Uneven detectability of species.
All 4 of these variations are present in the Seasearch Ireland data set:
- Recording effort per year has risen and fallen over the course last 7 years in Ireland;
- Spatial coverage of sites is largely based on proximity to recorders and location of courses;
- Sampling effort per visit is based on recorders identification skills; and
- Detectability of species is likely to be highly variable taking into account factors such as underwater visibility, size of species, timing of the tides and time of year (in addition to being based on ability of recorders to accurately identify species).
Thus while the existing Seasearch framework can provide useful data and improvements can potentially be made in the quality and quantity of data a new approach is needed to achieve a scientifically robust system for monitoring marine ecosystems.
A National Marine Monitoring Scheme…
A number of schemes exist that use divers to monitor individual sites (e.g. REEF Check and Seasearch Australia) but use transects and formalised survey methodologies requiring specialist training and equipment. The Victoria based Seasearch, Australian initiative run by the Parks service in Victoria, requires 4 divers to complete a survey with the Seasearch Manual running to 91 pages (Seasearch, 2013) and thus requires a level of participation and training that is unduly onerous for ‘citizen scientists’ and a volunteer organisation.
Our scheme allows us to adopt a more informal survey methodology combining the existing Seasearch methodology with a list of bench mark species to be monitored at each site. Sites are selected by participants themselves to facilitate repeat sampling. “Recorder minutes” are used to standardise effort with the number of recorders and the length of survey measured (rather than the length of dive as used in the existing Seasearch methodology). Abundance is then measured for each species using a simple coded system SCOR (Super-abundant, Common, Occasional, Rare).
Isaac, N.J.B. et al., 2014. Statistics for citizen science: extracting signals of change from noisy ecological data. Methods in Ecology and Evolution 5, pp.1052-1060
Robertson, M.P., Cumming, G.S. & Erasmus, B.F.N., 2010. Getting the most out of atlas data. Diversity and Distributions, 16(3), pp.363–375.