Studland Bay Marine Conservation Zone (MCZ): Subtidal Seagrass Monitoring Survey 2021.
Abstract
In July 2021 a new cycle of monitoring the subtidal seagrass (Zostera marina) beds in Studland Bay MCZ, in Dorset, commenced. The site was previously surveyed in 2018 by the Environment Agency to record the seagrass extent and percent cover (Green, 2018). Natural England led the 2021 survey programme following the methods developed for surveying seagrass beds in Torbay. The data collected will allow the condition of the subtidal seagrass beds to be assessed against some of the targets for this feature of the MCZ. The survey programme (including the 2018 Environment Agency survey) was designed primarily to monitor the following attributes of the subtidal seagrass bed: Extent and distribution: The seagrass bed has the target to either remain stable or increase in size. Structure and function: The bed quality (density, overall health) and species composition of characteristic biological communities (diversity and abundance of species in the habitat) with the target to remain healthy and not deteriorate. It also aimed to provide data to support the assessment of the spiny (long-snouted) seahorse attributes: Quality and quantity of the habitat available with the same targets as above for the seagrass bed attribute. Population size and age / sex ratios with the target to enable the population to thrive by maintaining these parameters. The data collected in 2018 and 2021 provide the first step toward recording statistically robust and repeatable monitoring data against which future data can be compared. Historical data available from a variety of different survey programmes and organisations recorded prior to these surveys only permit qualitative comparisons and are discussed in this report. The following key findings were determined: The monitoring sites selected were based on the 2018 Environment Agency survey data of bed extent and percent cover. With one exception the density and distribution (patchiness) of the seagrass at each monitoring station was broadly in line with the results of that survey. Where seagrass does occur in the bay, overall mean percentage cover values were in the range of 24-81%. Long, luxurious stands of seagrass provide habitat for a range of species, many of which have been recorded in previous surveys. Seagrass wasting disease, Labyrinthula sp. was observed across the sites monitored. The lowest infection scores were from the most northern site and the highest from the most southern. Non-native species were recorded throughout the bay and were mostly observed to be in low abundance. The exception was the tetrasporophyte phase of harpoon weed, Asparagopsis armata, which occurred in high numbers in some areas. Anchor and mooring damage to the seagrass was apparent throughout the areas monitored, leaving bare sand patches, exposed rhizomes and detached plants. Not all bare sand patches could be attributed to anchor or mooring impacts although the cause of some damage observed was unequivocal. No seahorses were observed during the survey, but the divers were operating outside the areas considered most likely to support them. The following recommendations were made for future surveys: The planned repetition of the 2018 Environment Agency survey (Green, 2018) in 2022 and every three years thereafter will go some way toward monitoring the bed status in a comparable and robust manner and will improve the resolution in data and understanding of potential seagrass bed dynamics. The present survey programme does not address the issue of small-scale patchiness (<50 m resolution). Consideration could be given to the idea of surveying transects to produce and monitor patchiness ratios at selected points throughout the bed. Increased aerial surveys (drone) could be used to monitor anchor / mooring damage within the seagrass bed, or part thereof. Future surveys can be made more efficient by reducing the post-survey sample processing. Assigning divers to specifically collect data on the seagrass bed biological communities will enhance our understanding of the diversity within Studland Bay and enable quantification and statistical analysis of the data.