As foundation species, seagrass meadows are vital to coastal ecosystems. They provide important services such as carbon sequestration, coastal protection, and are a home for a wide array of animal biodiversity. Like many other coastal habitats worldwide, seagrass meadows are challenged by anthropic pressures such as dredging, eutrophication, and sea-level rise. Achieving a thorough understanding of the environmental drivers influencing seagrass dynamics is essential to implement efficient coastal zone management, in order to prevent seagrass meadows from further human impacts and to identify where conservation intervention is particularly required to sustain essential ecosystem services. Amongst a variety of environmental interactions, seagrass herbivory is of particular interest because grazing influence vegetation dynamics via top-down control, and because seagrass trajectories could subsequently influence herbivore status and population size via bottom-up interactions.
While there are numerous examples of the potential of Earth Observation to provide spatially and temporally resolved measurements of seagrass status worldwide, combined analyses of remotely sensed seagrass indicators and seagrass herbivores trajectories are still scarce. The objective of the present study was to analyze a long-term time-series of a Zostera noltei intertidal seagrass meadow in combination with the concurrent temporal variations in Brent goose (Branta bernicla bernicla) abundance at a wintering site along the Atlantic flyway. Brent goose is a migratory bird breeding in Siberia during summer and wintering along the North Sea and French Atlantic coasts. As Zostera seagrasses constitute about 95% of their diet, Brent goose migratory route and subsequent breeding success are highly dependent on the status of intertidal Z. noltei meadows in Europe.
In this work, seagrass density was measured using high spatial resolution satellite images in Bourgneuf Bay, an intertidal zone hosting one of the main seagrass meadow of the French Atlantic coast. A multi-mission Landsat, SPOT, and Sentinel2 time-series of seagrass normalized difference vegetation index (NDVI) was compiled and processed from 1985 - 2020 (Zoffoli et al., 2021). For each year, a summertime satellite image was selected during the period of maximal annual seagrass development. Seagrass percent cover was then computed from NDVI with an accuracy of about 15% (Zoffoli, et al., 2020), from which the meadow-averaged seagrass cover was estimated. The long-term dynamics of the seagrass indicators were then compared with concurrent time-series of Brent goose wintertime abundance. From 1984 - 2021, monthly records of Brent goose counts in Bourgneuf Bay were performed as part of the International Waterbird Census from September to April. Only years with coincident data of seagrass and goose counts were analyzed (N = 29). Seagrass and Brent goose datasets were normalized by their mean (x ̅) and standard deviation (σ), and covariance analysis (ANCOVA) was performed to assess the long-term trend over the past four decades. Spearman correlations were also performed between Brent goose maximal wintertime abundance and seagrass density for two situations: (i) with both seagrass and bird series corresponding to the same year; and (ii) with goose counts from the winter preceding seagrass summertime development. While the first situation indicated the influence of seagrass dynamics on Brent goose number (bottom-up interaction), the second situation was an indicator of seagrass top-down control by grazing birds.
Seagrass averaged density was significantly and positively correlated with Brent goose maximal wintertime abundance. Interestingly, the correlation was significant in the two types of configurations, i.e. when seagrass density and birds were evaluated during the same year (p-value < 0.05; R = 0.74) as well as when seagrass and birds were evaluated with a one year lag (p-value < 0.05; R = 0.64). In the first case, the positive correlation between seagrass and Brent geese was expected as a result of bottom-up interactions (i.e. the higher food supply in the seagrass pasture, the better for the birds). In the second case, the positive correlation was somehow counter intuitive, as a negative impact associated with overgrazing by geese has been previously observed in several seagrass meadows. On the other hand, the grazing effect might be reduced because Brent goose landings occur at the end of the seagrass growing season, thus causing little impact on seagrass development. Indeed, birds arrive at the meadow during seagrass senescent phase (in October), and they mostly depart before the start of seagrass growing phase (in March). Furthermore, previous field investigation showed that Brent geese could promote Z. noltei growth by seed propagation and sediment reworking. In complement to statistical correlation, seagrass density and Brent goose abundance presented positive temporal trends from 1985 to 2020. In particular, the slope of the long-term trend was similar for the normalized bird counts and meadow-averaged seagrass density (p-value < 0.05). Such a coincidence further demonstrates the strong link between Z. noltei meadow trajectories and Brent goose dynamics.
While the detailed ecological mechanisms underlying seagrass herbivory remain to be quantitatively evaluated through in situ experiments, our results confirmed that Brent geese - seagrass interactions go beyond trophic relationships, and suggest that Brent geese may positively influence seagrass meadow functioning and habitat structure. As migratory birds use coastal resources independent of any kind of migration policy, efficient ecosystem management calls for coordinated conservation partnerships at continental and global scales. Such international conservation actions are crucial to protect seagrass meadows and the many species they sustain.