4.5 Article

Temporal variability of a protected multispecific tropical seagrass meadow in response to environmental change

Journal

ENVIRONMENTAL MONITORING AND ASSESSMENT
Volume 191, Issue 12, Pages -

Publisher

SPRINGER
DOI: 10.1007/s10661-019-7977-z

Keywords

Monitoring; Temporal dynamics; Marine protected area; East Africa; Tanzania

Funding

  1. Uppsala University
  2. Swedish Research Council Formas
  3. Swedish Science Council (VR)

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In a changing environment, there is an increasing interest to monitor ecosystems to understand their responses to environmental change. Seagrass meadows are highly important ecosystems that are under constant pressure from human activities and climate impacts, with marked declines observed worldwide. Despite increasing efforts, monitoring of multispecific tropical seagrass meadows is scarce, particularly in low-income regions. Based on data from a monitoring programme in a marine protected area in Zanzibar (Tanzania), we assessed temporal changes in seagrass cover and species composition during a 10-year period in relation to local variability in environmental variables. We observed a strong, gradual decline in seagrass cover and changes in species composition, followed by a period of recovery. However, the timing and length of these temporal patterns varied in space (between transects). Multiple environmental variables-cloud cover, temperature, storm occurrence, sunspot activity, and tidal amplitude and height-influenced seagrass cover, although only to a minor extent, suggesting that the monitored seagrass meadow may be influenced by other unmeasured factors (e.g. water currents and sediment movement). Our results show that seagrass meadows can be highly dynamic at small (10-50 m) spatial scales, even in the absence of major local anthropogenic impacts. Our findings suggest that high-resolution monitoring programmes can be highly valuable for the detection of temporal changes in multispecific seagrass meadows; however, to understand the causes of change, there is a need of long-term (> 10 years) data series that include direct measurements of environmental variables and extreme events.

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