, Volume 13, Issue 2, pp 338-351,
Open Access This content is freely available online to anyone, anywhere at any time.

Spatial Synchrony in Intertidal Benthic Algal Biomass in Temperate Coastal and Estuarine Ecosystems

Abstract

Microphytobenthos plays a vital role in estuarine and coastal carbon cycling and food webs. Yet, the role of exogenous factors, and thus the effects of climate change, in regulating microphytobenthic biomass is poorly understood. We aimed to unravel the mechanisms structuring microphytobenthic biomass both within and across ecosystems. The spatiotemporal distribution of the biomass of intertidal benthic algae (dominated by diatoms) was estimated with an unprecedented spatial extent from time-series of Normalized Differential Vegetation Index (NDVI) derived from a 6-year period of daily Aqua MODIS 250-m images of seven temperate, mostly turbid, estuarine and coastal ecosystems. These NDVI time-series were related to meteorological and environmental conditions. Intertidal benthic algal biomass varied seasonally in all ecosystems, in parallel with meteorology and water quality. Seasonal variation was more pronounced in mud than in sand. Interannual variation in biomass was small, but synchronized year-to-year biomass fluctuations occurred in a number of disjointed ecosystems. Air temperature explained interannual fluctuations in biomass in a number of sites, but the synchrony was mainly driven by the wind/wave climate: high wind velocities reduced microphytobenthic biomass, either through increased resuspension or reduced emersion duration. Spatial variation in biomass was largely explained by emersion duration and mud content, both within and across ecosystems. The results imply that effects on microphytobenthic standing stock can be anticipated when the position in the tidal frame is altered, for example due to sea level rise. Increased storminess will also result in a large-scale decrease of biomass.

Author Contributions

D. van der Wal conceived and designed the study, compiled the data, performed the analyses and wrote the article. A. Wielemaker-van den Dool processed the satellite imagery to derive NDVI data. P. M. J. Herman contributed to study design, (statistical) analysis and interpretation and edited the article.