The spatial dynamics of vertical migration by Microcystis aeruginosa in a eutrophic shallow lake: A case study using high spatial resolution time‐series airborne remote sensing

Abstract

Time-series airborne remote sensing was used to monitor diurnal changes in the spatial distribution of a bloom of the potentially toxic cyanobacterium Microcystis aeruginosa in the shallow eutrophic waters of Barton Broad, United Kingdom. High spatial resolution images from the Compact Airborne Spectrographic Imager (CASI-2) were acquired over Barton Broad on 29 August 2005 at 09:30 h, 12:00 h, and 16:00 h Greenwich mean time. Semiempirical water-leaving radiance algorithms were derived for the quantification of chlorophyll a (R 2 5 0.96) and C-phycocyanin (R 2 5 0.95) and applied to the CASI-2 imagery to generate dynamic, spatially resolving maps of the M. aeruginosa bloom. The development of the bloom may have been fostered by a combination of the recent improvements in the ambient light environment of Barton Broad, allied to the acute depletion of bioavailable nutrient pools, and stable hydrodynamic conditions. The vertical distribution of M. aeruginosa was highly transient; buoyant colonies formed early morning and late afternoon near-surface aggregations across the lake during periods of nonturbulent mixing (wind speed ,4 m s 21 ). However, the extent of these near-surface aggregations was highly spatially variable, and nearshore morphometry appeared to be crucial in creating localized regions of nonturbulent water in which pronounced and persistent near-surface aggregations were observed. The formation of these near-surface scums would have been vital in alleviating light starvation in the turbid waters of Barton Broad. The calm water refuges in which persistent near-surface accumulations occurred may have been an important factor in determining the persistence of the bloom.

Which offers more scope to suppress river phytoplankton blooms: Reducing nutrient pollution or riparian shading?

“…Continuous monitoring technology for DO (Williams et al, 2000) and chlorophyll-a has become more commonplace recently. Coupled with the possibilities afforded by earth observation to record the development of blooms down a river system (Hunter et al, 2008) this will aid understanding of the wider impacts of phytoplankton, particularly on DO and fish habitats. In this context, a shorter model time-step (e.g.…”

Fourteen-Year Record (2000–2013) of the Spatial and Temporal Dynamics of Floating Algae Blooms in Lake Chaohu, Observed from Time Series of MODIS Images

“…To avoid the impact of meteorological conditions on algal bloom detection (wind, ice), daily information on wind speed, water temperature, and surface ice was obtained. As wind speed greater than 4 m/s has been used as a threshold for determining the vertical distribution of algal blooms, datasets where the synchronous average wind speed were greater than 4.0 m/s were not used [29][30][31]. Water column temperatures below 5 °C inhibit cyanobacteria renewal [32] and floating ice negatively influences the accuracy of FAI and APA algorithm performance [25,27].…”

Blowing in the wind: how many roads can a phytoplanktont walk down? A synthesis on phytoplankton biogeography and spatial processes

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