Dataset Information

Spatiotemporal variability and environmental factors of harmful algal blooms (HABs) over western Lake Erie.

ABSTRACT: Over the past decades, numerous studies have been carried out in understanding causes of Harmful Algal Blooms (HABs) and their dynamics, yielding great knowledge in this field. Lake Erie, the fourth-largest lake of the five Great Lake, is among those highly vulnerable to the impacts of HABs and has received substantial attention from the public, water management sectors, and academic field. Building upon previous work, this study aims to characterize spatiotemporal variability of Chlorophyll a (Chl-a), which is an important indicator of HABs, and to explore relative importance of environmental factors associated with HABs in the west Lake Erie. Ten years of biweekly Chl-a information over western Lake Erie were derived from MERIS data at the pixel scale. Based on the MERIS-derived information high concentrations of Chl-a were observed in the south near shore area in spring and fall and in the west corner area of western Lake Erie in all three seasons except winter. Wavelet analysis suggested that the 0.5- and 1-year periods were dominant modes for the Chl-a series. The Multivariate Adaptive Regression Splines (MARS) analysis was performed to explore factors associated with the dynamics of Chl-a. The results suggested that overall both phenological (e.g. wind) and ecological (e.g. nutrient levels) factors exhibited significant correlations with the remotely-sensed imagery based observations of Chl-a despite spatial and temporal variations. The important phenological and ecological factors include solar radiation and wind speed in spring, water temperature, solar radiation, and total Kjeldahl nitrogen concentration in summer, wind speed in fall, and water temperature and streamflow in winter. Both consistency and differences of findings of the study with others in the region may suggest strengths and limitations of the remotely sensed imagery-based analysis, offering valuable information for future work.

SUBMITTER: Tian D

PROVIDER: S-EPMC5489311 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Spatiotemporal variability and environmental factors of harmful algal blooms (HABs) over western Lake Erie.

Tian Di D Xie Gengxin G Tian Jing J Tseng Kuo-Hsin KH Shum C K CK Lee Jiyoung J Liang Song S

PloS one 20170628 6

Over the past decades, numerous studies have been carried out in understanding causes of Harmful Algal Blooms (HABs) and their dynamics, yielding great knowledge in this field. Lake Erie, the fourth-largest lake of the five Great Lake, is among those highly vulnerable to the impacts of HABs and has received substantial attention from the public, water management sectors, and academic field. Building upon previous work, this study aims to characterize spatiotemporal variability of Chlorophyll a ( ...[more]

PMID: 28658260

Similar Datasets

Project description:Harmful Algal Blooms (HABs) are of global concern, as their presence is often associated with socio-economic and environmental issues including impacts on public health, aquaculture and fisheries. Therefore, monitoring the occurrence and succession of HABs is fundamental for managing coastal regions around the world. Yet, due to the lack of adequate in situ measurements, the detection of HABs in coastal marine ecosystems remains challenging. Sensors on-board satellite platforms have sampled the Earth synoptically for decades, offering an alternative, cost-effective approach to routinely detect and monitor phytoplankton. The Red Sea, a large marine ecosystem characterised by extensive coral reefs, high levels of biodiversity and endemism, and a growing aquaculture industry, is one such region where knowledge of HABs is limited. Here, using high-resolution satellite remote sensing observations (1km, MODIS-Aqua) and a second-order derivative approach, in conjunction with available in situ datasets, we investigate for the first time the capability of a remote sensing model to detect and monitor HABs in the Red Sea. The model is able to successfully detect and generate maps of HABs associated with different phytoplankton functional types, matching concurrent in situ data remarkably well. We also acknowledge the limitations of using a remote-sensing based approach and show that regardless of a HAB's spatial coverage, the model is only capable of detecting the presence of a HAB when the Chl-a concentrations exceed a minimum value of ~ 1 mg m-3. Despite the difficulties in detecting HABs at lower concentrations, and identifying species toxicity levels (only possible through in situ measurements), the proposed method has the potential to map the reported spatial distribution of several HAB species over the last two decades. Such information is essential for the regional economy (i.e., aquaculture, fisheries & tourism), and will support the management and sustainability of the Red Sea's coastal economic zone.

Dataset Information

Spatiotemporal variability and environmental factors of harmful algal blooms (HABs) over western Lake Erie.

Publications

Spatiotemporal variability and environmental factors of harmful algal blooms (HABs) over western Lake Erie.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets