Environmental drivers behind the exceptional increase in cyanobacterial blooms in Okavango Delta, Botswana

被引:0
|
作者
Veerman, Jan [1 ]
Mishra, Deepak R. [1 ]
Kumar, Abhishek [1 ,2 ]
Karidozo, Malvern [3 ]
机构
[1] Univ Georgia, Ctr Geospatial Res, Dept Geog, Athens, GA 30602 USA
[2] Univ Massachusetts, Dept Environm Conservat, Amherst, MA 01003 USA
[3] Connected Conservat Trust, 516 Jacaranda Crescent, Victoria Falls, Zimbabwe
关键词
CyanoHABs; Remote sensing; Environmental drivers; Sentinel-2; Generalized additive models; Structural equation modeling; FRESH-WATER SYSTEMS; CLIMATE-CHANGE; LAND-USE; QUALITY; DROUGHT; INDEX; MODELS; IMPACT; EVAPOTRANSPIRATION; RIVER;
D O I
10.1016/j.hal.2024.102677
中图分类号
Q17 [水生生物学];
学科分类号
071004 ;
摘要
The Okavango Delta region in Botswana experienced exceptionally intense landscape-wide cyanobacterial harmful algal blooms (CyanoHABs) in 2020. In this study, the drivers behind CyanoHABs were determined from thirteen independent environmental variables, including vegetation indices, climate and meteorological parameters, and landscape variables. Annual Land Use Land Cover (LULC) maps were created from 2017 to 2020, with similar to 89% accuracy to compute landscape variables such as LULC change. Generalized Additive Models (GAM) and Structural Equation Models (SEM) were used to determine the most important drivers behind the CyanoHABs. Normalized Difference Chlorophyll Index (NDCI) and Green Line Height (GLH) algorithms served as proxies for chlorophyll-a (green algae) and phycocyanin (cyanobacteria) concentrations. GAM models showed that seven out of the thirteen variables explained 89.9% of the variance for GLH. The models showcased that climate variables, including monthly precipitation (8.8%) and Palmer Severity Drought Index- PDSI (3.2%), along with landscape variables such as changes in Wetlands area (7.5%), and Normalized Difference Vegetation Index (NDVI) (5.4%) were the determining drivers behind the increased cyanobacterial activity within the Delta. Both PDSI and NDVI showed negative correlations with GLH, indicating that increased drought conditions could have led to large increases in toxic CyanoHAB activity within the region. This study provides new information about environmental drivers which can help monitor and predict regions at risk of future severe CyanoHABs outbreaks in the Okavango Delta, Botswana, and other similar data-scarce and ecologically sensitive areas in Africa.
引用
下载
收藏
页数:16
相关论文
共 22 条
  • [21] Predictive Analytics of Cattle Host and Environmental and Micro-Climate Factors for Tick Distribution and Abundance at the Livestock-Wildlife Interface in the Lower Okavango Delta of Botswana
    Babayani, Nlingisisi D.
    Makati, Anastacia
    FRONTIERS IN VETERINARY SCIENCE, 2021, 8
  • [22] Great Lakes Center for Fresh Waters and Human Health: Using Advanced 'Omics Techniques and Novel Technologies to Investigate Environmental Drivers of Toxic Cyanobacterial Blooms, Discover Novel Compounds, and Improve Cyanotoxin Monitoring.
    Davis, T.
    Bullerjahn, G. S.
    McKay, R. M.
    Doucette, G.
    Chaffin, J.
    Dick, G.
    Sherman, D.
    Boyer, G. L.
    Wilhelm, S. W.
    Triezenberg, H.
    Paerl, H.
    Bridgeman, T.
    ENVIRONMENTAL AND MOLECULAR MUTAGENESIS, 2019, 60 : 32 - 33