Spatial-temporal analysis of chlorophyll changes and their spatial correlation with sea surface temperature in the Persian Gulf

Document Type : Original Article

Authors
1 Postdoc, Department of Climatology, Faculty of Earth Sciences, Shahid Beheshti University, Tehran, Iran
2 Associate Professor, Department of Natural Resources, Faculty of Agriculture and Natural Resources, Water Management Research Center, University of Mohaghegh Ardabili
10.22034/wmji.2023.710718
Abstract
The natural abundance of phytoplankton in the Persian Gulf has changed, creating a constant threat to biodiversity. Monitoring and predicting the spatial-temporal behavior of this phenomenon is crucial to prevent negative social-economic consequences and environmental planning. On this basis, the current research aims to assess the spatial-temporal changes of chlorophyll and analyze its relationship with the sea surface temperature in the Persian Gulf. To this end, we estimated and analyzed changes in the concentration of chlorophyll as an organic compound produced by algae and plants using MODIS sensor images from 2000 to 2021 (monthly and seasonally). Spatial indices of the barycenter were also calculated in addition to accuracy assessment using error evaluation criteria. Global Moran and G-star (G*) statistics were used to identify the degree of spatial autocorrelation and the magnitude of spatial patterns. The results showed that the intensity of this phenomenon on average varies between 0.05 and 16.38 mg m-2. The northwest and southwest have the maximum values and the central parts of the Persian Gulf have the minimum values. The northern coast of the Persian Gulf is located in Iran, and the northern parts, i.e., areas with less population and industries, have a low amount of this phenomenon. The ellipse line shows three standard deviations in the northwest and southeast directions following the cities and industries. The time series of changes showed that as the temperature decreases in the cold season, especially in January, the concentration increases, and as the temperature of the water surface increases in the hot season the amount of chlorophyll in the water decrease. Statistical analysis of the spatial distribution also indicates a significant cluster spatial pattern. Slope changes verified that the southern regions of the Persian Gulf, especially in the countries of Bahrain, UAE, and Saudi Arabia, have the most positive slope of changes. In the main part of the area, including the northern part of the Persian Gulf, whose coastline is entirely owned by Iran, except for the northwest, which includes the Mahshahr port and Asaluyeh, the slope of changes has been very low or decreasing. This research could identify areas exposed to adverse changes in phytoplankton concentrations and can be used in environmental planning.
Keywords

  1. Alijani, B. 2015. Spatial analysis. Journal of Spatial Analysis of Environmental Hazards, 2(3): 1-14. (In Persian).
  2. Anderson, D.M., Glibert, P., and Burkholder, J. 2002. Harmful algal blooms and eutrophication: nutrient sources, composition, and consequences. Estuaries, 25(4): 704-726.
  3. Andrew, W., Griffith, T., Christopher, J., and Gobbler, N. 2020. Harmful algal blooms: A climate change co-stressor in marine and freshwater ecosystems. Harmful Algae, 91: 101590.
  4. Asakareh, H., and Shadman, H. 2015. Identifying the spatial relationships of pervasive hot days in Iran. Geographical Research Quarterly, 30(1): 53-69. (In Persian).
  5. Asakereh, H., and Seifipour, Z. 2012. Spatial modeling of annual rainfall in Iran. Geography and Development, 10(29): 15-30. (In Persian).
  6. Attaran-Fariman, G., and Bolch, C.J.S. (2012). Morphology and phylogeny of scrippsiella trochoidea (dinophyceae) a potentially harmful bloom forming species isolated from the sediments of Iran’s south coast. Iranian Journal of Fisheries Sciences, 11(2): 252-270.
  7. Dai, A. 2011. Drought under global warming: a review: Drought under global warming. WIREs Climate Change, 2(1): 45–65.
  8. Farzin,, Nazari Saman, A., Menbar, A., Feiznia, S., and Kazemi, Gh. 2018. Identification of potential areas for presence of submarine springs in the Persian Gulf on the coasts of Bushehr province using thermal data of Landsat 8. RS & GIS for Natural Resources, 8(4): 91-108. (In Persian).
  9. Fazli, S.H., Sima, S., and Mosivand, A. 2022. Spatiotemporal analysis of harmful algal bloom (HAB) in the Strait of Hormuz and identifying abiotic driving forces. Journal of Environmental Studies, 48(2): 125-152. (In Persian).
  10. Gail, M., Krickeberg, K., Samet, J., Tsiatis, A., and Wong, W. 2007. Statistics for Biology and Health. USA: Springer.
  11. Gao, R., Clare, S., Rose, C., and Caldwell, G. 2017. Eutrophication and warming-driven green tides (Ulva rigida) are predicted to increase under future climate change scenarios. Mararine Pollution, 114: 439–47.
  12. Gurbisz,, and Kemp, W. 2014. Unexpected resurgence of a large submersed plant bed in Chesapeake Bay: Analysis of time series data. Limnology and Oceanography, 59(2), 482-494.
  13. Haining, R. 2004. Spatial data analysis: Theory and practice. UK: Cambridge University Press, 545.
  14. Hu, C., Lee, Z., and Franz, B. 2012. Chlorophyll a algorithms for oligotrophic oceans: A novel approach based on three-band reflectance difference. Journal of Geophysical Research, 117(C1): 518-531. https://doi.org/10.1029/2011JC007395
  15. IPCC, 2018. Summary for Policymakers. In: Global warming of 1.5_C. An.
  16. Kärcher, O., Filstrup, C. T., Brauns, M., Tasevska, O., Patceva, S., Hellwig, N., Walz, A., Frank, K., and Markovic, D. 2020. Chlorophyll a relationships with nutrients and temperature and predictions for lakes across perialpine and Balkan mountain regions. Inland Waters, 10(2): 29-41.
  17. Kumar, P., Roshin, P., Narvekar, J., Kumar, D., and Vivekanandan, E. 2010. What drives the increased phytoplankton biomass in the Arabian Sea. Current Science, 18: 101-106.
  18. Moriasi, D., Gitau, M., Pai, N., and Daggupati, P. 2015. Hydrologic and water quality models: Performance measures and evaluation criteria. Transactions of the ASABE. American Society of Agricultural and Biological Engineers, 58: 1763-1785.
  19. Modabberi,, Noori, R., Madani, K., Ehsani, A., Danandeh Mehr, A., Hooshyaripor, F., and Kløve, B. 2020. Caspian Sea is eutrophying: the alarming message of satellite data. Environmental Research Letters, 15: 124047.
  20. Ritzman J, Brodbeck A, Brostrom S, McGrew S, Dreyer S, Klinger T, Moore K. 2018. Economic and sociocultural impacts of fisheries closures in two fishing-dependent communities following the massive 2015 US West Coast harmful algal bloom. Harmful Algae, 80: 35-45.
  21. Shahri E, Sayadi M, Yousefi E. 2022. Monitoring of chlorophyll-A, organic carbon, salinity and water surface temperature off the coast of Sistan and Baluchestan using remote sensing data. RS & GIS for Natural Resources, 12(4): 119- 134. (In Persian).
  22. 2021. Sixth assessment report. Intergovernmental Panel on Climate Change.
  23. Al-Naimi, N., Raitsos, D.E., Ben-Hamadou, R., and Soliman, Y. 2017. Evaluation of Satellite Retrievals of Chlorophyll-a in the Arabian Gulf. Remote Sensing, 9(3): 301.
  24. Barzegari, A., Karimzadeh, M., and Moghaddam, B. (2022). Assessment of the spatial and temporal patterns of chlorophyll-a concentration in the Persian Gulf. Environmental Pollution, 287, 117826.
  25. Cai, W., Zhang, Q., and Li, J. 2022. Impacts of climate change on phytoplankton blooms in the Yellow Sea. Ecological Indicators, 136, 107963.
  26. Liu, L., Zhang, X., and Wang, Y. 2022. Global trends and spatial-temporal patterns of phytoplankton blooms in coastal oceans. Journal of Environmental Management, 316, 113790.