Landsat-derived environmental factors to describe habitat preferences and spatiotemporal distribution of phytoplankton

Abstract

Phytoplankton species are among the most abundant and diverse organisms in marine ecosystems and are highly sensitive to physical-chemical variable changes, so they show high spatial and temporal variability related to environmental changes. This study applied Generalized Additive Models (GAM) to describe the effect of environmental factors on abundance of four phytoplankton genera recorded in a small coastal water body of northwestern Mexico. The most influential variables in order of importance were sea surface temperature, chlorophyll-a concentration, pH, salinity and dissolved oxygen. Predictions of the GAM suggested that abundance had strong spatial and seasonal variability; abundance of Tripos and Gymnodinium was higher in spring (Apr-Jun) and lower in summer (Jul-Sep); Prorocentrum was higher in autumn (Oct-Dec) and lower in winter (Jan-Mar); Pseudo-nitzschia was higher in winter and lower in autumn. The approach in this study represents one of the first efforts to use species distribution models (SDM) in phytoplankton communities using high spatial resolution environmental factors that derived from Landsat imagery. Therefore, this technique could be a useful tool with the potential to transform environmental monitoring and serve as a valuable resource in the study and application of management strategies in a wide range of activities in coastal environments, such as aquaculture, fisheries and public health.