Habitat Delineation in Highly Variable Marine Environments

Abstract

The structure of the phytoplankton community in surface waters is the consequence of complex interactions between the physical and chemical properties of the upper water column as well as the interaction within the general biological community. Understanding the structure of phytoplankton communities is especially challenging in highly variable and dynamic marine environments. A variety of strategies have been employed to delineate marine planktonic habitats, including both biogeochemical and water-mass-based approaches. These methods have led to fundamental improvements in our understanding of marine phytoplankton distributions, but they are often difficult to apply to systems with physical and chemical properties and forcings that vary greatly over relatively short spatial or temporal scales. In this study, we have developed a method of dynamic habitat delineation based on environmental variables that are biologically relevant, that integrate over varying time scales, and that are derived from standard oceanographic measurements. As a result, this approach is widely applicable, simple to implement, and effective in resolving the spatial distribution of phytoplankton communities. As a test of our approach, we have applied it to the Amazon River-influenced Western Tropical North Atlantic (WTNA) and to the South China Sea (SCS), which is influenced by both the Mekong River and seasonal coastal upwelling. These two systems differ substantially in their spatial and temporal scales, nutrient sources/sinks, and hydrographic complexity, providing an effective test of the applicability of our analysis. Despite their significant differences in scale and character, our approach generated statistically robust habitat classifications that were clearly relevant to surface phytoplankton communities. Additional analysis of the habitat-defining variables themselves can provide insight into the processes acting to shape phytoplankton communities in each habitat. Finally, by demonstrating the biological relevance of the generated habitats, we gain insights into the conditions promoting the growth of distinct communities and the factors that lead to mismatches between environmental conditions and phytoplankton community structure.

Small pigmented eukaryote assemblages of the western tropical North Atlantic around the Amazon River plume during spring discharge

“… 35 : young plume core (YPC), old plume core (OPC), west plume margin (WPM), east plume margin (EPM) and oceanic seawater (OSW). Each habitat was characterized by a unique combination of sea surface salinity, sea surface temperature, nitrate availability index, mixed layer depth and chlorophyll maximum depth 35 . Geographically, the different habitats were unevenly distributed along the transect (Fig.…”

“…1 ). Habitat types are defined by the correlation of five environmental variables; sea surface salinity, sea surface temperature, a nitrogen availability index, the mixed layer depth and the chlorophyll maximum depth as defined by Weber et al 35 . The latter three are integrated parameters, derived from vertical profiles of dissolved nitrogen concentrations, buoyancy frequency, and chlorophyll fluorescence, respectively (Supplementary Fig.…”

“…Considering the multiple gradients that define the ARP, we hypothesized that small pigmented eukaryote communities vary widely across the different habitat types previously described by Weber et al . 35 . Given the global tendency of small pigmented eukaryote to thrive at deep chlorophyll maxima, we also hypothesized that their diversity varies vertically within the water column.…”

Resource partitioning among stranded aquatic mammals from Amazon and Northeastern coast of Brazil revealed through Carbon and Nitrogen Stable Isotopes

“…In the Amazon estuary and the marine region under its influence, low δ 13 C values and high δ 15 N values are reported near the estuary and within the most coastal core of the plume, mainly due to the terrestrial origin of the organic matter. Basal carbon isotope values then increase with salinity 31 − 33 while the increasing proportion of production based on N-fixation towards oceanic waters generates a decreasing trend in δ 15 N values 32 , 34 . Nevertheless, the influence of the organic input of the Amazon plume, can reach hundreds of kilometers from the mouth of the estuary, thus influencing the basal isotopic values of large estuarine and marine areas 32 , 33 .…”

Environmental Regulation of the Nitrogen Supply, Mean Trophic Position, and Trophic Enrichment of Mesozooplankton in the Mekong River Plume and Southern South China Sea

“…Colors indicate habitat types after Weber et al. (2019) (see legend). Stations 23 and 27 could not be assigned habitat types due to inadequate sampling at these sites.…”