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Spatial variability of estuarine environmental drivers and response by phytoplankton: A multivariate modeling approach
Journal article   Peer reviewed

Spatial variability of estuarine environmental drivers and response by phytoplankton: A multivariate modeling approach

Bhanu Paudel, David Velinsky, Tom Belton and Helen Pang
Ecological informatics, v 34, pp 1-12
Jul 2016
DOI: https://doi.org/10.1016/j.ecoinf.2016.04.013
Featured in Collection :   UN Sustainable Development Goals @ Drexel

Abstract

Bayesian linear regression Inflow Nutrients Phytoplankton Structural equation modeling
Environmental variables such as river inflow, dissolved chemicals, temperature, total suspended solids, dissolved oxygen, and pH are the environmental drivers that maintain phytoplankton growth in estuaries. Spatial variability of environmental drivers in Barnegat Bay, New Jersey, and their roles in the distribution of phytoplankton were investigated in order to identify spatial variability in phytoplankton production in the bay. The water quality data collected and analyzed by New Jersey Department of Environmental Protection from 14 different stations in Barnegat Bay were divided into two different data sets, i.e. Northern Barnegat Bay (NB) and Southern Barnegat Bay (SB) data. Structural equation modeling, Bayesian linear regression, and kriging interpolation were used for the modeling study. The study identified higher dissolved N:P(88:1) in NB as compared to SB (19:1). The NB phytoplankton growth was maintained by the dissolved chemicals transported by inflow, whereas, the SB phytoplankton growth was maintained by sediment–water processes and regeneration. The lower ratio of regression coefficients of dissolved N to P throughout SB, as compared to that of NB, indicates low dissolved nitrogen concentrations in SB. In addition, higher inflow induced transport of dissolved nutrients and carbon may explain the significant north–south chlorophyll-α concentration gradient. The findings identified indirect effects of inflow and direct effects of nutrients on NB phytoplankton growth. Within SB, there were direct effects of nutrients, carbon dynamics, dissolved oxygen, pH, and turbidity on phytoplankton growth. Therefore, the results of this study are useful to state and federal water quality agencies in developing management strategies for northern and southern Barnegat Bay. •Environmental drivers were identified in the northern (NB) and southern (SB) Barnegat Bay.•The northern bay had higher dissolved N:P than in the southern bay.•In NB, nutrients had direct while environmental flow had indirect effect on phytoplankton.•In SB, nutrients, carbon, DO, pH, and turbidity had direct effect on phytoplankton.

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17 citations in Web of Science
16 citations in Scopus

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UN Sustainable Development Goals (SDGs)

This publication has contributed to the advancement of the following goals:

#13 Climate Action
#14 Life Below Water

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Web of Science research areas
Ecology
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