Variability of Net Primary Productivity and Associated Biophysical Drivers in Bahía de La Paz (Mexico)

Rafael Cervantes-Duarte,Eduardo González-Rodríguez,Fernando Aguirre-Bahena,María Yesenia Torres-Hernández,Alejandro Ramos-Rodríguez,René Funes-Rodríguez

doi:10.3390/rs13091644

Abstract

The use of information of net primary productivity (NPP) from remote ocean color sensors is increasingly common in marine sciences. The resulting information has been used to explain variations in productivity at different spatio-temporal scales and in the presence of climate phenomena, such as the El Niño Southern Oscillation, and global warming. Satellite remote sensing data were analyzed in Bahía de La Paz (BLP), Mexico, to determine the spatio-temporal variation in NPP. In addition, in situ hydrographic data were obtained to characterize the water properties in the bay. The satellite data agree with in situ measurements, validating the satellite observations over this region. The NPP generally presented seasonal variation with maximum values in winter-spring and minimum values in summer–autumn. The variance explained by NPP from the measured variables was ranked as Chl-a < DEN < SST < PAR < WSC. The highest NPP values generally occurred when subtropical subsurface (SsStW) water was relatively shallow. Due to divergence and mixing processes, this water provided nutrients to the euphotic zone, and consequently an increase in NPP and changes in plankton biomass were observed. The annual trends of the variation in hydrographic data with respect to that of remote sensing data were similar; however, it is necessary to increase the number of data validation studies. The remote sensing and in situ measurements allowed for the main biophysical variables that modulate NPP in different time scales to be identified. The satellite-derived NPP data classifies the BLP as a high productivity zone with 432 g C m−2 year−1. The use of satellite NPP data is satisfactory and should be incorporated into marine primary productivity studies.

Highlights

Primary production resulting from the photosynthetic processes of phytoplankton and macrophytes constitutes the main source of organic compounds in the oceans [1], and the global production of phytoplankton has been estimated to be between 52–55 Pg C year −1 [2].The environmental parameters that either stimulate or limit phytoplankton growth are light, temperature, salinity, micronutrients, trace lements, and some organic compounds
The chlorophyll a (Chl-a) values for the whole series ranged from 0.1–6.91 mg m−3, with higher mean values observed from November to June (0.72–1.24 mg m−3 ) and comparatively lower values observed from July to October (0.16–0.66 mg m−3 )
Phosphate presented a range of values from 0.08 to 2.42 μM, with values observed in March and June (0.95 and 0.93 ± 0.44 μM ± 0.37 μM, respectively), and minimum values observed in September (0.43 ± 0.11 μM; Figure 2E)

Summary

Introduction

Primary production resulting from the photosynthetic processes of phytoplankton and macrophytes constitutes the main source of organic compounds in the oceans [1], and the global production of phytoplankton has been estimated to be between 52–55 Pg C year −1 [2].The environmental parameters that either stimulate or limit phytoplankton growth are light (i.e., intensity and spectral composition), temperature, salinity, micronutrients, trace lements, and some organic compounds. Primary production resulting from the photosynthetic processes of phytoplankton and macrophytes constitutes the main source of organic compounds in the oceans [1], and the global production of phytoplankton has been estimated to be between 52–55 Pg C year −1 [2]. Indirect factors that affect primary production in the ocean include physical processes that result in water-column mixings, such as winds, tides, and advection or retention due to currents or vortices, in addition to biological factors like zooplankton grazing [3,4]. The methods for evaluating net primary productivity (NPP) are diverse and range from the classic 14 CO2 fixation method introduced by Steemann-Nielsen [5] to the use of remote sensing satellites [6,7]. Coastal Zone Color Scanner (CZCS) and Ocean Color and Temperature

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