Seasonal variation in apparent conductivity and soil salinity at two Narragansett Bay, RI salt marshes.

Measurement of the apparent conductivity of salt marsh sediments using electromagnetic induction (EMI) is a rapid alternative to traditional methods of salinity determination that can be used to map soil salinity across a marsh surface. Soil salinity measures can provide information about marsh processes, since salinity is important in determining the structure and function of tidally influenced marsh communities. While EMI has been shown to accurately reflect salinity to a specified depth, more information is needed on the potential for spatial and temporal variability in apparent conductivity measures that may impact the interpretation of salinity data. In this study we mapped soil salinity at two salt marshes in the Narragansett Bay, RI estuary monthly over the course of several years to examine spatial and temporal trends in marsh salinity. Mean monthly calculated salinity was 25.8 ± 5.5 ppt at Narrow River marsh (NAR), located near the mouth of the Bay, and 17.7 ± 5.3 ppt at Passeonkquis marsh (PAS) located in the upper Bay. Salinity varied seasonally with both marshes, showing the lowest values (16.3 and 8.3 ppt, respectively) in April and highest values (35.4 and 26.2 ppt, respectively) in August. Contour plots of calculated salinities showed that while the mean whole-marsh calculated salinity at both sites changed over time, within-marsh patterns of higher versus lower salinity were maintained at NAR but changed over time at PAS. Calculated salinity was significantly negatively correlated with elevation at NAR during a sub-set of 12 sample events, but not at PAS. Best-supported linear regression models for both sites included one-month and 6-month cumulative rainfall, and tide state as potential factors driving observed changes in calculated salinity. Mapping apparent conductivity of salt marsh sediments may be useful both identifying within-marsh micro-habitats, and documenting marsh-wide changes in salinity over time.

Informations de copyright

©2019 McKinney et al.

Déclaration de conflit d'intérêts

Michael Charpentier is employed by General Dynamics Information Technology.