Effects of Shoreline Alteration and Other Stressors on Submerged Aquatic Vegetation in Subestuaries of Chesapeake Bay and the Mid-Atlantic Coastal Bays

Abstract

Submerged aquatic vegetation (SAV) provides many important ecosystem functions, but SAV has been significantly reduced in many estuaries. We used spatial-statistical models to identify estuarine shoreline characteristics that explain variations in SAV abundance among subestuaries of the Chesapeake Bay and mid-Atlantic Coastal Bays. We summarized digital spatial data on shoreline construction, shoreline land use, physical characteristics, watershed land cover, and salinity for each subestuary. We related SAVabundance to shoreline characteristics and other stressors using univariate regression and multivariate models. The strongest univariate predictors of SAV abundance were percent shoreline forest, percent shoreline marsh, the percentage of shoreline that is 5-10 m tall, percent riprap, the percentage of subestuary area <2 m deep, percent herbaceous wetland, and percent shrubland. Shoreline marsh, bulkhead, and shoreline forest had different effects on SAV in different salinity zones. Percent riprap shoreline was the most important variable in a regression tree analysis of all the subestuaries, and percent deciduous forest in the watershed was the most important variable in a separate regression tree analysis on the mesohaline subestuaries. Subestuaries with <5.4 % riprap followed a significantly different temporal trajectory than those with >5.4 % riprap. SAV abundance has increased steadily since 1984 in subestuaries with <5.4 % riprap, but has not increased since 1996-1997 in subestuaries with >5.4 % riprap. Some shoreline characteristics interact with larger-scale factors like land cover and salinity zone to affect the distribution of SAV, while the effects of other shoreline characteristics are consistent among subestuaries with different salinities or local watershed land covers. Many shoreline characteristics can be controlled by management decisions, and our results help identify factors that managers should consider in efforts to increase SAV abundance.

Linking the Abundance of Estuarine Fish and Crustaceans in Nearshore Waters to Shoreline Hardening and Land Cover

“…Daytime dissolved oxygen was measured in subestuary channels offshore of a subset of sample sites and from sample sites with depth >2.5 using a YSI 600 QS (n = 101 sites and 12 subestuaries). Areal coverage of SAV, which typically occurs in waters <2 m deep, was estimated sensu Patrick et al (2014) within each subestuary for each year from 2002 to 2012 and then averaged across years. This time period was chosen because it overlaps with the years in which fauna were sampled.…”

“…To explore this possibility, we developed a composite stressor index for all 39 sampled subestuaries by adding watershed cropland and % hardened shoreline together using z-scored data, which have comparable units. We also developed an index of vegetated fish habitat-% nearshore wetlands + SAV-using the same method because these variables are negatively correlated with one another (Patrick et al 2014). Subestuaries with aboveaverage stressor levels had below-average amounts of vegetated fish habitat and below-average abundances of three representative benthivore-piscivore species (blue crab, spot, and Atlantic croaker) (Fig.…”

“…Cropland data are plotted on the cropland subset, and % hardened shoreline data on the developed land subset. SAV and nearshore wetlands were presented as a composite index, calculated by adding z-scored values of SAV and % nearshore wetland together, because both forms of vegetation provide fishes with critical refuge habitat and because SAV and % nearshore wetland are negatively correlated with one another (Patrick et al 2014) affording large-bodied species greater access to nearshore areas (Hines & Ruiz 1995). Shoreline type-specific differences in water depth at 0 and 3 m from shore, compared with similar water depths at 16 m from shore, may explain the observed differences in faunal responses at different distances from shore.…”

“…10). Cropland is strongly tied to non-point nutrient pollution (i.e., eutrophication) in coastal systems (Jordan et al 1997), which can increase plankton production and lead to hypoxia (Kemp et al 2005;Diaz & Rosenberg 2008) and can reduce coverage and density of SAV by decreasing water clarity and promoting growth of epiphytic algae (Fisher et al 2006;Patrick et al 2014). We found evidence for this in our study, where increasing % watershed cropland was linked with nutrient enrichment and reduced dissolved oxygen as well as scarcity of SAV and nearshore wetlands.…”

Interannual variation in submerged aquatic vegetation and its relationship to water quality in subestuaries of Chesapeake Bay

“…The strengths of stressors on SAV can vary spatially. For example, stressors from human activities on the land are heterogeneously distributed among watersheds (Li et al 2007, Patrick et al 2014. The effects of natural stressors that drive SAV dynamics (Robbins & Bell 2000), particularly storms, also vary spatially.…”