Presented by Chase Colmorgen - Email: chaseco@udel.edu
With a constantly changing environment, the ability to retain and protect submerged aquatic vegetation (SAV: eelgrass (Zostera marina), widgeongrass (Ruppia maritima), and macroalgae (Ulva sp., Entermorpha sp, Gracilaria tikvahiae, and assorted Rhodophyta) is becoming more important as they provide critical ecosystem functions. SAV has many benefits to organisms including the Atlantic brant (Branta bernicula hrota) which is a specialist on these food sources. For example, after a stark decrease in eelgrass in the early 1930s due to a wasting disease from the slime mold Labyrintha zosterae, the population of Atlantic brant also decreased due to lack of food availability. With eelgrass never fully recovering, the brant substituted macroalgae as an alternative food source within a few years. Today, brant populations are still fluctuating raising questions as to whether current food abundance is a factor in their population changes. Thus, building a predictive model of SAV abundance will aid in predicting the potential carrying capacity of wintering brant within the Atlantic flyway. We used Landsat 8 imagery to create a Normalized Difference Vegetation Index (NDVI) of SAV between Long Island and Southern New Jersey which coincides with the highest population wintering grounds for brant. We collected water depth, quality, turbidity, salinity, and SAV biomass at 257 1m2 quadrats across the study area including 174 predicted SAV points and 82 null points. All SAV samples were identified to species, cleaned, dried, and weighed to determine energy density availability. Predictive Akaike Information Criterion (AIC) models of eelgrass and macroalgae presence indicated turbidity, water depth, and NH3-N are significant drivers of SAV presence. The NDVI results revealed higher modeling accuracy for algae species than eelgrass, but also supports the theory of more algae abundance than eelgrass. These modeling results coupled with the sorted biomass values allow estimations for wintering brant carrying capacity across the Mid-Atlantic.E.3-3: Building a Predictive Model of Submerged Aquatic Vegetation for Atlantic Brant
Chase Colmorgen, Department of Entomology and Wildlife Ecology, University of Delaware, Newark, Delaware
Christopher Williams, Department of Entomology and Wildlife Ecology, University of Delaware, Newark, Delaware
Christopher Williams, Department of Entomology and Wildlife Ecology, University of Delaware, Newark, Delaware