Watershed land use can affect submerged aquatic vegetation (SAV) by elevating nutrient and sediment loading to estuaries. We analyzed the effects of watershed use and estuarine characteristics on the spatial variation of SAV abundance among 101 shallow subestuaries of Chesapeake Bay during [1984][1985][1986][1987][1988][1989][1990][1991][1992][1993][1994][1995][1996][1997][1998][1999][2000][2001][2002][2003]. Areas of these subestuaries range from 0.1 to 101 km 2 , and their associated local watershed areas range from 6 to 1664 km 2 . Watershed land cover ranges from 6% to 81% forest, 1% to 64% cropland, 2% to 38% grassland, and 0.3% to 89% developed land. Landscape analyses were applied to develop a number of subestuary metrics (such as subestuary area, mouth width, elongation ratio, fractal dimension of shoreline, and the ratio of local watershed area to subestuary area) and watershed metrics (such as watershed area). Using mapped data from aerial SAV surveys, we calculated SAV coverage for each subestuary in each year during 1984-2003 as a proportion of potential SAV habitat (the area , 2 m deep). The variation in SAV abundance among subestuaries was strongly linked with subestuary and watershed characteristics. A regression tree model indicated that 60% of the variance in SAV abundance could be explained by subestuary fractal dimension, mean tidal range, local watershed dominant land cover, watershed to subestuary area ratio, and mean wave height. Similar explanatory powers were found in wet and dry years, but different independent variables were used. Repeated measures ANOVA with multiple-mean comparison showed that SAV abundance declined with the dominant watershed land cover in the order: forested, mixed-undisturbed, or mixed-developed . mixedagricultural . agricultural . developed. Change-point analyses indicated strong threshold responses of SAV abundance to point source total nitrogen and phosphorus inputs, the ratio of local watershed area to subestuary area, and septic system density in the local watershed.
Ocean ecosystems are subject to a multitude of stressors, including changes in ocean physics and biogeochemistry, and direct anthropogenic influences. Implementation of protective and adaptive measures for ocean ecosystems requires a combination of ocean observations with analysis and prediction tools. These can guide assessments of the current state of ocean ecosystems, elucidate ongoing trends and shifts, and anticipate impacts of climate change and management policies. Analysis and prediction tools are defined here as ocean circulation models that are coupled to biogeochemical or ecological models. The range of potential applications for these systems is broad, ranging from reanalyses for the assessment of past and current states, and short-term and seasonal forecasts, to scenario simulations including climate change projections. The objectives of this article are to illustrate current capabilities with regard to the three types of applications, and to discuss the challenges and opportunities. Representative examples of global and regional systems are described with particular emphasis on those in operational or pre-operational use. With regard to the benefits and challenges, similar considerations apply to biogeochemical and ecological prediction systems as do to physical systems. However, at present there are at least two major differences: (1) biogeochemical observation streams are much sparser than physical streams presenting a significant hinderance, and (2) biogeochemical and ecological models are largely unconstrained because of insufficient observations. Expansion of biogeochemical and ecological observation systems will allow for significant advances in the development and application of analysis and prediction tools for ocean biogeochemistry and ecosystems, with multiple societal benefits.
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