David J. Wilcox

Habitat requirements for submerged aquatic vegetation in Chesapeake Bay : Water quality, light regime, and physical-chemical factors

We developed an algorithm for calculating habitat suitability for seagrasses and related submerged aquatic vegetation (SAV) at coastal sites where monitoring data are available for five water quality variables that govern light availability at the leaf surface. We developed independent estimates of the minimum light required for SAV survival both as a percentage of surface light passing though the water column to the depth of SAV growth (PLWmin) and as a percentage of light reaching reaching leaves through the epiphyte layer (PLLmin). Value were computed by applying, as inputs to this algorithm, statistically dervived values for water quality variables that correspond to thresholds for SAV presence in Chesapeake Bay. These estimates ofPLWmin andPLLmin compared well with the values established from a literature review. Calcultations account for tidal range, and total light attenuation is partitioned into water column and epiphyte contributions. Water column attenuation is further partitioned into effects of chlorophylla (chla), total suspended solids (TSS) and other substances. We used this algorithm to predict potential SAV presence throughout the Bay where calculated light available at plant leaves exceededPLLmin. Predictions closely matched results of aerial photographic monitoring surveys of SAV distribution. Correspondence between predictions and observations was particularly strong in the mesohaline and polythaline regions, which contain 75–80% of all potential SAV sites in this estuary. The method also allows for independent assessment of effects of physical and chemical factors other than light in limiting SAV growth and survival. Although this algorithm was developed with data from Chesapeake Bay, its general structure allows it to be calibrated and used as a quantitative tool for applying water quality data to define suitability of specific sites as habitats for SAV survival in diverse coastal environments worldwide.

Analysis of the Abundance of Submersed Aquatic Vegetation Communities in the Chesapeake Bay

A procedure was developed using aboveground field biomass measurements of Chesapeake Bay submersed aquatic vegetation (SAV), yearly species identification surveys, annual photographic mapping at 1∶24,000 scale, and geographic information system (GIS) analyses to determine the SAV community type, biomass, and area of each mapped SAV bed in the bay and its tidal tributaries for the period of 1985 through 1996. Using species identifications provided through over 10,000 SAV ground survey observations, the 17 most abundant SAV species found in the bay were clustered into four species associations: ZOSTERA, RUPPIA, POTAMOGETON, and FRESHWATER MIXED. Monthly aboveground biomass values were then assigned to each bed or bed section based upon monthly biomass models developed for each community. High salinity communities (ZOSTERA) were found to dominate total bay SAV aboveground biomass during winter, spring, and summer. Lower salinity communities (RUPPIA, POTAMOGETON, and FRESHWATER MIXED) dominated in the fall. In 1996, total bay SAV standing stock was nearly 22,800 metric tons at annual maximum biomass in July encompassing an area of approximately 25,670 hectares. Minimum biomass in December and January of that year was less than 5,000 metric tons. SAV annual maximum biomass increased baywide from lows of less than 15,000 metric tons in 1985 and 1986 to nearly 25,000 metric tons during the 1991 to 1993 period, while area increased from approximately 20,000 to nearly 30,000 hectares during that same period. Year-to-year comparisons of maximum annual community abundance from 1985 to 1996 indicated that regrowth of SAV in the Chesapeake Bay from 1985–1993 occurred principally in the ZOSTERA community, with 85% of the baywide increase in biomass and 71% of the increase in are a occurring in that community. Maximum biomass of FRESHWATER MIXED SAV beds also increased from a low of 3,200 metric tons in 1985 to a high of 6,650 metric tons in 1993, while maximum biomass of both RUPPIA and POTAMOGETON beds fluctuated between 2,450 and 4,600 metric tons and 60 and 600 metric tons, respectively, during that same period with net declines of 7% and 43%, respectively, between 1985 and 1996. During the July period of annual, baywide, maximum SAV biomass, SAV beds in the Chesapeake Bay typically averaged approximately 0.86 metric tons of aboveground dry mass per hectare of bed area.

Modeling Dynamic Polygon Objects in Space and Time: A New Graph-based Technique

The analysis of dynamic spatial systems requires an explicit spatio-temporal data model and spatio-temporal analysis tools. Event-based models have been developed to analyze discrete change in continuous and feature-based spatial data. In this paper, a spatio-temporal graph model is described that supports the analysis of continuous change in feature-based polygon spatial data. The spatio-temporal graph edges, called temporal links, track changes in polygon topology through space and time. The model also introduces the concept of a spatial-interaction region that extends a models focus beyond short-term local events to encompass long-term regional events. The structure of the spatio-temporal graph is used to classify these events into five types of local polygon events and two types of spatial-interaction region events. To illustrate its utility, the model is applied to the ecological question of how patch size influences longevity in underwater plant communities in Chesapeake Bay, USA. Both a short-term local analysis and a longer-term regional analysis showed that patches of plants, or groups of patches, larger than one to two hectares in size were more likely to persist than smaller patches or groups of patches. Overall, the spatio-temporal graph model approach appears applicable to a variety of spatio-temporal questions.

Multiple stressors threaten the imperiled coastal foundation species eelgrass (Zostera marina) in Chesapeake Bay, USA

Abstract Interactions among global change stressors and their effects at large scales are often proposed, but seldom evaluated. This situation is primarily due to lack of comprehensive, sufficiently long‐term, and spatially extensive datasets. Seagrasses, which provide nursery habitat, improve water quality, and constitute a globally important carbon sink, are among the most vulnerable habitats on the planet. Here, we unite 31 years of high‐resolution aerial monitoring and water quality data to elucidate the patterns and drivers of eelgrass (Zostera marina) abundance in Chesapeake Bay, USA, one of the largest and most valuable estuaries in the world, with an unparalleled history of regulatory efforts. We show that eelgrass area has declined 29% in total since 1991, with wide‐ranging and severe ecological and economic consequences. We go on to identify an interaction between decreasing water clarity and warming temperatures as the primary drivers of this trend. Declining clarity has gradually reduced eelgrass cover the past two decades, primarily in deeper beds where light is already limiting. In shallow beds, however, reduced visibility exacerbates the physiological stress of acute warming, leading to recent instances of decline approaching 80%. While degraded water quality has long been known to influence underwater grasses worldwide, we demonstrate a clear and rapidly emerging interaction with climate change. We highlight the urgent need to integrate a broader perspective into local water quality management, in the Chesapeake Bay and in the many other coastal systems facing similar stressors.

Submersed aquatic vegetation in Chesapeake Bay: Sentinel species in a changing world

Abstract Chesapeake Bay has undergone profound changes since European settlement. Increases in human and livestock populations, associated changes in land use, increases in nutrient loadings, shoreline armoring, and depletion of fish stocks have altered the important habitats within the Bay. Submersed aquatic vegetation (SAV) is a critical foundational habitat and provides numerous benefits and services to society. In Chesapeake Bay, SAV species are also indicators of environmental change because of their sensitivity to water quality and shoreline development. As such, SAV has been deeply integrated into regional regulations and annual assessments of management outcomes, restoration efforts, the scientific literature, and popular media coverage. Even so, SAV in Chesapeake Bay faces many historical and emerging challenges. The future of Chesapeake Bay is indicated by and contingent on the success of SAV. Its persistence will require continued action, coupled with new practices, to promote a healthy and sustainable ecosystem.

Long-term nutrient reductions lead to the unprecedented recovery of a temperate coastal region

Significance Human actions, including nutrient pollution, are causing the widespread degradation of coastal habitats, and efforts to restore these valuable ecosystems have been largely unsuccessful or of limited scope. We provide an example of successful restoration linking effective management of nutrients to the successful recovery of submersed aquatic vegetation along thousands of kilometers of coastline in Chesapeake Bay, United States. We also show that biodiversity conservation can be an effective path toward recovery of coastal systems. Our study validates 30 years of environmental policy and provides a road map for future ecological restoration. Humans strongly impact the dynamics of coastal systems, yet surprisingly few studies mechanistically link management of anthropogenic stressors and successful restoration of nearshore habitats over large spatial and temporal scales. Such examples are sorely needed to ensure the success of ecosystem restoration efforts worldwide. Here, we unite 30 consecutive years of watershed modeling, biogeochemical data, and comprehensive aerial surveys of Chesapeake Bay, United States to quantify the cascading effects of anthropogenic impacts on submersed aquatic vegetation (SAV), an ecologically and economically valuable habitat. We employ structural equation models to link land use change to higher nutrient loads, which in turn reduce SAV cover through multiple, independent pathways. We also show through our models that high biodiversity of SAV consistently promotes cover, an unexpected finding that corroborates emerging evidence from other terrestrial and marine systems. Due to sustained management actions that have reduced nitrogen concentrations in Chesapeake Bay by 23% since 1984, SAV has regained 17,000 ha to achieve its highest cover in almost half a century. Our study empirically demonstrates that nutrient reductions and biodiversity conservation are effective strategies to aid the successful recovery of degraded systems at regional scales, a finding which is highly relevant to the utility of environmental management programs worldwide.

Land Use and Salinity Drive Changes in SAV Abundance and Community Composition

Conserving and restoring submerged aquatic vegetation (SAV) are key management goals for estuaries worldwide because SAV integrates many aspects of water quality and provides a wide range of ecosystem services. Management strategies are typically focused on aggregated abundance of several SAV species, because species cannot be easily distinguished in remotely sensed data. Human land use and shoreline alteration have been shown to negatively impact SAV abundance, but the effects have varied with study, spatial scale, and location. The differences in reported effects may be partly due to the focus on abundance, which overlooks within-community and among-community dynamics that generate total SAV abundance. We analyzed long-term SAV aerial survey data (1984–2009) and ground observations of community composition (1984–2012) in subestuaries of Chesapeake Bay to integrate variations in abundance with differences in community composition. We identified five communities (mixed freshwater, milfoil-Zannichellia, mixed mesohaline, Zannichellia, and Ruppia-Zostera). Temporal variations in SAV abundance were more strongly related to community identity than to terrestrial stressors, and responses to stressors differed among communities and among species. In one fifth of the subestuaries, the community identity changed during the study, and the probability of such a change was positively related to the prevalence of riprapped shoreline in the subestuary. Mixed freshwater communities had the highest rates of recovery, and this may have been driven by Hydrilla verticillata, which was the single best predictor of SAV recovery rate. Additional species-specific and community-specific research will likely yield better understanding of the factors affecting community identity and SAV abundance, more accurate predictive models, and more effective management strategies.

Analysis of Historical Distribution of Submerged Aquatic Vegetation (SAV) in the York and Rappahannock Rivers as Evidence of Historical Water Quality Conditions

Recommended Citation Moore, K., Wilcox, D. J., Anderson, B., & Orth, R. J. (2001) Analysis of Historical Distribution of Submerged Aquatic Vegetation (SAV) in the York and Rappahannock Rivers as Evidence of Historical Water Quality Conditions. Special Reports in Applied Marine Science and Ocean Engineering (SRAMSOE) No. 375. Virginia Institute of Marine Science, William & Mary. https://doi.org/10.21220/V5Z740

Analysis of Histocial Distribution of SAV in the Eastern Shore Coastal Basins and Mid-Bay Island Complexes as Evidence of Historical Water Quality Conditions and a Restored Bay Ecosystem

Kenneth Moore, David Wilcox, Britt Anderson and Robert Orth The Virginia Institute of Marine Science School of Marine Science, College of William and Mary Gloucester Point, Virginia 23062 Special Report No. 383 in Applied Marine Science and Ocean Engineering Funded by: Environmental Protection Agency Chesapeake Bay Program Annapolis, MD 21401 Assistance ID No. CB983501-01-2 April 2003

Intensive Water Quality Mapping of Nearshore and Mid-Channel Regions of the James River Relative to SAV Growth and Survival Using the DATAFLOW Surface Water Quality Mapping System

Recommended Citation Moore, K., Anderson, B., & Wilcox, D. J. (2003) Intensive Water Quality Mapping of Nearshore and MidChannel Regions of the James River Relative to SAV Growth and Survival Using the DATAFLOW Surface Water Quality Mapping System. Special Reports in Applied Marine Science and Ocean Engineering (SRAMSOE) No. 385. Virginia Institute of Marine Science, William & Mary. https://doi.org/10.21220/ V5JX79