A pilot project to detect and forecast harmful algal blooms in the northern Gulf of Mexico

More timely access to data and information on the initiation, evolution and effects of harmful algal blooms can reduce adverse impacts on valued natural resources and human health. To achieve this in the northern Gulf of Mexico, a pilot project was initiated to develop a user-driven, end-to-end (measurements to applications) observing system. A key strategy of the project is to coordinate existing state, federal and academic programs at an unprecedented level of collaboration and partnership. Resource managers charged with protection of public health and aquatic resources require immediate notice of algal events and a forecast of when, where and what adverse effects will likely occur. Further, managers require integrated analyses and interpretations, rather than raw data, to make effective decisions. Consequently, a functional observing system must collect and transform diverse measurements into usable forecasts. Data needed to support development of forecasts will include such properties as sea surface temperature, winds, currents and waves; precipitation and freshwater flows with related discharges of sediment and nutrients; salinity, dissolved oxygen, and chlorophyll concentrations (in vivo fluorescence); and remotely-sensed spatial images of sea surface chlorophyll concentrations. These data will be provided via a mixture of discrete and autonomous in situ sensing with near real-time data telemetry, and remote sensing from space (SeaWiFS), aircraft (hyperspectral imagery) or land (high-frequency radar). With calibration across these platforms, the project will ultimately provide a 4-dimensional visualization of harmful algae events in a time frame suitable to resource managers.     

Application of the benthic index of biotic integrity to environmental monitoring in Chesapeake Bay

The Chesapeake Bay benthic index of biotic integrity (B-IBI) was developed to assess benthic community health and environmental quality in Chesapeake Bay. The B-IBI provides Chesapeake Bay monitoring programs with a uniform tool with which to characterize bay-wide benthic community condition and assess the health of the Bay. A probability-based design permits unbiased annual estimates of areal degradation within the Chesapeake Bay and its tributaries with quantifiable precision. However, of greatest interest to managers is the identification of problem areas most in need of restoration. Here we apply the B-IBI to benthic data collected in the Bay since 1994 to assess benthic community degradation by Chesapeake Bay Program segment and water depth. We used a new B-IBI classification system that improves the reliability of the estimates of degradation. Estimates were produced for 67 Chesapeake Bay Program segments. Greatest degradation was found in areas that are known to experience hypoxia or show toxic contamination, such as the mesohaline portion of the Potomac River, the Patapsco River, and the Maryland mainstem. Logistic regression models revealed increased probability of degraded benthos with depth for the lower Potomac River, Patapsco River, Nanticoke River, lower York River, and the Maryland mainstem. Our assessment of degradation by segment and water depth provided greater resolution of relative condition than previously available, and helped define the extent of degradation in Chesapeake Bay.     

Competitive Retention of Lead and Cadmium on an Agricultural Soil

Lead and cadmium contamination of an agricultural soil has been studied using batch and column experiments. Thermodynamics of theretention phenomena may be represented by a Langmuir isotherm foran aqueous metal concentration up to 100 mg L^-1. First order kinetics with respect to the solid phase yield good predictabilityfor both batch and column experiments. Kinetics and thermodynamics of lead retention predominate over those ofcadmium. As a consequence, lead is preferentially retainedand can even displace sorbed cadmium. In the event of anspill involving both metals, cadmium would move further inthe soil and its aqueous concentration downstream could beeven higher than that of the influent solution, increasingpotential risks. A two-region model has been used to fit all the experimental results. Satisfactory predictions for column experiments are obtained with parameters which are consistent with those obtained for the batch experiments, for which sorption is described by a Langmuir isotherm including competitive retention.     

Cumulative effect assessment in Canada: a regional framework for aquatic ecosystems

Sustainable development of the aquatic environment depends upon routine and defensible cumulative effects assessment (CEA). CEA is the process of predicting the consequences of development relative to an assessment of existing environmental quality. Theoretically, it provides an on-going mechanism to evaluate if levels of development exceed the environment's assimilative capacity; i.e., its ability to sustain itself. In practice, the link between CEA and sustainable development has not been realized because CEA concepts and methods have developed along two dichotomous tracks. One track views CEA as an extension of the environmental assessment (EA) process for project developments. Under this track, stressor-based (S-B) methods have been developed where the emphasis is on local, project-related stressors, their link with aquatic indicators, and the potential for environmental effects through stressor-indicator interactions. S-B methods focus on the proposed development and prediction of project-related effects. They lack a mechanism to quantify existing aquatic quality especially at scales broader than an isolated development. This limitation results in the prediction of potential effects relative to a poorly defined baseline state. The other track views CEA as a broader, regional assessment tool where effects-based (E-B) methods specialize in quantification of existing aquatic effects over broad spatial scales. However, the predictive capabilities of E-B methods are limited because they are retrospective, i.e., the stressor causing the effect is identified after the effect has been measured. When used in isolation, S-B and E-B methods do not address CEA in the context necessary for sustainable development. However, if the strengths of these approaches were integrated into a holistic framework for CEA, an operational mechanism would exist to better monitor and assess sustainable development of our aquatic resources. This paper reviews the existing conceptual basis of CEA in Canada including existing methodologies, limitations and strengths. A conceptual framework for integrating project-based and regional-based CEA is presented.     

Investigation of the Influence of Seagrass on Fisheries Catch Level Using Isotonic Regression

The relationship between seagrass area and the commercial catch of some economically important South Australian fish species is not known in any quantitative sense. However, there is evidence in the literature to suggest that seagrass decline will detrimentally impact on species abundance and composition, and consequently that the presence or absence of seagrass will compromise the commercial and recreational fishery. In this paper we describe the construction of models based on order restricted (isotonic) regression and discuss the role of seagrass area, in terms of its influence on the level of commercial catch through modifying the effect of fishing 'effort'.     

Metal Pollution Assessment of Sediment and Water in the River Hindon, India

The metal pollution in water and sediment of the River Hindon in western Uttar Pradesh (India) was assessed for Cd, Cr, Cu, Fe, Mn, Ni, Pb and Zn. The metal concentrations in water showed wide temporal variation compared with bed sediment because of variability in water discharge and variations in suspended solid loadings. Metal concentrations in bed sediments provided a better evaluation of the degree and the extent of contamination in the aquatic environment, Santagarh and Atali being the most polluted sites of the river. The ratio of heavy metals to conservative elements (Fe, Al, etc.) may reveal the geochemical imbalances due to the elevated metal concentrations normally attributed to anthropogenic sources. Metal/Al ratios for the bed sediments of the river Hindon were used to determine the relative mobility and general trend of relative mobility occurred Fe > Mn > Zn > Cr > Ni > Pb > Cu > Cd.     

Linking Land Cover and Water Quality in New York City’S Water Supply Watersheds

The Catskill/Delaware reservoirs supply 90% of New York City’s drinking water. The City has implemented a series of watershed protection measures, including land acquisition, aimed at preserving water quality in the Catskill/Delaware watersheds. The objective of this study was to examine how relationships between landscape and surface water measurements change between years. Thirty-two drainage areas delineated from surface water sample points (total nitrogen, total phosphorus, and fecal coliform bacteria concentrations) were used in step-wise regression analyses to test landscape and surface-water quality relationships. Two measurements of land use, percent agriculture and percent urban development, were positively related to water quality and consistently present in all regression models. Together these two land uses explained 25 to 75% of the regression model variation. However, the contribution of agriculture to water quality condition showed a decreasing trend with time as overall agricultural land cover decreased. Results from this study demonstrate that relationships between land cover and surface water concentrations of total nitrogen, total phosphorus, and fecal coliform bacteria counts over a large area can be evaluated using a relatively simple geographic information system method. Land managers may find this method useful for targeting resources in relation to a particular water quality concern, focusing best management efforts, and maximizing benefits to water quality with minimal costs.The United States Environmental Protection Agency through its Office of Research and Development funded and managed the research described here. It has been subjected to Agency’s administrative review and approved for publication as an EPA document.     

A Spatial Model to Estimate Habitat Fragmentation and Its Consequences on Long-Term Persistence of Animal Populations

The increasing use of the landscape by humans has led to important diminutions of natural surfaces. The remaining patches of wild habitat are small and isolated from each other among a matrix of inhospitable land-uses. This habitat fragmentation, by disabling population movements and stopping their spread to new habitats, is a major threat to the survival of numerous plant and animal species. We developed a general model, adaptable for specific species, capable of identifying suitable habitat patches within fragmented landscapes and investigating the capacity of populations to move between these patches. This approach combines GIS analysis of a landscape, with spatial dynamic modeling. Suitable habitat is identified using a threshold area to perimeter ratio. Potential movement pathways of species between habitat patches are modeled using a cellular automaton. Habitat connectivity is estimated by overlaying habitat patches with movement pathways. The maximum potential population is calculated within and between connected habitat patches and potential risk of inbreeding within meta-populations is considered. The model was tested on a sample map and applied to scenario maps of predicted land-use change in the Peoria Tri-county region (IL). It (1) showed area of natural area alone was insufficient to estimate the consequences on animal populations; (2) underscored the necessity to use approaches investigating the effect of land-use change spatially through the landscape and the importance of considering species-specific life history characteristics; and (3) highlighted the model's potential utility as an indicator of species likelihood to be affected negatively by land-use scenarios and therefore requiring detailed investigation.     

Determination of pollution trends in an abandoned mining site by application of a multivariate statistical analysis to heavy metals fractionation using SM&T-SES

The mobility, availability and persistence of Heavy Metals (HMs), As, Cd, Cu, Ni, Pb and Zn, in contaminated soils of a former abandoned mining area were evaluated by means of a sequential extraction scheme (SES) and applying a multivariate statistical analysis to the obtained data. Chemical partitioning of HMs in each sample was determined in four fractions (acid-soluble, reducible, oxidable and residual) following the Standard Measurements and Testing (SM&T) SES, formerly BCR-SES. Statistical evaluation of results by pattern recognition techniques allowed identification of groups of samples with similar characteristics and observations of correlations between variables, determining the pollution trends and distribution of HMs within the studied area. Typical metal-fraction association and metal availability characteristics of heavy metals have been depicted. The obtained results indicate an urgent need to attenuate the hazard in that area posed by high concentrations of toxic metals, which exceed the limits specified by different European legislations on soil reclamation.     

Flow-injection analysis with fluorescence detection for the determination of trace levels of ammonium in seawater

A method using flow-injection, gas-diffusion, derivatisation and then fluorescent detection has been established for ammonium ion determination in seawater. The fluorescent derivative formed by reacting ortho-phthaldialdehyde (OPA) and sulfite with ammonia gives high sensitivity while removing potential interferences. This is required to measure the low concentrations of ammonium often seen in the open ocean. The experimental conditions (flow-rate, reagent concentrations, membrane configurations, etc.) were manipulated to improve performance. For a sample throughput of 30 samples h(-1), the limit of detection was 7 nM, the coefficient of variation was 5.7% at 800 nM, and the calibration curve was linear to at least 4 micromol L(-1). Interferences were minimised by a gaseous diffusion step. Volatile small molecular-weight amines as interferents were discriminated against by this method. They neither passed through the membrane as efficiently as ammonia, nor reacted as readily with OPA when sulfite was the reductant. Contamination by ammonia from laboratory and shipboard sources complicates application of the method to natural waters, especially measurement of low concentrations (<100 nM) in open-ocean waters. Steps to overcome contamination are described in detail. Some results are presented for ammonium determination in Southern Ocean and Huon Estuary (Tasmania) waters.