Revisiting the Chesapeake Bay phytoplankton index of biotic integrity

A novel comprehensive model of set pair analysis with extenics for river health evaluation and prediction of semi-arid basin - A case study of Wei River Basin, China

The accelerated development of urbanization in semi-arid areas is easy to cause varying degrees of disturbance to its fragile aquatic ecosystem. To find a general method for assessing the health status in semi-arid basins in China, and to provide theoretical basis for river health management and sustainable development, this study is that health evaluation index system is established in the Wei River Basin, covering a huge semi-arid area, and analyzed the biological structure of plankton obtained by field sampling and identified in laboratory, chemical conditions including dissolved oxygen, water temperature, ammonia nitrogen, pH, chlorophyll and other water physical and chemical factors determined by field instruments and sediment heavy metals analyzed in laboratory, physical habitat scored on site and social factors including water resource utilization rate and water consumption per 10,000 yuan of GDP collected in local water resource bulletin. Based on the idea of game theory, an improved coupling model of set pair analysis with extenics is established to assess and predict health. The results show that Wei River System and Jing River System are healthy, Beiluo River System is sub-healthy, and the whole Wei River Basin is also healthy; most of the cross-sections have a tendency to change to a bad level. Compared with simple weighting, set pair analysis and variable fuzzy set methods based on the corresponding sampling data and the weight in this paper, the coupling model can explain the transition and its trend between levels, reflect the certainty and uncertainty, and get more accurate results. It is suggested that daily monitoring and management should be strengthened in most sections to improve their health. And improve the development level of ecological function and social service function, give priority to the development of downstream water resources economy.

Development of a multimetric water quality Indicator for tracking progress towards the achievement of Chesapeake Bay water quality standards

A multimetric water quality standards (WQS) attainment indicator (MMI) was created to assess the habitat quality of the Chesapeake Bay and its tidal tributaries. The indicator uses metrics of dissolved oxygen concentrations, water clarity assessments, underwater bay grass acreages, and season-specific chlorophyll a distributions. This suite of metrics is recognized as symptomatic of eutrophication and responsive to nutrient and sediment management actions. Habitat criteria for these metrics were established by the US Environmental Protection Agency (USEPA) to protect the survival, growth, and reproduction of tidal bay living resources. The criteria were adopted into state WQS used to define outcome targets of the regulatory 2010 Chesapeake Bay Total Maximum Daily Load (TMDL). Direct accounting of monitoring results compared with state standards would be the most direct measure of water quality status related to achieving habitat health goal conditions under the TMDL. However, the Chesapeake Bay Program long-term water quality monitoring program that supports Clean Water Act 303d water quality impairment assessments does not provide sufficient measurement resolution across all temporal scales represented in these TMDL-related WQS. Recognizing data and analysis gaps, we developed the indicator to provide estimates of WQS attainment for the Chesapeake Bay. The structure of the indicator uses metrics that have been measured consistently with the historical Chesapeake Bay tidal water quality data collections since 1985. The ability to compute scores on contemporary and historical data will provide for bay-wide and spatially explicit long-term trend evaluations of habitat quality.

Remote sensing of bacterial response to degrading phytoplankton in the Arabian Sea

A remote sensing technique has been developed to detect physiological condition of phytoplankton using in situ and moderate imaging spectroradiometer (MODIS)-Aqua data. The recurring massive mixed algal bloom of diatom and Noctiluca scintillans in the Northern Arabian Sea during winter-spring was used as test bed to study formation, growth and degradation of phytoplankton. The ratio of chlorophyll (chl) to particulate organic carbon (POC) was considered as an indicator of phytoplankton physiological condition and used for the approach development. Algal blooms represent the areas of new production, and therefore, knowledge of their degradation is important to the study microbial loop and export carbon flux. Relation of chl/POC ratio with bacterial abundance revealed Gaussian distribution. Bacteria were strongly correlated with POC, and hence, the latter which is available from satellite data could be used as a proxy for remote assessment of bacteria. Thresholds for active and degrading phytoplankton were determined using the ratio computed from the satellite data. The criteria were implemented on MODIS data to generate an image representing distribution of degrading algal bloom. Bacteria abundance data from two validation cruises during dinoflagellate and cyanobacteria bloom confirmed well match up of phytoplankton degradation information from the satellite. Comparison of environmental parameters during decay phase of dinoflagellate (N. scintillans bloom (winter) and Trichodesmium bloom (summer) revealed that degradation after active Trichodesmium bloom was more severe as compared to the N. scintillans. The present study also highlights the prediction capability of phytoplankton degradation using a time series of satellite retrieved chlorophyll/POC images.