Concentrations of major ions in the stream water of the River Duddon, England, 1970-1974 [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of some major ions in the stream water of the River Duddon in Cumbria. Measurements of sodium, calcium, potassium, magnesium and chloride ions and pH were taken at 5 stations in the River Duddon between January 1970 and August 1974.

Concentrations of major ions in the stream water of the upper basin of the River Duddon, England, 1972-1974 [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of some major ions in the stream water of the upper basin of the River Duddon in Cumbria. Measurements of sodium, calcium, potassium, magnesium and chloride ions and pH were taken at 26 stations in the River Duddon basin between 1972 and 1974.

Analysis of stream waters in the catchment of Lake Windermere (1975-1978), England [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of some major ions in the stream water of the catchment of Lake Windermere in Cumbria. Measurements of sodium, calcium, potassium, magnesium, chloride ions and pH were taken at 37 stations in the catchment between 1975 and 1978.

Analyses of treated sewage effluent from Grasmere Treatment Unit (1974-1976), England [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of treated sewage effluent from Grasmere Treatment Unit in Cumbria. Measurements of sodium, calcium, potassium, magnesium and chloride ions were taken between 1974 and 1976.

Major ions in 25 frequently sampled tarns in the English Lake District (1954-56, 1974-1976) [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of 25 frequently sampled tarns in Cumbria. Measurements of sodium, calcium, potassium, magnesium, pH, chloride ions, alkalinity, sulphite, strong acids and nitrate were taken between 1954 and 1956 and between 1974-1976.

Concentrations of major ions in 182 tarns in the English Lake District (1953-1978) [Dataset]

This dataset provides raw data of chemical analyses made during studies on seasonal variations of 182 tarns in the English Lake District, Cumbria. Measurements of sodium, calcium, potassium, magnesium, pH, chloride ions, alkalinity, sulphite, strong acids and nitrate were taken between 1953 and 1978.

Physical Constraints to Aquatic Plant Growth in New Zealand Lakes

The nature of aquatic plant communities often defines benthic habitat within oligotrophic and mesotrophic lakes and lake management increasingly recognizes the importance of maintaining plant diversity in order to sustain biological diversity and capacity within lakes. We have developed simple statistical relationships between key physical and vegetation variables that define the habitat requirements, or “habitat-templates”, of key vegetation types to facilitate management of plant communities in New Zealand lakes. Statistical relationships were derived from two datasets. The first was a multi-lake dataset to determine the effects of water level fluctuation and water clarity. The second dataset was from a comprehensive shoreline survey of Lake Wanaka, which allowed us to examine within-lake variables such as beach slope and wave action. Sufficient statistical relationships were established to develop a habitat template for each of the major species or assemblages. The relationships suggested that the extent and diversity of shallow-growing species was related to a combination of the extent of water level fluctuation and wave exposure. (PDF contains 9 pages.)

Investigating changes in global tropical cyclone storm frequency and intensity

Understanding fluctuations in tropical cyclone activity along United States shores and abroad becomes increasingly important as coastal managers and planners seek to save lives, mitigate damage, and plan for resilience in the face of changing storminess and sea-level rise. Tropical cyclone activity has long been of concern to coastal areas as they bring strong winds, heavy rains, and high seas. Given projections of a warming climate, current estimates suggest that not only will tropical cyclones increase in frequency, but also in intensity (maximum sustained winds and minimum central pressures). An understanding of what has happened historically is an important step in identifying potential future changes in tropical cyclone frequency and intensity. The ability to detect such changes depends on a consistent and reliable global tropical cyclone dataset. Until recently no central repository for historical tropical cyclone data existed. To fill this need, the International Best Track Archive for Climate Stewardship (IBTrACS) dataset was developed to collect all known global historical tropical cyclone data into a single source for dissemination. With this dataset, a global examination of changes in tropical cyclone frequency and intensity can be performed. Caveats apply to any historical tropical cyclone analysis however, as the data contributed to the IBTrACS archive from various tropical cyclone warning centers is still replete with biases that may stem from operational changes, inhomogeneous monitoring programs, and time discontinuities. A detailed discussion of the difficulties in detecting trends using tropical cyclone data can be found in Landsea et al. 2006. The following sections use the IBTrACS dataset to show the global spatial variability of tropical cyclone frequency and intensity. Analyses will show where the strongest storms typically occur, the regions with the highest number of tropical cyclones per decade, and the locations of highest average maximum wind speeds. (PDF contains 3 pages)

A chemical survey of standing waters in south-east England, with reference to acidification and eutrophication

This study looks at the distribution and magnitude of acidification and eutrophication in south-east England where there are no natural lakes but a large number of shallow artificial ponds. The study area is defined as the region lying within a 100 km radius of central London but excluding the area within the M25 motorway. Water samples were taken from 120 sites between mid-January and the end of February 1990, with a subsequent monthly survey of a subset of 31 of these waters. Twelve chemical variables were measured in the laboratory using standard techniques. PH values for the full dataset ranged from 3.2 to 8.4, although the majority of sites had pH values in the range 7.0 to 8.5; only five sites had a pH of less than 6.0. The five low pH sites expectedly had low alkalinities and are the only sites with values below 0.1 meq per litre. Concentrations of calcium, sodium, potassium, magnesium, chloride, sulphate and nitrate had normal distributions. The majority of sites had total phosphorus concentrations in the range 25 to 200 mu g per litre, although 10 sites had concentrations above 400 mu g per litre. The low number of acid sites suggests that surface water acidity is not a widespread regional problem in south-east England. However the survey shows that a large number of standing waters in the region have high total phosphorus and nitrate concentrations, and 89% may be considered moderately to considerably eutrophic.

An introduction to RIVPACS

RIVPACS (River InVertebrate Prediction And Classification System) is a software package developed by the Institute of Freshwater Ecology (IFE). The primary application is to assess the biological quality of rivers within the UK. RIVPACS offers site-specific predictions of the macroinvertebrate fauna to be expected in the absence of major environmental stress. The expected fauna is derived by RIVPACS using a small suite of environmental characteristics. The biological evaluation is then obtained by comparing the fauna observed at the site with the expected fauna. RIVPACS also includes a site classification based on the macroinvertebrate fauna of the component reference sites. New sites, judged by their fauna to be of high biological quality, may be allocated to classification groups within the fixed RIVPACS classification. This has potential for evaluating sites for conservation. In this chapter, the origins and history of the RIVPACS approach are described, including major scientific and operational developments over the life of the project. RIVPACS III is described in detail and predictions at different taxonomic levels are demonstrated. The value of the reference dataset for river management and conservation is examined, and the chapter concludes with a brief consideration of some future challenges.

Economic and social impacts of Integrated Aquaculture-Agriculture technologies in Bangladesh

This study estimated the adoption rate of integrated aquaculture-agriculture (IAA) technologies in Bangladesh and their impact on poverty and fish and food consumption in adopting households. We used a novel, simulation-based approach to impact assessment called Tradeoff Analysis for Multi-Dimensional Impact Assessment (TOA-MD). We used the TOA-MD model to demonstrate how it is possible to use available data to estimate adoption rates in relevant populations, and to quantify impacts on distributional outcomes such as poverty and food security, thus demonstrating ex ante the potential for further investment in technology dissemination. The analysis used baseline and end-of-project survey data from WorldFish-implemented Development of Sustainable Aquaculture Project (DSAP), promoting IAA. This dataset was used to simulate adoption and assess its impacts on poverty and food security in the target population. We found that, if adopted, IAA had a significant positive impact on reducing poverty and improving food security and income.

A guide to monitoring reef fish in the National Park Service's South Florida/Caribbean Network

Reef fishes are conspicuous and essential components of coral reef ecosystems and economies of southern Florida and the United States Virgin Islands (USVI). Throughout Florida and the USVI, reef fish are under threat from a variety of anthropogenic and natural stressors including overfishing, habitat loss, and environmental changes. The South Florida/Caribbean Network (SFCN), a unit of the National Park Service (NPS), is charged with monitoring reef fishes, among other natural and cultural resources, within six parks in the South Florida - Caribbean region (Biscayne National Park, BISC; Buck Island Reef National Monument, BUIS; Dry Tortugas National Park, DRTO; Everglades National Park, EVER; Salt River Bay National Historic Park and Ecological Preserve, SARI; Virgin Islands National Park, VIIS). Monitoring data is intended for park managers who are and will continue to be asked to make decisions to balance environmental protection, fishery sustainability and park use by visitors. The range and complexity of the issues outlined above, and the need for NPS to invest in a strategy of monitoring, modeling, and management to ensure the sustainability of its precious assets, will require strategic investment in long-term, high-precision, multispecies reef fish data that increases inherent system knowledge and reduces uncertainty. The goal of this guide is to provide the framework for park managers and researchers to create or enhance a reef fish monitoring program within areas monitored by the SFCN. The framework is expected to be applicable to other areas as well, including the Florida Keys National Marine Sanctuary and Virgin Islands Coral Reef National Monument. The favored approach is characterized by an iterative process of data collection, dataset integration, sampling design analysis, and population and community assessment that evaluates resource risks associated with management policies. Using this model, a monitoring program can adapt its survey methods to increase accuracy and precision of survey estimates as new information becomes available, and adapt to the evolving needs and broadening responsibilities of park management.

Habitat availability and heterogeneity and the Indo-Pacific warm pool as predictors of marine species richness in the tropical Indo-Pacific

Range overlap patterns were observed in a dataset of 10,446 expert-derived marine species distribution maps, including 8,295 coastal fishes, 1,212 invertebrates (crustaceans and molluscs), 820 reef-building corals, 50 seagrasses and 69 mangroves. Distributions of tropical Indo-Pacific shore fishes revealed a concentration of species richness in the northern apex and central region of the Coral Triangle epicenter of marine biodiversity. This pattern was supported by distributions of invertebrates and habitat-forming primary producers. Habitat availability, heterogeneity and sea surface temperatures were highly correlated with species richness across spatial grains ranging from 23,000 to 5,100,000 km2 with and without correction for autocorrelation. The consistent retention of habitat variables in our predictive models supports the area of refuge hypothesis which posits reduced extinction rates in the Coral Triangle. This does not preclude support for a center of origin hypothesis that suggests increased speciation in the region may contribute to species richness. In addition, consistent retention of sea surface temperatures in models suggests that available kinetic energy may also be an important factor in shaping patterns of marine species richness. Kinetic energy may hasten rates of both extinction and speciation. The position of the Indo-Pacific Warm Pool to the east of the Coral Triangle in central Oceania and a pattern of increasing species richness from this region into the central and northern parts of the Coral Triangle suggests peripheral speciation with enhanced survival in the cooler parts of the Coral Triangle that also have highly concentrated available habitat. These results indicate that conservation of habitat availability and heterogeneity is important to reduce extinction and that changes in sea surface temperatures may influence the evolutionary potential of the region.

Analyzing and mapping fish assemblages off central California, USA

This study describes fish assemblages and their spatial patterns off the coast of California from Point Arena to Point Sal, by combining the results of the multivariate analyses of several fisheries datasets with a geographic information system. In order to provide comprehensive spatial coverage for the areas of inshore, continental shelf, and continental slope, three fisheries datasets were analyzed: 1) Inshore: the California Department of Fish and Game dataset of fishery-dependent commercial passenger fishing vessel trips that targeted rockfish; 2) Continental Shelf: the National Marine Fisheries Service (NMFS) fishery-independent bottom trawls; and 3) Continental Slope: the NMFS fishery-independent bottom trawls on the continental slope. One-hundred seven species were analyzed. These species represented those captured in at least 5% of the fishing trips or trawls in at least one of the three data sets. We analyzed each of the three datasets separately, and the three sets of results were combined to define 28 species assemblages and 23 site groups. A species assemblage consisted of species caught together, whereas a site group consisted of fishing trips or trawl locations that tended to have the same species assemblages. At the scale of these datasets, 97% of all site groups were significantly segregated by depth.

Real-time climate monitoring using an AVHRR-based vegetation index

A normalized difference vegetation index (NDVI) has been produced and archived on a 1° latitude by 1° longitude grid between 55°S and 75°N. The many sources of data errors in the NDVI include cloud contamination, scan angle biases, changes in solar zenith angle, and sensor degradation. Week-to-week variability, primarily caused by cloud contamination and scan angle biases, can be minimized by temporally filtering the data. Orbital drift and sensor degradation introduces interannual variability into the dataset. These trends make the usefulness of a long-term climatology uncertain and limit the usefulness of the NDVI. Elimination of these problems should produce an index that can be used for climate monitoring.