Relationships between land use and nitrogen and phosphorus in New Zealand lakes

Developing policies to address lake eutrophication requires an understanding of the relative contribution of different nutrient sources and of how lake and catchment characteristics interact to mediate the source–receptor pathway. We analysed total nitrogen (TN) and total phosphorus (TP) data for 101 New Zealand lakes and related these to land use and edaphic sources of phosphorus (P). We then analysed a sub-sample of lakes in agricultural catchments to investigate how lake and catchment variables influence the relationship between land use and in-lake nutrients. Following correction for the effect of co-variation amongst predictor variables, high producing grassland (intensive pasture) was the best predictor of TN and TP, accounting for 38.6% and 41.0% of variation, respectively. Exotic forestry and urban area accounted for a further 18.8% and 3.6% of variation in TP and TN, respectively. Soil P (representing naturally-occurring edaphic P) was negatively correlated with TP, owing to the confounding effect of pastoral land use. Lake and catchment morphology (zmax and lake : catchment area) and catchment connectivity (lake order) mediated the relationship between intensive pasture and in-lake nutrients. Mitigating eutrophication in New Zealand lakes requires action to reduce nutrient export from intensive pasture and quantifying P export from plantation forestry requires further consideration

A study of Minnesota land and water resources using remote sensing

A pilot study of 60 lakes in Minnesota shows that LANDSAT data correlate very well with the Carlson trophic state index which is derived from measurements in the field. Nimbus satellite data reveal improvement in water quality in Lake Superior since the dumping of taconite tailings stopped in 1980. A feasibility study of using color infrared photography as a near real time tool for soil and crop management in corn and soybean areas of the state generated strong interest from farmers and agribusiness firms. The state geological survey had success in the use and applications of LANDSAT images. Subtleties of changes in vegetation, soil, and topography are such that ground water presence and depth to water table are nearly always impossible to qualify except for broad scale applications. Bedrock and structural differences as shown in lineaments offer great potential for resolution of some kinds of geologic studies. A synergistic concept is to be used to search for mineral resources in the northeastern part of the state

A study of the relative effectiveness and cost of computerized information retrieval in the interactive mode

Results of a number of experiments to illuminate the relative effectiveness and costs of computerized information retrieval in the interactive mode are reported. It was found that for equal time spent in preparing the search strategy, the batch and interactive modes gave approximately equal recall and relevance. The interactive mode however encourages the searcher to devote more time to the task and therefore usually yields improved output. Engineering costs as a result are higher in this mode. Estimates of associated hardware costs also indicate that operation in this mode is more expensive. Skilled RECON users like the rapid feedback and additional features offered by this mode if they are not constrained by considerations of cost

Environmental factors controlling lake diatom communities: a meta-analysis of published data

p. 15889, 15909Diatoms play a key role in the development of quantitative methods for environmental reconstruction in lake ecosystems. Diatom-based calibration datasets developed dur-ing the last decades allow the inference of past limnological variables such as TP, pH or conductivity and provide information on the autecology and distribution of diatom taxa. However, little is known about the relationships between diatoms and climatic or geographic factors. The response of surface sediment diatom assemblages to abi-otic factors is usually examined using canonical correspondence analysis (CCA) and subsequent forward selection of variables based on Monte Carlo permutation tests that show the set of predictors best explaining the distributions of diatom species. The results reported in 40 previous studies using this methodology in different regions of the world are re-analyzed in this paper. Bi- and multivariate statistics (canonical cor-relation and two-block partial least-squares) were used to explore the correspondence between physical, chemical and physiographical factors and the variables that explain most of the variance in the diatom datasets. Results show that diatom communities respond mainly to chemical variables (pH, nutrients) with lake depth being the most important physiographical factor. However, the relative importance of certain param-eters varied along latitudinal and trophic gradients. Canonical analyses demonstrated a strong concordance with regard to the predictor variables and the amount of variance they captured, suggesting that, on a broad scale, lake diatoms give a robust indication of past and present environmental conditions.S

Seafloor characterization using airborne hyperspectral co-registration procedures independent from attitude and positioning sensors

The advance of remote-sensing technology and data-storage capabilities has progressed in the last decade to commercial multi-sensor data collection. There is a constant need to characterize, quantify and monitor the coastal areas for habitat research and coastal management. In this paper, we present work on seafloor characterization that uses hyperspectral imagery (HSI). The HSI data allows the operator to extend seafloor characterization from multibeam backscatter towards land and thus creates a seamless ocean-to-land characterization of the littoral zone

Local institutions and Natural Resource Management

As researchers and policy-makers confront the challenges of and opportunities for improving natural resource management, increasing attention is being given to the dynamics of coupled natural-human systems. Interdisciplinary study of these coupled systems has generated considerable research and management innovations. Among these are more intensive research of the emergence and behavior of local institutions and consideration of the potential for voluntary and/or collaborative approaches to supplement conventional natural resource policy and management approaches. Front and center in this line of research are studies of local institutional responses to common pool resource management issues. Over time, this productive line of research is encouraging greater integration of insights across social science fields and identification of systematic patterns in research findings. Responding to such encouragement, this research blends insights from collective action theory, institutional rational choice and the institutional analysis and development (IAD) framework to investigate the distribution and success of resource-based organizations. Moreover, our research makes a unique contribution to this literature by considering the spatial aspects of these institutions' formation, behavior and success. Lake associations are an interesting class of resource-based organizations. These local, lake-centered institutions strive to address management issues using informal and voluntary strategies. Lake associations are most common in lake-rich states, including Minnesota, Michigan, Wisconsin, New York, New Hampshire and Maine. The objectives of these groups vary from narrow (private road maintenance) to broad (watershed health). These organizations allow for lake-centered boundaries including multiple jurisdictions, provide a voice to seasonal property owners, and resolve some issues related to coordination, property rights, and transaction costs. The numerous and diverse lake associations of Maine are the focus of our empirical work. The primary research objective of this analysis is to develop an integrated empirical modeling framework of lake association presence and lake management success. To fulfill this objective, we examined the relative performance of empirical econometric models that ignore and address potential sample selection bias. Because we only observe measures of lake association management success on lakes that have a lake association, the sample is non-random. In our empirical work, entry into the lake association management success sample is further complicated by our reliance on survey data to describe management behavior and performance. A broad secondary research objective is to continue exploring the extent to which the Institutional Development Analysis (IAD) framework can be used to explain the distribution and behavior of Maine lake associations. We assembled an extensive spatial database describing natural and human features of 2,602 Maine lakes (Maine's great ponds; > 10 acres in size) to support this analysis. We integrated this extensive database with a smaller survey-based database describing lake association behavior and natural resource management success. Data describing the distribution and success of lake associations were drawn from non-government organization, federal and state agency databases and primary survey data collected to describe social and economic characteristics of Maine lakes. We captured additional lake and association attributes by manipulating various state and federal GIS databases and creating primary spatial databases. Results to date reveal support for the IAD theoretical framework in describing factors influencing the presence of lake associations. These results offer guidance on how to better integrate the informal approaches of local institutions with more formal, regional government-based management approaches. By understanding where local institutions are likely to form and what issues they are best suited to address, state and federal government agencies can better work with local organizations to address the complexities of natural resource management. Results explaining variation in natural resource management success and the potential gains from an integrated model of presence and success are less robust and are constrained by limited available data describing management behavior and success.local institutions, natural resource management, institutional economics, lake associations, Resource /Energy Economics and Policy,

Peace education, militarism and neo-liberalism: conceptual reflections with empirical findings from the UK

This article explores ‘peace days’ in English schools as a form of peace education. From a historical overview of academic discussions on peace education in the US and Great Britain since the First World War, we identify three key factors important for peace education: the political context, the place in which peace days occur and pedagogical imperatives of providing a certain narrative of the sources of violence in politics. Although contemporary militarism and neoliberalism reduce the terrains for peace studies in English schools, peace days allow teachers to carve out spaces for peace education. Peace days in Benfield School, Newcastle and Comberton Village College, Cambridgeshire, are considered as case studies. We conclude with reflections on the opportunities and limitations of this approach to peace education, and on how peace educators and activists could enlarge its reach

Table Augmentation in Data Lakes

Data lakes are centralized repositories that store large quantities of raw, unstructured, and structured data, allowing for ad-hoc data analysis, exploratory data analysis, and machine learning. However, the lack of metadata and schema in data lakes makes it challenging to work with tabular data and find related information stored in different tables. However, it is still an open problem how efficiently retrieve these tables at large scale when the settings of a data lake holds. The thesis introduces a novel approach to table augmentation that enables efficient data integration from multiple sources in a data lake. Table augmentation involves adding new data to an existing table in a horizontal fashion (by retrieving tables that can be horizontally concatenated to a query that serves as query table). The proposed approach consists of several components, including data lakes hashing, join search, similarity, and augmentation. The proposed approach is named TASH. TASH is a framework based on a spatial index in which tables are mapped and queried. Its goal is to identify the most useful columns for subsequent machine learning tasks. The table retrieval process employs a combination of set containment search and similarity search. Candidate tables are initially identified using set containment search and then ranked based on their similarity to the query. Experimental results demonstrate that TASH can effectively identify joinable tables and select the most relevant features, thereby enabling efficient table augmentation in data lakes. This research contributes to the field of big data by providing a practical solution to the challenges of data integration and analysis in data lake environments