Using Marxan and Marxan with Zones to support marine planning

With the growth in human pressures on the marine environment and the increase in competition for space and resources there has been recognition by many governments of the need to use the marine environment sustainably and allow for its acceptable allocation for each sector. The aim of this thesis is to evaluate the use of Marxan and Marxan with Zones as practical tools to enable the production of marine plans that integrate environmental and socioeconomic data and to suggest best practice in the types of data used. In this thesis three key aspects of data type and integration were identified and evaluated. The resolution and complexity of data required to protected marine biodiversity was assessed. The effects of using different substrate data resolution on the selection of sites to protect a range of biotopes using Marxan are determined. The nature of the data used in marine planning has significant implications for the protection of marine biodiversity. Using less complex data, of any resolution, did not adequately protect marine biodiversity. There is a need to determine what is an acceptable allocation of marine resource to each sector. Two case study areas were used to determine how to integrate conservation and socioeconomic data and objectives in a marine plan. Objectives for all the sectors could not be met completely in a single marine plan and each sector had to compromise. This research highlighted the potential compromises required and indicates that if marine heritage and biodiversity are to be protected each sector will have to change the impact it has on the marine environment. Currently marine conservation assumes that all data on habitats and species presented for use in marine planning are equal, in accuracy, precision and value. This is not always the case, with data based on a wide range of sources including routine government monitoring, specific innovative research and stakeholder based data gathering. A case study area was used to evaluate the impacts of using confidence levels in habitat data on marine biodiversity. It was found that data outputs that best protected marine biodiversity used data over 20% and over 30% confidence. With the data currently available for the UK marine environment it is not possible to be confident that a representative MPA network can be created. Together these studies contribute key recommendations for best practice in marine planning and demonstrate that the use of spatial decision support tools (Marxan and Marxan with Zones) are essential for the integration of data in marine planning, to assess how using different types of data will impact marine planning and marine biodiversity protection and to explore implications of different management actions

The modern and late Holocene marine environments of Loch Sunart, N.W. Scotland

The first study to exploit the sedimentary archives of Loch Sunart, a relatively well-flushed fjord on the NW coast of Scotland, for palaeoenvironmental reconstruction is presented. In order to understand environmental influences on past environments, the modern physical, chemical and biological conditions of the loch and surrounding catchment were studied. Both observational and computer modelled annual inner basin salinity show a clear response to climatic forcing, modulated by NAO behaviour. Main basin salinity appears to remain very stable and a well-defined salinity: δ¹⁸O relationship suggests excellent potential for palaeotemperature reconstructions based on foraminiferal δ¹⁸O . Multi-variate statistical analyses identified 4 benthic foraminiferal assemblage groups in the surface sediments of the loch: A) restricted basin (E. scaber); B) very high current activity (C. lobatulus-A. mammilla -A. beccarii); C) calm environment undera stratified water column (B. marginata-N. turgida-S. fusiformis) and D) coastal water influence and mild/episodic current activity (A. beccarii-C. lobatulus-S. wrightii-E. excavatum). Using assemblage data, an existing benthic foraminiferal transfer function was modified in order to reconstruct Loch Sunart bottom water temperature (BWS); these reconstructions agree well with Scottish coastal temperature series (Millport). C. lobatulus appears to calcify close to theoretical equilibrium δ¹⁸O calcite (Δδ¹⁸O = -0.11 ± 0.17 %), probably during the warm bottom water temperatures (BWT) of late autumn, and predominantly reflects changes in BWT rather than BWS in the main basin of Loch Sunart. The first late Holocene high resolution palaeoenvironmental reconstruction from the deep (121 m) main basin of Loch Sunart is presented; gravity core (GC023) is 3 m long and spans the last 2,000 years. Despite difficulties with geochronology, palaeoenvironmental reconstructions from Loch Sunart suggest that these high resolution sedimentary archives have the potential to resolve inter-annual marine climate variability of the order of 1-2°C and capture an integrated record of changes in the catchment and marine environment

Ecological monitoring methods for the assessment of pesticide impacts in the tropics

The use of agrochemicals in developing countries has increased greatly in recent years and those used in greatest quantities, insecticides and herbicides, tend to have the most severe side-effects on the environment. Following UNCED 1992 and its adoption of Agenda 21, there is now a requirement for all countries to carry out pesticide impact monitoring and assessment to counter environmental degradation. The recent UNCED Summit 2002 has set targets to step up the implementation of this commitment. Ecological Monitoring Methods for the Assessment of Pesticide Impact in the Tropics aims to assist developing countries build their capability in ecotoxicological monitoring. It harnesses the knowledge of pesticide impact and monitoring specialists to provide guidance on the measurement, analysis and interpretation of change in animal populations and key soil functions. This handbook will be of primary interest to those in government, development agencies, donors and non-governmental organizations who carry responsibility for the environment, agricultural and public health. Academics and students of ecotoxicology in developing countries should find both the specialist chapters and the field methodology useful

Machine Learning in Sensors and Imaging

Machine learning is extending its applications in various fields, such as image processing, the Internet of Things, user interface, big data, manufacturing, management, etc. As data are required to build machine learning networks, sensors are one of the most important technologies. In addition, machine learning networks can contribute to the improvement in sensor performance and the creation of new sensor applications. This Special Issue addresses all types of machine learning applications related to sensors and imaging. It covers computer vision-based control, activity recognition, fuzzy label classification, failure classification, motor temperature estimation, the camera calibration of intelligent vehicles, error detection, color prior model, compressive sensing, wildfire risk assessment, shelf auditing, forest-growing stem volume estimation, road management, image denoising, and touchscreens