Transboundary research in fisheries

Spatial boundaries have become an indispensable part of regimes and tools for regulating fisheries, with examples including marine protected areas, regional fisheries management organizations and Exclusive Economic Zones. Yet, it is also widely acknowledged that boundaries are a social construct, which may be resisted by both fishers and fish ecology. The ensuing spatial and institutional mismatches have been shown to frustrate management efforts, exacerbating issues of non-compliance and ultimately leading to conflicts and overfishing. Interestingly, the often static and rigid nature of these boundaries has also led to a concomitant research interest in ‘transboundary’. This paradoxical situation of more boundary-setting entailing more transboundary thinking warrants a deeper understanding about boundaries and the role of transboundary research in fisheries. The aims of this review article are twofold: (1) a theoretical clarification on the meanings and uses of spatial boundaries drawing on geographical “boundary studies” literature; and (2) a construction of a typology that outlines how transboundary research is being articulated and envisioned. Together, the study reveals that transboundary scholarship in fisheries are mostly related to resources, fleets, trade and governance aspects and that dealing with the “boundary paradox” encompasses re-incorporating, re-scaling and re-imagining of boundaries. This article provides a conceptual basis for reflecting upon boundaries in world's fisheries and opens up discussions for a more nuanced boundary application that can better cope with multi-level interactions and dynamicity

Simulating Land Use Land Cover Change Using Data Mining and Machine Learning Algorithms

The objectives of this dissertation are to: (1) review the breadth and depth of land use land cover (LUCC) issues that are being addressed by the land change science community by discussing how an existing model, Purdue\u27s Land Transformation Model (LTM), has been used to better understand these very important issues; (2) summarize the current state-of-the-art in LUCC modeling in an attempt to provide a context for the advances in LUCC modeling presented here; (3) use a variety of statistical, data mining and machine learning algorithms to model single LUCC transitions in diverse regions of the world (e.g. United States and Africa) in order to determine which tools are most effective in modeling common LUCC patterns that are nonlinear; (4) develop new techniques for modeling multiple class (MC) transitions at the same time using existing LUCC models as these models are rare and in great demand; (5) reconfigure the existing LTM for urban growth boundary (UGB) simulation because UGB modeling has been ignored by the LUCC modeling community, and (6) compare two rule based models for urban growth boundary simulation for use in UGB land use planning. The review of LTM applications during the last decade indicates that a model like the LTM has addressed a majority of land change science issues although it has not explicitly been used to study terrestrial biodiversity issues. The review of the existing LUCC models indicates that there is no unique typology to differentiate between LUCC model structures and no models exist for UGB. Simulations designed to compare multiple models show that ANN-based LTM results are similar to Multivariate Adaptive Regression Spline (MARS)-based models and both ANN and MARS-based models outperform Classification and Regression Tree (CART)-based models for modeling single LULC transition; however, for modeling MC, an ANN-based LTM-MC is similar in goodness of fit to CART and both models outperform MARS in different regions of the world. In simulations across three regions (two in United States and one in Africa), the LTM had better goodness of fit measures while the outcome of CART and MARS were more interpretable and understandable than the ANN-based LTM. Modeling MC LUCC require the examination of several class separation rules and is thus more complicated than single LULC transition modeling; more research is clearly needed in this area. One of the greatest challenges identified with MC modeling is evaluating error distributions and map accuracies for multiple classes. A modified ANN-based LTM and a simple rule based UGBM outperformed a null model in all cardinal directions. For UGBM model to be useful for planning, other factors need to be considered including a separate routine that would determine urban quantity over time

framework of the ESPON 2013 Programme, partly financed by the European Regional Development Fund.

consists of the EU Commission and the Member States of the EU27, plus Iceland, Liechtenstein, Norway and Switzerland. Each partner is represented in the ESPON Monitoring Committee. This report does not necessarily reflect the opinion of the members of the Monitoring Committee. Information on the ESPON Programme and projects can be found on www.espon.eu The web site provides the possibility to download and examine the most recent documents produced by finalised and ongoing ESPON projects. This basic report exists only in an electroni

A flood vulnerability index for coastal cities and its use in assessing climate change impacts

Worldwide, there is a need to enhance our understanding of vulnerability and to develop methodologies and tools to assess vulnerability. One of the most important goals of assessing coastal flood vulnerability, in particular, is to create a readily understandable link between the theoretical concepts of flood vulnerability and the day-to-day decision-making process and to encapsulate this link in an easily accessible tool. This article focuses on developing a Coastal City Flood Vulnerability Index (CCFVI) based on exposure, susceptibility and resilience to coastal flooding. It is applied to nine cities around the world, each with different kinds of exposure. With the aid of this index, it is demonstrated which cities are most vulnerable to coastal flooding with regard to the system's components, that is, hydro-geological, socio-economic and politico-administrative. The index gives a number from 0 to 1, indicating comparatively low or high coastal flood vulnerability, which shows which cities are most in need of further, more detailed investigation for decision-makers. Once its use to compare the vulnerability of a range of cities under current conditions has been demonstrated, it is used to study the impact of climate change on the vulnerability of these cities over a longer timescale. The results show that CCFVI provides a means of obtaining a broad overview of flood vulnerability and the effect of possible adaptation options. This, in turn, will allow for the direction of resources to more in-depth investigation of the most promising strategies