The Invisible Forest: Conservation Easement Databases and the End of the Clandestine Conservation of Natural Lands

Olmsted talks about invisible forest refers to forest lands -- and, for that matter, any other land types -- protected by a perpetual conservation easement, the existence and location of which are concealed from the public, whether deliberately or because of the opaque nature of the easement process. Because easements, like other forms of deeds, must be recorded at the local land registry or recorder\u27s office, they can never be made undiscoverable. But, despite the efforts of some states and conservation organizations to compile conservation easement data for public consumption, there are few functional systems that comprehensively track and provide easy access to conservation easement data

Simple identification tools in FishBase

Simple identification tools for fish species were included in the FishBase information system from its inception. Early tools made use of the relational model and characters like fin ray meristics. Soon pictures and drawings were added as a further help, similar to a field guide. Later came the computerization of existing dichotomous keys, again in combination with pictures and other information, and the ability to restrict possible species by country, area, or taxonomic group. Today, www.FishBase.org offers four different ways to identify species. This paper describes these tools with their advantages and disadvantages, and suggests various options for further development. It explores the possibility of a holistic and integrated computeraided strategy

Economic valuation of marine and coastal ecosystems: is it currently fit for purpose?

In this paper, we consider whether the current “state of the art” of environmental valuation is suitable for producing policy-relevant estimates of the benefits or costs of changes in marine and coastal ecosystems. We review recent changes in European legislation which has meant an increasing demand for economic valuation from the policy and regulatory community. The next section considers, at a more conceptual level, whether the economic “toolbox” and scientific evidence is up to the task of meeting the demand for more evidence-based policy. Finally, three case studies are used to explore the nature of the valuation task and review what is currently known. These case studies are of salt-marsh restoration, marine renewable energy investments, and deep sea conservation

The European ex situ PGR Information Landscape

In this paper the authors try to describe the current situation regarding the documentation of Plant Genetic Resources (PGR) maintained in ex situ collections in Europe. It will tackle the systems that are used to manage the information involved, the mechanisms and systems that exist to exchange this information, and we will discuss the developments and challenges in this area. Apart from this technical description, the authors also try to give a functional description of the changing role of these systems in the light of international, technical and legal developments

Building a Portal for Scientific Collections at the University of Lisbon

Tese de mestrado, Bioinformática e Biologia Computacional, Universidade de Lisboa, Faculdade de Ciências, 2020As coleções científicas, reunindo uma enorme quantidade e diversidade de objetos e os dados que lhes estão associados, constituem um valioso património histórico, científico e cultural. Estas coleções estão, geralmente, sob a responsabilidade dos museus e dos seus respetivos curadores, sendo importante que exista uma plataforma sobre a qual os responsáveis das mesmas possam efetuar operações de gestão e de manutenção das mesmas. Atendendo a diversidade das coleções, estes dados, pertencentes a diferentes domínios científicos e com propriedades distintas, colocam problemas de integração, disponibilização e manutenção, problemas estes cada vez mais pertinentes numa realidade que vive de dados e da análise e partilha dos mesmos. Este projeto, centrado neste desafio, pretendeu desenvolver, para o Museu Nacional de História Natural e da Ciência da Universidade de Lisboa, uma plataforma que agregasse as variadíssimas coleções desta instituição, tirando partido de uma plataforma open-source base chamada CollectiveAccess. No decorrer do mesmo, foi desenvolvida uma metodologia generalizada para qualquer coleção que cobre os processos desde a aquisição dos dados, o seu processamento e correção ate a sua importação e disponibilização dentro da plataforma. Foram, também, desenvolvidas e implementadas funcionalidades especificas que visaram resolver determinadas características particulares dos diferentes conjuntos de dados como e o caso da implementação de um sistema hierárquico para dados relacionados com taxonomia, sistema de introdução de dados geográficos utilizando uma API externa e desenvolvimento das funcionalidades de pesquisa de modo a satisfazerem as necessidades de cada conjunto de dados. Estas funcionalidades e o desempenho do sistema foram avaliados através de dois questionários de usabilidade (System Usability Scale), atraves de dois Google Form diferentes. Estes questionários foram direcionados para dois tipos principais de utilizadores do sistema: curadores e publico, em geral. Para alem disto, foram pedidos comentários e sugestões de melhorias ou acrescento de funcionalidades. Os resultados dos questionários foram satisfatórios obtendo-se uma classificação de A e B, por parte dos testes do publico e dos curadores respetivamente, na escala de usabilidade. A analise dos comentários e sugestões também permitiu obter uma ideia sobre possíveis melhoramentos e novas funcionalidades a implementar.With scientific collections bringing together a huge number and diversity of objects and the data associated with them, they constitute a valuable historical, scientific and cultural heritage. These collections are generally under the responsibility of museums and their respective curators, and it is important that there is a platform on which those responsible for them can carry out management and maintenance operations. Given the diversity of the collections, these data, belonging to different scientific domains and with different properties, pose problems of integration, availability and maintenance, problems that are increasingly relevant in a data-centric world that relies on the analysis and sharing of the data. This project, focused on this challenge, aimed to develop, for the Museu Nacional de Historia Natural e da Ciência da Universidade de Lisboa, a platform that aggregates the very diverse collections of this institution, taking advantage of an open-source base platform called CollectiveAccess. In the course of the same, a generalized methodology was developed for any collection, covering the processes from the acquisition of the data, its processing and correction to its import and availability within the platform. Specific features were also developed and implemented that aimed at solving certain particular characteristics of different data sets, such as the implementation of a hierarchical system for taxonomyrelated data, geographic data entry system using an external API and development of the base search features, meeting the requirements for each collection. These functionalities and the overall performance of the system were evaluated through two usability questionnaires (System Usability Scale), via two different Google Forms. These questionnaires were aimed at two main types of users of the system: curators and the general public. In addition, comments and suggestions for improvements or addition of features were requested. The results of the questionnaires were satisfactory, obtaining a classification of A and B, by the tests of the public and the curators, respectively, on the usability scale. The analysis of comments and suggestions also provided an idea of possible improvements and new features to be implemented

User-centered semantic dataset retrieval

Finding relevant research data is an increasingly important but time-consuming task in daily research practice. Several studies report on difficulties in dataset search, e.g., scholars retrieve only partial pertinent data, and important information can not be displayed in the user interface. Overcoming these problems has motivated a number of research efforts in computer science, such as text mining and semantic search. In particular, the emergence of the Semantic Web opens a variety of novel research perspectives. Motivated by these challenges, the overall aim of this work is to analyze the current obstacles in dataset search and to propose and develop a novel semantic dataset search. The studied domain is biodiversity research, a domain that explores the diversity of life, habitats and ecosystems. This thesis has three main contributions: (1) We evaluate the current situation in dataset search in a user study, and we compare a semantic search with a classical keyword search to explore the suitability of semantic web technologies for dataset search. (2) We generate a question corpus and develop an information model to figure out on what scientific topics scholars in biodiversity research are interested in. Moreover, we also analyze the gap between current metadata and scholarly search interests, and we explore whether metadata and user interests match. (3) We propose and develop an improved dataset search based on three components: (A) a text mining pipeline, enriching metadata and queries with semantic categories and URIs, (B) a retrieval component with a semantic index over categories and URIs and (C) a user interface that enables a search within categories and a search including further hierarchical relations. Following user centered design principles, we ensure user involvement in various user studies during the development process

Overcoming Biological Data Deficiencies in Environmental Permitting for Offshore Wind Energy

The offshore wind final net technical resource of 2,059 GW in the United States is unrealized in part due to a cumbersome permitting process. In this dissertation, I examine the role of biological data in the permitting process, and explore frameworks for overcoming identified deficiencies. Criteria analyses and semi-structured interviews were conducted to understand how biological data impede impact assessments of offshore wind projects, which are required by the National Environmental Policy Act of 1969 (NEPA). In addition, spatiotemporal scales of biological data in NEPA assessments were evaluated against federal requirements. Case studies and semi-structured interviews were then conducted to evaluate how the marine spatial planning (MSP) process and its outcomes could address identified data impediments, how MSP could otherwise advance the offshore wind permitting process, what are the limiting factors of MSP, how limiting factors could be overcome, and how species distribution models could provide appropriate data to improve documentation. The research conducted for my dissertation showed that scales of biological data are inadequate in impact assessments and insufficient biological data are impediments in the offshore wind permitting process. Data from species distribution models contribute marginal value to impact assessments, and should not be exclusively relied upon. MSP can improve data access and analyses in NEPA documentation, in addition to facilitating communications, minimizing conflict, and providing a common operating picture. However, the full value of MSP is limited due to lack of political support and methodological changes in implementation. Therefore, other initiatives to facilitate data management should be pursued, such as industry sponsored research and relaxing the proprietary nature of baseline biological data. The results of this project highlight the significance that biological data has in impeding offshore wind projects and suggest solutions to overcome this in order to responsibly advance the offshore wind sector in the United States

Greening development finance in the Americas

This repository item contains a report from the Boston University Global Economic Governance Initiative. The Global Economic Governance Initiative (GEGI) is a research program of the Center for Finance, Law & Policy, the Frederick S. Pardee Center for the Study of the Longer-Range Future, and the Frederick S. Pardee School of Global Studies. It was founded in 2008 to advance policy-relevant knowledge about governance for financial stability, human development, and the environment