The Digital Observatory for Protected Areas (DOPA) Explorer 1.0

The Digital Observatory for Protected Areas (DOPA) has been developed to support the European Union’s efforts in strengthening our capacity to mobilize and use biodiversity data, information and forecasts so that they are readily accessible to policymakers, managers, experts and other users. Conceived as a set of web based services, DOPA provides a broad set of free and open source tools to assess, monitor and even forecast the state of and pressure on protected areas at local, regional and global scale. DOPA Explorer 1.0 is a web based interface available in four languages (EN, FR, ES, PT) providing simple means to explore the nearly 16,000 protected areas that are at least as large as 100 km2. Distinguishing between terrestrial, marine and mixed protected areas, DOPA Explorer 1.0 can help end users to identify those with most unique ecosystems and species, and assess the pressures they are exposed to because of human development. Recognized by the UN Convention on Biological Diversity (CBD) as a reference information system, DOPA Explorer is based on the best global data sets available and provides means to rank protected areas at the country and ecoregion levels. Inversely, DOPA Explorer indirectly highlights the protected areas for which information is incomplete. We finally invite the end-users of DOPA to engage with us through the proposed communication platforms to help improve our work to support the safeguarding of biodiversity.JRC.H.5-Land Resources Managemen

An introduction to the Digital Observatory for Protected Areas (DOPA) and the DOPA Explorer (Beta)

The Digital Observatory for Protected Areas (DOPA) is conceived around a set of interacting Critical Biodiversity Informatics Infrastructures (databases, web modelling services, broadcasting services, ...) hosted at different institutions, including the Joint Research Centre of the European Commission, the World Conservation Monitoring Centre (UNEP-WCMC), the International Union for Conservation of Nature (IUCN), the Global Biodiversity Information Facility (GBIF) and BirdLife International. The current services of DOPA provide to a large variety of end-users, ranging from park managers, funding agencies to researchers, with means to assess, monitor and possibly forecast the state and pressure of protected areas at the local, national and global scales. With an introduction to the DOPA, the readers will find here a user manual of the beta version of DOPA Explorer, a first web based assessment tool where information on 9 000 protected areas covering almost 90% of the global protected surface has been processed automatically to generate a set of indicators on ecosystems, climate, phenology, species, ecosystem services and pressures. DOPA Explorer can so help identify the protected areas with most unique ecosystems and species and assess the pressures they are exposed to because of human development. Ecological data derived from and near real-time earth observations are also made available for the African continent. Inversely, DOPA Explorer indirectly highlights the protected areas for which the information is incomplete.JRC.H.5-Land Resources Managemen

Mapping ignorance: 300 years of collecting flowering plants in Africa

Aim Spatial and temporal biases in species-occurrence data can compromise broad-scale biogeographical research and conservation planning. Although spatial biases have been frequently scrutinized, temporal biases and the overall quality of species-occurrence data have received far less attention. This study answers three questions: (i) How reliable are species-occurrence data of flowering plants in Africa? (ii) Where and when did botanical sampling occur in the past 300 years? (iii) How complete are plant inventories for Africa? Location Africa. Methods By filtering a publicly available dataset containing 3.5 million records of flowering plants, we obtained 934,676 herbaria specimens with complete information regarding species name, date and location of collection. Based on these specimens, we estimated inventory completeness for sampling units (SUs) of 25 x 25 km. We then tested whether the spatial distribution of well-sampled SUs was correlated with temporal parameters of botanical sampling. Finally, we determined whether inventory completeness in individual countries was related to old or recently collected specimens. Results Thirty-one percent of SUs contained at least one specimen, whereas only 2.4% of SUs contained a sufficient number of specimens to reliably estimate inventory completeness. We found that the location of poorly sampled areas remained almost unchanged for half-century. Moreover, there was pronounced temporal bias towards old specimens in South Africa, the country that holds half of the available data for the continent. There, high inventory completeness stems from specimens collected several decades ago. Main conclusions Despite the increasing availability of species-occurrence data for Africa, broad scale biogeographical research is still compromised by the uncertain quality and spatial and temporal biases of such data. To avoid erroneous inferences, the quality and biases in species-occurrence data should be critically evaluated and quantified prior to use. To this end, we propose a quantification method based on inventory completeness using easily accessible species-occurrence data.JRC.D.6-Knowledge for Sustainable Development and Food Securit