This synthesis focuses on estimates of biodiversity change as projected for the 21st century by models or extrapolations based on experiments and observed trends. The term “biodiversity” is used in a broad sense as it is defined in the Convention on Biological Diversity to mean the abundance and distributions of and interactions between genotypes, species, communities, ecosystems and biomes. This synthesis pays particular attention to the interactions between biodiversity and ecosystem services and to critical “tipping points” that could lead to large, rapid and potentially irreversible changes. Comparisons between models are used to estimate the range of projections and to identify sources of uncertainty. Experiments and observed trends are used to check the plausibility of these projections. In addition we have identified possible actions at the local, national and international levels that can be taken to conserve biodiversity. We have called on a wide range of scientists to participate in this synthesis, with the objective to provide decision makers with messages that reflect the consensus of the scientific community and that will aid in the development of policy and management strategies that are ambitious, forward looking and proactive.
Resource Type: ReportsDatasets Available from UNEP-WCMC: Excluding WDPA
Access to UNEP-WCMC datasets is provided on the understanding that you read and consent to be bound by the Terms and Conditions attached. For the purposes of this Agreement the “Data” comprise any of the spatial data and associated attribute data downloadable from the UNEP-WCMC website, excluding the World Database on Protected Areas.
This dataset shows the global distribution of wetlands. It was produced at UNEP-WCMC from various sources alongside the publication 'Wetlands in Danger", Dugan, P ed. (1993).
Datasets Available from UNEP-WCMC: Excluding WDPA
Access to UNEP-WCMC datasets is provided on the understanding that you read and consent to be bound by the Terms and Conditions attached. For the purposes of this Agreement the “Data” comprise any of the spatial data and associated attribute data downloadable from the UNEP-WCMC website, excluding the World Database on Protected Areas.
This dataset shows the location of tropical montane cloud forest sites as recorded in a worldwide inventory compiled by UNEP-WCMC and published in "A Global Directory of Tropical Montane Cloud Forests", Aldrich et al., 1997. This inventory was compiled from literature searches and correspondence with regional experts, and contains a total of 529 sites. The central location for each site is recorded but does not identify the great variability in their size, which ranges from 50 hectares to hundreds of square kilometres.
This collaborative project, sponsored by the Global Environment Facility (GEF) and others, developed biodiversity indicators to support planning and decision-making at the national level in four participating countries. In each country national partners developed and tested several indicators for a single focal ecosystem, using an iterative process of consultation, inventory and synthesis of existing data.
The BINU project has launched this 20-page booklet on its experience and lessons learned in developing biodiversity indicators for national use.
Resource Type: ReportsDatasets Available from UNEP-WCMC: Excluding WDPA
Access to UNEP-WCMC datasets is provided on the understanding that you read and consent to be bound by the Terms and Conditions attached. For the purposes of this Agreement the “Data” comprise any of the spatial data and associated attribute data downloadable from the UNEP-WCMC website, excluding the World Database on Protected Areas.
To provide a global context for a discussion of mountain forests, it is first necessary to define the locations and types of mountain forests, and this in turn requires a definition of mountains or mountain areas. Altitude and slope and the environmental gradients they generate are key components of such a definition, but their combination is problematic. Simple altitude thresholds both exclude older and lower mountain systems and include areas of relatively high elevation that have little topographic relief and few environmental gradients. Using slope as a criterion on its own or in combination with altitude can resolve the latter problem, but not the former. As a first step to evaluating global mountain forest resources and the threats to them, UNEP-WCMC (in collaboration with the Environmental Change Institute and kindly supported by the Swiss Agency for Development and Co-operation - SDC) in 2000 made a first attempt to map the mountain forests of the world.
Chapter from Biodiversity Loss & Conservation in Fragmented Forest Landscapes. The Forests of Montane Mexico and South America.
Resource Type: ReportsDatasets Available from UNEP-WCMC: Excluding WDPA
Access to UNEP-WCMC datasets is provided on the understanding that you read and consent to be bound by the Terms and Conditions attached. For the purposes of this Agreement the “Data” comprise any of the spatial data and associated attribute data downloadable from the UNEP-WCMC website, excluding the World Database on Protected Areas.
To provide a global context for a discussion of mountain forests, it is first necessary to define the locations and types of mountain forests, and this in turn requires a definition of mountains or mountain areas. Altitude and slope and the environmental gradients they generate are key components of such a definition, but their combination is problematic. Simple altitude thresholds both exclude older and lower mountain systems and include areas of relatively high elevation that have little topographic relief and few environmental gradients. Using slope as a criterion on its own or in combination with altitude can resolve the latter problem, but not the former. The mountains dataset shows the location of mountain land estimated from a digital elevation model using criteria based on elevation alone (the upper three classes: > 2 500 metres) and at lower elevation, on a combination of elevation, slope and local elevation range. This is an update of the Mountain's of the World 2000 and was produced for the UNEP-WCMC publication Mountain Watch, 2002.
The mountains dataset has been overlayed with a global data set on percent tree cover taken from MODIS 1-km resolution percent tree cover data, courtesy of University of Maryland Global Land Cover Facility. Species richness, density and forest height tend to reduce with increasing altitude; the boundary between forest vegetation and more open ground cover at higher elevation 'the treeline' is an ecological marker signifying the transition to more extreme climatic conditions.
Resource Type: Spatial Data / MapsThis report is a contribution to the UN’s International Year of Biodiversity and is a complement to the UNEP-hosted Economics of Ecosystems and Biodiversity (TEEB) which is bringing visibility to the wealth of the world’s natural capital. It documents over 30 successful case studies referencing thousands of restoration projects ranging from deserts and rainforests to rivers and coasts. The report confirms that restoration is not only possible but can prove highly proftable in terms of public savings; returns and the broad objectives of overcoming poverty and achieving sustainability. It also provides important recommendations on how to avoid pitfalls and how to minimize risks to ensure successful restoration.
Resource Type: ReportsThe third edition of Global Biodiversity Outlook (GBO-3) summarizes the latest data on status and trends of biodiversity and draws conclusions for the future strategy of the Convention. GBO-3 is based on a range of information sources, including National Reports, biodiversity indicators information, scientific literature, and a study assessing biodiversity scenarios for the future.
Resource Type: ReportsOver recent decades, biodiversity conservation and poverty reduction have both become international societal and political goals. There is recognition of the links between these two goals both within the Convention on Biological Diversity and the Millennium Development Goals. However, the causal relationships are not so simple either that one can say poverty causes biodiversity loss, or improvements in biodiversity reduce poverty. This suggests a need to be more specific in defining what types of poverty and biodiversity issues are being assessed.
Two “state of knowledge” reviews were commissioned to explore the evidence base for two common assumptions about the link between biodiversity conservation and poverty reduction: 1) that the poor depend on biodiversity; and 2) that biodiversity conservation can be a mechanism for poverty reduction. These attempt to tease apart the issues of what type of poverty and what type of biodiversity are being assessed.
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