While there is an increasing demand for active public involvement in forestry decision-making, there are as yet few successful models for achieving this in the new sustainable forest management (SFM) context. This paper describes the special needs of forest managers conducting participatory SFM planning in a sometimes-polarized public context, and outlines criteria for designing decision-support processes to meet these needs.
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This paper describes the GTAP land use data base designed to support integrated assessments of the potential for greenhouse gas mitigation. It disaggregates land use by agro-ecological zone (AEZ). To do so, it draws upon global land cover data bases, as well as state-of-the-art definition of AEZs from the FAO and IIASA. Agro-ecological zoning segments a parcel of land into smaller units according to agro-ecological characteristics, including: precipitation, temperature, soil type, terrain conditions, etc. Each zone has a similar combination of constraints and potential for land use.
Global energy use projections predict that biomass will be an important source of renewable energy in the coming decades. Short-rotation woody crops will be the prime source of this biomass. However, the sustainability of woody crops has been questioned. Using internationally accepted forest sustainability criteria, an assessment of willow biomass crops indicates that they are sustainable compared to agricultural land and the fossil fuel-based energy systems they will replace.
The paper describes the on-going project of the GTAP land use data base. We also present the GTAPE-AEZ model, which illustrates how land use and land-based emissions can be incorporated in the CGE framework for Integrated Assessment (IA) of climate change policies. We follow the FAO fashion of agro-ecological zoning (FAO, 2000; Fischer et al, 2002) to identify lands located in six zones. Lands located in a specific AEZ have similar (or homogenous) soil, landform and climatic characteristics.
There is increasing pressure on the forestry industry to adopt sustainable practices, but a lack of knowledge about how to facilitate this, and how to measure sustainability. This book reviews current thinking about scientifically based indicators, and sustainable management of natural forests and plantations. Information is applicable to boreal, temperate and tropical biomes. The contents have been developed from papers presented at a IUFRO conference held in Australia, in order to develop a state-of the art report on this subject.
Until recently, advanced very high-resolution radiometer (AVHRR) observations were the only viable source of data for global land cover mapping. While many useful insights have been gained from analyses based on AVHRR data, the availability of moderate resolution imaging spectroradiometer (MODIS) data with greatly improved spectral, spatial, geometric, and radiometric attributes provides significant new opportunities and challenges for remote sensing-based land cover mapping research.
The need for new criteria and indicators for the assessment of biodiversity conservation as part of sustainable forest management of tropical forests has been identified as a priority by many international organisations. Those biodiversity criteria and indicators which formed part of a much broader initial assessment by the Center for International Forestry Research (CIFOR) (Prabhu et al. 1996) were found to be deficient. This Working Paper contains specific proposals for biodiversity criteria and indicators.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.
This working paper contains proposals for specific genetic criteria and indicators (C&I) which are expected to be part of a more general set of biological C&I. These proposals are intended for use in guiding tropical forest management but the indicators and verifiers we describe are not in the form of simple prescriptions where a single measurement can be recommended for a single causal effect.
Background: This study evaluates the global economic effects of the current US RFS2, and the potential contribution from advanced biofuels. Results & discussion: Our simulation results suggest that these mandates lead to an increase of 0.21% in the global gross domestic product in 2022, including an increase of 0.8% in the USA and 0.02% in the rest of the world, relative to our baseline no-RFS scenario. The incremental contributions to gross domestic product from advanced biofuels in 2022 are estimated at 0.41 and 0.04% in the USA and the rest of the world, respectively.
Funded from the U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy, Bioenergy Technologies Office.
FAOSTAT provides time-series and cross sectional data relating to food and agriculture for some 200 countries.
The national version of FAOSTAT, CountrySTAT, is being developed and implemented in a number of target countries, primarily in sub-saharan Africa. It will offer a two-way data exchange facility between countries and FAO as well as a facility to store data at the national and sub-national levels.
This database contains current and historical official USDA data on production, supply and distribution of agricultural commodities for the United States and key producing and consuming countries.
Converting forest lands into bioenergy agriculture could accelerate climate change by emitting carbon stored in forests, while converting food agriculture lands into bioenergy agriculture could threaten food security. Both problems are potentially avoided by using abandoned agriculture lands for bioenergy agriculture. Here we show the global potential for bioenergy on abandoned agriculture lands to be less than 8% of current primary energy demand, based on historical land use data, satellite-derived land cover data, and global ecosystem modeling.
Many investigators need and use global land cover maps for a wide variety of purposes. Ironically, after many years of very limited availability, there are now multiple global land cover maps and it is not readily apparent (1) which is most useful for particular applications or (2) how to combine the different maps to provide an improved dataset. The existing global land cover maps at 1 km spatial resolution have arisen from different initiatives and are based on different remote sensing data and employed different methodologies. Perhaps more significantly, they have different legends.
Two of the most widely used land-cover data sets for the United States are the National Land-Cover Data (NLCD) at 30-m resolution and the Global Land- Cover Characteristics (GLCC) at 1-km nominal resolution. Both data sets were produced around 1992 and expected to provide similar land-cover information. This study investigated the spatial distribution of NLCD within major GLCC classes at 1-km unit over a total of 11 agricultural-related eco-regions across the continental United States.