Soil erosion is a severe problem for many developing regions that lack adequate infrastructure to combat the problem. The authors established a first-order method for prioritizing areas to be examined and remediated using preexisting data and expert knowledge where data are lacking. The Universal Soil Loss Equation was applied to the Rio Lempa Basin in Central America using geographic information systems and remote sensing technologies, and the estimated erosion rates were compared with sediment delivery ratios. Spatial analysis indicates that agriculture on very steep slopes contributes only a small fraction to the total estimated soil erosion, whereas agriculture on gentle and moderately steep slopes contributes a large fraction of the erosion. Although much of the basin is in El Salvador, the greatest estimated amount of erosion is from Honduras. Data quality and availability were impaired by a lack of coordination among agencies and across countries. Several avenues for improving the authors' methods are described.

No abstract

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, the MC2 model. The results suggest that climate change will cause forest outputs (such as timber) to increase by approximately 30% over the century. Aboveground forest carbon storage also is projected to increase, by approximately 26 Pg C by 2115, as a result of climate change, potentially providing an offset to emissions from other sectors. The effects of climate mitigation policies in the energy sector are then examined. When climate mitigation in the energy sector reduces warming, we project a smaller increase in forest outputs over the timeframe of the analysis, and we project a reduction in the sink capacity of forests of around 12 Pg C by 2115.

Sustainable hunting, the extraction of game without reducing its density, is a desirable approach to the use of wildlife. Assessment of sustainable extraction in many parts of the world is difficult; it has recently been done by a method proposed by Robinson and Redford (1991): a maximum number of animals that can be extracted per unit area is calculated based on life-history parameters and density estimates. If extraction is higher than that maximum number, it is deemed unsustainable. We extended the method by adding spatial and stochastic components through an individual-based model of a population of female tapirs ( Tapirus sp.) and conducted a sensitivity analysis to evaluate the importance of spatial and life-history parameters. Our analysis suggests that spatial factors, such as the shape of the hunted area and the size of the surrounding population, may be important in determining the sustainability of extraction. For long-lived, slow-reproducing mammals such as tapirs, survival to age of last reproduction is the most critical parameter, but the shape of the hunting zone and population density can be critical, especially in unsustainable hunting scenarios. We advocate long-term studies of tapirs to collect information on spatial movements and survival rates that could then be used for development of proper management plans. Factores Espaciales y Estocasticidad en la Evaluación de la Cacería Sustentable de TapiresResumen: La cacería sustentable, extracción de animales de caza sin reducción de su densidad, es un enfoque deseable para el uso de vida silvestre. La evaluación de la extracción sustentable es difícil en muchas partes del mundo y se ha hecho utilizando un método propuesto por Robinson y Redford (1991): el número máximo de animales que se puede extraer por unidad de área se calcula con base en parámetros de la historia de vida y estimaciones de la densidad. Si la extracción es mayor que ese número máximo, se considera no sustentable. Extendimos el método agregando componentes espaciales y estocásticos por medio del modelo basado en individuos de una población de tapires ( Tapirus sp.) hembras y realizamos un análisis de sensibilidad para evaluar la importancia de los parámetros espaciales y de la historia de vida. Nuestro análisis sugiere que factores espaciales, tal como la forma del área de cacería y el tamaño de la población circundante, pueden ser importantes en la determinación de la sustentabilidad de la extracción. Para especies longevas de reproducción lenta como el tapir, la supervivencia hasta la última edad reproductiva es el parámetro más crítico; pero la forma del área de cacería y la densidad pueden ser críticas, especialmente en poblaciones bajo caza no sustentable. Recomendamos estudios de largo plazo de tapires para obtener información de movimientos espaciales y tasas de supervivencia que pueda utilizarse para el desarrollo de planes de manejo adecuados.

We analyze a set of simulations to assess the impact of climate change on global forests where MC2 dynamic global vegetation model (DGVM) was run with climate simulations from the MIT Integrated Global System Model-Community Atmosphere Model (IGSM-CAM) modeling framework. The core study relies on an ensemble of climate simulations under two emissions scenarios: a business-as-usual reference scenario (REF) analogous to the IPCC RCP8.5 scenario, and a greenhouse gas mitigation scenario, called POL3.7, which is in between the IPCC RCP2.6 and RCP4.5 scenarios, and is consistent with a 2°C global mean warming from pre-industrial by 2100. Evaluating the outcomes of both climate change scenarios in the MC2 model shows that the carbon stocks of most forests around the world increased, with the greatest gains in tropical forest regions. Temperate forest regions are projected to see strong increases in productivity offset by carbon loss to fire. The greatest cost of mitigation in terms of effects on forest carbon stocks are projected to be borne by regions in the southern hemisphere. We compare three sources of uncertainty in climate change impacts on the world's forests: emissions scenarios, the global system climate response (i.e. climate sensitivity), and natural variability. The role of natural variability on changes in forest carbon and net primary productivity (NPP) is small, but it is substantial for impacts of wildfire. Forest productivity under the REF scenario benefits substantially from the CO 2 fertilization effect and that higher warming alone does not necessarily increase global forest carbon levels. Our analysis underlines why using an ensemble of climate simulations is necessary to derive robust estimates of the benefits of greenhouse gas mitigation. It also demonstrates that constraining estimates of climate sensitivity and advancing our understanding of CO 2 fertilization effects may considerably reduce the range of projections.