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This study examines the ability of bilinguals to judge their linguistic competence. Participants evaluated their Spanish and English language skills both before and after administration of the Woodcock-Muñoz Language Survey, which provided an objective measure of these skills. Self-assessments were more accurate for Spanish than for English and, in the case of English, varied with the skill being rated. Feedback from the objective test improved self-rating accuracy more for Spanish than for English. There was little support for the conclusion that the language in which the self-assessments are presented influences bilinguals’ self-ratings of their linguistic skills. Implications for the use of self-assessments in applied situations are discussed.

Abstract. Although forest conservation activities particularly in the tropics offer significant potential for mitigating carbon emissions, these types of activities have faced obstacles in the policy arena caused by the difficulty in determining key elements of the project cycle, particularly the baseline. A baseline for forest conservation has two main components: the projected land-use change and the corresponding carbon stocks in the applicable pools such as vegetation, detritus, products and soil, with land-use change being the most difficult to address analytically. In this paper we focus on developing and comparing three models, ranging from relatively simple extrapolations of past trends in land use based on simple drivers such as population growth to more complex extrapolations of past trends using spatially explicit models of land-use change driven by biophysical and socioeconomic factors. A comparison of all model outputs across all six regions shows that each model produced quite different deforestation baseline. In general, the simplest FAC model, applied at the national administrative-unit scale, projected the highest amount of forest loss (four out of six) and the LUCS model the least amount of loss (four out of five). Based on simulations of GEOMOD, we found that readily observable physical and biological factors as well as distance to areas of past disturbance were each about twice as important as either sociological/demographic or economic/infrastructure factors (less observable) in explaining empirical land-use patterns.We propose from the lessons learned, a methodology comprised of three main steps and six tasks can be used to begin developing credible baselines. We also propose that the baselines be projected over a 10-year period because, although projections beyond 10 years are feasible, they are likely to be unrealistic for policy purposes. In the first step, an historic land-use change and deforestation estimate is made by determining the analytic domain (size of the region relative to the size of proposed project), obtaining historic data, analyzing candidate historic baseline drivers, and identifying three to four major drivers. In the second step, a baseline of where deforestation is likely to occur --a potential land-use change (PLUC) map-is produced using a spatial model such as GEOMOD that uses the key drivers from step one. Then rates of deforestation are projected over a 10-year baseline period using any of the three models. Using the PLUC maps, projected rates of deforestation, and carbon stock estimates, baseline projections are developed that can be used for project GHG accounting and crediting purposes: The final step proposes that, at agreed interval (eg, +10 years), the baseline assumptions about baseline drivers be re-assessed. This step reviews the viability of the 10-year baseline in light of changes in one or more key baseline drivers (e.g., new roads, new communities, new protected area, etc.).The potential land-use change map and estimates of rates of deforestation cou...