David T. Shoch

Accurately assessing forest structure and productivity is critical to making timely management decisions and monitoring plant communities. This study aims to evaluate the prediction accuracy of site-level stand and biomass tables from the diameter distribution models. The efficacy of the single Weibull function and two finite mixture models was compared for six species groups on three mixed-hardwood sites in eastern Tennessee, USA. To evaluate model performance, two types of stand/biomass tables were generated. The first type was constructed from all species on a given site (site-specific), whereas the second type was built for a single species from all sites (species-specific). Results indicate that both types of stand and biomass tables were consistently well quantified by the two-component mixture model in terms of goodness of fit, parsimony, and robustness. The two-component mixture model better characterized the complex, multimodal diameter distributions than the single Weibull model, which underpredicted the upper portion of the distributions. The three-component model tends to overfit the data, which results in lower prediction accuracy. Among the three models examined, the two-Weibull mixture model is suggested to construct site-level stand/biomass tables, which provides more reliable and accurate predictions to assess forest structure and product class.

Projects to reduce emissions from deforestation and degradation (REDD) are designed to reduce carbon emissions through avoided deforestation and degradation, and in many cases, to produce additional community and biodiversity conservation co-benefits. While these co-benefits can be significant, quantifying conservation impacts has been challenging, and most projects use simple species presence to demonstrate positive biodiversity impact. Some of the same tools applied in the quantification of climate mitigation benefits have relevance and potential application to estimating co-benefits for biodiversity conservation. In western Tanzania, most chimpanzees live outside of national park boundaries, and thus face threats from human activity, including competition for suitable habitat. Through a case study of the Ntakata Mountains REDD project in western Tanzania, we demonstrate a combined application of deforestation modelling with species distribution models to assess forest conservation benefits in terms of avoided carbon emissions and improved chimpanzee habitat. The application of such tools is a novel approach that we argue permits the better design of future REDD projects for biodiversity co-benefits. This approach also enables project developers to produce the more manageable, accurate and cost-effective monitoring, reporting and verification of project impacts that are critical to verification under carbon standards.