Invitational rhetoric : alternative rhetorical strategy for transformation of perception and use of energy in the residential built environment from the Keweenaw to Kerala

This dissertation explores the viability of invitational rhetoric as a mode of advocacy for sustainable energy use in the residential built environment. The theoretical foundations for this study join ecofeminist concepts and commitments with the conditions and resources of invitational rhetoric, developing in particular the rhetorical potency of the concepts of re-sourcement and enfoldment. The methodological approach is autoethnography using narrative reflection and journaling, both adapted to and developed within the autoethnographic project. Through narrative reflection, the author explores her lived experiences in advocating for energy-responsible residential construction in the Keweenaw Peninsula of Michigan. The analysis reveals the opportunities for cooperative, collaborative advocacy and the struggle against traditional conventions of persuasive advocacy, particularly the centrality of the rhetor. The author also conducted two field trips to India, primarily the state of Kerala. Drawing on autoethnographic journaling, the analysis highlights the importance of sensory relations in lived advocacy and the resonance of everyday Indian culture to invitational principles. Based on field research, the dissertation proposes autoethnography as a critical development in encouraging invitational rhetoric as an alternative mode of effecting change. The invitational force of autoethnography is evidenced in portraying the material advocacy of the built environment itself, specifically the sensual experience of material arrangements and ambience, as well as revealing the corporeality of advocacy, that is, the body as the site of invitational engagement, emotional encounter, and sensory experience. This study concludes that vulnerability of self in autoethnographic work and the vulnerability of rhetoric as invitational constitute the basis for transformation. The dissertation confirms the potential of an ecofeminist invitational advocacy conveyed autoethnographically for transforming perceptions and use of energy in a smaller-scale residential environment appropriate for culture, climate, and ultimately part of the challenge of sustaining life on this planet.

Towards greater accuracy in individual-tree mortality regression

Background mortality is an essential component of any forest growth and yield model. Forecasts of mortality contribute largely to the variability and accuracy of model predictions at the tree, stand and forest level. In the present study, I implement and evaluate state-of-the-art techniques to increase the accuracy of individual tree mortality models, similar to those used in many of the current variants of the Forest Vegetation Simulator, using data from North Idaho and Montana. The first technique addresses methods to correct for bias induced by measurement error typically present in competition variables. The second implements survival regression and evaluates its performance against the traditional logistic regression approach. I selected the regression calibration (RC) algorithm as a good candidate for addressing the measurement error problem. Two logistic regression models for each species were fitted, one ignoring the measurement error, which is the “naïve” approach, and the other applying RC. The models fitted with RC outperformed the naïve models in terms of discrimination when the competition variable was found to be statistically significant. The effect of RC was more obvious where measurement error variance was large and for more shade-intolerant species. The process of model fitting and variable selection revealed that past emphasis on DBH as a predictor variable for mortality, while producing models with strong metrics of fit, may make models less generalizable. The evaluation of the error variance estimator developed by Stage and Wykoff (1998), and core to the implementation of RC, in different spatial patterns and diameter distributions, revealed that the Stage and Wykoff estimate notably overestimated the true variance in all simulated stands, but those that are clustered. Results show a systematic bias even when all the assumptions made by the authors are guaranteed. I argue that this is the result of the Poisson-based estimate ignoring the overlapping area of potential plots around a tree. Effects, especially in the application phase, of the variance estimate justify suggested future efforts of improving the accuracy of the variance estimate. The second technique implemented and evaluated is a survival regression model that accounts for the time dependent nature of variables, such as diameter and competition variables, and the interval-censored nature of data collected from remeasured plots. The performance of the model is compared with the traditional logistic regression model as a tool to predict individual tree mortality. Validation of both approaches shows that the survival regression approach discriminates better between dead and alive trees for all species. In conclusion, I showed that the proposed techniques do increase the accuracy of individual tree mortality models, and are a promising first step towards the next generation of background mortality models. I have also identified the next steps to undertake in order to advance mortality models further.

Spatial and temporal analysis of land cover and landscape structure change in Zagros Forests

The Zagros oak forests in Western Iran are critically important to the sustainability of the region. These forests have undergone dramatic declines in recent decades. We evaluated the utility of the non-parametric Random Forest classification algorithm for land cover classification of Zagros landscapes, and selected the best spatial and spectral predictive variables. The algorithm resulted in high overall classification accuracies (>85%) and also equivalent classification accuracies for the datasets from the three different sensors. We evaluated the associations between trends in forest area and structure with trends in socioeconomic and climatic conditions, to identify the most likely driving forces creating deforestation and landscape structure change. We used available socioeconomic (urban and rural population, and rural income), and climatic (mean annual rainfall and mean annual temperature) data for two provinces in northern Zagros. The most correlated driving force of forest area loss was urban population, and climatic variables to a lesser extent. Landscape structure changes were more closely associated with rural population. We examined the effects of scale changes on the results from spatial pattern analysis. We assessed the impacts of eight years of protection in a protected area in northern Zagros at two different scales (both grain and extent). The effects of protection on the amount and structure of forests was scale dependent. We evaluated the nature and magnitude of changes in forest area and structure over the entire Zagros region from 1972 to 2009. We divided the Zagros region in 167 Landscape Units and developed two measures— Deforestation Sensitivity (DS) and Connectivity Sensitivity (CS) — for each landscape unit as the percent of the time steps that forest area and ECA experienced a decrease of greater than 10% in either measure. A considerable loss in forest area and connectivity was detected, but no sudden (nonlinear) changes were detected at the spatial and temporal scale of the study. Connectivity loss occurred more rapidly than forest loss due to the loss of connecting patches. More connectivity was lost in southern Zagros due to climatic differences and different forms of traditional land use.