Tracking a Governance Transition: Identifying and Measuring Indicators of Social Forestry on the Willamette National Forest

Abstract

National Forests in the United States have undergone a spatially and temporally uneven governance transition in response to social and economic pressures and contemporary policy changes, with many national forest units moving from a wholly government-led “dominant federal” model to a more collaborative “social forestry” model in which nonfederal actors have greater influence and authority. Here we report on an effort to develop a suite of indicators designed to capture some of the most tangible elements of a transition from dominant federal to social forestry modes of governance. We pilot test these data on the Willamette National Forest using data from a variety of sources internal and external to the USDA Forest Service. We assess the suitability of these indicators for tracking governance transitions and discuss their applicability to other national forest units nationwide.     

Multi-variable error correction of regional climate models

Climate change impact research needs regional climate scenarios of multiple meteorological variables. Those variables are available from regional climate models (RCMs), but affected by considerable biases. We evaluate the application of an empirical-statistical error correction method, quantile mapping (QM), for a small ensemble of RCMs and six meteorological variables. Annual and monthly biases are reduced to close to zero by QM for all variables in most cases. Exceptions are found, if non-stationarity of the model’s error characteristics occur. Even in the worst cases of non-stationarity, QM clearly improves the biases of raw RCMs. In addition, QM successfully adjusts the distributions of the analysed variables. To approach the question whether time series and inter-variable relationships are still plausible after correction, we evaluate the root-mean-square error (RMSE), autocorrelation and inter-variable correlation. We found improvement or no clear effect in RMSE and autocorrelation, and no clear effect on the correlation between meteorological variables. These results demonstrate that QM retains the quality of the temporal structure in time series and the inter-variable dependencies of RCMs. It has to be emphasised that this cannot be interpreted as an improvement and that deficiencies of the RCMs in those features are retained as well. Our results give some indication for the performance of QM applied to future scenarios, since our evaluation relies on independent calibration and evaluation periods, which are affected by climate variability and change. The effect of non-stationarity, however, can be expected to be larger in far future. We demonstrate the retainment of the RCM’s temporal structure and inter-variable dependencies, and large improvements in biases. This qualifies QM as a valuable, though not perfect, method in the interface between climate models and climate change impact research. Nonetheless, in case of no correlation between re-analysis driven RCM and observation, one should consider that QM does not correct this correlation.     

Overcoming cross-scale challenges to climate change adaptation for local government: a focus on Australia

This paper aims to identify key cross-scale challenges to planned adaptation within the context of local government in Australia, and suggest enabling actions to overcome such challenges. Many of the impacts of climate change and variability have or will be experienced at the local level. Local governments are embedded in a larger governance context that has the potential to limit the effectiveness of planned adaptation initiatives on the ground. This study argues that research on constraints and barriers to adaptation must place greater attention to understanding the broader multi-governance system and cross-scale constraints that shape adaptation at the local government scale. The study identified seven key enabling actions for overcoming cross-scale challenges faced by local governments in Australia when undertaking climate change adaptation planning and implementation. A central conclusion of this study is that a cooperative and collaborative approach is needed where joint recognition of the scale of the issue and its inherent cross-scale complexities are realised. Many of the barriers or constraints to adaptation planning are interlinked, requiring a whole government approach to adaptation planning. The research suggests a stronger role at the state and national level is required for adaptation to be facilitated and supported at the local level.     

Land use change and anthropogenic driving forces: A case study in Yanhe River Basin

Human activities alter land use patterns and affect landscape sustainability. It is therefore very important to investigate the relationship between land use change and human activities. This study focuses on the detection of changing land use patterns in the Yanhe River Basin in northern Loess Plateau of China between 1995 and 2008. Landscape metrics were used to analyze the changing land use patterns and to explore the related anthropogenic driving forces. Results show that:1) Totally, 186 590 ha of cropl...     

Voluntary relocation - An exploration of Australian attitudes in the context of drought, recycled and desalinated water

Throughout history settlements have been abandoned due to lack of water. Such a fate is of concern to public officials in settlements facing water scarcity - a condition which is anticipated to increase due to the impacts of climate change, and other factors including increasing per capita water use, and population growth. Key questions surround how to best adapt to these circumstances. A strategy little explored is relocation. This paper presents results from a qualitative study conducted in eight geographically diverse Australian locations. The willingness of individuals to relocate under three hypothetical water scenarios was investigated: (1) if the water in their community ran out, (2) if recycled wastewater was put in their community's drinking water supply, and (3) if desalinated water was put in their community's drinking water supply. Results indicate that most people would not relocate if recycled or desalinated water was used to augment their community's drinking water supply, but they would if their water supply ran out. Our results highlight that while there is initial public opposition to the augmentation of existing potable water supplies with recycled or desalinated water, people would prefer these solutions, over being forced to move location. Respondents were highly aware of the social, economic and public infrastructure costs associated with relocation decisions. Relocation would therefore, for most, only be the very last option if their water demands could not be met. However, it was difficult for most to imagine the situation becoming so dire. Our results highlight the importance of a comprehensive and consultative approach to managing supply in water scarce locations.