Community managed rural water supply systems in the Dominican Republic : assessment of sustainability of systems built by the National Institute of Potable Water and Peace Corps, Dominican Republic

In the Dominican Republic economic growth in the past twenty years has not yielded sufficient improvement in access to drinking water services, especially in rural areas where 1.5 million people do not have access to an improved water source (WHO, 2006). Worldwide, strategic development planning in the rural water sector has focused on participatory processes and the use of demand filters to ensure that service levels match community commitment to post-project operation and maintenance. However studies have concluded that an alarmingly high percentage of drinking water systems (20-50%) do not provide service at the design levels and/or fail altogether (up to 90%): BNWP (2009), Annis (2006), and Reents (2003). World Bank, USAID, NGOs, and private consultants have invested significant resources in an effort to determine what components make up an “enabling environment” for sustainable community management of rural water systems (RWS). Research has identified an array of critical factors, internal and external to the community, which affect long term sustainability of water services. Different frameworks have been proposed in order to better understand the linkages between individual factors and sustainability of service. This research proposes a Sustainability Analysis Tool to evaluate the sustainability of RWS, adapted from previous relevant work in the field to reflect the realities in the Dominican Republic. It can be used as a diagnostic tool for government entities and development organizations to characterize the needs of specific communities and identify weaknesses in existing training regimes or support mechanisms. The framework utilizes eight indicators in three categories (Organization/Management, Financial Administration, and Technical Service). Nineteen independent variables are measured resulting in a score of sustainability likely (SL), possible (SP), or unlikely (SU) for each of the eight indicators. Thresholds are based upon benchmarks from the DR and around the world, primary data collected during the research, and the author’s 32 months of field experience. A final sustainability score is calculated using weighting factors for each indicator, derived from Lockwood (2003). The framework was tested using a statistically representative geographically stratified random sample of 61 water systems built in the DR by initiatives of the National Institute of Potable Water (INAPA) and Peace Corps. The results concluded that 23% of sample systems are likely to be sustainable in the long term, 59% are possibly sustainable, and for 18% it is unlikely that the community will be able to overcome any significant challenge. Communities that were scored as unlikely sustainable perform poorly in participation, financial durability, and governance while the highest scores were for system function and repair service. The Sustainability Analysis Tool results are verified by INAPA and PC reports, evaluations, and database information, as well as, field observations and primary data collected during the surveys. Future research will analyze the nature and magnitude of relationships between key factors and the sustainability score defined by the tool. Factors include: gender participation, legal status of water committees, plumber/operator remuneration, demand responsiveness, post construction support methodologies, and project design criteria.

Applications of LiDAR remote sensing of forest structure in the Upper Great Lakes region, USA

We used active remote sensing technology to characterize forest structure in a northern temperate forest on a landscape- and local-level in the Upper Peninsula of Michigan. Specifically, we used a form of active remote sensing called light detection and ranging (e.g., LiDAR) to aid in the depiction of current forest structural stages and total canopy gap area estimation. On a landscape-level, LiDAR data are shown not only to be a useful tool in characterizing forest structure, in both coniferous and deciduous forest cover types, but also as an effective basis for data-driven surrogates for classification of forest structure. On a local-level, LiDAR data are shown to be a benchmark reference point to evaluate field-based canopy gap area estimations, due to the highly accurate nature of such remotely sensed data. The application of LiDAR remote sensed data can help facilitate current and future sustainable forest management.

Evaluation of sugar maple dieback in the Upper Great Lakes region and development of a forest health youth education program

Acer saccharum Marsh., is one of the most valuable trees in the northern hardwood forests. Severe dieback was recently reported by area foresters in the western Upper Great Lakes Region. Sugar Maple has had a history of dieback over the last 100 years throughout its range and different variables have been identified as being the predisposing and inciting factors in different regions at different times. Some of the most common factors attributed to previous maple dieback episodes were insect defoliation outbreaks, inadequate precipitation, poor soils, atmospheric deposition, fungal pathogens, poor management, or a combination of these. The current sugar maple dieback was evaluated to determine the etiology, severity, and change in dieback on both industry and public lands. A network of 120 sugar maple health evaluation plots was established in the Upper Peninsula, Michigan, northern Wisconsin, and eastern Minnesota and evaluated annually from 2009-2012. Mean sugar maple crown dieback between 2009-2012 was 12.4% (ranging from 0.8-75.5%) across the region. Overall, during the sampling period, mean dieback decreased by 5% but individual plots and trees continued to decline. Relationships were examined between sugar maple dieback and growth, habitat conditions, ownership, climate, soil, foliage nutrients, and the maple pathogen sapstreak. The only statistically significant factor was found to be a high level of forest floor impacts due to exotic earthworm activity. Sugar maple on soils with lower pH had less earthworm impacts, less dieback, and higher growth rates than those on soils more favorable to earthworms. Nutritional status of foliage and soil was correlated with dieback and growth suggesting perturbation of nutrient cycling may be predisposing or contributing to dieback. The previous winter's snowfall totals, length of stay on the ground, and number of days with freezing temperatures had a significant positive relationship to sugar maple growth rates. Sapstreak disease, Ceratocystis virescens, may be contributing to dieback in some stands but was not related to the amount of dieback in the region. The ultimate goal of this research is to help forest managers in the Great Lakes Region prevent, anticipate, reduce, and/or salvage stands with dieback and loss in the future. An improved understanding of the complex etiology associated with sugar maple dieback in the Upper Great Lakes Region is necessary to make appropriate silvicultural decisions. Forest Health education helps increase awareness and proactive forest management in the face of changing forest ecosystems. Lessons are included to assist educators in incorporating forest health into standard biological disciplines at the secondary school curricula.