APPLICATION OF AN IMPUTATION METHOD FOR GEOSPATIAL INVENTORY OF FOREST STRUCTURAL ATTRIBUTES ACROSS MULTIPLE SPATIAL SCALES IN THE LAKE STATES, U.S.A.

Credible spatial information characterizing the structure and site quality of forests is critical to sustainable forest management and planning, especially given the increasing demands and threats to forest products and services. Forest managers and planners are required to evaluate forest conditions over a broad range of scales, contingent on operational or reporting requirements. Traditionally, forest inventory estimates are generated via a design-based approach that involves generalizing sample plot measurements to characterize an unknown population across a larger area of interest. However, field plot measurements are costly and as a consequence spatial coverage is limited. Remote sensing technologies have shown remarkable success in augmenting limited sample plot data to generate stand- and landscape-level spatial predictions of forest inventory attributes. Further enhancement of forest inventory approaches that couple field measurements with cutting edge remotely sensed and geospatial datasets are essential to sustainable forest management. We evaluated a novel Random Forest based k Nearest Neighbors (RF-kNN) imputation approach to couple remote sensing and geospatial data with field inventory collected by different sampling methods to generate forest inventory information across large spatial extents. The forest inventory data collected by the FIA program of US Forest Service was integrated with optical remote sensing and other geospatial datasets to produce biomass distribution maps for a part of the Lake States and species-specific site index maps for the entire Lake State. Targeting small-area application of the state-of-art remote sensing, LiDAR (light detection and ranging) data was integrated with the field data collected by an inexpensive method, called variable plot sampling, in the Ford Forest of Michigan Tech to derive standing volume map in a cost-effective way. The outputs of the RF-kNN imputation were compared with independent validation datasets and extant map products based on different sampling and modeling strategies. The RF-kNN modeling approach was found to be very effective, especially for large-area estimation, and produced results statistically equivalent to the field observations or the estimates derived from secondary data sources. The models are useful to resource managers for operational and strategic purposes.

Restoration of forest wetlands: Case studies in Michigan and Finland

Forested wetlands throughout the world are valuable habitats; especially in relatively species-poor northern regions, they can be considered biological hotspots. Unfortunately, these areas have been degraded and destroyed. In recent years, however, the biological importance of wetlands has been increasingly recognized, resulting in the desire to restore disturbed habitats or create in place of destroyed ones. Restoration work is taking place across the globe in a diversity of wetland types, and research must be conducted to determine successful techniques. As a result, two studies of the effects of wetland restoration and creation were conducted in forested wetlands in northern Michigan and southern Finland. In North America, northern white-cedar wetlands have been declining in area, despite attempts to regenerate them. Improved methods for successfully establishing northern white-cedar are needed; as a result, the target of the first study was to determine if creating microtopography could be beneficial for white-cedar recruitment and growth. In northern Europe, spruce swamp forests have become a threatened ecosystem due to extensive drainage for forestry. As part of the restoration of these habitats, i.e. rewetting through ditch blocking, Sphagnum mosses are considered to be a critical element to re-establish, and an in-depth analysis of how Sphagnum is responding to restoration in spruce swamp forests has not been previously done. As a result, the aim of the second study was to investigate the ecophysiological functioning of Sphagnum and feather mosses across a gradient of pristine, drained, and restored boreal spruce swamp forests.

Assessing success of forest restoration efforts in degraded montane cloud forests in southern Mexico

Montane cloud forests are home to great biodiversity. However, non-sustainable anthropogenic activities have led to the loss of forest cover in southern Mexico. Increasing conservation, restoration and sustainable use of forest resources prevents the loss of cloud forests. In this study, success of forest restoration was evaluated in a degraded forest of Highlands Chiapas. The goal of this study was to assess the structure and composition of native tree species. We evaluated vegetation composition at three sites that had undergone enrichment plantings. Floristic composition and structure of the herbaceous, seedling, sapling, and overstory layers were measured. A total of sixty-six native tree species were recorded. Enrichment planting was found to have increased tree diversity. Moreover, 54% of the planted species were found in the understory, indicating that they were successfully recruiting. In conclusion, enrichment planting can aid in the conservation of forest cover in degraded areas.

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.

Effects of forest management and time on herbaceous species dynamics in the western Upper Peninsula of Michigan

The herbaceous layer is a dynamic layer in a forest ecosystem which often contains the highest species richness in northern temperate forests. Few long-term studies exist in northern hardwood forests with consistent management practices to observe herbaceous species dynamics. The Ford Forest (Michigan Technological University) reached its 50th year of management during the winter of 2008-2009. Herbaceous species were sampled during the summers pre- and post-harvest. Distinct herbaceous communities developed in the 13-cm diameter-limit treatment and the uncut control. After the harvest, the diameter-limit treatments had herbaceous communities more similar to the 13-cm diameter-limit treatment than the uncut control; the herbaceous layer contained more exotic and early successional species. Fifty years of continuous management changed the herbaceous community especially in the diameter-limit treatments. Sites used in the development of habitat classification systems based on the presence and absence of certain herbaceous species can also be used to monitor vegetation change over time. The Guide to Forest Communities and Habitat Types of Michigan was developed to aid forest managers in understanding the potential productivity of a stand, and often aid in the development of ecologically-based forest management practices. Subsets of plots used to create the Western Upper Peninsula Guide were resampled after 10 years. During the resampling, both spring and summer vegetation were sampled and earthworm populations were estimated through liquid extraction. Spring sampling observed important spring ephemerals missed during summer sampling. More exotic species were present during the summer 2010 sampling than the summer 2000 sampling. Invasive European earthworms were also observed at all sample locations in all habitat types; earthworm densities increased with increasing habitat richness. To ensure the accuracy of the guide book, plots should be monitored to see how herbaceous communities are changing. These plots also offer unique opportunities to monitor for invasive species and the effects of a changing climate.

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.