DEVELOPMENT OF A PROPAGATION PROGRAM FOR BEECH BARK DISEASE-RESISTANT AMERICAN BEECH (FAGUS GRANDIFOLIA) AND AN APPLIED RESTORATION PLAN FOR MITIGATION OF BEECH BARK DISEASE

This dissertation describes the work accomplished towards mitigation of beech bark disease (BBD) through a joint venture by Michigan Technological University and the National Park Service. American beech is an ecologically important species that is threatened throughout its range by beech bark disease and other newer, emergent pressures such as climate change and beech leaf disease. A literature review is included to synthesize recent advances in American beech (Fagus grandifolia Ehrh.) propagation and their application in mitigation of BBD (Chapter 2). These concepts are examined in an applied restoration framework to outline the importance of understanding ecological and technological context of the proposed project. It was determined that the target properties, Pictured Rocks and Sleeping Bear Dunes National Lakeshores, both in northern Michigan, are in differing phases of the progression of beech bark disease, making a restoration plan more complex. Planting sites and site preparation activities are proposed for the applied restoration project meeting ecological context and stakeholder’s objectives (Chapter 3). Development and refinement of methods for successfully grafting BBD-resistant American beech are described as knowledge transfer (Chapter 4). Furthermore, plain language, illustrated manuals were created to maintain institutional knowledge of the process to collect resistant scions and graft them to create resistant trees (Appendix A, B). Finally, a pilot study exploring methods for transplanting wildling American beech is described (Chapter 5) that confirms survivability for potentially a more cost-effective way to obtain grafting materials. This will also inform future work examining the potential transplanting of naturally resistant beech root sprouts, which may significantly reduce the monetary cost and increase long-term survival of fully resistant trees. Overall, the work described here details a holistic approach to the mitigation of beech bark disease through creation and planting of resistant American beech using local provenance genetic sources and considering a public agency’s objectives

Decision Tree Classifiers for Star/Galaxy Separation

We study the star/galaxy classification efficiency of 13 different decision tree algorithms applied to photometric objects in the Sloan Digital Sky Survey Data Release Seven (SDSS DR7). Each algorithm is defined by a set of parameters which, when varied, produce different final classification trees. We extensively explore the parameter space of each algorithm, using the set of $884,126$ SDSS objects with spectroscopic data as the training set. The efficiency of star-galaxy separation is measured using the completeness function. We find that the Functional Tree algorithm (FT) yields the best results as measured by the mean completeness in two magnitude intervals: $14\le r\le21$ ($85.2$) and $r\ge19$ ($82.1$). We compare the performance of the tree generated with the optimal FT configuration to the classifications provided by the SDSS parametric classifier, 2DPHOT and Ball et al. (2006). We find that our FT classifier is comparable or better in completeness over the full magnitude range $15\le r\le21$, with much lower contamination than all but the Ball et al. classifier. At the faintest magnitudes ($r>19$), our classifier is the only one able to maintain high completeness ($>$80%) while still achieving low contamination ($\sim2.5$). Finally, we apply our FT classifier to separate stars from galaxies in the full set of $69,545,326$ SDSS photometric objects in the magnitude range $14\le r\le21$.Comment: Submitted to A

Leaf-to-branch scaling of C-gain in field-grown almond trees under different soil moisture regimes

Branch/tree-level measurements of carbon (C)-acquisition provide an integration of the physical and biological processes driving the C gain of all individual leaves. Most research dealing with the interacting effects of high-irradiance environments and soil-induced water stress on the C-gain of fruit tree species has focused on leaf-level measurements. The C-gain of both sun-exposed leaves and branches of adult almond trees growing in a semi-arid climate was investigated to determine the respective costs of structural and biochemical/physiological protective mechanisms involved in the behaviour at branch scale. Measurements were performed on well-watered (fully irrigated, FI) and drought-stressed (deficit irrigated, DI) trees. Leaf-to-branch scaling for net CO2 assimilation was quantified by a global scaling factor (fg), defined as the product of two specific scaling factors: (i) a structural scaling factor (fs), determined under well-watered conditions, mainly involving leaf mutual shading; and (ii) a water stress scaling factor (fws,b) involving the limitations in C-acquisition due to soil water deficit. The contribution of structural mechanisms to limiting branch net C-gain was high (mean fs ∼0.33) and close to the projected-to-total leaf area ratio of almond branches (ε = 0.31), while the contribution of water stress mechanisms was moderate (mean fws,b ∼0.85), thus supplying an fg ranging between 0.25 and 0.33 with slightly higher values for FI trees with respect to DI trees. These results suggest that the almond tree (a drought-tolerant species) has acquired mechanisms of defensive strategy (survival) mainly based on a specific branch architectural design. This strategy allows the potential for C-gain to be preserved at branch scale under a large range of soil water deficits. In other words, almond tree branches exhibit an architecture that is suboptimal for C-acquisition under well-watered conditions, but remarkably efficient to counteract the impact of DI and drought events

A Novel Semisupervised Contrastive Regression Framework for Forest Inventory Mapping with Multisensor Satellite Data

Accurate mapping of forests is critical for forest management and carbon stocks monitoring. Deep learning is becoming more popular in Earth Observation (EO), however, the availability of reference data limits its potential in wide-area forest mapping. To overcome those limitations, here we introduce contrastive regression into EO based forest mapping and develop a novel semisupervised regression framework for wall-to-wall mapping of continuous forest variables. It combines supervised contrastive regression loss and semi-supervised Cross-Pseudo Regression loss. The framework is demonstrated over a boreal forest site using Copernicus Sentinel-1 and Sentinel-2 imagery for mapping forest tree height. Achieved prediction accuracies are strongly better compared to using vanilla UNet or traditional regression models, with relative RMSE of 15.1% on stand level. We expect that developed framework can be used for modeling other forest variables and EO datasets

Improved Land Management in the Lake Victoria Basin: Annual Technical Report, July 2000 to June 2001

ICRAF and the Kenyan Ministry of Agriculture and Rural Development (MOARD) are implementing a project on “Improved Land Management in the Lake Victoria Basin.” The project began in 1999 – 2000 with a one-year startup year of activities under the Sida-sponsored National Soil and Water Conservation Programme (NSWCP). The collaborative project of ICRAF and MOARD has now been continued for another three years under the National Agriculture and Livestock Extension Programme (NALEP). This paper summarizes achievements and findings for the project for the year 2000 / 2001. The Swedish International Development Agency (SIDA) supports “Improved Land Management in the Lake Victoria Basin” through NALEP. Additional financial support for the activities reported herein was also provided by the Rockefeller Foundation, ICRAF core funds, Danida, the University of Florida and the USAID. Research conducted during 2000 / 2001 addressed a range of issues across a large tract of Western Kenya. A coarse resolution assessment of soil erosion risk conducted for the entire Lake Victoria Basin identified the Nzoia / Yala and Kagera river basins as those with the greatest percentage of land at risk. Biophysical research on land management problem domains has quantified the widespread spatial extent of soil physical and chemical degradation in the Nyando river basin and illustrated four contrasting biophysical problem domains within the basin. District-level data on population density, poverty and agricultural production available from secondary sources have been complemented with baseline household and community survey data collected in 9 villages around the Nyando river basin. The overall picture that is emerging is that while much of the Nyando river basin has experienced some physical and chemical land degradation, there are pockets of severe poverty, severe environmental degradation and extremely low agricultural production. Different approaches to extension, investment and policy may be needed to address poverty – environment – agricultural problems in different parts of the river basin. Reversing trends in environmental deterioration will require interventions on farmers fields and in the many areas between farms that publicly-used, although usually privately-owned. Farmers have demonstrated their willingness to adopt recommended conservation practices on their individual family fields, but the intensity of adoption depends upon the potential returns to investments, their cultural grouping, and the approach that extension providers take to the provision of information and mobilization of community participation. Adoption of improved practices and investments on publicly-used areas between farms requires the mobilization of collective action among small, medium and large groups. Collective action in the Nyando River basin is most likely to be effective where it harnesses local institutional arrangements (e.g. sub-clan affiliations among the Luo) and advances common interests in the provision of high quality water and the generation of additional cash income. Among other opportunities, there appears to be good prospects for market-oriented agroforestry for production of fruit, fuelwood and timber. Changes in local and national policies would help to ensure good returns for smallholder farmers. This report begins with a presentation of a number of major findings, implications of those findings for extension and investment and implications for policy. A summary of progress by activity is then presented, followed by lists of personnel involved, presentations and publications. An annex presents detailed accomplishments by activity

ACLEESCF. SP. FOVEATUS(COLEOPTERA CURCULIONIDAE), AN EXOTIC PESTOF FICUS CARICAIN ITALY: A SUSTAINABLE APPROACH TO DEFENCE BASEDON ALUMINOSILICATE MINERALS AS HOST PLANT MASKING SOLIDS

The exceptionally frequent entries of alien pest are a major source of concern for the farmers who haveto protect their crops from unknown insects, often without natural enemies in the new areas. A new pestbelonging to the Molytinae family (Coleoptera: Curculionidae), tribe Hylobiini, reported as Acleessp. cf.foveatusVoss, was recently introduced in Italy. The species is responsible for severe damages in many Italianfig nurseries and orchards, particularly in the Italian Central Northern regions, i.e. Tuscany, Ligury andLatium. Currently, no active ingredients are registered against this insect on fig crops. An innovative and eco-friendly approach for controlling this exotic weevil infestation was investigated, by using montmorillonite-based clays, either in their native state or containing copper(II) species, and clinoptilolite zeolites, in order tocheck the perception of the adults’ weevil towards the different solid materials and, subsequently, to evaluatethe capability of these innovative products to act as masking agent with respect to the host plant and/or asrepellent upon contact. The formulations containing copper(II)-exchanged clay and clinoptilolite zeoliteshowed preliminary promising results in terms of efficacy and environmental sustainability