SUNY College of Environmental Science and Forestry
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Site Preparation: Planting the Willow Cuttings
No full textAfter the snow fence planting strip been prepared, willow cuttings are planted in a double-row patternhttps://digitalcommons.esf.edu/lsfgal/1008/thumbnail.jp
Norway Spruce Living Snow Fence (2012)
No full textNorway Spruce Living Snow Fence along Route 167 (Manheim Center, NY)https://digitalcommons.esf.edu/lsfgal/1023/thumbnail.jp
Species Matrix for New York State
Get PDFSpecies selection is an important step in the design of effective and efficient living snow fences. A species matrix assists in the plant selection process for living snow fences by providing a pallete of suitable species, and a summary of relevant plant traits to compare and contrast species. Recent research at SUNY ESF has built on previous research (Tabler, 2003) and identified key plant traits for living snow fences. Twenty-eight species that possess the traits relevant to living snow fences have been identified and included in this plant matrix. These species are tolerant to a variety of roadside conditions across New York State, and possess the traits necessary to achieve adequate snow trapping and snow storage capabilities. Every plant species is unique, and this matrix is therefore intended as a selection tool to compare and contrast a variety of plants for living snow fences within the context of design goals and site conditions
Willow Snow Fence Plant Shortly After Planting
No full textThis photograph shows a willow cutting shortly after planting a living snow fencehttps://digitalcommons.esf.edu/lsfgal/1009/thumbnail.jp
Partially Harvested Field (2012)
No full textPartially harvested field of willow biomass cropshttps://digitalcommons.esf.edu/hvstgal/1011/thumbnail.jp
Development of a Hydrologic Model to Predict Lakeshore Phosphorus Loadings for Prediction of Cladophora Biomass Blooms
Get PDFIn recent years, excess phosphorus in lake water columns has triggered the nuisance growth of the filamentous green algae, Cladophora glomerata, in the near-shore areas of Lakes Erie, Michigan and Ontario. One approach to limiting nuisance Cladophora blooms is to build a systems model of the watershed hydrologic loading and aquatic biogeochemical cycling to help managers identify phosphorus control options. In this research we built the Contributing Area-Dispersal Area (CADA) weighted Export Coefficient (EC) watershed runoff model in ArcGIS to identify watershed areas delivering the greatest phosphorus loads. We tested the CADA EC model in the Lake Ontario basin using 30 arc-second digital elevation models, remotely sensed land cover classifications, and regional phosphorus export coefficients. The watershed model will be coupled with a proven aquatic biogeochemical cycling model to better assist management of nuisance algal growth along lakeshores. This simulation tool has the potential to improve nutrient tracking and eutrophication management, which may result in a much greater chance for preserving sensitive aquatic ecosystems
Expression Pattern of Xtshz1 and Xtshz3 During Xenopus Early Eye Formation
Get PDFThe Drosophila gene teashirt (tsh) codes for a transcription factor that is part of a genetic network specifying eye identity. Three vertebrate tsh homologs have been identified (tshz1-3). All three mouse tshz genes can induce ectopic eyes in tsh loss-of-function flies. It is not yet known if any of the three tshz genes are required for vertebrate eye formation. This study was conducted to determine if any of the three Xenopus laevis tshz genes is expressed in the eye field or eye primordia during development. Although tshz1 mRNA was expressed in the neuroectoderm, spinal cord, branchial arches, and olfactory placode, transcripts were never detected in either the eye field or eye primordia at any of the stages tested. In contrast to tshz1, tshz3 mRNA was detected in the eye primordia as early as stage 22 with strongest expression at stage 24. In addition, tshz3 was also detected in the neuroectoderm, spinal cord, branchial arches, neural fold, and hindbrain. Expression of tshz3 in the eye primordia suggests its possible involvement in vertebrate early eye formation
Measuring Height of a Living Snow Fence
No full textHeight and optical porosity are the key characteristics effecting snow trapping capacity of living snow fenceshttps://digitalcommons.esf.edu/lsfgal/1015/thumbnail.jp
Integrating Local and Global Error Statistics for Multi-Scale RBF Network Training: An Assessment on Remote Sensing Data
Get PDFBackground
This study discusses the theoretical underpinnings of a novel multi-scale radial basis function (MSRBF) neural network along with its application to classification and regression tasks in remote sensing. The novelty of the proposed MSRBF network relies on the integration of both local and global error statistics in the node selection process. Methodology and Principal Findings
The method was tested on a binary classification task, detection of impervious surfaces using a Landsat satellite image, and a regression problem, simulation of waveform LiDAR data. In the classification scenario, results indicate that the MSRBF is superior to existing radial basis function and back propagation neural networks in terms of obtained classification accuracy and training-testing consistency, especially for smaller datasets. The latter is especially important as reference data acquisition is always an issue in remote sensing applications. In the regression case, MSRBF provided improved accuracy and consistency when contrasted with a multi kernel RBF network. Conclusion and Significance
Results highlight the potential of a novel training methodology that is not restricted to a specific algorithmic type, therefore significantly advancing machine learning algorithms for classification and regression tasks. The MSRBF is expected to find numerous applications within and outside the remote sensing field
White Fir Living Snow Fence
No full textWhite Fir Living Snow Fence along Interstate 88 (Cobleskill, NY)https://digitalcommons.esf.edu/lsfgal/1031/thumbnail.jp