Browsing by Author "Wilson, David C."
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Item Automating the Creation of Stem Maps for Permanent Forest Inventory Plots Using R (Revised)(University of Minnesota Department of Forest Resources, 2017-05) Wilson, David C.; Zobel, John M.; Ek, Alan R.A method is presented and documented for constructing tree location maps for permanent field plots to aid remeasurement and usage of the tree and plot data.Item Cloquet Forestry Center Continuous Forest Inventory Update for 2014(University of Minnesota, 2016-12) Shrestha, Maryada; Wilson, David C.; Zobel, John M.; Ek, Alan R.The Cloquet Forestry Center (CFC) is a field research and instructional station administrated by the University of Minnesota. This report compiles CFC Continuous Forest Inventory (CFI) results from the summer 2014 re-measurement of 402 permanent field plots. These plots serve both research and forest management on the CFC. The individual plots are 1/7 acre in size and were installed and first measured in 1959. The plots have been subsequently remeasured in 1964, 1969, 1976, 1982, 1990, 2000 and in 2014. Three more plots were also added in 2014 (totaling 405) on newly acquired acreage. The report also describes changes in the forest since 2000 and longer-term trends. Summaries provided include 2014 number of trees, basal area, volume and biomass per acre by covertype, and acreage by age class distributions. Longer-term trends from 1959 are also described. The report also details the inventory design and associated details for the permanent plots, including measurement technologies. Data collection and analysis procedures were developed using Microsoft Access and the R statistical analysis package. Access to the compiled data and preliminary analysis is also available in the University Digital Conservancy.Item Cost-effective Forest Inventory Designs: Field Data Collection(University of Minnesota Department of Forest Resources, 2018-02) Ek, Alan R.; Wilson, David C.; Edgar, Christopher B.; Zobel, John M.Item Description and Implementation of the Great Lakes Forest Projection System (GLFPS)(University of Minnesota Department of Forest Resources, 2020-09) Wilson, David C.; Ek, Alan R.Item Evaluating Old Age for Forests in Minnesota from Forest Inventory Records(University of Minnesota Department of Forest Resources, 2017-06) Wilson, David C.; Ek, Alan R.Item Evidence of Rapid Forest Change in Minnesota(University of Minnesota Department of Forest Resources, 2018-06) Wilson, David C.; Ek, Alan R.Item FACCS Application(2014) Wilson, David C.; Domke, Grant M.; Ek, Alan R.Item Forest Age Class Change Simulator (FACCS): A spreadsheet-based model for estimation of forest change and biomass availability(University of Minnesota, 2014-02) Wilson, David C.; Domke, Grant M.; Ek, Alan R.Item Forest Cover Type and Productivity as Related to Physiography(University of Minnesota Department of Forest Resources, 2018-11) Wilson, David C.; Zobel, John M.; Ek, Alan R.An analysis of statewide forest inventory data indicates the occurrence of various forest cover types on the landscape is closely associated with physiographic conditions on those sites. Tables quantifying these relationships are provided as an aid to interpretation of forest inventory data in Minnesota and associated silvicultural opportunities.Item Hardwood stand modeling using the Forest Vegetation Simulator (FVS)(University of Minnesota Department of Forest Resources, 2019-01) Wilson, David C.; Ek, Alan R.This note reports on the adaptation of the USDA Forest Service’s Forest Vegetation Simulator (FVS) to model individual stands and potential management scenarios for the hardwood forests of Southeastern MinnesotaItem Minnesota moose population: using forest inventory data to assess changes in habitat(St. Paul, Minn. : Department of Forest Resources, University of Minnesota, 2013-05) Wilson, David C.; Ek, Alan R.Item NPC Calculator(Department of Forest Resources, University of Minnesota, 2015-06-30) Wilson, David C.;This application contains the interactive version of the Native Plant Community Calculator incorporating FIA, FIM, and NPC field data, along with physiographic information to impute likely NPC class for inventoried stands.Item NPC Calculator Process County IIC(Department of Forest Resources, University of Minnesota, 2015-06-30) Wilson, David C.This application is a product of the "Rapid Forest Ecosystem and Habitat Inventory by Imputation" project. This application uses forest inventory management (FIM) data combined with native plant community (NPC) observations and physiographic data to impute likely NPC class for inventoried stands.Item Old Forest Extent and Changes in Minnesota 2003-2018(University of Minnesota Department of Forest Resources, 2021-03) Peters, Emily B.; Wilson, David C.; Edgar, Christopher B.; Ek, Alan R.Old forests are an important part of Minnesota’s landscape. Here we describe the extent and recent changes in the acreage of old forest in Minnesota by forest type. Statewide, the area of old forest increased from 3.8% of the total forest area in 2003 to 6.4% in 2018. The area of old forest increased for most forest types and across all major ownership categories, but there are exceptions, notably for forest types that occupy relatively small acreages, are actively managed for timber products, or have forest health issues.Item Stand Volume, Biomass and Carbon Equations for the Upper Great Lakes Region(University of Minnesota Department of Forest Resources, 2019-07) Wilson, David C.; Ek, Alan R.Item Whole stand growth and yield models for major forest types in the Upper Great Lakes Region(University of Minnesota, 2019-10-24) Ek, Alan R.; Wilson, David C.A system of models for forest growth and yield estimation for sixteen forest types common to the Upper Great Lakes region is presented. The system is novel in its use of representatively sampled and remeasured forest inventory plot data for modeling growth, and in its explicit incorporation of regular and irregular mortality. Component projection models are explicitly formulated with reference to stand age, site index and relative density. Models for predicting number of trees, quadratic mean diameter, relative density, and basal area are linked to build an expectation for basal area development from fundamental tree-based observations and relationships. Further, system projections are produced in terms of the above variables, and for timber volumes, with options for estimating biomass and carbon. The system of models was developed from USDA Forest Service Forest Inventory and Analysis (FIA) Program data for Minnesota, Wisconsin and Michigan. We designated this formulation the Great Lakes Forest Projection System (GLFPS). ... The GLFPS is intended for projecting future forest conditions including growth and yield on a local to region-wide basis assuming the kinds and levels of management and disturbance inherent in the data. User instructions, assumptions in usage, consistency of estimates, procedures for handling mixed species stands, and other considerations in modeling and applications are also discussed. The system is publicly available on-line in an Excel spreadsheet format. As such, it is highly customizable.