Poplar breeding and testing strategies in the north-central U.S.: Demonstration of potential yield and consideration of future research needs

2001 ◽  
Vol 77 (2) ◽  
pp. 245-253 ◽  
Author(s):  
Don E. Riemenschneider ◽  
J. G. Isebrands ◽  
William E. Berguson ◽  
Donald I. Dickmann ◽  
Richard B. Hall ◽  
...  
Keyword(s):  
Principal Component ◽  
Future Research ◽  
Environment Interaction ◽  
Research Needs ◽  
Above Ground Biomass ◽  
University Of Minnesota ◽  
Potential Yield ◽  
North Central ◽  
Ground Biomass ◽  
The North

We present results from a Populus Regional Testing Program that has been conducted in Minnesota, Iowa, Wisconsin, and Michigan over the past six years. Our objectives have been to: 1) identify highly productive, disease resistant intra- and inter-specific clonal selections and 2) understand patterns of genotype × environment interactions within the region that would, logically, govern commercial deployment of new clones. Clones were developed by breeding and selection programs at the University of Illinois, Iowa State University, University of Minnesota, and the USDA Forest Service for experiments established in 1995. We report results of analyses of variance and principal component analyses of tree diameters and estimated above-ground biomass that demonstrate significant genotype main effects and significant genotype × environment interactions. Maximum mean annual above-ground biomass increments have surpassed 16 Mg ha−1 y−1, exceeding previously reported yields of poplars grown under similar conditions in the north-central U.S. We also discuss the breeding and selection of poplars in general with specific attention to regional research needs. Key words: Populus, biomass, multi-trait selection, genotype, genotype × environment interaction

scholarly journals Comparison of Capability of SAR and Optical Data in Mapping Forest above Ground Biomass Based on Machine Learning

2020 ◽  
Vol 5 (1) ◽  
pp. 13
Author(s):  
Negar Tavasoli ◽  
Hossein Arefi
Keyword(s):  
Machine Learning ◽  
Carbon Stock ◽  
Vegetation Indices ◽  
Forest Biomass ◽  
Principal Component ◽  
Optical Data ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Texture Characteristics ◽  
Sentinel 2

Assessment of forest above ground biomass (AGB) is critical for managing forest and understanding the role of forest as source of carbon fluxes. Recently, satellite remote sensing products offer the chance to map forest biomass and carbon stock. The present study focuses on comparing the potential use of combination of ALOSPALSAR and Sentinel-1 SAR data, with Sentinel-2 optical data to estimate above ground biomass and carbon stock using Genetic-Random forest machine learning (GA-RF) algorithm. Polarimetric decompositions, texture characteristics and backscatter coefficients of ALOSPALSAR and Sentinel-1, and vegetation indices, tasseled cap, texture parameters and principal component analysis (PCA) of Sentinel-2 based on measured AGB samples were used to estimate biomass. The overall coefficient (R2) of AGB modelling using combination of ALOSPALSAR and Sentinel-1 data, and Sentinel-2 data were respectively 0.70 and 0.62. The result showed that Combining ALOSPALSAR and Sentinel-1 data to predict AGB by using GA-RF model performed better than Sentinel-2 data.

scholarly journals Tundra plant above-ground biomass and shrub dominance mapped across the North Slope of Alaska

2018 ◽  
Vol 13 (3) ◽  
pp. 035002 ◽  
Author(s):  
Logan T Berner ◽  
Patrick Jantz ◽  
Ken D Tape ◽  
Scott J Goetz
Keyword(s):  
North Slope ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
The North ◽  
North Slope Of Alaska ◽  
Shrub Dominance

scholarly journals The University of South Alabama Mesonet and Coastal Observing System: A Technical and Statistical Overview

2010 ◽  
Vol 27 (9) ◽  
pp. 1417-1439 ◽  
Author(s):  
Sytske K. Kimball ◽  
Madhuri S. Mulekar ◽  
Shailer Cummings ◽  
Jack Stamates
Keyword(s):  
Weather Forecasting ◽  
Meteorological Data ◽  
Future Research ◽  
Sensor Failure ◽  
North Central ◽  
The North ◽  
System A ◽  
The University ◽  
Mexico Coast ◽  
Good Agreement

Abstract The University of South Alabama Mesonet consists of 26 sites across the north-central Gulf of Mexico coast. Although the original purpose of the mesonet was monitoring landfalling tropical systems, meteorological data are collected and disseminated every 5 min year-round to serve a multitude of purposes, including weather forecasting, education, and research. In this paper a statistical analysis and like-sensor comparison demonstrates that variables, measured by different sensor types or by sensors at different heights, correlate well. The benefits of sensor redundancy are twofold, offering 1) backup sensors in the case of sensor failure during severe weather and 2) the ability to perform a large number of internal consistency checks for quality control purposes. An oceanographic compliment to the University of South Alabama Mesonet system, which was deployed by NOAA’s Atlantic Oceanographic and Meteorological Laboratory (AOML) to measure surface waves and ocean currents in an area south of Mobile, Alabama, is described. A preliminary comparison of mesonet wind data and ocean wave data show good agreement, offering promising opportunities for future research.

scholarly journals Models for estimating macronutrients in Mimosa scabrella Bentham

CERNE ◽  
2010 ◽  
Vol 16 (3) ◽  
pp. 323-334
Author(s):  
Saulo Jorge Téo ◽  
Sebastião do Amaral Machado ◽  
Afonso Figueiredo Filho ◽  
Carlos Bruno Reissmann
Keyword(s):  
Statistical Models ◽  
Metropolitan Region ◽  
Above Ground Biomass ◽  
Stem Biomass ◽  
Independent Variables ◽  
Macronutrient Content ◽  
Ground Biomass ◽  
The North ◽  
Dominant Height ◽  
Model Independent

The aim of this work was to adjust and test different statistical models for estimating macronutrient content in the above-ground biomass of bracatinga (Mimosa scabrella Bentham). The data were collected from 25 bracatinga trees, all native to the north of the metropolitan region of Curitiba, Paraná state, Brazil. To determine the biomass and macronutrient content, the trees were separated into the compartments leaves, branches < 4 cm, branches > 4 cm, wood and stem barks. Different statistical models were adjusted to estimate N, P, K, Ca and Mg contents in the tree compartments, using dendrometric variables as the model independent variables. Based on the results, the equations developed for estimating macronutrient contents were, in general, satisfactory. The most accurate estimates were obtained for the stem biomass compartments and the sum of the biomass compartments. In some cases, the equations had a better performance when crown and stem dimensions, age and dominant height were included as independent variables.

Linking indices of biotic integrity to environmental and land use variables: multimetric clustering and predictive models

2009 ◽  
Vol 59 (1) ◽  
pp. 1-8 ◽  
Author(s):  
Vladimir Novotny ◽  
David Bedoya ◽  
Hardik Virani ◽  
Elias Manolakos
Keyword(s):  
Land Use ◽  
Fish Community ◽  
Principal Component ◽  
Component Analysis ◽  
Stream Habitat ◽  
State Agencies ◽  
Data Bases ◽  
North Central ◽  
The North ◽  
Analyze Data

Advanced computerized methods and models of retrieving knowledge from large multiparameter data bases were used to analyze data on fish and macroinvertebrate composition (metrics), habitat, land use and water quality. The research focused on the north central and northeastern United States and involved thousands of sites monitored by the state agencies. The techniques and methodologies included supervised and unsupervised Artificial Neural Networks (ANN) modeling, Principal Component Analysis, Canonical Component Analysis (both linear and nonlinear), Multiple Regression Analyses, and analyses of variance by ANOVA. The research resulted in defining a concept of clusters of sites based on their biotic (fish) community composition, identified cluster dominating factors, and developed meaningful models for predicting fish composition based on environmental and in—stream habitat stresses.

Interaction between herbicides, time of application and genotype of wild oats (Avena fatua L.)

1977 ◽  
Vol 28 (4) ◽  
pp. 671 ◽  
Author(s):  
JG Paterson
Keyword(s):  
Seedling Emergence ◽  
Avena Fatua ◽  
Future Research ◽  
North Central ◽  
Time Of Application ◽  
Wild Oats ◽  
The North ◽  
Matter Production ◽  
Subspecies Level ◽  
Optimum Application

A glasshouse experiment was conducted on three groups of genotypes of Avena fatua L. representing those from the north, central and southern regions of the temperate area of Western Australia with a winter growing season. The interaction between genotype groups, three herbicides (barban, difenzoquat and flamprop-methyl) and six times of application was investigated. The results showed that all genotypes did not react similarly to the herbicides tested. Barban, in particular, was very susceptible to the genotype x time of application interaction. Reasons for this are suggested. These include the effect of climatic parameters on the evolution of predominant genotypes in various areas, together with micromorphological variability developed in response to environmental pressure. It is also suggested that the number of days after seedling emergence is as reliable a guide as leaf number for optimum application of barban and that mature wild oat seed-head counts may not adequately reflect important competitive attributes such as dry matter production. The possible erroneous extrapolation to subspecies level from data collected on a species basis is emphasized, as is the possibility of differentially specific herbicides contributing to population shifts towards greater herbicide resistance, and not only in wild oats. Lines of future research are indicated.

scholarly journals Carbon Flux of Down Woody Materials in Forests of the North Central United States

2010 ◽  
Vol 2010 ◽  
pp. 1-9 ◽  
Author(s):  
C. W. Woodall
Keyword(s):  
United States ◽  
Forest Inventory ◽  
Woody Debris ◽  
Stand Age ◽  
Future Research ◽  
Study Region ◽  
North Central ◽  
The North ◽  
C Stocks ◽  
Central United States

Across large scales, the carbon (C) flux of down woody material (DWM) detrital pools has largely been simulated based on forest stand attributes (e.g., stand age and forest type). The annual change in forest DWM C stocks and other attributes (e.g., size and decay class changes) was assessed using a forest inventory in the north central United States to provide an empirical assessment of strategic-scale DWM C flux. Using DWM inventory data from the USDA Forest Service's Forest Inventory and Analysis program, DWM C stocks were found to be relatively static across the study region with an annual flux rate not statistically different from zero. Mean C flux rates across the study area were 0.25, 0.12, 0.01, and 0.04 (Mg/ha/yr) for standing live trees, standing dead trees, coarse woody debris, and fine woody debris, respectively. Flux rates varied in their both magnitude and status (emission/sequestration) by forest types, latitude, and DWM component size. Given the complex dynamics of DWM C flux, early implementation of inventory remeasurement, and relatively low sample size, numerous future research directions are suggested.

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