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Tree-Ring Skeleton Plotting by Computer
No full textSkeleton plotting is an established manual technique for representing the relative narrowness of tree rings in a single radius. These plots can be used as a visual aid to crossdating. This paper describes a method for deriving these plots by computer. The method uses a low-pass digital filter, running means, and standard deviations of ring-width measurements. When the manual and computer plots are compared for the same series, approximately 85% agreement is found. Examples of results are presented for specimens from sensitive, moderate, and complacent sites. FORTRAN program listings are included for two subroutines for (a) identifying small rings and (b) producing the plot.This item is part of the Tree-Ring Research (formerly Tree-Ring Bulletin) archive. It was digitized from a physical copy provided by the Laboratory of Tree-Ring research at The University of Arizona. For more information about this peer-reviewed scholarly journal, please email the Editor of Tree-Ring Research at [email protected]
Small Farm Quarterly - Spring 2009
No full textSmall Farm Quarterly is for farmers and farm families — including spouses and children - who value the quality of life that smaller farms provide.CONTENTS:
SMALL FARM PROGRAM UPDATE: Cornell Small Farms Program Update, Page 3;
BUSINESS MANAGEMENT: Announcing the Strolling of the Heifers Microloan Fund for New Enland Farmers, by Dorothy Suput, Page 6;
COWS AND CROPS: Mass Nutrient Balance Project for Small Dairies, by Sara Zglobicki, Page 8; Dear Vicki Vetch, by the Drinkwater Lab, Page 17;
FOREST AND WOODLOT: Stop the Spread of Feral Swine, by Wendy Baltzersen and Marie Kautz, Page 4;
GRAZING: Key to Continued Sustainability is Profitability, by Mike Dennis, Page 7; The Grazier’s Eye, by Jean Tyler, Page 9;
HOME AND FAMILY: Radical Homemakers Reveal True Wealth, by Shannon Hayes, Page 18;
HORTICULTURE: Cover Crops Case Studies: Maple Tree Gardens, by Molly Shaw, Page 20;
LOCAL FOODS & MARKETING: Assessing the Market Potential of Products, by Laura Biasillo, Page 17; Does Your Marketing Program have a GPS? by Debra Perosio, Page 18;
NEW FARMERS: Anybody Can Feed a Pig, by Bob Comis, Page 5; Labor for Learning, by Carla Shafer, Page 14; Cultivating Vegetables and Myself, by Abha Gupta, Page 15;
NON-DAIRY LIVESTOCK: Does Raising Sheep Pay? by Ulf Kintzel, Page 16;
NORTHEAST SARE SPOTLIGHT: Pastured Livestock Internship Program, by Violet Stone, Page 10;
ORGANIC FARMING: Ecological Control of Pasture Flies, by Fay Benson, Page 13;
RESOURCE SPOTLIGHTS: Skills for Self-Reliance, Page 15;
SMALL FARM SPOTLIGHTS: Portrait of a Very Small Farm, by Nicole Ayers and Gary Olcott, Page 3; My Life at Sweet Grass Meats Farm, by Onagh MacKenzie, Page 12;
STEWARDSHIP & NATURE: Agricultural Environmental Management: Big Opportunities for Small Farms, by Barbara Silvestri, Page 19;
WOMEN IN AGRICULTURE: We Should Have Listened to Grandma, by Susan Neal, Page 15Cornell Small Farms Program, Cornell University Cooperative Extension, NYS 4-H Team Program, NY Farm Viability Institute, NY Agricultural Environmental Management, Watershed Agricultural Counci
Household Tree Planting in Tigrai, Northern Ethiopia: Tree Species, Purposes, and Determinants
No full textTrees have multiple purposes in rural Ethiopia, providing significant economic and ecological benefits. Planting trees supplies rural households with wood products for their own consumption, as well for sale, and decreases soil degradation. We used cross-sectional household-level data to analyze the determinants of household tree planting and explored the most important tree attributes or purpose(s) that enhance the propensity to plant trees. We set up a sample selection framework that simultaneously took into account the two decisions of tree growers (whether or not to plant trees and how many) to analyze the determinants of tree planting. We used logistic regression to analyze the most important tree attributes that contribute to households’ tree-planting decisions. We found that land size, age, gender, tenure security, education, exogenous income, and agro-ecology increased both the propensity to plant trees and the amount of tree planting, while increased livestock holding impacted both decisions negatively. Our findings also suggested that households consider a number of attributes in making the decision to plant trees. These results can be used by policymakers to promote tree planting in the study area by trengthening tenure security and considering households’ selection of specific tree species for their attributes.tree plantin, tree species, tree attributes or purposes, sample selection, Tigrai, Ethiopia
Members of the Darwin Tree of Life Barcoding author list
No full textThis document holds a record of the individuals from the Darwin Tree of Life Barcoding team who should be considered coauthors of publications arising from the work of the Darwin Tree of Life project (https://www.darwintreeoflife.org)
Estimation of tree lists from airborne laser scanning by combining single-tree and area-based methods
No full textIndividual tree crown segmentation from airborne laser scanning (ALS) data often fails to detect all trees depending on the forest structure. This paper presents a new method to produce tree lists consistent with unbiased estimates at area level. First, a tree list with height and diameter at breast height (DBH) was estimated from individual tree crown segmentation. Second, estimates at plot level were used to create a target distribution by using a k-nearest neighbour (k-NN) approach. The number of trees per field plot was rescaled with the estimated stem volume for the field plot. Finally, the initial tree list was calibrated using the estimated target distribution. The calibration improved the estimates of the distributions of tree height (error index (EI) from 109 to 96) and DBH (EI from 99 to 93) in the tree list. Thus, the new method could be used to estimate tree lists that are consistent with unbiased estimates from regression models at field plot level
Tree-width for first order formulae
No full textWe introduce tree-width for first order formulae φ, fotw(φ). We show that computing fotw is fixed-parameter tractable with parameter fotw. Moreover, we show that on classes of formulae of bounded fotw, model checking is fixed parameter tractable, with parameter the length of the formula. This is done by translating a formula φ with fotw(φ)<k into a formula of the k-variable fragment Lk of first order logic. For fixed k, the question whether a given first order formula is equivalent to an Lk formula is undecidable. In contrast, the classes of first order formulae with bounded fotw are fragments of first order logic for which the equivalence is decidable. Our notion of tree-width generalises tree-width of conjunctive queries to arbitrary formulae of first order logic by taking into account the quantifier interaction in a formula. Moreover, it is more powerful than the notion of elimination-width of quantified constraint formulae, defined by Chen and Dalmau (CSL 2005): for quantified constraint formulae, both bounded elimination-width and bounded fotw allow for model checking in polynomial time. We prove that fotw of a quantified constraint formula φ is bounded by the elimination-width of φ, and we exhibit a class of quantified constraint formulae with bounded fotw, that has unbounded elimination-width. A similar comparison holds for strict tree-width of non-recursive stratified datalog as defined by Flum, Frick, and Grohe (JACM 49, 2002). Finally, we show that fotw has a characterization in terms of a cops and robbers game without monotonicity cost
Small Farm Quarterly - Spring 2013
No full textSmall Farm Quarterly is for farmers and farm families — including spouses and children - who value the quality of life that smaller farms provide.CONTENTS:
SMALL FARM PROGRAM UPDATE -Cornell Small Farms Program Update, Page 3;
BOOK NOOK -Luscious Guide to Growing Fruit Naturally, by Jill Swenson, Page 15;
COMMUNITY AND WORLD -Rhubarb or Bust: Farming Notes from Interior Alaska, by Ruby Peck-Hollembaek, Page 19; Food Recovery Q&A, by Laurie “Duck” Caldwell, Page 6; Reconnecting Refugee Farmers to Their Agricultural Roots, by Laura McCandlish, Page 8;
FARM ENERGY -Is Wind Energy Right for Your Farm, by Mark Mayhew, Page 13;
FOREST AND WOODLOT -Regenerating Your Next Forest: Keys to Success, by Paul Curtis, Gary Goff, and Jason Boulanger, Page 18;
GRAZING -The Value of Increasing Pasture Numbers, by Bill Verbeten, Page 4;
HORTICULTURE -Uncommon Fruits with Commercial Potential, by Lee Reich, Page 9; Cut Flowers for Beauty and Business, by John Suscovich, Page 10;
LIVESTOCK & POULTRY -The Chute, by Ulf Kintzel, Page 12;
LOCAL FOODS & MARKETING -Using Software to Help Build and Support Local Food Markets, by Kim Mills, Sue Rau, Jason Evans, and Jim Ochterski, Page 14; GrowYour CSA Online, by Dan Livingston, Page 11;
NEW FARMERS -The Education of a Beginning Goat Farmer, by Stephanie Fisher, Page 16; The Dance of Farming, by June Bartos, Page 3;
PHOTO FEATURE -Peas: the Taste of Spring, Page 10;
POLICY CORNER -New Proposed Food Safety Laws, by Jason Foscolo, Esq, Page 7;
RESOURCE SPOTLIGHT -New Videos Teach Sheep Shearing, by Tianna Dupont, Page 7; The New York State Nut Tree Trail, by John Wertis, Page 5;
SEED STORIES -From Seed to Shining Seed, by Petra Page-Mann, Page 17;
STEWARDSHIP & NATURE -Conservation Sucess on Full Moon Farm, by Andrea Brendalen and John M.Thursgood, Page 20Cornell Small Farms Program, Cornell University Cooperative Extension, USDA NRCS, NYS 4-H Team Progra
A hybrid decision tree/genetic algorithm method for data mining
No full textThis paper addresses the well-known classification task of data mining, where the
objective is to predict the class which an example belongs to. Discovered
knowledge is expressed in the form of high-level, easy-to-interpret classification
rules. In order to discover classification rules, we propose a hybrid decision
tree/genetic algorithm method. The central idea of this hybrid method involves the
concept of small disjuncts in data mining, as follows. In essence, a set of
classification rules can be regarded as a logical disjunction of rules, so that each
rule can be regarded as a disjunct. A small disjunct is a rule covering a small
number of examples. Due to their nature, small disjuncts are error prone.
However, although each small disjunct covers just a few examples, the set of all
small disjuncts can cover a large number of examples, so that it is important to develop new approaches to cope with the problem of small disjuncts. In our hybrid approach, we have developed two genetic algorithms (GA) specifically designed for discovering rules covering examples belonging to small disjuncts, whereas a conventional decision tree algorithm is used to produce rules covering examples belonging to large disjuncts. We present results evaluating the performance of the hybrid method in 22 real-world data sets
The Steiner tree problem on graphs: inapproximability results
No full textAbstractThe Steiner tree problem on weighted graphs seeks a minimum weight subtree containing a given subset of the vertices (terminals). We show that it is NP-hard to approximate the Steiner tree problem within a factor 96/95. Our inapproximability results are stated in a parametric way, and explicit hardness factors would be improved automatically by providing gadgets and/or expanders with better parameters
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
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