Conditional Classification Trees Research Articles

Forest management plan pathways for non-industrial private forest owners in Norway: from acquisition to implementation

AbstractForest management plans (FMP) are key decision-support tools for forest managers and a central policy instrument in many countries. Despite its pivotal importance in forest management, there is a lack of studies that analyze the acquisition, familiarity and implementation of the FMP. These steps collectively contribute to making FMP a successful decision-support tool and forest policy instrument. We surveyed a sample representative of the population of Norwegian non-industrial private forest (NIPF) owners to quantify the importance of a broad set of factors, including ownership objectives, socio-demographic, property and information sources variables on the FMP pathway, i.e. acquisition of FMP, awareness of its content and implementation of the plans’ proposals. Applying principal component analysis on twelve ownership objectives, we found that most forest owners are multiobjective. We combined conditional classification trees and logistic regression analyses on the FMP pathway to unveil familiarity and use of FMP in forest owner subgroups as well as individual drivers. The results indicate that 37% of Norwegian NIPF owners have a FMP. Among the owners having FMP, 66% have good knowledge of its content and 40% implement its proposals. The strongest variables to predict FMP familiarity and use were previous harvests, productive area, advice about forestry from the public management, knowledge of public support schemes for forestry and perceived relevance of the FMP. We conclude that FMP suppliers, consultants, forestry bureaucracy and policy-makers should emphasize information dissemination and relevance of the FMP to increase its success as a decision-support tool and forest policy instrument.

Severity classes in adults with hypermobile Ehlers-Danlos syndrome/hypermobility spectrum disorders: a pilot study of 105 Italian patients.

This study is aimed at identifying discrete severity classes among adults with hypermobile Ehlers-Danlos syndrome (hEDS)/hypermobility spectrum disorders (HSD). Subjects were selected according to the old and new nomenclatures and all completed a set of questionnaires exploring pain, fatigue, dysautonomic symptoms, coordination and attention/concentration deficits and quality of life in general. Data were investigated by hierarchical clustering on principal components. Cluster comparisons were then performed by using the two-sample unpaired t test and the standardized mean difference was reported as a measure of effect size. Conditional classification tree analysis and multivariable logistic regression were carried out in order to identify the profiles that were at higher risk to belong to the more severe cluster. Weighted linear combination was used to identify a numerical score measuring this risk. A total of 105 patients were selected and distributed in two distinct severity groups. These groups were statistically separated on the basis of 47 of 59 items/characteristics. One group featured the worse values of most questionnaire items (complex/severe cluster) and the other was dominated by the better values (simplex/milder cluster). Only three items were able to stratify patients according to their risk to belong to the complex cluster. A severity score was then constructed on these three items. Adults with hEDS/HSD can be separated in two severity classes, which do not mirror either the old or new criteria for hEDS. The identified severity score could allow a bi-dimensional approach to adults with hEDS/HSD for optimal management planning.

Estimating population extinction thresholds with categorical classification trees for Louisiana black bears.

Monitoring vulnerable species is critical for their conservation. Thresholds or tipping points are commonly used to indicate when populations become vulnerable to extinction and to trigger changes in conservation actions. However, quantitative methods to determine such thresholds have not been well explored. The Louisiana black bear (Ursus americanus luteolus) was removed from the list of threatened and endangered species under the U.S. Endangered Species Act in 2016 and our objectives were to determine the most appropriate parameters and thresholds for monitoring and management action. Capture mark recapture (CMR) data from 2006 to 2012 were used to estimate population parameters and variances. We used stochastic population simulations and conditional classification trees to identify demographic rates for monitoring that would be most indicative of heighted extinction risk. We then identified thresholds that would be reliable predictors of population viability. Conditional classification trees indicated that annual apparent survival rates for adult females averaged over 5 years () was the best predictor of population persistence. Specifically, population persistence was estimated to be ≥95% over 100 years when , suggesting that this statistic can be used as threshold to trigger management intervention. Our evaluation produced monitoring protocols that reliably predicted population persistence and was cost-effective. We conclude that population projections and conditional classification trees can be valuable tools for identifying extinction thresholds used in monitoring programs.

Epistatic interaction between haplotypes of the ghrelin ligand and receptor genes influence susceptibility to myocardial infarction and coronary artery disease

Data from both experimental models and humans provide evidence that ghrelin and its receptor, the growth hormone secretagogue receptor (ghrelin receptor, GHSR), possess a variety of cardiovascular effects. Thus, we hypothesized that genetic variants within the ghrelin system (ligand ghrelin and its receptor GHSR) are associated with susceptibility to myocardial infarction (MI) and coronary artery disease (CAD). Seven single nucleotide polymorphisms (SNPs) covering the GHSR region as well as eight SNPs across the ghrelin gene (GHRL) region were genotyped in index MI patients (864 Caucasians, 'index MI cases') from the German MI family study and in matched controls without evidence of CAD (864 Caucasians, 'controls', MONICA Augsburg). In addition, siblings of these MI patients with documented severe CAD (826 'affected sibs') were matched likewise with controls (n = 826 Caucasian 'controls') and used for verification. The effect of interactions between genetic variants of both genes of the ghrelin system was explored by conditional classification tree models. We found association of several GHSR SNPs with MI [best SNP odds ratio (OR) 1.7 (1.2-2.5); P = 0.002] using a recessive model. Moreover, we identified a common GHSR haplotype which significantly increases the risk for MI [multivariate adjusted OR for homozygous carriers 1.6 (1.1-2.5) and CAD OR 1.6 (1.1-2.5)]. In contrast, no relationship between genetic variants and the disease could be revealed for GHRL. However, the increase in MI/CAD frequency related to the susceptible GHSR haplotype was abolished when it coincided with a common GHRL haplotype. Multivariate adjustments as well as permutation-based methods conveyed the same results. These data are the first to demonstrate an association of SNPs and haplotypes within important genes of the ghrelin system and the susceptibility to MI, whereas association with MI/CAD could be identified for genetic variants across GHSR, no relationship could be revealed for GHRL itself. However, we found an effect of GHRL dependent upon the presence of a common, MI and CAD susceptible haplotype of GHSR. Thus, our data suggest that specific haplotypes of the ghrelin ligand and its receptor act epistatically to affect susceptibility or tolerance to MI and/or CAD.