Short Communication. Application of Meta-Analysis if Forestry Related Topics.

<p><em>Aim of study</em>: Provision of the necessary knowledge to foresters in order carry out objective literature research, through meta-analysis.</p><p><em>Area of study</em>:Mediterranean</p><p><em>Material and Methods</em>: We describe in detail the methodology of meta-analysis. Then, we apply a meta-analysis in a set of independent studies of density of Aleppo pine (<em>Pinus halepensis</em> Mill.), a common forest species of theMediterranean.</p><p><em>Research highlights</em>: Making high quality meta-analyses, can help foresters in making the most of individual forest studies by synthesize them. In this work:</p><ul><li>We provide details on approaches for undertaking a meta-analysis.</li><li>We use a silvicultural example to demonstrate our idea.</li><li>We show how the method of meta-analysis could be applied to forestry also (besides the classical medical study reviews).</li><li>We have as ultimate goal the use of this article as a reference from other researchers as regards the application of meta-analysis to their area of expertise.</li></ul><p><strong>Keywords</strong>: Literature research; Systematic review.</p

Short communication. Application of meta-analysis in forestry related topics

Aim of study: Provision of the necessary knowledge to foresters in order carry out objective literature research, through meta-analysis.Area of study:MediterraneanMaterial and Methods: We describe in detail the methodology of meta-analysis. Then, we apply a meta-analysis in a set of independent studies of density of Aleppo pine (Pinus halepensis Mill.), a common forest species of theMediterranean.Research highlights: Making high quality meta-analyses, can help foresters in making the most of individual forest studies by synthesize them. In this work:We provide details on approaches for undertaking a meta-analysis.We use a silvicultural example to demonstrate our idea.We show how the method of meta-analysis could be applied to forestry also (besides the classical medical study reviews).We have as ultimate goal the use of this article as a reference from other researchers as regards the application of meta-analysis to their area of expertise.Keywords: Literature research; Systematic review.</p

Analyses of the Food Habits of the Red Fox and the Stone Marten in Central Greece Using a Tree-Fitting Model

The dietary habits of red fox (Vulpes vulpes) and stone marten (Martes foina) were studied in central Greece in period 2003 - 2005. The stomach contents of 219 red fox and 106 stone marten were characterised for their various prey items. The prey species were classified depending on their origin in six diet groups (mammals, birds, plants, arthropods, reptiles &ndash; amphibians and others). The samples were collected from regions where hunting is practised and in regions where hunting is not practised and classified across seasons and habitats (shrubs, agriculture, oaks). Plants, arthropods and mammals dominated the diet of the two carnivores in all seasons. The carnivores took birds and reptiles &ndash; amphibians at low levels, accounting for less than 11% of the food items for any season. Manmade items were more common in the red fox diet than for the other carnivore Using tree analysis, the only dependent variable included in the final model was &ldquo;season&rdquo;, indicating that &ldquo;season&rdquo; was the best predictor of &ldquo;diet group&rdquo;, while food habits were not significantly different with respect to &ldquo;year&rdquo;, &ldquo;habitat&rdquo; and &ldquo;hunting&rdquo;

Flood risk perception and adaptation capacity: a contribution to the socio-hydrology debate

International audienceAbstract. Dealing with flood hazard and risk requires approaches rooted in both natural and social sciences, which provided the nexus for the ongoing debate on socio-hydrology. Various combinations of non-structural and structural flood risk reduction options are available to communities. Focusing on flood risk and the information associated with it, developing risk management plans is required but often overlooks public perception of a threat. The perception of risk varies in many different ways, especially between the authorities and the affected public. It is because of this disconnection that many risk management plans concerning floods have failed in the past. This paper examines the private adaptation capacity and willingness with respect to flooding in two different catchments in Greece prone to multiple flood events during the last 20 years. Two studies (East Attica and Evros) were carried out, comprised of a survey questionnaire of 155 and 157 individuals, from a peri-urban (East Attica) and a rural (Evros) area, respectively, and they focused on those vulnerable to periodic (rural area) and flash floods (peri-urban area). Based on the comparisons drawn from these responses, and identifying key issues to be addressed when flood risk management plans are implemented, improvements are being recommended for the social dimension surrounding such implementation. As such, the paper contributes to the ongoing discussion on human–environment interaction in socio-hydrology

Combination of M-Estimators and Neural Network Model to Analyze Inside/Outside Bark Tree Diameters

Part 1: ANN-Classification and Pattern RecognitionInternational audienceOne of the most important statistical tools is linear regression analysis for many fields such as medical sciences, social sciences, econometrics and more. Regression techniques are commonly used for modelling the relationship between response variables and explanatory variables. In this study, inside bark tree diameter was used as the dependent variable and outside bark diameter and site type as independents. While generally it is assumed that inside and outside bark diameters are linearly correlated, linear regression application is weak in the presence of outliers. The purpose of this study was to develop a Multi-Layer Perceptron neural network model which considered significant variables from an a priori developed robust regression model. The application of robust regression could be considered in selecting the input variables in a neural network model