Abstract: We propose new methods for evaluating the spatial distribution of firms. To assess whether firms are concentrated or dispersed, economists have traditionally used indices that analyse the heterogeneity of a spatial structure at a single geographic level. We introduce distance-based methods, Besag's L function (derived from Ripley's K function) and Diggle and Chetwynd's D function to describe simultaneously spatial distribution at different geographical scales. Our empirical applications consider the distribution of French manufacturing firms in the Paris area and in France generally. For some geographic levels, results show significant concentration or dispersion of firms according to their sector of activity.

Abstract: Beta diversity is among the most employed theoretical concepts in ecology and biodiversity conservation. Up to date, a self-contained definition of it, with no reference to alpha and gamma diversity, has never been proposed. Using Kullback-Leibler divergence, we present the explicit formula of Shannon's β entropy, a bias correction for its estimator and a confidence interval. We also provide the mathematical framework to decompose Shannon diversity into several hierarchical nested levels. From botanical inventories of tropical forest plots in French Guiana, we estimate Shannon diversity at the plot, forest and regional level. We believe this is a complete and usefulness toolbox for ecologists interested in partitioning biodiversity. © 2011 The Authors. Oikos © 2012 Nordic Society Oikos.

Abstract: entropart is a package for R designed to estimate diversity based on HCDT entropy or similarity-based entropy. It allows calculating species-neutral, phylogenetic and functional entropy and diversity, partitioning them and correcting them for estimation bias. © 2015, American Statistical Association. All rights reserved.

Abstract: The data available in the literature concerning wood cutting forces permits to build models or to simulate the main wood machining processes ( milling, sawing, peeling, etc.). This approach contributes to a better understanding of formation of wood surfaces and chips and the data may be helpful to optimise cutting geometry, reduce tool wear, improve tool material, and to size tool-machines. The models may also be useful for industrial application in two ways: ( 1) providing data to optimise the settings for a given operation ( batch approach), and ( 2) building predictive models that could be the basis of an online control system for the machining processes ( interactive approach). A prerequisite for this is that numerous machining tests on different wood materials are performed based on experiences with different kind of tools and experimental devices. With a focus on potential industrial applications, the emphasis of this review was on the wood peeling process, which is a very demanding special case of wood cutting. Although not so many industrial machines are equipped with expensive force sensors, there is a lot of high quality information available about cutting forces which may be useful to improve the scientific or technological knowledge in wood machining. Alternative parameters, such as vibration or sound measurements, appear to be promising substitutes in the praxis, particularly to feed online control systems of any wood cutting process.

Abstract: Amazonian droughts are predicted to become increasingly frequent and intense, and the vulnerability of Amazonian trees has become increasingly documented. However, little is known about the physiological mechanisms and the diversity of drought tolerance of tropical trees due to the lack of quantitative measurements. Leaf water potential at wilting or turgor loss point (π<inf>tlp</inf>) is a determinant of the tolerance of leaves to drought stress and contributes to plant-level physiological drought tolerance. Recently, it has been demonstrated that leaf osmotic water potential at full hydration (π<inf>o</inf>) is tightly correlated with π<inf>tlp</inf>. Estimating π<inf>tlp</inf> from osmometer measurements of π<inf>o</inf> is much faster than the standard pressure-volume curve approach of π<inf>tlp</inf> determination. We used this technique to estimate π<inf>tlp</inf> for 165 trees of 71 species, at three sites within forests in French Guiana. Our data set represents a significant increase in available data for this trait for tropical tree species. Tropical trees showed a wider range of drought tolerance than previously found in the literature, π<inf>tlp</inf> ranging from -1·4 to -3·2 MPa. This range likely corresponds in part to adaptation and acclimation to occasionally extreme droughts during the dry season. Leaf-level drought tolerance varied across species, in agreement with the available published observations of species variation in drought-induced mortality. On average, species with a more negative π<inf>tlp</inf> (i.e. with greater leaf-level drought tolerance) occurred less frequently across the region than drought-sensitive species. Across individuals, π<inf>tlp</inf> correlated positively but weakly with leaf toughness (R2 = 0·22, P = 0·04) and leaf thickness (R2 = 0·03, P = 0·03). No correlation was detected with other functional traits (leaf mass per area, leaf area, nitrogen or carbon concentrations, carbon isotope ratio, sapwood density or bark thickness). The variability in π<inf>tlp</inf> among species indicates a potential for highly diverse species responses to drought within given forest communities. Given the weak correlations between π<inf>tlp</inf> and traditionally measured plant functional traits, vegetation models seeking to predict forest response to drought should integrate improved quantification of comparative drought tolerance among tree species. © 2015 British Ecological Society.