Abstract:In this study, eight airborne laser scanning (ALS)-based single tree detection methods are benchmarked and investigated. The methods were applied to a unique dataset originating from different regions of the Alpine Space covering different study areas, forest OPEN ACCESSForests 2015, 6 1722 types, and structures. This is the first benchmark ever performed for different forests within the Alps. The evaluation of the detection results was carried out in a reproducible way by automatically matching them to precise in situ forest inventory data using a restricted nearest neighbor detection approach. Quantitative statistical parameters such as percentages of correctly matched trees and omission and commission errors are presented. The proposed automated matching procedure presented herein shows an overall accuracy of 97%. Method based analysis, investigations per forest type, and an overall benchmark performance are presented. The best matching rate was obtained for single-layered coniferous forests. Dominated trees were challenging for all methods. The overall performance shows a matching rate of 47%, which is comparable to results of other benchmarks performed in the past. The study provides new insight regarding the potential and limits of tree detection with ALS and underlines some key aspects regarding the choice of method when performing single tree detection for the various forest types encountered in alpine regions.

Several hypotheses have been proposed to explain the direction and extent of sexual size dimorphism in anurans (in which males are usually smaller than females) as a result of sexual selection. Here, we present an analysis to test the hypothesis that sexual dimorphism in anurans is largely a function of differences between the sexes in life-history strategies. Morphological and demographic data for anurans were collected from the literature, and the mean size and age in each sex were calculated for 51 populations, across 30 species and eight genera. Comparisons across 14 Rana species, eight Bufo species and across the genera showed a highly significant relationship between size dimorphism, measured using the female-male size ratio, and mean female-male age difference. A comparison of a subset of 17 of these species for which phylogenetic information was available, using the method of independent contrasts, yielded a similar result. These results indicate that most of the variation in size dimorphism in the anura can be explained in terms of differences in the age structure between the sexes in breeding populations. If sexual selection has an effect on size dimorphism in anurans, it is likely to be only a secondary one.

International audienceNatural hazards are frequent in mountain areas where they regularly cause casualties and damages to human infras-tructures. Mountain forests contribute in mitigating these hazards, in particular rockfalls. Assessing the protective effect of a forest against rockfall is a difficult task for both forest managers and rockfall experts. Accurate and simple tools are therefore required to efficiently evaluate the level of protection that results from the presence of forest. This study defines three novel indicators to quantify the protective effect of forests against rockfalls, regarding 1) the reduction of the frequency of rockfalls, 2) the reduction of their maximum intensity, and 3) the combination of the reduction of the frequency and the energy of the rocks. The first two indicators are relevant for rockfall experts whereas the third is mostly interesting for foresters as it summarizes the protective effect of forest. The Rockyfor3D model was adapted and used to simulate rockfalls propagation on 3886 different forest stands located in all the French Alps. The results of the simulations were used to calculate the three indicators for each forest stand. Finally, the relations between the forest structures and compositions and the indicators values were investigated. Our principal result shows that only three forest characteristics are required to accurately predict the indicators and evaluate the protective level of a forest against rockfall. The two first variables correspond to the basal area and the mean diameter at breast height (DBH) of the forest stand which are two parameters commonly used by forest managers. The third characteristic is the length of forest in the maximum slope direction which can be computed with a geographic information system (GIS). The method proposed in this study is easily reproducible and is suitable to evaluate the protective effect of European mountain forests at different scales. At local scale, the proposed indicators can enrich rockfall studies in which forests are usually set aside to simplify the evaluation. Moreover, the indicators may find direct applications with foresters by allowing them to identify the protective level of their forest and consequently to adapt their management. Finally, the indicators are convenient to perform spatial analysis and produce maps of the protective effect of mountain forests that could find many applications in land settlement or evaluation of ecosystem services

Continuous maps of forest parameters can be derived from airborne laser scanning (ALS) remote sensing data. A prediction model is calibrated between local point cloud statistics and forest parameters measured on field plots. Unfortunately, inaccurate positioning of field measures lead to a bad matching of forest measures with remote sensing data. The potential of using tree diameter and position measures in cross-correlation with ALS data to improve co-registration is evaluated. The influence of the correction on ALS models is assessed by comparing the accuracy of basal area prediction models calibrated or validated with or without the corrected positions. In a coniferous, uneven-aged forest with high density ALS data and low positioning precision, the algorithm co-registers 91% of plots within two meters from the operator location when at least the five largest trees are used in the analysis. The new coordinates slightly improve the prediction models and allow a better estimation of their accuracy. In a forest with various stand structures and species, lower ALS density and differential Global Navigation Satellite System measurements, position correction turns out to have only a limited impact on prediction models.

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