Forests2015, 6(5), 1721-1747; doi:10.3390/f6051721 - published 15 May 2015 Show/Hide Abstract
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 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.
Forests2015, 6(5), 1696-1720; doi:10.3390/f6051696 - published 13 May 2015 Show/Hide Abstract
Abstract: Collaborative management is a new framework to help implement programmes in protected areas. Within this context, the aim of this work is twofold. First, to propose a robust methodology to implement collaborative management focused on ecosystem services. Second, to develop indicators for the main functions of ecosystem services. Decision makers, technical staff and other stakeholders are included in the process from the beginning, by identifying ecosystem services and eliciting preferences using the AHP method. Qualitative and quantitative data are then integrated into a PROMETHEE based method in order to obtain indicators for provisioning, maintenance and direct to citizens services. This methodology, which has been applied in a forest area, provides a tool for exploiting available technical and social data in a continuous process, as well as providing easy to understand graphical results. This approach also overcomes the difficulties found in prioritizing management objectives in a multiple criteria context with limited resources and facilitates consensus between all of the people involved. The new indicators define an innovative approach to assessing the ecosystem services from the supply perspective and provide basic information to help establish payment systems for environmental services and compensation for natural disasters.
Forests2015, 6(5), 1666-1695; doi:10.3390/f6051666 - published 13 May 2015 Show/Hide Abstract
Abstract: While sustainable forestry in Europe is characterized by the provision of a multitude of forest ecosystem services, there exists no comprehensive study that scrutinizes their sensitivity to forest management on a pan-European scale, so far. We compile scenario runs from regionally tailored forest growth models and Decision Support Systems (DSS) from 20 case studies throughout Europe and analyze whether the ecosystem service provision depends on management intensity and other co-variables, comprising regional affiliation, social environment, and tree species composition. The simulation runs provide information about the case-specifically most important ecosystem services in terms of appropriate indicators. We found a strong positive correlation between management intensity and wood production, but only weak correlation with protective and socioeconomic forest functions. Interestingly, depending on the forest region, we found that biodiversity can react in both ways, positively and negatively, to increased management intensity. Thus, it may be in tradeoff or in synergy with wood production and forest resource maintenance. The covariables species composition and social environment are of punctual interest only, while the affiliation to a certain region often makes an important difference in terms of an ecosystem service’s treatment sensitivity.
Forests2015, 6(5), 1649-1665; doi:10.3390/f6051649 - published 12 May 2015 Show/Hide Abstract
Abstract: Cinnamyl alcohol dehydrogenase (CAD) catalyzes the key step in the lignin monomer biosynthesis pathway, but little is known about CADs in larch (Larix olgensis). Larch is one of the most important conifer plantation species and is used worldwide for reforestation and paper making. However, the presence of lignin is a significant barrier in the conversion of plant biomass to bioethanol. In the current study, 240 individuals from the Northeast Forest University provenance progeny trial population were evaluated, and 47 single-nucleotide polymorphisms (SNPs) were identified in the CAD gene. We used a candidate gene-based association mapping approach to identify CAD gene allelic variants that were associated with growth and wood property traits in L. olgensis. We found that LoCAD harbors high single nucleotide polymorphism (SNP) diversity (πT = 0.00622 and θW = 0.00646). The results of an association analysis indicated that nine SNPs and six haplotypes were significantly associated with wood property and growth traits, explaining between 1.35% and 18.4% of the phenotypic variance. There were strong associations between SNP (g.590G > T) and SNP (g.1184A > T) in LoCAD. These SNPs might represent two quantitative trait nucleotides that are important for the analysis of lignin content.
Forests2015, 6(5), 1628-1648; doi:10.3390/f6051628 - published 12 May 2015 Show/Hide Abstract
Abstract: The Canadian boreal forest is largely represented by mixed wood forests of white spruce (Picea glauca (Moench) Voss) and trembling aspen (Populus tremuloides Michx). In this study, a total of 300 trees originating from three sites composed of trembling aspen and white spruce with varying compositions were investigated for wood quality traits: one site was composed mainly of aspen, one mainly of spruce and a third was a mixed site. Four wood quality traits were examined: wood density, microfibril angle (MFA), fibre characteristics, and cell wall chemistry. Social classes were also determined for each site in an attempt to provide a more in-depth comparison. Wood density showed little variation among sites for both species, with only significant differences occurring between social classes. The aspen site showed statistically lower MFAs than the aspen from the mixed site, however, no differences were observed when comparing spruce. Fibre characteristics were higher in the pure species sites for both species. There were no differences in carbohydrate contents across sites, while lignin content varied. Overall, the use of social classes did not refine the characterization of sites.
Forests2015, 6(5), 1613-1627; doi:10.3390/f6051613 - published 7 May 2015 Show/Hide Abstract
Abstract: Airborne Laser Scanning (ALS) data hold a great deal of promise in monitoring the reduction of single trees and forests with high accuracy. In the literature, the canopy height model (CHM) is the main input used frequently for forest change detection. ALS also has the key capability of delivering 3D point clouds, not only from the top canopy surface, but also from the entire canopy profile and also from the terrain. We investigated the use of two additional parameters, which exploit these capabilities for assessing the reduction of wooded area: Slope-adapted echo ratio (sER) and Sigma0. In this study, two ALS point cloud data sets (2005 and 2011) were used to calculate Digital Surface Model (DSM), sER, and Sigma0 in 1.5 km2 forest area in Vorarlberg, Austria. Image differencing was applied to indicate the change in the three difference models individually and in their combinations. Decision trees were used to classify the area of removed trees with the minimum mapping unit of 13 m2. The final results were evaluated by a knowledge-based manual digitization using completeness and correctness measures. The best result is achieved using the combination of sER and DSM, namely a correctness of 92% and a completeness of 85%.