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  • 1
    Language: English
    In: European Journal of Forest Research, 2010, Vol.129(5), pp.833-846
    Description: The three nonparametric k nearest neighbour ( k NN) approaches, most similar neighbour inference (MSN), random forests (RF) and random forests based on conditional inference trees (CF) were compared for spatial predictions of standing timber volume with respect to tree species compositions and for predictions of stem number distributions over diameter classes. Various metrics derived from airborne laser scanning (ALS) data and the characteristics of tree species composition obtained from coarse stand level ground surveys were applied as auxiliary variables. Due to the results of iterative variable selections, only the ALS data proved to be a relevant predictor variable set. The three applied NN approaches were tested in terms of bias and root mean squared difference (RMSD) at the plot level and standard errors at the stand level. Spatial correlations were considered in the statistical models. While CF and MSN performed almost similarly well, large biases were observed for RF. The obtained results suggest that biases in the RF predictions were caused by inherent problems of the RF approach. Maps for Norway spruce and European beech timber volume were exemplarily created. The RMSD values of CF at the plot level for total volume and the species-specific volumes for European beech, Norway spruce, European silver fir and Douglas fir were 32.8, 80.5, 99.0, 137.0 and 261.1%. These RMSD values were smaller than the standard deviation, although Douglas fir volume did not belong to the actual response variables. All three non-parametric approaches were also capable of predicting diameter distributions. The standard errors of the nearest neighbour predictions on the stand level were generally smaller than the standard error of the sample plot inventory. In addition, the employed model-based approach allowed k NN predictions of means and standard errors for stands without sample plots.
    Keywords: Forest inventory ; Model-based inference ; Lidar ; Nonparametric regression ; Upscaling ; Mapping ; Conditional inference trees ; Random forest ; Most similar neighbour inference
    ISSN: 1612-4669
    E-ISSN: 1612-4677
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  • 2
    Language: English
    In: Forest Ecology and Management, 15 November 2015, Vol.356, pp.136-143
    Description: Phosphorus is an essential yet scarce macronutrient, and as such forest nutrition often relies on cycling of P between biomass and soils through litterfall and roots. For technical and soil protection reasons, modern harvesting systems create thick brash mats on skid trails by depositing residues, thus concentrating P there. What portion of this redistributed P is immobilized, lost, or recycled could be significant to forest nutrition and management. However, open questions exist regarding the quantity and fate of P deposited on skid trials. The aim of this study was to determine how much P is redistributed to skid trails and what happens to that P. We modeled the amount of P deposited on a skid trail during a whole-tree thinning of an Mill. stand, and quantified P stocks in the forest floor and mineral soil five years after the operation. An estimated 60% of harvested P from the encatchment was deposited on the skid trail. Five years after the harvest, forest floor P stocks in the skid trail dropped from an extrapolated 8.9 to 4.4 g m . The difference of 4.5 g m of P was not evident in mineral soil stocks, and loss through runoff or leaching would be minimal. With the greatest concentration of roots in the forest floor on the middle of the skid trail, mineralization and uptake of the missing P was the most likely explanation. This suggests that accumulated P on skid trails can be recycled through uptake by trees. Further testing in other stands and on which vegetation takes up accumulated P is still needed.
    Keywords: Nutrient Cycling ; Plant Uptake ; Whole-Tree Harvesting ; Brash Mats ; Allometric Modeling ; Forestry ; Biology
    ISSN: 0378-1127
    E-ISSN: 1872-7042
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  • 3
    Language: English
    In: Journal of Environmental Management, 15 February 2014, Vol.134, pp.153-165
    Description: The paper deals with the management problem how to decide on tree species suitability under changing environmental conditions. It presents an algorithm that classifies the output of a range shift model for major tree species in Europe into multiple classes that can be linked to qualities characterizing the ecological niche of the species. The classes: i) Core distribution area, ii) Extended distribution area, iii) Occasional occurrence area, and iv) No occurrence area are first theoretically developed and then statistically described. The classes are interpreted from an ecological point of view using criteria like population structure, competitive strength, site spectrum and vulnerability to biotic hazards. The functioning of the algorithm is demonstrated using the example of a generalized linear model that was fitted to a pan-European dataset of presence/absence of major tree species with downscaled climate data from a General Circulation Model (GCM). Applications of the algorithm to tree species suitability classification on a European and regional level are shown. The thresholds that are used by the algorithm are precision-based and include Cohen's Kappa. A validation of the algorithm using an independent dataset of the German National Forest Inventory shows good accordance of the statistically derived classes with ecological traits for Norway spruce, while the differentiation especially between core and extended distribution for European beech that is in the centre of its natural range in this area is less accurate. We hypothesize that for species in the core of their range regional factors like forest history superimpose climatic factors. Problems of uncertainty issued from potentially applying a multitude of modelling approaches and/or climate realizations within the range shift model are discussed and a way to deal with the uncertainty by revealing the underlying attitude towards risk of the decision maker is proposed.
    Keywords: Range Shift Model ; Climate Change ; Tree Species Distribution ; Accuracy-Based Probability Threshold ; Bioclimatic Envelope ; Tree Species Suitability ; Environmental Sciences ; Economics
    ISSN: 0301-4797
    E-ISSN: 1095-8630
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  • 4
    In: Global Change Biology, October 2017, Vol.23(10), pp.4162-4176
    Description: Intense droughts combined with increased temperatures are one of the major threats to forest persistence in the 21st century. Despite the direct impact of climate change on forest growth and shifts in species abundance, the effect of altered demography on changes in the composition of functional traits is not well known. We sought to (1) quantify the recent changes in functional composition of European forests; (2) identify the relative importance of climate change, mean climate and forest development for changes in functional composition; and (3) analyse the roles of tree mortality and growth underlying any functional changes in different forest types. We quantified changes in functional composition from the 1980s to the 2000s across Europe by two dimensions of functional trait variation: the first dimension was mainly related to changes in leaf mass per area and wood density (partially related to the trait differences between angiosperms and gymnosperms), and the second dimension was related to changes in maximum tree height. Our results indicate that climate change and mean climatic effects strongly interacted with forest development and it was not possible to completely disentangle their effects. Where recent climate change was not too extreme, the patterns of functional change generally followed the expected patterns under secondary succession (e.g. towards late‐successional short‐statured hardwoods in Mediterranean forests and taller gymnosperms in boreal forests) and latitudinal gradients (e.g. larger proportion of gymnosperm‐like strategies at low water availability in forests formerly dominated by broad‐leaved deciduous species). Recent climate change generally favoured the dominance of angiosperm‐like related traits under increased temperature and intense droughts. Our results show functional composition changes over relatively short time scales in European forests. These changes are largely determined by tree mortality, which should be further investigated and modelled to adequately predict the impacts of climate change on forest function. Despite the direct impact of climate change on forest growth and shifts in species abundance, the effect of altered demography on changes in the composition of functional traits is not well known. In European forests, we observed that recent climate change generally favoured the dominance of angiosperm‐like related traits under increased temperature and intense droughts. Where recent climate change was not too extreme, the patterns of functional change generally followed the expected patterns under secondary succession. These changes were largely determined by tree mortality, which should be further investigated to adequately predict the impacts of climate change on forest function.
    Keywords: Climate Change ; Demographic Rates ; Drought ; Functional Traits ; Fundiveurope ; Mixed Modelling ; National Forest Inventory ; Piecewise Structural Equation modelling ; Temperature Anomaly ; Tree Growth
    ISSN: 1354-1013
    E-ISSN: 1365-2486
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  • 5
    Language: English
    In: Canadian Journal of Forest Research, 01/2011, Vol.41(1), pp.1-10
    Description: Forest edge length is important for landscape ecological analysis, including the analysis of fragmentation. In this paper, we estimate forest edge length using field sample data from the German National Forest Inventory as an example. The complex plot design of many large-area forest inventories allows for the estimation of forest edge length at different spatial resolutions. As expected, estimates depend on the spatial resolution: longer estimated edge lengths resulted from observations at finer spatial resolutions. From the comparison of estimated edge lengths at different spatial resolutions, conclusions about the irregularity of forest edges can be drawn: more irregular forest boundaries resulted in greater differences between the estimated lengths for different spatial resolutions. One conclusion is of particular relevance: reported forest edge length values are meaningless unless their spatial resolution is also reported. The analysis presented is an add-on to the standard estimations from a forest inventory, producing additional, ecologically meaningful information. It is contended that many more nonstandard analyses of forest inventory data are possible either immediately or with minor modifications to the plot design. Resume: La longueur de la lisiere forestiere est importante pour l'analyse ecologique du paysage, incluant l'analyse de la fragmentation. Dans cet article, nous estimons la longueur de la lisiere forestiere a l'aide de donnees d'echantillonnage terrain provenant a titre d'exemple de l'inventaire forestier national allemand. Le dispositif complexe de placettes de plusieurs inventaires forestiers couvrant de vastes territoires permet d'estimer la longueur de la lisiere forestiere a differentes resolutions spatiales. Comme prevu, les estimations dependent de la resolution spatiale: les observations realisees a des resolutions spatiales plus fines produisent des longueurs de lisiere forestiere plus longues. A partir de la comparaison des longueurs de lisiere estimees a differentes resolutions spatiales, on peut tirer des conclusions au sujet de l'irregularite de la lisiere forestiere: la difference entre les longueurs de lisiere estimees a differentes resolutions spatiales est plus grande lorsque la lisiere forestiere est plus irreguliere. Une conclusion est particulierement pertinente: les valeurs de longueur de lisiere forestiere n'ont aucune signification si la resolution spatiale n'est pas mentionnee. L'analyse presentee ici est un complement aux estimations standards d'un inventaire forestier qui fournit une information additionnelle importante du point de vue ecologique. Nous pretendons que plusieurs autres analyses non standards des donnees d'inventaire forestier sont possibles soit immediatement ou apres des modifications mineures au dispositif de placettes. [Traduit par la Redaction]
    Keywords: Forest Management -- Research ; Forest Ecology -- Management ; Estimation Theory -- Research;
    ISSN: 0045-5067
    E-ISSN: 1208-6037
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  • 6
    Language: English
    In: European Journal of Forest Research, 7/2014, Vol.133(4), pp.649-660
    Description: Issue Title: Special Section : Biological Reactions of Forests to Climate Change and Air Pollution The commitment to report greenhouse gas emissions requires an estimation of biomass stocks and their changes in forests. When this was first done, representative biomass functions for most common tree species were very often not available. In Germany, an estimation method based on solid volume was developed (expansion procedure). It is easy to apply because the required information is available for nearly all relevant tree species. However, the distributions of neither parameters nor prediction intervals are available. In this study, two different methods to estimate above-ground biomass for Norway spruce (Picea abies), European beech (Fagus sylvatica), and Scots pine (Pinus sylvestris) are compared. First, an approach based on information from the literature was used to predict above-ground biomass. It is basically the same method used in greenhouse gas reporting in Germany and was applied with prior and posterior parameters. Second, equations for direct estimation of biomass with standard regression techniques were developed. A sample of above-ground biomass of trees was measured in campaigns conducted previously to the third National Forest Inventory in Germany (2012). The data permitted the application of Bayesian calibration (BC) to estimate posterior distribution of the parameters for the expansion procedure. Moreover, BC enables the calculation of prediction intervals which are necessary for error estimations required for reporting. The two methods are compared with regard to predictive accuracy via cross-validation, under varying sample sizes. Our findings show that BC of the expansion procedure performs better, especially when sample size is small. We therefore encourage the use of existing knowledge together with small samples of observed biomass (e.g., for rare tree species) to gain predictive accuracy in biomass estimation. [PUBLICATION ]
    Keywords: Estimating Techniques ; Biomass ; Trees ; Plant Growth ; Bayesian Analysis ; Comparative Studies ; Regression Analysis;
    ISSN: 1612-4669
    E-ISSN: 1612-4677
    Source: Springer (via CrossRef)
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  • 7
    Language: English
    In: European Journal of Forest Research, 2013, Vol.132(5), pp.983-997
    Description: Modelling stem taper and volume is crucial in many forest management and planning systems. Taper models are used for diameter prediction at any location along the stem of a sample tree. Furthermore, taper models are flexible means to provide information on the stem volume and assortment structure of a forest stand or other management units. Usually, taper functions are mean functions of multiple linear or nonlinear regression models with diameter at breast height and tree height as predictor variables. In large-scale inventories, an upper diameter is often considered as an additional predictor variable to improve the reliability of taper and volume predictions. Most studies on stem taper focus on accurately modelling the mean function; the error structure of the regression model is neglected or treated as secondary. We present a semi-parametric linear mixed model where the population mean diameter at an arbitrary stem location is a smooth function of relative height. Observed tree-individual diameter deviations from the population mean are assumed to be realizations of a smooth Gaussian process with the covariance depending on the sampled diameter locations. In addition to the smooth random deviation from the population average, we consider independent zero mean residual errors in order to describe the deviations of the observed diameter measurements from the tree-individual smooth stem taper. The smooth model components are approximated by cubic spline functions with a B-spline basis and a small number of knots. The B-spline coefficients of the population mean function are treated as fixed effects, whereas coefficients of the smooth tree-individual deviation are modelled as random effects with zero mean and a symmetric positive definite covariance matrix. The taper of a tree is predicted using an arbitrary number of diameter and corresponding height measurements at arbitrary positions along the stem to calibrate the tree-individual random deviation from the population mean estimated by the fixed effects. This allows a flexible application of the method in practice. Volume predictions are calculated as the integral over cross-sectional areas estimated from the calibrated taper curve. Approximate estimators for the mean squared errors of volume estimates are provided. If the tree height is estimated or measured with error, we use the “law of total expectation and variance” to derive approximate diameter and volume predictions with associated confidence and prediction intervals. All methods presented in this study are implemented in the R-package TapeR .
    Keywords: Stem taper ; Timber volume ; Forest inventory ; Mixed-effects models ; Splines
    ISSN: 1612-4669
    E-ISSN: 1612-4677
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  • 8
    Language: English
    In: Forests, 01 January 2018, Vol.9(1), p.25
    Description: The alien invasive pathogen Hymenoscyphus fraxineus causes large-scale decline of European ash (Fraxinus excelsior). We assessed ash dieback in Germany and identified factors that were associated with this disease. Our assessment was based on a 2015 sampling of national forest inventory plots that represent a supra-regional area. In the time from 2012 to 2015, the number of regrown ash trees corresponded to only 42% of the number of trees that had been harvested or died. Severe defoliation was recorded for almost 40% of the living trees in 2015, and more than half of the crowns mainly consisted of epicormic shoots. Necroses were present in 24% of root collars. A total of 14% of the trees were in sound condition, which sum up to only 7% of the timber volume. On average, trees of a higher social status or with a larger diameter at breast height were healthier. Collar necroses were less prevalent at sites with a higher inclination of terrain, but there was no evidence for an influence of climatic variables on collar necroses. The disease was less severe at sites with smaller proportions of the basal area of ash compared to the total basal area of all trees and in the north-eastern part of the area of investigation. The regeneration of ash decreased drastically.
    Keywords: Fraxinus Excelsior ; Ash Dieback ; Hymenoscyphus Fraxineus ; National Forest Inventory ; Disease Progression ; Invasive Pathogen ; Crown Defoliation ; Collar Necrosis ; Regeneration ; Forestry
    E-ISSN: 1999-4907
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  • 9
    Language: English
    In: Annals of Forest Science, 2018, Vol.75(2), p.49
    Description: AbstractKey messageBiomass functions are relevant for an easy and quick estimation of tree biomass. Nevertheless, additive biomass functions for different species and different components have not been published for the area of Germany, yet. Now, we present a set of additive biomass functions for estimating component and total mass for eight species and up to nine components.ContextBiomass functions are relevant for an easy and quick estimation of tree biomass, e.g. for carbon budget calculation. Component-specific functions offer even more detail and can be used to answer questions about, e.g., biomass allocation to different components, (nutrient) element stock and flows or the amount and re-distribution of harvested biomass and its consequences.AimsSince there exists no published additive biomass functions in the context of Germany, we aimed at providing such equations for different species and different components using a comprehensive data set from different sources.MethodsWe collected several data sets for eight relevant tree species (Norway spruce, n = 1150 trees; Silver fir, n = 31; Douglas fir, n = 161; Scots pine, n = 460; European beech, n = 918; Oak, n = 313; Sycamore, n = 28 and European ash, n = 37) in Germany and adjacent countries, homogenised the component information, imputed missing values and applied nonlinear seemingly unrelated regression to eight (for deciduous trees species) respectively nine (for conifereous species) components simultaneously.ResultsThe collected data set contains trees from 7 cm diameter in breast height to around 80 cm. From this broad data basis, we established two sets of additive biomass functions: a simple model using the predictors diameter in breast height and tree height as well as a more elaborate model using up to six predictors.ConclusionFinally, we can present additive models for the eight relevant tree species in Germany. Models for Silver fir, European ash and Sycamore are rather limited in their model range due to their input data; the other models are based on a broad range of predictors and are considered to be broadly applicable.
    Keywords: Life Sciences ; Biomass Allocation ; Component Mass ; Multiple Imputation ; Sur Regression ; Norway Spruce–Scots Pine–Douglas Fir–European Beech–Oak ; Environmental Sciences ; Forestry
    ISSN: 1286-4560
    E-ISSN: 1297-966X
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  • 10
    Language: English
    In: Forests, 01 July 2017, Vol.8(7), p.239
    Description: Integration of remote sensing (RS) data in forest inventories for enhancing plot-based forest variable prediction is a widely researched topic. Geometric consistency between forest inventory plots and areas for extraction of RS-based predictive metrics is considered a crucial factor for accurate modelling of forest variables. Achieving geometric consistency is particularly difficult with regard to angle-count sampling (ACS) plots, which have neither distinct shape nor distinct extent. This initial study considers a new approach for integrating ACS and RS data, where the concept of ACS is transferred to RS-based metrics extraction. By using the relationship between tree height and diameter at breast height (DBH), pixels of a RS-based canopy height model are extracted if their value suggests a DBH that would lead to inclusion in an angle-count sample at the given distance to the plot centre. Different variations of this approach are tested by modelling timber volume in national forest inventory plots in Germany. The results are compared to those achieved using fixed-radius plots. A root mean square error of approximately 42% is achieved by both the new and fixed-radius approaches. Therefore, the new approach is not yet considered sufficient for overcoming all difficulties concerning the integration of ACS plot and RS data. However, possibilities for improvement are discussed and will be the subject of further research.
    Keywords: Remote Sensing ; Forest Inventory ; Angle Count Sampling ; Timber Volume Modelling ; Aerial Images ; Digital Surface Models ; Canopy Height Models ; Forestry
    E-ISSN: 1999-4907
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