ALBERT

Description: In boreal bogs plant species are low in number, but they differ greatly in their growth forms and photosynthetic properties. We assessed how ecosystem carbon (C) sink dynamics were affected by seasonal variations in photosynthetic rate and leaf area of different species. Photosynthetic properties (light-response parameters), leaf area development and areal cover (abundance) of the species were used to quantify species-specific net and gross photosynthesis rates (PN and PG, respectively), which were summed to express ecosystem-level PN and PG. The ecosystem-level PG was compared with a gross primary production (GPP) estimate derived from eddy covariance measurements (EC). Species areal cover rather than differences in photosynthetic properties determined the species with the highest PG of both vascular plants and Sphagna. Species-specific contributions to the ecosystem PG varied over the growing season, which in turn determined the seasonal variation in ecosystem PG. The upscaled growing-season PG estimate, 230 g C/m**2, agreed well with the GPP estimated by the EC, 243 g C/m**2. Sphagna were superior to vascular plants in ecosystem-level PG throughout the growing season but had a lower PN. PN results indicated that areal cover of the species together with their differences in photosynthetic parameters shape the ecosystem-level C balance. Species with low areal cover but high photosynthetic efficiency appear to be potentially important for the ecosystem C sink. Results imply that functional diversity may increase the stability of C sink of boreal bogs.

Description: A systematic evaluation of nonlinear fixed- and mixed-effects taper models in volume prediction was conducted. Among 33 taper equations, the best 1- to 10-parameter fixed-effects models according to fitting statistics were further analysed by comparing their predictions against the modelling data and an independent data set. Three alternative prediction strategies were compared using the best equation (Kozak II) in the absence of calibration data (the usual situation in forestry practice). Strategy 1 used a fixed-parameter model (marginal model), strategy 2 utilized the fixed part of a mixed-effects model (conditional model), and strategy 3 calculated a marginal prediction based on the mixed-effects model by averaging the predictions over the estimated distribution of random effects. Strategies 1 and 3 performed better than strategy 2 in model evaluation (in modelling data) and model validation (independent data). Strategy 3 was less biased than strategy 1 in model validation, and both had the same mean squared deviation. Strategy 3 shares the most advantageous features of the other prediction methods and is therefore recommended for forestry practice and for further research in different modelling disciplines within forest science.

Description: Individual tree heights are needed in many situations, including estimation of tree volume, dominant height, and simulation of tree growth. However, height measurements are tedious compared to tree diameter measurements, and therefore height–diameter (H–D) models are commonly used for prediction of tree height. Previous studies have fitted H–D models using approaches that include plot-specific predictors in the models and those that do not include them. In both these approaches, aggregation of the observations to sample plots has usually been taken into account through random effects, but this has not always been done. In this paper, we discuss four alternative model formulations and report an extensive comparison of 16 nonlinear functions in this context using a total of 28 datasets. The datasets represent a wide range of tree species, regions, and ecological zones, consisting of about 126 000 measured trees from 3717 sample plots. Specific R-functions for model fitting and prediction were developed to enable such an extensive model fitting and comparison. Suggestions on model selection, model fitting procedures, and prediction are given and interpretation of the predictions from different models are discussed. No uniformly best function, model formulation, or model fitting procedure was found. However, a 2-parameter Näslund and Curtis function provided satisfactory fit in most datasets for the plot-specific H–D relationship. Model fitting and height imputation procedures developed for this study are provided in an R-package for later use.

Description: In this study, Lorenz curve descriptors of tree diameter inequality were used to characterize the dynamics of forest development in a shelterwood-managed Pinus sylvestris (L.) dominated area. The purpose was to stratify the forest area into forest structural types (FST) from airborne laser scanning (ALS)-based wall-to-wall predictions of the chosen indicators: Gini coefficient (GC) and Lorenz asymmetry (LA). A clear boundary at GC = 0.5 was found, which separated even-sized (below) and uneven-sized (above) areas. Furthermore, a need for including LA in the characterization of the uneven-sized areas was detected, to distinguish bimodal from reverse J-shaped stands. Beta regression was used for the ALS predictions, yielding RMSEs of 19.67% for GC and 11.01% for LA. Based on our results, we concluded that forest disturbance decreases GC, whereas seed regeneration increases GC and, therefore, gap dynamics are characterized by shifts between either side of the GC = 0.5 threshold. In even-sized stands, GC decreases toward maturity owing to self-thinning occurring at the stem exclusion stage. In uneven-sized stands, the skewness of the Lorenz curve indicates understory development, as ingrowth decreases LA. The possible applications of the resulting FST map are discussed; for instance, in identifying areas needing silvicultural treatments or evaluating forest recovery from disturbances.

Description: In trees, the change from juvenile to adult vegetative phase can last for years. In Populus tremula L., this phase change is characterized by a morphological change in leaf shape, as leaves in the seedling phase typically are sharp-tipped, while saplings and trees have round-tipped leaves. In an open-field experiment, we studied the separate and combined effects of enhanced temperature and UVB radiation on 2-year-old P. tremula plantlets undergoing phase change. The concentration of salicylates was higher in the seedling-phase plants than in tree-type plants. In contrast, the concentration of condensed tannins was higher in the tree-type plants but only under ambient temperature. Enhanced temperature increased growth of the plants and the concentration of some salicylate compounds, and it decreased concentrations of flavonoids, phenolic acids, and condensed tannins. In addition, in the seedling-phase plants, the severity of rust infections decreased and herbivore damage increased under warming. The effects of enhanced UVB radiation were weaker, as concentrations of only two flavonoid compounds increased under enhanced UVB radiation. Based on our results, climate change may have a moderate delaying effect on the physiological development of both sexes of P. tremula, which may lead to lowered performance in their normal habitat in the future.

Description: A height–diameter (HD) model for Norway spruce (Picea abies (L.) Karst.) was estimated from longitudinal data. The Korf growth curve was used as the HD curve. Firstly, HD curves for each stand at each measurement time were fitted, and the trends in the parameters of the HD curve were modeled. Secondly, the trends were included in the HD model to estimate the whole model at once. To take the hierarchy of the data into account, a mixed-model approach was used. This makes it possible to calibrate the model for a new stand at a given point in time using sample tree height(s). The heights may be from different points in time and need not be from the point in time being predicted. The trends in the parameters of the HD curve were not estimated as a function of stand age but as a function of the median diameter of basal area weighted diameter distribution (dGm). This approach was chosen because the stand ages may differ substantially among stands with similar current growth patterns. This is true especially with shade-tolerant tree species, which can regenerate and survive for several years beneath the dominant canopy layer and start rapid growth later. The growth patterns in stands with a given dGm, on the other hand, seem not to vary much. This finding indicates that the growth pattern of a stand does not depend on stand age but on mean tree size in the stand.

Description: Airborne laser scanning based forest inventories employ two major methods: individual tree detection (ITD) and the area-based statistical approach (ABSA). ITD is based on the assumption that trees are of a certain form and can be delineated using airborne laser scanning techniques, whereas ABSA is an empirical method based on the relations between area-level forest attributes and laser echo height distributions. These two methods are compared here within the same test area in terms of their usefulness for estimating mean forest stand characteristics and tree size distributions. All evaluations were performed using leave-one-out cross validation. The average errors in volume and basal area did not differ significantly between the methods. ABSA resulted in overall better accuracies when estimating the diameter and height of the basal area median tree and the number of stems, whereas ITD produced significantly biased estimates for the number of stems and the mean tree size. Tree size distributions were estimated with slightly better accuracy using ABSA. More comprehensive investigations revealed that both methods were not able to estimate forest structure (tree size distribution and spatial distribution of tree locations), which in turn, affected the estimation accuracies.

Description: This work presents applications of the linear mixed-effects model calibration to predict individual tree volumes of Eucalyptus grandis W. Hill ex Maiden plantations on first and second rotations located in different farms of the same region in São Paulo, Brazil. We started with the Schumacher and Hall equation in its linearized form to develop our mixed-effects model. Some parameters were considered as random among the different farms, and the calibration was made at the farm level using a small number of sample trees. The approach was developed for univariate models of the first rotation, which were calibrated with first- and second-rotation trees, and for bivariate models of the two rotations, which were calibrated with first-rotation trees. The results showed that the calibrated mixed model provides more reliable predictions than the fixed part of the model alone; however, the benefit is only moderate due to the rather small variation of the stem form between farms and rotations. The results indicate that the approach can reduce the measurement requirements on second-rotation crops.

Description: Undetected trees and inaccuracies in the predicted allometric relationships of tree stem attributes seriously constrain single-tree remote sensing of seminatural forests. A new approach to compensate for these error sources was developed by applying a histogram matching technique to map the transformation between the cumulative distribution functions of crown radii extracted from airborne laser scanning (ALS) data and field-measured stem diameters (dbh, outside bark measured at 1.3 m aboveground). The ALS-based crown data were corrected for the censoring effect caused by overlapping tree crowns, assuming that the forest is an outcome of a homogeneous, marked Poisson process with independent marks of the crown radii. The transformation between the cumulative distribution functions was described by a polynomial regression model. The approach was tested for the prediction of plot-level stem number (N), quadratic mean diameter (DQM), and basal area (G) in a managed boreal forest. Of the 40 plots studied, a total of 18 plots met the assumptions of the Poisson process and independent marks. In these plots, the predicted N, DQM, and G had best-case root mean squared errors of 299 stems·ha−1 (27.6%), 2.1 cm (13.1%), and 2.9 m2·ha−1 (13.0%), respectively, and the null hypothesis that the mean difference between the measured and predicted values was 0 was not rejected (p 〉 0.05). Considerably less accurate results were obtained for the plots that did not meet the assumptions. However, the goodness-of-fit of the predicted diameter distribution was especially improved compared with the single-tree remote sensing prediction, and observations realistically obtainable with ALS data showed potential to further localize the predictions. Remarkably, predictions of N showing no evidence against zero bias were derived solely based on the ALS data for the plots meeting the assumptions made, and limited training data are proposed to be adequate for predicting the stem diameter distribution, DQM, and G. Although this study was based on ALS data, we discuss the possibility of using other remotely sensed data as well. Taken together with the low requirements for field reference data, the presented approach provides interesting practical possibilities that are not typically proposed in the forest remote sensing literature.