Publications
NIBIOs employees contribute to several hundred scientific articles and research reports every year. You can browse or search in our collection which contains references and links to these publications as well as other research and dissemination activities. The collection is continously updated with new and historical material.
2018
Abstract
Climate change could increase fire risk across most of the managed boreal forest. Decreasing this risk by increasing the proportion of broad-leaved tree species is an overlooked mitigation–adaption strategy with multiple benefits.
Abstract
No abstract has been registered
Abstract
Background: Generalized height-diameter curves based on a re-parameterized version of the Korf function for Norway spruce (Picea abies (L.) Karst.), Scots pine (Pinus sylvestris L.) and silver birch (Betula pendula Roth) in Norway are presented. The Norwegian National Forest Inventory (NFI) is used as data base for estimating the model parameters. The derived models are developed to enable spatially explicit and site sensitive tree height imputation in forest inventories as well as future tree height predictions in growth and yield scenario simulations. Methods: Generalized additive mixed models (gamm) are employed to detect and quantify potentially non-linear effects of predictor variables. In doing so the quadratic mean diameter serves as longitudinal covariate since stand age, as measured in the NFI, shows only a weak correlation with a stands developmental status in Norwegian forests. Additionally the models can be locally calibrated by predicting random effects if measured height-diameter pairs are available. Based on the model selection of non-constraint models, shape constraint additive models (scam) were fit to incorporate expert knowledge and intrinsic relationships by enforcing certain effect patterns like monotonicity. Results: Model comparisons demonstrate that the shape constraints lead to only marginal differences in statistical characteristics but ensure reasonable model predictions. Under constant constraints the developed models predict increasing tree heights with decreasing altitude, increasing soil depth and increasing competition pressure of a tree. A two-dimensional spatially structured effect of UTM-coordinates accounts for the potential effects of large scale spatially correlated covariates, which were not at our disposal. The main result of modelling the spatially structured effect is lower tree height prediction for coastal sites and with increasing latitude. The quadratic mean diameter affects both the level and the slope of the height-diameter curve and both effects are positive. Conclusions: In this investigation it is assumed that model effects in additive modelling of height-diameter curves which are unfeasible and too wiggly from an expert point of view are a result of quantitatively or qualitatively limited data bases. However, this problem can be regarded not to be specific to our investigation but more general since growth and yield data that are balanced over the whole data range with respect to all combinations of predictor variables are exceptional cases. Hence, scam may provide methodological improvements in several applications by combining the flexibility of additive models with expert knowledge.
Authors
Annika Kangas Rasmus Astrup Johannes Breidenbach Jonas Fridman Terje Gobakken Kari T. Korhonen Matti Maltamo Mats Nilsson Thomas Nord-Larsen Erik Næsset Håkan OlssonAbstract
The Nordic countries have long traditions in forest inventory and remote sensing (RS). In sample-based national forest inventories (NFIs), utilization of aerial photographs started during the 1960s, satellite images during the 1980s, laser scanning during the 2000s, and photogrammetric point clouds during the 2010s. In forest management inventories (FMI), utilization of aerial photos started during the 1940s and laser scanning during the 2000s. However, so far, RS has mostly been used for map production and research rather than for estimation of regional parameters or inference on their accuracy. In recent years, the RS technology has been developing very fast. At the same time, the needs for information are constantly increasing. New technologies have created possibilities for cost-efficient production of accurate, large area forest data sets, which also will change the way forest inventories are done in the future. In this study, we analyse the state-of-the-art both in the NFIs and FMIs in the Nordic countries. We identify the benefits and drawbacks of different RS materials and data acquisition approaches with different user perspectives. Based on the analysis, we identify the needs for further development and emerging research questions. We also discuss alternatives for ownership of the data and cost-sharing between different actors in the field.
Abstract
In the Nordic-Baltic region, there has been a growing concern about an increasing occurrence of multiple tops in young stands of Norway spruce. There is however a lack of documentation on the amount of such damages, and the causal agents involved. In two separate studies in SE Norway, we assessed the frequency of multiple tops in young sapling-sized stands, and studied the relationship between the occurrence of multiple tops and lammas growth the previous growing season on the sample trees. Study 1 included 44 planted and 10 naturally regenerated stands, while Study 2 included 68 planted stands with information on seed source. Among sample trees with multiple tops, 57% (Study 1) and 32% (Study 2) had signs of lammas growth the previous autumn, either in the form of an extended leading shoot or swollen bud. Site index as well as sample tree height were positively correlated to the occurrence of both lammas growth and multiple tops in both studies. In Study 1 we show that the probability of lammas growth was significantly higher in planted than in naturally regenerated stands. In Study 2 we show that it was higher in stands planted with seedlings grown from stand-origin seeds compared with improved seed material. Furthermore, the results of both studies show that lammas growth occurs most frequently among the dominant trees in the stand.
Authors
Jan Pisek Henning Buddenbaum Fernando Camacho Joachim Hill Jennifer L.R. Jensen Holger Lange Zhili Liu Arndt Piayda Yonghua Qu Olivier Roupsard Shawn P. Serbin Svein Solberg Oliver Sonnentag Anne Thimonier Francesco VuoloAbstract
Clumping index (CI) is a measure of foliage aggregation relative to a random distribution of leaves in space. The CI can help with estimating fractions of sunlit and shaded leaves for a given leaf area index (LAI) value. Both the CI and LAI can be obtained from global Earth Observation data from sensors such as the Moderate Resolution Imaging Spectrometer (MODIS). Here, the synergy between a MODIS-based CI and a MODIS LAI product is examined using the theory of spectral invariants, also referred to as photon recollision probability (‘p-theory’), along with raw LAI-2000/2200 Plant Canopy Analyzer data from 75 sites distributed across a range of plant functional types. The p-theory describes the probability (p-value) that a photon, having intercepted an element in the canopy, will recollide with another canopy element rather than escape the canopy. We show that empirically-based CI maps can be integrated with the MODIS LAI product. Our results indicate that it is feasible to derive approximate p-values for any location solely from Earth Observation data. This approximation is relevant for future applications of the photon recollision probability concept for global and local monitoring of vegetation using Earth Observation data.
Abstract
No abstract has been registered
Abstract
No abstract has been registered
Abstract
Productivity of a mechanized P. patula cut-to-length harvesting operation was estimated and modelled using two methods of data collection: manual time study and follow-up study using StanForD stem files. The objective of the study was to compare the productivity models derived using these two methods to test for equivalence. Manual time studies were completed on four different machines and their operators. Two Ponsse Bear harvesters fitted with H8 heads, and two Ponsse Beaver harvesters, fitted with H6 heads, were included. All machines were equipped with Ponsse Opti2 information system. All four operators had approximately 1 year of experience working with their respective machines. The four machines worked in separate four-tree-wide harvesting corridors, and they each harvested 200 trees. Individual tree diameter at breast height (DBH), and height measurements were made manually. Subsequently, data on the trees in each study were extracted from the StanForD stem reports from each of the harvesters. Cycle times in the stem reports were determined based on the difference between consecutive harvest timestamps. The two methods were compared in terms of their abilities to estimate equivalent measures for tree DBH, volume, and productivity. In all four cases, significant differences were found between the DBH and volume measures derived using the two methods. Subsequently, the volume measures from the manual methods were used as the basis for productivity calculations. Results of the productivity comparisons found no significant differences between the models developed from the two methods. These results suggest that equivalent productivity models can be developed in terms of time using either method, however volume discrepancies indicate a need to reconcile bark and volume functions with the high variability experienced in the country.
Authors
Markus Berger Stephanie Eisner Ruud van der Ent Martina Flörke Andreas Link Joseph Poligkeit Vanessa Bach Matthias FinkbeinerAbstract
Due to the increasing relevance of analyzing water consumption along product life cycles, the water accounting and vulnerability evaluation model (WAVE) has been updated and methodologically enhanced. Recent data from the atmospheric moisture tracking model WAM2-layers is used to update the basin internal evaporation recycling (BIER) ratio, which denotes atmospheric moisture recycling within drainage basins. Potential local impacts resulting from water consumption are quantified by means of the water deprivation index (WDI). Based on the hydrological model WaterGAP3, WDI is updated and methodologically refined to express a basin’s vulnerability to freshwater deprivation resulting from the relative scarcity and absolute shortage of water. Compared to the predecessor version, BIER and WDI are provided on an increased spatial and temporal (monthly) resolution. Differences compared to annual averages are relevant in semiarid and arid basins characterized by a high seasonal variation of water consumption and availability. In order to support applicability in water footprinting and life cycle assessment, BIER and WDI are combined to an integrated WAVE+ factor, which is provided on different temporal and spatial resolutions. The applicability of the WAVE+ method is proven in a case study on sugar cane, and results are compared to those obtained by other impact assessment methods.