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.
2021
Abstract
No abstract has been registered
Abstract
Background The Norwegian forest resource map (SR16) maps forest attributes by combining national forest inventory (NFI), airborne laser scanning (ALS) and other remotely sensed data. While the ALS data were acquired over a time interval of 10 years using various sensors and settings, the NFI data are continuously collected. Aims of this study were to analyze the effects of stratification on models linking remotely sensed and field data, and assess the accuracy overall and at the ALS project level. Materials and methods The model dataset consisted of 9203 NFI field plots and data from 367 ALS projects, covering 17 Mha and 2/3 of the productive forest in Norway. Mixed-effects regression models were used to account for differences among ALS projects. Two types of stratification were used to fit models: 1) stratification by the three main tree species groups spruce, pine and deciduous resulted in species-specific models that can utilize a satellite-based species map for improving predictions, and 2) stratification by species and maturity class resulted in stratum-specific models that can be used in forest management inventories where each stand regularly is visually stratified accordingly. Stratified models were compared to general models that were fit without stratifying the data. Results The species-specific models had relative root-mean-squared errors (RMSEs) of 35%, 34%, 31%, and 12% for volume, aboveground biomass, basal area, and Lorey’s height, respectively. These RMSEs were 2–7 percentage points (pp) smaller than those of general models. When validating using predicted species, RMSEs were 0–4 pp. smaller than those of general models. Models stratified by main species and maturity class further improved RMSEs compared to species-specific models by up to 1.8 pp. Using mixed-effects models over ordinary least squares models resulted in a decrease of RMSE for timber volume of 1.0–3.9 pp., depending on the main tree species. RMSEs for timber volume ranged between 19%–59% among individual ALS projects. Conclusions The stratification by tree species considerably improved models of forest structural variables. A further stratification by maturity class improved these models only moderately. The accuracy of the models utilized in SR16 were within the range reported from other ALS-based forest inventories, but local variations are apparent.
Authors
Stefano Puliti Johannes Breidenbach Johannes Schumacher Marius Hauglin Torgeir Ferdinand Klingenberg Rasmus AstrupAbstract
This study aimed at estimating total forest above-ground net change (ΔAGB; Gg) over five years (2014–2019) based on model-assisted estimation utilizing freely available satellite imagery. The study was conducted for a boreal forest area (approx. 1.4 Mha) in Norway where bi-temporal national forest inventory (NFI), Sentinel-2, and Landsat data were available. Biomass change was modelled based on a direct approach. The precision of estimates using only the NFI data in a basic expansion estimator was compared to four different alternative model-assisted estimates using 1) Sentinel-2 or Landsat data, and 2) using bi- or uni-temporal remotely sensed data. We found that spaceborne optical data improved the precision of the purely field-based estimates by a factor of up to three. The most precise estimates were found for the model-assisted estimation using bi-temporal Sentinel-2 (standard error; SE = 1.7 Gg). However, the decrease in precision when using Landsat data was small (SE = 1.92 Gg). We also found that ΔAGB could be precisely estimated when remotely sensed data were available only at the end of the monitoring period. We conclude that satellite optical data can considerably improve ΔAGB estimates, when repeated and coincident field data are available. The free availability, global coverage, frequent update, and long-term time horizon make data from programs such as Sentinel-2 and Landsat a valuable data source for consistent and durable monitoring of forest carbon dynamics.
Abstract
No abstract has been registered
Abstract
Key message Large-scale forest resource maps based on national forest inventory (NFI) data and airborne laser scanning may facilitate synergies between NFIs and forest management inventories (FMIs). A comparison of models used in such a NFI-based map and a FMI indicate that NFI-based maps can directly be used in FMIs to estimate timber volume of mature spruce forests. Context Traditionally, FMIs and NFIs have been separate activities. The increasing availability of detailed NFI-based forest resource maps provides the possibility to eliminate or reduce the need of field sample plot measurements in FMIs if their accuracy is similar. Aims We aim to (1) compare a timber volume model used in a NFI-based map and models used in a FMI, and (2) evaluate utilizing additional local sample plots in the model of the NFI-based map. Methods Accuracies of timber volume estimates using models from an existing NFI-based map and a FMI were compared at plot and stand level. Results Estimates from the NFI-based map were similar to or more accurate than the FMI. The addition of local plots to the modeling data did not clearly improve the model of the NFI-based map. Conclusion The comparison indicates that NFI-based maps can directly be used in FMIs for timber volume estimation in mature spruce stands, leading to potentially large cost savings.
Abstract
Forest harvest residue is a low-competitive biomass feedstock that is usually left to decay on site after forestry operations. Its removal and pyrolytic conversion to biochar is seen as an opportunity to reduce terrestrial CO2 emissions and mitigate climate change. The mitigation effect of biochar is, however, ultimately dependent on the availability of the biomass feedstock, thus CO2 removal of biochar needs to be assessed in relation to the capacity to supply biochar systems with biomass feedstocks over prolonged time scales, relevant for climate mitigation. In the present study we used an assembly of empirical models to forecast the effects of harvest residue removal on soil C storage and the technical capacity of biochar to mitigate national-scale emissions over the century, using Norway as a case study for boreal conditions. We estimate the mitigation potential to vary between 0.41 and 0.78 Tg CO2 equivalents yr−1, of which 79% could be attributed to increased soil C stock, and 21% to the coproduction of bioenergy. These values correspond to 9–17% of the emissions of the Norwegian agricultural sector and to 0.8–1.5% of the total national emission. This illustrates that deployment of biochar from forest harvest residues in countries with a large forestry sector, relative to economy and population size, is likely to have a relatively small contribution to national emission reduction targets but may have a large effect on agricultural emission and commitments. Strategies for biochar deployment need to consider that biochar's mitigation effect is limited by the feedstock supply which needs to be critically assessed.
Abstract
Old trees are important for biodiversity, and the process of their identification is a critical process in their conservation. However, determining the tree age by core extraction, ring counts, and eventually, cross-dating by means of dendrochronology is labor-intensive and expensive. Here we examine the alternative method of estimating determining tree age by visual characteristics for old Norway spruce and Scots pine trees. We used forest stands previously identified as “Old tree habitats” by visual criteria in Norwegian boreal forests. The efficiency of this method was tested using pairwise comparison of the age of core samples from trees within these sites, and within neighboring sites. Age regression models were constructed from morphological traits and site variables to investigate how accurately old trees can be detected. Cored trees in the Old-tree habitats were on average 41.9 years older than compared to a similar selection of trees from nearby mature forests. Several characteristics such as bark structure, stem taper and visible growth eccentricities can be used to identify old Norway spruce and Scots pine trees. Old trees were often found on less productive sites. Due to the wide range of environments included in the study, we suggest that these findings can be generalized to other parts of the boreal zone.
Abstract
Butt rot (BR) damage of a tree results from a decay caused by a pathogenic fungus. BR damages associated with Norway spruce (Picea abies [L.] Karst.) account for considerable economic losses in timber production across the northern hemisphere. While information on BR damages is critical for optimal decision-making in forest management, maps of BR damages are typically lacking in forest information systems. Timber volume damaged by BR was predicted at the stand-level in Norway using harvester information of 186,026 stems (clear-cuts), remotely sensed, and environmental data (e.g. climate and terrain characteristics). This study utilized Random Forests models with two sets of predictor variables: (1) predictor variables available after harvest (theoretical case) and (2) predictor variables available prior to harvest (mapping case). Our findings showed that forest attributes characterizing the maturity of forest, such as remote sensing-based height, harvested timber volume and quadratic mean diameter at breast height, were among the most important predictor variables. Remotely sensed predictor variables obtained from airborne laser scanning data and Sentinel-2 imagery were more important than the environmental variables. The theoretical case with a leave-stand-out cross-validation resulted in an RMSE of 11.4 m3 · ha−1 (pseudo-R2: 0.66) whereas the mapping case resulted in a pseudo-R2 of 0.60. When spatially distinct clusters of harvested forest stands were used as units in the cross-validation, the RMSE value and pseudo-R2 associated with the mapping case were 15.6 m3 · ha−1 and 0.37, respectively. The findings associated with the different cross-validation schemes indicated that the knowledge about the BR status of spatially close stands is of high importance for obtaining satisfactory error rates in the mapping of BR damages.
Authors
J. Julio Camarero Antonio Gazol Gabriel Sangüesa-Barreda Marta Vergarechea Raquel Alfaro-Sánchez Nicolas Cattaneo Sergio M. Vicente-SerranoAbstract
Background Equatorward, rear-edge tree populations are natural monitors to estimate species vulnerability to climate change. According to biogeographical theory, exposition to drought events increases with increasing aridity towards the equator and the growth of southern tree populations will be more vulnerable to drought than in central populations. However, the ecological and biogeographical margins can mismatch due to the impact of ecological factors (topography, soils) or tree-species acclimation that can blur large-scale geographical imprints in trees responses to drought making northern populations more drought limited. Methods We tested these ideas in six tree species, three angiosperms (Fagus sylvatica, Quercus robur, Quercus petraea) and three gymnosperms (Abies alba, Pinus sylvestris and Pinus uncinata) by comparing rear-edge tree populations subjected to different degrees of aridity. We used dendrochronology to compare the radial-growth patterns of these species in northern, intermediate, and southern tree populations at the continental rear edge. Results and conclusions We found marked variations in growth variability between species with coherent patterns of stronger drought signals in the tree-ring series of the southern populations of F. sylvatica, P. sylvestris, and A. alba. This was also observed in species from cool-wet sites (P. uncinata and Q. robur), despite their limited responsiveness to drought. However, in the case of Q. petraea the intermediate population showed the strongest relationship to drought. For drought-sensitive species as F. sylvatica and P. sylvestris, southern populations presented more variable growth which was enhanced by cool-wet conditions from late spring to summer. We found a trend of enhanced vulnerability to drought in these two species. The response of tree growth to drought has a marked biogeographical component characterized by increased drought sensitivity in southern populations even within the species distribution rear edge. Nevertheless, the relationship between tree growth and drought varied between species suggesting that biogeographical and ecological limits do not always overlap as in the case of Q. petraea. In widespread species showing enhanced vulnerability to drought, as F. sylvatica and P. sylvestris, increased vulnerability to climate warming in their rear edges is forecasted. Therefore, we encourage the monitoring and conservation of such marginal tree populations.
Abstract
Field-based monitoring of deer food availability and browsing on recruiting forest trees is a necessary but labour-intensive task. We explored how such estimates from a low-resolution multipurpose national forest inventory (NFI) (plot density 0.3 km−2) corresponded with estimates from local inventories that specifically and in greater detail monitor the availability of deer food and browsing intensity (LFI) (plot density 2–3 km−2). We used NFI and LFI data from 16 moose Alces alces ranges (mean area 276 ± SE 69 km2) in southern Norway. Only the height segment 30–130 cm of browsable trees could be obtained from the NFI data, while moose can browse trees from 30 to 300 cm in height. According to the LFI, the browse species did not have similar proportions of their browsable stems below 130 cm. Using only the stems from heights of 30–130 cm overestimated the availability of RAS (rowan, aspen and sallow) relative to birch (silver birch and downy birch) and Scots pine. The browsable biomass per stem of each species also varied between ranges, which introduces uncertainty to the food availability estimates that are based on stems only. Nevertheless, the NFI density of stems at 30–130 cm heights can be a useful index for species-specific comparisons of browse availability across ranges, because the variations between ranges in stem densities outweighed the biomass variations per stem. The NFI and LFI estimates of the species-specific densities of stems at 30–130 cm heights were significantly related and close to isometric (1:1), especially for RAS and pine. We did not find strong relationships between NFI and LFI in the browsing intensity (i.e. proportion of shoots that were browsed during the winter). The explained variation was only 11% (R2) for RAS (p = 0.281) and 32% for pine (p = 0.028). This was likely due to the small sample sizes of browsed trees in the NFI and methodological differences between the NFI and LFI in how browsing intensity is estimated. Conclusions Using data from national forest inventories can be an efficient but low-resolution way to monitor browse availability for deer, provided that the monitoring includes the full range of tree heights reachable for the deer (e.g., 30–300 cm for moose). It is also a prerequisite that the number of NFI plots is sufficient to cover the spatial variability of the area. Regarding browsing intensities, adjustments in both the NFI and LFI approaches are needed to make the two monitoring schemes more comparable.