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.
2023
Authors
Milan Mataruga Branislav Cvjetković Bart De Cuyper Ina Aneva Petar Zhelev Pavel Cudlín Marek Metslaid Ville Kankaanhuhta Catherine Collet Peter Annighöfer Thomas Mathes Tsakaldimi Marianthi Paitaridou Despoina Rakel J. Jónsdóttir Maria Cristina Monteverdi Giovanbattista de Dato Barbara Mariotti Dana Dina Kolevska Jelena Lazarević Inger Sundheim Fløistad Marcin Klisz Wojciech Gil Vasco Paiva Teresa Fonseca Valeriu-Norocel Nicolescu Vladan Popović Jovana Devetaković Ivan Repáč Gregor Božič Hojka Kraigher Enrique Andivia Julio J. Diez Henrik Böhlenius Magnus Löf Nebi Bilir Pedro Villar-SalvadorAbstract
The relationship between the quality of forest seedlings and their outplanting survival and growth has long been recognized. Various attributes have been proposed to measure the quality of planted seedlings in forest regeneration projects, ranging from simple morphological traits to more complex physiological and performance attributes, or a combination thereof. However, the utility and meaning of seedling quality attributes can differ significantly among regions, nursery practices, site planting conditions, species and the establishment purpose. Here, forest scientists compiled information using a common agreed questionnaire to provide a review of current practices, experiences, legislation and standards for seedling quality across 23 European countries. Large differences exist in measuring seedling quality across countries. The control of the origin of seed and vegetative material (genetic component of plant quality), and control of pests and diseases are common practices in all countries. Morphological attributes are widely used and mandatory in most cases. However, physiological attributes are hardly used at the operative level and mainly concentrated to Fennoscandia. Quality control legislation and seedling quality standards are less strict in northern European countries where seedling production is high, and quality control relies more on the agreements between producers and local plant material users. In contrast, quality standards are stricter in Southern Europe, especially in the Mediterranean countries. The control of seedling quality based on plantation and reforestation success is uncommon and depends on the conditions of the planting site, the traditional practices and the financial support provided by each country. Overall, European countries do not apply the “target seedling concept” for seedling production except for seed origin. Seedling production in many countries is still driven by traditional “know-how” and much less by scientific knowledge progress, which is not adequately disseminated and transferred to the end-users. Our review highlights the need for greater harmonization of seedling quality practices across Europe and the increased dissemination of scientific knowledge to improve seedling quality in forest regeneration activities.
Abstract
Planting healthy seedlings with optimal growth potential is essential for proper growth and survival in forest regeneration. Assessing the seedling quality prior to planting is therefore important. In this Icelandic study, effects of root damage induced with artificial freezing in young Russian larch seedlings were examined using the root growth capacity method (RGC). Frost tolerance of roots varied during the winter, and root growth in undamaged seedlings fluctuated, indicating seasonal variations in growth rhythm. The LT50 value for root frost tolerance was −13.9°C in late January, but already at −10.6°C (LT10) root damages were severe. After one growing season, shoot elongation was significantly lower in seedlings frozen to −9°C, −13.5°C, and −15.5°C by 23%, 54%, and 72%, respectively, compared with undamaged seedlings. Control seedlings and seedlings frozen to −9°C achieved 100% survival after the first growing season. Survival in seedlings frozen to −13.5°C and −15.5°C was 85% and 27%, respectively. After the second growing season, survival decreased in all frost-damaged seedlings. The ongoing mortality demonstrates the long-lasting effects of planting seedlings with damaged root systems, and the fluctuation in root frost tolerance of young Russian larch seedlings during winter emphasises the need for care when seedlings are moved to outdoor storage.
Authors
Aksel GranhusAbstract
No abstract has been registered
Authors
Sofia Junttila Jonas Ardö Zhanzhang Cai Hongxiao Jin Natascha Kljun Leif Klemedtsson Alisa Krasnova Holger Lange Anders Lindroth Meelis Mölder Steffen M. Noe Torbern Tagesson Patrik Vestin Per Weslien Lars EklundhAbstract
Northern forest ecosystems make up an important part of the global carbon cycle. Hence, monitoring local-scale gross primary production (GPP) of Northern forest is essential for understanding climatic change impacts on terrestrial carbon sequestration and for assessing and planning management practices. Here we evaluate and compare four methods for estimating GPP using Sentinel-2 data in order to improve current available GPP estimates: four empirical regression models based on either the 2-band Enhanced Vegetation Index (EVI2) or the plant phenology index (PPI), an asymptotic light response function (LRF) model, and a light-use efficiency (LUE) model using the MOD1732 algorithm. These approaches were based on remote sensing vegetation indices, air temperature (Tair), vapor pressure deficit (VPD), and photosynthetically active radiation (PAR). The models were parametrized and evaluated using in-situ data from eleven forest sites in North Europe, covering two common forest types, evergreen needleleaf forest and deciduous broadleaf forest. Most of the models gave good agreement with eddy covariance-derived GPP. The VI-based regression models performed well in evergreen needleleaf forest (R2 = 0.69–0.78, RMSE = 1.97–2.28 g C m−2 d−1, and NRMSE =9-11.0%, eight sites), whereas the LRF and MOD17 performed slightly worse (R2 = 0.65 and 0.57, RMSE = 2.49 and 2.72 g C m−2 d−1, NRMSE = 12 and 13.0%, respectively). In deciduous broadleaf forest all models, except the LRF, showed close agreements with the observed GPP (R2 = 0.75–0.80, RMSE = 2.23–2.46 g C m−2 d−1, NRMSE = 11–12%, three sites). For the LRF model, R2 = 0.57, RMSE = 3.21 g C m−2 d−1, NRMSE = 16%. The results highlighted the necessity of improved models in evergreen needleleaf forest where the LUE approach gave poorer results., The simplest regression model using only PPI performed well beside more complex models, suggesting PPI to be a process indicator directly linked with GPP. All models were able to capture the seasonal dynamics of GPP well, but underestimation of the growing season peaks were a common issue. The LRF was the only model tending to overestimate GPP. Estimation of interannual variability in cumulative GPP was less accurate than the single-year models and will need further development. In general, all models performed well on local scale and demonstrated their feasibility for upscaling GPP in northern forest ecosystems using Sentinel-2 data.
Authors
Marleen Pallandt Bernhard Ahrens Marion Schrumpf Holger Lange Sönke Zaehle Markus ReichsteinAbstract
Soil organic carbon (SOC) is the largest terrestrial carbon pool, but it is still uncertain how it will respond to climate change. Especially the fate of SOC due to concurrent changes in soil temperature and moisture is uncertain. It is generally accepted that microbially driven SOC decomposition will increase with warming, provided that sufficient soil moisture, and hence enough C substrate, is available for microbial decomposition. We use a mechanistic, microbially explicit SOC decomposition model, the Jena Soil Model (JSM), and focus on the depolymerization of litter and microbial residues by microbes. These model processes are sensitive to temperature and soil moisture content and follow reverse Michaelis-Menten kinetics. Microbial decomposition rate V of the substrate [S] is limited by the microbial biomass [B]: V = Vmax * [S] * [B]/(kMB + [B]). The maximum reaction velocity, Vmax, is temperature sensitive and follows an Arrhenius function. Also, a positive correlation between temperature and kMB-values of different enzymes has been empirically shown, with Q10 values ranging from 0.71-2.80 (Allison et al., 2018). Q10 kMB-values for microbial depolymerization of microbial residues would be low compared to those of a (lignified) litter pool. An increase in kMB leads to a lower reaction velocity (V) and V becomes less temperature sensitive at low substrate concentrations. In this work we focus on the following questions: “how do temperature and soil moisture changes affect modelled heterotrophic respiration through the Michaelis-Menten term? Is there a temperature compensation effect on modelled decomposition rate because of the counteracting temperature sensitivities of Vmax and kMB?” We model these interactions under a mean warming experiment (+3.5 °K) as well as three soil moisture experiments: constant soil moisture, a drought, and a wetting scenario.
Authors
Holger Lange Jaana Bäck Georg Jocher Natascha Kljun Anne Klosterhalfen Alexander Knohl Natalia Kowalska Adam Kristensson Corinna Rebmann Teresa Saura-Yera Alberto VilagrosaAbstract
Utilizing forest ecosystems to mitigate climate change effects and to preserve biodiversity requires detailed insights into the feedbacks between forest type, climatic and soil conditions, and in particular forest management history and practice. Analysis of long-term observations at the site level, remote sensing proxies and understanding relevant biogeochemical and biophysical processes are key to achieving these insights. In the recently started EU H2020 project “CLimate Mitigation and Bioeconomy pathways for sustainable FORESTry” (CLIMB-FOREST), we address these issues based on intensely monitored sites with flux measurements (ICOS, Fluxnet), other ecosystem research and observation networks (eLTER, National Forest Inventories), remotely sensed observations and process understanding. This presentation outlines the activities of CLIMB-FOREST regarding (1) carbon stocks and fluxes according to stand age, species distribution, management and disturbance history; (2) biophysical effects of forest structure; (3) effects and importance of short-lived climate forcers (e.g. BVOCs) and (4) management and extreme event (drought, fire) impact on SOC and N dynamics. We also outline how the gained knowledge informs scenario runs of the Vegetation and Earth System Model RCA-GUESS in the project.
Authors
Peter Zubkov Barry Gardiner Bjørn Egil Kringlebotn Nygaard Sigmund Guttu Svein Solberg Tron Haakon EidAbstract
Forest damage caused by heavy wet snow accumulation in the canopy is the second most important abiotic forest disturbance agent in Nordic conifer stands after wind. The extent and frequency of snow damage in the future climate in the Nordic region is a major uncertainty. Few mechanistic models of snow damage risk to trees exist that could support forest management scenario analysis and decision making. We propose a snow damage risk model consisting of a numerical weather prediction-based snow accumulation model for forest canopies and a mechanistic critical snow load model. Snow damage probability predictions were validated on snow breakage data from the winters of 2016 and 2018 covering 3.5 million individual trees in south-eastern Norway derived from pre- and post-damage aerial laser scanning campaigns. The proposed model demonstrated satisfactory damage and no-damage class separation with an AUC of 0.72 and 0.77 in Norway spruce and Scots pine, respectively, and an F1 score of 0.7 in conifers taller than 10 m that suffered moderate stem breakage. The model achieved a classification accuracy that is comparable to that of statistical models but is simpler and requires fewer inputs.
Abstract
We tested whether windthrow damage to Nordic conifer forest stands could be reliably detected as canopy height decrease between a pre-storm LiDAR (Light Detection and Ranging) digital surface model (DSM) and a photogrammetric DSM derived from a post-storm WorldView-3 stereo pair. The post-storm ground reference data consisted of field and unmanned aerial vehicle (UAV) observations of windthrow combined with no-damage areas collected by visual interpretation of the available very high resolution (VHR) satellite imagery. We trained and tested a thresholding model using canopy height change as the sole predictor. We undertook a two-step accuracy assessment by (1) running k-fold cross-validation on the ground reference dataset and examining the effect of the potential imperfections in the ground reference data, and (2) conducting rigorous accuracy assessment of the classified map of the study area using an extended set of VHR imagery. The thresholding model produced accurate windthrow maps in dense, productive forest stands with a sensitivity of 96%, specificity of 71%, and Matthews correlation coefficient (MCC) over 0.7. However, in sparse and high elevation stands, the classification accuracy was poor. Despite certain collection challenges during the winter months in the Nordic region, we consider VHR stereo satellite imagery to be a viable source of forest canopy height information and sufficiently accurate to map windthrow disturbance in forest stands of high to moderate density.
Abstract
Questions Observations in permanent forest vegetation plots in Norway and elsewhere indicate that complex changes have taken place over the period 1988–2020. These observations are summarised in the “climate-induced understorey change (CIUC)” hypothesis, i.e. that the understorey vegetation of old-growth boreal forests in Norway undergoes significant long-term changes and that these changes are consistent with the ongoing climate change as an important driver. Seven testable predictions were derived from the CIUC hypothesis. Location Norway. Methods Vegetation has been monitored in a total of 458 permanently marked plots, each 1 m2, in nine old-growth forest sites dominated by Picea abies at intervals of 5–8 years over the 32-year study period. For each of the 52 combinations of site and year, we obtained response variables for the abundance of single species, abundance and species density of taxonomic–ecological species groups and two size classes of cryptogams, and site species richness. All of these variables were subjected to linear regression modelling with site and year as predictors. Results Mean annual temperature, growing-season length and the number of days with precipitation were higher in the study period than in the preceding ca. 30-year period, resulting in increasingly favourable conditions for bryophyte growth. Site species richness decreased by 13% over the 32-year study period. On average, group abundance of vascular plants decreased by 24% (decrease in forbs: 38%). Patterns of group abundance change differed among cryptogam groups: although peat-moss abundance increased by 39%, the abundance of mosses, hepatics and lichens decreased by 13%, 49% and 67%, respectively. Group abundance of small cryptogams decreased by 61%, whereas a 13% increase was found for large cryptogams. Of 61 single species tested for abundance change, a significant decrease was found for 43 species, whereas a significant increase was found only for 6 species. Conclusions The major patterns of change in species richness, group species density and group abundance observed over the 32-year study period accord with most predictions from the CIUC hypothesis and are interpreted as direct and indirect responses to climate change, partly mediated through changes in the population dynamics of microtine rodents. The more favourable climate for bryophyte growth explains the observed increase for a few large bryophyte species, whereas the decrease observed for small mosses and hepatics is interpreted as an indirect amensalistic effect, brought about by shading and burial in mats of larger species and accelerated by reduced fine-scale disturbance by microtine rodents. Indirect effects of a thicker moss mat most likely drive the vascular plant decline although long-term effects of tree-stand dynamics and former logging cannot be completely ruled out. Our results suggest that the ongoing climate change has extensive, cascading effects on boreal forest ecosystems. The importance of long time-series of permanent vegetation plots for detecting and understanding the effects of climate change on boreal forests is emphasised.
Abstract
After fungal decay experiments chemical characterisation of the wood is often a routine and several methodological approaches are available. In this study, we tested if simultaneous thermal analysis (STA) is a valid alternative to traditional wet chemical methods since STA allows significantly smaller sample size and faster analysis. Three model fungi including the brown rot fungi Rhodonia placenta and Gloeophyllum trabeum and the white rot fungus Trametes versicolor were employed in the study using Norway spruce as substrate. The experiment was harvested after 10, 20 and 52 weeks. At each harvest interval, aliquots of the material were characterized by STA and wet chemical methods. The results validated that STA can be effectively used to estimate cell wall composition of brown rot depolymerised wood. However, STA slightly overestimated cellulose at brown rot decay above 50%. The method was not verified for simultaneous white rot because STA only estimated hemicellulose correctly compared to the wet chemical method. Hence, STA is considered suitable for brown rot fungi below 50% mass loss but not for simultaneous white rot because STA did not estimate cellulose and lignin correctly.