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.
2025
Abstract
Climatic drought and changes in precipitation patterns are key features of the ongoing and predicted climatic changes in northern latitudes such as the boreal forest of Norway. Recent droughts highlight on the possible difficult future of spruce forests in southern Norway. To better understand and monitor these forests under a more extreme climate, it is crucial to gain a better understanding of the water relations of spruce trees across forest stands. Sap flow sensors are typically used for directly measuring the water demands for transpiration in individual trees. There are however limitations to their use in examining the hydraulic and physiological responses to extreme water supply variability: i) manufactured high-resolution sensors such as those following the Heat Ratio Method (HRM) or Heat Field Deformation (HFD) are expensive, limiting their deployment to a few trees in a stand, and ii) the sap flow sensors only measure the movement of water within the active sapwood, not accessing other physiological mechanisms and responses (radial growth, water storage) associated with stress response. Point dendrometers have become increasingly used, monitoring sub-daily stem size fluctuations resulting from both seasonal patterns of radial growth increment and the dynamics of plant tissue water balance. Manufactured point dendrometers are much cheaper to buy and easier to install and maintain than manufactured sap flow sensors. They can therefore be much more extensively deployed across forest stands. We aimed to analyse the relationship between sub-daily stem diameter changes and sap flow using point dendrometers and HRM sap flow sensors installed in a Norway spruce forest located 50 km north of Oslo, Norway. We linked these relationships with individual tree physical attributes, meteorology and soil climate over two growing seasons in 2022 and 2023. Our goal was to assess whether a predictive model of sap flow could be built from measured diameter changes, tree properties and climate, to ultimately reduce the uncertainty of stand level transpiration estimation at the daily resolution across entire forest stands.
Authors
Klaus Steenberg Larsen Carl-Fredrik Johannesson Jenni Nordén Holger Lange Hanna Marika SilvennoinenAbstract
Non-steady-state chambers are widely used for measuring the exchange of greenhouse gases (GHGs) between soils or ecosystems and the atmosphere. It is known that non-steady-state chambers induce a non-linear concentration development inside the chamber after closure, even across short chamber closure periods, and that both linear and non-linear flux estimates are impacted by the chamber closure period itself. However, despite the existence of recommendations on how long to keep the chamber closed, it has been little explored to what extent the length of the chamber closure period affects the estimated flux rates, and which closure periods may provide the most accurate linear and non-linear flux estimates. In the current study, we analyzed how linear regression and Hutchinson and Mosier (1981) modeled flux estimates were affected by the length of the chamber closure period by increasing it in increments of 30 s, with a minimum and maximum chamber closure period of 60 and 300 s, respectively. Across 3,159 individual soil CO2 and CH4 flux measurements, the effect of chamber closure period length varied between 1.4–8.0% for linear regression estimates and between 0.4–17.8% for Hutchinson–Mosier estimates and the largest effect sizes were observed when the measured fluxes were high. Both linear regression and Hutchinson–Mosier based flux estimates decreased as the chamber closure period increased. This effect has been observed previously when using linear regression models, but the observed effect on Hutchinson-Mosier modeled estimates is a novel finding. We observed a clear convergence between the short-period linear regression estimates and the long-period Hutchinson–Mosier estimates, showing that closure periods as short as possible should be used for linear regression flux estimation, while ensuring long-enough closure periods to observe a stabilization of flux estimates over time when using the Hutchinson-Mosier model. Our analysis was based on soil flux measurements, but because the perturbation of the concentration gradient is related to the non-steady-state chamber technique rather than the measured ecosystem component, our results have implications for all flux measurements conducted with non-steady-state chambers. However, optimal chamber closure times may depend on individual chamber designs and analyzer setups, which suggests testing individual chamber/system designs for optimal measurement periods prior to field application
Authors
Carl-Fredrik Johannesson H. Ilvesniemi O. Janne Kjønaas K.S. Larsen A. Lehtonen Jenni Nordén D. Paré Hanna Marika Silvennoinen J. Stendahl I. Stupak L. Vesterdal Lise DalsgaardAbstract
No abstract has been registered
Abstract
Long-term monitoring of ecosystems is the only direct method to provide insights into the system dynamics on a range of timescales from the temporal resolution to the duration of the record. Time series of typical environmental variables reveal a striking diversity of trends, periodicities, and long-range correlations. Using several decades of observations of water chemistry in first-order streams of three adjacent catchments in the Harz mountains in Germany as example, we calculate metrics for these time series based on ordinal pattern statistics, e.g. permutation entropy and complexity, Fisher information, or q-complexity, and other indicators like Tarnopolski diagrams. The results are compared to those obtained for reference statistical processes, like fractional Brownian motion or ß noise. After detrending and removing significant periodicities from the time series, the distances of the residuals to the reference processes in this space of metrics serves as a classification of nonlinear dynamical behavior, and to judge whether inter-variable or rather inter-site differences are dominant. The classification can be combined with knowledge about the processes driving hydrochemistry, elucidating the connections between the variables. This can be the starting point for the next step, constructing causal networks from the multivariate dataset.
Abstract
In terrestrial ecosystems, forest stands are the primary drivers of atmospheric moisture and local climate regulation, making the quantification of transpiration (T) at the stand level both highly relevant and scientifically important. Stand-level T quantification complements evapotranspiration monitoring by eddy-covariance systems, providing valuable insight into the water use efficiency of forested ecosystems in addition to serving as important inputs for the calibration and validation of global transpiration monitoring products based on satellite observations. Stand level T estimates are typically obtained by scaling up individual tree estimates of water movement within the xylem – or sap flow. This movement affects the radius of a tree stem, whose fluctuations over the diel cycle provide pertinent information about tree water relations which can be readily detected by point (or precision) dendrometers. While sap flow measurements have greatly advanced our understanding of water consumption (T) at the level of individual trees, deploying conventional sap flow monitoring equipment to quantify T at the level of entire forested stands (or ecosystems) can quickly become costly since sap flow measurements from many trees are required to reduce the uncertainty of the upscaling. Using a boreal old-growth Norway spruce stand at an ICOS site in Southern Norway as a case study, we assess the potential of augmenting conventional sap flow monitoring systems with sap flow modeling informed by point dendrometer measurements to reduce the uncertainty of stand level T estimation at the daily resolution. We test the hypothesis that the uncertainty reduction afforded by a boosted tree sample size more than offsets the propagation of uncertainty originating from the point dendrometer-based sap flow estimates.
Abstract
No abstract has been registered
Authors
Mikolaj Lula Kjersti Holt Hanssen Martin Goude Hannu Hökkä Sauli Valkonen Andreas Brunner Pasi Rautio Charlotta Erefur Aksel GranhusAbstract
No abstract has been registered
Authors
Simone Bianchi Andreas Brunner Kjersti Holt Hanssen Hannu Hökkä Urban Nilsson Nils Fahlvik Jari HynynenAbstract
No abstract has been registered
Authors
Mekjell Meland Oddmund Frøynes Darius Kviklys Uros Gasic Uroš Gašić Tomislav Tosti Milica Fotiric AksicAbstract
No abstract has been registered
Abstract
No abstract has been registered