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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

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Abstract

Nordic and Canadian forests store substantial amounts of carbon (C) and are largely managed in a silvicultural system with clear-cut harvest. Previous meta-analyses of harvesting effects on soil C have shown short- to long-term declines after harvest, but effects of clear-cutting on boreal and northern temperate forest soil C stocks remain unresolved. We harmonized National Forest Soil Inventory (NFSI) data from Sweden, Denmark, Finland, Norway and Canada to examine soil C stocks up to 53 years following clear-cut harvest using a space-for-time approach. We analyzed forest floor and mineral soil C stocks in coniferous and deciduous/mixed forests. Coniferous forest floor C stocks decreased for ∼30 years after clear-cutting: when at its lowest stock level, Picea and Pinus forest floor C stocks had decreased by 23 % and 14 % relative to initial stock levels, respectively. Picea forest floor C stocks then remained close to its lowest levels until 53 years after clear-cutting, while for Pinus-dominated forests they increased again and recovered to the pre-harvest level 48 years after clear-cutting. No C stock changes were detected in the 0–10 cm or 10–20 cm mineral soil layers, while a small increase in 55–65 cm mineral soil was detected in Podzol soils. Data was too limited to detect statistical signals of clear-cutting for deciduous/mixed forests. Our results shows that clear-cut harvest has substantial and long-lasting effects on northern temperate and boreal forest soil C storage, and that combining data from several NFSIs can help elucidate forest management effects on soil C storage. Soil organic carbonForest harvestClear-cuttingBorealTemperateNational forest inventoryNational forest soil inventory

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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.