Helge Meissner

Overingeniør

(+47) 916 42 157
helge.meissner@nibio.no

Sted
Ås - Bygg H8

Besøksadresse
Høgskoleveien 8, 1433 Ås

Sammendrag

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.

Til dokument

Sammendrag

Forest soils harbor hyper-diverse microbial communities which fundamentally regulate carbon and nutrient cycling across the globe. Directly testing hypotheses on how microbiome diversity is linked to forest carbon storage has been difficult, due to a lack of paired data on microbiome diversity and in situ observations of forest carbon accumulation and storage. Here, we investigated the relationship between soil microbiomes and forest carbon across 238 forest inventory plots spanning 15 European countries. We show that the composition and diversity of fungal, but not bacterial, species is tightly coupled to both forest biotic conditions and a seven-fold variation in tree growth rates and biomass carbon stocks when controlling for the effects of dominant tree type, climate, and other environmental factors. This linkage is particularly strong for symbiotic endophytic and ectomycorrhizal fungi known to directly facilitate tree growth. Since tree growth rates in this system are closely and positively correlated with belowground soil carbon stocks, we conclude that fungal composition is a strong predictor of overall forest carbon storage across the European continent.

Sammendrag

Hurdal (NO-Hur) is a recently labelled ICOS class 2 station in Southeast Norway. It represents a typical southern boreal forest of medium productivity, dominated by old Norway spruce (average tree height: 25 m, ages: up to 100 years) with some pine and broadleaved trees. The eddy covariance technique is used to measure CO2 fluxes on a 42 m tower since 2021 . The measurements have an average footprint area of approximately 63 ha. In 2023, the region experienced an unusual dry spring and then an extraordinary flood in August. Both events showed significant impact on the Net Ecosystem Exchange (NEE) and heat fluxes. The station is also equipped with automatic dendrometers and sap flow devices on the dominant spruce trees, allowing us to investigate the impact of these events at the individual tree scale. We will present tree growth and transpiration flux at different temporal scales (from sub-daily to seasonal), and relate these single tree observations with environmental variables, ecosystem-level NEE and evapotranspiration using phase synchronization analysis. These observational data will yield insights into carbon and water processes of a boreal forest at different scales in response to multiple disturbances.