Morgane Merlin
Research Scientist
Abstract
Formålet med denne rapporten var å bruke matematiske modeller for å simulere utvikling i skog med alternative skogbehandlinger og sammenlikne dem med hensyn på omfang av vindskader. Vi spesifiserte fire alternativer som verdiorientert og stabilitetsorientert rotasjonsskogbruk, bledningsskogbruk og skjøtselsbelter langs kraftlinjer. Vi kjørte simuleringen på et 30 km2 område sør for Kongsvinger. Vi brukte modellene Heureka for å simulere bestandsutvikling i 5-årsperioder over 100-år, ForestGales for å beregne kritisk vindstyrke og beregnet volum vindskade ved å kombinere dette med frekvensfordeling for vindstyrke i området. Simuleringene gav en tydelig rangering av skogbehandlingsalternativene. Bledning gav 4,5 ganger mer skadevolum enn verdiorientert skogbehandling som igjen gav tre ganger mer enn stabilitetsorientert. Langs kraftlinjene ble vindskader omtrent eliminert ved å ha skjøtselsbelter med ekstra lav utgangstetthet og sluttavvirkning ved 18 m høyde. Ved å også se på volumproduksjon i sammenlikningene ble rangeringen lite endret. Bledning gav lavest volumproduksjon og verdiorientert skogbehandling gav kun 4% høyere produksjon enn en stabilitetsorientert. Vi konkluderer med at bledning fører til mer vindskader enn rotasjonsskogbruk, og at vi i rotasjonsskogbruk kan redusere skadeomfanget med lav utgangstetthet, ingen tynning og kort omløpstid. Langs kraftledninger kan vindskader nesten elimineres ved å gå enda lenger i samme retning.
Abstract
Tree falls along linear infrastructures and in particular powerlines pose a significant economic, safety and environmental challenge for the companies and institutions managing these infrastructures. The quick progression and affordability of remote sensing technologies such as drone-based inventories offers the opportunity to quickly and efficiently map individual trees along these infrastructures, enabling precise vegetation management to reduce risks. Here, we show how the hybrid empirical and mechanistic wind risk model ForestGALES can be applied to assess the vulnerability of individual trees to windfalls along selected powerlines in southern Norway. The validation dataset contained 180 recorded individual tree falls along powerlines from the winter 2020–2021. There was no major wind event recorded that winter. However, still, the ForestGALES model performed adequately, with an AUC (area under the curve) of 0.67. Combining the vulnerability index from ForestGALES with all other available tree and environmental variables in a machine learning model (extreme gradient boost algorithm) did however significantly improve the prediction performance. These results highlight how a combination of high-quality remote sensing data at the individual tree level can be utilized with ForestGALES and machine learning to provide managers with high-resolution vulnerability information for vegetation management.
Abstract
Forest transpiration is often quantified by scaling up stem sap flow measured on a few trees within a stand. This procedure carries uncertainty related to the (ill)representativeness of the sampled trees for the entire stand, often comprising several thousand transpiring trees. Here, we explored the uncertainty reduction potential afforded by increasing the number of sampled trees within the stand – not by costly sap flow monitoring equipment – but by point dendrometers measuring sub-daily fluctuations in stem radii which partially correlate with xylem water movement (i.e., sap flow). Using measurements collected in a forest dominated by even-aged spruce trees over two growing seasons, we built an empirical model for estimating hourly sap flow from individual trees equipped with point dendrometers, then applied it to estimate the daily transpiration of the stand both with and without trees equipped with point dendrometers. We found that the expanded tree sample size reduced the uncertainty of the stand-level estimate by 31–37 %, suggesting that the benefit afforded by increasing the stand representativeness outweighed the cost of introducing modeling error. Given their relative simplicity and affordability, we encourage additional investigations into the use of point dendrometers for studying tree water relations and water consumption patterns of entire forested stands.
Division of Biotechnology and Plant Health
FORESIGHT: Forest opportunities, risks and ecosystem services in a changing climate in Norway
Forest ecosystems are increasingly under pressure from climate change, emerging pests and pathogens, and more frequent extreme weather events. When such disturbances occur simultaneously—or interact with one another—the risk of severe damage can increase substantially. The FORESIGHT project aims to understand these complex, interacting challenges and to translate this knowledge into practical applications.
Division of Forest and Forest Resources
PathFinder - Towards an Integrated Consistent European LULUCF Monitoring and Policy Pathway Assessment Framework
Division of Environment and Natural Resources
Precilience: Precision climate resilience for agriculture and forestry sectors in the European boreal regions
Precilience will develop precision solutions with farmers, foresters, landowners, and other actors to increase climate resilience in the Nordic-Baltic regions of Denmark, Estonia, Finland, Norway and Sweden.