Biodiversity mapping of forests from above

Our goal is to develop a method to locate important biodiversity in Norwegian coniferous forests. This method should be usable for forest management to prevent loss of species and the functions they provide. In Norway, change and loss of habitats are the primary reasons for species declines. To conserve these species, we need to know where they are located. As much as 48% of Norway's threatened species are associated with forest landscapes. Most of these species are insects and fungi, which are particularly time-consuming to map with traditional surveys. We will test whether remote sensing technology can be used to map forest structures and other elements that we know are important for insect and fungal species. We also want to test whether the vegetation, based on the Norwegian Nature Mapping (NiN) system, can be used to explain the distribution of insects and fungi. The forest property of Mathiesen Eidsvold Værk (MEV) will be used as a demonstration area in the project. We will acquire new remote sensing data and use DNA analysis to identify insects and fungi from soil, dead wood, and air. The biodiversity will be monitored at 300 locations that represent large variation in biodiversity and species composition. Using remote sensing data, environmental variables and species occurrences we model wall-to-wall maps of the biodiversity at the property and compare with existing biodiversity data. We will develop an alternative forest management plan to demonstrate how the model can be incorporated into practical land management. We will also assess whether our models can be used outside the demonstration area; For this purpose we will use existing remote sensing data from other forests in Southeastern Norway and predict biodiversity where similar insect and fungal surveys have already been conducted (NCR-project EcoForest). This project involves researchers from NMBU and UiO, representatives from the forestry sector (MEV and NORSKOG), and NGOs (WWF and SABIMA).

Many species face extinction within a few decades unless actions are taken to reduce the intensity of drivers of biodiversity loss. The most important drivers of species decline worldwide are changes in land use and direct exploitation of natural resources. During the last century, the boreal forests of northern Europe have been transformed by stand based forest management for wood production, strongly affecting the forest biodiversity and associated ecosystem functions. To maintain wood production and counteract the decline of species, transformative changes in technology, economic, social and political factors are needed. In BioDivAbove, we propose an innovative concept coupling environmental predictors, including remotely sensed data, with DNA-based biodiversity surveys, to produce wall-to-wall biodiversity maps as a foundation for sustainable forest management. We will establish a demonstration area in a production forest in SE Norway, where historical forestry data are available (>70 years). Here, the forest structure will be characterized through both remote sensing and ground-based measurements of vegetation and important drivers of biodiversity, such as amount of dead wood. Using a stratified random sampling design, biodiversity data on fungi and insects will be generated from 300 plots by DNA metabarcoding analyses of air, soil and dead wood samples. We will reveal which variables are driving the forest biodiversity and establish predictive models of the spatial distribution of biodiversity. Furthermore, we will produce a wall-to-wall biodiversity-map of the property based on the prediction model and make consistent analysis of the relationships between biodiversity benefits and corresponding impacts on forest management. Alternative forest management plans will be discussed and produced for the demonstration area. The models will be validated and upscaled to 24 other forest sites distributed throughout SE Norway, where biodiversity data are available.