Ingrid Bekken Snøan’s research while affiliated with Natural History Museum, Norway and other places

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Publications (1)


Map of 45 study sites in Norway. Each point on the map corresponds to the placement of an ungulate exclosure fence and an adjacent open plot. Numbers are site ID’s and refers to Table 1.
A canopy height model for the open plot at site 9 showing the extent of the spatial data which is 32 × 32 m, the exclusion fence (20 × 20 m, corners marked with circles) and the final extent after removing a 2 m inner buffer (18 × 18 m). The green areas are remnant tree left after clear cutting, and these were removed from the ALS point cloud by cutting around the outlining polygons.
ALS canopy height distribution for an 18 × 18 m ungulate exclosure and an adjacent open area. The data comes from one of the most productive sites (site 17), where the experimental duration has been 12 years. Arrows indicate the position of the 95th percentile which is used as a measure for canopy height in this study. The figure illustrates how the foliar density (or density of points) inside large herbivore exclosures has increased in height above the ground.
Variables of interest derived from airborne laser scanning from 43 boreal forest sites in Norway which each had one 20 × 20 m ungulate exclosure and a corresponding and adjacent open plot. (A) Canopy height (defined as the 95th percentile) increased with experimental duration, and this increase was greater inside exclosures. Dotplots showing the distribution of canopy height (B) and above ground biomass (C) across the 43 study sites and the two treatments. The diamond symbol represents the mean. (D) Vertical complexity index (VCI) is higher inside exclosures and shows a diminishing positive relationship with site productivity. Regression lines are predicted values (±se) derived from averaged linear mixed effects models, with all other explanatory variables set to their mean value. Note: AGB is predicted from an external model and hence the units on the y‐axis are therefore approximate.
Results from multi‐model inference on three response variables: above ground biomass (AGB), Vertical Complexity Index (VCI) and Canopy Height. Relative variable importance (horizontal bars; left) and standardized, model averaged parameter estimates with 95% confidence intervals (right) are shown. Predictors that include ungulate exclusion are of special interest and are coloured red. The response variables are also scaled, allowing a direct comparison of effect sizes between the two models. The predictors are centered, including the categorical predictor Herbivore Exclusion, so that main effects are interpretable as their effect when all other variables are set to their mean value, and irrespective of herbivore exclusion. The numbers behind the figure are also presented in Table S1.

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Airborne laser scanning reveals increased growth and complexity of boreal forest canopies across a network of ungulate exclosures in Norway
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August 2021

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7 Citations

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Ingrid Bekken Snøan

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Large herbivores are often classed as ecosystem engineers, and when they become scarce or overabundant, this can alter ecosystem states and influence climate forcing potentials. This realization has spurred a call to integrate large herbivores in earth system models. However, we lack a good understanding of their net effects on climate forcing, including carbon and energy exchange. A possible solution to this lies in harmonizing data across the myriad of large herbivore exclosure experiments around the world. This is challenging due to differences in experimental designs and field protocols. We used airborne laser scanning (ALS) to describe the effect of herbivore removal across 43 young boreal forest stands in Norway and found that exclusion caused the canopy height to increase from 1.7 ± 0.2 to 2.5 ± 0.2 m (means ± se), and also causing a marked increase in vertical complexity and above‐ground biomass. We then go on to discuss some of the issues with using ALS; we propose ALS as an approach for studying the effects of multiple large herbivore exclosure experiments simultaneously, and producing area‐based estimates on canopy structure and forest biomass in a cheap, efficient, standardized and reproducible way. We suggest that this is a vital next step towards generating biome‐wide predictions for the effects of large herbivores on forest ecosystem structure which can both inform both local management goals and earth system models. We used airborne laser scanning to describe the effect of removing large herbivores from young boreal forests. Exclusion caused a marked increase in canopy height, vertical complexity, and above ground biomass. Our method can be extended to cover a much bigger future network of exclosure studies, which is a vital next step towards quantifying the climate forcing potential of large herbivores.

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Citations (1)


... Unfortunately, there is a lack of management tools (such as GIS layers) to differentiate between oldgrowth forests, which contain hollow-bearing trees, and logged forests, which have few remaining habitat trees [1]. Therefore, there is a clear need to develop accessible, costeffective and transferable methods to map vertical forest structure, which can be applied across a broad landscape for various applications [40]. Therefore, in this study, we aim to develop an accessible and easily replicable geospatial approach to refine habitat mapping by identifying potential hollow-bearing trees to better inform conservation outcomes for hollow-dependent species. ...

Reference:

Possibilities and Limitations of a Geospatial Approach to Refine Habitat Mapping for Greater Gliders (Petauroides spp.)
Airborne laser scanning reveals increased growth and complexity of boreal forest canopies across a network of ungulate exclosures in Norway