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

Abstract

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 AE 0.2 to 2.5 AE 0.2 m (means AE 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.

Airborne laser scanning reveals uniform responses of forest structure to moose (Alces alces) across the boreal forest biome

“…The ALS data available to us were at relatively low point densities (≤5 points m 2 ) in contrast to what can be achieved using bespoke collected data (either from airborne or terrestrial‐based LIDAR scanning). However, the available data were clearly at high enough resolution to detect moose impacts on forest canopies, and a previous study has highlighted the similarity between ALS and field data in assessing moose effects on forest canopies (Kolstad et al, 2021; Snøan, 2019). We used externally calibrated models to estimate AGB from ALS metrics.…”

“…AGB was predicted for each plot using equations specific to the location, forest type and stand age of the site. For all Fennoscandian sites, the equation for AGB1999 from (Økseter et al, 2015) was used (accounting for the correction to a typographical error as reported by Kolstad et al (2021)). For the sites in Canada and the USA, equations from Boudreau et al (2008) were used, depending on forest type.…”

“…Both digital terrain and vegetation models can then be created from ALS data, with the top‐level returns representing the upper canopy of the vegetation, and various indices relevant to forest ecology can be estimated from the returned point clouds (Maltamo et al, 2014). ALS can detect moose browsing impacts in boreal forests (Melin et al, 2016) and has been used to investigate the impact of moose on forest structure within experimental exclosures at a regional scale (Kolstad et al, 2021). For analysing experimental exclosures, ALS has the advantage of synthesising responses across whole plots and the entire canopy, in contrast to field data, which are often collected in small subplots or at the stem level.…”

Net Climate Effects of Moose Browsing in Early Successional Boreal Forests by Integrating Carbon and Albedo Dynamics

“…The data set also included detailed measurements of diameter‐at‐ground‐level (mm) and height (cm) for trees at Trøndelag sites in 2016. We chose to exclude trees greater than 6 m in height, as these were likely retained at the harvest (Kolstad et al., 2022). We then used allometric biomass models to estimate aboveground tree biomass for each tree in the long‐term data set.…”