期刊
REMOTE SENSING IN ECOLOGY AND CONSERVATION
卷 8, 期 1, 页码 5-17出版社
WILEY
DOI: 10.1002/rse2.224
关键词
biomass; herbivory; large herbivores; LiDAR; moose; remote sensing
资金
- Research Council of Norway [184036, 262064]
- Norwegian Environment Agency
- County Administrations and County Governors in Trondelag, More og Romsdal, Vestland, Innlandet, Viken and Vestfold og Telemark counties
Research suggests that the exclusion of large herbivores in boreal forests can lead to an increase in canopy height, vertical complexity, and above-ground biomass. Authors propose using airborne laser scanning as a method to study the effects of multiple large herbivore exclosure experiments simultaneously.
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.
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