Ecosystem aboveground structures of an open-canopy black spruce forest in interior Alaska for ecosystem modeling

• Format: Article in Journal/Newspaper
• Language: English
• Published: National Institute of Polar Research 2023
• Subjects: leaf area index; leaf mass per area; forest above ground biomass; forest census; ecosystem modelling; Arctic; Fairbanks; Japanese National Institute of Polar Research; National Institute of Polar Research; Alaska
• Online Access: http://id.nii.ac.jp/1434/00000050/; https://pdr.repo.nii.ac.jp/?action=repository_uri&item_id=65; https://pdr.repo.nii.ac.jp/?action=repository_action_common_download&item_id=65&item_no=1&attribute_id=22&file_no=1; https://pdr.repo.nii.ac.jp/?action=repository_action_common_download&item_id=65&item_no=1&attribute_id=22&file_no=2; https://pdr.repo.nii.ac.jp/?action=repository_action_common_download&item_id=65&item_no=1&attribute_id=22&file_no=3

Recent warming trends in the Arctic and boreal regions far exceed the global average, and this trend is likely to continue in the future. To establish accurate benchmarks for models and represent the current status of carbon stocks and flows, it is essential to provide detailed descriptions of forest ecosystem structures, including understory plant communities alongside carbon flux data. In this data paper, we present a synthesis data set of aboveground forest structural characteristics. Field campaigns were performed from 2010 to 2018 at the Poker Flat Research Range of the Geophysical Institute of the University of Alaska, Fairbanks, located on the outskirts of Fairbanks, AK, USA. The forest is a sparse evergreen needle-leaf forest. The field campaigns include tree census surveys in the years 2010 and 2014, direct measurement of tree aboveground biomass and their vertical profiles in 2012, tree leaf area index (LAI) measurement using a non-destructive method in 2018, and biomass and LAI survey of forest floor vegetation through direct sampling in 2018. The ecosystem structure data sets described in this paper are helpful for the calibration of the forest stand representations in the ecosystem and land surface models and for the validation of the simulated forest growth and stand structures. The data are available for download from the Japanese National Institute of Polar Research Arctic Data archive System, listed under Kobayashi et al. 2023.