NGEE Arctic
Next-Generation Ecosystem Experiments
Advancing the predictive power of Earth system models through understanding
of the structure and function of Arctic terrestrial ecosystems
Publications
] "Evaluation of an untargeted nano-liquid chromatography-mass spectrometry approach to expand coverage of low molecular weight dissolved organic matter in Arctic soil." Scientific Reports 9, no. 1 (2019).
"Untargeted Exometabolomics Provides a Powerful Approach to Investigate Biogeochemical Hotspots with Vegetation and Polygon Type in Arctic Tundra Soils." Soil Systems 5, no. 1 (2021): 10.
"New calculations for photosynthesis measurement systems: what's the impact for physiologists and modelers?" New Phytologist 233, no. 2 (2022): 592-598.
"Arctic vegetation mapping using unsupervised training datasets and convolutional neural networks." Remote Sensing 11, no. 1 (2019): 69.
"Mapping Arctic plant functional type distributions in the Barrow Environmental Observatory using WorldView-2 and LiDAR datasets." Remote Sensing 8, no. 9 (2016): 733.
"Convolutional neural network approach for mapping Arctic vegetation using multi-sensor remote sensing fusion." 2017 IEEE International Conference on Data Mining Workshops (ICDMW) (2017): 770-778.
"Tundra landform and vegetation productivity trend maps for the Arctic Coastal Plain of northern Alaska." Scientific Data 5 (2018): 180058.
"Local-scale Arctic tundra heterogeneity affects regional-scale carbon dynamicsAbstract." Nature Communications 11, no. 1 (2020).
"Reduced arctic tundra productivity linked with landform and climate change interactions." Scientific Reports 8, no. 1 (2018).
"Polygonal tundra geomorphological change in response to warming alters future CO2 and CH4 flux on the Barrow Peninsula." Global Change Biology 21, no. 4 (2015): 1634-1651.