Enter Note Done
Go to previous page in this tab
Author/Chair
  • Bookmark Icon
  • Jonathan Wang

    University of Utah
Notes
Meeting roles in:
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change I Oral
Four-decades of annual aboveground biomass maps at 30m reveal impacts of disturbances in Arctic and Boreal North America
Predicting forest burn risk from 2026 to 2040 in interior Alaska
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change II Oral
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change III Poster
Cross-scale controls of Arctic phenology: Vegetation and local topography shape climate responses and long-term trends
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change IV Poster
Shrinking lakes, Shifting color: Long-Term Surface Reflectance Trends Linked to Lake Shrinkage in Great Basin Saline Lakes
Contemporary Arctic-boreal Zone Carbon Dioxide and Methane Flux Budgets and their Radiative Impact
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change V Oral
Meta-analysis of North American Arctic and Boreal Aboveground Carbon Maps to Provide Guidance for User Communities
The Resilience and Vulnerability of Arctic and Boreal Ecosystems to Climate Change VI Oral
Post-fire Succession in North American Boreal Forests Increases Rates of Evapotranspiration
What spatial and temporal variation should exist in a useful and effective satellite-based aboveground biomass data product? A practical guide
Developing high-resolution maps of aboveground biomass from airborne lidar to estimate the current and future contribution of non-forest ecosystems to western U.S. carbon stocks under rapid climate change
Open-Source High Resolution Biomass Benchmark Maps from Airborne Lidar with Propagated Uncertainties for Satellite Product Evaluation
Detecting Forest Mortality in Western US Forests by Monitoring Spatial and Temporal Anomalies in Land Surface Temperature
Quantifying the Controls on Boreal Forest Reburning with Interpretable Machine Learning

Sessions

Links & Materials