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Simulating Impacts of Ice Storms on Forest Ecosystems
Published on: June 30, 2020
7.3K
Pervasive shifts in forest dynamics in a changing world.
Nate G McDowell1, Craig D Allen2, Kristina Anderson-Teixeira3,4
1Pacific Northwest National Laboratory, Richland, WA 99354, USA. nate.mcdowell@pnnl.gov.
Science (New York, N.Y.)
|May 30, 2020
Summary
Forest dynamics are shifting due to climate change and land use, leading to younger forests. New Earth system models and remote sensing data offer improved understanding of these vegetation changes.
Area of Science:
- Forest Ecology
- Global Change Biology
- Earth System Science
Background:
- Forest dynamics are driven by environmental factors, disturbances, and demographic processes.
- Global changes in climate and land use are altering historical forest disturbance and recovery patterns.
- These shifts are leading to forests with younger age structures and reduced height.
Purpose of the Study:
- To investigate the impact of changing environmental drivers, land use, and disturbance regimes on forest dynamics.
- To explore the influence of rising carbon dioxide, acclimation, adaptation, and migration on forest responses.
- To assess how advancements in Earth system models and remote sensing can enhance our understanding of vegetation changes.
Main Methods:
- Utilizing advanced Earth system models for vegetation dynamics simulation.
- Leveraging emerging remote sensing datasets for vegetation structure analysis.
- Integrating data to study forest demographics and disturbance processes.
Main Results:
- Identified a trend towards younger, shorter forest stands globally.
- Recognized the complex interplay of environmental drivers, land use, and disturbances.
- Highlighted the potential of novel data and models to reveal underlying mechanisms.
Conclusions:
- Forest dynamics are undergoing significant shifts due to anthropogenic global change.
- Integrated modeling and remote sensing approaches are crucial for understanding these complex changes.
- Future research should focus on combining these tools to improve predictions of forest responses.
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