Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Authors

Institutions

Publication Details

Journal
Earth s Future
Published
2024-08-01
DOI
https://doi.org/10.1029/2024ef004563
Citations
5
Primary Topic
Climate change and permafrost
Type
article
Field-Weighted Citation Impact
1.88

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Verity Salmon, Jennifer A. Holm, Margaret S. Torn, Yanlan Liu et al.
5 citations
Earth s Future
Climate change and permafrost
1.88
article

Large Divergence of Projected High Latitude Vegetation Composition and Productivity Due To Functional Trait Uncertainty

Verity Salmon, Jennifer A. Holm, Margaret S. Torn, Yanlan Liu, Alistair Rogers, Charles D. Koven
article en
5 citations

Abstract

Abstract Vegetation distribution and composition are expected to change in northern high latitudes under rapid warming, which regulates ecosystem functions but remains challenging to predict. Vegetation change arises from the interplay of chronic climate trends such as warming and transient demographic processes of recruitment, growth, competition, and mortality. Most predictive models overlooked the role of demographic dynamics controlled by plant traits. Here, we simulate vegetation dynamics at the Kougarok Hillslope site in Alaska under historical and future climates using the E3SM Land Model coupled to the Functionally Assembled Terrestrial Simulator (ELM‐FATES). To evaluate the roles of plant traits, we parameterize the model with 5,265 trait configurations representing diverse physiological and demographic strategies. Results show current modeled biomass, composition, and productivity are most sensitive to traits controlling photosynthetic capacity, carbon allocation, allometry, and phenology. Among all trait configurations, ∼5% reproduce in situ biomass and plant functional type (PFT) composition measured in 2016, that are indistinguishable from these two observed ecosystem states. Notably, these same trait configurations produce diverging biomass, composition, and productivity under future climate, where the uncertainty attributable to traits is twice the change attributable to climate change. The variation of projected productivity arises from emerging PFT composition under novel climate regimes, primarily explained by traits controlling cold‐induced mortality, recruitment, and allometry. Our findings highlight the importance and uncertainty of demographic dynamics and its interaction with climate change in shaping Arctic vegetation change. Improved model predictions will likely benefit from explicit consideration of vegetation demography and better constraints of critical traits.

Earth s FutureVol. 12(8)
Oak Ridge National Laboratory (US), Lawrence Berkeley National Laboratory (US), Brookhaven National Laboratory (US), The Ohio State University (US)
National Science Foundation, U.S. Department of Energy, National Aeronautics and Space Administration, Nuclear Safety and Security Commission, Office of Science, Biological and Environmental Research, Brookhaven National Laboratory, Lawrence Berkeley National Laboratory
Climate action
Openalex Percentile: Top 16%
Climate change and permafrost
1.88
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.