Abstract Process-based models of tree-ring width are used both for reconstructing past climates and for projecting changes in growth due to climate change. Since soil moisture observations are unavailable at appropriate spatial and temporal scales, these models generally rely on simple water budgets driven in part by temperature-based potential evapotranspiration (PET) estimates, but the choice of PET model could have large effects on simulated soil moisture, moisture stress, and radial growth. Here, I use four different PET models to drive the VS-Lite model and evaluate the extent to which they differ in both their ability to replicate observed growth variability and their simulated responses to projected 21st century warming. Across more than 1200 tree-ring width chronologies in the conterminous United States, there were no significant differences among the four PET models in their ability to replicate observed radial growth, but the models differed in their responses to 21st century warming. The temperature-driven empirical PET models (Thornthwaite and Hargreaves) simulated much larger warming-induced increases in PET and decreases in soil moisture than the more physically realistic PET models (Priestley–Taylor and Penman–Monteith). In cooler and more mesic regions with relatively minimal moisture constraints to growth, the models simulated similarly small reductions in growth with increased warming. However, in dry regions, the Thornthwaite- and Hargreaves-driven VS-Lite models simulated an increase in moisture stress roughly double that of the Priestley–Taylor and Penman–Monteith models, which also translated to larger simulated declines in radial growth under warming. While the lack of difference in the models’ ability to replicate observed radial growth variability is an encouraging sign for some applications (e.g. attributing changes in growth to specific climatic drivers), the large differences in model responses to warming suggest that caution is needed when applying the temperature-driven PET models to climatic conditions with large trends in temperature.
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Delineating Environmental Stresses to Primary Production of U.S. Forests From Tree Rings: Effects of Climate Seasonality, Soil, and Topography
Primary production is the entry point of energy and carbon into ecosystems, but modeling responses of primary production to “environmental stress” (i.e., reductions of primary production from nonoptimal environmental conditions) remains a key challenge and source of uncertainty in our understanding of Earth's carbon cycle. Here we develop an approach for estimating annual “environmental stress” from tree rings based on the proportion of the optimal diameter growth rate (from species‐specific allometric equations) that is realized in a given year. We assessed climatic, topographic, and soil drivers of environmental stress, as well as their interactions, using both empirical model experiments and linear mixed effect models. Climate gradients and interannual climate variability dominated spatial and temporal variability of environmental stress in much of the western United States, where the tree‐ring environmental stress index was positively correlated with antecedent climatic water balance (precipitation minus potential evapotranspiration) and negatively correlated with temperature and vapor pressure deficit. Excluding topographic and soil information from empirical models reduced their ability to capture spatial gradients in environmental stress, particularly in the eastern United States, where growth was not as strongly limited by climate. Mean climate conditions and topographic characteristics had significant interaction effects with the climatic water balance, indicating an increasing importance of winter moisture for warmer and drier sites and as elevation and topographic wetness index increased. These results suggest that including effects of antecedent climate (particularly in dry regions) and site topographic and soil characteristics could improve parameterization of environmental stress effects in primary production models.
more » « less- Award ID(s):
- 1832210
- NSF-PAR ID:
- 10457678
- Publisher / Repository:
- DOI PREFIX: 10.1029
- Date Published:
- Journal Name:
- Journal of Geophysical Research: Biogeosciences
- Volume:
- 125
- Issue:
- 2
- ISSN:
- 2169-8953
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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