Parameter sensitivity and transferability for simulating ET and GPP of Dryland ecosystems across a climate gradient

Authors: Flerchinger, Gerald; CHU, XIAOSHENG - North American Orchid Conservation Center (NAOCC); LOHSE, KATHLEEN - Idaho State University; Clark, Pat; SEYFRIED, MARK - Retired ARS Employee

Submitted to: Ecological Modelling
Publication Type: Peer Reviewed Journal
Publication Acceptance Date: 11/30/2024
Publication Date: 12/7/2024
Citation: Flerchinger, G.N., Chu, X., Lohse, K., Clark, P., Seyfried, M. 2024. Parameter sensitivity and transferability for simulating ET and GPP of Dryland ecosystems across a climate gradient. Ecological Modelling. 501. Article 110973. https://doi.org/10.1016/j.ecolmodel.2024.110973.
DOI: https://doi.org/10.1016/j.ecolmodel.2024.110973

Interpretive Summary: Ecosystem models are important tools for predicting future trends that ecosystems may experience under the pressures of changing climate and increasing fire regimes. However, these models often struggle to reproduce seasonal patterns of plant productivity, particularly in rangeland ecosystems. Inaccurate predictions of plant productivity cause further errors in the model with respect to plant growth, forage production, carbon storage, and vegetation changes over time. In this study, we demonstrated the accuracy of the Simultaneous Heat and Water (SHAW) model for predicting plant productivity, the challenges in applying the model to different ecosystems, and methods that can be used to transfer the model to different ecosystems. This is a critical step forward in assessing future trajectories of ecosystems and the propensity of these ecosystems to release/store carbon dioxide to/from the atmosphere.

Technical Abstract: Ecohydrology models are essential tools for better understanding and quantifying water and carbon fluxes for different ecosystems and across climate gradients. Parameter uncertainty limits our ability to simulate ecosystem processes. We evaluated parameter sensitivity of the Simultaneous Heat and Water model for simulating evapotranspiration (ET) and gross primary productivity (GPP) for three sagebrush ecosystems across an elevation/climate gradient within the Reynolds Creek Critical Zone Observatory. This gradient spanned annual precipitation rates of 292 to 800 mm and GPP from 420 to 849 gC/m2. We used a Monte-Carlo approach of 10,000 to 20,000 model runs to assess the distribution of optimal parameter values for each site. Distributions of best-case values for sagebrush parameters controlling carbon uptake were similar for the Wyoming big sagebrush and mountain big sagebrush sites but differed for the low sagebrush site. Differences in sagebrush transpiration parameters were consistent with soil water regimes for these different species and subspecies. Parameter values for the herbaceous understory showed less similarity between sites, perhaps due to the varying composition of grasses and forbs. Post-optimization root mean square deviation for ET were 0.37, 0.45, and 0.51 mm/d and for GPP were 0.47, 0.48, and 0.75 gC/m2/d from lowest to highest elevation. Peak seasonal GPP was replicated by the model, with understory vegetation contributing up to 80% of peak GPP. R2 values for simulated GPP ranged from 0.78 to 0.90 for the optimization period and 0.61 to 0.89 for the validation period. A composite parameter set for each site obtained by combining parameter values whose best-case distributions did not significantly differ, resulted in no real difference in simulations. This study reveals the extent to which parameters can be transferred across ecosystems, thereby reducing parameter uncertainty, which is a critical step forward in assessing future trajectories of ecosystem carbon fluxes.