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Comparing simulated tree biomass from daily, monthly, and seasonal climate input of terrestrial ecosystem model

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  • Wang, Qinying
  • He, Hong S.
  • Liu, Kai
  • Zong, Shengwei
  • Du, Haibo

Abstract

Terrestrial ecosystem models are driven by climate data, which often have daily, monthly, and seasonal resolutions, but few have examined the effects of different temporal resolutions of climate data on modeled vegetation change. In this study, we investigated the effects of daily, monthly, and seasonal climate data on simulated tree-species biomass in a temperate forest region of northeast China. We conducted the study by using the LINKAGES terrestrial ecosystem model to quantify the relative importance of climate data resolutions (daily, monthly and seasonal) and interspecific competition on predicted tree-species biomass from short-term (<40 years) to long-term (70–100 years) simulations. Results showed that simulated tree-species biomass was sensitive to daily, monthly, and seasonal climate data. The difference in the simulated biomass based on daily vs. monthly climate data was not significant for tree species monocultures, suggesting that monthly climate data can be used as a surrogate for daily climate data in such simulations. However, interspecific competition amplifies the differences in biomass simulations under daily and monthly climate data, thus increasing prediction uncertainties in mixed-species systems. Results based on climate data at the seasonal resolution showed the greatest departure from the daily and monthly climate data, because averaging climate data over a season may result in unrealistic climate estimates for modeling tree biomass growth. Simulated biomass of shade-intolerant tree species was highest when using climate data at the daily resolution, followed by monthly and seasonal climate data. The opposite pattern was true for shade-tolerant tree species. At the early stages of simulated tree growth, inter-tree competition was a more important factor affecting the biomass of late-successional, shade-tolerant tree species while different temporal resolutions of climate data were more important for early- and mid-successional species. This trend reverses at the late stages of stand development. These results can help guide choosing climate input of terrestrial ecosystem models and aiding results interpretation.

Suggested Citation

  • Wang, Qinying & He, Hong S. & Liu, Kai & Zong, Shengwei & Du, Haibo, 2023. "Comparing simulated tree biomass from daily, monthly, and seasonal climate input of terrestrial ecosystem model," Ecological Modelling, Elsevier, vol. 483(C).
    • Handle: RePEc:eee:ecomod:v:483:y:2023:i:c:s0304380023001515
    DOI: 10.1016/j.ecolmodel.2023.110420
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    References listed on IDEAS

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    1. Groemping, Ulrike, 2006. "Relative Importance for Linear Regression in R: The Package relaimpo," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 17(i01).
    2. Wang, Tao & Brender, Pierre & Ciais, Philippe & Piao, Shilong & Mahecha, Miguel D. & Chevallier, Frédéric & Reichstein, Markus & Ottlé, Catherine & Maignan, Fabienne & Arain, Altaf & Bohrer, Gil & Ces, 2012. "State-dependent errors in a land surface model across biomes inferred from eddy covariance observations on multiple timescales," Ecological Modelling, Elsevier, vol. 246(C), pages 11-25.
    3. Irauschek, Florian & Barka, Ivan & Bugmann, Harald & Courbaud, Benoit & Elkin, Che & Hlásny, Tomáš & Klopcic, Matija & Mina, Marco & Rammer, Werner & Lexer, Manfred J, 2021. "Evaluating five forest models using multi-decadal inventory data from mountain forests," Ecological Modelling, Elsevier, vol. 445(C).
    4. Chiesi, M. & Maselli, F. & Moriondo, M. & Fibbi, L. & Bindi, M. & Running, S.W., 2007. "Application of BIOME-BGC to simulate Mediterranean forest processes," Ecological Modelling, Elsevier, vol. 206(1), pages 179-190.
    5. de Bruijn, Arjan & Gustafson, Eric J. & Sturtevant, Brian R. & Foster, Jane R. & Miranda, Brian R. & Lichti, Nathanael I. & Jacobs, Douglass F., 2014. "Toward more robust projections of forest landscape dynamics under novel environmental conditions: Embedding PnET within LANDIS-II," Ecological Modelling, Elsevier, vol. 287(C), pages 44-57.
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