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Early spring onset increases carbon uptake more than late fall senescence: modeling future phenological change in a US northern deciduous forest.
Teets, Aaron; Bailey, Amey S; Hufkens, Koen; Ollinger, Scott; Schädel, Christina; Seyednasrollah, Bijan; Richardson, Andrew D.
Afiliação
  • Teets A; Center for Ecosystem Science and Society (ECOSS), Northern Arizona University, Flagstaff, AZ, USA. aft49@nau.edu.
  • Bailey AS; Department of Biological Sciences, Northern Arizona University, Flagstaff, AZ, USA. aft49@nau.edu.
  • Hufkens K; USDA Forest Service, Northern Research Station, Durham, NH, USA.
  • Ollinger S; BlueGreen Labs, Melsele, Belgium.
  • Schädel C; Earth Systems Research Center, University of New Hampshire, Durham, NH, USA.
  • Seyednasrollah B; Center for Ecosystem Science and Society (ECOSS), Northern Arizona University, Flagstaff, AZ, USA.
  • Richardson AD; School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University, Flagstaff, AZ, USA.
Oecologia ; 201(1): 241-257, 2023 Jan.
Article em En | MEDLINE | ID: mdl-36525137
ABSTRACT
In deciduous forests, spring leaf development and fall leaf senescence regulate the timing and duration of photosynthesis and transpiration. Being able to model these dates is therefore critical to accurately representing ecosystem processes in biogeochemical models. Despite this, there has been relatively little effort to improve internal phenology predictions in widely used biogeochemical models. Here, we optimized the phenology algorithms in a regionally developed biogeochemical model (PnET-CN) using phenology data from eight mid-latitude PhenoCam sites in eastern North America. We then performed a sensitivity analysis to determine how the optimization affected future predictions of carbon, water, and nitrogen cycling at Bartlett Experimental Forest, New Hampshire. Compared to the original PnET-CN phenology models, our new spring and fall models resulted in shorter season lengths and more abrupt transitions that were more representative of observations. The new phenology models affected daily estimates and interannual variability of modeled carbon exchange, but they did not have a large influence on the magnitude or long-term trends of annual totals. Under future climate projections, our new phenology models predict larger shifts in season length in the fall (1.1-3.2 days decade-1) compared to the spring (0.9-1.5 days decade-1). However, for every day the season was longer, spring had twice the effect on annual carbon and water exchange totals compared to the fall. These findings highlight the importance of accurately modeling season length for future projections of carbon and water cycling.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tumores Neuroectodérmicos Primitivos / Ecossistema Tipo de estudo: Prognostic_studies Idioma: En Revista: Oecologia Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Tumores Neuroectodérmicos Primitivos / Ecossistema Tipo de estudo: Prognostic_studies Idioma: En Revista: Oecologia Ano de publicação: 2023 Tipo de documento: Article País de afiliação: Estados Unidos