Literature DB >> 24105949

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf-out times across groupings of species in a dynamic vegetation model.

Eugénie S Euskirchen1, Tobey B Carman, A David McGuire.   

Abstract

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970-2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf-out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf-out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.
© 2013 John Wiley & Sons Ltd.

Entities:  

Keywords:  Arctic tundra; carbon cycling; dynamic vegetation model; ecosystem composition; ecotonal boreal forest; leaf phenology

Mesh:

Year:  2014        PMID: 24105949     DOI: 10.1111/gcb.12392

Source DB:  PubMed          Journal:  Glob Chang Biol        ISSN: 1354-1013            Impact factor:   10.863


  9 in total

1.  Estimating the onset of spring from a complex phenology database: trade-offs across geographic scales.

Authors:  Katharine L Gerst; Jherime L Kellermann; Carolyn A F Enquist; Alyssa H Rosemartin; Ellen G Denny
Journal:  Int J Biometeorol       Date:  2015-08-11       Impact factor: 3.787

Review 2.  Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems.

Authors:  Stan D Wullschleger; Howard E Epstein; Elgene O Box; Eugénie S Euskirchen; Santonu Goswami; Colleen M Iversen; Jens Kattge; Richard J Norby; Peter M van Bodegom; Xiaofeng Xu
Journal:  Ann Bot       Date:  2014-05-02       Impact factor: 4.357

3.  Standardized phenology monitoring methods to track plant and animal activity for science and resource management applications.

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Journal:  Int J Biometeorol       Date:  2014-01-25       Impact factor: 3.787

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6.  Advancing the match-mismatch framework for large herbivores in the Arctic: Evaluating the evidence for a trophic mismatch in caribou.

Authors:  David Gustine; Perry Barboza; Layne Adams; Brad Griffith; Raymond Cameron; Kenneth Whitten
Journal:  PLoS One       Date:  2017-02-23       Impact factor: 3.240

7.  Prediction of Arctic plant phenological sensitivity to climate change from historical records.

Authors:  Zoe A Panchen; Root Gorelick
Journal:  Ecol Evol       Date:  2017-02-01       Impact factor: 2.912

8.  Phylogeography and ecological niche modeling unravel the evolutionary history of the Yarkand hare, Lepus yarkandensis (Mammalia: Leporidae), through the Quaternary.

Authors:  Brawin Kumar; Jilong Cheng; Deyan Ge; Lin Xia; Qisen Yang
Journal:  BMC Evol Biol       Date:  2019-06-01       Impact factor: 3.260

9.  Assessing dynamic vegetation model parameter uncertainty across Alaskan arctic tundra plant communities.

Authors:  Eugénie S Euskirchen; Shawn P Serbin; Tobey B Carman; Jennifer M Fraterrigo; Hélène Genet; Colleen M Iversen; Verity Salmon; A David McGuire
Journal:  Ecol Appl       Date:  2021-12-13       Impact factor: 6.105

  9 in total

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