Modeling leaf phenology variation by groupings of species within and across ecosystems in northern Alaska
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 and 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 a regional to global scale typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observational data 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 ecotonal 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. This implementation improves the timing of the onset of carbon uptake in the spring, permitting a more accurate assessment of the contribution of each grouping of species to ecosystem performance. Furthermore, this implementation provides a more nuanced perspective on light competition among species and across ecosystems. For example, in the shrub tundra, the sedges and grasses leaf-out before the shade-inducing willow and dwarf birch, thereby providing the sedges and grasses time to accumulate biomass before shading effects arise. Also in the shrub tundra, the forbs leaf-out last, and are therefore, more prone to shading impacts by the taller willow and dwarf birch shrubs. However, in the wet sedge and heath tundra ecosystems, the forbs leaf-out before the shrubs, and are therefore less prone to shading impacts early in the growing season. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape. These findings also demonstrate that high-latitude dynamic vegetation models should consider variation in leaf-out by groupings of species within and across ecosystems in order to provide more accurate projections of future plant distributions in Arctic regions.
- Publication:
-
AGU Fall Meeting Abstracts
- Pub Date:
- December 2012
- Bibcode:
- 2012AGUFM.B11C0453E
- Keywords:
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- 0429 BIOGEOSCIENCES / Climate dynamics;
- 0438 BIOGEOSCIENCES / Diel;
- seasonal;
- and annual cycles;
- 0476 BIOGEOSCIENCES / Plant ecology;
- 0718 CRYOSPHERE / Tundra