We are modeling the post-fire biomass, carbon cycling recovery along a burning severity gradient. The data we used is eddy flux tower measurement from 2008 – 2012, right after the 2007 Anaktuvuk River Fire which is the large recorded tundra fire (> 1,000 km2) on the North Slope of Alaska.
The MEL model (Rastetter et al. 2012) structure. Rastetter, Edward B., Ruth D. Yanai, Robert Quinn Thomas, Matthew Vadeboncoeur, Timothy J. Fahey, Melany C. Fisk, Bonnie L. Kwiatkowski, and Steven Hamburg. In press. Recovery from Disturbance Requires Resynchronization of Ecosystem Nutrient Cycles. Ecological Applications. http://dx.doi.org/10.1890/12-0751.1
If you need some tundra picture from me, feel free to ask for. In “Slideshow of Tundra”, the slides shows a bunch of pics, awesome. Under a warming condition, after several years, it may not be looked like the same as today.
Arctic tundra is beautiful, totally natural……… I took around 2000 pictures using my Nikon D7000 with nikkor 18-200mm F3.5-5.6 VR II, Sigma 8-16mm F4.5-5.6 DC HSM and nikkor 50mm 1.4 lens. In “Current study”, the slides shows a bunch of pics, awesome.
In one of my recent studies, we modeled soil temperatures at different depths and results agree very well with ground-based measurement. This study provides useful tool to better explore the soil thermal and hydraulic change due to either fire disturbance or warming temperatures. The citation is as follows Jiang, Y., Q. Zhuang, and J. A. …
This slideshow tells you what the tundra looks like… pretty cooooooooooooooooool…….. We are modeling the post-fire biomass, carbon cycling recovery along a burning severity gradient. The data we used is eddy flux tower measurement from 2008 – 2012, right after the 2007 Anaktuvuk River Fire which is the large recorded tundra fire (> 1,000 km2) … Continue reading »
Our study largely improve the CO2 Flux simulation in current modeling effort. Will upload the detail when the paper is published. If you are interested, could also contact ahead. Continue reading »
Jiang, Y., Q. Zhuang, and J. A. O’Donnell (2012), Modeling thermal dynamics of active layer soils and near-surface permafrost using a fully coupled water and heat transport model, J. Geophys. Res., 117, D11110, doi:10.1029/2012JD017512. Thawing and freezing processes are key components in permafrost dynamics, and these processes play an important role in regulating the hydrological and carbon … Continue reading »
Jiang, Y., Q. Zhuang, S. Schaphoff, S. Sitch, A. Sokolov, D. Kicklighter, and J. Melillo (2012), Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model, Ecol. Evol., 2(3), 593–614, doi:10.1002/ece3.85. This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century … Continue reading »
This study quantitatively related fire frequency and burned size to climate variables (i.e. air temperature and precipitation) and elevation.Jiang et al. (2012) Modeling Large Fire Frequency and Burned Area in Canadian Terrestrial Ecosystems with Poisson Models, Environmental Modeling & Assessment, 17, 483-493, doi: 10.1007/s10666-012-9307-5. Large wildland fires are major disturbances that strongly influence the carbon cycling and vegetation dynamics of Canadian … Continue reading »
Jiang Y. and Q. Zhuang, Extreme value analysis of wildfires in Canadian boreal forest ecosystems, Canadian Journal of Forest Research, 2011, 41:1836-1851, 10.1139/x11-102. Large fires are a major disturbance in Canadian forests and exert significant effects on both the climate system and ecosystems. During the last century, extremely large fires accounted for the majority of Canadian burned … Continue reading »
The advantage of this paper is that it quantitatively modeled the relationship between fire frequency and burned area. It could be directly used for predicting fire return intervals with different fire size. The most important parameter in the power-law relationship could be replaced by a function of climate variables (e.g., air temperature, precipitation, soil moisture), … Continue reading »
