Modelling vegetation dynamics and carbon fluxes in a high Arctic mire

Abstract

High Arctic wetlands are an important component of the global climate system. Nevertheless estimations of their expected response to climate change and associated climate-feedbacks have large uncertainties. Improving models for vegetation and carbon dynamics of ecosystems is an important step towards making predictions more accurate.
In this study, an arctic-enabled version of the LPJ-GUESS dynamic global vegetation model (LPJ-GUESS-WHyMe) was used to conduct a local modelling study on vegetation dynamics and carbon fluxes in the high Arctic mire Rylekærene in north-western Greenland. LPJ-GUESS-WHyMe includes process descriptions of wetland hydrology, soil freezing and wetland carbon (carbon dioxide and methane) emission, as well as wetland PFTs.
The aims of this study were: 1) to assess uncertainties of parameters and process representations; 2) to assess the possibility of including grazing into the model; and 3) to lay a ground for future studies in which the response of the mire ecosystem to climate change and changes in grazing pressure can be simulated. Field data from several studies in Rylekærene were used for parameter calibration and comparison with model outputs.
The field data included carbon dioxide and methane flux chamber measurements, measurements of environmental variables and vegetation analyses. Model parameters were calibrated in the following order: 1) hydrology and permafrost; 2) vegetation; and 3) methane dynamics, using data from 2013. Data from 2011 was used for validation.
The calibration improved model performance within hydrology, permafrost and vegetation dynamics for both 2013 and 2011. For methane fluxes the calibration did not improve the model performance for 2011. Sensitivity analyses were performed for parameters related to vegetation and methane dynamics. An important finding in the sensitivity study was that increasing the fraction of vascular plant net primary production allocated to root exudates also decreased vascular plant productivity which had a net-effect of decreasing methane emissions. Main challenges for future studies were identified to be: 1) the inclusion of the effect of run-on/off from snowmelt on soil hydrology and temperature; 2) modeling competition between grasses and mosses; and 3) modeling the effect of graminoid density on methane fluxes accurately. Data from a three-year musk-ox exclosure experiment was used to build a simple module for modelling changes in grazing pressure. The results showed that improvements in the representation of model processes are needed before the effects of musk ox grazing on different parts of the ecosystem could be simulated accurately.

Popular Abstract

When hearing about “Arctic research” many people probably picture polar bears, glaciers and sledge dog expeditions. While these things are certainly a part of Arctic research there is another important part to it that affects us all: The Arctic is a key component of the global climate system. What happens in the Arctic has strong effects on how much and how fast the climate is going to change in the future.

Why is that? One reason is that Arctic soils contain a lot of carbon. It has built up from dead plants and animals for thousands of years, much of it in wetlands. When the climate gets warmer, decomposition will become faster and more carbon could be released into the atmosphere in form of greenhouse gases (mostly carbon dioxide and methane). This would further accelerate the warming. Additionally the warming happens faster in the Arctic than on the rest of our planet. In the past 30 years average temperatures in the Arctic have risen by almost 2°C, twice as much as the global average!

Earth system models – a tool to predict climate change

Many scientists all over the world are working together to predict the future rise in temperature under different greenhouse gas emission scenarios. This is a very difficult task because there are so many parts involved that work together and affect each other: The atmosphere, the oceans, soils, plants, human activity and many more. To make predictions, scientists build large and complex computer models of the earth system that include all of these components. Model simulations are then used for making reports to inform policy makers, like the IPCC reports. The models are constantly being tested and improved. Studies have shown that the role of the Arctic in the climate system is still a weak spot of earth system models.

Testing a wetland model

In my master thesis I worked with a model for wetland carbon cycling, called LPJ-GUESS-WHyMe, that could be used within an earth system model. It simulates plant growth of different kinds of plants, carbon uptake through photosynthesis and emission through respiration, hydrology and soil processes. I tested the model by comparing the results of different simulations to measurement data that was taken in a wetland in north-eastern Greenland. The measurement data included carbon dioxide and methane fluxes from the wetland, as well as information on the vegetation. As a result I found that the following components of the model should be improved as a next step to make its predictions better:
1. The model needs to take into account melt water coming from the mountains in the hydrology scheme. 2. The mechanisms of competition between grasses and mosses in the model need to be improved. 3. Grasses and sedges have a large impact on methane fluxes in wetlands. The model does take this into account, but currently underestimates the influence.

• author: Reinelt, Laura
• supervisor: Paul Miller; Lena Ström
• organization: Dept of Physical Geography and Ecosystem Science
• course: NGEM01 20151
• year: 2015
• type: H2 - Master's Degree (Two Years)
• subject: Earth and Environmental Sciences
• keywords: methane dynamics, biogeochemical cycling, vegetation dynamics, ecosystem modelling, LPJ-GUESS, geography, physical geography, high Arctic wetland, Zackenberg
• publication/series: Student thesis series INES
• report number: 358
• language: English
• id: 8081414
• date added to LUP: 2015-10-22 17:07:17
• date last changed: 2015-10-22 17:07:17