Modelling Carbon Dynamics

Model results displaying annual net primary production over boreal North America. These results were derived from a production efficiency model (PEM).

Our current research tries to explain how patterns of carbon storage and release are important to boreal forests. We do this because boreal forests are a critical component of the global ecosystem and changes in the structure of boreal forests might have critical feedbacks to the climate system. Our research takes data we collect in the field at individual points and uses it to better interpret satellite imagery that covers a much larger area. Specifically, combining field measurements of carbon exchange between the ecosystem and the atmosphere with remote sensing allows us to infer patterns of carbon sequestration in different ecosystems that have experienced different kinds of disturbance.

This part of our research improves our understanding of carbon dynamics in current forests, and gives us some idea of how forests will recover from fires and disease outbreaks. If we want to know how the patterns of carbon sequestration in boreal forests will respond to change, in climate or fire severity for instance, we need to know more about the ecological and physiological processes that control the exchange of carbon between the atmosphere and the ecosystem. We can accomplish this with predictive process-based ecosystem modeling, which is a way to simulate the response of the forests to changes to the elements that control plant growth. We use computer models that simulate the response of the forests to changes in the elements that control tree growth, like temperature and soil moisture. This “mechanistic” approach means that the forests are grown using physiological principles and calculations, rather than through statistical inference. This, in turn, allows us create future landscapes by using various projections of future climates outside the range of our current data to forecast what will happen to the carbon cycle in the coming decades.

For our research, we are using a microclimate model that takes monthly meteorological measurements from permanent weather stations and extrapolates those data to every point in our field sites on a one-kilometer map by using mathematical expressions of physical principles. In this way, the changes in climate experienced by each stand of trees can be calculated.

A forest biogeochemistry model (CARLUC) uses these microclimate calculations (such as solar radiation and precipitation) and appropriate physiological parameters (such as the fraction of photosynthetically active radiation absorbed by the forest canopy) to estimate vegetation response in terms of net primary production of biomass (carbon). CARLUC also allows us to change the type of forest we simulate (aspen versus spruce, for instance) and keeps track of changes in carbon stemming from fire or logging. We can test the model's skill at capturing boreal carbon dynamics by comparing the simulated ecosystem processes for the present conditions with our field measurements of the real ecosystem.

Schematic illustrating the effects of fire on forest state and carbon exchange in a typical boreal forest.

By running these simulations millions of times with subtle changes in the model inputs we can simulate forest ecosystem processes for many years and under many different climate scenarios. Because forecasting future climates is difficult, a huge advantage of models is that a variety of climate scenarios can be used to simulate the range of outcomes. As independent climate model estimates improve, we can use the new forecasts to identify increasingly probable changes to the carbon cycle in boreal forests.

A key advantage to ecosystem modeling is that it helps us to systematically organize our current knowledge of the ecology of boreal forests and provides us with quantitative estimates that we can test in the field. Once underlying ecological principles have been validated in the model by successful field tests, we can use a model to get a glimpse of the future and help prepare for it. Like climate change models, simulation systems of this type will be continually improved. It is clear that these models will challenge us to think more specifically about the effects of climate change on boreal forests and will be essential tools for understanding the future status and trends of carbon in the boreal regions.