Mark Johnston Saskatchewan Research Council johnston@src.sk.ca Energy Managers Task Force 12 January 2012 1
Carbon sequestration in Saskatchewan forests How much is there? What factors determine the amount? How does it change over time and why? Can it be enhanced through human activity? 2
Why forests? The following slide is based on the Global Carbon Project s annual update on the global carbon cycle Released December 05 2011 http://www.globalcarbonproject.org/ Highly recommended! 3
Fate of Anthropogenic CO 2 Emissions (2010) 9.1±0.5 PgC y -1 5.0±0.2 PgC y -1 50% 2.6±1.0 PgC + y-1 0.9±0.7 PgC y 26% -1 Calculated as the residual of all other flux components 24% 2.4±0.5 PgC y -1 Average of 5 models Global Carbon Project 2010; Updated from Le Quéré et al. 2009, Nature Geoscience; Canadell et al. 2007, PNAS
100 90 Emissions from Industrial Sources and Forest Fires in Saskatchewan 1990 2008 (2010) Source: Industrial Canada's National GHG Inventory Report, 2010 Source: Forest fires National Forestry Database Program, 2011 80 70 Industrial Emissions 2010 Emissions (Mt CO 2 eq) 60 50 40 1995 Fires 30 20 10 0 1985 1990 1995 2000 2005 2010 2015 Year 5
Federal Government s Risk Analysis Used to support decision making under the Kyoto Protocol Annex I countries had options to include forest management (and other activities) in their GHG reporting Canada (Fed Prov) carried out a highly sophisticated risk analysis based on forest carbon budget modeling at the provincial and national level (2001 2006) Used Monte Carlo analysis to generate a distribution of outcomes probability based decision making Will give an overview of the analysis with updated information 6
Silly question: What is a forest? Risk analysis recognized several categories of forest land based on the extent of human intervention (i.e. management): 1. Area of forest contributing to AAC 2. Area where additional harvesting could occur 3. Area subject to fire and insect management 4. Area of protected forest provincial parks etc. Area of forest outside of these areas not considered 7
FMS 1 6.4 Mha FMS 2 1.5 Mha FMS 3 4.9 Mha FMS 4 0.55 Mha Source: Canadian Forest Service, SK Risk Analysis, 2005 8
Background: Probabilistic risk assessment during CP Probability Probability Insects Probability Probability Fire Area Disturbed Area Disturbed Area Disturbed Area Disturbed Probability Probability Source Sink Net C Stock Change Net C-stock Change 9
3.50E+06 Annual area burned (ha) 3.00E+06 2.50E+06 2.00E+06 1.50E+06 1.00E+06 5.00E+05 Median Max 0.00E+00 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 Year 10
Characteristics of Insect Outbreaks Stochastic Parameters 1. Interval between the end of one outbreak and the start of the next 2. Outbreak Length 3. Area of outbreak 4. Temporal dynamics of the outbreak (shape). Area 1 Outbreak Interval 3 Total Area 2 Outbreak Length Time 11
Insects Included both mortality and loss of growth Three main pests of SK forests: Forest Tent Caterpillar Spruce Budworm Jack Pine Budworm Analysis could now be redone with Mountain Pine Beetle scenarios! 12
Forest tent caterpillar 1.20E+07 Area infested (ha) 1.00E+07 8.00E+06 6.00E+06 4.00E+06 2.00E+06 min median max 0.00E+00 1930 1940 1950 1960 1970 1980 1990 2000 2010 2020 2030 2040 Year 13
184 growth curves represented growth rates for various forest types, e.g.: CanFI Chronosequence Growth Curve Example: Manitoba Boreal Shield fully-stocked pine on site quality 12.5 Merchantable Volume (m3/ha) 150 140 130 120 110 100 90 80 70 60 50 40 30 20 10 0 softwood hardwood 0 10 20 30 40 50 60 70 80 90 100 110 120 130 140 150 160 170 180 190 200 Stand Age (years) 14
Harvest 45,000 Area (ha) 40,000 35,000 30,000 25,000 min max mean median 20,000 2000 2010 2020 2030 2040 Year 15
Scenario 1 Carbon stock estimates Forest Management Scenario 1 Year 1990 Dead Area Biomass Org. Matter Ecosystem Stratum (Mha) (Mt C) (Mt C) (Mt C) Boreal Shield 1.02 60 240 300 Boreal Plains 5.39 321 1 211 1 532 Prairies 0 0 0 0 Total 6.41 381 1 451 1 832 16
Scenario 1 Carbon stock dynamics Monte Carlo runs with highest or lowest total carbon in 2032 FM Scenario 1 1.9 1.85 Run 33 Run 76 Carbon stock (Gt) 1.8 1.75 1.7 1.65 1.6 1.55 1990 1995 2000 2005 2010 2015 2020 2025 2030 2035 Year 17
Scenario 1 2008 2012 Distribution of Total Ecosystem Flux among MC runs South of the Churchill North of the Churchill 18
Provincial 2008 2012 Total ecosystem flux 30 25 Scenario 1: 96% probability of being a source during CP 1 Source Sink Frequency 20 15 10 5 0-14 -13-12 -11-10 -9-8 -7-6 -5-4 -3-2 -1 0 1 MtCarbon per year (numbers indicate top of class) 19
Provincial 2008 2012 Total ecosystem flux Source Sink 12 Scenario 3: 66% probability of being a source during CP 1 10 Frequency 8 6 4 2 0-19 -18-17 -16-15 -14-13 -12-11 -10-9 -8-7 -6-5 -4-3 -2-1 0 1 2 3 4 Mt Carbon per year (numbers indicate top of class) 20
Conclusions The net carbon balance of Saskatchewan will be strongly affected by annual disturbance rates and the defined monitoring area. The probability distribution of the 2008 2012 net C balance is asymmetrical, with a risk of between 66 and 96% that the provincial forest will be a carbon source in the future. This analysis ignores the impacts of climate change, which are likely to increase the frequency and intensity of insect outbreaks and fires. 21
Enhancing sequestration Reducing impacts of disturbance Fire suppression, insect control Cost, environmental impacts? Forest management practices Improved planting stock, GM trees, stand management Social license? Afforestation with fast growing species High C accumulation rates up to 10 times natural forest Role in SK economy forest products, bioenergy Social license, economic viability? 22