Climate Feedback Research: Consequences of climate and disturbance changes for the Carbon feedback in Interior Alaska Patrick Endres, AK photographics.

Slides:



Advertisements
Similar presentations
Gridded Biome-BGC Simulation with Explicit Fire-disturbance Sinkyu Kang, John Kimball, Steve W. Running Numerical Terradynamic Simulation Group, School.
Advertisements

Biospheric Process Models: The Challenge of Integrating Ecosystem Dynamics and Land Cover Change A. David McGuire USGS and University of Alaska.
Effects of Forest Thinning on CO 2 Efflux Peter Erb, Trisha Thoms, Jamie Shinn Biogeochemistry 2003: Block 1.
The Tundra Carbon Balance - some recent results with LPJ-GUESS contributions Paul Miller Ben Smith, Martin Sykes, Torben Christensen, Arnaud Heroult, Almut.
Modeling Changes in Vegetation Dynamics in Alaska: Implications for Arctic Herbivores Eugénie Euskirchen ESPSCoR All Hands Meeting, May , 2010.
The Alaska Forest Disturbance Carbon Tracking System T. Loboda, E. Kasischke, C. Huang (Univ. MD), N. French (MTRI) J. Masek, J. Collatz (GSFC), D. McGuire,
The Downscaled Climate Projection Has Arrived – NOW WHAT?
Carbon Information Needed to Support Forest Management Bob Davis, Director Of Planning, Watershed And Air, USDA Forest Service 0.
A Synthesis of Terrestrial Carbon Balance of Alaska and Projected Changes in the 21 st Century: Implications for Climate Policy and Carbon Management To.
Magnitude and Spatial Distribution of Uncertainty in Ecosystem Production and Biomass of Amazonia Caused by Vegetation Characteristics Christopher Potter.
Monitoring Effects of Interannual Variation in Climate and Fire Regime on Regional Net Ecosystem Production with Remote Sensing and Modeling D.P. Turner.
Mathias Göckede College of Forestry Oregon State University The ORCA2 West Coast Project Synthesizing multiple approaches to constrain regional scale carbon.
An Assessment of the Carbon Balance of Arctic Tundra: Comparisons among Observations, Models, and Atmospheric inversions A. David McGuire and Co-authors.
Estimating the contribution of agricultural land use to terrestrial carbon fluxes in the continental US Keith Paustian 1,2, Steven Ogle 2, Scott Denning.
Carbon Cycle and Ecosystems Important Concerns: Potential greenhouse warming (CO 2, CH 4 ) and ecosystem interactions with climate Carbon management (e.g.,
Effects of Future Warming and Fire Regime Change on Boreal Soil Organic Horizons and Permafrost Dynamics in Interior Alaska Comparison of Historical and.
TRANSFORMATION OF LARCH- DOMINATED FORESTS AND WOODLANDS INTO MIXED TAIGA E. Levine 1, H. Shugart Jr. 2, J. Ranson 1, N. Mölders 3, J. Shuman 2, R. Knox.
Increasing Wetland Emissions of Methane From A Warmer Artic: Do we See it Yet? Lori Bruhwiler and Ed Dlugokencky Earth System Research Laboratory Boulder,
Fire effects on vegetation recovery Summary of Results and Project Deliverables Jill Johnstone, Teresa Hollingsworth, Emily Bernhart & Katie Villano.
Overview of Proposed Climate Sensitivity Research.
Carbon sequestration in China’s ecosystems, Jingyun Fang Department of Ecology Peking University Feb. 14, 2008.
Global Carbon Cycle Feedbacks: From pattern to process Dave Schimel NEON inc.
References 1. Zhang F.M., J.M. Chen, Y. Pan, R. A. Birdsey, S.H. Shen, W.M Ju, and L.M. He, Attributing carbon sinks in conterminous US forests to disturbance.
Climate change, land use and forests in India: research and institutional framework in the context of the Indo-US flux programme R. Sukumar & N.H.Ravindranath.
Global Climate Impacts of Thawing Permafrost National Snow and Ice Data Center, University of Colorado Tingjun Zhang Kevin Schaefer Tim Schaefer Lin Liu.
Fires and the Contemporary Global Carbon Cycle Guido van der Werf (Free University, Amsterdam, Netherlands) In collaboration with: Jim Randerson (UCI,
STUDI Land Surface Change & Arctic Land Warming Department of Geography Jianmin Wang The Ohio State University 04/06/
Circumpolar Assessment of Organic Matter Decomposibility as a Control Over Potential Permafrost Carbon Loss Dr. Ted Schuur Department of Biology, University.
Climate Sensitivity of Boreal Forest Ecosystem Carbon Dynamics A. David McGuire and Colleagues BNZ LTER Annual Symposium 5 March 2009.
Modeling climate change impacts on forest productivity with PnET-CN Emily Peters, Kirk Wythers, Peter Reich NE Landscape Plan Update May 17, 2012.
EFIMOD – a system of models for Forest Management A.S. Komarov, A.V. Mikhailov, S.S. Bykhovets, M.V.Bobrovsky, E.V.Zubkova Institute of Physicochemical.
SOME ASPECTS OF ACCUMULATED CARBON IN FEW BRYOPHYTE- DOMINATED ECOSYSTEMS: A BRIEF MECHANISTIC OVERVIEW Mahesh Kumar SINGH Department of Botany and Plant.
Regional Ecosystem Dynamics and Climate Feedbacks A. David McGuire Ted Schuur Scott Rupp Helene Genet Eugenie Euskirchen BNZ Annual Symposium 20 February.
1. Ecological legacies are: Anything handed down from a pre-disturbance ecosystem (Perry 1994). The carry-over or memory of the system with regard to.
Summary of Research on Climate Change Feedbacks in the Arctic Erica Betts April 01, 2008.
Fire Ecology and Fire Regimes in Boreal Ecosystems Oct 19, 2010.
PERD POL Toronto Jan. 23, 2003 Estimating the effects of climate change on large scale natural disturbances, and their impact on biomass productivity.
Post-fire recovery in black spruce forests Analysis Summary October 2007 Jill Johnstone.
Nelius Foley, Matteo Sottocornola, Paul Leahy, Valerie Rondeau, Ger Kiely Hydrology, Micrometeorology and Climate Change University College Cork, IrelandEnvironmental.
How do forest ecosystems respond to environmental change?
BIOME-BGC estimates fluxes and storage of energy, water, carbon, and nitrogen for the vegetation and soil components of terrestrial ecosystems. Model algorithms.
An Assessment of the Carbon Balance of Arctic Tundra in North America: Comparisons among Observations, Models, and Atmospheric inversions A. David McGuire.
The impacts of land mosaics and human activity on ecosystem productivity Jeanette Eckert.
Translation to the New TCO Panel Beverly Law Prof. Global Change Forest Science Science Chair, AmeriFlux Network Oregon State University.
Scott Goetz Changes in Productivity with Climate Change at High Latitudes: the role of Disturbance.
Spatial and temporal patterns of CH 4 and N 2 O fluxes from North America as estimated by process-based ecosystem model Hanqin Tian, Xiaofeng Xu and other.
Modeling Modes of Variability in Carbon Exchange Between High Latitude Ecosystems and the Atmosphere Dave McGuire (UAF), Joy Clein (UAF), and Qianlai.
Future climate change drives increases in forest fires and summertime Organic Carbon Aerosol concentrations in the Western U.S. Dominick Spracklen, Jennifer.
Importance of Recent Shifts in Soil Thermal Dynamics on Growing Season Length, Productivity, and Carbon Sequestration in Terrestrial High-Latitude Ecosystems.
Coupling between fire and permafrost Effects of permafrost thaw on surface hydrology between better- drained vs. poorly- drained ecosystems Consequences.
Change in vegetation growth and C balance in the Tibetan Plateau
The patterns and consequences of post-fire successional trajectories in Alaska’s boreal forest The “Generators” - Fire severity - Abiotic and biotic site.
Methane in the atmosphere; direct and indirect climate effects Gunnar Myhre Cicero.
Land cover & fire at high latitudes: model-data comparison and model modification NCEO Land Science Meeting, February 2012, Sheffield, UK E.Kantzas,
Greenhouse Gas Balance of Russia GCP Regional Carbon Budgets WS Beijing, China, Nov S. Nilsson, a E.A. Vaganov, b V.A. Rozhkov, b A. Shvidenko,
Band Dendrometer, Inventory, and Litterfall Data A.D. McGuire, R.W. Ruess, J.S. Clein, J.Yarie Ecological Question What is the sensitivity of AGNPP to.
Boreal forest resilience Some initial thoughts BNZ LTER meeting, March 2009 Terry Chapin & Jill Johnstone.
Diploma thesis (Spanien – Österreich): Title of the Project: “Effect of burning of Mediterranean macchia on ecosystem nitrogen stocks and the soil-atmosphere.
Ecosystem carbon storage capacity as affected by disturbance regimes: a general theoretical model Introduction Disturbances can profoundly affect ecosystem.
Synthesis of Arctic System Carbon Cycle Research Through Model-Data Fusion Studies Using Atmospheric Inversion and Process-Based Approaches (SASS PI Meeting.
Dr. Monia Santini University of Tuscia and CMCC CMCC Annual Meeting
Resilience of Alaska’s boreal forest Terry Chapin Bonanza Creek LTER.
Impacts of Arctic Tundra Wildfires on Carbon Cycling Mack MC, Bret-Harte MS, Hollingsworth TN, Jandt RR, Schuur EAG, Shaver GR, Verbyla DL (2011) Carbon.
Whats new with MODIS NPP and GPP MODIS/VIIRS Science Team Meeting May 20, 2015 Steven W. Running Numerical Terradynamic Simulation Group College of Forestry.
What research results are policy relevant? Annette Freibauer.
Arctic RIMS & WALE (Regional, Integrated Hydrological Monitoring System & Western Arctic Linkage Experiment) John Kimball FaithAnn Heinsch Steve Running.
Carbon Sequestration Akilah Martin Fall 2005.
Continental Modeling and Analysis of the North American Carbon Cycle
OGWC – Forest C Bev Law Prof. Global Change Biology & Terrestrial Systems Science Oregon State University Oct 6, 2016.
Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.
Presentation transcript:

Climate Feedback Research: Consequences of climate and disturbance changes for the Carbon feedback in Interior Alaska Patrick Endres, AK photographics Genet H., Zhang Y., McGuire A.D., He Y., Johnson K., D’Amore D., Zhou X., Bennett A., Biles F., Bliss N., Breen A., Euskirchen E.S., Kurkowski T., Pastick N., Rupp S., Wylie B., Zhu Z., Zhuang Q.

(modified from Hayes et al. 2014) ATMOSPHERE Δ SOILC active Δ SOILC frozen Δ VEGC decomposition litterfall NPP N feedback ALT OL RH CH 4

(modified from Hayes et al. 2014) ATMOSPHERE Δ SOILC active Δ SOILC frozen Δ VEGC decomposition litterfall NPP N feedback ALT OL RH Fire emission Mortality Δ Tair CH 4

Modeling framework ALFRESCO Environmental module Ecological moduleOrganic Soil module Disturbance module OL thickness & Soil structure Atm & Soil env. LAI Fire severity Litter Fire occurrence Climate, topography Climate, Atm. CO 2 TEM logging rate MCM-TEM NPP, LAI

Environmental Drivers

Climate Drivers Mean Annual Temperature (MAT) and Annual Sum of Precipitation (ASP) from 1950 to 2100 summarized for the simulation extent. The black line represents the CRU data for the historical period and the colored lines represent the CCCMA (solid) and ECHAM5 (dotted) projections for the 3 emission scenarios.

Disturbance regimes : Fire Simulated fire scars for the historical period Individual fire scar colors indicate age of burn from oldest (red) to youngest (green). Cumulated area burned for the historical period (black line) are estimated from the Alaskan Large Fire Databases. Projections from 2009 to 2100 are simulated by ALFRESCO for the 6 climate scenarios.

Evaluate TEM performances TEM soil C stocks compared with soil C stocks based on 315 samples collected in Alaska (Johnson et al. 2011). Both simulated and observed soil C stock estimates are for the organic and 0-1m mineral horizons. Evaluation of TEM for vegetation biomass using data from 190 permanent study plots of the Cooperative Alaska Forest Inventory (CAFI) for boreal forest communities and LTER data for the arctic tundra communities.

Evaluate TEM performances TEM soil C stocks compared with soil C stocks based on 315 samples collected in Alaska (Johnson et al. 2011). Both simulated and observed soil C stock estimates are for the organic and 0-1m mineral horizons. Evaluation of TEM for vegetation biomass using data from 190 permanent study plots of the Cooperative Alaska Forest Inventory (CAFI) for boreal forest communities and LTER data for the arctic tundra communities.

Historical change in Net Ecosystem C balance [ ] -7.3 TgC/yr were lost on average between 1950 and 2009 in Interior Alaska. The loss over the 60 year period is primarily driven by unprecedented fire emissions during the decade of 2000s (record fire years in 2004 and 2005). Δ VEGC -2.6 Δ SOILC+DWDC -4.7 NPP 96.5 RH 73.1 Litter 88.5 Fire 30.7 Unit = TgC/yr

The spatial heterogeneity of the NECB in Interior Alaska is largely driven by the fire regime.

B1 A1B A2 Δ VEGC 2.6 Δ SOILC 2.1 NPP RH 84.6 Litter 94.3 Fire 10.8 Δ VEGC 4.7 Δ SOILC 3.3 NPP RH 86.8 Litter 94.5 Fire TgC/yr4.8 TgC/yr Δ VEGC 3.8 Δ SOILC 3.3 NPP RH 87.6 Litter 98.9 Fire 11.4 Δ VEGC 5.2 Δ SOILC 4.9 NPP RH 82.2 Litter 98.9 Fire TgC/yr7.2 TgC/yr Δ VEGC 3.9 Δ SOILC 7.4 NPP RH 77.4 Litter 97.2 Fire 16.4 Δ VEGC 5.3 Δ SOILC 5.6 NPP RH 84.3 Litter Fire TgC/yr11.3 TgC/yr

Increasing warming trend

(Wylie et al. in prep)

Δ VEGC 2.6 Δ SOILC 2.1 NPP RH 84.6 Litter 94.3 Fire 10.8 Δ VEGC 3.8 Δ SOILC 3.3 NPP RH 87.6 Litter 98.9 Fire 11.4 Δ VEGC 3.9 Δ SOILC 7.4 NPP RH 77.4 Litter 97.2 Fire 16.4 Δ VEGC 4.7 Δ SOILC 3.3 NPP RH 86.8 Litter 94.5 Fire 6.2 Δ VEGC 5.2 Δ SOILC 4.9 NPP RH 82.2 Litter 98.9 Fire 16.4 Δ VEGC 5.3 Δ SOILC 5.6 NPP RH 84.3 Litter Fire 15.5 B1 A1B A TgC/yr 10.9 TgC/yr 8.0 TgC/yr4.8 TgC/yr 7.2 TgC/yr 11.3 TgC/yr

Δ VEGC 2.6 Δ SOILC 2.1 NPP RH 84.6 Litter 94.3 Fire 10.8 Δ VEGC 3.8 Δ SOILC 3.3 NPP RH 87.6 Litter 98.9 Fire 11.4 Δ VEGC 3.9 Δ SOILC 7.4 NPP RH 77.4 Litter 97.2 Fire 16.4 Δ VEGC 4.7 Δ SOILC 3.3 NPP RH 86.8 Litter 94.5 Fire 6.2 Δ VEGC 5.2 Δ SOILC 4.9 NPP RH 82.2 Litter 98.9 Fire 16.4 Δ VEGC 5.3 Δ SOILC 5.6 NPP RH 84.3 Litter Fire 15.5 B1 A1B A TgC/yr 10.9 TgC/yr 8.0 TgC/yr4.8 TgC/yr 7.2 TgC/yr 11.3 TgC/yr CH CH CH CH CH CH TgC/yr TgC/yr -9.9 TgC/yr-11.0 TgC/yr TgC/yr TgC/yr

Conclusion Interior Alaska lost 365 TgC from soil respiration and wildfire burn from 1950 to 2010 that represents 3.4% of the total C stocks in the region in 1950 (10.6 PgC). In addition, 30 Tg CH 4 were emitted, mainly in wetlands. CH 4 warming potential being 21 times higher than CO 2, the total C loss in CO 2 eq. was 1.4 PgC, i.e. 13% of the C stocks in Upland ecosystems in interior Alaska are C sinks over the 21 st Century: the increase of productivity with projected climate warming offset increased carbon loss from soil respiration and wildfire emission for all climate scenarios. However, this sinks become strong sources when taken into consideration methane emissions from the wetlands. By 2100, Interior Alaska is projected to gain between 0.43 and 1.01 Pg C in uplands and loose between 0.07 and 0.17 PgC of CH 4 in wetlands. In CO 2 eq., the total loss would range from 0.89 to 2.6 PgC by 2100.

To what extent post-fire succession will offset C loss ?

Fire severityDrainageStand age Relative influence and partial dependency plots for variables in a boosted regression tree predicting relative spruce dominance

Post-fire succession model in development Drainage Pre-fire vegetation (PFV) Mesic Subhygric Failure High/moderate low Mixed trajectory Pre-fire stand age Xeric Pre-fire vegetation (PFV) < 50 yr > 50 yr Failure Mixed trajectory high low/mod erate Deciduous trajectory Pre-fire stand age Thermokarst model < 50 yr > 50 yr Failure Evergreen trajectory PFV = decid. Deciduous trajectory Fire severity PFV = everg. PFV = decid. Deciduous Fire severity PFV = everg. Thermokarst model

Patrick Endres, AK photographics Genet H., Zhang Y., McGuire A.D., He Y., Johnson K., D’Amore D., Zhou X., Bennett A., Biles F., Bliss N., Breen A., Euskirchen E.S., Kurkowski T., Pastick N., Rupp S., Wylie B., Zhu Z., Zhuang Q. Climate Feedback Research: Consequences of climate and disturbance changes for the Carbon feedback in Interior Alaska Thank you

Response of the vegetation to climate change Changes in productivity among Vegetation types

Hot spot map of NECB Uncertainty for the future period related to emission and climate forcing

Atmospheric Forcing

Hayes et al. 2014

Modeling fire severity The set of observation : -178 sites dominated by black spruce in Alaska - Data collected from 31 fire events between 1983 and Courtesy: IARCC ROL = OL loss / pre-fire OL thickness Relative Organic Layer loss (Genet et al. 2013)

Climate Drivers Mean Annual Temperature (MAT) and Annual Sum of Precipitation (ASP) from 1950 to 2100 summarized for the simulation extent. The black line represents the CRU data for the historical period and the colored lines represent the CCCMA (solid) and ECHAM5 (dotted) projections for the 3 emission scenarios.

(modified from Hayes et al. 2014) ATMOSPHERE Δ SOILC active Δ SOILC frozen Δ VEGC decomposition litterfall NPP N feedback ALT OL RH Δ Tair

(modified from Hayes et al. 2014) ATMOSPHERE Δ SOILC active Δ SOILC frozen Δ VEGC decomposition litterfall NPP N feedback ALT OL RH Δ Tair logging