USING THE FOREST VEGETATION SIMULATOR TO MODEL STAND DYNAMICS UNDER THE ASSUMPTION OF CHANGING CLIMATE Climate-FVS Version 0.1 Developed by : Nicholas.

Slides:



Advertisements
Similar presentations
MODELING THE IMPACTS OF CLIMATE CHANGE – CHANGES MADE IN A SPECIES SPECIFIC MODELING SYSTEM Jim Chew, Kirk Moeller, Kirsten Ironside Invited presentation.
Advertisements

FVS, State - Transition Model Assumptions, and Yield tables – an Application in National Forest Planning Eric Henderson Analyst, Hiawatha National Forest,
Figure 3. Outlines of the study with links between different components used. The figure presents the main inputs and outputs from the model used (Glob3PG)
Evaluating Approaches to “Ecosystem Management” Using FVS Steve McConnell NWIFC August 29, 2002.
Meeting Forest Carbon Planning Needs with Forest Service Data and Satellite Imagery Sean Healey, Gretchen Moisen RMRS Inventory, Monitoring, and Analysis.
Predicting Sapling Recruitment Following Partial Cutting in the Acadian Forest: Using Long-Term Data to Assess the Performance of FVS-NE David Ray 1, Chad.
Modeling Tree Growth Under Varying Silvicultural Prescriptions Leah Rathbun University of British Columbia Presented at Western Mensurationists 2010.
Evaluating Growth Models: A Case Study Using Prognosis BC Evaluating Growth Models: A Case Study Using Prognosis BC Peter Marshall, University of British.
SENSITIVITY ANALYSIS of the FOREST VEGETATION SIMULATOR Southern Variant (FVS-Sn) Nathan D. Herring Dr. Philip J. Radtke Virginia Tech Department of Forestry.
Forest Mensuration II Lecture 11: Stocking and Stand Density Nick Buda Northwest Science and Information Ontario Ministry of Natural Resources November.
Maximum Density-Size Relationships for Douglas-fir, Grand-fir, Ponderosa pine and Western larch in the Inland Northwest Roberto Volfovicz-Leon1, Mark.
Modeling bark beetle effects in a fireshed assessment An application of the Westwide Pine Beetle Model & the FFE in the Deschutes National Forest Andrew.
Growth Model Users Group Growth Model Run-Off January 2002.
Development of external Regeneration Models for FVS – another wrench in the toolkit Don Robinson ESSA Technologies Vancouver, Canada.
Forest Surveys and GIS Applications on the Nez Perce Reservation GIS on Fire! Worley - Plummer, Idaho May 11, 2005 Rich Botto, Nez Perce Tribe
Use of FVS for a Forest-wide Inventory SPOKANE INDIAN RESERVATION.
Growth and yield Harvesting Regeneration Thinning Fire and fuels.
Premise Three Basic Forms of Uncertainty - Level of Change - Process Impacts - Time and Space 1.
Modeling Effects of Genetic Improvement in Loblolly Pine Plantations Barry D. Shiver Stephen Logan.
Impact of plot size on the effect of competition in individual-tree models and their applications Jari Hynynen & Risto Ojansuu Finnish Forest Research.
Climate Change as a Driver in Mountain Pine Beetle Outbreaks in Eastern Washington Washington State Climate Change Impacts Assessment Conference Seattle,
Climate Change and Douglas-fir Dave Spittlehouse, Research Branch, BC Min. Forest and Range, Victoria.
F.O.F.E.M. 5 First Order Fire Effects Module Adapted from: Missoula Fire Sciences Laboratory Systems for Environmental Management.
Impact of Southern Pine Beetle Outbreaks on Wildlife Habitat Suitability Maria D. Tchakerian 1, Robert N. Coulson 1, Jaehyung Yu 1, and Forrest Oliveria.
The Rural Technology Initiative –“Better technology in rural areas for managing forests for increased product and environmental values in support of local.
Simulating growth impacts of Swiss needle cast in Douglas-fir: The blood, sweat and tears behind the ORGANON growth multiplier Sean M. Garber April 26,
Forest simulation models in Finland: main developments and challenges WG1 Jari Hynynen, Annikki Mäkelä & Kalle Eerikäinen COST ACTION FP0603: Forest models.
Climate Impacts: Mountain pine beetle in Eastern Washington Elaine Oneil PhD. Rural Technology Initiative College of Forest Resources Climate Impacts Group.
What Do You See? Message of the Day: The management objective determines whether a site is over, under, or fully stocked.
Improving longleaf pine mortality predictions in the Southern Variant of the Forest Vegetation Simulator R. Justin DeRose 1 John D. Shaw 2 Giorgio Vacchiano.
Comparison of FVS projection of oak decline on the Mark Twain National Forest to actual growth and mortality as measured over three FIA inventory cycles.
 Discuss silvicultural principles related to restoration/fuels treatments  Compare conditions from the 1900 Cheesman Lake reconstruction to current.
West Virginia University Division of Forestry 3 rd Forest Vegetation Simulator Conference February 13-15, 2007 Fort Collins, Colorado.
Incorporating Landscape Fuel Treatment Modeling into the Forest Vegetation Simulator Robert C. Seli Alan A. Ager Nicholas L. Crookston Mark A. Finney Berni.
Genecology and Adaptation of Douglas-Fir to Climate Change
Oct-03FOFEM 5 Overview An Overview of FOFEM 5 Missoula Fire Sciences Laboratory Systems for Environmental Management.
Bringing stand level fire risk to the landscape level: Fire risk assessment using FFE-FVS with the Landscape Management System. Kevin Ceder And James McCarter.
FireBGCv2: A research simulation platform for exploring fire, vegetation, and climate dynamics Robert Keane Missoula Fire Sciences Laboratory Rocky Mountain.
FVS Carbon Reporting Using the Forest Vegetation Simulator USDA Forest Service Forest Management Service Center Forest Vegetation Simulator staff.
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.
Fire Prevention as a GHG Mitigation Strategy Presented by Robert Beach, RTI International Brent Sohngen, The Ohio State University Presented at Forestry.
Modeling water and biogeochemical cycles in the Front Range, Colorado: effects of climate and landuse changes Landrum, Laura L., Natural Resource Ecology.
Comparing Stand Age 140 Basal Area per Acre Outputs from the DFC, FVS and ORGANON Models Steve McConnell Forest Integrity Spokane, WA Growth Model Users.
Non-pollutant ecosystem stress impacts on defining a critical load Or why long-term critical loads estimates are likely too high Steven McNulty USDA Forest.
FVS The Forest Vegetation Simulator (FVS) A review of the Pacific Northwest Variants Chad Keyser Forest Vegetation Simulator.
SIMULATING THE IMPACT OF AREA BURNED ON GOALS FOR SUSTAINABLE FOREST MANAGEMENT Jimmie Chew, RMRS Christine Stalling, RMRS Barry Bollenbacher, Region One.
Stefan Zeglen, Forest Pathologist, West Coast Region Jim Brown, Senior Analyst, Forest Analysis and Inventory Branch CSC Winter Workshop, Nanaimo, BCFebruary.
FVS Data Base Extension The Database Extension to the Forest Vegetation Simulator Nicholas L. Crookston Dennis Gammel March 11, 2003.
STRATIFICATION PLOT PLACEMENT CONTROLS Strategy for Monitoring Post-fire Rehabilitation Treatments Troy Wirth and David Pyke USGS – Biological Resources.
Cooperative FVS ! Functional Requirements for a Shared Library Version of FVS, or Calling FVS from R! Nicholas L. Crookston Rocky Mountain Research Station.
The Setting Inventories of forest lands in the U.S. have been done by different agencies: –National Forests inventoried by the NFS in the 1990s –Private.
Effects of Regeneration Abundance on Predicted Development of Interior Douglas-fir Stands By Cornel Lencar Graduate Student, Faculty of Forestry University.
Potential impact of climate change on growth and wood quality in white spruce Christophe ANDALO 1,2, Jean BEAULIEU 1 & Jean BOUSQUET 2 1 Natural Resources.
Modeling the effects of forest succession on fire behavior potential in southeastern British Columbia S.W. Taylor, G.J. Baxter and B.C. Hawkes Natural.
Thinning mixed-species stands of Douglas-fir and western hemlock in the presence of Swiss needle cast Junhui Zhao, Douglas A. Maguire, Douglas B. Mainwaring,
Comparisons of DFSIM, ORGANOIN and FVS David Marshall Olympia Forestry Sciences Laboratory PNW Research Station USDA Forest Service Growth Model Users.
Thursday Sept 12/Friday Sept 13 AGENDA Stamp and review homework Activity: Interactions Among Organisms Notes: Populations in Ecosystems HOMEWORK Read.
Annualized diameter and height growth equations for plantation grown Douglas- fir, western hemlock, and red alder Aaron Weiskittel 1, Sean Garber 1, Greg.
Silvicultural Prescription Rob Lusk. B All Species PlotTPATPA SD Basal Area BA SD Average Stand Diameter Average Stand Diameter SD Mean Quadratic Diameter.
Restoring whitebark pine ecosystems in the face of climate change pine Bob Keane, USDA Forest Service Rocky Mountain Research Station Fire Sciences Laboratory.
Feeding Across the ESN: Studying Herbivore-Ecosystem Interactions Following Fire in Black Spruce Forests Characterizing and inferring patterns and processes.
Forest Management Service Center Providing Biometric Services to the National Forest System Program Emphasis: We provide products and technical support.
What is new with the Forest Vegetation Simulator?
ln(CR) = HAB + b1BA + b2BA2 + b3ln(BA)
Western Mensurationists Meeting 2016
3-PG The Use of Physiological Principles in Predicting Forest Growth
Developing Edition 3.0 of CIPSANON
Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.
Harvesting Early Good or Bad?
Presentation transcript:

USING THE FOREST VEGETATION SIMULATOR TO MODEL STAND DYNAMICS UNDER THE ASSUMPTION OF CHANGING CLIMATE Climate-FVS Version 0.1 Developed by : Nicholas L. Crookston, USDA-FS, RMRS, Moscow, ID Gary E. Dixon, (Retired) USDA-FS, FMSC, Fort Collins, CO Gerald E. Rehfeldt, (Retired) USDA-FS, RMRS, Moscow, ID

Presentation Road Map Background on Base FVS Background on Climate Models Climate-FVS Architecture Climate-FVS “How to”

Description of FVS FVS is a distance-independent, individual-tree forest growth model widely used in the United States to support forest management decision-making Individual stands are the basic projection unit and projections are dependent on interactions among trees within stands, as well as site and stand conditions. FVS allows users to compare management scenarios, to meet landowner objectives. Extensions to FVS model the impact of disturbance- causing agents (fire, insects, and disease)

Applications example of FVS Applications range from development of silvicultural prescription for single stands to landscape and large regional assessments No Action Shelterwood

Variants of FVS The component models differ depending on the geographic region represented by regionally specific model variants Coefficients are estimated using available data from the variant’s geographic region Each variant is a self- contained program executable written in FORTRAN (FORmula TRANslation) Under development

FVS Basic Operation FVS needs a keyword file to run Keywords are mnemonic words with associated data that provide information to FVS Keywords are used to  enter stand and tree information  describe management treatments  control the printing of output  adjust model estimates Suppose prepares the keyword file for you and executes the FVS variant of choice

Processing Sequence Initialize Stand Simulation Individual Tree Growth (DBH & HT) Mortality Fire and Fuels Adjustments Crown ChangeRegeneration Performs Cutting Activities Report Projected Conditions 132 Insect and Pathogen Adjustments End Stand Simulation Growth Cycle Prior to Projection

General Circulation Models Canadian Center of Climate Modeling and Analysis  CGCM3-A2  CGCM3-B1  CGCM3-A1B Met Office Hadley Centre –UK (HADMC3)  HADMC3-A2  HADMC3-B2 Geophysical Fluid Dynamics Laboratory -Princeton University, NOAA Research (GFDLCM21)  GFDLCM21-A2  GFDLCM21-B1

Emission Scenarios

Example of predicted changes in climate

Example of Viability Scores Viability Scores* Location on Gifford Pinchot NF CODES:PSMETSHEPIPO * Lat: 46.67, Long: , Elev: 2583, based on Hadley A2 Scenario

Douglas-fir climate profile stays new recede Douglas-fir climate profile location change (current to 2060)

Climate-FVS: Architecture Base FVS assumes site is constant over time, this assumption is not tenable under changing climate. The current structure of FVS to apply management has not changed Climate-FVS does NOT contain a climate model, it uses species viability scores. The species viability scores are for 75 western U.S. species predicted from seven future climate scenarios (presently based on Rehfeldt et al, but user could use any source of scores) Viability scores are used to compute mortality rates and modify FVS-predicted growth rates.

Changes to the model under Climate-FVS Carrying capacity may change Additional species specific mortality Species Establishment changes Growth is impacted  by genetics  by site quality changes

Site Carrying Capacity Changes maximum density as a function of climate. Presently FVS uses Maximum SDI or BA as a measure of carrying capacity and uses it to compute density related mortality. These maximum densities are typically species based and the maximum for the stand varies based on the basal area-weighted average maximum Climate-FVS computes a proportional change in carry capacity, where the viability scores are used instead of basal area-weighted to compute maximum density.

Additional Species Specific Mortality Additional species specific mortality is applied to all species with a viability score below As the viability score decreases, the mortality rate increases. The mortality rate is proportional to the viability score.

Species Establishment Climate-FVS will establish 500 seedling/acre when stand density falls below a stocking threshold The four most viable species will be regenerated The number of trees of each species will be apportioned based on the relative viability scores The consequence is that more trees of the most viable species will be regenerated If no species are viable, none are regenerated.

Growth Site quality  If the stand site quality changes due to climatic change, growth will be affected.  The Annual Dryness Index (ADI) is used as an indicator of site quality change. As ADI increases or decreases compared to contemporary, it proportionally affects Site Quality. Tree genetics  Trees growing on sites they are adapted for grow faster than those growing on site they are maladapted for.  Transfer distances, seed zones

Growth modified based on Seed Transfer Distance Leites, L. (preliminary work, Univ. of Idaho)

How To Run Climate-FVS Obtain climate executable from FMSC Additional input file needed that contains viability scores One additional keyword is mandatory (CLIMDATA), that specifies the location of the viability scores files, and specifies the GCM scenario to be used. Four other option keywords can me used to change the assumptions on climate change impacts on growth, mortality, and regeneration.

Example of additional input file needed A source of the climate and species viability data file is at this web address: data.php. data.php Filename: FVSClimAttrs.csv

Four Optional Keywords AutoEstb: Signal that Climate-FVS automatic establishment logic is turned on and that the base FVS automatic establishment features are turned off. GrowMult :Specify a species-specific adjustment of the growth-rate multiplier computed by Climate- FVS. MortMult :Specify a species-specific mortality multiplier. MxDenMlt: Specify an adjustment of the maximum density multiplier computed by Climate-FVS.

Climate-FVS Reports Main Output File – Options Selected by input  lists viability scores by species Climate Reports  none yet developed  see effects in standard output reports

Compare Climate Scenarios

Compare Species by Climate Scenarios

Compare Scenarios BASEGCM Scenario

Climate-FVS Nicholas L. Crookston USDA- Forest Service Rocky Mountain Research Station, Moscow, Idaho Forest Management Service Center USDA- Forest Service Fort Collins, CO Questions?