Forest Management Service Center Providing Biometric Services to the National Forest System Program Emphasis: We provide products and technical support.

Slides:



Advertisements
Similar presentations
The Central Washington Landscape Assessment (CWLA) project update and discussion.
Advertisements

EU INTAS SILVICS Project Pushchino Research Centre of the Russian Academy of Sciences Institute of Mathematical Problems in Biology (Pushchino.
MODELING THE IMPACTS OF CLIMATE CHANGE – CHANGES MADE IN A SPECIES SPECIFIC MODELING SYSTEM Jim Chew, Kirk Moeller, Kirsten Ironside Invited presentation.
KATIE IRELAND, ANDY HANSEN, AND BEN POULTER Modeling Vegetation Dynamics with LPJ-GUESS.
FVS, State - Transition Model Assumptions, and Yield tables – an Application in National Forest Planning Eric Henderson Analyst, Hiawatha National Forest,
Evaluating Approaches to “Ecosystem Management” Using FVS Steve McConnell NWIFC August 29, 2002.
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.
Lecture 13 FORE 3218 Forest Mensuration II Lecture 13 Growth and Yield Models Avery and Burkhart, Chapter 16.
FVS Regeneration Imputation Don Vandendriesche USDA Forest Service Forest Management Service Center Growth and Yield Group.
Carbon Information Needed to Support Forest Management Bob Davis, Director Of Planning, Watershed And Air, USDA Forest Service 0.
Maximum Density-Size Relationships for Douglas-fir, Grand-fir, Ponderosa pine and Western larch in the Inland Northwest Roberto Volfovicz-Leon1, Mark.
Using FIA Data to Strategically Assess Fire Hazard and Management Opportunities in Montana and New Mexico Charles E. Keegan III The University of Montana.
Improving soils data for better vegetation modeling Wendy Peterman, Dominique Bachelet Conservation Biology Institute  Abstract Over.
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.
TIM ROBARDS UNIVERSITY OF CALIFORNIA, BERKELEY CAL. DEPT. OF FORESTRY & FIRE PROTECTION, FIRE & RESOURCES ASSESSMENT PROGRAM Climate Sensitive Individual.
Growth and yield Harvesting Regeneration Thinning Fire and fuels.
Impact of plot size on the effect of competition in individual-tree models and their applications Jari Hynynen & Risto Ojansuu Finnish Forest Research.
Forest Growth Model and Data Linkage Issues Limei Ran Carolina Environmental Program UNC Steve McNulty Jennifer Moore Myers Southern Global Change Program,
Managing for Forest Carbon Storage. USDA Forest Service GTR NE-343.
F.O.F.E.M. 5 First Order Fire Effects Module Adapted from: Missoula Fire Sciences Laboratory Systems for Environmental Management.
Effects of Climatic Variability and Change on Forest Resources: A Scale- based Framework for Analysis David L. Peterson USDA Forest Service, PNW Station.
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.
What Do You See? Message of the Day: Informed forest management decisions need information about current and projected conditions.
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.
Sustainable Forest Management on the Yakama Reservation.
 Discuss silvicultural principles related to restoration/fuels treatments  Compare conditions from the 1900 Cheesman Lake reconstruction to current.
TARA L. KEYSER, RESEARCH FORESTER, USDA FOREST SERVICE, SOUTHERN RESEARCH STATION FREDERICK (SKIP) W. SMITH, PROFESSOR OF SILVICULTURE, COLORADO STATE.
Effects of Silvicultural Practices on Woody Vegetation John Kabrick, Steve Shifley, and Dan Dey – USDA Forest Service Northern Research Station Randy Jensen,
What Do You See? Message of the Day: Use variable area plots to measure tree volume.
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.
Powered By Powered by: Simulating Regeneration Dynamics in Upland Oak Stands USDA Forest Service Southern Research Station Dr. David Loftis.
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.
Fire Prevention as a GHG Mitigation Strategy Presented by Robert Beach, RTI International Brent Sohngen, The Ohio State University Presented at Forestry.
Combining historic growth and climate data to predict growth response to climate change in balsam fir in the Acadian Forest region Elizabeth McGarrigle.
FVS The Forest Vegetation Simulator (FVS) A review of the Pacific Northwest Variants Chad Keyser Forest Vegetation Simulator.
FORESTRY AND FOREST PRODUCTS Project Level Carbon Accounting Toolkit CSIRO Forestry and Forest Products Department of Forestry, Australian National University.
Watershed Assessment and Planning. Review Watershed Hydrology Watershed Hydrology Watershed Characteristics and Processes Watershed Characteristics and.
Validating the Prognosis DDS model for the Inland Empire Robert E. FroeseAndrew P. Robinson School of Forest Resources Etc.Department of Forest Resources.
Strategic criteria for compensating Natura areas Allan Sims, Allar Padari.
Effects of Regeneration Abundance on Predicted Development of Interior Douglas-fir Stands By Cornel Lencar Graduate Student, Faculty of Forestry University.
Lecture 12 FORE 3218 Forest Mensuration II Lecture 12 Tree-Growth and Stand-Table Projection Avery and Burkhart, Chapter 16.
Do stem form differences mask responses to silvicultural treatment? Doug Maguire Department of Forest Science Oregon State University.
Extension of the forest ecosystem simulation model FORECAST: incorporating mountain pine beetle, fire, climate change, and wildlife Hamish Kimmins, Kim.
Growth and Yield Lecture 6 (04/17/2015). Overview   Review of stand characteristics that affect growth   Basic Stand Growth Terminology Yield curve;
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.
FOR 274: Forest Measurements and Inventory Tree Age and Site Indices Age Site Indices.
Local Climate & Management: Using stand-level modeling to predict climate change effects on forests WADE TINKHAM Wildfire in Idaho, 2007 © National Geographic.
RAP-ORGANON A Red Alder Plantation Growth Model David Hibbs, David Hann, Andrew Bluhm, Oregon State University.
USING THE FOREST VEGETATION SIMULATOR TO MODEL STAND DYNAMICS UNDER THE ASSUMPTION OF CHANGING CLIMATE Climate-FVS Version 0.1 Developed by : Nicholas.
Ecological Site Descriptions Foundation for Resource Management Decisions George Peacock Grazing Lands Technology Institute USDA-NRCS.
Annualized diameter and height growth equations for plantation grown Douglas- fir, western hemlock, and red alder Aaron Weiskittel 1, Sean Garber 1, Greg.
Establishing Plots to Monitor Growth and Treatment Response Some do’s and don’ts A discussion.
GROWTH AND YIELD How will my forest grow? Dr. Glenn Glover School of Forestry & Wildlife Sciences Auburn University.
What is new with the Forest Vegetation Simulator?
FOR 350 Silvicultural Terminology Review
Western Mensurationists Meeting 2016
How Do Trees and Stands Grow?
STANDCARB Elissa Chott February 22, 2017.
Figure 1. Spatial distribution of pinyon-juniper and ponderosa pine forests is shown for the southwestern United States. Red dots indicate location of.
Stand and Tree Characteristics at Age 30
What Do You See? Message of the Day: Informed forest management decisions need information about current and projected conditions.
50 Essential Forestry Terms Afforestation All-aged (uneven-aged) Artificial Regeneration Basal Area Biomass Broadleaf Clear-cut Harvest Climax Forest.
Kirk Hanson (360)
Presentation transcript:

Forest Management Service Center Providing Biometric Services to the National Forest System Program Emphasis: We provide products and technical support for forest vegetation modeling and forest product measurements to the National Forests and our partners.

Biometric: Support Areas  Forest Products Measurement  develops and applies practical and efficient methods of timber cruising, scaling, volume and biomass estimation, and area determination  Forest Vegetation Modeling  enhances, maintains and supports the Forest Vegetation Simulator (FVS), a nationally supported framework for growth and yield modeling

Geographic Variants of FVS  Represent species commonly found in a geographic region  Local Data are used to create models that predict tree growth, mortality, and regeneration Under development

Stand Inventory Data  Location  Ecological Code: Ecoregion, Plant Assoc, Habtype  Slope  Aspect  Elevation  Site Index  Carrying Capacity (Max SDI/MaxBA)  Species  DBH  Height (total)  Crown Ratio  Past Growth Increment  Tree Count (from inventory design) Stand /Site ConditionsTree Characteristics

FVS is a distance-independent individual tree growth model comprised of empirical equations that predict diameter and height growth, crown change and mortality of individual trees over time yrsFVS Inventory+ 100 yrs Forest Vegetation Simulator

FVS Extensions  Models that interact with base FVS variants  Simulate the effects of various ecological disturbances  Insects and diseases  Fire and Fuels (FFE)  Climate change

FVS Growth and Yield Modeling  Projects single or multiple stands in a single simulation  Models stand development with and without taking into consideration forest health concerns  Simulates common and user-defined management actions  thinning methods  regeneration methods  fuels and fire management

FVS-WRENSS Water Yield Post-Processor for FVS Calculates Water Yield Based on: WRENSS Regional Evapotranspiration Relationships Stand Elevation, Aspect, Forest Type FVS-Simulated Stand Density Dynamics Monthly Precipitation Data WRENSS - An Approach to Water Resources Evaluation of Non-Point Silvicultural Sources, Forest Service, USDA, EPA-IAG-D6-0660, 1980

FVS-WRENSS Processing Flow Chart FVS Output Parse the FVS main output (.out) file Vegetative Data WRENSS Precip. Data Water Yield Output Hydrologic Parameters

FVS-WRENSS Summary INPUT ANNUAL PRECIP.= STAND ID= YEAR EFF. PRECIP. ET YIELD CHANGE BA F-TYPE

Alternate Management Scenarios 1) No Treatment 2) Thin from 0 – 16 inches DBH in ) Prescribed Fire in 2030 Initial Stand Composition ponderosa pine Douglas fir Gambel oak

FVS-WRENSS - Water Yield Postprocessor for FVS Robert Havis, FVS Staff