program expansions a brief history
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Program Expansions A Brief History. Early 20 th Century – Timberland End of 20 th Century – Forestland In the 21 st Century – Today – Land Use Change Tomorrow – Treed Lands ? Day After Tomorrow – All Veg ?. Program Expansions The Broader the look; the Better the Parts. - PowerPoint PPT PresentationTRANSCRIPT
Program ExpansionsA Brief History
• Early 20th Century – Timberland
• End of 20th Century –
Forestland
• In the 21st Century – – Today – Land Use Change – Tomorrow – Treed Lands?– Day After Tomorrow – All Veg?
Program ExpansionsThe Broader the look; the Better the Parts
Timberland to Forestland Timberland; Reserved Forestland;Unproductive Forestland
Forestland plus Land Use ChangeForestlandUrbanAgriculture RangelandWater
Land Use Change ≠ NO Trees
Trees Falling thru Gap
Not an Acre
Not 120’ Wide
Wrong Land Use
Why Fill the GapAll trees:• Sequester Carbon• Provide Habitat• Filter Water• Stabilize Soils• Provide Biomass• Enhance Biodiversity• Create JobsSome trees:• Increase crop yields• Protect livestock• Conserve energy• Improve health and safety
Handy trees should be tally trees!
Filling the GapOne Constituency at a Time
• Trees on Non-Forestlands– Urban– Agricultural “Working Trees”– Riparian– Rangelands
Filling the GapOne Constituency at a Time
• New Constituency = Support• New Support = Funding
– Direct– Indirect
• New Funding = Filling the Gap WITHOUT compromising the base forestland mission
Filling the GapUrban
• Lot’s of Statewide Urban Pilots– IN, WI, TN, CO, WA, OR, CA, HI, AK– Confirmed we can– Quantified urban forests– Confirmed value and benefits– Not resulted in strategic national investment– Maybe the scale is wrong???
• FIA scale.. urban forests of USA• Urban Constituency Scale…my city
Filling the GapUrban
Vibrant Cities Initiative (http://vcuf.files.wordpress.com/2012/11/vcuf_report.pdf)
• Urban areas - where most people live (84%) and vote!• Urban forests key to vibrant urban environments
“At the root of every vibrant city is an urban forest”• Urban areas viewed as ecosystems
– People, infrastructure, and forest intermix/interact– “Ecosystem” key to scale issue
• Core Based Statistical Areas – Scale at which FIA can contribute
Filling the GapUrban
12 Vibrant City Recommendations (Goals):• Create a national education and awareness campaign.• Foster urban forestry and natural resources stewardship and volunteerism.• Create sustainable jobs in urban forestry and green infrastructure.• Cultivate partnerships between public and private sectors.• Develop new public administration models for urban ecosystems.• Create comprehensive, multi-jurisdictional Urban Regional Natural Resource Plans.• Integrate federal agencies’ green infrastructure goals.• Establish energy efficiency programs that emphasize the use of trees.• Ensure equal access to urban forestry and green infrastructure resources.• Support collaborative urban ecosystem-focused research.• Encourage open access to and use of social assessment tools.• Establish national Vibrant Cities Standards.
Filling the GapUrban
FIA contributions to 12 Vibrant City goals:• Baseline accounting of urban forests • Long-term monitoring of change in urban forests• Valuate urban forest benefits and services• Platform for sample intensification/augmentation • Nationally consistent methods and procedures • Data sharing and distribution tools • Job opportunities
Filling the GapUrban
FIA Benefits• Extends FIA to voting populace• Makes FIA key to their needs• Broadens support network
• Parks and People Foundation• ICLEI Local Governments for Sustainability USA• Chicago Wilderness • Tree Care Industry Association • Urban Greenspaces Institute • New York City Department of Parks & Recreation • Arbor Day Foundation • TreePeople, Inc. • Cascade Land Conservancy • Congress for New Urbanism • Trees Forever • Open Space Institute • International Society of Arboriculture • Sacramento Tree Foundation • Sustainable Urban Forests Coalition• New York Restoration Project • Society for Municipal Arborists • Alliance for Community Trees • National Urban and Community Forestry Advisory Council
• Strategic urban forest inventory– Built one metro area at a time– Allows seamless urban to rural monitoring
Filling the Gap - Defining Urban
Filling the Gap - Defining Urban
Filling the Gap – Defining Urban
Filling the Gap - Urban City Intensifications —Maintaining continuity with past Urban inventories
(I-Tree, FIA Urban Pilots, ARRA, etc.)• Overlay new FIA hex sampling frame on old urban grid
– If new hex contains FIA base grid plot then keepElse
– If new hex contains old grid plot then keepElse
– If neither base FIA nor old then add new plot• Possibility to maintain some historic trend data
– If resources available
City Intensified Hexes
Old
New
Filling the GapUrban
Dave Nowak design Single 1/10th acre fixed Fast and efficient in cities
FIA design Cluster of 4 - 1/6th acre fixed Clunky in cities
Pragmatic Suggestion
National Urban InventoryPlot Type in Urban Stratum Total Count FIA Forest Plots 2,051 FIA Non-Forest Plots 8,895Total FIA Plots 10,946
Filling the Gap Rural/Urban Strata
Dual Plot Design Model
Rural StratumTraditional FIA Forestland
4 subplot cluster
Urban StratumSingle 1/6 acre fixed plot at subplot 1 on FIA non-forestland
Dual DesignOn FIA Forestland in Urban Stratum
= Percent of FIA plots
32.8%
0.7%
3.6%
Filling the Gap -- Urban Urban Plot Size Options
Practical plot size in Urban areas:
1/10th acreUrban plot37.2 ft. radius
1/6th acre on par with rural
Else
1/10th acre same as i-Tree
Else
1/24th acre same as subplot 1
Filling the Gap - Urban
Filling the Gap - Urban
The NWOS contacts forest-land owners from across the country to ask them questions about:
The forest land they own Their reasons for owning it Their uses of it Their management of it Their information needsTheir future intentions for itTheir demographics
Extend NWOS to urban areasDifferent focus; different questions; same
foundational sampling frame/processing engine
Filling the Gap – Urban Team
• National Urban Team – Mark Majewsky– Members from all Units/partners– IM Planning Sub-team (Mark Hatfield)– Reporting Sub-team (Tonya Lister)– Pre-field Sub-team (James Blehm)
• Plot sheet design (Cassandra Olson)• Navigational aids (Cassandra Olson)
– Field Guide Sub-team (Mark Majewsky)– PDR Sub-team (Jay Solomakos)– Ownership Sub-team (Brett Butler)– TPO Sub-team (Ron Piva)
Filling the GapUrban
Logical Partnership with i-Tree– Dave Nowak, FS R&D, NRS
• Urban Forest Specialist• Established user base• Established partnerships• Does urban forest inventory for a living• Partner in all our urban pilots• Has developed software
– I-Tree– Urban Forest Effects Model (UFORE)– Has read and emulated the little green book
• Established processing engine• Established reporting format
Filling the Gap--Urban Pr
efie
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Fiel
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Proc
essi
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Ana
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Dis
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Stag
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n FIAI-Tree/D. Nowak
Conceptual Partnering Model
Old Model
State Pilot Model
New Model
Future Model?
Filling the Gap --Urban FIA Lead
I-Tree LeadNew FIA / I-Tree Partnering Model
Plot Selection- overlay new FIA
grid on top of any existing grid to
facilitate trending/change
estimation if resources available
MIDAS – modify to capture/edit combined field manual data on
single-plot design and dual design for FIA forest plots in urban
Pre-Field – determine
visitation; prepare navigational aids;
consistency in cover/use calls with
FIA/Urban/ICE
MIDAS – post-field edit; create urban output file that is UFORE
input ready, streamline the
pass to UFORE
FIELD – FIA train, certify, and QA; data
collection (feds, states,
cities, or contracts)
NIMS – process traditional FIA rural data as
normal
I-Tree – Dave et al. analyze and publish
typical UFORE report
embellished with FIA data
I-Tree – process urban data through
UFORE; accommodate FIA
table outputs, condition
weighting, error estimation, change
estimation as practical/over time
FIA – pass estimation
“weighting” info to I-
Tree/UFORE engine
I-Tree – create FIADB-like
standardized output file
from UFORE that has UFORE variables
concatenated at appropriate
levels (tree, condition, plot)
I-Tree – create a new level of the I-Tree database to
store FIA-certified urban forest
inventory data (the standardized FIADB-like file from UFORE)
FIA – Develop data distribution tool to hit against FIADB-like UFORE output …UrbanEvalidator
Filling the Gap – Urban 2014
• Initiate Baltimore CBSA• Annualized 7-year cycle• ~29 City (red) plots/yr• ~14 Urban (blue) plots/yr• Partners
– Dave Nowak/i-Tree– Baltimore LTER– City of Baltimore– State
Filling the Gap – Urban 2014
• Initiate Austin CBSA• Annualized 10-year cycle• ~20 City (red) plots/yr• ~4 Urban (blue) plots/yr• Accelerated City Cycle
– 1 or 2 years– Report out sooner
• Build Support
• Partners– Dave Nowak/i-Tree– State– City of Austin
Filling the Gap - Urban 2015+Vibrant Cities 7-year plan: • Select at least 25 cities of various sizes and in multiple regions
to test new data gathering tools, providing for standard collection of assessment using identical methodologies and allowing comparison across municipalities.
• Encourage implementation of these tools by 2020 in: – 25% of cities with populations <250,000 – 50% of cities with populations of 250,000 to 1 million – 100% of cities with populations > 1 million
STATE CBSA sorted by area & urban base plotsLARGEST CITY
ACRES UAUC (blue)
BASE PLOTS UAUC
NY New York-Northern New Jersey-Long Island, NY-NJ-PA New York city 2435835 406GA Atlanta-Sandy Springs-Marietta, GA Atlanta city 1835256 306IL Chicago-Joliet-Naperville, IL-IN-WI Chicago city 1793357 299TX Dallas-Fort Worth-Arlington, TX Dallas city 1419858 237PA Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Philadelphia city 1396086 233MA Boston-Cambridge-Quincy, MA-NH Boston city 1335650 223TX Houston-Sugar Land-Baytown, TX Houston city 1318641 220CA Los Angeles-Long Beach-Santa Ana, CA Los Angeles city 1261760 210DC Washington-Arlington-Alexandria, DC-VA-MD-WV Washington city 1090700 182MI Detroit-Warren-Livonia, MI Detroit city 1025429 171CA Riverside-San Bernardino-Ontario, CA Riverside city 860661 143FL Miami-Fort Lauderdale-Pompano Beach, FL Miami city 853111 142AZ Phoenix-Mesa-Glendale, AZ Phoenix city 845030 141MN Minneapolis-St. Paul-Bloomington, MN-WI Minneapolis city 823956 137FL Tampa-St. Petersburg-Clearwater, FL Tampa city 771211 129WA Seattle-Tacoma-Bellevue, WA Seattle city 759492 127MO St. Louis, MO-IL St. Louis city 713061 119PA Pittsburgh, PA Pittsburgh city 685440 114NC Charlotte-Gastonia-Rock Hill, NC-SC Charlotte city 633535 106FL Orlando-Kissimmee-Sanford, FL Orlando city 615752 103MD Baltimore-Tow son, MD Baltimore city 605767 101OH Cincinnati-Middletown, OH-KY-IN Cincinnati city 590262 98CA San Francisco-Oakland-Fremont, CA San Francisco city 547762 91OH Cleveland-Elyria-Mentor, OH Cleveland city 532904 89MO Kansas City, MO-KS Kansas City city 524331 87CA San Diego-Carlsbad-San Marcos, CA San Diego city 504835 84TN Nashville-Davidson--Murfreesboro--Franklin, TN Nashville-Davidson metropolitan government (balance)484356 81IN Indianapolis-Carmel, IN Indianapolis city (balance)480209 80FL Jacksonville, FL Jacksonville city 459627 77RI Providence-New Bedford-Fall River, RI-MA Providence city 462719 77CO Denver-Aurora-Broomfield, CO Denver city 448461 75CT Hartford-West Hartford-East Hartford, CT Hartford city 426870 71TX San Antonio-New Braunfels, TX San Antonio city 424969 71VA Virginia Beach-Norfolk-New port New s, VA-NC Virginia Beach city 424255 71OH Columbus, OH Columbus city 401566 67OR Portland-Vancouver-Hillsboro, OR-WA Portland city 388531 65TX Austin-Round Rock-San Marcos, TX Austin city 391194 65
STATE CBSA sorted by largest city popLARGEST
CITY CITY POP
CBSA TOTAL
POPNY New York-Northern New Jersey-Long Island, NY-NJ-PA New York city 8175133 18897109CA Los Angeles-Long Beach-Santa Ana, CA Los Angeles city 3792621 12828837IL Chicago-Joliet-Naperville, IL-IN-WI Chicago city 2695598 9461105TX Houston-Sugar Land-Baytown, TX Houston city 2099451 5946800PA Philadelphia-Camden-Wilmington, PA-NJ-DE-MD Philadelphia city 1526006 5965343AZ Phoenix-Mesa-Glendale, AZ Phoenix city 1445632 4192887TX San Antonio-New Braunfels, TX San Antonio city 1327407 2142508CA San Diego-Carlsbad-San Marcos, CA San Diego city 1307402 3095313TX Dallas-Fort Worth-Arlington, TX Dallas city 1197816 6371773CA San Jose-Sunnyvale-Santa Clara, CA San Jose city 945942 1836911FL Jacksonville, FL Jacksonville city 821784 1345596IN Indianapolis-Carmel, IN Indianapolis city (balance)820445 1756241CA San Francisco-Oakland-Fremont, CA San Francisco city 805235 4335391TX Austin-Round Rock-San Marcos, TX Austin city 790390 1716289OH Columbus, OH Columbus city 787033 1836536NC Charlotte-Gastonia-Rock Hill, NC-SC Charlotte city 731424 1758038MI Detroit-Warren-Livonia, MI Detroit city 713777 4296250TX El Paso, TX El Paso city 649121 800647TN Memphis, TN-MS-AR Memphis city 646889 1316100MD Baltimore-Towson, MD Baltimore city 620961 2710489
Filling the Gap – Urban Road Rules • Partnership Model
– FIA and I-Tree Under Vibrant Cities Umbrella• Goals:
– Long-term Strategic Inventory and Monitoring of the Nation’s Urban Forests » Not another pilot» Built one Census Core Based Statistical Area (CBSA) at a time» Annualized to FIA rural forest inventory cycles within the CBSA» Strategic monitoring of all urban forests within each CBSA» Intensified monitoring of urban forests in the target city within each CSBA» Provide annual information on the status and trends in target city forests» Provide for the broader-scale monitoring of all forests along the urban to rural gradient » Place city forests into context within the broader urban to rural continuum» Forward Vibrant City goals
• Design– Population
• Census--Core Based Statistical Areas (multi –county areas which build to national)– Census-defined urban areas and urban clusters boundaries within
» Target-city boundary within
– FIA Hexagonal Sampling Frame• Sampling Intensity
– FIA base intensity (1 plot/~6000 acres) in urban boundary– Intensify as necessary to achieve 200 total plots in the target city
Filling the Gap – Urban Road Rules – Plot Design
• 4-subplot cluster for FIA (rural) forests• Single plot at subplot one for urban
– 1/6 acre fixed • Dual design for FIA forest plots in urban
– Exploit marginal cost opportunity (FIA already visits 20% of urban plots)– Maintain consistency with rural and urban designs/estimation
– Annualize• Match FIA rural forest cycle• Match FIA production/delivery goals
– Collect data in 1 year– Process/post data within 6 months of last plot– Publish comprehensive report every 5 years– Develop data distribution tools– Met by combination of FIA and I-Tree systems
– Data Collection• Start by merging FIA and I-Tree UFORE field manuals
– Traditional outputs of both Programs– Augment/refine in time
» Learn from initial efforts» Only after initial effort firmly underway
Filling the Gap – Urban Road Rules – Data Collection
• Staffing– Best mix (fed, partners, contracts)– All must be trained – All must be certified – All must pass check plots
• Quality Standards and Attainment– Trained and Certified crews– 4% - 10% of plots checked annually
» Blind, Hot, and Cold– Measurement Quality Objectives
» Basis for passing check plot» Quantified and reported
– Estimates with sampling errors» Statistical precision goals
• Full breadth of FIA program with logical urban refinements– Plots
» Characterize vegetation and sites upon which it grows» P1, P2, P2 + (ecosystem indicators)
– Timber Product Output» Characterize mills, wood used, products made, and residues generated
– National Woodland Owners Survey» Characterize owners, attitudes, behaviors, and intentions
Filling the Gap – Urban Road Rules – Sample Integrity Protections
• Do not bias the sample– Access– Ancillary efforts
» May not be the best platform for some R&D efforts
– Privacy Protections• Get permission to collect• Do not divulge individual’s proprietary data
– Spatial Data Services• Maximize data utility while staying compliant with Integrity/Privacy protections
• Augmentation opportunities paid by partner– Spatial intensification
• Increase the number of samples (sample intensity)– More precise estimates/more confidence for smaller areas of interest
– Temporal intensification• Speed the number of plots installed in a year/shorten the cycle length
– Report out sooner– Establishment of rolling average and change estimation sooner
– Additional Data Attributes– Augment when mutually beneficial and not detrimental to base effort