Aerial RootDisease SurveyLongview Region - PowerPoint PPT Presentation

Title: Aerial RootDisease SurveyLongview Region


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ESC 432Forest Health An Industry
PerspectiveWill LittkeWeyerhaeuser Company
Laminated Root Rot
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Forest Health is one measure of ecosystem
function the qualitative expression of forest
health integrates various elements

• Change a dynamic condition of the forest with
  both temporal and spatial variation.
• Resiliency a situation or condition where future
  risk of forest damage from biological or physical
  factors have been minimized.
• Resource Goals defined by site specific and
  user group objectives wildlife, timber, water,
  recreation, biodiversity, etc. Disease and
  insects may threaten resources or serve important
  natural ecosystem regulatory functions while
  creating diversity of forest structure and
  habitat.
• Assessments measurements based on the resource
  objective.
• Interaction usually involves a broader
  stakeholder perspective across landscape units,
  resource goals and time.

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Forest Health in the Old-Growth
Predominate loss agents 1) heartwood decay
(Fomitopsis pini-red ring rot) 2) mistletoe
caused defect (Hemlock DMT) 3) blowdown (storm
events, eruptions) 4) fire and bark
beetles (lightning, Douglas-fir beetle)
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Westside Douglas-fir/Hemlock Forest Growing Region

• These young production forests (060 years) are
  affected by
• Root-Rot Root-Disease
• Needle Cast
• Dwarf Mistletoe in Western Hemlock stands
• Spruce Weevil in Sitka Spruce Stands

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Laminated Root-rot Management On Industrial
Forest Lands

• Detection methods

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Principle Phellinus Project Objectives

• Identify methods to detect stands with
  significant levels of Phellinus weirii (gt10
  stand area) and track these through following
  rotations.
• Quantify mortality (present and future) across
  acres using both ground based and aerial
  reconnaissance methodologies.
• Develop and test detection and location
  capabilities for mortality across a variety of
  stand ages from 15-100 years.
• Develop GIS maps of mortality to facilitate
  ground-surveys of areas for specific mortality
  causes and to investigate non-mortality areas.
• Develop recommendations for management of
  Phellinus.

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Laminated root-rot is the greatest single
pathogen agent affecting the management of
Douglas-fir.
Disease resistant WH seedlings
Root-ball
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Phellinus weirii is the major loss factor in the
management of Douglas-fir on 5-10 of industrial
forest land.
Losses Wind-throw Growth loss Decay Log grades
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Phellinus caused wind throw and mortality losses
are compounded by invested in thinning and
pruning.
Proper identification of Phellinus during
previous post-harvest exam would have resulted in
a shift in regeneration species and management
alternatives.
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The presence of Phellinus in stands can be a
limiting factor in management decisions such as
where to place buffer strips, decisions on
commercial thinning, variable retention
strategies (no cc-management), and future
regeneration opportunities.
Cut-blocks which utilize group selection of trees
for wind throw stability are severely compromised
by the presence of Phellinus.
Control Option pre-cruise survey would have
detected high level of Phellinus. CC-Option
preferred to group selection.
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Phellinus Detection Opportunities

• Pre-harvest Final Exam
• Harvest Survey
• Early Regeneration Survival Exam
• Free-To-Grow Exam
• PCT and CT, Fertilization Exam
• Aerial Surveys for Mortality USFS, WA DNR, and
  ODF

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• By Stand age 5-10 years, disease centers may show
  up as single or clumps of trees. However,
  significant diseased area is still not
  represented by above ground symptoms (possibly
  only 40 of the total inoculum sources are
  visible).
• Waiting to do land surveys in early age stands
  leads to severe losses if the presence of disease
  was underestimated.
• Loss of stocking and stocking with
  non-merchantable species.
• Lost future opportunities
• High cost of ground transect survey.

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• At harvest, Phellinus can be detected in the
  residual cull and long-butt sections left after
  logging. Movement of materials does not allow a
  determination of where the root rot is located on
  the landscape. The definitive stain
  characteristic of Phellinus quickly fades after
  felling.
• Fellers can be trained to mark stumps with the
  characteristic stain of Phellinus. Planters can
  switch to resistant species upon entering disease
  centers.
• No true quantitative determination on a acre
  basis to facilitate the regeneration planting.
• Regeneration stock sometimes requires 3-years
  planning to be ready for a particular unit.

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Ground based transect mapping can be highly
accurate when signs and symptoms are abundant.
Accuracy depends on width of the transect, and to
get to 50 meter level requires several
person-days to cover 100 acres.
Hollow stumps and root wads
Pitted laminated decay
Ectotrophic mycelium
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Aerial Based Color Photographic Identification of
Root Disease Centers

• Opportunities
• Reduce the cost and increase the acres surveyed
• Facilitate the better application of ground based
  transect surveys
• Address root-rot on a stand and landscape
  perspective
• Identify other agents

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Methodology

• Northwest Aerial Recon maintains a proprietary
  ownership of the specific methodology. However
  the general method is as follows
• Uses a standard color aerial photograph from
  12,000 ft elevation but shot with a longer focal
  length lens.
• Photos taken in mid to late summer (July) capture
  the best distinction between healthy and dead
  trees. Dead trees must be co-dominants or
  dominants in a stand or on the edge of stands to
  be detected.
• Dead tree (-s) are designated on the map as a
  30-foot circle so as to make area impact
  assessment possible.
• Typically, a 10 cruise of survey site is used to
  establish causative agents, with a follow-up
  survey to check areas with no target hits.

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Mortality centers can consist of small single
dead trees, multiple dead tree centers, and relic
snags from previous rotations.
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Survey Results The Yacolt Blockis a forest
management zone due north of Woodland, WA. Total
of some 1200 acres were flown and analyzed for
mortality by age class.
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Yacolt Survey Damage agents as verified by
ground survey of photo determined mortality
centers.
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Stand compartments in Yacolt forest and disease
centers with a 90 possibility of containing
mortality.
Ground survey found scattered mortality in DF
caused by high-water table and Armillaria root-rot
Segregation of Phellinus on drier site portion of
stand.
Heavy mortality from post-thinning bear kill
damage
Armillaria caused mortality on old skid trail
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Survey Results Yacolt BlockGround Truthing
Results

• Phellinus was the dominant root-rot agent (61)
  found in the ground survey another 39 of the
  root-rot centers were associated with Armillaria.
• The overall pattern of Armillaria caused
  mortality was associated with stress conditions
  such as periodic high water table, seepage zones
  and compacted soils .
• Windthrow common in disease centers with
  Phellinus and Armillaria.
• Root-rot caused mortality appears as a diffuse
  patch-work of dead trees, while rapid and severe
  mortality at a young stand age was associated
  with bear damage (masking other disease signs).
• Areas without designated mortality were found to
  mostly clean, although some disease pockets were
  missed.

22
Survey Results Silver Lake forest management
area is due east of Castle Rock, WA. Some 1500
acres were flown during the same 4-day period as
the Yacolt. Total acre and mortality acres
23
Survey Results Silver Lake BlockDamage agents
found in ground survey
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A portion of the Silver Lake aerial survey
showing disease centers with various stand
management areas.
Root-rot center
Red circles indicate high probability of cavity
nest sites around snag rich areas (pink circles)
Tree kill behind beaver dam
Young stand group tree kill by Mt. beaver
girdling.
Red alder planted in Phellinus infested stands
25
Survey Results Silver Lake BlockGround Truthing
Results

• Phellinus was the dominant root-rot mortality
  agent found in the ground survey (77.4 vs 22.6
  Armillaria).
• In a young stand (lt25yrs) an aggressive mortality
  pattern was associated with animal damage.
• A disperse pattern of mortality is more likely to
  be associated with root-rot.
• Armillaria found associated with old tractor
  skid-road compaction.
• A large tree patch kill was associated with high
  spring water table along riparian zone.

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Aerial Survey Validation Results-Root-rot and
Mortality Detection Comparisons- Yacolt Vs.
Silver Lake

• Yacolt
• Agent Present
• Root-Rot 72
• Other 23
• Miss 5
• Agent Present
• Dead Tree 95
• Miss 5

• Silver Lake
• Agent Present
• Root-Rot 67
• Other 28
• Miss 5
  
  
  
  
• Agent Present
• Dead Tree 95
• Miss 5

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Results/Conclusions

• Accuracy of detection of tree mortality by GIS
  location was similar at Yacolt and Silver Lake
  (95). Root-rot detection accuracy varied from
  67-72 (Silver Lake vs. Yacolt respectively).
• Specific mortality agents cannot be easily
  distinguished exceptions (a) heavy mortality
  at a young age (lt25yrs) most likely be associated
  with animal or abiotic damage (b) disperse
  mortality pattern in well-stocked DF stand is
  most likely root-rot.
• Spatial patterns of Armillaria mortality appear
  associated with areas or reoccurring stress from
  compaction, periodic high water tables or seep
  zones. In wetter areas, there appears to be a
  gradual transition from DF to alder, hemlock or
  cedar.

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Results/Conclusions

• Some Method Limitations
• Quiescent disease centers (root-rot) with no
  standing dead component can not be detected.
  These may be occupied by resistant species such
  as brush, big-leaf maple, alder or Cedar.
• At a young stand age lt10-years, not enough
  contact with existing Phellinus inoculum has
  occurred to accurately depict stand inoculum
  levels and there is inadequate height
  differential to be accurately used by NAR to ID
  mortality.
• High levels of other disturbance agents (bears
  or Mt. Beavers) interferes with detection of
  root-rot.
• Photos are best done late June through
  mid-August, which limits the total acres which
  can be sampled.

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Management Solutions

• Accurate locations of current mortality levels on
  a landscape and stand basis can be obtained for
  2-2.50/ac.
• Mortality maps can be used to more effectively
  investigate causative agents using limited
  manpower to validate disturbance agents and to
  make impact assessments.
• The information provided should aid in the
  decision making process at various stand ages
• (15-25) stocking levels and thinning
  recommendations, skip areas etc.
• (30-40) commercial harvest-windthrow potential,
  early rotation harvest
• (50) harvest-planting unit classification,
  future regeneration planning.
• Riparian Management Zones- classification of wind
  throw potential based on root-rot or other
  factors.

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Management Solutions

• Wildlife surveys (bears, birds, cavity nesters,
  bats etc.) associated with dead snags or downed
  trees could be facilitated using the located dead
  tree snags. Age class of stand could be used to
  estimate snag size prior to survey
• Mortality areas have greater potential for
  association with unique understory plants and
  biodiversity.

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Ground based floristic surveys conducted in
root-rot centers show a diversity of plant
species in an other wise conifer landscape.
32
Survey of snag centers show a important link
between root-rot caused mortality and wildlife.
These aerial surveys can have potential to aid in
the identification of unique forest biotopes.
33
Estimates of aerial survey data show that
root-rot is creating a large number of snags on a
per acre basis. Such scattered mortality on a
landscape basis is difficult to detect and manage.
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Next Steps

• Select a stand component to develop a more
  specific stand recommendation based these
  findings, and using other management decision
  making tools (FIRS Tree Growth Model).
• Use other data bases such as soils and
  topographic features in GIS to investigate the
  association, if any, between disease occurrence
  and impact.
• Input specific stand data into the USFS
  root-disease model to predict stand losses over
  the current and future rotations.
• Further explore the wildlife/root-rot
  interrelationship.