Forest Health and TSR: how do pests “move the needle”?

Stefan Zeglen, Forest Pathologist, West Coast Region

Jim Brown, Senior Analyst,

Forest Analysis and Inventory Branch

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Scale matters

CSC Winter Workshop, Nanaimo, BC February 27, 2014

The Mythology of Pests

Myth 1: Pests don’t matter on the Coast like they do in the Interior.

Myth 2: Even if pests are present they never do enough damage to worry about.

Myth 3: Pest losses are already accounted for in growth & yield models.CSC Winter Workshop, Nanaimo, BC February 27, 2014

Accounting for pest impacts

Most basic: Unsalvaged loss estimates or non-

recoverable loss estimates (NRL) More refined:

Operational Adjustment Factors (OAF) for model estimates

Catastrophic loss estimates: One-off calculations for large scale

events

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Unsalvaged loss estimates Required component of TSR data packages. Usually include losses to wind, wildfire,

landslides, insects and diseases. Data used comes from wildfire records,

aerial overview surveys (AOS) and other reports.

Usually provided as a m³/year adjustment. Tempered by district knowledge of salvage

rates for various events. Updated each TSR cycle.

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Operational Adjustment Factors

Used to adjust model output (e.g., TASS/TIPSY) of stand volume projections.

Restricted to a set of insects or diseases in a defined area (e.g., root disease in the CDFmm and

CWHxm1) Data is usually sourced from fixed plots

(e.g., G&Y PSP, research trials) measured over time.

Updated as new information becomes available.

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Catastrophic loss estimates

Rarely necessary. Attempts to predict impact on a large

scale from biological spread and mortality factors.

Most recent example is the Provincial Level Projection of the Current Mountain Pine Beetle Outbreak (M Eng and A Walton).

Intended to drive decision-making and mitigation response over a large area.

CSC Winter Workshop, Nanaimo, BC February 27, 2014

CSC Winter Workshop, Nanaimo, BC

Factoring Forest Health into Timber Supply ForecastsSome Considerations What are the forest health factors influencing the

forest What stand types / tree species / ages are affected What are the ST/ LT influences of these factors:

timber yield (recoverable volume) timber grades and species mix stand development, growth and future yields

Are losses constant over time (endemic) or periodic (epidemic)

To what extent is it possible to salvage damaged timber (considering access, economics, shelf life)

Unsalvaged loss estimates

Often applied as a constant reduction in the periodic supply, though estimates could vary over time or by forest type if information supports doing so.

Estimates are based on observed losses, taking into account salvage and recovery, ideally over the previous 10 years or more.

Recognized uncertainty that historic losses = future losses (given changing economics, management practices and climate)

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Unsalvaged loss estimates

Cause of loss

Annual loss within the

THLB (m³/year)

Salvage rate (%)

Annual unsalvaged

losses within the THLB (m³/year)

Wind 3100 25 2340

Fire 16500 0 16500

Mountain Pine Beetle 400 0 400

Douglas-fir Bark Beetle

8800 50 4400

Spruce Beetle 200 0 200

Western Balsam BB 3100 0 3100

Total 33120 26940

CSC Winter Workshop, Nanaimo, BC February 27, 2014

Example, Fraser TSA, 2013 TSR

Operational Adjustment FactorsIn Timber Supply Analysis

Natural stands are modelled using VDYP7, often with the assumption that endemic losses are reflected in the net volume estimates.

Managed stands are modelled using TASS/TIPSY. Since TASS models fully stocked stands free of significant health factors, OAFs are necessary.

A standard OAF1 of 15% was developed from research trials to account for stands gaps and losses that act over the life of the stand.

Locally defined OAFs are needed to account for accute outbreaks or other endemic factors not accounted in the standard OAF1

Ideally local defined OAFs are based on stand monitoring data (e.g. a YSM/CMI) including field derived volume estimates.

CSC Winter Workshop, Nanaimo, BC February 27, 2014

CSC Winter Workshop, Nanaimo, BC

Operational Adjustment Factors

A YSM project in the Morice TSA targeted stands between 15 and 50 years old

Initial results suggested that inventory site index and TIPSY volumes are underestimated.

The project also provided information to assess the incremental forest health impact of pine stem rusts

There are a number of approaches that could be used to adjust MSYT for forest health factors using YSM results

CSC Winter Workshop, Nanaimo, BC

Operational Adjustment Factors

0 5 10 15 20 25 30 35 40 45 50 55 60 65 70 75 80 85 90 951000

500

1000

1500

2000

2500harvest ('000s m3/year)

years from 2014

OAF1 (10%) for stem rusts

A worst-case scenario assumes affected trees will die at rotation and applies an incremental OAF1 to account for losses. This is similar to how we typically adjust for root disease on the coast

Operational Adjustment Factors

CSC Winter Workshop, Nanaimo, BC

0 10 20 30 40 50 60 70 80 90 1000

500

1000

1500

2000

2500

3000

3500

4000

None1000/ha 2000/ha

Stand age

Liv

e t

rees p

er

ha Natural

Regen.

0 10 20 30 40 50 60 70 80 90 1000

500

1000

1500

2000

2500

3000

3500

4000

None - no rustNone - 25% rust

Stand age

Liv

e t

rees p

er

ha

Natural earlyRegen. rust

Alternatively, TASS can be used to simulate the change in stand dynamics from a (e.g. western gull rust)

Early rust event

adapted from J. Goudie & I Cameron 2014

CSC Winter Workshop, Nanaimo, BC

Operational Adjustment Factors TASS allow for a more complex simulation of stand

response to early mortality and growth losses.

0 10 20 30 40 50 60 70 80 90 1000

500

1000

1500

2000

2500

3000

3500

4000

None - none - noneNone - 25% - noneNone - 25% - 2%

Stand age

Liv

e t

rees p

er

ha

Natural rustRegen. early late

Early rust event

0 10 20 30 40 50 60 70 80 90 1000

50

100

150

200

250

300

350

400

450

500

None - none - noneNone - 25% - noneNone - 25% - 2%1000/ha - 25% - 2%2000/ha - 25% - 2%

Stand age

Merc

hanta

ble

volu

me (

m3/h

a

-6%-15%

Natural rustRegen. early late

adapted from J. Goudie & I Cameron 2014

CSC Winter Workshop, Nanaimo, BC

Operational Adjustment Factors

YSM provides a means of collecting data on the effects of forest health factors and developing assumptions to account for them in T.S.A.

When using OAFs one must understand how the factor alters the dynamics and conditions of a stand and how well the model effectively simulates those dynamics.

TASS modelling and/or custom OAFs may be the most appropriate means of adjusting for both tree mortality and live-stem volume losses.