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Pelletier, G., Landry, D., Girouard, M., 2016: A Tree Classification System for New Brunswick. Northern Hardwoods Research Institute, Edmundston, New Brunswick, 53 p.

Authors:
  • Northern Hardwoods Research Institute inc.
Northern Hardwoods Research Institute
165, boulevard Hébert
Edmundston, New Brunswick
E3V 2S8
Telephone : 506 737-4736
Fax : 506 737-5373
E-mail : info@irfn-nhri.org
Website : www.irfn-nhri.org
A Tree Classification System for
New Brunswick
Version 2.0 September 2016
iii
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Notes about the Second Edition
The Tree Classification System for New Brunswick has been in place since 2012. It has since been
gradually implemented in many jurisdictions for different purposes such as in forest sample plot
inventory (FDS and PSP) by the New Brunswick Energy and Resource Development and in a variety of
research projects by organisations in New Brunswick, Quebec and Maine, USA. Throughout its
implementation, comments and suggestions provided by different users have been collected. This
prompted a process to prepare a second edition of the Tree Classification System for New Brunswick.
To accomplish this task, valuable inputs were obtained from Bruno Boulet (forest engineer, pathologist
and entomologist from Ministère des ressources naturelles et de la faune du Québec). During a
workshop he facilitated, the discussion lead to improvements of the Risk key by observing external
defects . Additionally, some fine adjustments were made to the Form determination.
The improvements to the Second edition are therefore, mainly with regards to the two determination
keys (Form and Risk). The document was edited by HNRI staff: Sharad Baral, Emmanuelle Fréchette,
Pamela Hurley-Poitras and Monique Girouard. Field validation of the current version of the two
determination keys was done by Pamela Hurley-Poitras.
iv
Adapted from
A Tree Classification System for New Brunswick, Gaetan Pelletier, 2012
Project Manager and Classification System Development
Gaetan Pelletier, Northern Hardwoods Research Institute
Coordination, Research and Editing
Diane Landry, Experimental Forest, School of Forestry
Université de Moncton, campus d’Edmundston
Research and Editing of Chapter 3
Monique Girouard, Northern Hardwoods Research Institute
Translation
Martine Mercure, Northern Hardwoods Research Institute
Revision and Quality Assurance
Megan de Graaf
Layout
Amélie Jarret, Ajarret Consultante
Photography
Marcel Cyr, CFDS Entreprise Inc.
Cover Page Photograph
Pamela Hurley Poitras, Northern Hardwoods Research Institute
Revision Team
Chris Bringloe, Department of Natural Resources, Province of New Brunswick
Chris Hennigar, Department of Natural Resources, Province of New Brunswick
Edwin Swift, Natural Resources Canada, Canadian Forest Service
Eric R. Labelle, Northern Hardwoods Research Institute
Laura Kenefic, Northern Research Station, United States Department of Agriculture Forest Service
Michel Soucy, School of Forestry, Université de Moncton, campus d’Edmundston
Ralph Nyland, College of Environmental Science and Forestry, State University of New York
v
Foreword
The Northern Hardwoods Research Institute (NHRI), located at the Edmundston campus of Université de
Moncton, is a research center supported by a partnership among four forest companies, the Université
de Moncton, the Government of New Brunswick, and the Government of Canada. Its mission is to
encourage the sustainable development of hardwood resources and to support, through applied
research activities, the optimal development of our hardwood forests for the benefit of businesses and
organizations working in the forestry sector.
This document introduces a classification system that is both practical and innovative, to assist forestry
professionals, managers and researchers to make silviculture decisions, predict product distribution, and
determine harvesting costs, etc.
Acknowledgements
The NHRI would like to thank the following organizations for their support:
Atlantic Canada Opportunities Agency
Acadian Timber Corp.
AV Group, Aditya Birla Group
Groupe Savoie Inc.
J.D. Irving Ltd.
The Institute expresses its gratitude to the following people who were instrumental in the development
of the classification system:
Adam Dick, Department of Natural Resources, Province of New Brunswick
Edwin Swift, Natural Resources Canada, Canadian Forest Service, Canadian Wood Fibre Centre
Michel Soucy, School of Forestry, Université de Moncton, campus d’Edmundston
André Cyr, Experimental Forest, School of Forestry, Université de Moncton, campus d’Edmundston
Finally, we wish to thank those who field-tested our system and provided valuable comments and
criticism namely :
Marcel Cyr, CFDS Entreprise Inc.
Sylvain Caron (and crew), Four Best Management Inc.
Roger Gagné, Natural Resources Canada, Canadian Forestry Service, Canadian Wood Fibre Centre
© Northern Hardwoods Research Institute 2013
vi
The contents of all pages, including but not limited to text, graphics, logos, or registered trademarks,
have been created by the NHRI or its employees or are used herein under license and may not be used,
copied or reproduced in whole or in part for any purpose without expressed permission.
How to cite this document:
Pelletier, G., D. Landry and M. Girouard. 2016. A Tree Classification System for New Brunswick.
Version 2.0. Northern Hardwoods Research Institute. Edmundston, New Brunswick.
vii
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table of Content
FOREWORD __________________________________________________________________ V
ACKNOWLEDGEMENT _________________________________________________________ V
LIST OF TABLES ______________________________________________________________ VIII
LIST OF FIGURES _____________________________________________________________ VIII
INTRODUCTION ________________________________________________________________ 1
1. ELEMENTS OF TREE FORM AND VIGOR ___________________________________________ 3
1.1 Importance and impact of tree form ____________________________________________________________ 3
1.2 Importance and impacts of tree vigor ___________________________________________________________ 6
1.2.1 Recognize defects, injuries and signs of decay ________________________________________________ 10
2. COMPONENTS OF THE TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK __________ 15
2.1 Evaluating tree form ________________________________________________________________________ 15
2.2 Evaluating risk (of deterioration and mortality) __________________________________________________ 32
3. LINKS WITH OTHER SYSTEMS __________________________________________________ 45
3.1 The AGS / UGS and Six class systems (USA and Ontario) ___________________________________________ 45
3.2 The MSCR Classification system (Québec) ______________________________________________________ 46
3.3 The ABCD classification system (Québec) _______________________________________________________ 47
3.4 The Petro classification system (Nova Scotia) ___________________________________________________ 47
4. FUTURE WORK _____________________________________________________________ 48
BIBLIOGRAPHY _______________________________________________________________ 49
APPENDICES _________________________________________________________________ 50
APPENDIX A - SAMPLE IMAGES OF FORM RATINGS __________________________________ 51
APPENDIX B - SAMPLE IMAGES OF RISK OF LOSING VIGOR RATINGS ____________________ 56
viii
List of Tables
Table 1. Description of the eight form classes ............................................................................................ 16
Table 2. Summary of tree forms .................................................................................................................. 17
Table 3. Definition of terms used in the determination of form ................................................................ 20
Table 4. Examples of tree form ratings ....................................................................................................... 24
Table 5. Description of the four classes of risk ............................................................................................ 33
Table 6. Summary of risk classes ................................................................................................................. 34
Table 7. Joint effects of tree size and vigor on tree mortality and probability of product downgrade ...... 34
Table 8. Definitions of terms used when rating the risk of losing vigor ...................................................... 37
Table 9. Summary of risk ratings including images ..................................................................................... 43
Table 10. Links between the New Brunswick tree classification system and the AGS/UGS system ........... 45
Table 11. Links between the New Brunswick tree classification system and the Six class system ............. 46
Table 12. Links between the New Brunswick tree classification system and the MSCR classification system
..................................................................................................................................................................... 46
Table 13. Links between the New Brunswick tree classification system and the ABCD classification system
..................................................................................................................................................................... 47
Table 14. Links between the New Brunswick tree classification system and the Petro classification system
..................................................................................................................................................................... 47
List of Figures
Figure 1. Observable defects (minor, moderate and major) (adapted from OMNR 2004) ___________ 13
Figure 2. Determination key for determining form ("F" rating) ________________________________ 18
Figure 3. Determination key for determining risk of losing vigor ("R" rating) _____________________ 35
1
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Introduction
For many forest management activities, the knowledge of single-tree external stem attributes is critical
to the decision-making process. As an example, it is important to take into account tree vigor and health
when choosing a silvicultural system and prescriptions. Tree form and crown shape are in turn useful
information in determining product potential, as well as predicting harvesting and processing costs.
Currently, there is no known tree classification system in New Brunswick that provides the necessary
information to make silvicultural decisions, predict product distribution, and determine harvesting and
processing costs. Tree classification systems used in other jurisdictions were investigated, but we could
not find one that meets all of our requirements. While most of the existing systems only provide
information for a single purpose such as product determination or overall health, others provide a
general subjective rating that limits usefulness at later times and for purposes that are different than
that of the original intent.
To be useful for making forest management decisions, a tree-level classification system should not only
consider the current state of the tree but also allow the assessor to predict the long-term potential of
the whole tree by looking at tree form and vigor (health). This information is used not only to estimate
the product value of a tree at the present time but is also used to predict future growth and the
evolution of its quality.
Given these needs, it was decided to create a new classification system that would have the following
attributes:
Able to assist in silvicultural decisions, determine product potential and harvesting implications;
Applicable at the tree level but integrated in inventory and forest management planning
activities at all scales;
Easy to implement, flexible and adaptable;
Focused on key variables rather than determining “grades”;
Linkable with existing systems from other jurisdictions;
Predictions such as product breakdowns for tree classes are outputs determined through ad-hoc
studies.
Despite its many features, the tree classification system presented in this guide is a simple tool for
objectively classifying hardwood trees as well as softwoods. It is intended to become a reference system
for forestry professionals, managers and researchers creating a common language to describe trees.
2
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
In addition to improve the manager’s ability to characterize trees, the new tree classification system will
enhance the overall picture of the forest inventory and will also be used in forest development surveys
(FDS), permanent sample plots (PSP), research sites, and in other forest inventory programs. This system
should also be integrated with the growth & yield processes already in place in New Brunswick. It will
also provide data to generate management information from remote sensing tools, linking the observed
characteristics with the key tree attributes.
Note that log grading is not covered by this system or in this guide. This type of classification represents
a different activity, usually presented in scaling guidelines of the relevant jurisdiction.
Str ucture of the guide
This guide is divided into three main sections: a first section presents an overview of the concepts of tree
form and vigor, a second section presents the components of the classification system and finally, a third
section proposes links with other existing classification systems.
Throughout the guide, pictures and diagrams have been
included to provide examples in order to help the reader
understand the material. Additional images are presented in
the appendices.
Field tool!
Once familiar with the tree
classification system presented in
this guide, print the determination
keys on pages 17 and 34 on
waterproof paper and bring them in
the forest as a handy reminder.
3
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
1. ELEMENTS OF TREE FORM AND VIGOR
There are several methods of classifying trees, but most consider form, vigor or other criteria separately.
Before presenting the details of the tree classification model developed for New Brunswick, here is an
overview of some important concepts about the tree form and vigor.
1.1 Importance and impact of tree form
Along with species and tree diameter, tree form is a key element to consider when characterizing trees.
It is a metric describing the geometry of a tree (ideotype) used to describe current and potential value
(type and quality of product).
First, tree form can help predict current and future product distribution
1
within the tree. Indeed, tree
form affects product potential according to their location on the tree. For example, defects present on
the first 5 meters of the trunk greatly affect the volume of lumber available since this section usually
represents nearly 60 % of the total usable volume (Boulet 2005). In addition, given that the goal is to
generate the greatest value for products now or in the future, tree form analysis can enable the planner
to evaluate the consequences of silviculture decisions such as harvesting valuable timber (e.g. veneer log
potential).
Tree form also helps us understand the factors that must be considered in operations planning and in
determining harvesting costs by providing clues to the operability challenges that are caused by tree
form. For example, certain tree shapes cause difficulties during de-limbing and processing that result in
lower productivity and higher wood costs or, in extreme cases, could limit the choice among harvesting
systems.
Trees may present forks that can compromise survival, by making them more vulnerable to disturbances
or by creating entry points for pathogens or exposing injured sections to micro-organisms that can
eventually damage the tree (Boulet 2005). Consequently, some forms of trees could become priorities
for removal (e.g. a tree with significant lean) or trigger a particular silvicultural regime.
In the following section, we review common tree malformations and some examples of their impact on
product potential, harvesting costs, and implications for silvicultural alternatives when the goal is to
maximize sawlog production.
1
Veneer, lumber, pulp or chip.
4
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Mu ltiple trees
For timber production, a tree should ideally have a single stem; however, it is common to see tree
clusters with two or more trees from the same point of origin and fused at the base when trees are
regenerated from stump sprouts or root suckers (Boulet 2005). The presence of tree cluster can affect:
Product distribution
The potential for high value products is limited. Tree clusters are usually smaller than if they
grew as a single tree. Also, it is commonly observed that trees in a clump have a heart that is
displaced from the geometric center of the stem (off-center pith).
Harvesting costs
Usually, the cycle time to process all of the trees in a group is greater than processing them if
they were individual trees. The ability to position harvesting heads is compromised and more
time is required to handle trees in a cluster than single trees of the same size.
Silvicultural decisions
While tree distribution metrics for a stand with a high incidence of multiple trees may be
identical (on paper) to one with single trees only, the implications for silviculture choices are very
different in practice.
Fo rks and crowns con t a ining la rge br anches
Some trees have large forks or crowns with large branches. These can affect:
Product distribution
The presence of significant forks on trees limits trunk length. When it occurs in the section of a
tree that would normally contain a sawlog (i.e. in the first 5 meters), the impact on overall value
is very important. Also, large branches may or may not contain certain product types as they
have a tendency to curve as a result of competition for light.
Harvesting costs
It usually takes more time to de-limb or process trees with large limbs and forks. It may increase
production costs and often causes mechanical damage to the stem that can downgrade
products. A high frequency of trees with large limbs and forks may influence the type of
equipment used during forest operations.
5
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Silvicultural decisions
V-shaped forks are more vulnerable to cracks, making them more likely to be colonized by
pathogens that cause decay (Boulet 2005) and deterioration of economic value. Trees with large
limbs and forks should be prioritized for removal as they are considered unacceptable growing
stock (UGS). When the proportion of these types of trees is high in a stand, the silvicultural
options may become limited.
Cu rvature of the tree ( sweep)
It is common for trees to have light sweeps, but some trees have one or multiple significant curves in the
first 5 meters of the trunk. This can affect:
Product distribution
A significant curve on a tree considerably reduces the amount of usable wood for lumber and
thus downgrades the log (GQ 2012, Boulet 2005, OMNR 2004).
The presence of curves on a stem also leads to the formation of tension and compression wood
fibers.
Harvesting costs
Trees that have significant sweeps are more difficult to process and de-limb. Operators will often
need to slowdown the processing in order to adjust their bucking decisions to account for the
defect.
Silvicultural decisions
Because sweeps affect the economic value of a tree, which trees to keep or remove becomes a
significant silviculture decision for a stand. In stands where there is a large number of crooked
trees it can affect the eligibility of silviculture regimes.
In clinati o n of th e tree ( lean)
Trees with significant lean are considered in a precarious situation because they are more vulnerable to
falling due to strong winds or injury under the weight of snow or ice. The condition normally exists
where competition surrounding a tree is uneven.
These trees are likely to die standing or get up-rooted before the next cutting cycle (Boulet 2005).
Quebec considers that the maximum acceptable level of inclination is 30° deviation from the vertical axis
(Boulet 2005), while Ontario considers the maximum acceptable level of inclination to be 10° (OMNR
2004).
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A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Product distribution
Excessive lean in trees can produce wood property issues such as the growth of tension and
compression wood. Furthermore, the heart of the tree is generally displaced geometrically when
compared to trees that grow under normal conditions.
Harvesting costs
Leaning trees may be difficult to fell because the direction is already pre-determined. Feller-
bunchers, harvesters and chain saw operators productivity will be reduced in order to override
the natural felling direction when it is not appropriate. Also, damage to crop trees and the felled
tree may occur because of mitigation measures used during felling. Re-directing a tree is a
difficult task and is compounded when on slopes.
Silvicultural decisions
Trees with excessive lean should be prioritized for cutting. If the presence of leaning trees is
disproportionally high in a stand, it can affect tree selection and the choice of a silviculture
regime.
1.2 Importance and impacts of tree vigor
Tree vigor can be defined as its ability and potential to grow (OMNR 1990 in OMNR 2004) and is a
function of competitive status and health. It is a component of risk which indicates the likelihood of
deterioration that will cause a reduction in value, or of mortality.
Measuring vigor must therefore assess the overall tree health and predict its evolution over time. It can
be evaluated by observing various parameters of a tree’s external appearance, such as crown shape and
bark appearance. Other environmental factors such tree position within the cohort and competition
level may, in turn, indicate the risk that a tree may lose vigor over time. In addition to these parameters,
it is important to evaluate tree defects causing loss of vigor (e.g. injury and decay) and the conditions
Risk
Vigor
Health
status
Competitive
status
Form
7
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
that contribute to increase the risk of vigor loss such as the presence of major defects (e.g. significant
fork) and vulnerability to natural disturbances (e.g. tree inclination) (OMNR 2004, Boulet 2005).
Traditionally, the identification of defects
2
affecting tree vigor is the first step in tree classification
(Calvert and Petro 1993). Since partial cutting aims at releasing crop trees and promoting regeneration of
desirable species, it is important to carefully choose trees to harvest. A poor choice may reduce overall
stand vigor and increase mortality in the residual stand, thereby resulting in a significant drop in
productivity. To counter this, it is essential to develop the ability to recognize trees that may die first (as
a gradient of probability through time) by identifying defects that are present (Boulet 2006). It is
important to remember however that this may not apply in the same manner to species that
compartmentalize well, depending on the type of defect.
According to their impacts on tree vigor, the OMNR (2004) classifies defects into three broad categories:
minor defects (trees with these defects should not lose vigor during the next cutting cycle);
moderate defects (trees with these defects will slowly lose vigor during the next cutting cycle);
major defects (trees with these defects will quickly lose vigor before the next cutting cycle).
Thus, the combination of species, diameter, tree form (section 1.1) and vigor (health status and
competitive status) are the key elements to guide forestry professionals in their decision making.
Tree vigor is a key driver to predict current and future product distribution within the tree. Indeed,
depending on the severity and location of defects, the potential for high-value forest products can be
severely limited (OMNR 2004).
Tree vigor also helps understand factors that should be considered in operations planning and
determining harvesting costs by providing clues as to the operational limits imposed by the current and
future value of the tree. For example, a less vigorous tree is likely to continue losing value over time and
reduce operation profitability. But, as stated below, it may not always be the case.
Tree vigor will inform removal prioritization (e.g. those losing vigor) and is a key input in the selection of
a silvicultural system (regime) to use. The OMNR (2004) also points out that a successful single-tree
selection treatment is characterized by residual trees that are vigorous, or potentially vigorous, and will
increase in value. But, it also points out that even trees with low vigor can increase in value if they have
the chance to gain and maintain their maximum vigor for a sufficiently long period after the intervention.
In this context, the Quebec Government prioritizes the harvest of trees that may tip over, break, perish
2
Note that Section 1.2.1 presents the identification concepts of tree defects.
8
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
or deteriorate over time while healthy trees or trees with no serious defects (that will still be healthy in
25 years) represent acceptable growing stock (Boulet 2005).
Here is an overview of visible signs that may indicate poor tree vigor and some examples of their
potential impacts on product distribution, harvesting costs, and silvicultural options when the goal is to
maximize sawlog production.
Pr e sence of fruit ing bodi es (Fu ngus)
Fruiting bodies are the visible part of fungi present within a tree. These structures carry the spores (the
reproductive units of the fungus) and their presence on a tree indicates that the inside of the tree suffers
from a decay that is likely very significant (OIFQ 2003, GQ 2012). Although there are many different
types of decay-associated fungi that can affect trees in various ways (Boulet 2005), their presence is
usually an indicator of a serious loss of tree vigor.
For example, the presence of fungus can affect:
Product distribution
The presence of fruiting bodies on a tree indicates that the quality of the wood can be greatly
compromised. In various stages of decomposition, it is not usable and represents a significant
loss in volume.
Harvesting costs
The presence of decayed tree sections may require further processing to work around affected
areas.
Silvicultural decisions
Since tree decay reduces net merchantable volume to a point where it may even result in
negative long-term growth (Boulet 2005), its presence is a key input in determining removal
priority and the choice of a silviculture regime.
Ho l es and injuri e s on the main s tem
Cavities on the main stem, such as holes and injuries caused by animals, insects or humans are defects
that have different impacts on products, but are also entry points for pathogens and insects that may
affect tree vigor.
9
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Product distribution
Cavities or holes affect product potential in two ways; by limiting the length of usable wood and
by extending internal decay into the trunk.
Harvesting costs
Notable decreases in machine productivity are associated with the extra time required to
merchandize trunks.
Silvicultural decisions
An injured tree has an increased likelihood of mechanical failure, and a greater probability of
being colonized by various pests; the potential impacts of these openings on a tree are similar to
those of trees with fruiting bodies and indicates a high priority for removal.
Fo rks and splits
Some stems have large forks or crowns with large branches. These forms can affect:
Product distribution
Defects such as large branches reduce the length of the usable trunk and impact current and
future potential products (product basket). Their presence also contributes to the likelihood of
splits that in turn affect the proportion of discolored wood (Boulet 2005). These features also
increase the proportion of knots and, eventually, rot.
Harvesting costs
The presence of forks and splits decreases the productivity of machines such as processors and
delimber, and therefore increases cost.
Silvicultural decisions
Silviculture options are limited when the proportion of trees with large limbs and splits is high or
un-evenly distributed.
Co mpetit i ve stat us
A tree’s position in the cohort (crown class) and the relative amount of sunlit foliage will reflect, among
other things, its competitive ability to acquire and process resources required for growth
(photosynthesis). Indeed, the growth condition of a tree and the availability of resources greatly
influence the tree’s growth and development. The availability of light is the most limiting factor for its
10
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
growth and development (OIFQ 2009). Generally speaking, trees under significant competition (by other
trees) or those with unhealthy crowns have limited ability for photosynthesis. Notwithstanding the
impact of the species degree of shade tolerance, under those conditions, the risk of losing vigor is likely
to be high (Boulet 2005).
Product distribution
Trees that have had poor vigor resulting from strong competition for long periods tend to be
smaller in size. Trees that are older for a given diameter have a higher likelihood of being
damaged with time. Eventually, older trees contain lower proportions of valuable wood
products or exhibit signs of deterioration.
Harvesting costs
Processing time increases for trees showing signs of decay due to stress.
Silvicultural decisions
Trees under stress are more likely to be invaded by damaging insects and pathogens, and
represent logical candidates for harvest. Signs of stressed trees include poorly healed branch
stubs, large open and decayed stem wounds, and dead branches in the crown (Calvert and Petro
1993). When they represent a high proportion of the stand, then silvicultural options are limited.
In summary, to determine tree vigor we must consider the degree of competition and look for signs that
indicate potential health issues such as the presence and severity of:
Fruiting bodies on the main stem - indicating internal rot and wood discoloration (Kenefic 2012);
Holes in the main stem - indicating a structural weakness that might lead to breakage (Kenefic 2012);
Dead or dying main branches from the upper crown (Kenefic 2012);
Points of weakness (forks, stilted roots from growing on a stump, significant lean; Nyland 2012);
Evidence of decay or entry point for decay (bleeding, ants, sapsucker holes, trunk wounds or
swelling, broken crown; Nyland 2012);
Other indicators of poor health (thin or discolored crown, branch stripping by porcupines etc.;
Nyland 2012).
1.2.1 Recognize defects, injuries and signs of decay
As showed in the previous section, defects, injuries and
decay are factors that may significantly affect tree vigor. It is
therefore important to be able to recognize signs of their
Reference guide
Défauts externes et
indices de la carie des
arbres.
Gouvernement du
Québec, 2005.
11
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
presence on trees. Even experienced professionals may from time to time feel uncomfortable with the
identification of pathological, entomological, and abiotic problems. While this guide is not intended to
be a tool for identifying specific defects or decay, its purpose is to present some basic criteria to help
recognize key signs and symptoms. It is advisable to acquire existing material on the subject such as the
Québec guide Défauts externes et indices de la carie des arbres, which is a very complete tool.
The reference guides listed below also present different pictures of defects, injuries and signs of decay
and may be useful in helping identify them when observing a tree:
Ontario Ministry of Natural Resources. 2004.
Ontario Tree Marking Guide, Version 1.1.
Ont. Min. Nat. Resour. Queen’s
Printer for Ontario. Toronto. 252 p.
http://www.mnr.gov.on.ca/stdprodconsume/groups/lr/@mnr
/@forests/documents/document/mnre000526.pdf
Carpenter, R.D., Sonderman, D.L., Rast, E.D., Jones, M.J. 1989.
Defects in hardwood timber.
Agriculture Handbook No. 678.
United States Department of Agriculture. Washington, DC. U.S. 88 p.
http://www.nrs.fs.fed.us/pubs/aghandbk/AgHandbook678.pdf
Nova Scotia Ministry of Natural Resources. 2005.
Hardwood tree grading field guide.
Nova Scotia Department of Natural Resources,
Forest Inventory Division, 69 p.
http://www.gov.ns.ca/natr/forestry/reports/sawlogguide.pdf
Shigo, A.L. and Larson, E. 1969.
A Photo guide to the patterns of discoloration and decay in
living northern hardwood trees.
U.S.D.A. Forest service research paper NE-127.
Northeastern forest experiment station, Upper Darby, PA.
Forest service, U.S. Department of agriculture, 100 p.
http://www.nrs.fs.fed.us/pubs/rp/rp_ne127.pdf
Shortle, W.C., Dudzik, K.R. 2012.
Wood decay in living and dead trees: A pictorial overview.
Gen. Tech. Rep. NRS-97. Newtown Square, PA: U.S.
Department of Agriculture, Forest Service, Northern Research Station. 26 p.
http://www.nrs.fs.fed.us/pubs/gtr/gtr_nrs97.pdf
12
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Some defects that affect stem value are difficult to recognize; however, several methods of estimating
defects from external signs were developed. They are usually categorized into two groups, biotic defects
(caused by the action of living organisms such as fungus or insects) or abiotic defects (caused by the
action of nonliving factors such as wind or freezing rain). These external indicators are important
components in assessing tree vigor (OMNR 2004). Damage from previous harvesting activities are
another major source of defects. They range from scrapes and wounds on the stems and roots to broken
limbs and boles in severe cases. The Ontario Ministry of Natural Resources (2004) has prepared a
methodology to classify defects (minor, moderate and major) depending on the magnitude of their
impacts on tree vigor (Figure 1).
13
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Figure 1. Observable defects (minor, moderate and major) (adapted from OMNR 2004)
According to the authors, there are three types of minor defects and their presence on a tree should not
lead to a loss of health over the next cutting cycle. The 16 types of moderate defects have more impact
on tree vigor since their presence causes a tree to degrade or slowly decay and lose vigor during the next
cutting cycle. Finally, the 20 types of major defects, such as fungus and canker, have the greatest impact
on tree vigor and their presence indicates that the tree may quickly lose vigor before the next cutting
cycle.
Minor defects
- Crooks and sweep
- White-faced scar
- Burl
Moderate defects
- Mossy top
- Sugar maple borer
- Spiral seam
- Frost cracks and seams
- Small darkface scar
< 900 cm2
- Sunscald
- Black knot
- Epicormic branching
- Pine engraver beetles
- Feeding damage
- Mechanical damage
- Broken or dead top
crown dieback
- Lightning injury
- Root wounds
- Fire scar
- Lean > 10°
Major defects
- Spine tooth fungus
- Punk knot
- Coal fungus
- Yellow cap fungus
- Shoestring root rot
- False tinder fungus
- Clinker (cinder) fungus
- Eutypella (cobra)
canker
- Nectria (target) canker
-Artist’s conk
- Butt flare (barrelling)
- Black bark
- Large darkface scar
> 900 cm2
- Fire scar
- Fomes root rot
- Tomentosus root rot
- White pine blister rust
- Velvet-top fungus
- Red ring rot
- White pine weevil
14
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
As mentioned previously, tree form, species, and diameter are useful parameters for predicting current
and future product potential from trees. Although some aspects of tree form influence the risk of losing
vigor (e.g. significant fork that tends to create a split), it is mainly the assessment of health and
competitive status that are key for predicting the risk of losing vigor.
This section has provided important information about tree form and vigor that constitute the basis of
our new tree classification system of New Brunswick presented in Chapter 2.
In summary:
Tree form is a stand-alone metric used to describe the geometry of a tree and is valuable to
determine product distribution, harvesting equipment productivity and risk of mechanical failure or
to lose value;
Competitive status indicates the amount of stress a tree is under from the competition of other trees
and plants;
Health is assessed by verifying for the presence and severity of features that may limit the trees
future growth;
Vigor is function of health, competitive status and tree size;
Risk is an index that considers vigor and tree form used to predict the likelihood of mechanical
failure leading to tree mortality and can be used to infer potential losses in product value;
All of those elements are critical to make silvicultural decisions.
15
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Forest Inventories
Easily integrate the tree
classification system to your
regular forest inventories by
adding two additional fields:
code "F" and code "R".
5 m
Total height 12 meters
3.25 m
Total height 6.5 meters
2. Components of the Tree Classification System for New Brunswick
The tree classification system is a tool used to evaluate standing trees according to four variables,
primarily their species and their diameter, but also their form and risk of mortality or of losing value. It
was decided that it would not include the direct assessment of vigor (health and competitive status) but
would focus on estimating risk (a composite indicator that consider many of these individual factors). As
presented in the next sections, tree form ("F") can be classified according to eight different codes
(section 2.1.1) and the risk of losing vigor ("R") can be classified according to four different codes (section
2.2.1). The other two elements, species and diameter, are straightforward and are not covered in this
guide.
Our classification system was developed for merchantable trees having a DBH of 10 cm or more,
although it could also be used for smaller diameter trees.
2.1 Evaluating tree form
In our system, tree form is related to categories of crown
ideotypes. Tree form is assessed for the first 5 meter
section on merchantable trees greater than 10 meters in
height or on the bottom half (50 % of total height) of
shorter merchantable trees (< 10 m.).
16
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
To properly assess tree form, an observer determines the number of stems, the presence of curves or
sweeps, the inclination or lean and the general shape of the crown. The eight form classes and their
characteristics
3
are described in detail in Table 1 and summarized in Table 2.
Table 1. Description of the eight form classes
F1 Ideal tree form:
A single stem in the first 5 meters
Without curve or sweep on max. 1 axis
Inclination of less than 15° from the vertical axis
F2 Acceptable tree form:
A single stem in the first 5 meters
Sweep on 2 axes or 1 significant curve on the stem
Inclination of less than 15° from the vertical axis
F3 Poor tree form:
A single stem with large branches in the first 5
meters
Large branches potentially carrying roundwood
products
F4 Unacceptable tree form:
A single stem with large branches in the first
5 meters
Large branches have no potential for roundwood
products
F5 Poor tree form:
A principal stem which is divided into a fork
between 0.3 and 2.5 meters from the base of the
tree
F6 Poor tree form:
A single stem in the first 5 meters
Sweep on max. 1 axis
Significant inclination of more than 15° from the
vertical axis
F7 Acceptable tree form:
A principal stem which is divided into a fork
between 2.5 and 5 meters from the base of the
tree
F8 Poor tree form:
A fork or multiple stems are present under 0.3
meters from the base of the tree
Can represent a clump of trees of the same species
or various tree species
3
Refer to Table 3 for definition of terms related to tree form determination.
17
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 2. Summary of tree forms
Code
Silhouettes
Stem count
Stem
curve
Stem inclination
angle (°)
Comment
F1
Single stem
below 5 m
Sweep on
max. 1 axis
Less than 15°
N/A
F2
Single stem
below 5 m
Sweep on
2 axes or 1
significant
curve
Less than 1
N/A
F3
Single stem,
large branches
below 5 m
N/A
N/A
Presence of large
branches
Potentially
carrying
roundwood
products
F4
Single stem,
large branches
below 5 m
N/A
N/A
Presence of large
branches
No roundwood
products
F5
Multiple stem,
Fork between
0.3 m and 2.5 m
N/A
N/A
N/A
F6
Single stem
below 5 m
Sweep on
max. 1 axis
Significant lean
more than 15°
N/A
F7
Multiple stem,
Fork between
2.5 m and 5 m
N/A
N/A
N/A
F8
Multiple trees or
fork below 0.3 m
N/A
N/A
N/A
18
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Examine subject tree
Fork, multiple stems or large
branches below 5 m?
(1)
Multiple trees ?
(2)
Significant lean more
than 15° ?
(3)
F6 Less than
2 sweeps?
(4)
F1 F2
F8
Fork below 0.3m ?
(5)
F8 Fork between
0.3 m and 2.5 m ?
(6)
F5 Fork between
2.5 m and 5 m ?
(7)
F7 Potential for roundwood
products in large branch?
(8)
F3 F4
The determination key (Figure 2) illustrates the logic followed to grade a tree for form. Details are
further provided for each decision point in the key.
Figure 2. Determination key for determining form ("F" rating)
No
No
Yes
Yes
No
No
Yes
Yes
No
Yes
No
Yes
No
Yes
Yes
No
No
Yes
19
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
To reduce subjectivity, following is a brief description of the questions to answer at various decision
points in the key found in Figure 2. For definitions of technical terms, refer to Table 3 below.
(1) Fork, multiple stems or large branches below 5 m?
Does the tree have a single stem (e.g. no forks, no multiple stems, no large branches) in the first 5
meters of the main stem?
(2) Multiple trees?
Is there more than one stem, coming from the same point of origin or growing very close ( 5cm)
(stems will touch when they will get larger) from each other?
(3) Significant lean?
Does the tree have an inclination of 15° or more from the vertical axis?
(4) Less than 2 sweeps?
Does the stem have none or one sweep and no large branches within the first 5 meters?
(5) Fork below 0.3 m ?
Does the tree fork in the first 0.3 meters of the stem?
(6) Fork between 0.3 and 2.5 m ?
Does the tree fork between 0.3 and 2.5 meters of the stem?
(7) Fork between 2.5 and 5 m ?
Does the tree fork between 2.5 and 5 meters of the stem?
(8) Potential for roundwood products in large branches?
Is it possible to make roundwood products from this tree do large branches contain, at least, a pulp
product on a section of 2.44 meters without a significant curve and are at least 8 cm in diameter at
the small end?
Table 3 defines the various terms used in the determination of form. Please note that the red spot in the
images indicates Diameter at Breast Height (DBH) of the sample tree (at 1.3 meter).
20
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 3. Definition of terms used in the determination of form
Term
Definition
Example
Single main stem
Main axis of tree does not include significant
fork(s) below 5 meters.
Multiple stems
Trunk of tree divides into significant forks
between 0.3 and 5 meters.
Multiple trees
Cluster of trees stemming from the same
point of origin or growing very near4 to each
other (OIFQ 2003).
Multiple trees can be of different species.
4
Stems that are 5 cm apart at the base.
21
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Example
Straight stem
Stem which presents no visible lean or
curvature.
Sweep
Stem presenting a visible, but not significant
curve: i.e. the stem axis is diverted
compared with its normal axis, but the loss
of yield in sawtimber is decreased by less
than 33 %.
(See next definition).
Evaluation of the deviation (X) :
Determine the length of the curved
section (e.g. 2 m in the above figure)
on the first 5 meters.
Measure the deviation (X) at the
middle of the curve.
Refer to the table (left) to compare
against the maximum allowed.
Significant curve
Deviation from the main axis resulting in a
loss of sawtimber yield of more than 33 %
(NBG 2012)
For each DBH classes, the maximum
deviation is indicated in the table below.
DBH Class
(cm)
*Acceptable
maximum deviation
"X" (cm)
10-20
10
20-30
13
30-40
17
40-50
20
50 and over
28
*If the deviation is longer than the value in
the table, the curve is considered significant.
X
2 m
22
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Example
Significant lean
Tree leans 15° or more from the vertical axis
on the first 5 meters of the tree.
In presence of leaning curved tree, measure
the first 5 meters from the base of the tree.
Large branches
Branch measuring 1/3 of the diameter of
the main stem (measured below the fork).
Significant fork
Fork where one of the branches measures
1/3 of the main stem diameter (measured
below the fork).
In presence of a significant fork, none of the
branches can be identified as the main stem.
The point where the fork is identified is
where the wood fibers separate and take
different directions.
>15°
5 m
30 cm
20 cm
>15°
5 m
20 cm
60 cm
23
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Example
Roundwood products
potential
Large branches that contain, at least, a pulp
product:
2.44 meter section without significant
curve;
Diameter at the small end ≥ 8 cm.
Example of tree form ratings (F1 to F8) are presented in Table 4 (see appendix A for more examples).
2,44 m
> 8 cm
24
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 4. Examples of tree form ratings
F1
Single main stem below 5 meters
Lean less than15°
Straight stem, fewer than 2 sweeps
Tamarack
Yellow birch
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A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F2
Single main stem below 5 meters
Lean less than 15°
Sweeps on 2 axis or more, or 1 significant curve
White birch
Sugar maple
Sweeps on
2 axis
Significant
curve
26
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F3
Single stem below 5 meters
→ Large branches below 5 meters
No lean or sweeps
Potential for roundwood products
Norway Spruce
Sugar Maple
Roundwood product
Roundwood
product
3.5 m
m
27
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F4
Single stem below 5 meters
Large branches below 5 m
No lean or sweeps
No potential for roundwood products
Jack pine
Yellow birch
28
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F5
Multiple stems below 5 meters
→ Fork between 0.3 and 2,5 meters
Red maple
Yellow birch
29
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F6
Single stem below 5 meters
Significant lean more than 15°
Sugar maple
Balsam fir
>15°
15o
5 m
cm
30
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Tamarack
Sugar maple
F7
Multiple stems below 5 meters
→ Fork between 2.5 and 5 meters
No lean or sweeps
4 m
3.5 m
31
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F8
Multiple stems or multiple trees below 5 meters
→ Significant fork under 0.3 meter
Trees stemming from the same point
White birch
Yellow birch
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A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
2.2 Evaluating risk (of deterioration and mortality)
We made the deliberate decision not to assess individual factors such as health class, competitive class
and vigor in our system but rather record risk of losing vigor as a composite index. Risk rating is
determined for the whole tree.
Rating for risk requires us to look for the presence of visible signs and symptoms that indicate a
reduction of health status. The three broad categories of signs and symptoms are:
1. The presence of fruiting bodies (fungus) or large holes, open wounds or open splits on the main
stem.
2. The presence of significant forks, splits, or injuries caused by animals, mechanical damage, small
holes, healed wounds and other factors.
3. The presence of strong competition and/or a ratio of live crown to total height and the ratio of
dead branches.
The process for assessing the risk of losing vigor is different than that of rating for form, since it is not
only the presence of features on the tree that are indicative but also the severity and the anticipated
trajectory of change. It is rather subjective but a high risk tree might exhibit:
Poor vigor (small, thin crown);
Overmaturity relative to pathological longevity;
Structural weakness (stilt roots, lean > 15 degrees, fork, large low branch);
Decay (fruiting bodies, ants);
Damage (entry points for decay: broken top, split, or skidding/felling or other physical damage).
Below is a description of the four risk classes, along with some examples of signs or defects
5
that are
useful in the assessment. Risk classes are also summarized in Table 6.
5
Refer to Figure 1 in Section 1.2.1 for a complete list of minor, moderate and major defects.
33
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 5. Description of the four classes of risk
R1 Healthy and vigorous tree
Unlikely to lose vigor during the next
cutting cycle
Very low (or zero) probability of dying
during the next 25 years
Monetary value of the tree likely to
increase over time
Low probability of product value loss
No defects or only the presence of minor
defects, such as:
Crook and sweep, white face scar or burl
R2 Unhealthy tree
Will slowly lose vigor
Low probability of dying during the next
15 to 25 years
Monetary value of the tree probably
stable over time
Moderate probability of product
downgrade
Presence of moderate defects, such as:
Frost cracks, small dark face scar, lean, fire
scar, insect or wildlife feeding damage
R3 Unhealthy tree
Likely to lose vigor fairly quickly
Moderate probability of dying during the
next 10 to 15 years
Monetary value of the tree likely to
decrease over time
High probability of product value loss
Presence of fungus on the tree or the
presence of moderate defects such as:
Frost cracks, small dark face scar, lean,
insect or wildlife feeding damage
R4 Dying tree
Likely to continue to quickly lose vigor
High probability of mortality during the
next 10 years
Monetary value of the tree will probably
reduce significantly over time or has
already reached a minimum
Very high probability of product value loss
Presence of major defects, such as:
Spine tooth fungus, punk knot, black bark,
velvet-top fungus
To assess a tree according to risk of losing vigor, we recommend you follow the steps listed below:
1. Follow the determination key shown in Figure 3.
2. Refer to the summary of risk classes if necessary (Table 6).
3. Adjust the rating if necessary.
The determination key in Figure 3 illustrates the logic of classifying a tree according to the risk of losing
vigor. Follow the key as you answer questions about the subject tree. Note that the number listed under
each question of the key refers to helpful information presented in Table 8, aimed to help rating the risk.
34
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 6. Summary of risk classes
The effect of tree size is an additional factor affecting tree vigor and product potential. Studies
have found that larger diameter hardwood trees that are associated with moderate or major
defects (injuries) have higher probability of product downgrade as such trees are not vigorous
enough to compartmentalize the damages efficiently. Therefore, it is suggested to consider
interactive (joint) effects of defects (of different size and severity) and the tree size (DBH) on
probability of product downgrade (Table 7) while making silvicultural decisions.
Table 7. Joint effects of tree size and vigor on tree mortality and probability of product downgrade
Rating
Probability of mortality
Value ($) projected in time
Probability of product downgrade
R1
Nil, > 25 years
Improve
Low
R2
Low, 15-25 years
Stable
Moderate
R3
Medium, 5-15 years
Deteriorate
High
R4
High < 5 years
Substantial loss
Very high
Rating
Presence of
damages
DBH
(cm)
Probability of
mortality
Value ($) projected
in time
Probability of product
downgrade
R1
No or minor
defects
< 40
Nil
Improve
Very Low
> 40
Nil
Stable
Low
R2
Moderate
defects
< 40
Low
Stable
Low
> 40
Low
Deteriorate
Moderate
R3
Moderate or
major defects
< 40
Medium
Deteriorate
Moderate
> 40
High
Substantial loss
High
R4
Major defects
< 40
High
Substantial loss
High
> 40
High
Substantial loss
Very high
35
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Figure 3. Determination key for determining risk of losing vigor ("R" rating)
36
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Below is additional information for determination of risk of lowing vigor (from Figure 3). For technical
term definitions, refer to Table 8.
(1) Presence of fruiting bodies, obvious signs of decay, deep splits, big holes or canker on at least 3 faces
of main stem?
Does the main stem have fruiting bodies (visible fungus), obvious signs of decay, deep splits, large
visible holes (> 8 cm2), or canker on more than 3 faces of the main stem?
(2) Significant forks or tree cluster?
Does the tree have a significant fork, or is it part of a cluster of trees stemming from the same point
of origin or growing very near to each other?
(3) High competition? Live crown ratio less than 30 %? Dead branches more than 30% (tolerant spp.) or
more than 10% (intolerant spp.)?
Is the tree under significant competition from neighboring trees?
and/or
Does the tree have a live crown ratio of less than 30 %
and/or
Does the tree have more than 30 % of dead branches in the case of a tolerant species or more than
10% in the case of an intolerant species?
(4) Canker, small holes, healed splits or wounds, animal damage, mechanical damage on at least 2 faces
of main stem?
Does the tree have canker, small holes, healed splits or wounds, animal damage, mechanical
damage on 2 or more than 2 sides of the main stem?
37
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 8. Definitions of terms used when rating the risk of losing vigor
Term
Definition
Examples
Fruiting body
Visible part of a fungus that
produces or carries spores.
Its presence indicates that the
interior of the tree is affected by
decay, which can already be in an
advanced state.
Fruiting bodies may be present
anywhere at the base, stem or at
the junction of branches and the
trunk (OIFQ 2003, GQ 2012).
Obvious signs of decay
Decay is the decomposition of
wood by fungi or other micro-
organisms, resulting in softening,
progressive loss of strength and
weight and often changes of
texture and color (OIFQ 2003).
It originates from a wound (branch
death) that didn’t heal for a long
period of time.
Presence of fungi sporophores
Swelling at the base of the tree
38
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Examples
Split
Open split: unhealed split (length
1.5 m) present at any height on the
stem or main branches, leaving an
opening to pathogens, which may
worsen mechanically over time.
A severe seem that has affected
the cambium may be treated as a
significant split.
Open split
Healed or healing split
Hole on main stem
Visible opening on the stem that
reaches cambium. Caused by
factors agents, such as:
Birds
Sap-sucking insects or
insect larvae
Rotten nodes
(Calvert and Petro 1993, GQ 2012).
- Small hole : 2 to 8 cm diameter
- Large hole : > 8 cm diameter
Canker
Swelling with necrosis of the
underlying bark and cambium,
resulting in exfoliated bark and
distorted main stem. Canker
provides openings for organisms
responsible for discoloration and
decay.
39
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Examples
Face of main stem
The stem is divided vertically into 4
faces of equal dimensions, from
the bottom to the top of the stem.
Significant fork
Fork where one of the branches
measures 1/3 of the main stem
diameter (measured below the
fork). Can be located at any height
on the tree.
In presence of a significant fork,
none of the branches can be
identified as the main stem.
A significant fork, in addition to
being a key feature to determine
form, is an important indicator of
the risk of losing vigor. In fact, even
on a healthy tree, a fork is likely to
suffer damage and split during
significant weather events (e.g.
wind, freezing rain). It will likely
become a gateway for pathogens
or insects, and will increase the risk
of the tree losing vigor.
Multiple trees
Cluster of trees stemming from the
same point of origin or growing
very near to each other (OIFQ
2003).
High competition
An established tree whose crown is
not free to grow and might not
develop in the future.
20 cm
60 cm
Fir tree under
heavy
competition
competed
40
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Examples
For shade-tolerant species, a tree is
considered under high competition
when at least 3 faces of its crown
are shaded by neighboring trees.
For shade-intolerant species, a tree
is considered under high
competition when at least 2 faces
of its crown are shaded by
neighboring trees.
Live crown ratio (LCR)
Ratio indicating the length of live
crown available for photosynthesis.
Length of live crown x 100
Total tree height
(OMNR 2004, GQ 2005)
𝐿𝐶𝑅 =
3 m
20 m x 100 =15 %
Dead branches
Extent of dead, dying, or missing
crown foliage expressed as a
percentage (Boulet 2005).6
6
Excludes natural pruning
3 m
20 m
White birch with
70% dead
branches
41
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Examples
Shade-tolerant species
A species capable of growing and
successfully reproducing beneath
the shading canopy of other
species.
In New Brunswick, shade-tolerant
tree species include: balsam fir,
sugar maple, American beech,
white ash, white spruce, black
spruce, red spruce, eastern white
cedar red maple and yellow birch.
Shade-intolerant species
A species not capable of growing
successfully in shade.
In New-Brunswick, shade-
intolerant tree species include:
white birch, pines and
aspen/poplars.
Animal damage
Unhealed injury present on the
stem or main branches, leaving an
opening to pathogens, which may
worsen over time.
Includes injuries caused by:
Birds (woodpecker holes)
Insects (worm holes, maple
borer, larvae)
Mammals (cervids, rodents,
etc.).
Injury from a woodpecker
Injury caused by a moose
Mechanical damage
Damage occurred to the tree by
another tree falling on it or injury
caused by machinery.
42
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Term
Definition
Examples
Wound
Open wound : no callus tissue has
been formed
Healed wound: callus tissue has
been formed to compartmentalize
the wound.
Dead branches
Extent of dead, dying, or missing
crown foliage expressed as a
percentage (Boulet 2005).7
White birch with 70 % dead
branches
Table 8 contains a summary of the section on rating trees for risk of losing vigor. Sample images are
included to help in the interpretation (see Appendix B for more examples).
7
Excludes natural pruning
43
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Table 9. Summary of risk ratings including images
R1
Very low probability of mortality
Value ($) of the tree should increase over time
Low probability of product downgrade
Absence of defects or presence of minor defects
Burl
(red maple)
Live Crown > 30 %,
dead branches < 25 %
(White Birch)
R2
Low probability of mortality
Value ($) of the tree should be stable over time
Moderate probability of product downgrade
Presence of moderate defects
Hole on main
stem
(sugar maple)
Healing split
(sugar maple)
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A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
R3
Moderate probability of mortality
Value ($) of the tree should decrease over time
High probability of product downgrade
Presence of moderate defects significantly affecting the vigor
Fruiting
bodies on
main stem
(Sugar Maple)
Significant fork
& split
(Yellow Birch)
R4
High probability of mortality
Value ($) of the tree should decrease over time
High probability of product downgrade
Presence of major defects
Significant fork & live
crown < 30 %
(red maple)
Fruiting bodies on
main stem
(red maple)
45
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
3. Links with other systems
To relate tree classes from this system with existing classification systems from other jurisdictions,
conversion matrices were prepared. They are introduced only as a quick way to compare classification
schemes and are no substitute for grading trees in their original systems.
3.1 The AGS / UGS and Six class systems (USA and Ontario)
The Ontario Tree Marking guide refers to indicators such as vigor, potential risk and tree quality
potential. It consists of two scales: the first one has two classes: AGS (Acceptable Growing Stock) and
UGS (Unacceptable Growing Stock). The second classification is more detailed and has six classes. The
latter is recommended for pre-cut cruising and for stand analysis (OMNR 2004).
Table 10. Links between the New Brunswick tree classification system and the AGS/UGS system
Species
Good form
(F1, F2, F7)
Poor form with log potential
(F5, F6, F8)
Poor form with no log
potential (F3, F4)
R1
R2
R3
R4
R1
R2
R3
R4
R1
R2
R3
R4
Beech
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Poplar
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Red maple
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Red oak
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Sugar maple
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
White ash
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
White birch
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Yellow birch
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Black spruce
AGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Cedar
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Fir
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Hemlock
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Jack pine
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
46
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Red pine
AGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Red spruce
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Eastern
white pine
AGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
White spruce
AGS
AGS
UGS
UGS
AGS
UGS
UGS
UGS
UGS
UGS
UGS
UGS
Table 11. Links between the New Brunswick tree classification system and the Six class system
Good form (F1, F2, F7)
Poor form with log potential
(F5, F6, F8)
Poor form with no log
potential (F3, F4)
R1
R2
R3
R4
R1
R2
R3
R4
R1
R2
R3
R4
A1
A
A
-
B1
B
B/C
C
-
-
D
D
3.2 The MSCR Classification system (Québec)
The MSCR guide is used to identify principle tree defects and to evaluate their effects on the tree's
change in vigor, and is used primarily to assign a harvest priority. There are four classes
8
: M (Non-
growing stock), S (Poor growing stock), C (Acceptable growing stock) and R (Premium growing stock)
(Boulet 2005).
Table 12. Links between the New Brunswick tree classification system and the MSCR classification
system
R1
R2
R3
R4
R
C
S
M
8
Forms are not included in the matrix because not all the forms had an equivalent in the classification system.
47
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
3.3 The ABCD classification system (Québec)
The ABCD classification system is designed to grade stems from the perspective of sawtimber
production, by evaluating the best 3.7 meters section within the first 5 meter butt log. The section to
evaluate is then separated into 4 faces to assess clear cuttings and percentage (%) of volume reduction.
A minimum diameter is required for each class: A: 40+ cm, B: 34+ cm, C: 24+ cm, D: 24+ cm stems that
don’t meet the criteria of class C (GQ 2012).
Table 13. Links between the New Brunswick tree classification system and the ABCD classification
system
Good form
(F1, F2, F7)
Poor form with log potential
(F5, F6, F8)
Poor form with no log potential
(F3, F4)
3.1 m
2.5 m
1.8 m
3.1 m
2.5 m
1.8 m
-
A
B
C
A
B
C
-
3.4 The Petro classification system (Nova Scotia)
The Petro classification system is used to evaluate all visible defects and characteristics that could affect
the quality of the end product. The system includes three grades for standing trees: G1, G2, and G3.
These classes are determined for the best 3.66 meter (12’) section within the first 4.88 meter (16’) butt
log, which is divided into four faces. Cutting sizes and percent yield of cuttings (including rot, sweep, and
crook) result into the specific grades. A minimum diameter is assigned to each class: 40.64 cm or 16”
(G1), 33.02 cm or 13” (G2), G3: 25.4 cm or 10” (G3) (Calvert and Petro 1993).
Table 14. Links between the New Brunswick tree classification system and the Petro classification
system
Good form
(F1, F2, F7)
Poor form with log potential
(F5, F6, F8)
Poor form with no log potential
(F3, F4)
3.05 m
(10’)
2.44 m
(8’)
1.83 m
(6’)
3.05 m
(10’)
2.44 m
(8’)
1.83 m
(6’)
-
G1
G2
G3
G1
G2
G3
-
48
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
4. Future work
The system we have created allows characterizing trees in terms of their form and the risk to deteriorate
over time. Those two factors are useful in determining product distributions, understanding impacts on
harvesting costs and making silvicultural decisions. In the future, specific projects will be initiated to
increase knowledge of the impacts of risk and tree form on key forest management activities. They will
primarily aim at :
Increasing knowledge of tree form on stem volume and product distribution
The current approach to predict merchantable volume in stems relies on volume equations that are
independent of tree form and the geometry of the tree. There are known biases and errors associated
with this simplification in particular for hardwoods. The derivation of new taper equations that take into
account tree form will reduce variation significantly.
Very little information exists to predict product potential as a function of species, size, form and risk.
Product potential in hardwood trees is highly variable and dependant on several factors other than gross
merchantable volume. Tree bucking studies considering those factors will improve our capability of
understanding product distributions within a tree.
Understanding the impacts of tree characteristics on harvesting cost
Forest stands have high variability (species composition, tree characteristics, stand structure, etc.) and
using average machine productivity and associated harvesting costs could be misleading. It is recognized
that certain tree forms can significantly increase processing time. However, the effect of tree form has
not yet been quantified. This lack of knowledge limits our ability to forecast machine productivity, and
improve harvesting prescriptions to increase profitability. Furthermore, this knowledge is a key missing
piece of the foundation for a financially driven decision support system. Depending on the harvesting
system, felling and processing costs can represent up to 50% of the total costs of mill wood supply. We
are currently limited to average productivity and cost functions that tend to overlook the influence of
tree form. The understanding of those relationships will allow to develop machine productivity functions
that are specific to changes in tree characteristics (form and risk classes), and to suggest BMP’s to
improve machine productivity and lower operating costs.
Enabling silviculture decision-making by increasing knowledge of the resource
Silviculture guides will be prepared in order to leverage the additional information provided by
implementating our tree classification system. Determination keys for prescribing silviculture treatments
will be improved by discouraging treatments where the potential to increase value is low as a
consequence of high occurances of trees at high risk and poor form. We intend to test this classification
system and to improve our ability to assess risk and form and to validate it on the scientific grounds.
Finally, we hope that growth and yield modelers will adopt the system in order to predict, with accuracy,
the optimal development of our forests so that it will be used broadly by practitioners and regulators.
49
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Bibliography
Boulet, B. 2005. Défauts externes et indices de la carie des arbres : guide d’interprétation. Ministère des
Ressources naturelles et de la Faune (MRNF). Québec, Canada. 291 p.
Boulet, B. 2006. Potentiel d’utilisation du système MSCR pour aménager les forêts feuillues et
mélangées. Ministère des Ressources naturelles et de la Faune du Québec, présentation Power
Point dans le cadre du 85e congrès de l’OIFQ, 45 diapositives.
Calvert, W.W. and Petro, F.J. 1993. Grading standing hardwood trees in Nova Scotia. Canada/Nova Scotia
Cooperative Agreement for Forestry Development. 71p.
Gouvernement du Québec (GQ). 2012. Classification des tiges d’essences feuillues : normes techniques,
Version révisée provisoire. Ministère des Ressources naturelles et de la Faune (MRNF). Québec,
Canada. 93p.
Kenefic, L. 2012. Notions of tree vigor and health. Personal Communication 2012.
New Brunswick Government (NBG). 2012. New Brunswick Scaling Manual, 4th Edition. Forest
Management Branch, Natural Resources. New Brunswick, Canada. 85 p.
Nyland, R. 2012. Notions of tree vigor and health. Personal Communication 2012.
Ontario Ministry of Natural Resources (OMNR). 2004. Ontario Tree Marking Guide, Version 1.1. Ont. Min.
Nat. Resour. Queen’s Printer for Ontario. Toronto. 252 p.
Ordre des ingénieurs forestiers du Québec (OIFQ). 2003. Dictionnaire de la foresterie, Éd. spéciale XIIe
Congrès forestier mondial. Québec, Canada. 744p.
Ordre des ingénieurs forestiers du Québec (OIFQ). 2009. Manuel de foresterie. Nouvelle édition
entièrement revue et augmentée. Les Éditions MultiMondes, Québec, Canada. 1 540 p.
50
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Appendices
51
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Appendix A - Sample images of form ratings
52
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
5.5 m
F1 - White spruce
F1 - Red maple
Significant curve
Significant curve
F2 - Yellow birch
F2 - White birch
53
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Roundwood products
1.8 m
Roundwood products
3 m
F3 - White birch
F3 - Beech
F4 - Jack pine
F4 - Yellow birch
54
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F5 - Red maple
F5 - White birch
F6 - Red maple
F6 - Eastern white cedar
55
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
F7 -
2.7 m
3 m
F7 - Sugar maple
F7 - Norway spruce
F8 - White birch
F8 - Red maple
56
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
Appendix B - Sample images of risk of losing vigor ratings
57
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK
R1 - White face scar
R3 - Hole (≥ 5 cm)
on main stem
R1 - Burl
R2 - Hole ( 5 cm)
on main stem
R2 - Fork and split
R3 - Over 25 % of dead branches
R4 - Hole on main stem
& significant split
R4 - Fruiting bodies on main stem
... While capable of producing valuable wood products, hardwood species generally demonstrate a much greater range of product quality compared to softwood species (Cockwell and Casperen 2014). The variation in product quality results from the large variety of stem damage such as seams, cracks, rot, stain, and fungal infections (Cockwell and Casperen 2014; Drouin et al. 2010) as well as stem form characteristics including sweep, significant forks and multiple stems that hardwoods can demonstrate (Pelletier et al. 2013, Fortin et al. 2009). The impact of stem defects has been shown to reduce product value for several hardwood species by compromising internal wood quality or reducing product recovery. ...
... While these classification systems all evaluate stem defects on individual trees, their overall purpose can differ. For instance, the ABCD system and Perot system (Pelletier et al. 2013) evaluate a tree's stem quality in relation to product output and value while the MSCR and AGS/UGS system are predominantly used to assess a tree's vigor, which refers to its potential future growth and susceptibility to mortality (Guillimette et al. 2008;Hartmann et al. 2008). The use of different tree classifications has shown to have important implications on predicting the presence of internal defects (Drouin et al. 2010), product recovery (Fortin et al. 2009;Cockwell and Casperen 2014;Schneider et al. 2008), and value for hardwood species (Cockwell and Casperen 2015;Havreljuk et al. 2014). ...
... The Northern Hardwood Research Institute (NHRI) released a new protocol in 2014 to enhance silvicultural management of hardwood species in New Brunswick (Pelletier et al. 2013). ...
Article
Northern hardwood and mixed-wood forest types occupy a considerable percentage of the forest landscape across the Northeastern United States and portions of eastern Canada. While capable of producing valuable saw timber and veneer products, hardwood species demonstrate a wide range of stem quality resulting from the large variety of stem forms and defects that these species can manifest. The effect of different stem forms and damage has largely not been accounted for in predictions of volume, growth, and mortality. In addition to potential bias in growth and yield applications, the lack of quantification of these features has left the efficacy of silvicultural tools such as tree classification guides untested. Using a tree classification system developed by the Northern Hardwood Research Institute (NHRI), form and risk classifications were assigned to several commercial hardwood species across sites in Maine, New Hampshire, and New Brunswick. Regression analyses were used to accomplish the following objectives; 1) quantify sawlog recovery as a function of a trees size, form, and risk; 2) determine the occurrence of stem form and risk among species; 3) and evaluate the influence of stem form and risk on individual tree diameter growth and survival. For the first chapter, a linear mixed effects model was used to quantify the proportion of sawlog material in individual trees. Results indicated three form classifications and a binary classification of risk were sufficient to account for variation in sawlog recovery. The average proportion of sawlog was largest for trees with single straight stems and smallest for those displaying a large significant fork on the first 5 m of their stem. Stem damage also had substantial implications on product recovery where trees considered to be high-risk had overall lower proportions of sawlog volume. Using the simplified form and risk classes, a series of logistic regression models were developed to predict the occurrence of risk and form across hardwood species. Among the species in the analysis, yellow birch and red maple had the highest probability of being high-risk. Sugar maple had the highest probability of demonstrating good form while red maple and red oak were the most likely to have poor form. In the second chapter continuous forest inventory data from five locations in Maine and New Hampshire were used to evaluate the influence of form and risk on tree growth and survival for hardwood species. The influence of form and risk on growth were analyzed by assessing bias in the regional diameter increment equation used in the Acadian Variant of the Forest Vegetation Simulator FVS-ACD and through development of a periodic annual increment model (PAI). The regional FVS-ACD equation tended to over predict for species and risk class while binary form and risk classifications were significant variables in the PAI model, although their effect was relatively small. A nonlinear model was used to quantify annualized individual tree survival. Trees with single straight stems had statistically higher survival probabilities compared to all other stem forms, however the magnitude of the difference in survival was not substantial.
... Of the 113 studies for which tree selection methods were determined, more than half of the studies imposed sampling restrictions by selecting trees of average and better vigor and by avoiding forked (as noted by MacFarlane and Weiskittel 2016) and otherwise deformed trees. Using models that avoid trees that are poorly formed (e.g., low forking or with a broken top) or at a high risk of mortality (i.e., of low vigor), as evidenced by broken branches, severe mechanical damage, and fungal pathogens (Pelletier et al. 2013), may overestimate the biomass of low vigor/high risk trees, leading to overestimates at larger strata. ...
... Height to the lowest branch was almost never included as a predictor, and only a few biomass studies assessed the influence of form or health on biomass estimates (e.g., ). In addition, classifying trees in terms of form and risk (Pelletier et al. 2013) may improve estimates of tree merchantable volume (Castle et al. 2017) and decay (Frank et al. 2018), which in turn affects volume and biomass estimates when discounted from gross volume. It is recommend that future studies examine how variation in tree form and health may influence biomass estimates by sampling diseased and deformed trees. ...
Technical Report
Full-text available
When estimating tree-level biomass and carbon, it is common practice to develop generalized models across numerous species and large spatial extents. However, sampling efforts are generally incomplete and trees are not randomly selected. In this analysis, of the more than 1,000 biomass-related articles that were reviewed, trees were destructively sampled in over 300 studies to estimate biomass in the United States. Studies were summarized and past sampling efforts were explored to illuminate where the largest data gaps occurred in terms of tree components sampled, tree size, tree form, tree species, and location. The most prominent gaps were in large trees, particularly in Douglas-fir trees in the Pacific Northwest. In addition, tree roots were notably undersampled. Lastly, trees of poor or unusual form and low vigor were often not sampled, and this may introduce a systematic bias if not dealt with appropriately. More than 200 species did not have a biomass model or a single data point. The gaps presented here can be viewed as suggestions for future destructive sampling efforts, but the magnitude of a gap for a given model will ultimately depend on the selected modeling framework and the user's objectives.
... However, since the province of New Brunswick has already adopted the Tree classification system (TCS) developed by the NHRI (Figure 3), we wanted to explore the use of this system in a machine productivity context because of its inherent simplicity and ease of use. The TCS was developed to quickly gather tree information to make silvicultural decisions, predict product distribution, and determine harvesting and processing costs (Pelletier et al. 2013). It concentrates on assessing the first 5 m of a tree where tree form is assigned a number between 1 and 8 ( Figure 3). ...
... Tree classification system developed by the NHRI and adopted for Crown Lands by the province of New Brunswick (adapted fromPelletier et al. 2013). ...
Conference Paper
Full-text available
Among the variables that influence harvesting costs, it is commonly accepted that tree form has a significant impact because of its presumed effects on harvesting and processing time. However, it is not clear what form or elements of form have a considerable impact or if their effect is really significant. Based on the new tree classification system developed by the Northern Hardwoods Research Institute (NHRI) and adopted by the province of New Brunswick, this project aimed at determining cut-to-length machine productivity as a function of tree form. A detailed time and motion study of harvester movements in a hardwood dominated stand suggests that the presence of a fork or a large branch between 1.3 and 10.0 meters on the main stem reduce machine productivity in the order of 12-15%. Results also suggest that in terms of harvesting productivity, some forms may be combined. To translate these results into improvement opportunities for the forest industry, it would be appropriate to conduct an additional study with other types of harvesting equipment to determine whether there would be an advantage in selecting the type of equipment according to the form of the trees to be harvested.
Article
The visual assessment of tree vigour before partial cutting is a key element of the long-term sustainability of managed hardwood forests. Several classification systems have been developed and applied to perform this task during the tree marking process. They segregate trees in different vigour classes based on the presence and severity of stem and crown defects. Yet, the relevance of using these defects to assess tree vigour has rarely been empirically validated. In this study, we analysed the relationships between quantitative vigour indicators and a full range of individual defects using 336 sugar maple and 84 yellow birch trees. Among the tested defects, the tree crown density showed the best ability to identify slow growing, non-vigorous sugar maple trees, regardless of their size. However, none of the stem-related defects, such as bark aspect, the presence of cambial necrosis or conks and stromata were strongly related to our quantitative vigour indicators. For yellow birch, none of the stem defects and crown conditions were found to be related to our vigour indicators. We conclude that, pending longitudinal studies that will provide a full empirical validation of classification systems, crown density should be used to assess recent growth and vigour of sugar maple trees and guide tree marking.
Article
Full-text available
It is commonly accepted that tree form has an impact on the productivity of single-grip harvesters. However, it remains unclear, which elements of tree form are significant and to what degree they impact harvesting productivity. This is of particular importance in hardwood dominated stands, where hardwood trees often exhibit complex and variable stem and crown architecture that can complicate and prolong the processing phase. With the development of specialized harvesting heads, hardwoods, which were mostly subject to motor-manual operations, are now increasingly being cut and processed with fully mechanized harvesting systems. The goal of this pilot project was to determine the effect of tree form on the productivity of mechanized cut-to-length harvesting. A time and motion study of a single-grip harvester, operating in a hardwood dominated stand, suggests that the presence of a fork or a large branch on the main stem can reduce machine harvesting productivity by 15 to 20%.
Défauts externes et indices de la carie des arbres : guide d'interprétation. Ministère des Ressources naturelles et de la Faune (MRNF)
  • A Tree Classification System For New Brunswick Bibliography Boulet
A TREE CLASSIFICATION SYSTEM FOR NEW BRUNSWICK Bibliography Boulet, B. 2005. Défauts externes et indices de la carie des arbres : guide d'interprétation. Ministère des Ressources naturelles et de la Faune (MRNF). Québec, Canada. 291 p.
Potentiel d'utilisation du système MSCR pour aménager les forêts feuillues et mélangées. Ministère des Ressources naturelles et de la Faune du Québec
  • B Boulet
Boulet, B. 2006. Potentiel d'utilisation du système MSCR pour aménager les forêts feuillues et mélangées. Ministère des Ressources naturelles et de la Faune du Québec, présentation Power Point dans le cadre du 85e congrès de l'OIFQ, 45 diapositives.
Grading standing hardwood trees in Nova Scotia. Canada/Nova Scotia Cooperative Agreement for Forestry Development
  • W W Calvert
  • F J Petro
Calvert, W.W. and Petro, F.J. 1993. Grading standing hardwood trees in Nova Scotia. Canada/Nova Scotia Cooperative Agreement for Forestry Development. 71p.
Classification des tiges d'essences feuillues : normes techniques, Version révisée provisoire. Ministère des Ressources naturelles et de la Faune (MRNF)
  • Québec Gouvernement Du
Gouvernement du Québec (GQ). 2012. Classification des tiges d'essences feuillues : normes techniques, Version révisée provisoire. Ministère des Ressources naturelles et de la Faune (MRNF). Québec, Canada. 93p.
Notions of tree vigor and health
  • L Kenefic
Kenefic, L. 2012. Notions of tree vigor and health. Personal Communication 2012.
Notions of tree vigor and health
  • R Nyland
Nyland, R. 2012. Notions of tree vigor and health. Personal Communication 2012.
Défauts externes et indices de la carie des arbres : guide d'interprétation. Ministère des Ressources naturelles et de la Faune (MRNF)
  • B Boulet
Boulet, B. 2005. Défauts externes et indices de la carie des arbres : guide d'interprétation. Ministère des Ressources naturelles et de la Faune (MRNF). Québec, Canada. 291 p.