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Resource Analysis Guide For Sustainable Resource Management

Planning Volume 2: Appendices

Forests, Lands and Marine Branch Ministry of Sustainable Resource Management

December 2004

Appendices for Resource Analysis Guide for SRM Planning i

Table of Contents Table of Contents............................................................................................................................. i

Appendix 1 Examples of Computer Models for Planning .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 Appendix 2 Conduct ing and Determining the Results of a Socio-economic and

Environmental Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Appendix 3 Conduct ing and Determining the Results of an Environmental Risk

Assessment . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Appendix 4 Ensuring Consistency wi th the Forest and Range Pract ices Act . . . . . . 23 Appendix 5 Determining SRMP Level of Complexi ty: Focused versus

Comprehensive SRMPs .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Appendix 6 Methods for Undertaking Implementat ion and Effect iveness

Monitor ing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 31 Appendix 7 Recreat ion Opportuni ty Spectrum .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Appendix 8 Visual Qual i ty Object ives Rating for Backcountry Tour ism .. . . . . . . . . . . . . 39 Appendix 9 Examples of Analysis Methods for Backcountry Tourism Products . . . 41 Appendix 10 Decis ion Analys is and Report ing Tool (DART) . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 45 Appendix 11 Coarse and Fine Fi l ter Habitat Supply Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 Appendix 12 Provincial Her i tage Register Database .. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Appendices for Resource Analysis Guide for SRM Planning 1

Appendix 1 Examples of Computer Models for Planning This appendix describes various computer models that may be used to support resource analysis in sustainable resource management planning.

Forest Service Simulator (FSSIM) Timber Supply Model FSSIM is used by the BC government to forecast how the forest changes, decade by decade, over long time horizons (typically 250 years) in response to different harvest levels and management actions and requirements.

The model describes how different parts of the forest grow and how they are expected to respond to changes, such as timber harvesting. It categorizes areas according to whether or not they are available for timber harvesting and what kinds of management requirements might be applied to the areas. This makes it possible to compare how alternative management strategies affect forest structure and timber production over time.

FSSIM cannot model spatial relationships explicitly, such as stand adjacency, because it has no information about which stands are adjacent. Instead, proxies, such as number of harvest passes, are used to approximate spatial management requirements. These proxies may over- or under-estimate the true effect of these requirements, depending on the spatial structure of the forest and the history of logging.

Landscape Models Landscape models depict when, where and how landscapes will change in response to land use scenarios. Unlike FSSIM which is spatially implicit, landscape models are spatially explicit (i.e., they directly model where changes occur on the land base in order to estimate changes in forest age and structure and implications for related economic and environmental values).

Landscape models combine maps (and related data) of current forest conditions with formal predictions about the consequences of land management activities and ecological processes to create “projected maps” of the future forest. Landscape models typically simulate landscape change over a period of approximately 200 to 500 years (the “planning horizon”).

There are a number of landscape models available for forest planning. Each has a specific approach to modeling landscape condition over time (absolute versus probabilistic, simulation versus optimization, etc). Some will be more suited to SRMPs than others. Landscape models can be very complex. Technical

Append ix 1 Example Compute r Mode ls fo r P lann ing


experts are often needed to run the model and domain experts are required to interpret outputs, adding to the cost of the process. Things to consider when choosing a landscape model are:

• Does this model address our questions?

• Can it address the range of resources of concern?

• Who can use the model?

• Does it require special expertise to run the model and interpret outputs and are the resources available for this?

Landscape models are most suited to resource analysis of timber, biodiversity and habitat supply, although they may be applied to any resource that is affected by changes in landscape pattern.

Habitat Models Habitat models apply current knowledge about the ecology of species by linking life requirements to quantifiable attributes on the land. For example, a model for northern goshawk might rate the condition of the land based on a combination of variables related to the suitability of nesting habitat, such as stand height, canopy closure, tree species, and amount of edge. Linking the quality and supply of habitat to land-based conditions allows planning teams to assess the implications for species as a result of land management scenarios.

Because the variables used in habitat modelling can change over time (e.g., trees grow, amount of forest edge changes with logging and subsequent regeneration), it is possible to build in models of successional processes to show how habitat suitability changes over time. When adequate information is available linking habitat supply to wildlife populations, it is also possible to use these models to predict trends in populations over time.

Habitat supply models can vary in complexity from simple look-up tables to complex spatio-temporal analyses. Planning teams, including domain experts and analysts, can work together to identify the appropriate approach to modeling the indicators for each species, including the level of complexity required.

A summary of various models and modeling approaches used to assess habitat supply is contained in “A Strategy for Habitat Supply Modeling for British Columbia. Draft Volume II. - Appendices” (http://www.for.gov.bc.ca/hfp/silstrat/habitat/habitat-docs.htm#hsmbc)

Visual Landscape Model ing The Ministry of Forests employs 3-D terrain modelling software to portray the visual impact of forest harvesting. The computer program is capable of producing photorealistic terrain modeling, visualization, rendering, and animation. Perspective view images

Append ix 1 Example Compute r Mode ls fo r P lann ing


depicting proposed clearcuts, partial cuts, and roads can be created from a number of viewpoints. Accurate visual simulation of proposed forest harvesting is important to assure that established visual quality objectives are met.

Custom-designed Models It is possible to custom-design models to address specific problems. For example, the West Babine SRMP used a simple spatial model to assess the implications of road development on grizzly bears and timber accessibility. However, it may take time to develop and finesse even a simple model and this should be factored into decisions on which analytical tool to select.


Appendix 2 Conducting and Determining the Results of a Socio-economic and Environmental Assessment

This appendix provides an overview of the SEEA framework and data sources and discusses the scope and timing of SEEA. A more detailed description of the process for conducting and interpreting SEEA is provided at http://srmwww.gov.bc.ca/rmd/ecdev/docs/GuidingPrinciples.pdf

Appendix Table 1: SEEA Frames, Techniques and Indicators

Frame Analysis Techniques Indicators

Economic Development

Economic activity Direct, indirect & induced employment in Person Years (PYs); wage and salary levels; employment income; Gross Domestic Product (GDP)

Net Resource Value Benefit-cost analysis For commercial sectors: economic rent - revenues less production costs + typical profit; in addition, any estimated economic rent captured by labour For non-commercial sectors: estimation of consumer surplus (what people would be willing to pay for enjoyment/preservation of a recreational activity or environmental amenity) and environmental and health damage costs

Social Social impact Population; infrastructure; employment duration; job quality; qualitative stakeholder preferences

First Nations Social and heritage impact Cultural heritage inventory changes; qualitative First Nations preferences

Government Finances Fiscal impact Revenues (taxes, royalties, etc.); expenditures

Environmental Values Environmental impact Risk levels and qualitative measures of outcomes on key environmental indicators; estimates of monetary values where possible to compare with the Net Resource Value account

When undertaking a SEEA within a SRMP context, it is preferable that the analyst devotes some effort to researching each frame, at least to some level of coverage.

Append ix 2 Conduc t ing and Dete rmin ing the Resu l t s o f a Soc io -economic Env i ronmenta l Assessment


It is recognized that the Net Resource Value frame is often difficult to address because:

• Benefit-cost analysis techniques require the involvement of a qualified analyst, and

• Satisfactory data is often not available.1

To overcome the second barrier, a reasonable Net Resource Value analysis can often be conducted by adapting existing data items, such as standard revenue and cost estimates from Building Blocks (see below) and Appraisal Manuals and harvesting and visitation estimates from local experts, such as woodland managers and lodge owners. This data is not “perfect” but offers a better alternative than going with no Net Resource Value information. Excluding the Net Resource Value frame from a SEEA means that economic efficiency information is likely to receive little or no attention in SRM decision-making.

Deciding the Scope of a SEEA The first task in undertaking a SEEA is to determine the scope of the analysis2, which requires answering a few basic questions as shown in the following decision tree.

1 In certain situations, MSRM expects businesses and industry associations with interests in a SRM planning area to provide some support to the plan making process. One area where they can contribute is by supplying basic data to facilitate estimation of Net Resource Values.

2 Pre-supposing that a SEEA is necessary. A SEEA may not be needed. SRM planners should consult with staff in MSRM’s Sustainable Resource Development Branch to determine whether a SEEA is required.



Appendix Figure 1 SEEA Decision Tree

Comprehensive SEEA – All important resource values covered by the plan would be analyzed within the framework specified in Socio-Economic and Environmental Assessment for Land and Resource Management Planning in British Columbia: Guiding Principles and Socio-Economic and Environmental Impact Assessment for Land and Resource Management Planning in British Columbia. The SEEA would likely include a socio-economic profile of the plan area and adjacent areas that the plan directly impacts. It would also likely include an analysis of two distinct scenarios for the SRMP area. A comprehensive SEEA, with its broad analysis approach, is primarily suited for enhanced SRMPs.

SEEA was undertaken for an LRMP that covers the SRMP area, and is viewed as reasonably current?

Comprehensive SEEA is likely not required

Certain resource values are subjects of debate/controversy

Certain resource values are subjects of debate/controversy

Condensed SEEA, projection of

anticipated socio-economic results for

SRMP scenario

Yes No

Focused SEEA, highlighting resource

values and plan sub-areas of most

interest

Condensed SEEA, projection of

anticipated socio- economic results

for SRMP scenario

Yes No

No

Comprehensive SEEA should be

undertaken

Focused SEEA, highlighting resource values and plan sub-areas of most interest

Yes

A broad SEEA approach is required; there are several contentious issues at play

Yes No



Focused SEEA – Only resource use values that are proving difficult to reconcile within the SRM planning process would be analyzed in a focused SEEA. An analyst would use MSRM’s SEEA guidelines to structure a focused SEEA, which provides succinct and abbreviated analysis. It would include an analysis of alternative scenarios (or at least alternative development situations3). The output of a focused SEEA would contribute to decision-making on how to best reconcile the conflicting uses under study.4 A focused SEEA approach could be applied to either enhanced or compact SRMP.

Condensed SEEA – Analysis in a condensed SEEA would be limited to projecting social and economic impacts of the SRMP and its management directions. It would not compare alternative scenarios; the focus would be on one scenario comprising the draft management directions. It would contain a brief description of current socio-economic conditions in the study area, highlighting the main drivers of resource based economic activity. Thus a condensed SEEA is most suitable for a compact SRMP, which is limited to management of relatively fewer resource issues. An analyst preparing a condensed SEEA would rely on Building Block information and the Resource Analysis of the SRMP planning team for quantitative information and would not attempt to undertake new quantitative analysis. The main purpose of the SEEA would be to demonstrate how the SRMP supports or harms current and short-term economic activity and value and if harm is anticipated, recommend some mitigation options. Because a condensed SEEA will require less preparation time, its completion can be coordinated with the completion of the compact SRMP draft.

Who conducts the SEEA? One approach is to contract a consulting economist to prepare a SEEA. A qualified economist will have the appropriate skills to tackle the Net Resource Value analyses. They will also be perceived as independent. The second choice is for a BC

3 For example, comparing option values for use of two distinct sets of resources within the same geographical area. 4 The classic case in BC of difficult to reconcile resource value use is timber harvesting versus wilderness tourism. An MOF study

(Forest Practices Branch. December 2002. “The Benefits of Managing Forestry and Tourism at Nimmo Bay”. BC Ministry of Forests) is an example where a net resource value approach was taken to compare alternative management scenarios that dealt with possible conflicts between managing for timber harvesting and tourism at a nearby wilderness resort. The researchers estimated and compared economic rents from five scenarios, which were based on different timber harvesting prescriptions and perceptions of lodge visitors and employees about different viewscape impacts. Another example is presented in the SEEA conducted for the Besa-Prophet area of the Muskwa-Kechika (BriMar Consultants Ltd. August 2002. “Socio-Economic Assessment of the Besa-Prophet Pre-Tenure Plan”. BC Ministry of Sustainable Resource Management). The consultant focused on net resource value analyses of natural gas exploration/development and recreation use option values, examining economic value trade-offs between the two that are likely to arise if the area’s natural gas resources are explored and developed.



Government economist to undertake a SEEA. The third choice is for the planners who are preparing the SRMP to conduct the SEEA. MSRM’s Sustainable Resource Development Branch can supply a list of qualified consulting economists.

Timing for SEEA Work SEEA work may be required early in the SRMP process to work out issues associated with resource management conflicts. Or, the SEEA may wait until the end of the SRMP process when only a condensed SEEA is needed. Thinking can be done at this point on how new economic and social information can contribute to decisions that planners expect to make in devising and applying resource objectives.

It is always desirable to prepare terms of reference for a SEEA, setting explicit research priorities and boundaries to guide the consultant(s). The work of planners in devising terms of reference will have a significant impact on the utility of SEEA products; the planners need to make explicit their SEEA needs.5

When should a SEEA be started? The answer depends on whether a comprehensive, focused or condensed SEEA is planned.

Comprehensive SEEA – The timing of a comprehensive SEEA should be structured similar to the following Table.

5 SRMP planners should consult with staff in MSRM’s Sustainable Resource Development Branch while drafting a terms of

reference and reviewing draft SEEA reports. As well, completed terms of reference and SEEA reports should be filed with MSRM’s Sustainable Resource Development Branch.



Appendix Table 2: Timing Outline for a Comprehensive SEEA

Planning Steps Socio-Economic Input to Planning

Preliminary Organization and Plan Initiation After considering Resource Analysis and identifying key SRMP issues, select SEEA approach (comprehensive, focused or condensed)

Five months prior to submission of SRMP Prepare terms of reference (TOR) using templates6, assemble SEEA steering committee, consult with MSRM’s Sustainable Resource Development Branch re draft TOR, develop distribution list for TOR, issue TOR to distribution list, and develop decision-making criteria for selecting consultants

Three months prior to submission of SRMP Award contract to consultant(s) to undertake SEEA

Two months prior to submission of SRMP Review consultant(s) interim report on SEEA

One month prior to submission of SRMP Review draft SEEA report

Month prior to submission of SRMP Integrate results of SEEA into proposed SRM plan

Focused SEEA – A focused SEEA should be timed to offer information for decision-making as resource objectives are being finalized. This situation suggests that a focused SEEA should start soon after a Resource Analysis is conducted for the resource use values and plan sub-area(s) in question. The focused SEEA should be an integral piece in plan development and should not await the plan evaluation stage. Approximately four months should be allocated for a focused SEEA: two months to establish a terms of reference and select a consultant and two months for a consultant to research and submit a draft report.

Condensed SEEA – A condensed SEEA is primarily a descriptive product and will require less preparation time. Its completion can be coordinated with completion of the SRMP. Although a condensed SEEA will require about 12-15 consulting days, six to eight weeks should be allocated for selected consultants to prepare it. Another three weeks will be needed to prepare a suitable terms of reference and select a consultant, longer if a competition is staged to award the contract.

6 Available from MSRM’s Sustainable Resource Development Branch.



Cost to Conduct a SEEA SEEA cost will depend upon its scope and depth.

• Comprehensive SEEA – in the range of $20-25,000 in consulting fees plus travel expenses.

• Focused SEEA – in the range of $12-15,000 in consulting fees plus travel expenses.

• Condensed SEEA – in the range of $10,000 in consulting fees. No travel should be needed for a condensed SEEA.

The cost of a focused or condensed SEEA is highly dependent on the availability of viable information from secondary sources. If data must be developed from primary sources, such as tourism or forestry operator surveys, then the above-suggested costs are likely to be higher.

Data Sources for SEEAs • Building Blocks MSRM has developed a tool, referred to as economic “Building Blocks”, which provides information for socio-economic and economic development analysis. Each Building Block describes a resource-based economic activity as carried out in BC. They are assembled from secondary sources such as reports and anecdotal insights from industry experts.

Building Blocks provide a snapshot of the financial and operational characteristics of an ‘average’ business/operation and the characteristics and regulation of the resources that it relies on. They are written and organized so that qualitative and quantitative information can be extracted and applied in analysis exercises.

As well as providing an information source for SEEA, planners can use Building Blocks to improve their understanding of resource and infrastructure requirements of economic activities that are or could be located in the plan area. For example, Building Block information could be incorporated into their thinking on design of resource objectives and their application to particular areas. They can also be used in SRM plan meetings and presentations to inform plan stakeholders and other interested parties about key economic and regulatory relationships between business activities and resources.7

Table 3 provides an outline of Building Block content.

7 See Socio-Economic Analysis Building Blocks at http://srmwww.gov.bc.ca/rmd/ecdev/analysis/building_blocks.htm



Appendix Table 3: Building Block Outline

Elements What is Covered

Overview Brief description of the economic activity covered by the building block (sector/sub-sector/economic sphere) Identification of the geographic unit/area that the building block is restricted to

• The business that uses the resource • The associated businesses that provide materials and other direct

inputs into the business that uses the resources • The geographic area over which the building block would be

considered representative (i.e., the economic activity identified in the building block might vary significantly in the interior versus the coast – in such cases there may be a need to develop two building blocks for the same economic activity)

Coast/Land Resource Requirements/Sensitivities Overview of the coast and land resource inputs that are needed to support the economic activities

• Typically will consider Crown resources that must be accessible and usable to support the business. May include: rangeland; viewscapes; foreshore access; critical thresholds (level of resource use); and complementary/conflicting relationships with other resource values

Investment Requirements Provides a general overview of the level of investment required to start and maintain the business

• Start-up costs • Ongoing costs

• Future capital requirements (improvements, etc.)

Infrastructure Overview of the physical infrastructure that the businesses depend on

• Transportation • Energy • Communications, etc.

Market Overview of the general market for the products and services produced

• Location of the market (domestic/export)

• Access to the market (access costs, other market barriers) • Market demand

Labour Market Overview of general labour market requirements and benefits associated with the businesses represented by the building block

• Skill requirements • Wage rates (annual)

• Employment generated (person years) • Seasonality/intensity of the job (hours/year)



Appendix Table 3: Continued

Capacity Potential/capacity for growth/expansion given status quo

• Resource availability

Regulatory Regime Overview of the nature of the regulatory regime that governs activity within the business represented by the building block or the use of resources that the business depends upon

• Time generally taken to gain approval for use of resources or for the business

• General restrictiveness of the regulatory regime • Opportunities offered by the regulatory regime relative to

competitors

Government Revenues Overview of the types of government revenues generated

• Provincial revenues and where appropriate municipal and other revenues

Indicators Table Overview of inputs and outputs • Inputs required to support the economic activity

• Outputs resulting from the economic activities • Ratios showing economic activity/resource consumption

relationships, e.g. economic indicators (such as employment) per unit of consumed/produced resource

• Table supported by a brief discussion of critical thresholds affecting business viability and limits to growth

An analyst undertaking a SEEA could possibly extract the following pieces of information from a Building Block.

Economic Development frame – employment and income multipliers; employment per unit of consumed resource ratios; employment income levels; market drivers and success factors

Net Resource Value frame – cost of production; revenue per unit of consumed resource or production

Social frame – skill requirements and levels; seasonality

Government Finances frame– types of government revenue

• Other Data Sources for SEEA Other important data sources for conducting SEEAs are shown in Table 4.



Appendix Table 4: Other Data Sources for SEEA

Data Type Document Source

Regional Multipliers & Local Area Economic Dependencies

BC Local Area Economic Dependencies & Impact Ratios – 1996: BC STATS, 1999.

BC STATS

Provincial Multipliers from BC Input-Output Model

BC Provincial Economic Multipliers & How to Use Them: BC STATS, 2001. For a nominal sum, Statistics Canada sells a range of direct and indirect expenditure multipliers by industry and province.

BC STATS Statistics Canada

Timber Supply & Socio-Economic Analyses for Timber Supply Areas

Timber Supply Reviews http://www.for.gov.bc.ca/tsb/tsr2/tsr2.htm

Ministry of Forests

SEEAs for Land and Resource Management Plans (LRMPs)

http://srmwww.gov.bc.ca/rmd/lrmp MSRM

Allowable Annual Cut Decisions by the Provincial Chief Forester

Allowable Annual Cut Rationale Statements Ministry of Forests

Census data on population, labour force, and other demographic variables

See http://www.bcstats.gov.bc.ca Statistics Canada and/or BC STATS

Regional and community profiles See http://www.bcstats.gov.bc.ca/data/sep BC STATS

Data on Mineral Occurrences MINFILE Database MEM

Provincial Tourism Indicators See http://www.hellobc.com Tourism BC

Existing Tourism Use and Opportunities

Tourism Opportunities Studies MSRM

Agricultural Statistics Census of Agriculture Statistics Canada

Listings of Endangered Species Tracking Lists Conservation Data Centre, MWLAP




Data Type Document Source

Mapped Resource Values Maps of Existing and Potential Values for most Economic and Environmental Resources

MSRM and other Ministries

Source: adapted from Socio-Economic and Environmental Impact Assessment for Land and Resource Management Planning in British Columbia, November 2001.

A starting point in undertaking a SEEA is to take the Resource Analysis information and translate it into indicator data, such as person-years of employment, which are inputs to the various socio-economic analyses, such as economic activity analysis.

Assessing Incremental Impacts • Baseline In setting up a SEEA, the analyst should assemble a Baseline impact projection to compare against the SRMP impact projection.

The Baseline is current management directions and rules projected into the future. It is a “what if” analysis exercise and is a yardstick with which to gauge incremental impacts.

The incremental differences between the Baseline and the SRMP Scenario should be portrayed neutrally. SRMP planners and stakeholders will take the output of the SEEA and feed it into their own decision-making frameworks.

• No Approved Regional or Sub-regional Plan If a broader plan is not in place or that plan is judged as no longer relevant, a SRMP process may involve more than one scenario. In this situation, the SEEA would qualitatively and quantitatively estimate incremental differences in social, environmental and economic indicators between the alternative scenarios and a Baseline.

• Focused SEEA Situation There will likely be many situations where planners create and discuss alternative management directions/strategies for certain resource values in certain areas as they are developing a package of management directions for the SRMP area. Through discussion and sharing of available resource value information, most of these situations will be refined into a single agreed upon scenario. However, certain situations may evolve into conflicts between stakeholders and/or intense negotiations. For example, the subject of negotiation could be access into a high quality timber harvesting area where a nearby wilderness resort operator



is concerned about reduction of the wilderness experience. Planners could devise a few alternative access scenarios specific to this situation but each will have different social and economic implications. A SEEA applied to these access management scenarios could develop information that feeds into a decision-making process. In this type of situation, the aforementioned “focused SEEA” is likely to be appropriate.


Appendix 3 Conducting and Determining the Results of an Environmental Risk Assessment (ERA)

ERA is a science-based, transparent approach to assessing the implications of plan scenarios on environmental values.

Steps in Environmental Risk Assessment The following table summarizes the steps in ERA. Note that Steps 1 – 3 are the same steps that are undertaken in standard resource analysis. ERA goes further by identifying critical thresholds and risk classes (Step 4) and linking those to the magnitude and likelihood of impacts (Step 5). Steps 4 and 5 are described below in more detail. The final product allows planning teams to assess proposed management strategies with an understanding of the potential impacts on selected ecological indicators.

This approach is outlined in more detail in the document ‘Environmental Risk Assessment (ERA): an Approach for Assessing and Reporting Environmental Conditions’ (MELP 2000).8

Appendix Table 5: Steps in Environmental Assessment

Step 1 Establish context for ERA, e.g., scope of assessment data needs

Step 2 Identify cause-effect linkages, e.g. road access and wildlife mortality

Step 3 Specify key environmental values and identify indicators, e.g., seral stage distribution

Step 4 Identify critical thresholds and define risk classes, e.g., range of natural variability

Step 5 Determine magnitude and likelihood of impacts Assess degree of risk (very low-very high), e.g., computer modelling, GIS, professional judgement

Step 6 Report results and develop risk reduction strategies, e.g., identify mitigation measures

8 http://wlapwww.gov.bc.ca/wld/documents/era.pdf

Append ix 3 Conduc t ing and Dete rmin ing the Resu l t s o f an Env i ronmenta l R isk Assessment


Identifying Critical Thresholds and Risk Classes Risk assessment involves identifying “how much is enough” (i.e., how much can an ecosystem be changed before the effects on that ecosystem and the species it supports are unable to function adequately?). Each management regime that the planning process explores implies a set of changes on the land base. Risk classes are the categories of risk associated with those changes. ERA assumes that the more we change natural conditions, the higher the risk.

Appendix Figure 2: Environmental Risk Spectrum

“Threshold” and “benchmark” values (see Figure 2) provide the upper and lower bounds of risk assessment. “Thresholds” define the upper level of risk (i.e., the critical level beyond which there is a significant increase in risk to the ecological value of concern, for example, minimum viable population size, road density thresholds; habitat area requirements, habitat attributes). Conversely, a “low risk benchmark” is a condition with a high probability of sustaining the environmental value over the long term. Generally, low risk benchmarks are equated with the “range of natural variability” (RONV) i.e., the range of conditions that would be expected in an unmanaged system. The risk to an ecosystem is increased when the amount of change is beyond the range of natural variability.

There is no generic method for identifying thresholds and benchmarks. Domain experts can identify the most appropriate thresholds and benchmarks for the resources in your plan area, based on scientific evidence of the effect of change on ecological systems.

If you don’t have benchmarks and thresholds and don’t have the time or resources to figure them out, it is also possible to carry out a simple risk assessment by simply assuming that a certain amount of risk will be associated with each type of management zone.

Magnitude of change to ecological indicators Very low risk Low Risk Mod erate Risk High Risk V ery high risk

Range of natural variability (RONV);

Low risk benchmarks

Threshold

Magnitude of change to ecological indicators Very low risk Low Risk Mod erate Risk High Risk V ery high risk

Range of natural variability (RONV);

Low risk benchmarks

Threshold



Assessing the Likelihood and Magnitude of Impacts Step 5 in Table 5 involves applying a measurable value to each of the risk classes for each indicator. For example, the risk to northern goshawk might be assessed using the following risk classes in Table 6.

Appendix Table 6: Environmental Risk Spectrum for Northern Goshawk

Risk Class Amount of old and mature seral forest as a percentage of total forested land base by landscape unit

Low 75%

Moderate 50%

High 25%

Applying measurable values to risk classes is the crux of risk assessment. However, there can be a large amount of uncertainty involved, particularly where the cause-effect links are not well understood. Tools such as Bayesian Belief Networks can make explicit the process of assigning values and any associated uncertainties.

Once you have assigned values to the risk classes, it is a relatively straightforward process to conduct an analysis of your plan area and assess the level of risk associated with the outputs. It may be possible to apply this analysis to other SRMPs having similar ecological values. It may be useful to look to work done within your region or provincially to minimize duplication of effort.

Simplified Environmental Risk Assessment The risk assessment process does not need to be overly complex. At the very least, a simple qualitative approach to environmental risk assessment is possible. Table 7 lists a simple set of assumptions linking level of resource management to risk. Table 8 translates these simple assumptions into risk categories for a hypothetical plan area. This approach allows a relative comparison between alternative plan scenarios.



Appendix Table 7: Assumptions for Estimating Environmental Impacts

Factor Assumed Effect on Risk Rationale

Resource development intensity

Increased intensity of development results in increased risk to biodiversity

Lower intensity development areas provide more options and opportunities for maintaining native species and ecological processes

Habitat diversity Maintaining habitat diversity (variety of ecosystems, structural stages, patch sizes etc.) results in less risk to biodiversity

The needs of most forest organisms can be met by providing a variety of habitats (coarse filter)

Species range Plant and animal species with restricted ranges are more vulnerable than widely distributed species

Fewer options are available to maintain species with restricted ranges than those with wide ranges

High use public and commercial recreation activity

Increasing levels of recreational use will increase risks to environmental values

High levels of recreational use associated with trampling of vegetation, disturbance of wildlife, bear-human conflicts, human waste and litter

Uncertainty Lack of explicit management strategies for a resource increases risks to environmental values

Maintains the current level of risk

Open road density Increasing road density will increase risks to biodiversity

Increased human access associated with higher mortality risks for large mammals, esp. bears. Partly mitigable with access control

Timber harvesting land base (THLB)

Habitats within the THLB are at higher risk than habitats occurring outside the THLB

Habitat in the THLB is generally at higher risk of road development, increased human and machinery disturbance, and altered seral stage distributions

Appendix Table 8: Relative Risk Levels and Potential Impacts of Management Zones

Current Land Use Designations

Risk Level Rationale and Implications

Protected Areas Low Resource development not permitted. Road development limited; usually unroaded and undisturbed. Fish and wildlife habitat expected to remain stable. Potential disturbance from recreation

Preservation VQO Low Not included in timber harvesting land base




Current Land Use Designations

Risk Level Rationale and Implications

Retention VQO Low Low disturbance level (Max 5%) results in relative stability

Partial Retention VQO Moderate Maximum 15% disturbance permitted

Community Watershed Moderate “Maintaining water quality, quantity and timing of flow" are primary management objectives. Water quality objectives required; timber harvesting constrained

General Management High General landscape unit biodiversity measures (i.e. OGMAs) mitigate some impacts

Private land High Few restrictions on land use

Settlement High High degree of human use, high road density and fragmentation

Timber Harvesting Land Base (operable + marginal; subset of Retention and Partial Retention VQOs, Community Watershed, General, and Settlement)

High Significantly reduced mature and old forest cover; increased fragmentation and road density

Domain experts will still be needed to provide input into the relative risk of different management scenarios on an ecosystem or species. For example, the level of risk may change, depending on the amount of area in each type of zone.


Appendix 4 Ensuring Consistency with the Forest and Range Practices Act (FRPA)

Government sets resource objectives under the FRPA Forest Planning Practices Regulation and Government Actions Regulation for the purpose of forest stewardship plans. Objectives established by FRPA are an important baseline that should be considered when developing objectives in a SRMP. Objectives established in a SRMP, when legally established, may override a FRPA objective.

Objectives under FRPA are described in the Forest Planning Practices Regulation (FPPR) and Government Actions Regulation (GAR), and include:

• Default objectives listed in Part 2 of FPPR; and • Objectives established under Part 9 by the Minister of Forests

or Minister of Water, Land and Air Protection. (Note that MSRM has no objective setting powers under FRPA, only the power to designate Scenic Areas and Community Watersheds. All objective setting powers for MSRM come from the Forest Practices Code or the Land Act.)

It is recommended that a checklist similar to the following table be used to help ensure that the SRMP is consistent with the FRPA.

Append ix 4 Ensur ing Cons is tency w i th the Fores t and Range Prac t i ces Ac t


Appendix Table 9: Sample Checklist of Objectives Set by Government by Source

Value Source of Objective Set by Government

(In Order of Priority) Policy Direction Consistent

OIC

Regional LUP/

LRMP SRMP

Set by FRPA Regulation

FRPA Enabled

EBM, Working Forest, etc Yes No N/A

Soils

Timber

Water

Fish

Biodiversity

Wildlife

Resource Features

Cultural Heritage Resources

Recreation Resources

Visual quality

FRPA

Val

ues

Forage and Associated Plant Communities

Agriculture

Oil and Gas

Minerals

Non

FR

PA V

alue

s

Tourism/ Commercial Recreation



Appendix Table 10: FRPA Value Matrix

Value Addressed in FRPA

Objective Set by Government under FPPR and GAR

Default Results / Strategies in FPPR Factors in FPPR

Designations, Established Objectives, CF Standards in FPPR Practice Requirements

Soils s5: Conserve productivity and function

s35: Soil Disturbance

s36: Permanent access structures

s12.2: No practice requirements if result or strategy submitted and approved

Schedule-Factors s1: Factors for PAS and soil disturbance

N/A s37: Must not cause landslides

s38: Must not cause gully processes

s39: Must maintain natural surface drainage

s40: Must revegetate soils if …

Timber s6: Maintain or enhance supply; enable exercise of rights

N/A

FSP content requirement - s16: FSP must specify stocking standards

s26: Minister’s consideration of stocking standards

Schedule-Factors s6: Factors relating to stocking specifications

FRPA s26(3): alternate forest health

s43(2): CF may make standards for the use of seed

s41: Must not destroy brood if concentrated

s44(1)&(2): Must establish a stand

s44(4): Must ensure stocking standards for commercial thinning & special forest products

s43: Must comply with CF standards or altern-ative for use of seed; must keep records of seed use

s42: Use of livestock







Water s8: Conserve across landscape, water quality, fish habitat, wildlife habitat, and biodiversity associated with riparian areas

s47: Stream riparian classes and widths

s48: Wetlands

s49: Lakes


Schedule-Factors s2: Factors for water, fish, wildlife and biodiversity in riparian areas

s6 of GAR: Lakeshore management zones

s47(6): specify RRZ for S1 – A streams

s48(5): specify wetland zones

s49(3): specify RMA for L1 – A lakes

s8 of GAR: Community watersheds (CWS)

s62(1): Identify spring in CWS and specify distance

s50: Restrictions within RMA

s51: Restrictions within RRZ

s52: Restrictions within RMZ

s53: Requirements for temp sensitive streams

s54: Fan destabilization

s55: Stream crossings

s58: Use of livestock in riparian areas

s59: Protecting water quality

s60: Waterworks

s61: Excavated trails in CWS

s62: Roads in CWS if spring identified

s63: Fertilizer in CWS

Fish s8: Conserve across landscape, water quality, fish habitat, wildlife habitat, and biodiversity associated with riparian areas

N/A Schedule-Factor s2: Factors for water, fish, wildlife and biodiversity in riparian areas

s14 of GAR: Fisheries sensitive s56: Fish passage

s57: Protection of fish habitat

Bio-diversity

s9: Emulate natural disturbance patterns at the landscape level and retain wildlife trees at stand level

s64(1): Max cutblock, minor tenures exempt

s64(2)-(4): Exemptions

s65: Adjacency, minor tenures and s65(2)-(4) exempt

s66: Wildlife tree retention


s129: Factors for biodiversity

N/A s67: Must not harvest from wildlife tree retention areas referred to in s67

s68: Must retain coarse woody debris







Wildlife s7: Conserve sufficient area for survival of species at risk, regionally important species, and specified winter survival

N/A N/A s105: Species at risk, regionally important wildlife and specified ungulate species

s106: Wildlife habitat areas

s107: Ungulate winter range

s108: General wildlife measure

s115: Identify…list…as a wildlife habitat feature (FRPA s154(2)(a)(ii))

S69: Must comply with general wildlife measure

s70(2): Must ensure that the activity does not damage or render ineffective a wildlife habitat feature

Resource Features

s5(1) of GAR: Definition of Resource Features

N/A N/A s5(1) GAR: Identify as a resource feature

s70(1): Must ensure that the activity does not damage or render ineffective a resource feature

Cultural Heritage Resources

s10: Conserve or where more appropriate, protect cultural heritage resources

N/A Schedule-Factors s4: relating to traditional use by an aboriginal people

N/A N/A

Recreation Resources

N/A N/A N/A s56 FRPA: Interpretive forest site, recreation site or recreation trail and features

N/A

Visual Quality

S9.2 establishes VQOs for scenic areas established prior to October 2002

N/A N/A s7(1) GAR: establish an area as a Scenic Area

s7(2) GAR: establish VQOs for a Scenic Area

N/A

Forage and Associated Plant Com-munities

N/A s17: FSP must specify measures to prevent the spread of invasive plants and mitigate impacts on natural range barriers

N/A N/A N/A

Append ix 5 De te rmin ing SRMP Leve l o f Complex i t y : Focused Versus Comprehens ive SRMPs


Appendix 5 Determining SRMP Level of Complexity: Focused versus Comprehensive SRMPs

A SRMP that is developed to address a small number of specified issues involving a small number of resource values (e.g. resolution of conflicts between motorized and non-motorized recreation, management direction for expansion of heli-skiing, grizzly bear management strategy, etc.) is referred to as a focused SRMP.

A SRMP that is developed to address more complex planning issues involving a multitude of resource values is referred to as a comprehensive SRMP.

Notwithstanding the reference to focused and comprehensive SRMPs, the degrees of complexity for SRMPs can best be described as a spectrum that ranges from very simple and focused plans at one end to highly complex multiple resource use plans at the other end. Ultimately, both focused and comprehensive processes will need to be based on analysis methods that result in the establishment of balanced objectives. The following table compares each SRMP type.

Appendix Table 11: SRMP Comparison Table

SRMP TYPE PROS CONS

FOCUSED • May be lower costs in the short term • Fast track SRMP planning process in

assessing one scenario • Fewer requirements for detailed

resource inventory information and data coverages

• Less intensive data preparation and resource analysis

• Less complex process

• Reduced timelines to complete SRMP plan development

• May be higher costs over the long term • Reduced involvement of stakeholders and public

interests and scientific domain expertise • Is subjective due to lack of quantitative evidence

• Less capacity for anticipating future uncertainties • May inadvertently forego more sustainable future

scenarios

• Less transparent process • Less likely to achieve up-front buy-in by diverse

interests of the SRMP results • SRMP results may be challenged by public

interests and other experts

Focused SRMP The resource analysis requirements and the time and effort required to complete a focused SRMP are fairly minimal compared to a comprehensive SRMP.

Comprehensive SRMP The analysis requirements for a comprehensive SRMP will usually require analysis of several planning issues and an assessment of multiple planning options or scenarios. In addition, a socioeconomic assessment and/or environmental risk assessment of a final preferred planning scenario would likely be required.

Append ix 5 Methods fo r Under tak ing Imp lementa t ion and E f fec t i veness Mon i to r ing



SRMP TYPE PROS CONS

COMPRE-HENSIVE

• May be lower costs in the long term

• Involvement of diverse stakeholders, public interests, scientific domain expertise improves quality of learning scenarios and composite scenario

• More intensive and explicit analysis of inter-relationships (compatibilities and conflicts) amongst resource values and objectives

• Utilizes comprehensive resource inventory data coverages in SRMP scenario analysis and reporting

• Multiple scenario analysis enables greater capacity and flexibility to respond to future uncertainties

• Results are likely to be more integrated

• May be higher costs in the short term

• Is subjective due to lack of quantitative evidence • Requires more comprehensive resource

information and availability of clean data coverages for use in analysis

• Requires commitment and continuity of participation by stakeholders, local interests and scientific domain expertise

• More time consuming process to complete scenario planning process in support of SRMP plan development


Appendix 6 Methods for Undertaking Implementation and Effectiveness Monitoring

This appendix describes approaches that can be used to undertake implementation and effectiveness monitoring for SRMPs.

Goals of SRMP Moni tor ing and Repor t ing To be successful SRMP monitoring must be able to collect data, summarize the data into useful information, and interpret that information to advance knowledge and improve management decisions. Key components of a structured monitoring program include data collection, information management, preparation of data summaries and interpretive reports, feedback to management, and program coordination and support. Essentially, monitoring helps MSRM and SRM planning partners to determine whether or not the plan is being implemented consistently and if implementation is being effective. Steps could then be taken to modify aspects of SRMP direction on resource and land use if necessary.

SRMP monitoring and reporting is intended to provide decision-makers, practitioners and the public with the following benefits:

• Support planning and decision-making – provide information on the status of SRM planning across the province to help set priorities, improving and influencing decisions, legislation, policies, planning, plan implementation and practices.

• Reveal key trends and conditions – advise about the overall state and trends relative to plan desired outcomes, including the identification of potential issues that require special attention.

• Enable science, research, information and knowledge systems – provide scientific and technical knowledge, expertise, and tools and supporting information systems to improve SRMP implementation and effectiveness.

• Clarify the status of risk-based values and priorities – provide information about the status and course of plan values that are currently or potentially considered a priority due to their level of risk.

Designing an SRMP Moni tor ing Program The following material describes the general steps to design and implement an SRMP implementation and effectiveness monitoring and evaluation program. These steps are based on the Monitoring Guide prepared by the USDA Forest Service, Inventory and



Monitoring Group.9 This approach supplements MSRM’s existing policy and procedure on Strategic Land Use Plan monitoring.10

Step 1 Program Initiation

Initiate monitoring program and organize monitoring logistics:

• Identify the SRMP Interdisciplinary Team (ID Team); and • Define roles associated with monitoring and evaluation (e.g.,

management, data correction, interpretation, reporting).

Step 2 Define Monitoring Program Purpose and Scope

Identify the purpose/objective of monitoring:

• Clarify the purposes for monitoring, e.g., To monitor specific SRMP decisions (particularly those

with high risk); To monitor public concerns about the SRMP; To monitor the results of specific administrative

decisions; and To monitor the state of systems.

• Identify the desired outcomes of monitoring: Who will do what with the information as a result?

• Determine the relationship of SRMP level monitoring to other scale monitoring programs.

Define the study area for monitoring: • Define the bounds or outer extent of the monitoring program

(SRMP boundary or other defined area); and • Determine if the monitoring program is designed and

implemented on a single SRMP or multi-SRMP initiative.

Define the role of partners: • Identify the role of other agency partners in monitoring in the

design, implementation and analysis of the monitoring program; and

• Collaborative efforts can play an important role in the sustainability monitoring process in a number of ways:

Creating a basis for dialogue;

9 United States Department of Agriculture - Forest Service. Program Guidance for Development of a Forest/Grassland Monitoring

and Evaluation Program. Inventory and Monitoring Institute, Fort Collins, Colorado. Pamela A. Wright. http://www.fs.fed.us/institute/lucid/final_report/

10 See Provincial Monitoring Framework for Strategic Land Use Plans (July, 1999), and Strategic Land Use Plan Monitoring Procedures (May 2, 2000). Available at http://srmwww.gov.bc.ca/rmd/lrmp/lrmppolicy.htm



Helping to identify key components for monitoring; Establishing reference values; Finding alternative sources of data.

Review the policy context for monitoring: • Legislation and regulations; and • MSRM policy objectives.

Step 3 Define the Framework and Approach to Monitoring

Review the SRMP outputs (objectives, targets, measures, criteria and indicators) and use these as the common core to organize and select monitoring elements:

• Adopt a common SRM planning framework defined by principles, criteria and indicators that serves as the common core for organizing the monitoring program (e.g. old growth targets by LU and BEC).

Step 4 Identify the Monitoring Purposes and Questions

Identify SRMP specific monitoring question(s) for each systems framework element based on the specific concerns and issues:

• Questions relate to the broad purposes (e.g., specific SRMP decisions, public concern, administrative decision, state of system); and

• Monitoring questions are higher order questions relating to the aspect of the plan to be evaluated or the structure or function of the system.

Categorize the monitoring question according to the broad purposes for the monitoring activity:

• To monitor specific SRMP decisions (particularly those with high risk, for example, high biodiversity emphasis LUs with significant resource pressures to ensure a balance between economic outcomes and sustainability);

• To monitor public concerns about the SRMP; • To monitor the results of specific administrative decisions (e.g.

objectives to balance oil and gas with timber harvesting in a sustainable manner); and

• To monitor the state of ecosystems, resource use, etc.

Step 5 Identify Monitoring Indicators

Select monitoring indicators based on the following desirable characteristics of “good” indicators:



• Measurable: Measures should be quantitative, i.e. subject to measurement.

• Reliable: Measures should be capable of being assessed precisely and accurately (repeatable measures by different personnel).

• Cost-effective: Measures should be capable of being measured cost-effectively, generally by field personnel using simple equipment and techniques.

• Significant: Measures must relate to significant conditions or features. A good measure should be capable of detecting changes that, if they occurred, would be considered serious problems.

• Relevant: The types of changes that are to be detected through the monitoring of indicators should identify changes that result from management activities that we can control. Changes caused by natural acts should be handled on a case-by-case basis.

• Sensitive: Measures should focus on sensitive components of the monitoring element e.g., components that provide an early warning system, alerting managers to deteriorating (or improving) conditions while there is still time to change things.

• Efficient: Measures are most efficient if they reflect the condition of more than themselves, because this reduces the number of parameters that must be monitored.

• Responsive: The types and/or causes of change that are to be detected through the monitoring of measures should be responsive to management control.

Step 6 Describe and Define Individual Monitoring Protocols

Determine and document the specific methods, protocols, frequency of collection, statistical requirements, data storage, cost, and persons responsible for each monitoring element.

• Where possible, identify reference values to help interpret and evaluate the meaning of monitoring results.

Step 7 Write the Monitoring and Evaluation Chapter of the SRMP

Describe the monitoring program in the Monitoring and Evaluation Section of the SRMP.



Step 8 Develop annual monitoring program based on available budget and monitoring direction contained in the SRMP

• Maximize linkage to project level monitoring programs for an efficient program;

• Look to form partnerships with volunteers, other agencies, and special interest groups to accomplish the monitoring objectives; and

• Document the work to be done for each monitoring indicator.

Step 9 Conduct monitoring/collect monitoring data, including the incorporation of new data, following the agreed upon monitoring protocols.

Maximize linkage to project level monitoring programs for an efficient program. For example, watershed monitoring for fish sustainability, conducted at the LU level, should be linked to objectives in the SRMP.

Step 10 Analyze monitoring data against reference values

Compare the monitoring results against the defined reference values to determine if the reference values are exceeded. For example, measure wildlife tree retention (WTR) targets in the SRMP against any new information such as timber harvesting or other depletions to determine if the WTR threshold by LU is met or exceeded.

Step 11 Evaluate monitoring results to identify changed conditions, risks, management concerns, etc.

Describe and document situations that indicate where plan provisions are and are not working as intended .For example, indicate where a measure to attain economic return from backcountry recreation is not being successfully met and indicate where modifications in direction might provide better economic return for this value.

Step 12 Document monitoring findings and recommendations

Document recommendations and findings based on the data analysis and evaluation. Possible recommendations might include:



• No need for change, continue implementation as directed in the objectives; for example, timber targets are being attained as planned, continue on course;

• Continue implementation but intensify monitoring activities where results are questionable; for example, water quality in an identified LU may be compromised, confirm through local watershed specific water quality assessment as appropriate;

• Improve implementation of current plan; • Prepare a minor amendment to the plan; for example, this may

consist of new or amended objectives that apply in portions of the SRMP or to the entire SRMP area;

• Prepare a major amendment to the plan; for example, a new resource chapter for oil and gas is required for a SRMP, based on new resource use demand, requiring integration with existing resource values and the establishment of new, balanced objectives to account for oil and gas in the SRMP area; and

• Adjust the monitoring program; for example, adjust subsequent monitoring to account for oil and gas economic measures in the preceding SRMP.


Appendix 7 Recreation Opportunity Spectrum This appendix describes the various classifications that are included in the Recreation Opportunity Spectrum (ROS).

Primitive (P) – very high degree of remoteness and naturalness; very little or no motorized use; 5,000 ha or more in size; eight km or more from a rough dirt or gravel road.

Semi-primitive, non-motorized (SPNM) – similar to the remoteness and naturalness criteria for the ‘P’ ROS class; very little or no motorized use within area; 1,000 ha or more in size; one km or more from a rough dirt or gravel road.

Semi-primitive, motorized (SPM) – similar to SPNM except for greater motorized use within the area.

Roaded natural (RN) – a moderate to high degree of naturalness in the surrounding environment as viewed from a travel route (existing visual condition would be preservation or retention in perspective view); area is within 1 km of a 2-wheel drive road and has no size criteria.

Roaded modified (RM) – dominated by resource extraction and numerous roads (e.g., timber harvesting and dominant man-made structures, such as a ski hill); within one km of a 2 or 4-wheel drive road and has no size criteria.

Rural (R) – dominated by human development and settlements associated with agricultural land (e.g., farmland, utility corridors, and some service commercial); many interactions with other people are expected; recreation facilities may be highly developed and easily accessed.

Urban (U) – landscape substantially altered by urban development; highly developed recreation facilities; very high number of recreation users expected; intensified motorized use and parking available.


Appendix 8 Visual Quality Objectives Rating for Backcountry Tourism

The following table describes the different visual quality objectives that are used for rating backcountry tourism visual landscapes.

Appendix Table 12: Visual Quality Objectives Rating for Backcountry Tourism

VQO Rating Description

Preservation No visible change will occur in the landscape from forest development practices

Retention Management activities or alterations may occur but are not visually apparent. The goal is to repeat the line, form colour and texture of the characteristic landscape. In perspective, openings are generally 0.1 to 1.5% of the landscape assessed

Partial Retention

Human-caused alterations are visibly apparent but remain subordinate to the characteristic landscape. Repetition of the line, form colour and texture is important to ensure a blending with the dominant elements. In perspective, opening sizes are generally 1.5 to 7% of the landscape unit assessed

Modification Human-caused alterations dominate the original characteristic landscape; however, alterations must borrow from natural line and form to such an extent and on such a scale that they are comparable to natural occurrences. In perspective, opening sizes are generally 7.1 to 18% of the landscape unit assessed

Maximum Modification

Human-caused alterations are out-of-scale on the landscape and exhibit attributes that are not in keeping with natural occurrences, particularly in the foreground and middle ground. In perspective, opening sizes are generally 18.1 to 30% of the landscape unit assessed


Appendix 9 Examples of Analysis Methods for Backcountry Tourism Products

This appendix includes two examples of analysis methods for assessing backcountry tourism products.

Example 1. Def ining Backcountry Tourism and Recreat ion Prior i ty Zones

A possible SRMP product might be the identification of zones that will receive a management priority for backcountry tourism and recreation management. Such zones could, for example, be characterized by objectives to maintain a particular ROS, or the definition of objectives and strategies aimed at preventing/mitigating other economic development activities from impacting adversely on tourism/recreation values. If this was the case, then the technical process could be expected to generally involve the following steps, aimed at ensuring that:

• The zones are established on lands that possess valuable tourism/recreation characteristics;

• There is some justification for establishing the zones, in terms of there being a sufficient level of existing and/or future demand for tourism and recreation experiences in this area;

• That the proposed tourism and recreation uses have been considered in relation to the presence of other resource values and users so that resource use integration and impact mitigation occurs; and

• The environmental, social and economic implications of the proposed tourism and recreation uses have been duly considered.

Step 1 Understand Backcountry Tourism and Recreation Capability and Suitability Identify the geographic locations in the plan area with relatively high biophysical capability and land use suitability for various backcountry tourism and recreation uses. Include the identification of existing tourism and recreation uses. Sources of information for this step are likely to include: MSRM inventories for tourism and recreation, and tourism opportunity studies if they have been developed. Also, local knowledge is likely to be an important information source.

Step 2 Demand Analysis

Append ix 9 Examples o f Ana lys is Methods fo r Backcoun t ry Tour i sm Produc ts


Confirm that there is sufficient expected demand for the tourism/recreation activities to warrant the identification of plan zones, objectives and strategies that are designed to support the allocation and management of Crown lands and resources for these purposes. This will require assembling trends information on historical and projected visitor use for various activities. Some tourism opportunity studies develop this type of information and BC Stats data is a source that should be referenced. The extent of demand and the associated socio-economic benefits associated with the demand will help provide a justification for the zones and will assist in shaping planning decisions on how extensive and ‘strong’ the zones, objectives and strategies should be relative to the need to consider and accommodate other sectors’ needs.

Step 3 Analyze Resource Interactions Assess the interactions with other valued resources. Normally this will involve performing overlay analysis of inventory maps showing resource capability and suitability or surrogate mapping if capability/suitability mapping is not available. For example, an overlay analysis of tourism/recreation value mapping with forestry values, wildlife habitat, resource tenures, etc., will reveal the geography of value conflict and compatibility.

Step 4 Develop Tentative Zones and Objectives Develop draft tourism/recreation priority zones and objectives based on the preceding demand and resource interaction analyses. Draft zones and objectives will also be guided by direction provided in broader LRMPs (if available), the statement of issues that the planning process has formerly identified, and plan-wide goals or objectives that have been developed for tourism/recreation during the planning process.

Step 5 Assess Implications Evaluate the implications of the tentative zones and objectives. Normally this will occur as part of a broader evaluation of a complete land use plan scenario. An attempt would be made to estimate the environmental, social and economic ramifications of the proposed priority management zones for tourism and recreation. Indicators that have been developed during the planning process would be used for this purpose. The evaluation results will determine



whether or not the draft zones/plan represents an appropriate package, or if modifications to zones and objectives are warranted.

The same general sequence of events could be followed to deal with backcountry tourism – recreation conflicts, or conflicts with wildlife resources. That is, the information on values of concern would be assembled; the information would be analyzed to understand resource interactions; draft objectives/strategies/zones would be designed to integrate resources and mitigate impacts; and the implications of the draft proposals would be evaluated to determine the nature and scope of the pros and cons. The evaluation might include an environmental risk assessment of the alternatives.

GIS will play an important role in this process to reveal resource interactions and to generate tabular statistics necessary for measuring indicators. GIS models can also be developed to help determine where it might be appropriate to locate priority management zones, either for tourism/recreation or wildlife habitat to protect this value from the potential impacts of tourism/recreation. This would involve developing some ‘decision rules’ (i.e., criteria) for guiding zone definitions. For example, if the aim is to assign a backcountry tourism management priority to certain areas (for example, because of an interest in economic diversification and knowledge of suitability and demand), you could start by identifying the specific land characteristics that are needed to support that priority, such as:

• High capability/suitability polygons for winter-based recreation product;

• Areas that are experiencing steady growth in demand for winter-based recreation activities;

• Areas with relatively low importance for mountain goat and caribou wintering and kidding/calving areas; and,

• Areas with no active or projected industrial development in the foreseeable future (e.g., 10 year timeframe).

Querying the GIS to generate a derivative map showing the intersection of these areas will provide a first approximation of where the top priorities might be for a tourism/recreation priority zone. Working iteratively with more detailed mapping, developing objectives and strategies for integrating resource values and mitigating impacts and assessing implications would then follow to enable planners to arrive at a proposed land use plan scenario that includes land use zones and objectives for backcountry tourism and recreation.



Example 2. Addressing Capacity Management Issues

If a key backcountry tourism/recreation management issue in a SRMP process relates to managing for carrying capacity, the analysis challenge will be to define appropriate indicators and thresholds for monitoring trends in the indicators and committing to an adaptive management approach. The general steps to develop provisions in a SRMP that attempt to deal with capacity management are:

• Define the spatial area where carrying capacity issues are evident (i.e., where you want the capacity management provisions to apply), and sub-units, as appropriate;

• Identify social and environmental concerns and issues;

• Collect and record baseline data;

• Formulate recreation capacity objectives for the area;

• Select and monitor social and environmental indicators; and

• Adapt recreation management on the basis of monitoring results.

For specific instructions on how to implement a capacity management program see: "A Recreational Capacity Management Program for BC" – available at http://srmwww.gov.bc.ca/rmd/lrmp/s2s/reports/


Appendix 10 Decision Analysis and Reporting Tool (DART) MSRM has recently developed reporting and analysis tools that will provide information that can be used to assess potential timber supply and environmental impacts from landscape/watershed planning.

Decision Analysis and Reporting Tool (DART) The SRMP Decision Analysis and Reporting Tool (DART), is a corporate, computer-based tool that enables standard analysis routines and reporting in support of ministry landscape/watershed level planning.

Within the DART tool there is the capability to analyze the biological effectiveness of proposed Old Growth Management Areas (OGMAs) using the “Automated Effectiveness Indicators” (AEI) tool. The AEI tool queries the Forest Cover database to generate a list of surrogate indicators that identify potential old growth attributes. The AEI tool primarily focuses on comparing attributes of OGMAs with attributes of the remainder of the old forest, or remainder of the landscape (as appropriate) to allow experts to summarize the biological values captured or not captured in implementation of the LUPG. The deviation from existing natural forest conditions can then be interpreted within a relative risk framework to inform the planning process. Some of the more useful old growth attributes available in the AEI tool include:

• Average site index by leading species – by BEC variant. Representation within OGMAs compared with entire landscape unit;

• Average height by leading species – by BEC variant. Representation within OGMAs compared with all old forest in a landscape unit;

• Slope/Aspect class – Representation within OGMAs compared with landscape unit;

• Leading species – Representation of leading species in OGMAs compared with landscape unit – by BEC variant;

• Seral stage distribution – Compares seral distribution within OGMAs with seral stage distribution within Landscape Unit. Presents seral stage distribution for ‘predicted historic’, ‘current’ in Landscape Unit and ‘OGMAs’;

• Forest interior – Amount of forest captured within all OGMAs – all variants combined compared to targets in the Biodiversity Guidebook (Width of interior buffers: NDT1&2: 160m; NDT3: 120m; NDT4: 100m);

Append ix 10 Dec is ion Ana lys is and Repor t ing Too l (DART)


• Size classes of forest interior for each OGMA – A breakdown of the number of OGMAs that fall within various size classes;

• Connectivity – An assessment of the connectedness of the OGMAS within the Landscape Unit;

• Patch size – Number of OGMAs that are within patch size classes 1 (<50ha), 2 (51—250ha), 3 (251-500ha), 4 (501-1000ha), 5 (1000ha +); and

• Recruitment – A breakdown of the area within OGMAs that falls within 20-year age groupings.

An example of the DART/AEI output is provided in Figure 8. This indicator compares the average site index (forest productivity) by leading trees species (Inventory Type Group) for areas proposed as OGMAs to the remainder of the BEC variant (SBSvk) in a landscape unit. An inspection of this output indicates that the average site index for deciduous tree species (DECID) as well as lodgepole pine (PL) is slightly higher in the proposed OGMAs, whereas the average site index for Douglas fir (Fd) and western hemlock (H) is lower compared to the remainder of the SBSvk within that landscape unit. To determine if there is significant over-representation or under-representation, the variation between the OGMAs and available forest in the landscape unit needs to be considered. This can be ascertained from the second graph, which shows the variation between the OGMA and the existing natural conditions of the landscape unit. This deviation can be interpreted to assess how well the proposed OGMAs compare to the rest of the landscape unit using assigned risk thresholds.

For example, using a five-level risk rating scheme where 0-20% variation is considered ‘very low’ risk; 21-40% ‘low’ risk; 41-60% ‘moderate’ risk; 61-80% ‘high’ risk and > 80% ‘very high’ risk, this output suggests that the proposed OGMAs in the SBSvk are fairly representative of the available forested area considering only the site index by leading species indicator. This is due to the fact that there is a only a small deviation (<20% or very low risk) for five of seven leading species with only a slightly higher over-representation for the remaining two leading species (20-40% or low risk) compared to existing natural conditions. It should be emphasized, however, all of the variables need to be compared because there may be both positive and negative aspects when all attributes are summarized (see the AEI tool document for further details).

Append ix 10 Dec is ion Ana lys is and Repor t ing Too l (DART)


The following is an example of DART and AEI Tool output.

Although the DART and AEI tool is a useful analytical technique that will enhance the analysis of potential OGMAs, it has limitations including:

• It uses surrogate variables based on forest cover data, which may not be ecologically appropriate;

• Some of the indicators are difficult to interpret because of unknown natural patterns or high variation in natural patterns; and

• At this time, the AEI tool assesses OGMAs only.

Potential opportunities exist, however, to improve the AEI and DART tool by importing stand attribute data from other inventories, such as Vegetation Resource Inventory (VRI) or Rare Ecosystem Mapping, and extending the analysis to include other areas of old forest that contribute to biodiversity objectives (e.g. riparian areas). A summary of sample sizes should also accompany any of the DART/AEI outputs.

0

5

10

15

20

25

30

B CW DECID FD H PL S

Leading Species (ITG Group)

Representation of Average Site Index by ITG Groups: SBS vk

BEC Variant OGMA

Representation of Average Site Index by ITG Groups (Variation): SBS vk

-100

-75

-50

-25

0

25

50

75

100

B CW DECID FD H PL S

Leading Species (ITG Group)


Appendix 11 Coarse and Fine Filter Habitat Supply Models Habitat Supply Models11 are another group of decision-support tools that can provide useful data for risk assessment. They provide a means of forecasting habitat availability over time similar to timber supply models. Habitat supply models are useful for evaluating and comparing alternative land use scenarios because they provide planners with output that can depict the spatial distribution and total amount of suitable habitat available at discrete time periods. For example, coarse filter models can be developed using seral stage data or forest cover age classes and run through a computer simulation tool (see “A Strategy for Habitat Supply Modeling for British Columbia. Draft Volume II. Appendices”) 12. Spatially explicit simulations provide a variety of outputs to users but are most useful because they allow planners to “see” the effects of alternative management strategies. Similarly, fine filter habitat supply models can be developed for a particular species and used to understand the long-term consequences of management actions at the landscape and stand levels. These models are most useful for predicting the supply of habitat to provide a specific life requisite (e.g., nesting habitat, winter range) for a particular species or group of species with similar habitat requirements (i.e., species guilds).

In addition to models that are solely habitat-based, there are spatially explicit population models (SEPMs) that can also be applied to understand species responses to management at the landscape scale. However, these models require habitat-specific information about demography, dispersal behaviour and habitat selection. Although these models could provide valuable information to inform the decision-making process, the types of data required are rarely available for risk assessment purposes during land use planning. As such, models that are solely habitat-based are the most likely models developed to inform land use decisions.

If there are opportunities during the planning process to develop habitat supply models, their outputs should be interpreted within the ERA framework. This would typically require estimating how much habitat or seral stage will be present (total hectares) at discrete time periods (e.g., 0, 20, 50, 100 years) and comparing that amount to a predefined benchmark with established

11 http://www.for.gov.bc.ca/hfp/silstrat/habitat/habitat-docs.htm#hsmbc A Strategy for Habitat Supply Modeling for British Columbia.

Draft Volume I.” 12 http://www.for.gov.bc.ca/hfp/silstrat/habitat/habitat-docs.htm#hsmbc A Strategy for Habitat Supply Modeling for British Columbia.

Draft Volume II. Appendices”

Append ix 11 Coarse and F ine F i l te r Hab i ta t Supp ly Mode ls


thresholds. Establishing scientifically defensible benchmarks and thresholds, however, poses significant challenges to planners and analysts because they are inherently complex and there is often a lack of empirical research to support specific thresholds. Nonetheless, benchmarks and thresholds must be defined using the best available information with full recognition of their limitations. Maintaining seral stage distributions within the range of natural variability13 is considered to be an appropriate ecological benchmark for comparison.

Although maintaining components of biodiversity within their range of natural variability is intuitively appealing, and may make ecological sense, a number of factors complicate the use of this benchmark. In particular, there often is insufficient data on past conditions and natural disturbance regimes to actually define the range of variation. Furthermore, defining an appropriate time period is often confounded by past human activities, climate change and the nature of vegetation response (i.e. how far back do you go?). Although these are difficult issues to address, the best approach is to define an ecological rationale for choosing a particular benchmark as well as clearly stating the assumptions and associated uncertainties. In an effort to provide the most relevant time period, for example, the range of natural variability should be assessed over relatively consistent climatic conditions. As some researchers have suggested, understanding what kinds of changes have occurred in a region and how particular ecosystems respond may be most relevant because they provide clues on how to manage for adaptability and resilience.

Using a “low risk benchmark” may be a pragmatic approach to assessing impacts from land use change. The ERA approach defines a low risk benchmark as conditions with a high probability of sustaining the environmental value over the long term. Defining this benchmark helps to identify what landscape and stand-level attributes need to be maintained, but also highlights the linkages between environmental threats or pressures and potential impacts. The low risk benchmark should be based on scientifically and biologically sound principles and not on a particular agencies’ or interests “acceptable level” of risk. However, critical thresholds still need to be identified to determine the level at which the probability of maintaining specific environmental values diminishes significantly. Although this also poses challenges to analysts as critical thresholds are often species and scale dependent, some threshold values have been suggested based on modeling and empirical research. For example, using various landscape metrics

13 According to Landres et al. 1999 ‘natural variability’ is defined as the ecological conditions and the spatial and temporal variation

in these conditions that are relatively unaffected by people within a period of time and geographical area appropriate for an expressed goal.



and applying those to a broad range of taxa, thresholds for the proportion of suitable habitat that must remain in a landscape have been estimated to be between 60-70% (i.e., 40-30% unsuitable), below which habitats become fragmented and species abundance are likely to decline. Using these values as critical thresholds, risk categories can be developed along a linear or non-linear continuum and the significance of the habitat supply output from either a coarse or fine filter model could be interpreted using the percent reduction in habitat suitability and placed into risk categories.

Appendix Table 13: Example of Habitat Supply Thresholds and Assigned Risk

Risk Level Percent Reduction in Habitat Availability

Very Low 0-10

Low 11-20

Medium 21-40

High 41-60

Very High 61-100%

Other examples of thresholds have also been identified relating road density to mortality risk, habitat suitability and occupancy for large vertebrates (e.g., bears, wolves, ungulates). This research has suggested 0.6 km/km2 as a potential threshold above which areas become unsuitable for wide ranging species that are vulnerable to human-caused mortality.

Although using habitat supply models is a preferred decision-making tool to inform the planning process and risk assessment, a number of key technical barriers to using habitat supply models have been identified including: a lack of knowledge about habitat–species relationships, thresholds, and baseline information; insufficient detailed biophysical inventory and inadequate training and extension (Jones et al. 2002). These constraints often limit the scope of the risk assessment forcing planners and assessors to rely on static area summaries and professional judgement to make conclusions.

Habitat supply models are also limited to evaluating the effects of forestry activities. In plan areas where other forms of resource development are the primary threat to biodiversity, other models and methods may need to be developed. This may require explicitly modeling responses to human disturbance, linear developments and/or relying on static GIS areas summaries.



Bayesian Belief Networks Bayesian Belief Networks (BBNs) provide a means of modeling likelihoods of management effects. A BBN is a form of influence diagram, which depicts the hypothesized or causal relations among ecological factors that influence the likelihood of outcome states of interest, such as forest condition or wildlife species viability. Bayesian Belief Networks have been developed to assess sediment risk, salmonid population viability and to evaluate effects of land management alternatives for the Interior Columbia River Basin in the United States (Marcot et al 2001). In British Columbia, BBNs have recently been used to assess risks to coarse and fine filter biodiversity as part of the North Coast Land and Resource Management Plan (LRMP). These assessments incorporated a number of decision-analysis tools, static area summaries and habitat supply models that were fed into a BBN.

BBNs are particularly useful because they can incorporate both empirical information and expert opinion. They are relatively transparent because the ‘causal webs’ or how a particular pressure (e.g., road density) influences a particular habitat or population variable is made explicit. In addition, they can provide a method of dealing with uncertainty through sensitivity analysis and varying input parameters and conditional probabilities. Despite some of these positive aspects, BBNs can become overly complicated and rely too heavily on expert opinion. This is usually the result of including too many nodes, which reduces communication value, and not having enough empirical information, which reduces objectivity. Used appropriately, however, they can provide useful insights into land use planning processes.

It is worth emphasizing that whether BBNs are used or not, identifying linkages through a diagram or a conceptual model is a useful way to express the relationships described by the risk hypotheses. Conceptual model diagrams or “envirograms” can help communicate important pathways in a clear and concise way and identify major sources of uncertainty. The primary purpose of a conceptual model is to clearly identify the linkage between land use change and a particular element of biodiversity. Risk assessors can use these diagrams and risk hypotheses to identify the most important pathways and relationships that will be evaluated in the analysis phase. The ERA framework provides examples and also describes the data and measures to be used in the risk assessment including how risks will be characterized.


Appendix 12 Provincial Heritage Register Database The Archaeology and Registry Services Branch of MSRM maintains a database of all known archaeological sites as the Provincial Heritage Registry. Locations and details of archaeological sites province-wide will soon be available from this database through web access - the Remote Archaeological Access Database (RAAD) to selected users. RAAD users have the ability to undertake spatial and attribute table queries, and save results to tabular and shape file format on the local computer. All known archaeological sites are mapped as polygons. The Archaeology and Registry Services Branch maintains this database as the Heritage Resource Inventory Application (HRIA), and access to certain data is restricted and may not be included in public planning documents. Archaeological consultants and possibly planners will have access to RAAD.

A danger in using known archaeological inventory as a planning tool is that the distribution of inventoried archaeological sites in an area often reflects where archaeologists have looked for sites, not necessarily where the resources (including both recorded and undiscovered) are actually distributed. This problem has been addressed through predictive modeling, which indicates the probability of encountering an archaeological site anywhere within a landscape. Modeling proceeds from an assumption that demonstrated correlations between archaeological sites and mapped environmental and cultural features can be extrapolated to the overall landscape. Archaeological predictive models have been constructed for many areas of the province, often as part of an Archaeological Overview Assessment (AOA). In some cases, Archaeological Inventory studies were conducted as part of the AOA in order to fill data gaps. Most of these predictive models, applied as maps, are viewable as an electronic layer on RAAD, and can be obtained through a special data request to the Inventory Section of the Archaeology and Registry Services Branch, or at Forest District headquarters.

Archaeological potential mapping has been developing rapidly in the last decade, and these analytical improvements, together with the 1:250,000 mapping scale mandated early in the LRMP process, and the large data gaps present when the models were created, makes many of the earlier models imprecise or unreliable. In addition, many of the data gaps apparent when the models were constructed have been addressed through several years of Archaeological Impact Assessment (AIA) work on forestry blocks. Consideration should be given to assessing and, if necessary, updating older models prior to use for planning. A qualified archaeologist should do such an assessment. However, even if the model is out-of-date it should be used if it cannot be updated, since it may be the only data available to SRM planners. Out-of-date models should not be used if they have been demonstrated to be highly misleading.

Many of the archaeological predictive models created for LRMP or operational planning purposes have a dual or tri-state measurement of

Append ix 12 Prov inc ia l Her i tage Reg is te r Da tabase


archaeological potential – usually high, medium, or low. This simple division aids managers in determining what level, if any, of archaeological assessment is appropriate for any particular development. Planners should be aware that in many cases, potential has been predicted with more precision, but the potential has been grouped into smaller potential classes. A map graded with the full range of potential scores might be more useful for planning, rather than one grouped by potential class, which is most useful for making operational decisions on the need for archaeological assessment. In some cases, the more detailed model results are available in the attribute tables of the potential coverages, and such a map could be created at minimal cost by a GIS consultant or the GIS department of a major licensee, with input from an archaeologist.

In some cases, no AOA is available for an area but there are usually many AIA reports available. In most cases, these are too specific for general planning use and the information they contain that would be useful may not be simple to find. One exception may be “blanket permit reports”. These are collations of dozens of individual AIA “Interim Reports” and have a summary section, including an assessment of how any current archaeological predictive model is performing, or observations about general site location patterning. AIA reports also are the principal source of ‘negative data’ – places where an archaeological survey has occurred and nothing was found, an analysis of which is critical to creating defensible models. Planners may need to hire an archaeological consultant to conduct an AOA using existing data and/or to map archaeological potential. Model performance assessment and archaeological predictive modeling can be funded through Forest Investment Accounts.

Occasionally, no data may be available. An archaeologist with appropriate experience can determine if it is possible to extrapolate a nearby archaeological predictive model to the area where sufficient cultural and environmental similarities exist. In severe cases an Archaeological Inventory Study may be necessary to address data gaps.

The results of any such funded projects should be shared with the Archaeology and Registry Services Branch so that the data can be entered into the corporate data warehouse.

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