. FINALREPOR'I Phase I: Background Document Renewable Resources: Sus tai nab e Dev,elopment Indicators Submiffed fo The National Round Table on the Environment Environmental and the Economy Sustainable Development Indicator DSS Management Consultants Inc. Initiative I November 26,200l DSS Management Designers of Decision Consultants Support Inc. Systems November 26,200l Ms. Carolyn Cahill Policy Advisor National RoundTable on the Environment and the Economy 344 Slater St. Suite 200 Ottawa, ON KlR 7Y3 Dear Ms. Cahill: Re: NRTEE’s Environment and SustainableDevelopmentIndicators(ESDI) Phase1 BackgroundDocument - RenewableResources Our File No. 296-l Contract#: NRT-2001108 Following is the background report for the above project. This report documents our research findings and provides a reasonablebasis on which to begin the developmentof renewableresource indicators. Throughoutthe report, considerableeffort has takento avoid reachingconclusionsas to the merits of one SDI relative to others. This hasnot beeneasy. This being said we did net I%d any SDI which is currently in use which satistïes ah of the requirementsthat the NTREE has establishedfor nationallevel SDIs for renewableresources. Hopefully the SDIs which are included in this report Will be useful for the cluster group to arrive at their recommendationsfor national-level renewableresource SDIs. As we bave discussed,a great multitude of SDI initiatives and SDIs are currently being advanced relating to renewableresourcesand in particular relating to forestry. A comprehensiveinventory is beyond the scope of this research however; we bave tried to include the main SDIs and any exceptional SDIs that may relate specitïcally to the mandateof the cluster group. The referencelist contains links to many of theseinitiatives SOthat those wishing to delve more deeply into a specitïc initiative or indicator type Will be able to do SOeasily. ‘EdwardHanna C.C.Claire Aplevich, NTREE 1886Bowler Drive, Pickering, ON LlV 3E4 Telephone: (905) 839-8814, Fax 839-0058 ii Table of Contents COVERING LETTER ................................................................................................................................... i TABLE OF CONTENTS .............................................................................................................................. ii LIST OF ACRONYMS.. ............................................................................................................................... iii . ...................... ... ..................................................... 1 BACKGROVND .................................................................................................................................... I. ........................................................ PURPOSE .................................................................................. SCOPE ................................................................................................................................................. ................................................................................................................................. METHODOWGY -PORT ORGANIZATION ..................................................................................................................... 1 1 1 3 4 INTRODUCTION.. 1.1 1.2 1.3 1.4 1.5 ......... ....................................... COMMON ELEMENTS 2.1 2.2 2.3 ............ ........................................................................................... *.............. 4 EXTENSIVE MANAGEMENT ................................................................................................................ SUSTAINABLE YIELD .......................................................................................................................... POPULATION AND ECOSYSTW HEALTI.I.. ........................................................................................... FISHERIES RESOURCES AND MARINE ECOSYSTEMS ... .......................................................... 3.1 MAJOR INITIATIVES.. .......................................................................................................................... 3.1.1 3.1.2 3.1.3 3.1.4 3.2 Department of Fisheries and Oceans.. ...................................................................................... Environment Canada.. .............................................................................................................. FAO and UN ............................................................................................................................. GPL.. ......................................................................................................................................... ECOLQGICAL SD& ................... . ......................................................................................................... 3.2.1 Population Health. .................. .:. ............................................................................................... 3.2.2 Ecosystem Health .................................................................................................................... 3.3 ECONOMIC SDIs .............................................................................................................................. 3.3.1 Measures of Economie Flows ................................................................................................. 3.3.2 Memures of Economie Stocks.. ............................................................................................... 3.4 CONCLUDING OBSERVATIONS.. ........................................................................................................ 5 5 6 7 7 7 8 8 8 9 9 II 13 13 14 15 I5 3.4.1 Biodiversity Conservation Caps ............................................................................................. I6 Theoretical Limifations ........................................................................................................... 3.4.2 16 3.4.3 EcologicalData Limitations.. ................................................................................................. FOREST RESOURCES .......... .................................... ....... . ......................................... .................... .. 17 4.1 MAJOR INITIATIVES .......................................................................................................................... 4.1.1 4.1.2 4.1.3 4.1.4 4.1.5 4.1.6 4.2 ECOLQGICAL 4.2.1 4.2.2 4.2.3 4.2.4 4.3 MontrealProcess. ................................................................................................................... Canadian Council of Forest Minisfers .................................................................................... .. Provlncral Initiatives ............................................................................................................... ModelForests.. ....................................................................................................................... Volunkvy Cer@cation ........................................................................................................... Other Initiatives ...................................................................................................................... SD& ........................................................................................................................... Ecosysfem Heakh.. .................................................................................................................. Wood Supply ........................................................................................................................... Supply of Non-(imber Values .................................................................................................. Provision of Environmental Services.. .................................................................................... ECONOMIC SD& 4.3.1 17 17 17 18 18 18 19 19 19 26 28 29 .............................................................................................................................. 31 Wood Supply ........................................................................................................................... 31 111 4.3.2 4.4 Non-timber Values .................................................................................................................. CONCLUDMG OBSERVATIONS.......................................................................................................... 4.4.1 Complexity ofForest Management ......................................................................................... 4.4.2 Abundance of SDIs.. ................................................................................................................ 4.4.3 Data Limitations ..................................................................................................................... 4.4.4 Aggregation Challenges ......................................................................................................... 4.4.5 Absence of Forecasting ........................................................................................................... REFERENCES.. ..... . ... ................................................................................. .. ..... . .............. . ... c..................... APPENDIX A ................................................................................................................... :. ......................... APPENDIX B ...... .., ..................................................................................................................................... 32 33 33 33 34 34 35 36 46 68 iv List of Acronyms AAC C&l CAI CCFM CCME CFS COSEWIC DFO ESDI FAO FSC GDP GIS GM0 GPI IFMP ITQ MAI NES NGOs NRTEE NTV P-S-R RENEW SDI TSI UN VTE Annual allowable tut Criteria andindicators Cumulative annualincrement CanadianCouncil of ForestMinisters CanadianCpuncil of Ministers of the Environment CanadianForest Service Committee on the Statu~of EndangeredWildlife in Canada Departmentof Fisheriesand Oceans Environmental and sustainable development indicators Food and Agriculture Organization ,ForestStewardshipCouncil Grassdomesticproduct Geographicinformation system Genetically moditïed organism GenuineProgressIndicator Integratedtïsheriesmanagementplans Individua transferquotas Mean annualincrement National EnvironmentalIndicator Series Non-govemmentorganizations National RoundTable on the Economy andthe Environment Non-timber values Pressure-state-response mode1for sustainabledevelopmentindicators Recoveryof Nationally EndangeredWildlife Sustainabledevelopmentindicators Timber sustainability index United Nations Vulnerable,threatened,rare or endangeredspecies 1 INTRODUCTION 1.1 Background This report has been prepared for the National Round Table on the Environment and the Economy (NRTEE) as part of its Environment and SustainableDevelopment Indicators (ESDI) initiative. This is one of a number of similar reportspreparedfor different sectorsor clustersfor which sustainable development indicators (SDIs) are being evaluated/developed and recommendedfor adoption. These other clusters include non-renewablenatural resources,land and soils, water resources,air quality and atmosphericconditions and human capital. 1.2 Put-pose This report is a technical referencefor the renewableresourcescluster group. No attempt has been madeto undertakeany comparativeanalysisor evaluationamongthe SDIs presentedin this report. Instead, key information conceming each indicator or indicator set is provided. This information is designedto assistthe cluster group membersin developingtheir recommendedset of SDIs for forestsand marine fisheries. 1.3 Scope The scope of the indicators featured in this paner is based on the mandate provided to the renewableresourcescluster group. This cluster group comprises two distinct but conceptually similar resources,namely forests and marine tïsheries. Specifically, the mandateof the cluster group has been described for each of these resource categories separately. Specitïcally the renewableresourcescluster group’s mandate is: Fisheries andAauatic Resources:The group hasbeenaskedto: 2 - Examine the feasibility of developing a national indicator of marine ecosystem health, particularly related to biodiversity and other ecosystem factors (cg. the availability of spawninghabitat, and water or habitat quality), and - Examine the feasibility of determining stock estimates and indicators of commercially exploited marine species. m: - The group hasbeenaskedto: Develop a stock estimate and indicators of connnercially exploitable forest resourcesand determine what additional information Will be needed to determine whether this stock is being useo sustainably. Stock estimates may be derived from the Statistics Canadatimber account and other sourcesof data. As with the non-renewableresourcecluster group, this group Will be asked to examine whether to include indicators of economically exploitable stocks, or those related to the total resourcebase of timber in Canada,a broader definition that includes a11land suitablefor timber production and wheretimber harvestingis allowed, - Examine the feasibility of determining an indicator of the quality of timber stocks (e.g. productivity), and - Develop a national indicator that best representsthe health of all forest ecosystems(not necessarily ecosystemscontaining timber stock), particularly related to biological divers@ and to the environmentalservicesthat forestsprovide. The group has been asked to consider how to incorporate a spatial dimension into the data underlying the recommendedindicators. This inventory of renewableresourceSDIs contained in this backgroundreport has focused on Canadian SDIs and related databases. SDIs developedby foreign organizations are included where appropriate but an exhaustive search of a11SDIs developed by jurisdictions and organizationsoutside of Canadahasnot beenundertaken. This inventory deals with the two renewableresourcescategoriesseparately. In both cases,the inventory examinesSDIs relating to the supptyof resourcesas well as to the overall health of the supportingecosystems.Severalaspectsof forest resourcesand fisheries resourcesare outsidethe scopeof this report. 3 In terms of forest resources,the focus is on SDIs related to natural forests and does not include activities such as agroforestry, Christmas tree farms and short rotation plantations. These activities are more closely aligned with agriculhrral practices rather than the type of forest managementpracticesincluded within the scopeof this report. Similarly this report does not include SDIs relating to tieshwater or marine aquaculhne. The focus is on marine fisheries. Freshwaterfïsheries are included within the definition of the water resourcecluster’s responsibility. Finally, a number of fisheries and forestry SDIs have beenproposedto deal with social, cultural and institutional sustainability. These SDIs are outside the scopeof this cluster group and bave not beenincluded in this report. 1.4 Methodology The NRTEE provided much valuable information at the outset of this project. Some cluster group members also .provided suggestionsas to additional information and data sources,which might be useful. Al1 sourcesrelied on in preparingthis report are listed in the referencessection. Most of our researchwas done through the Internet. As well, our experiencethrough other projects on fïsheries and forest managementwas used to supplementthese sources. Published sourcesnot digitally available were also examined For the purposes of this background report, persona1contact with representativesof most organizationshas proven not to be necessary. Adequateinformation to characterizethe crurent state of knowledge has generallybeenavailable throughthe Internet and other publicly available sources. As the cluster group narrows its focus on candidate SDIs, direct contact with some organizationsand datamanagersWill likely be necessary.Contactinformation hasbeencollected for eachorganisationwith this potential needin mind. A key part of this report is to provide an outline of the availability of the data required to calculate SDI values. The NRTEE provided the latest version of databasesfor environmental 4 analysis(CCME, 1998)which includes listings for somerenewableresourcesdatabases.As well, many government agenciesprovide quite comprehensivesummaries of the renewableresource databasesavailable through their website. Al1 of these sourceswere used in our evaluation of dataavailability. 1.5 Report Organization The following report has been organizedinto two main sections,the fïrst dealing with fisheries and the secondwith fores&. Before dealing with thesetwo topics in detail the report examines certain common elements involved in developing SDIs for both types of resources. The examinationof eachmajor topic is organizedin a similar mariner. First, major initiatives relating to the developmentand application of SDIs are reviewed. Next, the specific SDIs relating to the ecological and economic aspects of each resource are examined. Finally some concluding observationsrelating to eachtype of resourcearepresented. A detailed list of referencesis included. As well, two appendicesare provided with summary information for individual SDI.? for both forests and fïsheries resources. These appendices outline the SDIs identified through our research. Pertinent information pertaining to each is included in thesesummaries. 2 COMMON ELEMENTS Fisheries and forest resourcesbave been included within the mandateof one cluster group. In certain respectsthe nature and managementof theseresourcesare distinctly different. Many of those differences are obvious even to laypersons. On the other hand, a number of common themes tie these two resource categories closely together and provide strong ieasons for ’ The terni “sustainabledevelopmentindicator(SDI)” is usedextensivelythroughoutthis report. Strictly speakingwithin the contextof the overallNTREE ESDI initiative,SDI refersto indicatorssatis@ingtbe requirementsof a sustainabledevelopmentindicatorwithin a naturalcapital framework. None of the indicatorsreviewedin this reportsatistïedtheserequirements.Aceordingly,readersare advisedto be awarethattheterniSDI is usedlessrigorouslyin thisbackground report. 5 combining them within the mandateof the samecluster group. Some of thesecommon elements are examined in the following sections. 2.1 Extensive Management Extensive managementinvolves relatively low human inputs. Economie benefits are realized largely through “Nature’s bounty”. In other words, a continuousyield of resourcesis provided largely throughthe independentfunctioning of natural ecosystems.Intensivemanagementlies at the other end of the scale and involves high Ievels of humaninputs to achieveincreasedyields of a narrow range of products having particular value to humans. With intensive management systems,much greaterhuman influence on (almost to the point of control over) the supporting ecosystem is common. Agriculture and aquaculture areshvo good examples of intensive managementsystems. Tbe management of forest resources and marine fisheries largely involves an extensive managementstyle although the tendency has been (and Will likely continue to be as greater demandsareplacedon theseecosystemsto supply goodsand servicesfor human benefit) to move more toward an intensive managementregime. However, given the large geographic areas involved in these activities and the relatively low human density, these activities Will likely continue to consist mainly of extensive managementfor the foreseeablefuture. This is one reasonwhy SDIs relating to ecosystemhealth as well as resourcesuppliesare required for these renewableresourcetypes. Ecosystemhealth is vital to sustainresourcesupplies. 2.2 Sus tainable Yield The concept of sustainablti yield has formed the central foundation for forest and fisheries managementin Canada for many decades. The concept is founded on biological principles relating to the productive capacity of natural ecosystemsand the need to conserve adequate growing stocksto sustaina continuousfuture yield of resources. Forest and fïsheries management systems have been largely influenced by the concept of sustainableyield. Accordingly, much managementeffort has been focused on gaining greater 6 understanding of the underlying biological systems and retïning estimates of maximum sustainableyield. Ecanomics, and evenmore SO,social factorsbave beenmuch less of a concern historically in terms of applying the concept of sustainable yield. Many past resource managementdecisionswere basedalmost exclusively on biological sustainableyield (e.g., annual allowable tut, total allowable catch). Social and economic factors played a relatively miner secondaryrole in the determination of these limits. For this reason biologically based SDIs relating to sustainableyield aremuch more common and are generallywell supportedby relevant data. In the case of economic and social factors affecting sustainability, both data and managementpracticesare lagging well behind. 2.3 Population and Ecosystem Health Estimation of sustainableyield generallyinvolves forecastingthe population dynamics of a target species (be it a population of tïsh or trees). These forecasts rely on a number of critical population coefficients (e.g., growth rates like mean annual increment, recruitment or regenerationrates,mortality lossesfor exampledueto tire or from predatorsor disease). A major weakness in these forecasts is the inability to link dynamically and quantitatively critical coefficients in a theoretically soundmannerto forecastchangesin the supportingecosystem(e.g., as a result of pollution, climate change,changesin trophic structure). For example, how Will a given level of oceanpollution affect recruitment andsurvival ratesof a target fish species?What is the long-term impact of acid deposition on forest productivity? These linkages, however, are crucial to understandinghow sustainableyield Will changein accordancewith thesebroader-level ecosystemchanges. Both tïsheries and forest managementare faced with the same basic problem of forecasting population behaviour in the face of dynamic and uncertain ecosystem behaviour. A key challenge in developingSDIs for thesetwo types of renewableresourcesis deciding how best to incorporateuncertainty,particularly in terms of overall ecosystembehaviour. 3 FISHERIES RESOURCES AND MARINE ECOSYSTEMS 3.7 Major Initiatives The developmentof SDIs for marine fisheries has been influenced by a tiumber of important initiatives und&taken by Canadianand’foreign organisations. This section reviews some of the more salient initiatives relating to SDIs for Canadianmarine tïsheries. 3.1.1 Department of Fisheries and Oceans The Departmentof FisheriesandOceans(DFO) is responsiblefor the managementand regulation of marine fïsheries. DFO has historically preparedtïsheries managementplans for key target species. In 1995, the DFO began a new initiative. Specifically, DFO committed itself to preparingintegratedtïsheriesmanagementplans (IFMPs) for a11significant fisheries. The purposes of these IFMPs are to achieve consistency in management processes and approachesfor a11Canadianfïsheries, to integrate complex fïsheries managementfactors in a cohesive and cogent managementframework and to provide a comprehensiveplanning system, multi-year wherepos$ible,for the conservationand sustainableuse of fisheries resources. As a result of this initiative, a consistentsystematic framework for developing IFMPs has been developedand applied to many Canadianmarine fisheries. IFMPs provide a clear and concise summary of the tïshery, the management objectives for the fishety, the management and conservation measures to be used to achieve those. objectives, and tht? criteria by which attainment of objectives Will be measured. IFMPs identify goals relating to conservation, managementarid scienceas well as resourcemanagement,protection and conservationmeasures. IFMPs also determineyield allocationsbetweenvarious usersand fleet areas. While the JMFP initiative is not directly linked to SDIs, in principle many of the tïsheries managementfactors others bave proposedas SDIs are contained in lFMPs for target fïsheries. 8 For this reaaon,this initiative is of important significance to the development SDIs for Canadian marine tïsheries. Much of the data required to plot trends over tinte are summarized or referencedin the relevant IFMPs for individual tïsh species or stocks. As well, target and thresholdlevels bave been establishedfor potentially key SDIs that relate to population health and sustainableyield. 3.1.2 Environment Canada Environment Canadahas included in its National Environmental Indicator Series,Pacitïc hening tïsh stocks as an indicator for sustainingmarine resources. In doing SO,much relevant data on Pacitïc herring stocks bave been compiled and presentedin a convenient and easy-to-access format. While this SDI is for only one target flsh specieson the Pacitïc toast, this initiative is important in establishinga foothold for implementing more broadly SDIs for marine resources. 3.1.3 FAO and UN The Food and Agriculture Organization (FAO) and various United Nations and international fisheries organizationsbave been actively developing SDIs for marine fisheries. The work of these organizationshas influenced, and is continuing to influence, signitïcantly the design and implementationof SDI systemsfor marine fïsheriesin many counhies, including Canada. These organizationsbave adopteda pressure-state-response (P-S-R) conceptual framework for designing and organizing their SDIs. This conceptualframework differs substantially with the natural capital approachwhich is the foundation for the NTREE ESDI initiative. Nonetheless, many of the SDIs, which bavebeenproposed,are applicable to marine fisheries whether a P-S-R framework or a natural capital framework is being used. For this reason,the FAO systemof SDIs is examinedin this report. 3.1.4 GPI The NTREE provided a draft copy of a proposedset of SDIs for Nova Scotia marine tïsheriesthat was preparedaccordingto the general“Genuine ProgressIndicator” framework. This is the only 9 Canadian example of a comprehensive set of SDIs covering a11aspects (ie., ecological, economic, social and institutional) of sustainabledevelopment. These SDIs are included in the inventory presentedin this report, however; only those dealing with ecological and economic factors areexamined in detail. 3.2 Ecological SDls This examination of ecological SDIs is divided into two parts. The,tïrst section examinesSDIs designedto measurethe ecological status and prospectsof populations of target species (i.e., those species intentionally being exploited to obtain specific resourceproducts). .The second sectionexaminesSDIs relating to the overall stateof the marine ecosystem. The health of marine ecosystemsaffects directly the sustainability of specific target speciesof value to humansand is also directly relatedto the provision of certain environmental servicesto society in general. 3.2.1 Population Health Numerousdirect and indirect measuresof the population healthof tïsh stocks bavebeenproposed and use by fïsheriesmanagersfor decades. Some of thesemeasurestrack changesin the flow of benetïts(i.e., yield) and otherstrack the statusof the supportinglïsh stock. Each SDI included in the inventoty has been classified as being a direct or indirect measureof population health and whetherit providesa measureof flow or stock characteristics. The fundamental biological principles of tïsheries management are based on population modelling and its supporting theory. Key attributes affecting population dynamics are used in population models and are natural choices for SDIs for marine fïsheries. For example, DFO includes in IFMPs, measuresof total fish stock biomass, spawningbiomass, recruitment rates, ageclass structureof the population and geographicdistribution of individual fish stocks. These factors, which include measuresof both stock and flow, are key regulators or predictors of population health and the future productivity and sustainability of tïsh stocks. Indeéd given accurate.estimates of a11thesefactors,reasonableshort-termforecastsof sustainableyields cari be produced. Such forecastsaregenerallyrequiredas part of the IFMP preparationprocess. 10 Environment Canadachoseone of thesefactors (Le., spawning biomass)as a primaty SDI for the population health of Pacitïc herring stocks. While the rationale for choosing this particular population factor is trot given, certainly spawningbiomass is one of the (if net the most) critical factors deterring the sustainability of a given tïsh stock. If a suftïcient biomass of mature spawnersis available each year, adequateanimal recruitment is a good possibility. Adequate annual recruitment Will help to ensure that fish stocks Will be at least sustained for the next generationof tïsh. Another population level indicator proposedby the FAO is exploitation rate. Exploitation rate is basically the mortality rate in tïsh population attributable to tishing. High exploitation rates indicate a fishery, near, at or beyond the limit of sustainability. If exploitation rates exceedthe net rate of recruitment, the population size Will decline and ultimately SOWill the annualyield. As well, the exploitation rate may vary among age classes; this cari affect signitïcantly the reproductive potential of a population. For example, if fishing gear selectively harvests the largest and most fecund individuals in a population, the impact of harvesting may be much greateron population sustainability and yield than if the harvestis spreadmore evenly acrossall population segments. The challenge is determining sustainableexploitation rates for a given. population and tïshing system. DFO, FAO and GPI also use several other sustainability measureswhich gauge the health of individual tïsh in a population. Weight-at-ageand condition factors both are measuresof the .growth rate and overall health of an individual fish. Individual fïsh in a stressedfish population may exhibit different responsesin terms of these indicators depending on the nature of the stresses. If habitat quality is declining, and/orpollutants are affecting the ecosystem,weight-atage and condition factor measuresmay decline irrespective of fishing pressure. On the other hand, high exploitation rates may causea positive increasein both factors due to compensating responses by surviving tïsh to reduce conspecitïc competition. As a result, detïnitive interpretation.of the significance of trends over time for these factors, in isolation fiom other ecological indicators,cari de diffcult. For many years,fisheriesmanagershavecommonly used anotherset of SDIs to assesspopulation health, albeit with mixed success. Two of the indicators in this group are reported catch and 11 catch ageclass structure(ix., the age of the tïsh harvestedby tïshers). The diftïculties with the interpretationof thesefactors are accountingfor changesin: 1) tïshing effort, 2) fishing eftïciency (e.g.,impact of improved tïshing technology), 3) fishing patterns(e.g.,tïshersexploiting new stocksand new locations). High catch ratesdo not necessarilyindicate a high level of sustainability. Often the opposite is truc. High catch rates may be an indicator of incipient collapse of the tïshery. While catch age class structureprovides greaterinsight into the underlying population dynamics of exploited fish stock, similar interpretationdiftïculties arise due to the selectivity of many tïsheries in terms of the individuals taken from a population. This selectivity is due to the type of gearused, fishing methods and the practice of discarding less desirable individuals of certain species of tïsh., particularly where harvest quotas are in effect Nonetheless, these SDls do provide some information regardingthe population health of target fish specieswhich cari be useful when used in combinationwith other SDIs. 3.2.2 Ecosystem Health Only relatively recently bave marine tïshery managers tumed their attention to assessing ecosystemhealth in marine environments as an integrated and linked component of tïsheries management. Some initiatives in this regard are beginning to appearbut the overall level of effort and knowledge is relatively limited. Three basic types of SDIs to measureecosystem health bave beenproposed. One set of SDIs deals with trends in the trophic structureof marine ecosystems. A seconddeals with habitat changesand the final set deals with the presenceof pollutants. Each of these types of SDIs for ecosystem health is reviewed in the following sections. A divers@ of SDIs is proposed for assessingtrends over time in marine ecosystem trophic structure. These range from indicators of community-level dynamics, to measuresof biomass utilization effciency, to impacts of fishing on non-targetspecies. A number of community-level SDIs are proposedincluding the ratio between the catch of piscivorous (i.e., fïsh-eating,hightrophic-level species) and planktivorous species (i.e., plankton-eating, lower-trophic-level species). Another involves the proportion of human mortality relative to mortality from other 12 predatorson populations of target species. Finally, sophisticatedstatistical measureshave been proposedwhich track the level of variation and long-ternichangesin the total catchrate acrossa11 target speciesin a marine ecosystem. Al1 of theseindicators are designedto detectchangesin the trophic structureof marine ecosystemsthat might be causedby tïshing. Significant alterationsto trophic structureare consideredto be undesirableand indicative of a potentially unsustainable level of exploitation. Any exploitation of marine resourcesby people, however, clearly alters energy and material cycles in marine ecosystems. What constitutesa significant alteration (at least in terms of long-term sustainability) remainsan important but largely unansweredquestion. Another type of ecosystem SDI relates to biomass utilization eftïciency. Conceptually, low utilisation effciency involves a high level of wastageand greaterdemandboth on the ecosystem to supply fish resourcesand to assimilate waste products. Measures of biomass utilisation effciency reflect theserelationships. Measuring the impact of a lïshery on non-targetspeciesis also proposedas a meansto assessbroaderlevel impacts of tïshing on ecosystemhealth. Several SDIs have been proposedto deal with impacts on marine fish habitat. One type of indicator deals with the direct effects of fishing gear on critical habitat. These SDIs involve monitoring and predicting the impact of different types of gearon the supply of different types of benthic habitat. Interpretationof theseSDIs is diffïcult however since the relative abundanceof different habitat components Will play a dominant role in the net effect of habitat alteration impacts. For example, a small amount of damageto a critical habitat in short supply may have direct and signifïcant impacts on a fïsh population. On the other hand, much more extensive damageto an abundanthabitat componentin excesssupply may haveno signiflcant effect on fish populations. This problem may be addressedby meansof a subsetof habitat supply SDIs. This group of SDIs tracks the total supply of critical habitats. With theseSDIs, the total areaand quality of important habitats is monitored over time. Major limitations with this approachare; 1) the unavailability of data relating to the areaand quality of important habitatsand 2) limited understandingin a quantitative senseof the relationship between different levels,of areaand quality of habitat and fisheries productivity. 13 While conceptually, these critical habitat SDIs are an improvement over current practice, the ability to make determinationsof what habitat componentsare most limiting for a fish stock is highly limited. For these reasons, the practical application of habitat-basedSDIs is quite restrictedat this time and is mostly at the conceptualstageof development. The final group of ecosystemhealth SDIs relate to the presenceof pollutants in the marine environment. A close connection between these SDIs and other SDIs associatedwith other environmental components(e.g., water) and economic sectors(e.g., agriculture) is present. For example, one potential SDI is pollutant loadings. Much of the nuhient pollution load to marine ecosystemscornesultimately from agriculture. In addition to such direct measuresof ecosystem health, a number of indicators of ecosystem health in terms of level of pollution are also proposed. For example, organe-chlorinecontaminantsin seabirdeggsbave beenproposedas an indicator of pollutant loads. Another indirect measureis the number and duration of shellfish harvesting closures. Shellfish closurescari be causedby high levels of pollutants in shellfish or indirectly through nutrient pollution causing algal blooms, which also cari lead to shellfïsh closures. 3.3 Economie SDls SDIs for economic componentsof marine tïsheriesbave beengroupedinto measuresof the flow of economicbenefits andmeasuresof the stock or capital value of marine fisheries. 3.3.1 Measures of Economie Flows SDIs comon in many sustainabledevelopmentframeworks include the value of the harvest of individual target species or combined for the entire fishing sector. These SDIs are typically calculated based on prevailing market prices (at the time the fïsh are harvested)times the total quanti@of the landedharvest. As such,theseSDIs yield estimatesof the total grossvalue of the landedharvest. These SDIs do not, however,accountfor the actual net benefit (i.e., grossbenefit net of managementand harvestingcosts)realized fiom the h&vest. Reasonablyreliable data are available over extendedtime periodsto calculatehistorical valuesfor grossbenefit SDIs. Three other measures of economic flows are commonly proposed as SDIs. These include contributions to GDP, income received by employeesin the fisheries sector and total expert of 14 tïsh products. Each of thesethree types of SDIs is a measureof the transfer and distribution of economic benefits. The sustainable development iiterature however is replete with articles criticizing these types of SDIs as potentially giving perverse signais in terms of long-term sustainability. Nonetheless,these indicators do provide insight into the distribution of benefits from a fïshery and their impact within the economy. A final measureof economic flow that has beenproposedbut hasnot beenpractically applied on a routine basis is the total economic value of environmental services provided by marine ecosystems.Severalbarriersto applying such SDIs, are apparent,namely: 1) philosophical challenges regarding the assignment of economic values to such services, 2) limitations in economic theory in valuing non-substitutableenvironmentalservices, 3) limited data to estimateeconomic coefficients for key environmental services 4) significant theoretical and practical limitations in using prevailing market prices to value servicesnot included in the market and 5) limited understandingof marine ecosystem behaviour in terms of the supply of environmentalservicesrelative to ecosystemhealth. Despite these barriers, tïrst estimates of the value of the environmental services provided by marine ecosystemsshow them to be highly significant in economic terms and worthy of careful attention. 3.3.2 Measures of Economie Stocks Three types of SDIs bavebeenproposedto track changesin the assetvalue of a tïshery. The tïrst type of SDI in this categoty measureschangesin the produced capital in the fïshing sector. Produced capital includes such things as fishing boats, tïsh processing equipment and establishmentsand related human capital components of fishing enterprises. These types of capital assets,however, are already included in conventional national accounts. Accordingly, tare needsto be exercisedin interpreting theseSDIs and to avoid the risk of double counting. The secondtype of SDI proposedto provide measuresof economic stocks involves the value of the extant biomass having economic value. For example, SDIs basedupon the grossvalue of cod 15 stocksbavebeenproposedfor the East Coast. Changesin grossvalue over time, however,caribe difficult to interpret since declining resource supplies may cause increasesin prices. The net result may be an overall increase in gross value of cod stocks despite a decline in the total physical quanti@of biomasspresent. A third type of SDI proposed deals with appreciation/depreciationtrends in resourcestocks. These SDIs track changes in the gross value of tïsh stocks relative to preceding years. Interpretation of appreciation/depreciationSDIs cari be confounded in the same way as interpretationof measuresof the grossvalue of resourcestockscari be confounded. 3.4 Concluding Observations This section provides general observationsarising tiom the background researchon tïsheries resourceSDIs. 3.4.1 Biodiversity Conservation Gaps Several current and emerging issuesrelating to this sustainability of tïsheries resourcesare not encompassedwithin the list of SDIs discussed in the preceding section. Biodiversity conservation is referred to by many organizations involved in sustainability assessments. However, developing meaningful and easily interpretable measuresof biodiversity remains a significant challenge. As well, certain aspects of biodiversity conservation are not well addressed. SDIs dealing specitïcally with vulnerable, threatenedand endangeredspecies are requiredbut often, insuftïicient biological information is available to,determinethe presence,let alonethe statusof such speciesin many marine environments. A related issue involves the introduction of exotics. While exotics are not as much of a threat in an expansiveopen oceanenvironment,the potential for negative impacts still exists with the full consequencesbeing unknown. A current example is the escapeof the Pacitïc salmon species from East Coast aquacultureestablishments(and Atlantic salmon from West Coast facilities). Closely related to, the introduction of exotics is the introduction of genetically moditïed marine 16 organisms, through escapement from aquaculture establishments, through intentional introductions or through unregulatedreleases. A major challengewith a11of theseindicators of sustainability is developing a metric suitable for hacking the aggregatestatusof the biodiversity of marine ecosystemsat a regional andnational level. 3.4.2 Theoretical Limitations A quite different type of gap in the choosing or developing of SDIs involves the absenceof underlying supporting theory for deciding on the appropriatenessof various measures of sustainability. Major gaps are evident in ecological understandingand, in particular, the relationship between overall ecosystemhealth and the yield of specitïc resource value. How energyandmaterial cycles in complex marine environmentsWill respondwhen certain fïsh stocks are exploited at high rates is largely unknown. For this reason, broad support for the precautionaryprinciple or approachhasdevelopedamongmarine tïsheriesmanagers. Similarly, economic theory is weak in dealing with the evaluation of non-substitutable environmental services and irreversible changesto ecosystemcomponents. As marine resource exploitation ratesare pushedto the hmits, the potential for irreversibleshifts in marine ecosystem structure and function increasesgreatly. For this reason, the North Atlantic cod tïshery may never recover but may be replaced instead with a different ecosystemcommunity structure. Estimating where these thresholdsexist and valuing the risk of passing over a threshold are a major theoreticaland practical challengein developing SDIs 3.4.3 Ecological Data Limitations A primary limitation in developing ecological SDIs for marine resources is the absenceof comprehensivedata. Furthermore,the collection of thesedata is expensiveand diftïcult to ensure on a continuousongoing basis. While data pertaining to tïsh harvestsand economic factors are available,comprehensivedatarelating to ecosystemfimction, structureand changesover time are generally not available: Where detailed ecological data are available, they typically relate to a single stock of a particular speciesat a particular point in urne. 17 4 FOREST RESOURCES 4.1 Major Initiatives The need for SDIs of sustainableforest managementhas been a focus of attention for almost a decade,originating with the 1992 Earth Summit. Prier to this point, tbe issue of sustainability had been a major concem with forest managementand defïning and assessingsustainability had been the topic of much discussionand research. This section reviews those initiatives, which bave most greatly influenced the current state of SDI development for forest managementin Canada. 4.1.1 Montreal Process The Montreal Processformally beganin 1994 with the fïrst meeting of the Working Group on Criteria and Indicators for the Conservation and SustainableManagement of Temperate and Boreal Forests. Membership on the Working Group included representativesfrom North and South America, Australia and key northem Asian countries. The Montreal Processcontinuesto be active in refining and applying sustainableforest management(SFM) criteria and indicators (&Us). These G%IS,bave signifïcantly influenced other SDI initiatives pertaining to Canadian forests. 4.1.2 Canadian Council of Forest Ministers The CanadianCouncil of Forest Ministers (CCFM) comprisesthe Ministers responsiblefor forest managementin the federal,provincial and territorial govemments. CCFM has takenthe Montreal ProcessG%ISand refined their definition for application in a Canadiancontext. For this reason, the CCFM C&Is sharestrong similarities with the Montreal ProcessC&Is. The major difference is thè exclusion of Criterion 7, which involves largely institutional sustainability issues. The CCFM C&Is bave been adoptedas the framework for state of the environment reporting relating to Canadian forests. As well, these G%ISbave played a central role in provincial and local sustainability definition and monitoring initiatives. 18 4.1.3 Provincial Initiatives The provinces bave direct jurisdiction over te managementof forest resources. Accordingly, each province is faced with actually implementing the CCFM CL%. In so doing, the CCFM C&Is are heing tailored to accord with forest managementpractices and objectives in each province. The basic structureof the CCFM C&Is is constantacrossprovincial jurisdictions, what changes from province ta province are specific indicators and their local measurementand interpretations. In some cases;certain indicatorsmay be moditïed or new indicators addedfor a particular criterion. 4.1.4 Mode1 Forests The CanadianMode1 Forest Network startedin 1992. Currently, there are a total of 12 mode1 fores& in Canadainvolving different forest ecosystemtypes. Thesemode1forestsaredesignedto develop the planning and managementtools appropriatefor their local forest ecosystemsand to implement and monitor the performance of forest management. A major initiative by these mode1forests has been to develop sets of local indicators of sustainability suitable for tracking managementperformance. A compendium of these local indicators has been produced. In general,their indicators arebuilt aroundthe tore of the CCFM C&Is. 4.1.5 Voluntaty Certification A major transformation has occurred over the last decade in terms of forest management. Voluntary certification systemsbave beendevelopedas a meansto assuageconsumerconcerns (particularly in Europeanmarkets) about sustainableforest management. This transformation is not limited to North America but is presentglobally whereverforest productsare being exported to Westernmarkets. Two of the most common certification systemsin Canadacontain a comprehensiveset of SDIs. In the caseof the CanadianStandardsAssociation system,its SDIs are structuredaccordingto the 19 CCFM C&Is. The Forest StewardshipCouncil systemcontainsmany of the sametypes of SDIs but the overall structureof their SDIs is not tied SOclosely to the CCFM C&ls. The proportion of Canadianfore&, which are certified, is increasingyearly. Accordingly, the SDIs demandedby thesesystemsareplaying an increasingdominant role in forest management. 4.1.6 Other Initiatives Public concem in Canada about sustainable forest managementis widespread. Many nongovemment organisations (NGOs) have been involved in promoting improvements in forest managementto increasesustainability prospects. The most notable initiatives in terms of the development of SDIs are those involving the Genuine ProgressIndex (GPI). GPI initiatives involving forest resourcesbave been undertaken in Alberta and Nova Scotia. While these initiatives have used to varying extent the CCFM C&I structure, a. central theme in these initiatives is to apply not only SDIs based on physical measurcsbut to expressthese also in economic terms. 4.2 Ecological SDls This examination of ecological SDIs is divided into four parts. The tïrst section discussesSDIs relating to ecosystemhealth. The next two sectionsdealwith sustainableproduction of wood and non-timber values. The final section examinesSDIs relating to the provision of environmental services. AI1 thesesetsof ecological SDIs are closely interhvined. They a11involve physical (as opposedto economic)measuresof the statesof the forest. 4.2.1 Ecosystem Health The conceptof ecosystem,healthis not well defined in measurableterms. For the purposeof this analysis, ecosystemhealth involves issuessuchas biodiversity conservation,energyand material cycling and the provisions of key environmentalservices(e.g.,water regulation and fïltering). 20 4.2.1.1 Biodiversity Conservation What constitutesbiodiversity and how best ta measurebiodiversity continuesta be the basis for extensive discussion at a theoretical level. For practical purposes, biodiversity has been categorizedat varying levels of resolution. The broadestlevel involves conserving landscapelevel patterns and elements. The next level involves the structural diversity within forest communities or stands (e.g., number of snags,amount of downed Woody material). The third level is speciesdiversity. The final level is geneticdiversity. Al1 of thesebiodiversity elements contribute ta ecosystemhealth but the precise connectionsare poorly understoodand largely undefined. SDIs bavebeenproposedfor a11of theselevels of biodiversity. Following is a review of these. Canadasignedthe Convention on Biological Diversity and committed itself ta the principles and specitïc activities of the agreement. Accordingly, biodiversity conservationstrategieshavebeen developed by federal, provincial and local govemment organizations. Al1 SDIs for forest managementreviewedcontainedoneor more biodiversiti conservationmeasures. Landscaue-levelSDIs At the broadestscale, SDIs have been proposedrelating ta the spatial pattem of forest types acrossthe landscape(e.g.,patchsize and frequency),arealpercentagesof forest community types (e.g., speciesand age class composition) and conservationbiology issues (e.g., fragmentation, connectivity). A variety of metrics bave been proposedfor these landscapefeatures.Some of which are basedon complex statistics and theoty relating ta measuringspatial patterns. With the mathematically less complex measures(e.g.,percentagerepresentation),major challengesarise in defining desirablelevels (e.g.,historical benchmarks)and forecastingexpectedfuture levels. Perhapsan even more diffcult issue is the absenceof an unambiguousdefinition of biodiversity at a landscapescaleand a clear basista decideimprovementsor favourablechanges. The limited understandingof landscapebiodiversity conservationrelationships has resulted in most efforts being directed toward using historical landscapepattems ta guide managementdecisions. A 21 major problem that ariseshowever, is the fact that thesepattems are highly variable over Lime, particularly at titrer levels of resolution. Becausethe theoretical foundationsfor landscapebiodiversity conservation are still being laid, considerablevariatiorrin SDIs, mehics andbenchmarksis evident. Most of the focus is on spatial pattems and maintaining representativeforest communities across the landscape. Somewhat confusing the issuehas beenthe tendencyto combine biodiversity conservation.SDIs with those involving issues such as the supply of wildemess, roadless area and backcountry recreation opportunities. As a result, a wide assortment of SDIs has been proposed for landscape biodiversity, some of which are tied more closely and firmly to the landscapebiodiversity theme than others. The two most common SDIs for landscape-levelbiodiversity conservationare the proportions of different forest community types and the proportionsof different ageclasses. A variation on the latter is the proportion of old growth forest. Old growth forest has been the focus of much attention dueto biodiversity considerationas well as others(e.g.,aesthetic,spiritual, ethical). Extensive geographicaldata are available for Canadianforests. Geographicinformation system (GIS) databasesbave beencompiled for many managedforestsin Canadaand areusedroutinely for planning and monitoring. In many cases, private companies having long-term tenure agreementson public land assemble and maintain these GIS databases. While provincial govemmentsmaintain their own GIS databasesfor forested areasand work cooperatively with forest companies,the most accurateand complete information is held by those directly involved in forests operations(typically private forest products companies). These data are not often availableat a provincial or national level in a comprehensive,standardizedform. Coarseresolution data are available from remote sensing,primarily satellite imagery. As well, much of the air photo coverageof provincial forestsis being digitized. A primary limitation with thesedatais the diftïculty in discriminating forest type and ageclasspattems. A common concem with locally significant biodiversity characteristicsis the tendencyfor broad national averagestatistics of age classesor proportions of forest community types to mask 22 important local trends. Theselocal trendsmay bavesignificant biodiversity implications that are also significant in aggregateat a national level. Theselimitations are magnified when more complex data are required to measuresustainability. For example, estimation at a national scale of the level of forest fragmentation would require a level of spatial detail not available from existing centralizeddatabases.Estimates for thesetypes of spatial pattems are beginningto be producedat a forest managementunit level in some cases. Developing standardized measuresand estimating local values is diffcult enough without consideringthe complications involved in developingaggregateestimatesat a national scale. A related data issue is the matter of classification. Many provinces bave developed forest ecosystem classification systems, which are used by forest mangers in preparing forest managementplans. In somecases,the supportingdatabasesdescribethe forest accordingto these ecosystem types. However, the use of conventional timber classifications (e.g., hardwood, softwood, mixed wood) is still prevalent. The forest types containedin thesedatabaseslimits the potential resolution amongforest type desiredfor biodiversity conservationpurposes. Furthermore,the clarification systemsvary among provinces. This variation createsa challenge when aggregatingdata among provinces. A mapping of the correspondenceamong ecosystem types for a11provincial systemsis necessaryto integratethesedatasets.No integrateddatabaseof this sort is currently available. A final calculation issue relates to the appropriatemeans to aggregatemeasures for different geographicalareasto arrive at a national-level SDI. For example, the proportions of forest commun@ types Will vary from one areato the next. SOtoo Will benchmarklevels. This complexity in practically applying biodiversity measuresis a primary reasonfor CCFM to report only aggregateor surrogatebiodiversity measuresin its state of Canadian forest’reports. Forestcommunities are lumped into conventionaltimber supply groups(i.e., hardwood,softwood and mixed wood). Furthermore, these proportions are reported separately for 8 ecozones. Likewise, CCFM has reported these proportions by five different age classes. Finally, the proportions are reported separatelyfor private and public land. The net result is a total of 240 separatenational-level SDI measuresfor landscape-levelbiodiversity. No direction is given as to 23 how these measures should be aggregated. In summary, this one element of biodiversity conservation is the source of a plethora of SDI measures,which are difficult to aggregate mathematically and conceptually. As well, their interpretationis diffcult and disceming positive from negativetrendsis far from simple. None of the SDIs reviewed that relatedto biodiversity conservationat a landscapelevel overcame theseproblems. Intra-standStructural DiversiQ A large conservationbiology literamre exists discussingthe importance of intra-standstructural diversity for biodiversity. Forest managementguidelines, inventory and monitoring techniques andmitigative measuresbavebeendevelopedto enhancestructural diversity. Local-level indicator sets commonly include measuresof structural diversity (e.g., number of snagsper hectare). No SDIs for this elementof biodiversity conservatioonbavebeenproposedat the national level. Suitable data for a national-level SDI relating to infra-strandstructural diversity are even more limited than those relating to landscape-levelSDIs. These limitations are due to many of the samereasons. As well, many of thesemeasuresbave only relatively recently been proposedby conservation biologists for forest management planning. Accordingly, fïeld data for these features are trot generally included in conventional forest inventories. Furthermore, no comprehensive historical data are available nor is it likely that historical values cari be approximatedfor a broad geographicarealike Canada,at least in a short timeframe, if at all. SpeciesDiversiQ Speciesdivers@ is a more familiar conceptfor many when speakingof biodiversity. However, somesignitïcant theoreticaland datachallengesare presentwith this componentof biodiversity. The conceptof biodiversity encompassestwo elements“richness” and “fullness”. Richnessis the variety of speciespresent. The greateris the variety, the greateris the richness. Fullness reflects 24 the overall number of individual present. The greater is the overall number of individuals present,the greateris the “fullness” (typically related closely to ecosystemproductivity). When richness and fullness are high, divers@ is high and vice versa. The problem corneswhen one element is high and the other is low. Many indices have been proposedto measurediversity and some have even been proposedas SDI measures.But none are without their limitations. As well theseindices require a great deal of data, particularly if such mcasuresare to be applied at a national level. Furthermore, their values are sensitive to new information. Many species, even in Canada, remain unnamed (particularly smaller organisms) and as new speciesare added, historical values for diversity indices are difficult to use asbenchmarks. For thesereasonsamong others,no comprehensiveSDIs for speciesdiversity are widely applied. Instead, certain significant elements of species diversity are commonly proposed. The most common is the number of vulnerable, rare, threatened,endangeredor extirpated species, often referredto as vulnerable,threatenedor endangered(VTE) species. As speciesare extirpatedfrom an area or ultimately go extinct, indisputable diminishments in biodiversity do occur. Accordingly, this species divers@ SDI in a sense has a richness and fullness component. However, a speciesgoing from endangeredto threatened,would haveno impact on an SDI based simply on an enumerationof the number of VTE species. Likewise, taxonomie complications arise with local subspeciespopulations (e.g., Eastem cougar). The sensitivity of this SDI is primarily relatedto richness,not fullness. Severalother speciesdiversity SDIs have beenproposed. One of the most common is to Select populationsof indicator or keystonespeciesto gaugethe overall statusof biodiversity in a forest. Much technical debate about the advantagesand disadvantagesof this strategy exists in the published literature. The use of indicator species is futther complicated when developing national-level SDIs. The availability of species whose range and ecological requirementsare suitable to reflect forest ecosystem health across Canada is highly questionable. As well, historical data for populations of wildlife are quite limited and incomplete,even for megafaunaof particular economic signiflcance (e.g. game species). Accordingly, historical trend-over-time analysesare not available at a national level for most, if not at ah, candidateindicator species. 25 Genetic Diversity The final level of biodiversity conservation involves sustaining genetic diversity. Genetic diversity is more complex than the higher levels of biodiversity conservationfor many reasons, not the least of which is the technical diffïculties in characterizingthe genetic make-up of the myriad of speciesand populations within forest ecosystems. The theoretical and data challenges discussedare magnitïed manifold when considering SDIs for genetic diversity. Severalindirect SDIs havebeenproposedthat deal to a limited extent,with geneticdiversity conservation, A common SDI is the existenceand application of silvicultural guidelines relating to the genetic make-up of planting stock in reforestation operations. The idea is that by using planting stock derived from local seedsources,the risk of genetic “pollution” Will be reduced. Comprehensive data on regenerationpracticescould be compiled since historical recordsare often maintained for individual forest managementoperationsand in some cases,provincial standardsbavebeenset. Another SDI that has been establishedby the Forest StewardshipCouncil (FSC)) is the use of genetically modified organisms.(GMO). FSC refusesto certify any forest in which GMOs bave been used. Comprehensivedata on the use of GMOs in forest managementcould be compiled since planting stock recordsare generally available from forest managementorganisations. The calculation basis for such an SDI would need to be developedas no national-level SDI of this type is currently in use. Interestingly, FSC Will certify forest managementoperations involving plantations, even those using exotic species. This example illustrates the complexity in interpreting biodiversity SDIs. The introduction of new genotypes or even new species to an ecosystem may increase biodiversity measuresbut may result in negativeimpacts on ecosystemhealth. As a result, some organizationsbave proposedlocal Ievel indicators relating to the number and abundanceof exotic species. Data availability is an issue with this SDI since comprehensivedata on exotic species populations is often not available. As well, issuesarise as to how best to aggregateand interpret local measuresof exotic speciespopulationsat a national ievel. 26 4.2.2 Wood Supply A major focus of forest managementin Canadahas beenensuring a sustainablesupply of wood for the forest products industry. Ah sustainableforest managementsystemsinclude one or more SDIs relating to wood supply. These range from high-level comparisons of actual harvest to plannedharvestto detailedmeasuresof trendsin the mean and cumulative annual increment. The most direct measureof wood supply is the trend-over-timein annual allowable tut (AAC). AAC is used in a11jurisdictions as a primary means to regulate forest harvesting within sustainable levels. Calculation procedures for AAC vary somewhat from jurisdiction to jurisdiction but the basic principle is the same. Namely annualharvestingoperationsshould not exceedthe long-term averageannualproduction of wood. BecauseAAC is used extensively in Canada (except in the case of small private woodlots), comprehensiveforest inventory and yield information is available to calculate ACC. Likewise, systematictrends-over-timeanalysesare feasible sinceAAC hasbeenused for decadesin Canada althoughthe methodologyhas beenrevised from time to time. The interpretation of historical trends is complicated by theseperiodic retïnementsto the AAC methodology and as a result of improvements in forest inventoty data. Policy changes like allowances for natural losses and prescribed rotation ages cari also bave profound effects on ACC. In principle, however, a SDI basedon AAC should capturechangesin forest productivity and the impacts of over-harvesting(if present). Both lossesin productivity and over-harvesting Will be reflected in reducedAACs in future years. Several variants on the basic AAC SDI bave beenproposed. A common variant is the ratio or proportion betweenAAC and actual harvest. The underlying conceptis that if actual harvestis less than the sustainableyield, forest operationsare sustainable. Comprehensive and reliable data are available for the annual harvest of wood in Canada. Accordingly, the determination of the total harvestof wood at a national level is feasible on an annualbasis. 21 Environment Canadabas developeda timber harvest SDI that intiludes AK and harvest at a national level broken down by softwood and hardwood. As result, four separatetrends over time are presented.Notably, no method for deriving a single aggregatenational SDI is presented. In the GPI analysis for Alberta, a timber sustainability index (TSI) was used. The TSI was calculatedbasedon the ratio of annual timber growth (annualincrement) to total depletions(due to harvesting and natural losses and changes in land use). GPI suggeststhat “[ifj the TSI ratio.. .is greaterthan one this means.. .that we are living sustainability [sic] off the interest of the forest capital stock.” Unfortunately, this claim is flawed. The TSI ratio cari only be greater than one for a limited period. Trees die and decay. Wood cannotbe accumulatedindefinitely in the forest. Therefore over the long-tenn, the TSI value Will approximateunity. Interpretationof the TSI is diffcult for this reason. However, the data required to estimate TSI ratios are readily available. Many indirect SDIs are proposedthat relate to wood supply. These include measuresof natural losses (e.g., me, insects, disease),changes in canopy density or transparency,mean annual increment (MAI), cumulative annual increment (CAI) and other aspectsof animal wood biomass production. Some of these measuresare regularly monitored by forest mangers,(e.g., natural losses, MAI, CA& whereas others require specialized measurementsnot routinely taken. Extensive datasetsfor those forestmeasuresregularly monitored are available. For example, Environment Canadareports insect distribution and tire loss trends at a national level from 1980on. Insect lossesare broken down by speciesandby ecozone. With both insects and tire, they are measuredin areal units, not lest timber volume. Direct effects on harvestable wood supplies require somefurther statistical manipulation and estimation. Another indirect SDI relating to wood supply is the level of regeneration of disturbed land. Measuresof areassuccessfullyand unsuccessfullyregeneratedcari be informative. A variant of this measureis the percentageof the annual harvestareasuccessfullyregenerated In principle, the interpretation of these SDIs is relatively straightfonvard. The less area unsuccessfullyregenerated,the greateris the long-tenu security of wood supply. However, this 28 SDI cari be difficult to interpret in the short term since most reforestationassessmentsoccur five yearsor more after harvest. Most forest managementlicensesrequire regular regenerationsurveys to be carried out and the results publicly reported. These requirementsbave been in place for decadesalthough certain aspectsof the monitoring have changedover the years and variations in standardsand reporting amongjurisdictions are common. As a result, abundantdata are available to estimatevalues for this type of SDI. The precedingwood supply SDIs are largely measuresof the annual flow of wood. Another aspectof wood supply is hends in the total standing stock of timber (Le., physical quantity of wood). None of the CCFM C&Is deal with total standing stock, instead,the focus is on annual productivity. The same is truc for the GPI analysis for Nova Scotia. The Alberta GPI does include an economic measureof the total standing stock as does Statistics Canada,but neither report standing stock in physical terms. Extensive data on the standing stock of timber are available. 4.2.3 Supply of Non-timber Values Non-timber values (NTVs) involve those products and servicesprovided by forests that are not related to wood products. NTVs include consumptiveproductsand services(e.g.,country foods, recreationopportunities)andnon-consumptivevalues (e.g.,existenceand bequestvalues). Al1 of theseNTVs contribute to the benefits enjoyed from forests and which need to be sustainedfor enjoyment by future generations. The CCFM C&Is include Element 5.4 Non-timber Values. The availability and use of recreationalopportunitiesis the only non-economicindicator suggestedfor NTVs. The databasesupportingthis SDI in the Stateof the Forest report is quite restricted. Only datafor 1996 are presented. These .data reflect only the recreational opportunities consumed (Le., conceptually similar to wood harvest)and provide no insight into the actual level of supply of opportunities. At this point, no trend-over-timeanalysesfor this SDI are possible. 29 Environment Canada’sNEIS contains no SDIs relating to non-timber values. The same is truc for Statistics Canada’sEcoconnectionsalthough this limitation in the forestry (natural resource wealth) SDI is noted. The GPI accounts for Alberta do not include an SDI for NTVs but the Nova Scotia accountsdo, at least in economic terms. The Nova Scotia GPI includes NTVs like food production,recreationalopportunities’andcultural values as well as severalenvironmental~services. (Theselatter elementsare addressedseparately in the next section.) The physical supply of NTVS is not used as the measurefor theseSDIs. Instead,averageeconomic values on a per unit areabasis are used to generateprovincial totals. Accordingly trend-over-timeanalysesarenot possible. More detailedmeasuresare provided for maple sugarproducts. However, the datainvolve actual production (not potential production akin to AAC). As a result, interpretation from a sustainability perspectiveis hmited. A major limitation with SDIs involving NTVs is the paucity of relevantdata. Those data, which are available, are connnonly associatedwith a specitïc site on a one-time-basis. Comprehensive trend-over-time analysesWill likely not be possible at least for the next 10 years due to data limitations associatedwith NTV SDIs. 4.2.4 Provision of Environmental Services Forests provide several important environmental services, which contribute positively to sustainabledevelopment. SDIs bavebeenproposedfor many of theseservices. 4.2.4.1 CarbonSequestering CCFM Criterion #4 includes two elementsrelating to carbonsequestering,namely contributions to global carbon budget and forest sector carbon dioxide conservation. (The latter element is closely tied to air resourcesand is not examined further in the context of forest resources.) CCFM has lumped a number of SDIs dealing with various aspectsof the forest carbon budget 30 into one comprehensiveindicator. Trends-over-timein the total carbonpool in Canadianforests bavebeendevelopedgoing back to 1920. An extensive database is available regarding the standing biomass of forests, which is a signifïcant component of this carbon budget SDI. Data for forest soils are not updated as frequently or comprehensively,however, the relative stability of forest soils overall in terms of carboncontentreducesthe need for more frequentupdating. This carbon sequesteringSDI was expandedin Alberta to producean overall carbonbudget SDI. This budget netted out carbon releasesto the atmospherefrom carbon sequesteredin forest ecosystems. Similar data for carbon sequesteringrates were used as were used with the CCFM analysis. Carbonemission rateswerebasedon pollutant emissionsdatasimilar to thosediscussed in the air resourcesbackgroundreport. 4.2.4.2 Hydrological Cycle Water regulation and purification functions of forests are an important environmental service. However, little comprehensivemonitoring data directly measuring the functions of forests and changes over time in these functions are available. Accordingly, proposed SDIs for forest hydrological servicesare limited to indirect measuresor arebasedon expectedrelationships. No comprehensivedata set at the local, provincial or national level is available. CCFM hasproposedone indicator for this environmentalservice,namely the total surfaceareaof water within forested areas. This SDI however, is relatively insensitive to changes in this environmentalserviceand is tied obliquely to the hydrological fimctions of forests. The Nova Sc&ia GPI includes a seriesof SDIs measuringwater quality and quantity. However, values for many of these SDIs are not estimateddue to lack of data. The two SDIs for which values were reported(i.e., trends in streamflow and trends in fish populations) were not closely connectedto forest ecosystemconditions. Instead,a broad rangeof likely confounding factors was identifïed. Comprehensivedataarenot available for either of theseSDIs at a national level. 31 4.2.4.3 Soi1Protection The role of forests in protecting soils and conservingmaterials (in particular nutrients) is well understoodat a functional level. However, comphrensivemeasuresand monitoring data for these environmental services are not available. For this reason,no SDIs bave been proposed at a national level. 4.3 Economie SDls This sectionreviews thoseSDIs, which bavebeenpreparedto deal with economic componentsof SFM. In somecases,theseeconomiccomponentsare distinct from the ecological SDIs discussed in the preceding section. In other cases,these economic SDIs are clearly connected to the ecological SDIs andare essentiallyexpressionsof the sameelement exceptin economic terms. In accord with the underlying theory of natural capital, this discussion has examined these economic SDIs according to those basedon measurementof economic flows and those basedon extant capital. 4.3.1 Wood Supply Economie SDIs basedon the annual harvestof wood are measuresof economic flows. The most direct economic measureis the net value of the ~annualharvestof wood. None of the provincial or national scale SDIs included this measure. Instead,,most relied on conventional macroeconomic measureslike contributions to GDP, employment and annualexpenditures. Estimation of theseSDIs is relatively straightforward given the extensive economic data sets available and the supportingeconomic impact models. As discussedin the tïsheriessectionof this report, interpretationof thesemeasuresis complicated at least in terms of sustainability. Short-term increases in these SDIs may be in fact the harbingersof imminent collapse. 32 Statistics Canada’s natural wealth SDI includes a wood supply component. The unit of measurementis not, however, the capital stock (Le., total standing biomass) but instead, the expected annual flow of wood. This ammal rent basis for the wood supply SDI presumesa constantcapital stock Will be sustained. While extensive data are available on’physical yields of wood, economic data relating to extraction costs are more diftïcult to tie directly to forest operations. A major tendencyin the forestry sector is to barvest the cheapest wood first (an economically rational strategy). Projections of future extraction costs are often quite approximate if available at ail. Projecting expectedfuture values for the timber componentof Statistics Canada’snatural resourcewealth SDI Will, therefore,be a challenge. 4.3.2 Non-timber Values The Nova Scotia GPI provides the most extensive economic measureof NTVs. Included are consumedNTVs (e.g., food productsandrecreation)plus the provision of environmentalservices (e.g., climate regulation, soi1 conservation). These economic measuresare estimated using constanteconomic coefficients (extracted from a broad-level study) which are multiplied by the total forest area. Accordingly, these SDIs are insensitive to a11changesin the forest except for lossesor increasein the total forest area. Canadahas excellent data on the total forest area. Therefore this methodology could be applied at a national scale. The question is what policy analysis value would theseSDIs offer beyond that provided by a simple measureof total forest area. The Nova Scotia GPI also assigns economic measures to ecological health values (e.g., biodiversity conservation). These measures,however, reflect all-or-nothing choices and are of limited value for policy analysisand the interpretationof trendsin biodiversity conservationover time. As well, few economicdata are available on which to basetheseestimates. The most common approachfor developing economic SDIs for NTVs is basedon an economic impact framework, largely driven by expendituresassociatedwith NTVs. Data to supportthese SDIs is restricted and is derived primarily from targeted sweys. These surveys are often 33 national in scope and the results would, therefore,be applicable for national-level NTV SDIs. Similar diffculties in their interpretationexists as is the casewith comparablerneasuresfor wood SUPPlY. 4.4 Concluding Observa fions This section setsout some observationsfrom the review of forestresourceSDIs. 4.4.1 Complexity of Forest Management Historically, forest management,in effect, meant timber management. The scope of forest managementhas broadenedconsiderably over the last two’ decadesto include rnany forest ecosystemconsiderationsas well as supplies of NTVs. No other natural capital accountinvolves a comparablelevel of complexity. This is a particularly SOgiven the high level of public concem about and involvement in forest management. These complicating factors make the challenge of selecting one or several SDIs to gauge the sustainability of forest ecosystemsand resourcesuppliesenortnous.The tendencywith most SDI initiatives relating to forest resourceshas been to generatea great multitude of rneasuresrather than a few. 4.4.2 Abundance of SDls Forest managementSDI initiatives ‘abound at a11levels ranging from the local level to the international. For example, each of the 11 mode1forests bave developedtheir own set of SDIs with each set comprising anywherefrom 20 to 60 individual SDIs. While, many of these SDIs are comparable,invariably eachgroup has sorneSDIs unique to their forest. The sameis tme for provincial-scaleinitiatives. 34 This flood of SDIs reflects the diftïculties in arriving at a small set of SDIs, let alone one SDI, to reflect sustainableforest management. Even more SO,the questioncontinually arises“Has some group developeda break-throughSDI system7” While a defïnitive answer to this question Will only emergeover time through tria1 and errer, what is clear is that few of these initiatives are founded on a natural capital theoretical foundation and are driven instead by the conventional disciplinary elementsdominating forest management(e.g., forestry; ecological, economics). This report provides a “flavour!’ for these initiatives but in no way provides a comprehensive descriptive and analysis of a11of the SDIs arising t?om thesevarious initiatives, The volume of SDIs is beyond the scopeof this Proje:t. 4.4.3 Data Limitations Aside from the conceptuallychallengeof developingone or severalSDIs for SFM, an overriding constraint is the unavailability of data, particularly relating to ecological conditions and NTVs. Inadequatedataare available to representthe currentecological condition of the forest,but this is even more SOthe caseconceming the unavailability of data describing the historical ecological condition of the forest. These data are not available simply as a result of changing priorities over time. Much of the ecological and economic datarequired,particularly for NTVs, is diffcult to obtain and interpret. Signitïcant improvementsin this respectWill requiie an extendedperiod of time. 4.4.4 Aggregation Challenges Canadianforestsinclude 8 major ecozonesand a11of the provincesand territories. National-level SDIs need to integrate this diversity in some form of aggregatemeasure. Unfortunately, the theoretical foundations for undertaking such aggregationsare weak, particularly in relation to ecological factors and NTVs. Timber products and values cari be aggregatedrelatively easily given the global nature of forest products, their markets and the common use of economic mehics. No comparablecoherentfoundationexists to developaggregatemeasuresfor NTVs and ecosystemhealth SDIs. 35 Careful attention needsto be given to avoiding the problem of averaging. For example, looking on averageacross Canadaat the total supply of old growth, one might conclude an adequate supply is present. However, the issue may not be total supply of old growth but .its spatial distribution among ecozones(or tïner levels of ecological resolution). The problem of averaging increaseswith the spatial boundariesof an SDI. 4.4.5 Absence of Forecasting The great majority of SFM SDIs examined dealt with historical and current conditions. From a policy analysis perspective, the most critical conditions are the expected future state under alternativemanagementsystems. Few (if any) of the SDIs systemsexamined addressthe matter of how future measuresfor SDIs should be predicted. In somecases,the actual constructionof the SDIs may preclude such forecasting. If SFM SDIs are to be used in the same way as conventionaleconomic indicators,forecastsof their expectedvaluesare essential. A signitïcant problem arises in this respect, The temporal planning horizon of conventional economic measuresis typically 20 years maximum. With forest ecosystems,sustainability assessmentsinvolve examining expected forest conditions over several rotations at least (e.g., 200-300years). Reconciling thesevastly different planning horizon scalesin any aggregatesetof SDIs is mandatory. 36 REFERENCES 1. ABARE 2000, Australian Fisheries SurveyReport, 1999,Canberra 2. Agriculture, Fisheriesand Forestry Australia @FA). 1996.A Framework of Regional (SubNational) Level Criteria and Indicatorsof SustainableForestManagementin Australia. hM>://www.affa.~ov.au/content/outDut.cfm?Obiect~=D2C4SFS6-BAlA-lIAIA2200060BOA03758 3. Agriculture, Fisheries and ForestryAustralia (AFFA). 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United Nations SustainableDevelopment.1999.Chapter 17:Protection of the oceans,a11 kinds of seasandcoastalareas.h~://www.un.orp/esa/sustdev/indisd/en~lis~chaptl7e.htm 121. USDA Forest Service.2001. Sustainability: Sourcebook on Criteria and Indicators in the NortheastemArea (draft for discussion).Preparedby the NortheastForest Resource Planners/NortheastemArea Criteria and IndicatorsWork Group httm//www.na.fs.fed.us/sustainabilitv/draftsourcebook.htm 122. Vision 2020. 1998.Natural Areas andCorridors: Sustainability Indicators. h~://www.vision202O.hamilton-went.on.c~indicators/98repo~na~ralareas.html 123. Wagener,Karl. nd. EnvironmentalQuality in Connecticut. .CT Council on Environmental Quality, 79 Elm Street,Hartford, CT, 06106.karl.wagener@po.state.ct.us http://www.ceq.state.ct.us/ 124. Wilson, Mike. nd. Northern Forest Wealth Index. Wealth Index SteeringCommittee, Northem ForestCetiter. PO Box 210, Concord,NH, 03302-0210. mwilson@northernforest.org,httu://www.northemforest.org 125. Wright, Pamela.nd. Local Unit Criteria & Indicators DevelopmentProject (LUCDD): Ottawa,Blue Mtn. Province, Allegheny, Tonga%,Mondoc, & Mount Hood National Fores&. USDA Forest Service:Inventory & Monitoring Institute, 2150 CentreAve, Suite 300, Fort Collins, CO, 80526.ptiinht02@fs.fed.w, http://www.fs.fed.us/institute/lucid/index.html 46 APPENDIX A Summary of Individual Fisheries Resource SDIs This appendix provides summary information for the iïshery SDIs included in this inventory. The inventory is maintained in a relational databaseand cari be queriedand sorted. For eachSDI, the following information is provided. 0 Indicator Measure ii) Indicator Type iii) Indicator Code iv) Description v) vi) ResponsibleOrganization GeographicScope vii) Time Series viii) UpdateFrequency ix) Method of Calculation 4 xi) Source/Author Notes A brief explanationof eachof thesetïelds follows. i) Indicator Measure Fishery SDIs have’beendesignedto track various measuresof environmental quality. TO case comparisonsamong the various typesof measure,they havebeen groupedinto broad categories. Specifically, the SDIs havebeengroupedinto four measurementcategories. In many cases,a modifier code has been added to the main code. The two modifier codes indicate more specifically the natureof the resourcequality being measued. For example, the code “lf’ denotesan SDI basedon the population statusof a fish stock with the indicator being basedon a measureof the “flow” of resourcesbeingproduced by the fishery. 48 Code 1 Description Populationstatusof individual fish stocks 2 Ecosystemhealth 3 Economie performance 4 f Other measures Resourceflow s Resourcestock Table A.1 - Indicator Measure Codes Used to Categorize SDIs ii) Indicator Type SDIs may be basedon various parametersdirectty indicating the status of a fishery or marine ecosystem. Alternatively, indirect measuresmay be usedas indicators. Finally, some SDIs area composite index derived fiom multiple measuresof a fïshery or marine resource. As well, variants on eachof thesealternativeswere noted. Thesevariants are indicated in the databaseby one of threemodifiers (Table 2). For example,the code “Dh” connotesan SDI basedon a direct measureof habitat availability. Description Direct measureof indicator condition Indirect measureof indicator condition Index of multiple measuresof resourcecondition Measureof habitat quantity and/orquality Measureofeffects of pollutants Measureof trophic structure Table A.2 - Indicator Type Codes Used to Categorize SDIs 49 iii) Indicator Code Thesecodesbavebeenassignedto facilitate identification and referencing. The fïrst two or three letters refer to the organization using the SDI. The last two or three letters signify the factor being measured. iv) Description This field provides a concisedescriptionof what specifically is being measured. v) ResponsibleOrganisation Each SDI has been proposedandlor developedand maintained by a particular organization. In some cases, the responsible organization is different than the organization that collects monitoring datausedto calculateSDI values. vi) GeographicScope Each SDI pertains to a specific area as indicated in this tïeld. Some indicators have been proposedfor generalusebut are net being practically applied at the presenttime. In thesecases, the intendedscaleand scopeof application is indicated as being “ns” (i.e., not specifïed). vii) Time Series A key featureof SDIs is the ability to track changesover time. This fïeld provides information on the period ovcr which data tire available and have been used to calculate SDI values. Information is also included regarding any key specifics conceming any limitations or unusual featuresof the supportingdata set. viii) UpdateFrequency SDI valuesmay changeover time. This field provides information on how regularly monitoring dataarecollected and new SDI valuesare calculated. 50 ix) Method of Calculation This &Ad describesthe salient featuresof the method usedto calculate SDI values. Details are provided which may affect the reliability and interpretationof SDI values. In some cases,details on the calculation method may not be currently available or bave not been fully fommlated. These records are denoted by “ns” followed by ouï best interpietation as to how reasonable values for the SDI might be calculated. x) Source The large majority of fisheries resourcesSDI information is available through the Internet. This field provides one or two Internet addressesfrom which the data used to obtain information for the particular record were primarily obtainedand from which further details on the indicator are available xi) Notes This final field includes any observationsabout the SDI or its application that may be relevant when consideringits potential application in the NTREE ESDI initiative. 51 Indicator Measure Description Indicator Type li Indicator Code D FAO-EXR Exploitation rate ResponsibleOrganisation ns GeographicScope ns Tinte Series ns UpdateFrequency ns Calculation Method ns- Fishing Source Notes mortality rate in the poputatton of target species http:l/w.fao.ora/DOCREP/OO3lXSOO2E/X8EOO.htm This SDI is proposed but was net practicatly applied by the FAO (Food and Agriculture Organisation of the United States). Are there any reasons given as to why it was not practically applied that might be helpful for this group to know? Indicator Measure Description Indicator Type of D Indicator Code Commercial catch of Pacifie herring ResponsibleOrganisation Environment Canada GeographicScope Gmstal BCwaters Time Series Comprehensive UpdateFreqaency Annual Calculation Method Cbmbined source Notes sales slip data available sine 1950. total harvest of Pacifie herring from all coastal BC waters EC-PHH 52 Indicator Measure Description Indicator Type If D Indicator Code GPI-TLC Annual lobster reported landings ResponsibleOrgatiisation DFO GeographicScope Coasial NW Time Series Since 1946 Swtia UpdateFrequency ~nnua~ Calculation Method Totalreported landings of lobster Source Charles et al. 2001 Notes This SDI is used only for lobster since direct measures if standing biomass are net available. Indicator Meusure Description If Indicator Type D Indicator Code Catch structure - DefinitIon? (size. condition, and age of twvested ResponsibleOrganisation FAO-CAT fish) ns GeographicScope ns Time Series UpdateFrequency ns Calculation Method Six. condition and age of hawested fish Source htttxllw.fao.orqlDOCREPlOO3lX8OO2ElX8OO2EOO.htm Notes This SDI is proposed but was net practically applied by the FAO. Are any reasons given that would be helpful for this group to know? 53 Indicator Measure Description IS Indicator Type Population ~oastd Tinte Series Sine UpdateFrequency Annual Calculation Method Numbers ~’source Notes Description OF0 NOV~ ~cotia 1985 Charles for at least one herring of fish in each stock age class et al, 2001 Requires Indicator Measure GPI-PAS age structure ResponsibleOrganisation GeographicScope Indicator Code D IS Relative ResponsibleOrganisation regular biological surdeys to estimate Indicator Type abundance of target population numbers Indicator Code D FAO-ABD species ns GeographicScopc ns Tinte Series UpdateFrequency ns Calcatation Method -Population size (numben and biomass) of target species relative Sp?CiS source htto://www.fao.ora/D0CREP/003/X8002E00.htm Notes This SDI is proposed but vas net practically applied by the FAO to populations of other 54 Indicator Measure Description 1s Indicutor Type D Indicator Code EC-PHA Abundance of spawning biomass of Pacifie herring stocks ResponsibleOrganisation Environment Canada GeographicScope CoastalBC waters- Reported forfivedistinct stocks Time Series Data of higher quality are available since about 1970 wtth tends reported back to 1951 UpdateFrequency Annual Cakulation Method Spavming biomass estimates on an individual stock basis are weighted between the two stock assessment models according to a subjective evaluation of the reliability of the available data. Source http:llwww.ec.qc.ca/ind/EnqliSh/He~inq~ech Suplphsupi e.cfm Notes Indicator Measure Description IS Indicator Type D Indicator Code GPI-FBM Trends in fishable biomass ResponsibleOrganisation DFO GeographicScope Coastal lova Scotia Time Series Since 1970 for some species UpdateFrequency Annual Cakulation Method Measure of total, biomass of 8sh in the current stock of a target species which are of marketable size. Source Charles et al, 2001 Notes Three separate SDls presented for three Rnfish species. 55 Indicator Measure Description IS Indicator Type I Indicator Code GPI-SAA Size at age ResponsibleOrganisation DFO ,GeographicScope Coastal lova Swtia Time Series Since 1960 for some species and stocks UpdateFrequency Annual CahdatiOiI Method Average size (ie., weight) of individual fish at a given age Source Chartes et al, 2001 Notes Data from representative SamPles taken from landed hawest. Separate SOIS require for each stock of a targeted sPecies Indicator Measure Description 2 Indicator Type Dt Indicator Code Direct effects of fishing gear on non-target species ResponsibleOrganisation ns GeographicScope ns Time Series UpdateFrequency ns Calculation Method Source Notes ns - Fishing mortaty rate in populations of non-target species FAO-NTS 56 Indieator Measure Description 2 Indicator Type Ii Indicator Code EC-FMP Predators and commercial catch of West Coast Vanwuver Island herring stock ResponsibleOrganisation EnvironmentCanada GeographicScope west wast Vancouver Island Time Series Since 1983 UpdateFrequency Annual uQto 1993 CakdatiOn Method Estimated consumption.raieof herring by major Qredatorswmpared to commerciallandings Notes This SDI is based on detailed biologicalfesearch which may net be undertaken on a regular basis or over extensiveamas. Indicator Measure Description 2 Indicator Type 1, Indicator Code FAO-TPH Indirect effects of ftshing: trophic structure ResponsibleOrganisation ns GeographicScope ns Tinte Series UpdateFrequency ns Calcufation Method The ratio of the hnests of piscivorousto planktivorousspecies as an indicator of changes in the trophic structure of marine ewsystems. Source Notes This SDI is proposed but was not practiwlly applied by the FAO Indicator Code FAO-KV Indicator Measure 2 Indicator Type Xt Description Landings composite ResponsibleOrganisation GeographicEcope Applied TimeSeries Since UpdateFrequency Polential Calculation Method The index - landings volume ns to large 1975 ocean in some for regular landings normal zones (e.g., North using annual cases updating volume for each exploited hawest statistics species averaged over all categories using a log distribution Source http:l/w,w.fao.ora/DOCREP/OO3/X8OD2EJXSOO2EOO.htm Notes This SDI (cg., has North been applied Atlantic, to demonstrate West Central Indicator Measure 2 Indicator Type Xt Description Allantic) Landings composite ResponsibleOrganisation Geographic&Ope Applied Time Series Sine UpduteFrequency Potential application to Select regional fisheries Pacifie) Indicator Code FAO-LCR index landings variante ns to large 1975 ocean variante the average zones in some for regular Calculation Method The landings itS potential in each Nodh using annual Atlantic) cases updating in landings of the (e.g.. squared among harvest categories difference using between statistics a log normal the overall distribution. average landing The and variante the actual case. Source http://w.fao.oro/D0CREP1003»(8002E»(8002E00.ht”? Notes This SDI has been (e.g.. Notth Atlantic. applied West to demonstrate Central Pacifie) its potential application to Select regional fisheries is 58 Indicator Measure 2f Description Indicator Type Dh Indicator Code FAO-HAB Direct effects of gear on habitats ResponsibleOrganisation ns GeographicScope ns Time Series UpdateFrequency ns Cakulation Method ns - Some measure of the proportion of the available habitat annually disturbed by fkhing or oiher human activities. Source http://w.fao.orq/DOCREPlOO3lXSOO2ElXSOO2EOO.hlm Notes This SDI is proposed but was not practicallyapplied by.the FAO Indicator Measure Description 2f Indicator Type It hdicator Code GPI-BTE Eiomasstransfer efkiency ResponsibleOrganisation DFO GeographicScope Coastal Nova Scotia Tinte Series ns UpdateFrequency ns Cakutation Metbod Biomasstransfer eficiency = yield/(catch + byatch) for ail species combined Source Charleset al, 2001 Requires careful repoting of by-catchlandings and discards. These data are beginning to be regularlycollected. 59 Indicator Measure 2s Description Indicator Type Dh Indicator Code FAO-Q&A Area and quality of impotint or criticalhabitats ResponsibleOrganisation ns GeographicScope ns Time Series UpdateFrequekcy ns Calcuiation Method Changes in the avaitabtesuppty of important or criticathabitats Source htto:llww.fao.orq/DOCREPiOO3lX8OO2ElX8OO2EOO.htm Notes This SDI is proposed but was net practicallyapplied by the FAO Indicator Measure 2s Description Indicator Type IP Indicator Code GPI-SFC Areas closed to shellfishhawesting ResponsibleOrganisation EnvironmentCanada Swtia GeographicScope ~oastat NOV~ Tinte Series Update since 1960s Frequency Annual Calculation Method ns- Totalareactosed times the number of days closure in effect Source Charles et al. 2001 Notes Work is undeway to estimate values for this SDI 60 Indicator Measure Description Indicator Type ai Fisheries contribution ResponsibleOrganisation D Indicator Code FAO-$DP to GDP ns GeographicScope ns Time Series ns Vpdate Frequency ns Cakulation Method ns - Proootiion Source http://w.fao.ora/DOCREP/OO3/X6OO2E/X8OO2EOO.htm Notes This Indicator Measure 3f Description Produced of total SDI is proposed GDP attributable to fisheries but was net practically Indicator Type D ResponsibleOrganisation capital in fisbing applied sector by the FAO Indicntor Code FAO-$IV sector ns GeographicScope ns Tinte Series VpdateFrequency ns CdCuhtiOn Method ns-Total govemment value and of equipment insurance and property based on economic agencies Source Notes This SD1 is proposed but ws net practically applied by the FAO statistics supplied by fishers to 61 Indicator Measure Description 3f Indicator Type Indicator Code D ECJPH Eamomic value of Pacifie herring hawest ResponsibleOrganisation Environment Canada GeographicScope coastal SC waters Time Series Comparable data series since 1975 - reported tends since 1935 UpdateFrequency Annual Calculation Method Marketvalueof all herring prcducts (primarily me and roc-on-help products) irom all coastal SC waters expressed in constant dollars Source httQ://www.ec.qc.calind/EnqliSh/Herrinq~ech SudQhsuQ3 e.cfm Notes Indicator Measure Description 3f Indicator Type D Indicator Code FAO-PHR Annual quantity of harvest ,ResponsibIeOrganisation ns GeographicScope ns Time Suies annual UpdateFrequeticy ns Calculalion Method Total quantity (e.g.. tonnes) of target species captured Saufce htto://~.fao.ora/DOCREP/OO3/X8OO2E/X80O2EOO.htm Notes This SDI is Qrqposed but was net practically applied by the FAO based on reported catch statistics 62 Indicator Measure Description 3f Indicator Type D Indicator Code FAO-$HV Annual gras value of harvest Responsible Organisation Geographic Scope Time Series ns ns ns Update Frequency ns Calculation ns _ Grass market value based on reported catch statistics and constant dollar market prices Method Source Notes Indicator This SDI is proposed but was net practically applied by the FAO Measure 3f Indicator Type D Indicator Code GPI-$ES Description Responsible Organisatiorz Geographic Scope ns coasta~NOV~Scotia Time Series ns Update Frequertcy ns Calculalion Surface area of ocean times an aggregate economic coefficient designed to include the areal Method unit value of non-marketed environmental services Source Charles et a,, 2001 Notes No discussion is presented as to how trends in this SDI would be calculated. 63 Indicator Measure Description si Indicator Type D Indicator Code GPI-WV Annua, gross value of ha-est ResponsibleOrganisation DFO GeographicScope ~oastalNOV~ scotia Time Series Since 1969 UpdateFrequency Annual Cakulation Method Combined gross market value based on reported catch statistics and constant dollar market prices Source Charles et al. 2001 Notes Indicator Measure Description Indicator Type 3f GeographicScope kxa Since 1984 UpdateFrequency Annual Cabxlation Method GDP NS Dept. of Finance Scotia Time Series Notes Indicator Code GDP attributable to fisheries ResponsibleOrganisation Source D includes expenditures attributable to Bshing and fish processing activities Charles et al, 2001 GPI-GDP 64 Indicator Measure Description 3f Total Indicator Type D exporls ResponsibleOrganisation Indicator Code GPI-EXP of fish products ns GeographicScope NQWscotia Time Series Since UpdateFrequency Annual 1980 Calculation Method ~nnualgossexperts tomer countries masuresinconstanl dollars Source Charles et al, 2001 Notes Indicator Measure Description Indicator Type 3f Annual quantity ResponsibleOrganisation GeographicScope coasta~ Tïme Series Since UpdateFrequency Annual Caiculation Method Combined Notes Charles Indicator Code GPI-PHR of harvest DFO NOV~ Scotia 1919 total quantity staBstics Source D et al. 2001 (e.g., tonnes) of target species captured based on reported catch 65 Indicator Measure Description Indicator Type D 3s Indicator Code GPI-$CS Gras value of cod stocks ResponsibleOrganisation ns GeographicScope coastal NOV~ Swtia Tinte Series Since 1982 UpdateFrequency Annual Calculalion Method Total biomass of cod stocks times the prevailing market prie SOUIW Charles et al. 2001 Notes Interpretation of tiis SDI may be wnfounded by opposing tends in biomass and market prices. A separate SDI is required for each species. Indicator Measure Description 3s Indicator Type D Indicator Code GPI-$RS Grass value of herring stocks ResponsibleOrganisation ns . GeographicScope Coastal lova Scotia Time Series Since 1972 UpdateFrequency Annual Cakulation Method Total biomass of herring stocks times the prevailing market price Source Charles et al, 2001 Notes Interpretation of this SDI may be confounded by opposing prices. A separate SDI is required for each species. Vends in biomass and market 66 Indicator Measure Description 3s Indicator Type AQpreciaBOnldeQrecialion ResponsibleOrganisation in cod stocks NovaSc&ia Coastal Tinte Series Since 1981 UpdateFrequency Annual change in the gross value of cod stocks compared to the Qreceding year Source Charles et al, 2001 Notes A separate SDI is required for each species. Indicator Measure Description GPI-$AD ns GeographicScope Cakulation Method Annual Indicator Code D 3s Indicator Type Indicator Code D GPI-$HS Grass value of haddock stocks ResponsibleOrganisation ns GeographicScope Coastat lova Scotia Time Series Since 1972 UpdateFrequency Annual Calculution Method Total biomass of haddock stocks times the prevailing market prie Source Charles et al. 2001 Notes Interpretation of this SDI may be confounded by opposing trends in biomass and market prices. A separate SDI is required for each spectes. Indicator Measure 4 Indicator Type D Description Distdbution of harvest among Sarget species ResponsibleOrganisation ns GeographicScope Coastal Time Series Since 1972 Update Indicator Code GPI-DHV NOV~ Scotia Frequency ~nnua~ Cakulation Method Percentage of total harvest accounted for by major groups of target species Source Charles et al, 2001 Notes This SDI is net a single number but a combined display of values for the major groupings of target species 68 APPENDIX Summary B of Individbal Forest Resource SDIs 69 This appendix provides smnmary information for the forest resource SDIs included in this inventoty. The inventory is maintained in a relational databaseandcari be queriedand sorted. For eachSDI, the following information is provided. xii) Indicator Measure xiii) Indicator Type xiv) Indicator Code XV) xvi), Description xvii) GeographicScope xviii) Time Series xix) Update Frequency XX) xxi) Method of Calculation xxii) Notes ResponsibleOrganization Source/Author A brief explanationof eachof thesefields follows. i) Indicator Measure ForestresourceSDIs have beendesignedto track various measuresof environmentalquality. TO ease comparisons among the various types of measure, they bave been grouped into broad categories. Specitïcally, the SDIs bavebeengroupedinto four measurementcategories. Code 1 Description 2 Wood supply Non-timber resourcesupplies 3 Ecosystemhealth 4 Economie performance Table A.1 - Indicator Measure Codes Used to Categorize SDIs 70 ii) Indicator Type SDIs may be based on various parameters directly indicating ecosystem. Altematively, indirect measures may be used as indicators. composite index derived from multiple of these alternatives the statu of forest resources ,or an were noted. measures of a forest resource. These variants are indicated Finally, some SDIs are a As well, variants on éach in the database by one of hvo modifïers (Table 2). For example, the code “Ie” connotes an SDI based,on an indirect measure of ecosystem health. Code Description D Direct measure of indicator condition 1 Indirect measure of indicator condition X Index of multiple measures of resource condition e Measure of ecosystem condition S Measure of condition of individual species or resource value Table A.2 - Indicator Type Codes Used ta Categorize SDIs iii) Indicator Code These codes bave been assigned to facilitate identification letters refer to the organization using the SDI. and referencing. The first two or three The last two or three letters signify the factor being measured. iv) Description This tïeld provides a concise description of what specifically is being measured. 71 v) ResponsibleOrganization Each SDI has been proposedand/or developedand maintained by a particular organization. In some cases, the responsible organization is different than the organization that collects monitoring data usedto calculate SDI values. vi) GeographicScope Each SDI pertains to a specific area as indicated in this tïeld. Some indicators have been proposedfor generaluse but are not being practically applied at the presenttime. In thesecases, the intendedscale and scopeof application is indicatedas being “ns” (i.e., not specified). vii) Time Series A key feature of SDIs is the ability to track changesover time. This field provides information on the period over which data are available and bave been used to calculate SDI values. Information is also included regardingany key specifics concerning any limitations or unusual featuresof the supportingdata set. viii) Update Frequency SDI values may changeover time. This lïeld provides information on how regularly monitoring dataare collected and new SDI valuesare calculated. ix) Method of Calculation This field describesthe salient featuresof the method used to calculate SDI values. Details are provided which may affect the reliability and interpretationof SDI values. In some cases,details~ on the calculation method may not be currently available or bave not been fully formulated. These records are denoted by “ns” followed by our best interpretation as to how reasonable valuesfor the SDI might be calculated. 12 x) Source The large majority of forest resourceSDI information is availablethroughthe Internet. This field provides one or two Internet addressesfrom which the data used to obtain information for the particular record were primarily obtained and kom which further details on the indicator are available. xi) Notes This final field includes any observationsabout the SDI or its application that may be relevant when consideringits potential application in the NTREE ESDI initiative. 73 Indicator Measuve Indicator Type 1 Indicator Code CFM-$TL Responsible Organisation CCFM GeographicScope &ada Description Grass value of lest wood fiber from fire Tinte Series since 1974 UpdateFrequency annua~~y Calculation Method Grass value of the total voIume of wood fiber lxt to forest fires. Source http://wvw.nrcan.ac.ca/ds/Droi/~~iab/ci/2000 e.html Notes Estimating fie value of standing timber is complicated by the forest tenure systems in place in many provinces. Indicator Measure I Indicator Type D Indicator Code CFM-HYS Responsible Organisation CCFM GeographicScope Canada Description Annual harvest/yield balance Tinte Series Since 1970 UpdateFrequency annua~~y Calculation Method Total annual haivest relative to estimated sustainable annual yield Source httD:l/www.nrcan.ac.ca/cfs/oroilr>piablcil2000 Notes SDI broken down by hardwood and s3twood. calculated. e.html No single measure Bath yield and harvest are plotted side by each. 74 1 Indicator Measure Indicator Code Responsible’ Organisation Iadicator Type CFM-FTL CCFM GeographicScope canada Description Loss of wood fiber from ftre Tinte Series since 1974 UpdateFrequency annua~~y Caktdafion Method Source Total volume of wood ftber lest to forest ftres. http:llwww.nrcan.qc.ca/cfslproi/PPiab/cil2000 e.html Notes 1 Indicator Measure Indicator Code Responsible Organisation Indicator Type CFM-PFL CCFM GeographicScope canada Description Avaitable productive forest land Tinte Series ns UpdateFrequency ns Cabxlation Method Total area of productive forest land availabte for harvesting Source http:lIWWW.nrCan.qC.calcfSIDroill)lliablO~ e.htmt Notes No quantitative measures for this SDI are provided. Indicator Measure 1 Indicator Code Responsible Organisation hdicator Type NEIS-GDP Environment Canada GeographicScope canada Description Forest sector Grass Domestic Product Time Series 1970-96 Update Frequekcy annua~ Method The CakdatiOn Forest sector GDP is in relation to the volume of timber hawested, and its Mntdbution is based on 1992 Canadian dollars Source httD:/l~.ec.ac.calInd/En~lishlForestrr Notes Data source: CFS Indicator Measure 1 Indicator Code Envirodment Canada GeographicScope Canada Description Total volume hawested Time Series 1970.96 &hdUtiOU e.cfm Indicator Type NE6NH Responsible Organisation Update Suplfosup8 Frequency annual Method Total ahnual hardest volume (m3,millions) refers to the total industria roundwood production. which includes legs and bolts, pulpwood. and other industdal roundwood Source http:llwww.ec.~c.ca/Ind/Enalish/Fores~ech Notes Data source: CFS Suplfosupl) e.cfm Indicator Measure Indicator Code Responsible Organisation Geographic 1 Indicator NEIS-THL Environment Scope Canada canada Description Timber Tinte Series 1970-96 Update Frequency annual Calculation Annual AAC Method harvest level sofkwood and hardwood Source hUo://www.ec.ac.ca/Ind/EnalishlForestrrch Notes Data Indicator source: Measure Indicator Geographic volume Indicator NFA Scope NFA Forest Time Series na Update Frequency na Method Grming cwer stock stockby of timber forestry Source htto://www.NovaForestAlliance.com Notes Group has net yet met. M>VW type harvest Sur>ifosur>l & CCFM NFA-FCS Description Calculation CFS 1 Code Responsible Organisation Type Type in relation e.cfm to ’ 1 Indicator Measure Indicator Code Responsible Organisation Indicator Type NFA- %EP NFA GeographicScope NFA Description Perce”tage of area meeting expeciedproductivity Time Series na UpdateFrequency na Calculation Method Percentageof area meeting expectedgrowth targets for site type Source http:/l~.NovaForestAlliance.coB Notes Graup has not yet met. Indicator Measure 1 Indicator Code Responsible Organisation Indicator Type De CFM-FMI CCFM GeographicScope Canada - provincial/territodaI Description Forest management inventoly Time Series ns UpdateFrequency cyclicwith cyclesranging from 10 to 15 years Calculation Metbod Consistsof wmplete area coverage. land caver mapping and estimates of wood volume and biomass Source hltp:llwww.nrcan.~c.calcfs/proilppiab/cil2OOO e.html Notes Surveyof an area to determine volume. location,exient, composition and structureof the forest resource. Inventorysystems range from reconnaissanceto operational (detailedinventoryof a specificarea for operational harvestingplanning) 78 1 Indicator Measure Indicator Code Indicator Type NFA-HHD Responsibk Organisation NFA GeographicScope NFA Description Harwst area with human disturbance Time Series na UpdateFrequency na CalcuhztionMethod Area and type of human disturbance specific to forest harvesting Source htt~://www.NovaForestAlliance.wm Notes Group has not yet met. Indicator Measure Indicator Code 2 Indicator Type CFM-HGS Responsible Organisation CCFM GeographicScope Canada Description An~al Tinte Series Sine 1993 hawest of game svxies UpdateFrequency annua~l~ Calculation Method Hawest of economically important game species SOUW? hnD:lhvww.nrcan.qc.c,~f~,~~~i,~~i=b,~i,~ggg e.html Notes Estimated annual harvest is based on a recent study tbat evaluated the conservation status, geographical distribution, abundance population trends and factors affecting the abundance of 20 selected animal species. 79 Indîcator Measure Indicator Code Type CFM-RUD CCÇM Responsible Organisation Geographic Indicator 2 Scope Canada Description Recreational Tinte Series Since Update Frequency annual Calculation Number of days (million user days) spent participating in nature -based activities such as: outdca activities in nature area. tildlife viewing. recreational fishing and hunting in forested ecoprovinws vs. non-forested ewprovinces. Method Source user-days 1996 httn:llw.ccfm.ora/pi/4e.html Notes Indicator Measure Indicator Code Responsible Organisation Geographic Type I CFM-E/P CCFM Scope Canada Description Annual Tinte Series Since Update Frequency annu& Calculation Average Activities Source Notes Indicator 2 Method expenditurelperson 1996 yearly expenditure(million http:/lwwwxfm.orq/oi/4e.html dollars)/person on nature-related 80 Indicator Type 3 Indicator Measure Indicator Code De CFM-MAI Responsible Organisation CCFM GeographicScope Canada Description Mean Tinte Series 1996 UpdateFrequency irregutar Calculation Method The net volume qmual incremenl of wood . no systematic monitoring of wood produced Source htt~:l/www.nrcan.ac.ca/cfs/~roi/~~iab/ci/2000 Notes NO comprehensive trend-over-time Separate biomass are not included. ecozones. Indicator Code annually in place by commercial tree species e.html data are available. Other forms V~IN?S are estimated for each Indicator Type 3 Indicator Measure current~y of of 12 De CFM-%TF Responsible Organisation CCFM GeographicScope Canada Description Total Time Series ns UpdateFrequency Can forest area be derived CalcuhztionMethod Percentage percentage digitally of total area from in each Source htt~:l/www.nrcan.ac.calcfsloroilDpiablcil2000 Notes One indicator is required real time for each satellite Imagery of one of 15 ecozones e.html ecozone. covered by forest 81 3 Indicator Measure Indicator Code Responsible Organisation Indicator Type De CFM-SRA CCFM GeographicScope canada Description Forest area successfully regenerated Time Series Sine 1975 UpdateFrequency annua~~y Calculation Method Combined cumulative area of natural and artificial regenemtion provincial stoching standards meeting Source h~p://www.nrcan.~c.ca/cfs/Droil~~iab/ci~2OOO Notes Stocking standards relate only to commercially important tree species. Another relevant measure might be the accumulated area regenerating to .another forest community type. Indicator Measure 3 Indicator Code CFM-CUR e.html Indicator Type De Responsible Organisation CCFM GeographicScope Canada Description Change in cumulative forest area unsuccessfully regenerated Tinte Series since1975 UpdateFrequency annud~y Calculalion Method Annual change in cumulative area of harvested forest not meeting provincial stocking standards Source http:llwww.nrcan.gc.ca/cfs/oroil~~iab/ci/OOO e.html Stocktng standards relate only to commerctally important bec species. Most of these areas are vegetated but notwilh commercially important tree species. 82 Indicator Measure 3 Indicator Code Indicator Type De CFM-%AT Responsible Organisation CCFM GeographicScope Canada Description Forest type and age class mix Tinte Series ns UpdateFrequency ns Calcalation Method Area of forest in one of three caver types (Le., softwood, hardwood. mixedwood) in one of five age class categories in one of 8 ecozones on either private or public land Source htt~:/lwww.nrcan.~c.calcfsloroil~~iablcil2OOO Notes No composite indicator or index is proposed. This indicator category includes 120 separate values and does net include 6 of the etozones in Canada. Indicator Measure 3 Indicator Code e.html Indicator Type De CFM-FTA Responsible Organisation CCFM GeographicScope Canada Description Forest type area Time Series ns UpdateFrequency Approximately every 6years Calculation Method Total area of forest in one of three categories (i.e.. softwood. hardwood. mixedwood) in each of 8 ecozones Source htt~://www.nrcan.gc.ca/cfSIProi/DDiab/ci/2000 Notes Because the management inventories are being continually upgraded. the national inventory is composed of information gathered at different times, and cannot be used to monitor change relative b hisbric conditibn. e.html 83 3 Indicator Measure Indicator Code Indicator T}~pe De CFM-WA Responsible Organisation CCFM GeographicScope Canada Description surface water area Tinte Series ns UpdateFrequency ns Calculation Method Combined area of lakes and rivers wntained within foret lands Source httr>:l/www.nrcan.~c.ca/cfs/oroi/pr>iab/i/2000 Notes No trend over time data are available. It is not clear as to the relationship between this measure and trends in sustainability. Indicator Measure Indicator Code 3 e.html Indicator Type De CFM-URA Responsible Organisation CCFM GeographicScope Canada Description Forest area unsuccessfully regenerated Time Series Since 1975 UpdateFrequency annua~~y Cakxdation Method Cumulative area of hawested iorest net meeting provincial stocl«ng standards Source htttx//w.nrcan.w.ca/cfs/txoill>r>iab/ci/2000 Notes Stocking standards relate only to commercially important tree species. Most of these areas are vegetated but not with commercially important tree species. e.html 84 Indicator Measure 3 Indicator Code De Indicator Type NEIS-%PA Responsible Organisation Environment GeographicScope Setected ecozones of Canada: Pacifie Maritime, Boreat Shield. and Atlantic Maritime. Vegetation four forest types for Canada. The CCAD areas Description Percentage Time Series 1985995 Canada protected forest Montane Cordillera. Caver: data on protected by federal. area UpdateFrequency e”efy5 yr.3 Calculation Method Percentage intervals of protected forest Source htto:lIWWW.ec.qc.CalInd/Enalish/For Notes Data source : Canadian Wildlife 1 000 ha in size were used. Indicator Measure 3 Indicator Code area within a given ecozone BioiTech Su~/fbsulO Service(CWS). Protected Indicator Type for 5 year e.Cfm areas larger De NEIS-UR4 Responsible Organisation Environment GeographicScope Canada Description Forest Time Series 197597 UpdateFrequfncy annual Cakulation Method Cumulative standards area Canada unsuccessfully area regenerated of hawested Source hno://www.ec.qc.ca/lnd/Enalish/Forest/Tech Notes Data source: CFS forest net meeting provincial Suplfosup9 stocking e.cfm than 85 Indicator Measure 3 Indicator Code Indicator Type De NEIS-SRA Responsible Organisation Environment Canada GeographicScope canada Description Fcm?Slarea suca??.sfully reganerated Time Series 197587 UpdateFrequency annual Calculution Method Combined cumulative area of natural and artificial regeneration provincial stocking standards Source httr>:l/www.ec.ac.caIlnd/EnqlishlForestrch Notes The data include timber productive forest land in Canada and are limited to Crown land only. Indicator Measure Indicator Type 3 Indicator Code SuolfosuD9 meeting e.cfm De NFA-FTA Responsible Organisation NFA GeographicScope Nova Description Fores, type area Time Series na S&a Mode1 Forest UpdateFrequency ns Cakulation Method Total area of forest in one of three categories (Le., softwcod, hardwood. mixedwood) in each of 8 ecozones Source ht~://www.nrcan.~c.calcfsl~roilr>l>iab/OOO Notes Because the management inventories are being continually upgraded. the national inventory is composed of information gathered at different times. and canot be used to monitor change relative to historic condition. e.html 86 Indicator Measure Indicator Code Responsible Organisation Geographic 3 Indicator Type DS CFM-PIS CCFM Scope Canada Description POQUlStiOnS Tinte Series ns Update Frequency ns Calculation Population Method Of SSkCt Vend SQSCiSS of indicator species SOUITX httQ:lhvww.nrCan.~c.ca/cfs~proilQQiab/il2000 Notes The use of indicators species remains community. A sepaate SDI is required selected. Indicator Measure Indicator Code 3 the last several decades e.html Indicator controversial for each in the scientific indicator species Type DS CFM-CSD Responsible Organisation CCFM Geogvaphic Scope canada Description Species Time Series ns Update Frequency ns Cabxlation There is ,no database Ca”ad.3. Method over distribution describing historic and current ranges of specfes in Source httQ:~/~.nrcan.qc.ca/cfsfpr~ilQpiab/~f2000 e.html Notes Secause the management inventories are being continually upgraded. the national inventay is composed of information gathered at different times, and canot be used to monitor change relative to histodc condition. 87 Indicator Measure Indicator Code Responsible Organisation Indicator Type 3 DS CFM-V-TE CCFM GeographicScope Canada Description Extinct, lhreatened. endangered. Time Series ?? - SDI affected significanlly by new information rare or vulnerable species UpdateFrequency ns Calculation Method Proporkn of forestdependent species that bave been listed as extinct, endangered, threatened, rare OI vulnerable by COSEWIC or provincial organisations. Source Notes COSEWIC lists species, subspecies and populations in these categodes. Reliable estimates are only available for larger animal groups and vascular plants. Classifications of species vary among jurisdictions and from year to year with new information. Indicator Measure Indicator Code Indicator Type 3 DS WNMF-MD Responsible Organisation WNFM GeographicScope defined sturdy areas within WNMF Description Marten distribution Time Series Sin’ce 1992 UpdafeFrequency inegular: 4 stages (IsoO-19%) Cakulation Method Distribution map of Newfoundland n@en based on available’habitat. Source htt~:llw.wnmf.wm Notes Source of data from DFRA Inland fish and wildlife. 88 Indicator Measare Indicator Code Responsible Organisation . 3 Indicator Type WNMF-CPL WNMF GeographccScope WNMF Description Caribou QOQUktiOn kV'& Time Series Since 1992 UpdateFrequency irregular & dictated by Wildlife Division Cahxfation Method Population estirqates of the levels of caribou based on two census surveys for each of two district herds Source http:llww.wnmf.com Notes. Source of data from 0FP.A Indicator Measure Indicator Code 3 Indicator Type NE&%RA Responsible Organisation Environment Canada GeographicScope Timber-productive and total forest area, in the four main forested ecozone~ of Canada Description Percentage road axes.5 Tinte Series 1991 & 1994 Update Frequency everys yrs Cakulation Method Percentage of forest area in timber-productive area in the faur’main forested ecozones forest awa and total forest Source htt~:l/www.ec.sc.calIndlEnalishlFor Notes Data: CFS. Each record in CanFI (Canada% Forest Inventow) has a classifier indicating the type of road access per cell. A cell is considered road accessed if there is a road within 10 km. EioiTech Sup/fbswl e.cfm 89 Indicator Measure 3 Indicator Code Indicator Type NFA-CI Responsible Organisation NFA GeographicScope NFA Description Climate indices Time Series na UpdateFrequency na Calculation Method Climate indices: ph and amount of precipitation. Source htt[):llwww.NovaForeStAlliance.cOm Notes Group has net yet met Indicator Measure 3 Indicator Code Indicator Type ESLMF-AES Responsible Organisation BSLMF GeographicScope BSLMF Description Area Time Series Since 1997 of exotic species Update Frequency annually Cakulation Method Area in hectares occupied by exotic species Source htt~:l/www.foret.fmodbsl.4c.ca Noies Source of data from GIS 90 Indicator Measure 3 Indicator Code Indicator Type CFM-I&I Responsible Organisation CCFM GeographicScope canada Description Insect infestations Tinte Series since 1960s UpdateFrequency annua~ly Calculation Method Total area of forest severely infested with one of several species of defoliating or lethal insects (e.9.. caterpillars. beetles) Source htt~:/lwww.nrcan.ac.Ca/cfs~~rai/o~iab/ci/2000 Notes These data must be treated with caution as vaying standards of data collection and compilation exist across the nation. A separate SDI may be required for each pest species included. Indicator Measure 3 Indicator Code e.html Indicator Type le CFM-O3E Responsible Organisation CCFM GeographicScope Canada Description Exceedance of ozone titical Tinte Series Sine UpdatoFrequency periodically level 1964 Cakulation Method Changes in the total area of foiest exposed to more than 0.6 ppm of 03 ‘per heur cumulatively per year Source htt~:l/www.nrcan.ac.ca/cfslproil~~iab/OOO Notes This SDI cannot be expressed as a single value but is displayed geographically showing temporal and spatial trends. e.htm 91 Indicator Measure 3 Indicator Code Indicator Type CFM-F03 Responsible Organisation CCFM GeographicScope canada ozonecmcentmtions Description Ground-level Time Series Since 1996 UpdateFrequency annua~~y Calculation Method Average hourly means of 03 to which forest canopy is exposed SOUIW? htt~:/l~.nrCan.~c.calcfsl~~oikpiab/cil2000 Notes The interpretation of these monitoring data at a national level in the form of an SDI has not been detenined. 3 Indicator Measure Indicator Code e.htmt Indicator Type CFM-ADL Responsible Organisation CCÇM GeographicScope Canada Description Acid deposition load Tinte Series Sincs early 1980s UpdateFrequency annua~~y CalcuhztionMethod Total area of forest receiving greater than the critical load of acid deposition annually source htt~:l/www.nrcan.ac.ca/cfsbroilodab/ci/2000 Notes Critical loads for all forest ewsystems in Canada bave not been established. SDI calculated for two levels of exceedance. e.html 92 Indicator Measure 3 Indicator Code Responsible Organisation te Indicator Type CFM-EUE CCFM GeographicScope Canada Description CO2 emission rate Time Series Since 1980 UpdateFrequency annual Calculation Method The rate of annual direct and indirect CO2 emissions from forest sector arking from harvesting and wood processing divided by the total energy “se of the sector. Source htt~://w.nrcan.qc.ca/cfs/Droi/Lmiab/ci/2000 Notes This SDI measures improvements in CO2 emission reduction efficiency but does not account for changes in the absolute load of CO2 emissions being produced by the sector. Indicator Measure Indicator Code 3 e.html Indicator Type te CFM-CO2 Responsible Organisation CCFM GeographicScope Canada Description Carbon dioxide ernissions from forest sector Time Series Since 1980 UpdateFrequency annual Calculalion Method Annual direct and indirect CO2 emissions from forest sector arising from harvesting and wood processing Source http://w.nrcan.wxakfs/proi/p~iab/ci/2000 Notes Estimates are based on energy use by the forest sector and other emissions from~hawsting and certain production processes. e.html 93 Indicator Measure 3 Indicator Code Indicator Type CFM-FCP Responsible Organisation CCFM GeographicScope canada Description Forest carbon pool ‘Tinte Series 0 UpdateFrequency Last estimated for 1994 Calculation Method Combined quantity of carbon in forest ecosystems including biomass and soils Source hdp:llwww.nrcan.qc.clcfslproilppiab/ci/OOO Notes Historical and current estimates are based on carbon cycle model. Differences in the carbon pool are forecast for 7 ewclimates. Indicator Measure 3 Indicator Code e.html le Indicator Type CFM-RCG Responsible Organisation CCFM GeographicScope Canada Description Presence of road construction guidelines Tinte Series ns UpdateFrequency ns Calculation Method Percentage of total forest area covered by road construction guidelines intended to minimize soil and water impacts. Source http://~.nrcan.qc.ca/cfs/proi/ppiab/ci/2000 Notes This SDI does not measure th$ effediveness of these guidelines~only etistence. NO trend-over-time analyses are presented. e.html their 94 Indicator Measure 3 Indicator Code Indicator Type le CFM-FFA Responsible Orgaidsation CCFM GeographicScope canada Description Forest Time Series since1974 fire area Updaie Frequency annuall~ Calculation Method total area interannual tends. of forest burned by forest fires - Due to considerable variability, 10.year averages are used to eslimate Source http:llwww.nr~n.~c.cal~~lproi/DDiab/cil2000 Notes Interpretation ecologically Indicator Code e.html of this SDI is complicated by the need good” tends from bad trends. 3 Indicator Measure long-term to distinguish “natural le Indicator Type CFM-PAR Responsible Organisation CCFM GeographicScope canaga Description Representativeness Tinte Series ns UpdateFrequency periodically of protected Calculation Method ns- ~ercentage of area types relative to 12% in protected target Source http://~.nrcan.ac.ca/cfs/oroi/pro~/ppiab/ci/2000 Notes Protected area percentages used and the level of spatial areas amas in specific ecological land e.html depend on the ewlogical resolution. classification SyStem 95 Indicator Measure 3 Indicator Code Indicator Type le CFM-%PA Responsible Organisation CCFM GeographicScope canada Description Percentage of forest in protected areas Time Series ns Update Frequency ns Calculation Method Percentage of total area protected according to one of six IUCN protected area categorte?.. Source http://www.nrcan.qc.calcklproilwiab/ci/OOO Notes NO authoritative and comprehensive national mechanism exists to collect and report on biodiversity data in relation to protected areas. Distinguishing among forest types or behveen forest and non-forest protected areas is not yet possible. Indicator Measure 3 Indicator Code ehtml le Indicator Type CFM-SWP Responsible Organisation CCFM GeographicScope Canada Description Soit and water protection zones Time Series na UpdateFrequency na - required data are not systematically collected at present time Calculation Method Percentage of the forest area managed primadly for water and soit conservation. http:/iwww.nrCan.qc.ca/cfS/proi/ppiab/ci/2000 Notes e.html Interpretation of thie SDI would be difficult at a provincial or national level since level of protection required is highly variable and dependent on local conditions lil:l/www.nrcan.ac.ca/cfsl~roilDpiablcil2000 Notes Interpretation of this SDI is complicated by the need to distinguish “natural ecologically good” tends from bad trends. ehtml to 97 Indicator Measure Indicator Type 3 Indicator Code le NEIS-IDA Responsible Organisation Envimnment GeographicScope Two forested ecozones: Etoreal Shield and Atlantic Maritime Description Area affected by insect disturbance Time Series 1980-98 Canada UpdateFrequency aonual Cakulation Method Area of forest land affected by selected insect disturb&ces including the eastern spruce budwxm. the forest tent caterpillar. and the hemlock looper. Source htto:l/www.ec.~c.ca/Ind/Enqlish/Fores~ech Notes Data SO”I~~ CFS. Indicator Measure Indicator Code 3, SuDlfosuo4 e.cfm Indicator Type NEIS-CID Responsible Organisation Environment’Canada GeographicScope Canada Description Consecutive insect disturbance Time Series 1980-96 UpdateFrequemy annua~ Calculalion Method Consewtive years of spruce budworm defoliation presented as a map highlighting the spatial extent of area affected by two to fwe years and more than five years of consecutive defoliation Source httD:llwww.ec.ac.canndlEnqlish/ForesVTech’ SuUfosuDG exfm Notes Data source: CFS. Only moderate and severe defoliation categories were selected for analysis. Mod+e damage is detïned as 30-E&% and severe damage is defined as 70% or greater defoliation to a tree or stand 98 Indicator Measure 3 Indicator Code Indicator Type NEIS-FFN Responsible Organisation Environment GeographicScope canada Description Forest Time Series 1975.95 UpdateFrequency annual Calculation Method Number natura1 Canada fIre numbers of forest causes. fires whether Source httP:l/vw.v.ec.ac.ca/Ind/En4lishlForesbTech Notes Data SOU~~ Indicator Measure CCFM activities SuPlfosuP7 or from e.cfm Indicator Type le NEIS-FFA Responsible Organisation Environment GeographicScope Canada Description Fore*tfirearea Time Series 1975-95 Update by human & CFS. 3 Indicator Code caused Canada Freqaency~ annual Calculation Method The total forest land area is presented in hectares burned Source httr>:llwww.ec.ac.~a/IndlEnalishlForesVTech Notes Data source: CCFM intended for growing, not currently forested by fire disturbances SuPlfosuo7 annually in Canada e.cfm & CFS. Total forest land refers to land primarily Pr currently supporting, forests. Includes land that such as clear-tut land% is 99 3 Indicator Measure Indicator Code Indicator Type FMF-AFF Responsible Organisation ÇMF GeographicScope FMF Description Area of forest Time Series Since 1992 fragmentation UpdateFrequency 5 yrs Calculation Method Level road) of forest of forest fragmentation ecosystem Source hnp:/www.FundyModelForest.net Notes Source Indicator Measure of data fmm GFERG 3 Indicator Code (km2 of area) components & Stephen and connectedness Woodley Indicator Type NFA-HSD. Responsible Organisation NFA GeographicScope NFA Description Hawest Time Series na area with soi1 distürbance UpdateFrequency na Calculation Method Extent of harest area Source htto://www.NovaForestAlliance.com Notes Group bas not met. with significant (km of soil disturbance le 100 Indicator Measure Indicator Code Responsible 3 Indicator Type le NFA-%SS NFA Orgarrisation Geographic Scope NFA Description Percentage of maintained constructed stream crossings Time Series na Update Frequency na Calculalion Percentage of stream crossingscot~structedand maintained to standard. Metbod Source htt~:/l~.NovaForeStAlliance.Mm Notes Group has net met. Indicator Measure Indicator Code Responsible Organisation Geographic 3 Indicator Type NFA-%RS NFA Scope NFA Description Percentage of riparianzones meeting specifications Tinte Series na Update Frequency na Calculation Percentageof riparianzones meeting specifications Method Source h~~:/~.NovaFwestlliance.com Notes Group bas net met. 101 Indicator Measure Indicator Code Responsible Organisation Geographic 3 Indicator Type te NFA-%MG NFA Scope NFA Description Percentage of managed forest under guidelines Time Series na Update Frequency na Calculation Percentage of forest managed under BMPs (best management practices) and other guidslines. Method Source http:llWWw.NovaForeStAlliance.com Notes Group has not met. Indicator Measure Indicator Code Responsible Organisation Geographic 3 Indicator Type NFA-%CW NFA Scope NFA Description Percentage of wt watershed area Tinte Series na Update Frequency na Calculation Percentage ofwatershed Method area in a recent tut condition Source httr>:lI~.NovaForestAlliance.com Notes Group has not met. te 102 Indicator Measure Indicator Code Indicator Type 3 WNFM-SI Responsible Organisation WNMF GeographicScope WNMF & Island Description Species relative abundance Tinte Series Since 1992 UpdateFrequency annually CalcuhztionMethod Species interrelationships based on the relative abundan& snowshoe hare and lynx on the island. SOUITZ http:llw.wnmf.com Notes Source of data from DFRA Wildlife division fndicator Measure Indicator Code of Indicator Type 3 NElS-%TM Responsible Organisation Environment Canada Geographic$cope Timber-productive forest area of 3 main forested ecozones of Canada: Pacifie Maritime, Montane Cordillera, and Boreal Shield Description Percentage tree species mix Time Series 1991& 1994 UpdateFrequency ewy 5 yrs Calculation Method ~ercentage of tree àmber-productive species mix in accessed versus non-accessed forest. Source http://www.ec.ac.ca/Ind/En4lishlFor Notes Each record in CanFI has a classifier indicating the predominant tree species (genus) of the particular cell. The classifiers used in CanFI include Spruce. Pine, Fir. Hemlock. Douglas-fir, Larch. Cedar, Po~lar. Birch, Maple SioITech Sup/fb$w3 e.cfm 103 Indicator Measure Indicator Code Responsible Organisation Geograpbic 3 Indicator Type NEIS-ACD Environment Canada Scope Timber-productive forest area of selected ecozones of Canada: Pacifie Maritime. Montane Cordillera. and Boreal Shield Description Age-class distribution Tinte Series 1991 R 1994 Update Frequency evw 5 YB. Calculalion Percentage of age-class distribution (shown as % timber productive forest area) in accessed versus non-accessed Bmber-productive forest Method Source htt~:liwww.ec.ac.caIlnd/Enqlish/for Notes Data source: CFS. Each record in CanFI has a classifier describing the age-class of the particular cell. Only celIs identified as “Productive” were included in the data set. Iadicator Measure Imdicator Code Responsible Organisation Geographic 3 BioKech Indicator Suplfbsu~S Type e.cfm IS NEIS-FBP Environment Canada Scope Description Canadian Ereeding Eird Survey (BBS) data included over 377 survey routes across Canada. Thesa routes are located mainly in the southern half of lhe provinces. Forest bird populations Time Jeries 66.79 & 1980-1994 @date annually between May 28 and July 7 Frequency Calculaiion Method Number of specks with increasing ldecreasing populations Source http:/l~.ec.ac.ca/Ind/EnqlishlFor Notes Data source: NWRC. Forest birds are those species mainly associated with forest habitat during their breeding season in Notth America. BioiTech Sup/fbsw7 e.cfm 104 Indicator Measure 3 Indicator Code Indicator Type NEIS-#SR Responsible Organisation Environment GeographicScope Canada Description Number Time Series 1978-97 UpdateFrequeney annua~ Calculatioa Method Number of forestdependent reptiles, amphibians ,plants. endangered Canada of spacies a, risk species lichens. at risk: induding birds. Classifed as vulnerable, mammals, threatened Source htt~:llWWW.ec.ac.Ca/Ind/En4lishlFor Notes Data source: COSEWIC & RENEW. 83 forest-dependent national species as of 1997.lncludes any indigenous species, subspecies, or geographically defined population of wild fauna and flora. Indicator Measure Sur>/fbsuDS Indicator Type 3 Indicator Code SioTTech e.cfm 1s NFA-HSC Responsible Organisaiion NFA GeographicScope NFA Description Habitat Tinte Series Since UpdateFrequency ns Calculalion Method Area species for species conservation 1998 of habitat andlor suitable species Source htt~:,/www.N~“aF~~es~,,i~~~.~~ Notes Source of data from and available guilds theme regions for conservation field work. of selected risk variety. or 105 Indicator Measure Iadicator Code Responsible Organisation Geographic Indicator 4 Type CFM-$VGT CCFM Scope Canada Description Annual volume of global trade Time Series Since 1970 Update Frequency annual Cakulation % volume tends in Canada3 annual forest expert share of global trade Method Source Notes Indicator Measure Indicator Code Responsible Organisation Geographic Indicator 4 Type D SC-NRW Statistics Canada Scope Canada Description Natural resource wealth Tinte Series 1970-97 Update Frequency annua~ Calculalion Natural resource weatth masures the contdbution of Canada’% stocks of timber to national wealth at the end of each year. Valued at their estimated market value Method Source Ecoconnections: Notes Timber stocks are that portion of the forest that is accessible for hawsting, where commercial value species gmw to a marketable size within a reasonable length of time and where harvesting is allowed. Indicators and Detailed Statistics 2000 (16.ZOO-XKE) 106 4 Indicator Measure Indicator Code Iadicator Type CFM-$HP CCFM Responsible Organisation GeographicScope Canada Description Annual Tinte Series Since values of harvested pelts 1998 UpdateFrequency annually Calculation Method Economie value of harv%sted pelts from selected mammals Source http:llwww.nrcan.qc.ca/cfs/proi/DDiab/cil2000 Notes Estimated annual ha!wst is based on a recent study that evaluated conservation statu% geographical distribution, abundance population and factors affecting the abundance of 20 selected animal species. Indicator Measure the trends t Indicator Type 4 Indicator Code e.html CFM-$RF Responsible Organisation CCFM GeographicScope Canada Description A”n”al Time Series Since forestry dependent revenue 1986 UpdateFrequency annual Cakulation Method Source Notes Total tmiler revenue from forestry-dependant service par%. outitters. recreation and vacation http:l/www.nrcan.~c.ca/cfs/proilppiab/cOOO industries: camps. e.html campgrounds. 107 Indicator Measure Indicator Typé 4 Indicator Code CFM#EF Responsible Organisation CCFM GeographicScope Canada Description Annual Tinte Skies Sine forestty employment 11975 UpdateFrequency annual Calculation Method TO~~I annua~ number of employees in ~II forest-related sectors Source htt~:/l~.nrcan.ac.ca/cfsloroil~~iab/cOOO Notes A wide range of capital-intensive production technologies has been adopted by the forest industry over the last 20 years, thereby reducing the number of jobs created each cubic meter of timber hawested. Indicator Measure CFM-$EI Responsible Organisation CCFM GeographicScope Canada Description A”“Wl Time Series Since UpdateFrequency annual e",QlOye'S industries: Notes income 1971 Calculation Method Average Source I Indicator Type 4 Indicator Code e.html annual emptoyee incorne in the following paper and allied. logging. manufacturing foreshy and wood. for 108 Indicator Measure Indicator Code Responsible Organisation 4 Indicator Type I CFM-$RD CCFM GeographicScope canada Description Annuat research and development cosk Tinte Series since1990 UpdateFrequency atinuai Calculation Method Annual govemment expenditures in forest-based research. Source http://wwMl.nrcan.~c.ca/cfs/pr~i/poiablci/2000 Notes The information available on fore?.trj R&D acttvities is fragmented. Indicator Measure Indicator Code 4 e.html Indicator Type I CFWGDP Responsible Organisation CCFM GeographicScope Canada Description Annual gross domestic product Time Series since1961 UpdateFrequency annua~ Calculation Method Forest secton annual contribution to Canadian GDP (gross domestic product) Source httt):l/~.nrcan.~c,calcfs(oroi/odablci~2000 e.html Notes AIso presented individually as 1) maple products and Christmas trees. 2)paper and related industries. 3) logging and forest industries and 4) wood products. 109 4 Indicator Measure Indicator Code Indicator Type CFM-$FM Responsible Organisation CCFM GeographicScope Canada Description Annual forest management Time Series Since 1990 costs UpdateFrequency annually Calculation Method A~&I forest management expenditures from protection, silviculture. resources awess and other fores, management Source htto://~.nrcan.ac.ca/cfs/proi/~~iab/ci/2000 e.html Notes Indicator Measure 4 Indicator Code Indicator Type X CFM-$NP Responsible Organisation CCFM GeographicScope Canada Description Anoual net forestF/ profits Time Series Since 1988 UpdateFrequency annua~ Cakdation Method Net prof& in the Canadian focest sector: forestry services and operations, wocd producers. paper producers and integrated operations. Source Notes h~p:llwww.nr~n.ac.calcfslproilDDi~blcilOO e.html