Woodland caribou scientific review to identify critical habitat: chapter 4

Methodology

4.1 Framing the critical habitat question for Boreal Caribou

4.1.1 SARA: Critical Habitat

SARA Section 2 de.nes Critical Habitat as "... the habitat that is necessary for the survival or recovery of a listed wildlife species and that is identi.ed as the species' critical habitat in a recovery strategy or in an action plan for the species."
Note : SARA does not limit Critical Habitat identi.cation to the habitat that is currently occupied by the species at risk.

4.1.2 National Recovery Strategy

To identify Critical Habitat, a recovery target must be established. This target is qualitatively expressed in the draft National Recovery Strategy for boreal caribou through the following Recovery Goal and Population and Distribution Objective:

Recovery Goal:
Boreal caribou are conserved and recovered to self-sustaining levels, throughout their current distribution (extent of occurrence) in Canada.

Population and Distribution Objective:
Maintain existing local populations of boreal caribou that are self-sustaining and achieve population growth of local populations that are not self-sustaining, to the extent possible, throughout the current distribution (extent of occurrence) of boreal caribou in Canada. Note: "To the extent possible" appears in the population and distribution objective in recognition that technical and biological feasibility may affect the probability of conserving and/or recovering some individual local populations as described in the draft National Recovery Strategy for boreal caribou (Environment Canada 2007).

4.2 Definitions

The following de.nitions were established for the Boreal Caribou Critical Habitat Science Review. Development of these de.nitions was supported by the 2002 COSEWIC Status Assessment and 2007 draft National Recovery Strategy for boreal caribou (Environment Canada 2007), a review of relevant scienti.c work, and consultation with the Science Advisory Group for the review.

4.2.1 Current Distribution (Extent of Occurrence):

The area included in a polygon that encompasses the geographic distribution of all known local populations of boreal caribou (COSEWIC - Adapted from IUCN 2001), based on provincial and territorial distribution maps developed from observation and telemetry data, local knowledge (including in some cases Aboriginal and Traditional Knowledge), and biophysical analyses. The area may contain unsuitable or unoccupied habitats (see Appendix 6.2 for explanation of time frame for "Current").

4.2.2 Local Population:

A group of caribou occupying a de.ned area distinguished spatially from areas occupied by other groups of caribou. Local populations experience limited exchange of individuals with other groups, such that population dynamics are driven primarily by local factors affecting birth and death rates, rather than immigration or emigration among groups (see Appendix 6.2).

4.2.3 Habitat:

The suite of resources (food, shelter) and environmental conditions (abiotic variables such as temperature, and biotic variables such as competitors and predators) that determine the presence, survival, and reproduction of a population (Caughley and Gunn 1996).

4.2.4 Self-Sustaining:

A local population of boreal caribou that on average demonstrates stable or positive population growth (.= 1.0) over the short term, and is large enough to withstand stochastic events and persist over the long-term, without the need for ongoing intensive management intervention
(e.g. predator management or transplants from other populations).

4.2.5 Persistence:

The survival of a population expressed as a given probability or likelihood over a speci. ed time frame. The likelihood of not achieving speci.ed persistence levels is a measure of extinction risk. The IUCN criterion for classifying species as Vulnerable (equivalent to COSEWIC's Threatened category) is a risk of extinction =10% over 100 years (SSC 2001).

4.2.6 Range:

A geographic area occupied by individuals of a local population that are subjected to the same in.uences affecting vital rates over a de.ned time frame (see Appendix 6.2: Delineating Units of Analysis for Boreal Caribou Critical Habitat Identi.cation). Range is a function of both spatial extent and habitat conditions.

4.2.7 Critical Habitat:

The resources and environmental conditions (habitat as per Section 2.2.3) required for persistence of local populations of boreal caribou throughout their current distribution in Canada. The quantity, quality and spatial con.guration of resources and conditions may be in.uenced by both natural and human-induced factors.

4.3 Critical Habitat Identi.cation Framework for Boreal Caribou

A Critical Habitat Identi.cation Framework for Boreal Caribou (here referred to as the Framework) was developed to support a consolidated, scienti.cally defensible identi. cation of Critical Habitat for boreal caribou and a complementary Schedule of Studies. The Framework is not the sole product but rather a logic model to support the process. Development of the Framework was informed by Critical Habitat identi.cation approaches applied in Canada and elsewhere. Its systematic and transparent structure enables decision-analysis within the context of adaptive management. The approach was anchored by analysis and synthesis of available quantitative data and published scienti.c information of population and habitat ecology as well as boreal caribou population distribution, trends, habitat use, and conditions for persistence. Knowledge gaps and uncertainty are identi.ed throughout the process, and feed into a Schedule of Studies designed to improve knowledge and understanding of Critical Habitat over time. Aboriginal knowledge was not included in the present review, nor are needs speci.c to this body of knowledge included in the Schedule of Studies.

Development of the framework and the proposed Critical Habitat identi.cation were guided by the following set of principles:


4.3.1 Guiding Principles

1) Consider available published scienti.c information and seek multiple lines of evidence to support conclusions.
2) Recognize the need to address the dynamic nature of boreal systems, and the resultant effects on boreal caribou habitat.
3) Acknowledge and consider that the habitat requirements of this species operate at multiple spatial and temporal scales, including both physical and functional properties.
4) Recognize that variation in population structure, population and landscape condition, and state of knowledge may warrant different approaches to identifying Critical Habitat across the national distribution of this species.
5) Apply a precautionary approach when evidence suggests serious or irreversible harm, recognizing that absence of full scienti.c certainty should not be used as a reason to postpone decisions.
6) Consider the precautionary approach a provisional measure that requires follow-up activities such as research and monitoring to reduce signi. cant scienti.c uncertainty and improve decision-making.
7) Apply adaptive management to identify and reduce key uncertainties, and to achieve management objectives while gaining reliable knowledge.
8) Recognize that socio-economic considerations are not part of Critical Habitat identi.cation, but are appropriately considered in other phases of the overall SARA recovery planning process.

4.3.2 The Critical Habitat Identi. cation Framework

The Framework is used as a logic model to organize the acquisition and analysis of the best available knowledge to identify Critical Habitat, while recognizing uncertainty. Consistent with an adaptive management process, it is acknowledged that ongoing research and monitoring will provide new knowledge that can be used to re.ne the identi.cation of Critical Habitat over time. The Framework (see Figure 1) .ows from the following three major questions to be addressed in the identi.cation of Critical Habitat:

■ What is the current distribution of boreal caribou in Canada?
■ Where are the local populations within the current distribution of boreal caribou in Canada?
■ What conditions are required for long-term persistence of local populations of boreal caribou in Canada?

Identification of Critical Habitat is an outcome of these questions, such that:

Critical Habitat is comprised of the resources and environmental conditions required for persistence of local populations of boreal caribou throughout their current distribution in Canada. The quantity, quality and spatial con.guration of resources and conditions may be in.uenced by both natural and human-induced conditions.
Each component of the Framework (Figure 1) was informed by available quantitative data and published scienti.c information acquired or assembled as part of the Boreal Caribou Critical Habitat Science Review.

Each step in the framework is described below:

i) What is the current distribution of boreal caribou in Canada?

The recovery goal speci.es the geographic scope of boreal caribou recovery as the current distribution for the species. The current distribution of boreal caribou across Canada was described and mapped to de.ne the national spatial scope of Critical Habitat Identi.cation. Current distribution delineation was based on information provided by jurisdictions. Areas of uncertainty and needs for further assessment were identi.ed and included in the Schedule of Studies.


ii) Where are the local populations (or units of analysis) within the current distribution of boreal caribou in Canada?


The population objective of the Draft National Recovery Strategy speci.es local populations as the relevant unit of analysis for achieving the recovery goal. For the purposes of Critical Habitat identi.cation, the range associated with each local population was considered to be the unit of analysis. Several population patterns were recognized, and methods for range delineation varied according to the population pattern and the amount of animal location and movement data available. Areas of uncertainty regarding units of analysis were highlighted and included in the Schedule of Studies.

Figure 1: Critical Habitat Identi.cation Framework for Boreal Caribou

Figure 1: Critical Habitat Identi.cation Framework for Boreal Caribou

iii) What habitat conditions are required for long-term persistence of boreal caribou populations?


The recovery objective of self-sustaining populations is expressed quantitatively as the probability of a given set of habitat conditions supporting self-sustaining (persistent) local populations. Lower probability or certainty is generally associated with greater risk. While it is not the role of science to determine "acceptable" levels of risk, a science-based approach can be applied to explore a range of persistence parameters, given available knowledge. In the absence of scienti.c certainty, the identi.cation of Critical Habitat can thus be viewed as reflecting both our current state of understanding, and an explicit expression of risk, both of which should be evaluated and re.ned as new knowledge is generated.

iv) Critical Habitat Identi.cation

A central premise of the Framework is a de.nition of habitat that encompasses physical and functional attributes at a scale that is aligned with the goal of self-sustaining local populations. In this context "habitat" includes physical attributes (e.g. forage plants or thermal cover) used by caribou to carry out their life functions, as well as conditions (such as degree of natural and human disturbance) within the landscape mosaic that comprises the range of a local population. This approach addressed the in.uence of landscape conditions on mechanisms such as predation that affect short-term population trends and long-term persistence.


The Draft National Recovery strategy (Environment Canada 2007; see also Racey and Arsenault 2007) recognized that critical habitat for boreal caribou is appropriately conceptualized as caribou ranges and their components. Consistent with this recognition, Critical Habitat identi.cation within the framework focused on local population range as the scale at which habitat extent and conditions have the greatest in.uence on population persistence (see Section 2.5.2). The Critical Habitat Identi.cation framework incorporates the need for further re.nement of CH identi.cation where necessary for local populations.


v) Monitor, Adapt and Schedule of Studies

Because Critical Habitat for boreal caribou is not a .xed entity, but an emergent property of dynamic landscapes, a robust research and monitoring program is an important component of Critical Habitat identi.cation and management. New knowledge informs management actions that proceed with the best available information, gained through a structured process of adaptive management. Knowledge gaps and uncertainties are identi. ed, compiled, evaluated, and re.ected in a recommended Schedule of Studies. In the Schedule of Studies, emphasis is placed on the identi.cation of key uncertainties that prevent choosing between different conceptual models representing our understanding of what comprises Critical Habitat for boreal caribou.


Over time, understanding of the necessary conditions for persistence is improved by ensuring that Critical Habitat identi.cation is subject to evaluation and re.nement. Thus the adaptive management loop is fundamental to the question of "What is Critical Habitat?" and an essential component of the framework as a decision-analysis tool to re.ning what Critical Habitat is in the face of uncertainty.

4.4 Habitat and Persistence

Understanding the relationship between habitat selection and scale, and how this hierarchical approach is linked to persistence, is fundamental to the identi.cation of Critical Habitat for boreal caribou.

4.4.1 Habitat and Scale

In general, suitable boreal caribou habitat is characterized by large tracts of mature to old conifer forests with abundant lichens, or peatlands intermixed with uplands dominated by mature to old conifers (Darby and Pruitt 1984, Brown et al. 1986, Bradshaw et al. 1995, Stuart-Smith et al. 1997, Rettie and Messier 2000, Courtois 2003). However, there is variability among regions in vegetation types used.


Boreal caribou have habitat requirements at several spatial and temporal scales (Rettie and

Figure 2: Boreal caribou habitat exists at multiple spatial and temporal scales, and includes both physical and functional properties. The absolute magnitude of spatial and temporal scales for habitat may vary across the national distribution of boreal caribou.

TEMPORAL SCALE

Figure 2: Boreal caribou habitat exists at multiple spatial and temporal scales, and includes both physical and functional properties. The absolute magnitude of spatial and temporal scales for habitat may vary across the national distribution of boreal caribou.

Messier 2000, Johnson et al. 2001, O'Brien and Manseau 2003) as illustrated in Figure 2. Coarser scales encompass large areas (e.g. ranges) and broad time frames (e.g., seasons, years and decades), whereas .ner scales cover small areas (e.g., forest stands or habitat patches) and narrow time frames (e.g., hours and days). Boreal caribou select habitat to avoid predation at coarser scales (Bergerud 1988, Johnson et al. 2001) and then select habitat to meet forage requirements at .ner scales (Schaefer and Pruitt 1991, Rettie and Messier 2000).


At coarser scales, boreal caribou local populations require large range areas that contain suf.cient suitable habitat and reduce predation by allowing caribou to avoid areas of high predation risk (Rettie and Messier 2001, Brown et al. 2003). At .ner scales, boreal caribou select individual habitat patches (within ranges) that provide food, particularly ground and tree lichens during late winter and early spring, and they avoid early seral-stage forests and recently disturbed areas (Schaefer and Pruitt 1991, Stuart-Smith et al. 1997, Rettie and Messier 2000). Although forest .re destroys lichens and other vegetation in the short term, it is an important factor in regenerating caribou forage over long time scales (Dunford 2003). During winters with deep or crusted snow, boreal caribou require habitats that have shallower and uncrusted snow (such as in mature coniferous stands with closed canopies) and tree lichens to enable access to forage (Vandal and Barrette 1985, Thomas and Armbruster 1996).


In general, boreal caribou require habitats that provide necessary functional attributes (the conditions and resources that provide for all of their life requirements), including physiological health, dispersion of cows during calving and post-calving periods, and refuge from predation.

4.4.2 Scale and Persistence

There is increasing recognition within scienti.c and management communities that factors in.uencing caribou populations must be considered at regional scales (see Vistnes and Nellemann 2008 for a recent review). Changes in conditions that affect the number and distribution of alternative prey species and their associated predators, resulting in reduced habitat effectiveness for caribou, impact the viability of boreal caribou populations at the scale of their range. These changes are related to disturbances that increase the amount of early seral-stage forest, promote higher densities of prey species such as moose (Alces alces) and white-tailed deer (Odocoileus virginianus), which in turn support higher predator densities, especially of wolves (Canis lupus) (Bergerud and Elliott 1986; Seip 1992; Stuart-Smith et al. 1997, Racey and Armstrong 2000; Wittmer et al. 2005, 2007). The range of a given local population of caribou may contain a variety of habitat components that are differentially used by caribou, as well as the landscape matrix between these areas. Whether habitat components within a range are selected or avoided by caribou, all affect the viability of the population in positive or negative ways, thus are important when considering the conditions necessary for persistence.

Therefore, local population range is the relevant scale for the identi.cation of Critical Habitat to support self-sustaining local populations of boreal caribou, such that the range is a geographic area occupied by individuals of a local population that are subjected to the same in.uences affecting vital rates over a de.ned time frame. Range is a function of both spatial extent and habitat conditions. Extent refers to the physical area of the range and habitat conditions refer to the quantity, quality and spatial con.guration of resources (including the presence of other species) within the range. A more detailed discussion of the concept of range and methods of delineation is included in Appendix 6.2.

4.5 Scienti.c Undertakings to Support Application of the Framework

The large amount of scienti.c information that exists on boreal caribou in Canada facilitated the scienti.c review of Critical Habitat and identi.cation process. Relevant boreal caribou information was compiled, analyzed and synthesized to support the Framework (Figure 3).

Figure 3: Science components supporting the Critical Habitat Identi.cation Framework for Boreal Caribou

Figure 3: Science components supporting the Critical Habitat Identi.cation Framework for Boreal Caribou

The science activities were comprised of .ve main components presented as Appendices to the report, and summarized here: a habitat narrative, an environmental niche analysis (ENA), a meta-analysis of population and range condition, a non-spatial population viability analysis (PVA), and spatially-explicit population viability analysis. The habitat narrative summarized existing knowledge of boreal caribou habitat use and requirements across a variety of spatial and temporal scales, throughout their distribution in Canada. The other four components represent a spatial and analytical hierarchy of methods of decreasing generality and increasing complexity. The environmental niche analysis and range-wide meta-analysis provided top-level information, followed by the non-spatial PVA, and .nally the spatial PVA. Results from top-level analyses reveal overarching constraints on processes that can be examined at lower levels; lower-level results suggest factors missing from the top-level analyses, and completing the learning cycle, top-level analyses suggest the extent to which conclusions from the lower-level results may lack generality. These components informed the Critical Habitat identi.cation process by feeding into a Critical Habitat Decision Tree (introduced in Section 2.6).

4.5.1 Habitat Narrative (Appendix 6.3)


The habitat narrative provided a description of boreal caribou habitat, including spatial and temporal aspects of biophysical attributes used throughout the species' life cycle, and considered both physical and functional characteristics of the habitat. This work summarized the primary and grey literature pertaining to caribou habitat use across the current distribution. Boreal caribou habitat-use information was extensive in some regions and quite limited elsewhere. The narrative informed the environmental niche analysis through identi.cation of variables in.uencing the extent of occurrence, and potential areas of occupancy, of boreal caribou throughout their distribution. The narrative also provided detailed information to augment understanding of components of Critical Habitat that vary among and within local population ranges. The information is organized by ecological regions.

4.5.2 Environmental Niche Analysis (Appendix 6.4)

The environmental niche analysis was a tool to enhance understanding of the historic and current geographic distribution of boreal caribou, and patterns of occupancy, relative to abiotic and biotic factors. The ENA used abiotic factors (climate and topography) to characterize the potential distribution of observed boreal caribou locations, and then incorporated broad-scale biotic variables (land cover and human impact levels) to predict the pattern of occupancy within the current extent of occurrence. The ENA supports the Framework and associated decision-analysis by identifying areas of uncertainty and generating hypotheses about limiting factors, which guide sampling and re.nement efforts identi.ed in the Schedule of Studies. The results also identify areas supporting potentially suitable conditions for habitat restoration adjacent to current ranges, or potential corridors of movement between ranges.

4.5.3 Meta-Analysis of Population and Range Condition (Appendix 6.5)

A key element of the Critical Habitat Framework is determining attributes of a caribou range that support or compromise population persistence (e.g. the ability of the range to support a self-sustaining population). The meta-analysis compiled demographic data from boreal caribou populations across Canada to evaluate the hypothesized relationship between caribou population parameters (index of population condition) and levels of anthropogenic and/or natural (.re) disturbance on caribou ranges (index of range condition). Natural disturbances could also include insect outbreaks and their stand-level effects associated with climate change projections that may in fact result in a .re disturbance, however insect disturbances were not directly considered in this analysis. Results from the meta-analysis provided quantitative guidelines for one of the three assessment criteria (e.g. range condition) used in the evaluation of local populations for Critical Habitat identi.cation (see Section 2.6.3 and 2.6.4). 12

4.5.4 Non-Spatial Population Viability Analysis (Appendix 6.6)

The Critical Habitat Framework requires information on population persistence. The non-spatial PVA evaluated how population persistence is affected by aspects of boreal caribou life history and population age and sex structure, using the range of published population vital rates and their variance for boreal caribou across Canada. Results of this work provided quantitative guidelines for the population size required for persistence under various demographic conditions, the second of three criteria assessed in Critical Habitat identi.cation (see Sections 2.6.3 and 2.6.4), and informed the spatially-explicit PVA by providing information on the vital rates that most in.uence population dynamics of boreal caribou.

4.5.5 Spatially-explicit Population Viability Analysis (Appendix 6.7)

Spatially explicit population models have many more parameters and computational demands than a non-spatial PVA, such as simulating a dynamic landscape over time, and thus can explore only a subset of the parameter space for local populations. Spatial PVA adds consideration of landscape structure and individual movement, and when results are compared with a non-spatial PVA, helps assess whether spatial effects produce different predictions of population persistence. Application of spatial PVA can also help interpret results of the meta-analysis by offering heuristic insights of the mechanisms by which the ability of an area to support caribou scales up spatially from the scale of patch to the scale of landscape (range), and allows simulation of longer-term trends and scenarios to extrapolate relationships to future landscapes. The work completed as part of this review was a proof of concept for applications of methods exploring how landscape condition affects boreal caribou population persistence for two case study populations. Further elaboration of Critical Habitat outcomes at spatial scales .ner than range, over speci.ed time frames, can be achieved through spatially explicit population viability analysis linked with dynamic landscape modelling.

4.6 Decision Analysis to Support Identi.cation of Critical Habitat

As concluded in Section 2.4.2, local population range (including extent and habitat conditions) is the relevant scale for the identi.cation of Critical Habitat to support self-sustaining local populations of boreal caribou. The identi.cation of CH requires an understanding of the ability of existing habitat (with respect to extent and condition), to support self-sustaining local populations of boreal caribou. Expanding on the Critical Habitat Framework (Figures 1 and 3), the Critical Habitat Decision Tree (herein referred to as Decision Tree; Figure 4), is a more detailed decision analysis tool. The Decision Tree outlines the logical sequence of steps necessary for the identi.cation of CH for boreal caribou, considering the variability and uncertainty associated with ecological processes operating at the scale of local population ranges. The Decision Tree represents the alternatives available, the associated uncertainty, and the evaluation measures applied to support identi.cation. Where possible, uncertainties were represented through probabilities (see Sections 2.6.4 and 2.6.5) and knowledge gaps were directed to a Schedule of Studies. The process of CH identi.cation was framed as an exercise in adaptive management, integrating research and monitoring in a cycle of evaluation that addresses knowledge gaps and key uncertainties, and incorporates new knowledge to re.ne the identi.cation of Critical Habitat over time.

Figure 4: Boreal Canibou Critical Habitat Decision Tree

Steps in the Decision Tree are described below.


4.6.1 Identify Current Distribution

The recovery goal for boreal caribou speci.es the geographic scope as the current distribution for the species. Boreal caribou are distributed in the boreal forest across seven ecozones, including nine provinces and territories, from the Yukon Territory in the west, to Labrador in the east, and extending as far south as Lake Superior1. Figure 5 illustrates the current distribution of boreal caribou as depicted in the Draft National Recovery Strategy, based on information provided by jurisdictions. This geographic extent was used in the present Boreal Caribou Critical Habitat Identi.cation Framework and Decision Tree.
The current distribution (extent of occurrence) is subject to revision with new knowledge, and standard methods should be applied across the extent to ensure consistency in representation of understanding. The Environmental Niche Analysis (Appendix 6.4) can be used to identify areas of uncertainty based on available abiotic and biotic data, and therefore guide sampling efforts to re.ne understanding (model-based sampling), as part of the Schedule of Studies. Revisions are re.ected in the Decision Tree as adjustments to future assessments, as part of the adaptive management loop.

4.6.2 Determine Local Population Range (Units of Analysis)

Application of the Decision Tree required delineation of local populations and their associated ranges. It was recognized that populations often function demographically at scales that are different from those suggested by genetic indicators (e.g. Esler et al. 2006; see Appendix 6.2 for further detail). Demographically de.ned local populations are the appropriate population unit for Critical Habitat identi.cation to address the National Recovery strategy objective of self-sustaining local populations.


Local populations were de.ned as a group of caribou occupying an area distinguished spatially from areas occupied by other groups. Local populations experience limited exchange of individuals with other groups, such that population dynamics are driven by local factors affecting birth and death rates, rather than immigration or emigration among groups. Ecological conditions, as well as patterns and intensity of anthropogenic disturbance, vary tremendously across the national distribution for boreal caribou in Canada, resulting in variation in local population patterns. Some local populations may be spatially discrete and experience little or no exchange of individuals; other local populations may exist as part of a broader, continuous distribution where periodic exchange of individuals may be greater. Alternatively, a local population could occupy a large continuous distribution where regular exchange of individuals occurs.


1 Boreal caribou on the island of Newfoundland are excluded from this Report and the National Recovery Strategy because the insular Newfoundland population has been designated Not at Risk by COSEWIC.

Figure 5: The current distuibution of boreal Ganibou in Canada

Three local population patterns for boreal caribou were recognized:


1) Discrete local population with spatially discrete ranges

2) Multiple local populations within a large area of relatively continuous habitat

3) Single large local population across a large area of relatively continuous habitat


Movement data can be used to determine immigration and emigration rates and assess population patterns of boreal caribou (Bethke et al. 1996, McLoughlin et al. 2002). However, many regions lack suf.cient data covering an adequate time period to assess immigration/ emigration rates for the purpose of determining spatial population structure. In the absence of suf.cient immigration/emigration data, available animal movement/survey data and the degree of geographic separation of area of occupancy can be used to suggest the most plausible local population pattern for boreal caribou (see Schaefer et al. 2001, Courtois et al. 2007). Uncertainty should be addressed through a Schedule of Studies and resultant adjustments should be made to local population identi.cation and associated unit of analysis over time.


Where natural geographic boundaries and/or habitat alteration have resulted in discrete local populations, and range boundaries were delineated based on animal movement data and forest dynamics data, resultant local population and associated range were identi.ed as the unit of analysis for purposes of Critical Habitat identi.cation.


Where caribou local populations are not restricted by natural geographic boundaries or habitat alteration and are distributed across large areas of relatively continuous habitat, and animal movement data are not available, the delineation of range for local populations is more dif.cult. The draft National Recovery Strategy (Environment Canada 2007) speci. es a Population and Distribution Objective of self-sustaining boreal caribou populations throughout the current distribution (extent of occurrence) in Canada (see Section 2.1.2). Hence, for continuous distributions within which local populations were not identi.ed, the extent of occurrence was considered the range for the present assessment. For future evaluations, Appendix 6.2 provides potential criteria for subdividing large areas of continuous habitat into local population ranges based on animal movement and/or survey data and ecological criteria. Where studies have shown that large areas of relatively continuous habitat are occupied by one local population (> than 10% emigration and immigration among groups of animals) the extent of occurrence can be divided into contiguous sub-sample units in order to ensure that the mean condition does not mask variation that may occur across the range.


Local population ranges identi.ed by jurisdictions were used in the present application of the Decision Tree. Figure 6 depicts the resulting units of analysis. Several jurisdictions with extensive areas of continuous habitat have not yet completed the process of local population delineation and therefore only provided extent of occurrence of boreal caribou for the continuous distribution area within the jurisdictional boundaries. The identi.cation of local populations and associated range within large continuous distribution areas is a high priority, as identi.ed in the Schedule of Studies. When completed, the proposed Critical Habitat for these units should be re-evaluated.

Figure 6: Boreal Caribou Local Populations and Units of Analysis for Critical Habitat Identi.cation

Figure 6: Boreal Caribou Local Populations and Units of Analysis for Critical Habitat Identi.cation

Of the 57 recognized units of analysis assessed in this report, 39 represent discrete local populations and are referenced as "local populations" in the following .gures and tables. Of the remaining units of analysis, 6 units in NWT resulted from subdivision of a large area of relatively continuous habitat considered to be occupied by one large population into recognized management units; 8 units in Saskatchewan represent multiple local populations and recognized management units within an area of relatively continuous habitat. The remaining 4 units of analysis found in parts of Manitoba, Ontario, Quebec and Labrador may include multiple local populations within a large area of relatively continuous habitat. In the absence of de.ned local populations or units of analysis for these areas, the extent of occurrence was used as the analysis unit.

4.6.3 Population and Habitat Assessment

Having identi.ed local populations or units of analysis and associated ranges, the next step in the Decision Tree was the identi.cation and assessment of measurable criteria of population and habitat status for each local population range. The recovery goal (and population objective) is self-sustaining local populations, here interpreted as the probability of persistence. Three measurable criteria related to persistence probability were assessed:


Population Trend: an indicator of whether a population is self-sustaining over a relatively short measurement period (approximately 3-5 years). Four qualitative states were recognized: stable, increasing, declining and unknown. Information on trend of local populations was provided by the jurisdictions in Appendix 1 of the Draft National Recovery Strategy. Updates were solicited as part of this review (see Appendix 6.8). Development of standards for measurement of this criterion is identi.ed within the Schedule of Studies.


Population Size: an indicator of the ability of a population to withstand stochastic events and persist over the long-term. Results from the non-spatial population viability analysis (PVA) were used to derive empirical guidelines for size categories (states) related to probability of persistence (see Section 2.6.4.2 Population Size and Appendix 6.6). Three states were recognized in this review: very small (< 50), small (=50 and =300), and above critical (>300). Information on size of local populations was provided by the jurisdictions in Appendix 1 of the Draft National Recovery Strategy. Updates were solicited as part of this review (see Appendix 6.8). Development of standards for measurement of this criterion is identi.ed within the Schedule of Studies.


Range Disturbance: an indicator of the ability of a range to support a self-sustaining population. Results from a meta-analysis of demography and range disturbance (see Appendix 6.5) were used to derive empirical categories (states) for percent total range disturbance (anthropogenic and .re) related to demographic response (see Section 2.6.4.3 Range Disturbance). Five states were recognized in this review: very low, low, moderate, high and very high. Information on total range disturbance of local populations was measured from independent, national-scale data sources, consistent with methods applied in the meta-analysis.

Additional criteria were considered during the review, particularly measures of range condition in addition to disturbance. The amount, quality and spatial distribution of habitat components essential to caribou, such as winter and summer range, and calving and post-calving areas, also in.uence the ability of a range to support a self-sustaining population. Partitioning disturbance into natural and anthropogenic components, characterized by type, severity and distribution relative to habitat components could also help to re. ne evaluations. Other types of disturbances that cannot be readily extracted from maps can also in.uence range condition. However, access to readily available, standardized data on which to base a national assessment was a limiting factor in the current review. Development of a comprehensive Decision Tree and associated analyses are identi.ed in the Schedule of Studies. Supplementary information (e.g. new knowledge) can also augment Critical Habitat identi.cation through the adaptive management process.

4.6.4 Determination of States for Assessment Criteria

The population and habitat assessment criteria: population trend, population size and range disturbance, represent three lines of evidence used to evaluate local population ranges relative to their potential to support self-sustaining populations. This section describes the methods used to determine the states of assessment criteria.


4.6.4.1 Population Trend

The recognized states of population trend used in the Decision Tree and associated analyses were not rationalized beyond a literal interpretation of the trend state. For example, a population exhibiting a declining trend over a given measurement interval is, by de.nition, not self-sustaining, and thus has a low probability of persisting given continued decline. Alternatively, a stable or increasing population is, by de.nition, self-sustaining over the measurement interval, and has a moderate to high probability of persisting given continued stability or growth. Where trend was assigned a state of unknown, the population was considered to have an equal likelihood of being either self-sustaining or not, and thus may or may not persist (Table 1).


Table 1: Population trend states with corresponding values of population growth and assigned probability of persistence.

Trend State Lamba (.) Prob. Persistence
Declining 0≤.98 0.1
Stable 0.99 to 1.01 0.7
Increasing > 1.01 0.9
Unknown -------­ 0.5

4.6.4.2 Population Size

Small populations face a high risk of extinction due to demographic stochasticity, Allee effects and emigration (Levins 1970, Shafer and Samson 1985). The situation is exacerbated when populations become isolated (Harris 1984, Belovsky et al. 1994), as is the case for most small caribou populations in Canada, due to human-caused range loss.

The non-spatial population viability analysis (PVA; Appendix 6.6) suggested that, under good demographic conditions (e.g. relatively high adult female and calf survival; Scenario 75th Percentile, Table 2), a population size of 50 had a ~10% chance of quasi extinction, within 100 years, de.ned as the probability of declining to a population size of 10 animals or fewer (Figure 7). This analysis further suggested that a population of 300 with moderate calf and adult female survival (MHMM, Table 2) had a 10% probability of quasi-extinction. Finally, large populations (=300) had a high probability of persistence under favourable demographic conditions; however, no population size was suf.cient to buffer against poor demographic conditions (low calf survival, moderate adult female survival; LHMM, Table 2; Figure 7).


Table 2. Scenario parameter values to assess population size thresholds of boreal caribou for population assessment and identi.cation of Critical Habitat, based on calf and adult female survival (S) and variation (CV = coef.cient of variation).

 
Scenario Description of Scenario Calf
Survival
(Scalf)
CV1 Calf
Survival
Scalf CV
Adult
Female
Survival
(Sad)
CV Adult
Female
Survival
(Sad CV)
LHMM Low Scalf; High CV of Scalf;
Mean Sad, Mean CV of Sad
0.17 64% 0.85 8%
MHMM Mean Scalf; High CV of Scalf;
Mean Sad, Mean CV of Sad
0.38 64% 0.85 8%
75th Percentile 75thP_Scalf, 75thP_CV of Scalf;
75thP_Sad, 75thP_CV of Sad
0.44 51% 0.88 15%

 

Figure 7. The effect of population size on risk of quasi-extinction under various survival rates for boreal caribou adult females and calves. Quasi-extinction is de.ned as the risk of the population declining to 10 animals or less over 100 yrs.

Figure 7. The effect of population size on risk of quasi-extinction under various survival rates for boreal caribou adult females and calves. Quasi-extinction is de.ned as the risk of the population declining to 10 animals or less over 100 yrs.


While some small populations may persist for long periods, and perhaps even expand depending on range conditions (e.g., Krausman et al. 1993, Wehausen 1999), there is general agreement that they usually require special management interventions to do so (Krausman and Leopold 1986, Krausman et al. 1993, Wehausen 1999). Further, there is usually a long lag period (two decades or more) between a population declining below a critical threshold and eventual extirpation (Tillman et al. 1994, Vors et al. 2007), and the period over which trend data for caribou populations are available is often less than the probability period associated with the most likely range perturbation under natural conditions (e.g., fire).


Therefore, the population assessment component of Critical Habitat identi. cation recognized that very small populations (<50) are vulnerable to stochastic events and phenomena, resulting in an especially low probability of persistence, whereas local populations of >50 but <300 caribou are less vulnerable but are still at risk of quasi-extinction, and populations greater than 300 can persist inde.nitely when range conditions support average adult female and calf survival. However, no population size was adequate to buffer against poor demographic conditions. Three states with corresponding population sizes and persistence probabilities were thus considered in this component of the population assessment (Table 3).

Table 3. Population size states derived from a non-spatial population viability analysis (Appendix 5.6), with corresponding population sizes and probability of persistence.

 
Population State Population Sizep Prob. Persistence
Very Smallage < 50 0.1
Small 50 - 300 0.3
Above Critical > 300 0.5 / 0.9*
Unknown ---------- 0.5

* Declining or unknown, P=0.5; poor demographic or reference conditions
Stable or increasing, P=0.9


Given that the PVA did not include senescence (e.g. no constraints on maximum breeding age and maximum age), nor significant sources of environmental stochasticity, such as that caused by .re events, the population size thresholds could be considered liberal (e.g. conferring a greater probability of persistence than may be realized). However, the PVA
also only modeled single, closed populations (e.g. no immigration or emigration). This is a reasonable assumption for very small populations and for discrete small populations. Nevertheless, where the potential for immigration exists, extinction risk may be moderated through rescue effects.

4.6.4.3 Range Disturbance

The national meta-analysis of caribou demography and range disturbance (Appendix 6.5) revealed a negative relationship between recruitment rate, as re.ected in the ratio of calves to adult females in late winter population surveys, and the level of range disturbance. The percentage of the range disturbed by a non-overlapping measure of total area burned and disturbed by anthropogenic activities explained 61% of the variation in mean recruitment rates across 24 boreal caribou populations. For populations of caribou to be self-sustaining, population growth rates must be either stable or increasing. Population growth rate (.) is a function of recruitment (R) and adult survival (S), such that . = S / (1 - R) (adapted from Hatter and Bergerud 1991). Thus for . to be = 1.0 (stable or increasing), R must be ≥ S.


The non-spatial PVA reported mean annual female survival as 85%, based on a review of boreal caribou studies from across Canada. With this adult female survival rate, a recruitment rate of 15% female calves into the total population is required for a stable population, or . = 1.0, which is interpreted here as the condition necessary for a self-sustaining or persistent population. To achieve 15% female calves in a total population of 100 animals, assuming an equal sex ratio among calves, 14% yearlings in the population, an estimated 61% females in the adult population, and an average parturition rate of 0.76 (% yearlings, adult sex ratio and parturition rate from non-spatial PVA, see Appendix 6.6), a minimum recruitment rate of 28.9 calves/100 females is required. The non-spatial PVA suggested a positive probability of population persistence above this value, under a moderate female survival scenario, and given population size above critical (> 300 animals). Bergerud (1992) also reported that 27.7 calves/100 cows yielded a . value of 1 based on 32 herd determinations (population survey years) of barren-ground and woodland caribou. Clearly, the appropriateness of a 15% target and associated calf to cow ratio depends on the actual survival of adult females in a given population. However, the minimum recruitment rate or threshold of 28.9 calves/100 females provided a guideline for evaluating the probability of persistence (e.g. the ability of the range to support a self-sustaining population) of local populations associated with varying levels of range disturbance, for use in the habitat assessment component of the Decision Tree.

The results of the meta-analysis were extrapolated to predict persistence probability at varying levels of total range disturbance for individual local populations. To achieve this, it was necessary to account for the uncertainty of the measured response (the estimated empirical relationship based on sampled populations) and the predicted response (the expected value for a new observation). The uncertainty of the predicted response must be included if the interval used to summarize the prediction result is to contain the new observation with the speci. ed con.dence. As with conventional con.dence intervals, which quantify the certainty around the estimated empirical relationship, a probabilistic interval is used when predicting a new observation. To distinguish the types of prediction, however, the later probabilities are termed prediction intervals. Prediction intervals around the threshold recruitment value of 28.9 calves/100 cows were used to derive the disturbance states used in habitat assessment (Figure 8).

Figure 8. Disturbance states derived from the prediction intervals (PI) for the relationship between total range disturbance and boreal caribou recruitment, based on a recruitment threshold of 28.9 calves/100 cows (15% calves in total population).

Figure 8. Disturbance states derived from the prediction intervals (PI) for the relationship between total range disturbance and boreal caribou recruitment, based on a recruitment threshold of 28.9 calves/100 cows (15% calves in total population).

The lower and upper bounds of the 50%, 70% and 90% prediction intervals de.ned 5 states of disturbance: very low, low, moderate, high, and very high, corresponding to values of total disturbance associated with varying levels of persistence probability (Table 4).


Table 4. Disturbance states derived from the meta-analysis of caribou demography and range disturbance (Appendix 5.5), with corresponding values of total disturbance (% anthropogenic and burned), and persistence probability, based on recruitment threshold of 28.9 calves/100 cows for a stable population.

 
Disturbance State Total Disturbance Prob. Persistence
Very Low ≤15% 0.9
Low 16 - 23% 0.7
Moderate 24 - 49% 0.5
High 50 - 58% 0.3
Very High ≥59% 0.1

While total disturbance was used to assess disturbance state for purposes of assigning persistence probability, results from the meta-analysis indicated that most of the explained variance in recruitment was attributed to the anthropogenic component of the total disturbance measure. Thus, when total disturbance was moderate or above, but the majority of the disturbance was attributed to .re, a local population range might be expected to support a higher probability of persistence than suggested by the composite measure.

4.6.5 Integrated Probability Assignments to Local Population Ranges

Once the states of individual assessment criteria were assigned to local populations of boreal caribou, the next step in the Decision Tree integrated these criteria to assign a relative probability of population persistence to each local population range. The alternative hypotheses or outcomes evaluated at the local population level were:

RNSS (Range Not Self-Sustaining): current range conditions and/or extent are not adequate to
support a self-sustaining population; probability of persistence is low.

RSS (Range Self-Sustaining): current range conditions and extent are adequate to support a
self-sustaining population; probability of persistence is moderate to high.

The Decision Tree provided a systematic means to evaluate the probability of persistence for a local population given its observed state of population trend, population size, and range disturbance. Whether states of the three criteria were known or unknown, a "prior probability" (prior) was assigned to each criterion as an expression of available quantitative data and published scienti.c information. A prior, which varies between 0 and 1, is an inferred probability that a hypothesis is correct, or the plausibility of an outcome given incomplete knowledge. When a state is unknown, a reference prior is assigned. This is functionally equivalent to the inferred probability of alternate hypotheses, or plausibility of different outcomes, being equal.

Assignment of prior probabilities to possible states of each criterion was based on inferred persistence probability (population trend), the statistical distribution of simulation results related directly to persistence probability (population size), and a combination of measurement and prediction uncertainty from the statistical properties of the recruitment-disturbance relationship (range disturbance). Determination of the states was described in the previous section (2.6.4). The assignment of prior probabilities re.ects the probability of an observed state supporting a self-sustaining (SS) local population, given available information.


A conditional probability table for the joint distribution of criteria states was generated by averaging the individual, or marginal, priors to derive an integrated prior probability assignment for each combination set (Table 5). Integrated priors represent the prior probability distribution for the hypotheses RNSS and RSS. The variable SSƒR (probability of local population being self-sustaining given current range condition) is continuous from 0 to 1, with values ≤ 0.4 indicating the weight of evidence supports RNSS, 0.5 placing equal weight on RNSS and RSS (specific conditions are evaluated to aid interpretation), and ≥ 0.6 supporting RSS.


Table 5. Example portion of conditional probability table for the joint distribution of criteria states, with integrated prior probability assignments. SSƒR is the probability of a local population being self-sustaining, given present range and population conditions (See Appendix 6.8 for the complete table).

 
Trend Size Disturbance SSƒR Range
Assessment
Declining 0.1 Very Small 0.1 Very High 0.1 0.1 RNSS
    High 0.3 0.2 RNSS
    Moderate 0.5 0.2 RNSS
    Low 0.7 0.3 RNSS
    Very Low 0.9 0.4 RNSS
Stable 0.7 Small 0.3 Very High 0.1 0.4 RNSS
    High 0.3 0.4 RNSS
    Moderate 0.5 0.5 RSS/RNSS
    Low 0.7 0.6 RSS
    Very Low 0.9 0.6 RSS
Increasing 0.9 Above Critical 0.9 Very High 0.1 0.6 RSS
    High 0.3 0.7 RSS
    Moderate 0.5 0.8 RSS
    Low 0.7 0.8 RSS
    Very Low 0.9 0.9 RSS

The result of the integrated assessment was assignment of a probabilistic outcome to each local population or unit of analysis, based on the weight of evidence supporting a conclusion of self-sustaining or not self-sustaining given current range conditions and extent.

2.6.6 Proposed Identi.cation of Critical Habitat


The final step in the Decision Tree is the proposed identi.cation of Critical Habitat, based on the probability of the current range supporting a self-sustaining local population (see Section 2.6.5). Critical Habitat Identi.cation is expressed relative to the current range condition and extent for each local population or unit of analysis. Condition and extent determine the functional attributes of the range. Three Critical Habitat outcomes were considered, based on interpretation of the integrated and individual probability assignments and associated weight of evidence for range self-sustaining (Rss) or not self-sustaining (RNSS). The outcomes were:

■ Current Range -current range condition and extent are required to maintain potential for self-sustaining population.

■ Current Range and Consider Resilience - current range condition and extent may be suf.cient to absorb additional disturbance while maintaining capacity to support a self-sustaining population.

■ Current Range and Improved Conditions - current range condition and/or extent would need to be improved to restore potential to support a self-sustaining population.

The following decision rules were applied in the proposed identi.cation of Critical Habitat for each local population or unit of analysis.

■ Where range assignment was self-sustaining (RSS), based on weight of evidence from the integrated assessment (p≥0.6): .

□ If local populations or units of analysis were de.ned and all criteria had known states, proposed Critical Habitat was identi.ed as "Current Range and Consider Resilience".

□ If local populations or units of analysis were not de.ned for large areas of continuous habitat or if both population criteria (trend and size) were unknown, proposed Critical Habitat was identi.ed as "Current Range", with a note that population delineation and/or data were necessary before potential resilience could be evaluated.

□ If population trend was unknown and population size was small or very small proposed Critical Habitat was identified as "Current Range", with a note to address data gap.

□ If population trend was unknown and population size was above critical, proposed Critical Habitat was identified as "Current Range and Consider Resilience", with a note to address data gap.

■ Where range assignment was not self-sustaining (RNSS), based on weight of evidence from the integrated assessment (p≤0.4):

□ If level of total disturbance was very low or low, proposed Critical Habitat was identi.ed as "Current Range", with a note to investigate other measures of habitat condition, non-habitat stressors and consider range extent, as appropriate.

□ If level of total disturbance was moderate, high or very high and trend was stable, proposed Critical Habitat was identified as "Current Range", with a note to closely monitor trend.

□ If level of total disturbance was moderate, high or very high and population trend was declining, proposed Critical Habitat was identi.ed as "Current Range and Improved Conditions".

□ If population trend was unknown and total disturbance was moderate or total disturbance was high or very high with the anthropogenic component of disturbance low or very low, proposed Critical Habitat was identi.ed as "Current Range", with a note to address data gap.

□ If population trend was unknown and total disturbance was high or very high with anthropogenic component moderate or above, proposed Critical Habitat was identi.ed as "Current Range and Improved Conditions", with a note to address data gap.

Where range assignment was (RSS/RNSS), based on equal weight of evidence from the integrated assessment (p=0.5):

□ Proposed Critical Habitat was identifi ed as "Current Range"

□ If one or more of the criteria for the integrated assessment was unknown, addressing information gaps is indicated.

□ If all criteria states were known, situation was considered marginal; close monitoring of situation is recommended.

Where proposed Critical Habitat is identi.ed as being "Current Range and Improved Conditions" or "Current Range and Consider Resilience", this does not imply that Critical Habitat is unknown or un-identi.able. Rather, based on the current methodology, associated assumptions and data used, Critical Habitat is proposed as the Current Range, with direction on additional considerations necessary to re.ne the assessment. Ultimately, to meet the full requirement of "habitat that is necessary for the survival or recovery" (SARA S.2(1)), improved conditions and/or increased extent may be required (Current Range and Improved Conditions), or the Current Range could absorb additional disturbance without compromising persistence of the local population (Current Range and Consider Resilience).

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