Grizzly Bear DNA Inventory of the Prophet River Territory, Northeastern British Columbia

GRIZZLY BEAR INVENTORY OF THE PROPHET RIVER AREA, NORTHEASTERN BRITISH COLUMBIA

Submitted to:

Prophet River Indian Band Dene Tsaa First Nation Box 3250, Fort Nelson, BC V0C 1R0

Canadian Forest Products Ltd. Chetwynd Division P.O. Box 180, Chetwynd, BC V0C 1J0

B.C. Ministry of Environment, Lands and Parks Fish and Wildlife Branch, Peace Subregion Rm 400, 10003 110th Street, Fort St. John, BC V1J 6M7

Prepared by:

K. G. Poole, G. Mowat, and D. A. Fear Timberland Consultants Ltd. Fish and Wildlife Division P. O. Box 171 (2620 Granite Rd.) Nelson, BC V1L 5P9 Tele.: (250) 354-3880 e-mail: [email protected]

December 1999

Prophet River Wildlife Inventory Report No. 10 Prophet River grizzly bear inventory ii

ABSTRACT Current harvest management of grizzly bears (Ursus arctos) in British Columbia (B.C.) is based primarily on modeling of habitat capability/suitability. No research has been conducted in the northern half of the province to verify these habitat-based estimates. In reaction to concerns from First Nation peoples, outfitters and government managers about grizzly bear population size in northeastern B.C., a DNA-based mark-recapture inventory was conducted in the Prophet River area. The study area covered 8,527 km2, and stretched from the continental divide of the northern Rocky Mountains in the west to the boreal plains in the east. The area included the Northern Boreal Mountains and Taiga Plains ecoprovinces, and the Alpine Tundra, Spruce- Willow-Birch, and Boreal White and Black Spruce biogeoclimatic zones. Fieldwork was conducted between 25 May and 1 August 1998 using a helicopter and a truck with an all terrain vehicle. The study area was divided into a grid of 103 9 x 9 km (81 km2) cells. Bait sites consisted of fish rotted to a liquid and rotten beef blood poured on a mound of sticks, branches, stumps and moss placed in the centre of a site. The site was encircled by 20-30 m of barbed wire strung at 50 cm height around 3 or more trees. Sites were left for 12 days, then moved >1 km from all previous sites to a new site within each cell. Five sites were placed sequentially in all cells, resulting in 515 capture sites. We collected 2,062 hair samples from 332 sites. After sorting to remove identifiable black bear (U. americanus) samples and samples with no roots, we ran genetic species tests on 1,139 samples. We identified 544 grizzly samples, 453 black bear samples, 1 sample with hair from both bear species, 25 wolf (Canis lupus) samples, and obtained 116 tests which failed due to insufficient DNA or because they were not bear or wolf. We detected grizzly bears at 113 sites. DNA fingerprinting of grizzly bear samples identified 104 different bears; 48 of these individuals were females, 49 were males, and the remaining 7 individuals could not be sexed. Thirty-eight grizzly bears were caught at >1 site. We used Darroch's closed mark-recapture model (Mt-Darroch) to obtain a naïve population estimate for our study area of 169 grizzly bears [95% confidence interval (CI) 140-212]. We reduced this estimate by 6% to account for closure bias, which resulted in an adjusted population estimate of 159 grizzly bears (95% CI 130-202 or ± 23% of the mean) within the study area (19 bears/1,000 km2). We also estimated population size and density within the 2 broad biophysical provinces in the study area: corrected for closure the Northern Boreal Mountains in the western one-third of the study area contained 106 grizzly bears [(95% CI 84-141), 35 bears/1,000 km2] and the Taiga Plains in the eastern two-thirds contained 56 grizzly bears [(95% CI 38-100), 10 bears/1,000 km2]. Sex cohorts of bears (single males, single females and family groups) appeared to be distributed throughout the study area, and there was no evidence of clustering of bears around the study area border. The current habitat-based capability ratings for grizzly bears in the boreal ecoprovinces of B.C. are supported by our results in the Taiga Plains, but are lower than densities we obtained in the Northern Boreal Mountains by more than half. Additional DNA-based mark-recapture studies of grizzly bears in other locations in the northern boreal portion of B.C. should be conducted to provide comparative data to this study. Capture success during this study would suggest that future users of this technique could use fewer capture sessions and still achieve adequate precision for management requirements.

Timberland Consultants Ltd. Prophet River grizzly bear inventory iii

TABLE OF CONTENTS

ABSTRACT...... ii TABLE OF CONTENTS...... iii LIST OF FIGURES ...... iv LIST OF TABLES...... iv INTRODUCTION ...... 1 STUDY AREA ...... 1 METHODS ...... 3 Survey design...... 3 Field methods...... 4 DNA analysis...... 5 Data Analysis...... 6 RESULTS ...... 6 Hair collection and analysis...... 6 Population size...... 9 Effects of habitat on population density ...... 11 Bear movements...... 12 DISCUSSION...... 12 MANAGEMENT RECOMMENDATIONS...... 16 ACKNOWLEDGEMENTS...... 17 LITERATURE CITED ...... 17 APPENDIX 1. Results of Goodness of Fit tests from CAPTURE for the Prophet River grizzly bear inventory, summer 1998...... 20

Timberland Consultants Ltd. Prophet River grizzly bear inventory iv

LIST OF FIGURES

Figure 1. Prophet River grizzly bear DNA inventory study area, grid cells and site locations, 1998. Sites that captured grizzly bears are shown in solid circles, sites that did not are shown in open circles. Numbers refer to cell numbers...... 2 Figure 2. Location of black bear captures in the Prophet River grizzly bear DNA inventory study, 1998. Sites that captured black bears are shown in solid circles, sites that did not are shown in open circles...... 8 Figure 3. The total number of grizzly bears captured per trapping session, the number of new bears captured per session, and the proportion of captured bears which were new bears in each of 5 capture sessions on the Prophet River study area, 1998...... 10

LIST OF TABLES

Table 1. Grizzly bear hair capture results from the Prophet River grizzly bear DNA inventory, 1998. One hundred and three cells were sampled during each capture session...... 7 Table 2. Hair sorting identification checked by DNA species identification, Prophet River grizzly bear inventory, 1998...... 9 Table 3. Grizzly bear population estimates from 8 closed mark-recapture models in program CAPTURE from DNA analysis of hair collected at bait sites during summer 1998 for the Prophet River area...... 10 Table 4. The relationship between grizzly bear detection rate and ecosystem, topographic and habitat variables, Prophet River area, 1998...... 11 Table 5. Distance moved (km) among recaptured grizzly bears by ecoprovince and sex class, Prophet River, 1998...... 12 Table 6. Grizzly bear population estimate for the Prophet River study area based on current (August 1999) habitat capability modeling...... 13

Timberland Consultants Ltd. Prophet River grizzly bear inventory 1

INTRODUCTION Recent developments in techniques to estimate grizzly bear (Ursus arctos) population size have included use of remote hair capture to sample populations, DNA analysis to identify individuals, and mark-recapture modeling to estimate population size (Woods et al. 1996, 1999, Mowat and Strobeck 2000). These techniques appear to provide an accurate, less costly and less invasive alternative to population estimates derived from intensive capture and radio collaring efforts (i.e., McLellan 1989, Stirling et al. 1997). Currently, population management of grizzly bears in British Columbia (B.C.) is based primarily on estimates of carrying capacity via modeling of habitat capability and suitability and extrapolating population size using density estimates from previous research (Fuhr and Demarchi 1990). No research has been conducted in the northern half of the province to verify these habitat-based extrapolations. Industrial activity, primarily oil and gas development and logging, is increasing in the Prophet River area in northeastern B.C. Hunting by residents and outfitters is popular in the region. B.C. government bear managers suggest that the grizzly populations in northeastern B.C. are among the least studied and their densities the most contentious in the province [T. Hamilton and M. Austin, B.C. Ministry of Environment, Lands and Parks (MELP), Victoria, personal communication]. Local outfitters and First Nations (Prophet River Indian Band) identified grizzly bears as one of their top wildlife management concerns in the region (P. Gillis, Besa River Outfitters, personal communication; B. Wolf, Prophet River Indian Band, personal communication). Grizzly bears are a blue-listed species (vulnerable) in B.C., meaning they are of special concern because of characteristics that make them particularly sensitive to human activities or natural events (B.C. Conservation Data Centre). They have been identified as 1 of the main management concerns in the Forest Practices Code, which regulates logging practices on crown land in B.C., and many forest districts insist that forestry licensees take bear habitat needs into consideration when developing forest cutting plans. The grizzlies inhabiting the Prophet River area may be 1 of the few concentrations of the species in B.C. east of the Rocky Mountains. To address these concerns, we derived a DNA-based mark-recapture population estimate for a portion of the Prophet River area that ranged from the height of the northern Rocky Mountains east into the boreal forest. Our primary objective was to estimate grizzly bear population size for management needs and to provide a comparison to numbers predicted from the habitat based method currently in use. Secondary objectives were examining the distribution of grizzly bears across the study area and assessing the usefulness of the methods and study design we followed. Additional details on study rationale, design and fieldwork are provided in Poole et al. (1998). Black bear (U. americanus) frequent much of the study area, and we collected a large number of black bear samples.

STUDY AREA

We based study area selection on a number of interrelated factors, including geographic closure, cell size, session length, access, and cost (discussed in Methods). We selected an 8,527 km2 study area stretching from the continental divide of the northern Rocky Mountains (elevations up to 3,000 m), to the rolling boreal forest east of the Alaska Highway (elevations from 450 m) (Fig. 1). The study area is divided into the Northern Boreal Mountains

Timberland Consultants Ltd. Prophet River grizzly bear inventory 2

Timberland Consultants Ltd. Prophet River grizzly bear inventory 3

ecoprovince, which covered the western one-third (3,114 km2), and the Taiga Plains ecoprovince, which covered the eastern two-thirds (5,518 km2). The Northern Canadian Rocky Mountains ecoregion and the Eastern Muskwa Range and Muskwa Foothills ecosections lie within the Northern Boreal Mountains. The Muskwa Plateau (ecosection and ecoregion) and a very small portion of the Fort Nelson Lowlands ecosection are found within the Taiga Plains. The area covers 3 biogeoclimatic (BEC) zones; boreal white and black spruce (BWBS; mw2 and wk3 subzone/variants) in the lower elevation boreal forest; spruce- willow-birch (SWB) in the foothills; and alpine tundra (AT) in higher elevations (Meidinger and Pojar 1991). The AT and SWB zones essentially align with the Northern Boreal Mountains, and the BWBS zone aligns with the Taiga Plains. Winters are long and cold, and the growing season is relatively short. Mean July and January temperatures for Fort Nelson, 100 km north of the study area in the BWBS zone, are 16.7 and –22.0°C, respectively, with an average of 449 mm of precipitation annually, 191 mm of which falls as snow (Environment Canada climate normals, unpublished data). Frequent fire disturbances have resulted in a mosaic of successional coniferous [primarily lodgepole pine (Pinus contorta)] and deciduous [primarily trembling aspen (Populus tremuloides)] forests throughout the study area (MacKinnon et al. 1992). Black spruce (Picea mariana) and white spruce (P. glauca) stands are found throughout the BWBS zone, along with scattered stands of subalpine fir (Abies lasiocarpa). Willow (Salix spp.) and alder (Alnus spp.) often cover open areas. The SWB zone is characterized by white spruce and subalpine fir at lower elevations, grading to deciduous shrubs [scrub birch (Betula spp.) and willow] at higher elevations. Upper elevation valleys often have a mosaic of shrubs, grassland, and wetlands. AT zone vegetation includes dwarf willows, herbs, mosses and lichens. Several common plant species that are important foods of bears further south do not occur in this area, such as western springbeauty (Claytonia lanceolata), glacier lilies (Erythronium grandiflorum), and wild parsley (Lomatium spp.), or are uncommon, such as sweet-cicely (Osmorhiza spp.) and angelica (Angelica spp.; Fuhr and Demarchi 1990). Two of the most commonly eaten grizzly bear plant foods, sweet vetch (Hedysarum spp.) and cow parsnip (Heracleum sphondylium) occur throughout the region. The only permanent human residents within the study area were found at a lodge along the Alaska Highway, which bisected the study area from south to north. Various oil and gas leases also housed more ephemeral human residents. Oil and gas and forestry development had resulted in a system of all-weather and winter access roads and seismic lines centred along the Alaska Highway and extending over much of the eastern half of the study area. The study area covered roughly the southern two thirds of MELP Management Unit (MU) 7-48, about 80% of MU 7-42, and small portions of MUs 7-47 and 7-49.

METHODS

Survey design

Following methods outlined in Woods et al. (1996, 1999) and Mowat and Strobeck (2000), we used a systematic grid design to distribute sampling effort across the study area. We selected a 9 x 9 km cell size (81 km2) in order to balance between the smallest likely home range size in that northern habitat (typically a female with cubs; Nagy and Haroldson 1989) and enable

Timberland Consultants Ltd. Prophet River grizzly bear inventory 4 coverage of the area. We selected study area boundaries to maximize geographic closure. Geographic closure, potentially the most important assumption of mark-recapture models (Mowat and Strobeck 2000), is violated if there is movement of individuals on and off the study area among trapping sessions (White et al. 1982). We hoped to minimize movement by selecting the height of land between major drainages as the boundary, and by selecting a large area. The resulting study area boundary followed the height of land and enclosed complete drainages on all sides except where it crossed the main branches of the Prophet River in the north and the Sikanni Chief River in the southeast (Fig. 1). We recognise that there were no real physical or behavioural barriers to bear movement along the study area boundary except perhaps to the west where the height of land generally exceeded 2,000 m. We divided the study area into 103 cells. Irregular shaped cells <40.5 km2 in size along the boundary were lumped in with a neighbouring cell, resulting in a mean cell size of 82.8 km2. We installed 1 capture site in each cell for approximately 12 days, and trapped 5 sessions, ensuring that each new site in a cell was located >1 km from all previous sites and that all 5 sites were roughly evenly spaced throughout each cell. We selected sites based on our subjective interpretation of the best bear habitat in that area. We started the fieldwork in late May 1998 when we felt all bears would be out of their dens, based on timing of emergence by grizzly bear populations in other areas (Mace and Waller 1997; B. McLellan, B.C. Ministry of Forests, Revelstoke, B.C., personal communication). Females with cubs are typically the last age and sex cohort to leave their dens (Mace and Waller 1997). A 12-day trapping session was used to ensure that the study was completed by 1 August 1998. Stone sheep (Ovis dalli stonei) hunting in the mountains starts 1 August, after which time there may be increased potential for conflict between hunters and bears at bait sites. Also, in late July and early August bears tend to move to berry patches, which alters movement patterns and reduces catchability compared with previous sessions (Mowat and Strobeck 2000).

Field methods

We used a Bell 206B helicopter, a truck, and an ATV for access to sites. In the helicopter we used a Global Positioning System (GPS)-Geographic Information System (GIS) linked computer navigation and mapping program (Poole et al. 1999) to facilitate navigation and site placement. We recorded the locations of all sites both manually on data forms and digitally with the computer program. Site selection was left up to the field crew. Both crew leaders were experienced in site selection from previous grizzly bear DNA studies, and attempted to select the best sites for catching grizzly bears in each cell. We placed sites near natural travel corridors whenever possible (alpine passes, valley bottoms, games trails, etc.). Site selection in the mountains covered the range from river valley bottoms to high passes between drainages. In the boreal forest, site selection was restricted to road and seismic line access or suitable helicopter landing locations. We posted 2-4 warning signs at all sites where there was a risk of human encounter. Hair collection sites consisted of liquid bait poured on a 1-1.5 m high mound of logs, stumps, moss and boughs. The mound was placed in the middle of a perimeter fence of 20-30 m of barbed wire running around 3 or more trees at about 50 cm from the ground (Woods et al. 1999, Mowat and Strobeck 2000). For bait we used about 250 ml of rancid fish oil and 3-4 litres of rotten beef blood. For the last 2 trapping sessions we placed 30-40 g beaver (Castor

Timberland Consultants Ltd. Prophet River grizzly bear inventory 5 canadensis) castor wrapped in cloth and hung 2 m up in a tree within the site. The beaver castor was used in an attempt to provide a novel scent to enhance site attractiveness to previously captured bears. Capture success in the latter sessions of some previous grizzly bear studies appears to be lower compared with earlier sessions (Woods et al. 1999, Mowat and Strobeck 2000). Changes to the bait part way through the study will not affect the statistical analysis of the data since the change was uniform for all sites and several mark-recapture models accommodate this type of variation (White et al. 1982, Rexstad and Burnham 1991). However, if capture variation among sessions is strong, use of the commonly used heterogeneity model (Jackknife) is not possible. Field crews carried pre-cut lengths of barbed wire; capture sites could be installed or removed in less than 20 minutes by a 2-person crew. When sites were removed, all hair from each barb was placed in a small paper envelope and marked with the cell and site number. We placed all samples from the same site and a DNA collection form in a larger envelope, which we labelled with the date and cell/site. We left all sample envelopes out to dry at room temperature for 1 day before storing them frozen in a zip- lock bag with 5-10 g silica. Silica absorbs residual moisture, which should minimize DNA degradation (Foran et al. 1997).

DNA analysis

Using a dissecting microscope, all hair samples were sorted into 3 categories: black bear, grizzly bear, and unknown species. Samples which contained no roots or which were obviously not bear were removed. We identified black bear samples by the presence of glossy black guard hairs with a solid black tip, and grizzly bears by brown guard hairs with grey or silver tips. Unknown samples often contained hair from a species that was not readily identified, both black and brown guard hair, or no guard hair at all. This method of subjective sorting has been checked during a previous study where 98% of the samples identified as black bear were confirmed by genetic testing (Woods et al. 1999). Normally, only those samples classified as grizzly bear or unknown would be tested for species using a mitochondrial genetic marker (Woods et al. 1999). However, because of reports of a number of very dark grizzly bears in the area, at least 1 sample from each site was genetically tested for species. DNA analysis was conducted at the Wildlife Genetics International laboratory in Edmonton, Alberta, Canada. On samples with ≥ 6 roots we used chelex-based extraction (Walsh et al. 1991) on 6 roots, and stored the remaining roots. On samples with ≤ 5 roots, DNA from all roots was extracted using the tissue extraction protocol for QIAamp kits (Qiagen Inc., Ontario). We conducted species tests on each sample by amplifying a section of the control region of mitochondrial DNA (mtDNA) and comparing the results to a reference collection (Woods et al. 1999). We genotyped all grizzly bear samples using 6 microsatellite loci (Paetkau and Strobeck 1994, Paetkau et al. 1996, Woods et al. 1999). Genotyping failures were unacceptably high for the samples extracted using chelex (73%), thus we re-extracted 306 samples using QIAamp and re-ran the genotypes. We ran nuclear DNA analysis of the Amelogenin locus on individual grizzly bears to classify their sex (Ennis and Gallagher 1994). We used the sibling match test described in Woods et al. (1999) to measure the conditional probability that a given individual was a sibling to others already identified because we knew young bears often travel in sibling groups with the mother. We accepted new bears when P-values for the sibling match test were < 0.05.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 6

Data Analysis We used the mark-recapture models in program CAPTURE to estimate population size. Model selection was based on a subjective review of capture results, the model selection tests performed by CAPTURE, previous simulation results (Otis et al. 1978, Mowat and Strobeck 2000), and our knowledge of bear behaviour. We also estimated population size within the 2 broad biophysical ecoprovinces in the study area. Each ecoprovince formed a continuous portion of the greater study area and we used the captures within each ecoprovince to estimate specific densities. We compared grizzly bear detection rates among BEC subzone, ecoprovinces, ecosections, and aspects using likelihood ratio contingency analysis. We investigated the relationship between bear detection and elevation, slope, and stand age using logistic regression. Topographic variables were obtained from digital 1:20,000 scale Terrestrial Resource Inventory Mapping (TRIM), and stand age was obtained from digital 1:20,000 scale B.C. Ministry of Forests forest cover mapping. Spatial analysis was conducted using ArcView (Environmental Systems Research Institute, Redlands California). Distances moved by sex classes of bears were compared between ecoprovinces and sexes using t- tests.

RESULTS

Hair collection and analysis We conducted 5 sessions of fieldwork between 25 May and 1 August 1998. Five unique sites were placed in all 103 cells, resulting in the sampling of 515 sites (Fig. 1). Sites were active an average of 12.1 days (Table 1). We collected 2,062 hair samples from 332 sites (range 1-28 samples/site). Hair was collected in at least 1 site in all cells except 1 (cell 18). We ran mtDNA species checks on 1,139 samples; 544 were grizzly, 453 black bear, 1 contained DNA from both bear species, 25 samples were from wolves (Canis lupus), and 116 tests failed (primarily because of insufficient DNA) or they were not bear or wolf. Subjective identification of samples correctly identified 94.5% of black bear samples and 81.3% of grizzly bear samples, as verified by genetic testing (Table 2). We identified grizzly bear hair at 113 sites; the proportion of sites that removed at least 1 grizzly bear hair sample (mean 22.6%) and the number of grizzly bear hair samples per site (mean 4.9) varied with no consistent pattern among sessions (Table 1). We identified black bear hair at 203 sites, with proportionately more detections in the eastern half of the study area (Fig. 2). The number of sites that detected black bear was relatively constant for the first 4 sessions (39-47 sites/session), but dropped to 30 sites in the fifth session. Wolf hair was identified at 14 sites distributed throughout the study area; 86% of wolf captures were in the first 2 sessions. DNA fingerprinting was performed on the 545 confirmed grizzly bear hair samples (Table 1). Four hundred and twenty-six samples (78%) generated 104 genotypes with a sibling match probability < 0.05; 48 of these individuals were females, 49 were males, we could not assign sex to the remaining 7 individuals due to inadequate amounts of template DNA. We identified 10 family groups (females with cubs) based on exclusion (the principle that all offspring must share at least 1 allele with each parent), although we had low power to match mothers to offspring because we analyzed only 6 loci. There were 10 sites that removed grizzly bear hair but where we were unable to identify an individual (Table 1). The 104 grizzly bears

Timberland Consultants Ltd. Prophet River grizzly bear inventory 7

Table 1. Grizzly bear hair capture results from the Prophet River grizzly bear DNA inventory, 1998. One hundred and three cells were sampled during each capture session. Duration (days) Sites with hair No. of Hair samples/site Grizzly New grizzly Sites where Session Start date Mean (SE) samples (%) samples Mean (SE) bears bears ID failed 1 25 May 11.8 (0.10) 13 (12.6) 84 6.5 (1.70) 22 22 0 2 6 June 12.4 (0.12) 27 (26.2) 121 4.5 (0.67) 37 31 3 3 18 June 12.2 (0.11) 21 (20.4) 78 3.9 (0.54) 20 11 3 4 30 June 12.4 (0.13) 33 (32.0) 175 5.3 (0.57) 42 26 2 5 12 July 11.8 (0.14) 19 (18.4) 87 4.6 (0.80) 24 14 2 Grand mean 12.1 (0.06) 22.6 (21.9) 4.9 (0.35) 145 104 Total 113 545 10

Timberland Consultants Ltd. Prophet River grizzly bear inventory 8

Figure 2. Location of black bear captures in the Prophet River grizzly bear DNA inventory study, 1998. Sites that captured black bears are shown in solid circles, sites that did not are shown in open circles.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 9

Table 2. Hair sorting identification checked by DNA species identification, Prophet River grizzly bear inventory, 1998. Species identification based on mtDNA (%) Sorting ID1 n Black bear Grizzly bear Both bears Unknown2 Black bear 128 121 (94.5) 6 (4.7) 0 1 (0.8) Grizzly bear 433 45 (10.4) 352 (81.3) 1 (0.2) 35 (8.1) Unknown 578 287 (49.7) 186 (32.2) 0 105 (18.2) 1 Hair samples were sorted into black bear, grizzly bear and unknown based on gross hair morphology and colour. 2 Unknown samples included wolf, species other than bear or wolf, and species test failures.

were caught 162 different times during our study. However, for mark-recapture modeling a bear caught at 2 different sites in the same session counts as 1 capture; we captured bears 145 times in the 5 capture sessions. Thirty-eight grizzly bears were caught at >1 site. Individual sites generally caught 1-3 bears; 2 sites caught 4 bears and 1 site captured 7 bears. To our knowledge, no grizzly bears were removed from the study area during the study.

Population size

We examined 8 closed mark-recapture models and selected Darroch's time model (Mt- Darroch) to obtain a naïve population estimate for our study area of 169 grizzly bears [95% confidence interval (CI) 140-212] (Table 3). We selected Darroch's time varying model because there was obvious variation in capture success among sessions (Table 1; Fig. 3), there was weak evidence of heterogeneity variation based on the goodness of fit tests in CAPTURE (χ2 = 2.19, 1 df, P = 0.14; Appendix 1), and previous simulation and analysis suggest that Mt is robust to mild heterogeneity (Otis et al. 1978, Mowat and Strobeck 2000). The model selection routine in CAPTURE also suggested Mt; we selected Mt-Darroch over Mt-Chao because we did not consider capture probabilities were sparse enough to require the Chao model (Chao 1989). The overall capture probability was 0.17.

We considered the naïve estimate biased high because the majority of the study area boundary was not topographically closed. Because females have smaller home ranges than males (see summary in LeFranc et al. 1987) we estimated population size for males and females separately to investigate the potential impact of closure bias on the combined estimate. The population estimate for males (80 bears) was 12.7% higher than the estimate for females (71 bears). Added together, these estimates by sex are only slightly lower than the unadjusted estimate for the entire study (151 versus 169). Closure bias for females was likely to be smaller than for males because females have smaller home ranges and do not tend to wander outside their home range in search mates during the breeding season, as do males. The true sex ratio in the population is likely to approximate 50:50 or favour females (see Table 9 in LeFranc et al. 1987). Males probably had higher overall capture probabilities due to their larger home ranges and movements (Mace et al. 1994). Therefore, we reasoned that the difference between the male and female population estimate is probably largely due to closure bias in the male segment of

Timberland Consultants Ltd. Prophet River grizzly bear inventory 10

Table 3. Grizzly bear population estimates from 8 closed mark-recapture models in program CAPTURE from DNA analysis of hair collected at bait sites during summer 1998 for the Prophet River area

Model Nˆ SE 95% CI

Mo-Null 172 18.5 142-217

Mh-Jackknife 219 21.0 185-268 Mh-Chao 216 37.0 164-315 Mt-Darroch 169 17.7 140-212

Mt-Chao 188 27.8 148-262 Mth-Chao 207 36.5 157-306 Mb-Zippin 239 111 137-656

Mbh-Removal 239 111 137-651

45 1

0.8 35

s 30 0.6 25

20 0.4 15 Captures Number of grizzly bears New Captures

capture new of Proportion 10 % New captures 0.2

0 0 12345

Trapping session Figure 3. The total number of grizzly bears captured per trapping session, the number of new bears captured per session, and the proportion of captured bears which were new bears in each of 5 capture sessions on the Prophet River study area, 1998.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 11

Table 4. The relationship between grizzly bear detection rate and ecosystem, topographic and habitat variables, Prophet River area, 1998. Habitat variable Source of data1 Scale of dataset χ2 r2 P BEC zone/subzone QBEC_BC 1:250,000 48.40 0.001 Ecoprovince QBEC_BC 1:250,000 39.17 0.001 Ecosection QBEC_BC 1:250,000 39.63 0.001 Elevation TRIM 1:20,000 50.16 0.10 0.0001 Slope TRIM 1:20,000 12.11 0.02 0.0005 Stand age B.C. forest cover 1:20,000 0.49 0.001 0.48 Aspect TRIM 1:20,000 4.30 0.22 1 QBEC_BC = Quarter-million scale biogeoclimatic zone mapping; TRIM = Terrestrial Resource Inventory Mapping; B.C. forest cover mapping is produced by B.C. Ministry of Forests.

the population. We suggest that the overall population estimate should be reduced by 6% to account for closure bias. We consider this a conservative measure of the bias caused by lack of closure. This correction for lack of closure resulted in an adjusted population estimate of 159 grizzly bears (95% CI 130-202 or ± 23% of the mean) within the study area (19 bears/1,000 km2).

Effects of habitat on population density Based on simple contingency comparisons, we were more likely to detect grizzly bears in sites set in the more mountainous Northern Boreal Mountains and associated ecosections (primarily SWB and AT BEC zones) compared with the flatter Taiga Plains and associated ecosections (primarily BWBS) (Fig. 1, Table 4). This result suggested that bear densities may have been different between these 2 areas. We estimated population size independently within the 2 ecoprovinces using Darroch's time model. The naïve population estimate for the Northern Boreal Mountains was 113 grizzly bears (95% CI 91-148) and for the Taiga Plains was 60 bears (95% CI 42-104). These numbers appear accurate because together they approximate the unadjusted estimate for the entire study area (173 versus 169). Sample sizes were too small to analyse either region by sex to investigate closure bias, however we used the correction that was suggested for the entire study area (6%) as a rough guide to obtain adjusted population estimates and density for each region: Northern Boreal Mountains 106 grizzly bears (95% CI 84-141), 35 bears/1,000 km2; Taiga Plains 56 grizzly bears (95% CI 38-100), 10 bears/1,000 km2. Grizzly bear presence was also related to elevation, with increased bear captures with increasing elevation (Table 4). Other variables were either not related to bear presence (aspect and stand age) or the relationship explained a trivial amount of the variance associated with bear presence (slope; Table 4).

Timberland Consultants Ltd. Prophet River grizzly bear inventory 12

Table 5. Distance moved (km) among recaptured grizzly bears by ecoprovince and sex class, Prophet River, 1998. Ecoprovince Sex class n Mean SE Range Taiga Plains Male 10 19.2 5.55 3.9-64.9 Female 4 15.7 3.42 6.4-22.5 Northern Boreal Mountains Male 13 15.0 1.81 8.5-31.2 Female 15 10.0 1.59 2.3-21.0 Females 9 8.9 1.06 4.3-13.9 with cubs

Bear movements

There was no apparent difference in the distribution of sex cohorts (single males, single females, and family groups) throughout the study area. Of the 10 identified family groups, 2 were captured within the boreal plains, 2 were captured on or near the boundary between the mountain/foothills and boreal plains regions, and 6 were captured well within the mountains. Thirty-eight bears (including 5 family groups) were captured more than once during the study. Within ecoprovinces, there was a tendency for males to be move greater distances than single females, however a significant difference was obtained only for the mountainous region (t = 2.09, P = 0.046; Table 5). Family groups tended to move smaller distances than non-family groups (recaptures were only obtained in the mountains). Between regions, males and females again tended to move greater distances in the boreal plains, however, the differences were not significant (P > 0.13). Although a few bears were captured near the boundary between the mountain and plains regions, no individual bears were captured in both the mountain and plains regions during the study. One male grizzly captured well within the boreal plains during the second session was recaptured 65 km to the west near the interface between regions during the forth session, and subsequently was recaptured at 2 sites back in the boreal plains in the fifth session. The proportion of bears detected in cells on the border of the study area was mildly greater than the detection rate for interior cells (34% versus 28%, respectively). DISCUSSION

Grizzly bear population size in B.C. is currently extrapolated from densities taken from detailed population research projects and applied to habitat capability as described by BEC subzone/variants within ecosections (Fuhr and Demarchi 1990). These estimates of undisturbed habitat capability may then be stepped down based on current suitability, for example if the area in question is disturbed by humans or to account for harvest. Estimates may change over time through application of different density estimates to the 5 capability classes, through use of the low, mid-point or high values within each density range, and through changes to the capability class assigned to BEC subzone/variants within each ecosection. In summer 1997 the habitat- based, Fuhr/Demarchi-derived population estimate for our study area was roughly 70-80 grizzly bears. The current (August 1999) estimate for our study area is 110 grizzly bears (Table 6).

Timberland Consultants Ltd. Prophet River grizzly bear inventory 13

Table 6. Grizzly bear population estimate for the Prophet River study area based on current (August 1999) habitat capability modeling. Habitat BEC Area capability Ecoprovince Ecosection subzone/variant (km2) class1 Estimate2 Northern 48.7 Boreal Mts. EMR ATp 6703 5 0 EMR SWBmk 206 3 5.4 MUF ATp 663 4 4.0 MUF SWBmk 1,406 3 36.6 MUF BWBSmw2 109 3 2.8 Taiga Plains 61.5 MUP SWBmk 4 3 0.1 MUP BWBSmw2 4,734 4 28.4 MUP BWBSwk3 643 2 32.8 FNL BWBSmw2 32 4 0.2 Entire study 110.2 area 1 Density (bears/km2) in Class 1: 0.076-0.1; Class 2: 0.051-0.075; Class 3: 0.026-0.05; Class 4: 0.006- 0.025; Class 5: 0-0.005. 2 Population estimates were defined as the low value of the density range in all classes. 3 Approximately 60 km2 of lake and glacier (with a density of 0 bears) removed.

The current habitat-based estimate predicts similar overall densities to our estimates for the Taiga Plains (11 versus 10 bears/1,000 km2, respectively), but less than half our estimates for the Northern Boreal Mountains (16 versus 35 bears/1,000 km2, respectively). The combined habitat-estimates for the AT and SWB BEC zones within the Northern Boreal Mountains could be doubled to better reflect our results. Although our estimates within the Taiga Plains agree, the low end of capability class rating 2 for the BWBSwk3 variant within the Muskwa Plateau ecosection (MUP) appears to inflate the grizzly bear density (adding 33 bears to the estimate from only 643 km2), while the low end of rating 4 for the BWBSmw2 variant appears to considerably underestimate bear density (Table 6). Estimates from this study could be used to adjust the capability ratings for the Northern Boreal Mountains and Taiga Plains ecoprovinces of B.C. The annual grizzly bear harvest for the study area is difficult to determine precisely because our study did not align with MELP management units. MELP hunter harvest summary statistics derived from compulsory inspections recorded 20 grizzly bears harvested (11 F, 9 M) in MU 7-48 during 11 years between 1986 and 1996 (mean of 1.8 bears annually). For MU 7-42,

Timberland Consultants Ltd. Prophet River grizzly bear inventory 14

215 bears (76 F, 137 M) were taken in the 22 years between 1975 and 1996 (mean of 9.8 bears each year). Our study area incorporated roughly the southern two thirds of MU 7-48 and about 80% of MU 7-42, thus the annual harvest for the study area through to 1996 has been roughly 8- 9 bears. Prophet River Indian Band members do not actively hunt grizzly bears; the First Nation’s harvest of grizzly bears in the study area is negligible (B. Wolf, Prophet River Indian Band, personal communication). Assuming similar bear densities over the past 2 decades, the harvest rate for our study area has averaged 5-6% per year to 1996. There have been few studies conducted on grizzly bears that inhabit habitats similar to the foothills and boreal forests of the eastern Prophet River area. All of the Prophet study area appears to be located in the Cold Boreal Plains grizzly bear zone; Banci (1991) estimated the density in this zone to be roughly 3.3 bears/1,000 km2. Our study would suggest this number is conservative, especially for the western part of the zone. In the adjacent Subarctic Mountains and Plains the estimated density is roughly 15.4 grizzly bears/1,000 km2 (Banci 1991), which more closely approximates our estimate. The nearest studies on grizzly bears east of the Rocky Mountains were conducted in the west-central portion of Alberta. Estimated densities of grizzly bears in these study areas ranged from 4.6 bears/1,000 km2 in the Berland-Wildhay rivers region, 7.4/1,000 km2 in the areas of the South Wapiti River, and 7.4-9.6/1,000 km2 in the Swan Hills study (Alberta Forestry, Lands and Wildlife 1990). All these estimates are mildly lower than our density estimate for the boreal plains portion of the Prophet River study (10/1,000 km2). All 3 of these Alberta study areas are located in the Cold Boreal Plains grizzly bear zone but fall in 3 different ecoprovinces. Lower harvest, less human disturbance, greater connectivity to adjacent populations, and proximity to the more productive foothills and mountains region of the Rocky Mountains may have contributed to the higher densities observed in the boreal plains of the Prophet River study. In addition, these estimates were based on the assumption that the researchers had captured or identified all the bears on their study areas, which is difficult to achieve. There are currently no other estimates of grizzly bear density in the Northern Boreal Mountains ecoprovince of B.C. However, Larsen and Markel (1989) presented a preliminary estimate of 13-22 bears/1,000 km2 and Pearson (1975) estimated density that ranged from 37-44 bears/1,000 km2 for the same ecoprovince in southern Yukon. To the south, Russell et al. (1979) estimated bear density between 10-12 bears/1,000 km2 in Jasper National Park, which lies in the northern portion of the Southern Interior Mountains ecoprovince. It would seem that there is large variation in bear density in the northern mountains and that the relatively high density we report for the mountainous part of our study (35 bears/1,000 km2) is not unprecedented in that ecoprovince (Pearson 1975). We caution that all of the above-noted densities were derived from intensive capture and collaring studies; different methodologies and assumptions in each study suggest that these densities may not be directly comparable to those we used in the Prophet River area. Our field techniques generally followed techniques used in previous studies, however we used mounds of sticks, branches and stumps, topped with moss for bait-placement, rather than the conventional practice of suspending bait on a rope between trees (Woods et al. 1996, 1999, Mowat and Strobeck 2000). We suspect these mounds performed their task well; they were generally easy to build, their large size may have helped to entice bears past the barbed wire (as a large object worth investigating), the bait was 1-2 m off the ground which encouraged air flow, and the moss helped keep the bait moist and smelly during the relatively warm and dry summer.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 15

We were able to smell the bait at many sites after 12 days. Use of mounds and liquid baits also enabled consistency among bait sites throughout the study; many alpine sites were placed in areas where it would have been impossible to suspend bait from trees. We cannot assess whether the addition of beaver castor during the last 2 sessions aided our goal of increasing recaptures. It is interesting to note that total capture went up dramatically in the fourth session while the proportion of repeat captures increased in both the fourth and fifth sessions. Grizzly bears in the Taiga Plains may have been more difficult to capture compared to the bears in the Northern Boreal Mountains. Lower average capture probabilities in the Taiga Plains support this hypothesis (0.14 versus 0.18). We feel this was primarily because of the limited options on the Plains for accessible sites (generally roads, seismic lines or abandoned well sites) and a paucity of obvious travel corridors. Grizzly bears were often detected in the mountains on travel corridors in saddles, passes, and game trails along rivers and valleys; similar features were less obvious and perhaps less abundant in the boreal forest. We used the same technician as used by Woods et al. (1999) to sort out black bears samples, and her ability to identify black bear hair was similar for both studies. Success of species identification and genotyping for the Prophet River data set were higher than other studies we have conducted (Mowat and Strobeck 2000). This may have resulted from careful handling of samples between the field and the laboratory (drying and freezing samples with silica) or use of the QIAamp method to ultimately extract most samples. Genotyping failures were unacceptably high for the samples initially extracted using chelex, although we do not know the cause of these failures. In general, we have had greater genotyping success using QIAamp extraction versus chelex recently. It appears that the species test presented by Woods et al. (1999) will also identify wolves. We report here the first instances of verified capture of wolves at hair snagging bait sites. The cell size and number of trapping sessions we chose were more than adequate for the desired goal of providing a population estimate for management purposes. In fact, given that 95% confidence intervals were ±23% of the mean, one could argue for less intensive sampling, either fewer sessions or larger cell sizes, in order to cut costs. We dropped the first and last session from this dataset and the population estimate using the same model was similar (152 versus 169) and the CI was ±35% of the mean (Mowat, in prep.). Considerable cost saving could be realized if managers were willing to accept 95% CIs of about ±40% of the point estimate. Although it would appear one could use the model selection routine in CAPTURE for this dataset, interpretation of results was complicated by the fact that the proportion of new captures increased during sessions 4 and 5 (Fig. 3). While this result may simply be due to sampling variation, the movement of male bears off the study area after the breeding season during sessions 4 and 5 could also explain it. This hypothesis is supported by the closure test in CAPTURE which rejected closure at P = 0.03. Alternatively, it is possible that the addition of beaver castor in sessions 4 and 5 caused an increase in the capture of new bears that were not interested in the fish and blood baits used exclusively during sessions 1-3. We estimated that topography may have been severe enough to force bears to align their home range boundaries with the study area boundary for about 20% of the study area perimeter (along the height of the Rocky Mountains on the western end of the study area). This suggests the possibility for an important closure bias in this study. We calculated the maximum trappable area by extending all border cells out to their full size except for those cells that we felt had

Timberland Consultants Ltd. Prophet River grizzly bear inventory 16 closed borders (in the western mountains). Density was reduced by 20% when we used the maximum trapped area to calculate density. Individuals residing partially on the study area have reduced capture probabilities so the capture bias is likely to be less than the 20% we estimated based on the maximum trappable area. While the distribution of grizzly bear captures across our area was not homogenous we feel that lacking a more objective correction for closure the difference between male and female population sizes is the best, though possibly conservative, estimate of closure bias we have for this data set. Our habitat analyses probably focused at too small a scale. However, these simple analyses demonstrate the usefulness of presence/absence data in comparing species abundance across very broad scale habitats. We found that elevation influenced small-scale habitat choice in our study area. Grizzly bears are known to make seasonal movements in elevation in other mountainous areas (LeFranc et al. 1987, McLellen 1989, Mace and Waller 1997). Nams et al. (In Prep.) found that elevation was the most important variable in predicting small-scale habitat choice in their Selkirk Mountains study in southeastern B.C. MANAGEMENT RECOMMENDATIONS

We suggest that the capability ratings currently in use for the boreal biogeoclimatic zones of B.C. significantly underestimate density in the mountainous portions of the Prophet River area. These capability ratings could be adjusted if the Prophet River area is representative of the biogeoclimatic zones elsewhere in the province. We suggest it might be prudent to conduct a DNA-based mark-recapture study of grizzly bears in another location in the northern boreal portion of B.C. to provide a second set of data. We demonstrate that adequate capture success for grizzly bears can be achieved using liquid baits, however we do not know how important it is to add a novel bait or baits during a study. We suggest, as do Woods et al. (1999) and Mowat and Strobeck (2000), that removing obvious black bear samples before extraction can reduce DNA analysis costs. QIAamp extraction may improve genotyping success in some laboratories. We suggest that future workers could use less intensive sampling than described here, either by using larger cell sizes or fewer but longer capture sessions (to maintain adequate capture probabilities), and still generate population estimates adequate for management decisions. DNA-based inventories will only become an option for regional bear managers when the cost can be supported in yearly inventory budgets. We suggest that future workers consider fewer capture sessions in order to reduce costs. Study designs that use 2 or 3 sessions will not be able to use all the models available in CAPTURE so every effort must be made to minimize capture bias. We suggest a systematic sample design combined with the movement of sites at the end of each capture session will help minimize capture variation. We do not recommend the use of only 2 trapping sessions because of the large variation experienced in capture success among sessions; 1 weak session in a 2-session study would jeopardise the usefulness of the study. We corrected for closure bias in this study but our population estimate may still have been high. Application of mark-recapture to calculate population density will always involve a subjective component until there is an objective method to correct for closure bias. Large study areas, boundaries that provide topographic barriers, and short study duration will all minimize closure bias.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 17

ACKNOWLEDGEMENTS Funding was provided by the Prophet River Indian Band through an agreement with Forest Renewal B.C., Resources Inventory Program, and Canadian Forest Products Ltd., Fort St. John Division, through their Multiyear Agreement with Forest Renewal B.C. L. Wilkinson (MELP), B. Wolf (Prophet River Indian Band), and A. de Vries (Canadian Forest Products) provided administrative support. A. Walker, J. Wolf, K. Tsakoza, P. Johnstone and A. Christie assisted on field crews. M. Savage provided expert piloting and assisted greatly in many aspects of field activities. We thank B. and P. Gillis and the staff of the Buckinghorse River Lodge for their co-operation with the study. D. Pritchard wrote and fine-tuned the computer navigation and mapping program, and L. Macgregor and S. Dingwall produced maps. K. Stalker conducted hair extraction, and M. Paradon ran the DNA analysis. We thank all Band members, government staff, and outfitters for sharing their knowledge of bears. J. Boulanger, A. de Vries, J. Elliot, D. Heard and B. Wolf provided comments on an earlier draft of the manuscript.

LITERATURE CITED

Alberta Forestry, Lands and Wildlife. 1990. Management plan for grizzly bears in Alberta. Wildlife Management Planning Series No. 2, Edmonton. Banci, V. 1991. The status of the grizzly bear in Canada in 1990. COSEWIC Status Report. B.C. Ministry of Environment, Victoria. Chao, A. 1989. Estimating population size for sparse data in capture-recapture experiments. Biometrics 45:427-438. Ennis, S., and T. F. Gallagher. 1994. PCR based sex determination assay in cattle based on the bovine Amelogenin Locus. Animal Genetics 25:425–427. Foran, D. R., S. C. Minta, and K. S. Heinemeyer. 1997. DNA-based analysis of hair to identify species and individuals for population research and monitoring. Wildlife Society Bulletin 25:840-847. Fuhr, B., and D.A. Demarchi. 1990. A methodology for grizzly bear habitat assessment in British Columbia. B.C. Ministry of Environment, Wildlife Bulletin No. B-67, Victoria. Larsen, D. G., and R. L. Markel. 1989. A preliminary estimate of grizzly bear abundance in the southwest Yukon. Unpublished report, Yukon Fish and Wildlife Branch, Whitehorse. LeFranc, M. N., M. B. Moss, K. A. Patnode, and W. C. Sugg, editors. 1987. Grizzly bear compendium. Interagency Grizzly Bear Committee, Washington, D.C. McLellan, B. N. 1989. Dynamics of a grizzly bear population during a period of industrial resource extraction. I. Density and age-sex composition. Canadian Journal of Zoology 67:1856-1860. Mace, R. D., and J. S. Waller. 1997. Final report: grizzly bear ecology in the Swan Mountains, Montana. Montana Fish, Wildlife and Parks, Helena. Mace, R. D., S. C. Minta, T. L. Manley, and K. E. Aune. 1994. Estimating grizzly bear population size using camera sightings. Wildlife Society Bulletin 22:74-83.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 18

MacKinnon, A., J. Pojar, and R. Coupé. 1992. Plants of northern British Columbia. Lone Pine Publishing, Vancouver, B.C. Meidinger, D., and J. Pojar, editors. 1991. Ecosystems of British Columbia. Special Report Series 6, B.C. Ministry of Forests, Research Branch, Victoria. Mowat, G. In prep. Study design for mark-recapture inventories using two or three capture sessions. Canadian Journal of Zoology, expected submission Jan 2000. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, DNA profiling, and mark-recapture analysis. Journal of Wildlife Management 64(1):in press. Nagy, J. A. S., and M. A. Haroldson. 1989. Comparisons of some home range and population parameters among four grizzly bear populations in Canada. International Conference on Bear Research and Management 8:227-235. Nams, V. O., G. Mowat, and M. A. Panian. In Prep. Habitat selection of grizzly bears at different spatial scales. for Journal of Applied Ecology. Poole, K. G., G. Mowat, and D. A. Fear. 1998. Grizzly bear DNA inventory of the Prophet River Territory, northeastern British Columbia. Prophet River Wildlife Inventory Report No. 9. Unpublished report submitted to B.C. Ministry of Environment, Lands and Parks, Fort St. John. (Available at: http://www.timberland.org/publications.htm) Otis, D. L., K. P. Burnham, G. C. White, and D. P. Andersen. 1978. Statistical inference from capture data on closed animal populations. Wildlife Monographs 62:1-135. Paetkau, D., and C. Strobeck. 1994. Microsatellite analysis of genetic variation in black bear populations. Molecular Ecology 3:489-495. Paetkau, D., W. Calvert, I. Stirling, and C. Strobeck. 1995. Microsatellite analysis of population structure in Canadian polar bears. Molecular Ecology 4:347-354. Pearson, A. M. 1975. The northern interior grizzly bear (Ursus arctos L.). Canadian Wildlife Service Report Series No. 34., Ottawa. Poole, K. G., G. Mowat, and D. Pritchard. 1999. Using GPS and GIS for navigation and mark- recapture for sightability correction in moose inventories. Alces 35:1-10. Rexstad, E., and K. Burnham. 1991. User’s guide for interactive program CAPTURE. Colorado State University, Fort Collins. Russell, R. H., J. W. Nolan, N. G. Nagy, and G. H. Anderson. 1979. A study of the grizzly bear in Jasper National Park 1975 to 1978 – final report. Canadian Wildlife Service, Edmonton. Stirling, S. D., G. C. White, R. A. Sellers, H. V. Reynolds, J. W. Schoen, K. Titus, V. G. Barnes, Jr., R. B. Smith, R. R. Nelson, W. B. Ballard, and C. C. Schwartz. 1997. Brown and black bear density estimation in Alaska using radiotelemetry and replicated mark-resight techniques. Wildlife Monographs 133:1-55. Walsh, P. S., D. A. Metzger, and R. Higuchi. 1991. Chelex 100 as a medium for simple extraction of DNA for PCR-based typing from forensic material. BioTechniques 10:506-513.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 19

White, G. C., D. R. Andersen, K. P. Burnham, and D. L. Otis. 1982. Capture-recapture and removal methods for sampling closed populations. Los Alamos Nat. Laboratory LA-8787- NERP. Woods, J. G., B. N. McLellan, D. Paetkau, M. Proctor, and C. Strobeck. 1996. DNA fingerprinting applied to mark-recapture bear studies. International Bear News, Vol. 5(1):9- 10. Woods, J. G., D. Paetkau, D. Lewis, B. N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging of free-ranging black and brown bears. Wildlife Society Bulletin 27:616- 627.

Timberland Consultants Ltd. Prophet River grizzly bear inventory 20

APPENDIX 1. Results of Goodness of Fit tests from CAPTURE for the Prophet River grizzly bear inventory, summer 1998.

1. Test for heterogeneity of trapping probabilities in population. Null hypothesis of model M(o) vs. alternate hypothesis of model M(h) Chi-square value = 2.194 degrees of freedom = 1 Probability of larger value = 0.13855

2. Test for behavioral response after initial capture. Null hypothesis of model M(o) vs. alternate hypothesis of model M(b) Chi-square value = 0.627 degrees of freedom = 1 Probability of larger value = 0.42836

3. Test for time specific variation in trapping probabilities. Null hypothesis of model M(o) vs. alternate hypothesis of model M(t) Chi-square value = 15.115 degrees of freedom = 4 Probability of larger value = 0.00447

4. Goodness of fit test of model M(h) Null hypothesis of model M(h) vs. alternate hypothesis of not model M(h) Chi-square value = 16.167 degrees of freedom = 4 Probability of larger value = 0.00280

Test of model M(h) by frequency of capture (frequencies less than 2t are not calculated.)

Number of captures Chi-square d.f. Probability ------

1 7.861 4 0.09680 2 9.681 4 0.04616

5. Goodness of fit test of model M(b) Null hypothesis of model M(b) vs. alternate hypothesis of not model M(b) Chi-square value = 18.012 degrees of freedom = 6 Probability of larger value = 0.00620

5a. Contribution of first capture homogeneity across time Chi-square value = 11.650 degrees of freedom = 3 Probability of larger value = 0.00869

5b. Contribution of recapture homogeneity across time Chi-square value = 6.362 degrees of freedom = 3 Probability of larger value = 0.09525

6. Goodness of fit test of model M(t) Null hypothesis of model M(t) vs. alternate hypothesis of not model M(t) Chi-square value = 55.447 degrees of freedom = 51 Probability of larger value = 0.31075

7. Test for behavioral response in presence of heterogeneity. Null hypothesis of model M(h) vs. alternate hypothesis of model M(bh) Chi-square value = 14.971 degrees of freedom = 8 Probability of larger value = 0.05970

Timberland Consultants Ltd. Prophet River grizzly bear inventory 21

Model selection criteria. Model selected has maximum value.

Model M(o) M(h) M(b) M(bh) M(t) M(th) M(tb) M(tbh) Criteria 0.16 0.03 0.07 0.00 1.00 0.99 0.31 0.28

Appropriate model probably is M(t) or M(th) Suggested estimator is Darroch.

Test for closure procedure. See this section of the Monograph for details.

Overall test results --z-value -1.849 Probability of a smaller value 0.03226

Test of closure by frequency of capture. (Frequencies less than 10 are not computed.)

Number of captures z-value Probability ------

2 -1.877 0.03028

Timberland Consultants Ltd.