GRIZZLY BEAR MONITORING by the HEILTSUK PEOPLE AS a CRUCIBLE for FIRST NATION CONSERVATION PRACTICE Version: 1 Submitted: 2012-10-26 PDF Created: 2012/10/29

Ecology and Society - ES-2012-5316 1

This Portable Document Format version of the manuscript has been automatically created for your convenience. It was NOT submitted by the author and so may not be a perfect rendering of the content of the submitted documents or the accompanying html files. Please refer to the html version of the manuscript if you encounter any difficulties. Tables, figures, and appendices can be found at the end of the document. You may use the bookmarks on the left to jump to these attachments.

Research GRIZZLY BEAR MONITORING BY THE HEILTSUK PEOPLE AS A CRUCIBLE FOR FIRST NATION CONSERVATION PRACTICE Version: 1 Submitted: 2012-10-26 PDF Created: 2012/10/29

ABSTRACT 2. ABSTRACT 3. Guided by deeply-held social and cultural values, and increasingly sanctioned by legal decisions, 4. First Nations [indigenous] people in Canada are rapidly regaining authority to manage natural 5. resources. Often, however, indigenous values clash with the western philosophies and scientific 6. approaches commonly applied to resource management. Here we integrate worldviews and practices in a 7. “bear-salmon-human” system in Heiltsuk Territory (in what is now also referred to as coastal British 8. Columbia, Canada). Specifically, we share not only the ecological results from a monitoring project 9. that used a molecular genetics approach to monitor grizzly bears, but also the broader 10. socio-cultural drivers and implications of our work. Non-invasive sampling of bears occurred between 11. 2006 and 2009 in the Koeye watershed, a stronghold for grizzly bears, salmon and the Heiltsuk. 12. Demographic analyses and sampling in adjacent areas showed that there is a regionally-significant 13. population of bears that congregate at the Koeye each salmon spawning season, with very few new 14. bears detected among years. We also detected early evidence of a declining trend in population, best 15. explained by declining salmon numbers. These data, collected by the Heiltsuk for the Heiltsuk, 16. directly inform local decision-makers tasked with growing responsibility to manage this system 17. against a backdrop of widespread loss or declines of both bears and salmon in North America since 18. European colonization. Moreover, our extensive time in the Koeye among grizzlies and salmon served 19. to reconnect Heiltsuk people with the land and resources; these experiences in turn reinforce the 20. conservation-oriented philosophy that inspired the research. We argue that successful resource 21. management by indigenous people will require approaches like ours, in which science-based management 22. is embedded within a socially and culturally appropriate context. Such a strategy can maintain 23. ancient intimacy with traditional lands and resources as well as provide a powerful engine for 24. conservation. 25. Key words: First Nations science; social and ecological resilience; bear population monitoring; 26. non-invasive mark-recapture; grizzly bear; values; conservation; traditional stewardship; salmon; 27. British Columbia 28.

INTRODUCTION Indigenous or First Nations people across parts of North America are actively 29. reinvigorating lifestyles and livelihoods that were largely or wholly disrupted by European Ecology and Society - ES-2012-5316 2

30. colonization. The success of this endeavor rests fundamentally on control and stewardship of 31. traditional lands and the ecological integrity of associated resources. Although international law 32. and conventions recognize the rights of indigenous peoples to maintain or regain control of these 33. natural assets (review in Colchester 2004), this principle is only slowly manifesting into practice. 34. Support for aboriginal agency in resource management emerges from the growing awareness that 35. conservation strategies disregarding the rights and needs of indigenous peoples not only threaten 36. conservation values and outcomes, but also represent an egregious human rights violation (e.g. 37. Alcorn and Royo 2007; see Filardi et al 2012). 38. Strategies that embrace enduring connections between indigenous people and their lands are 39. increasingly recognized as key to achieving tangible conservation outcomes (Chapin 2004). Across 40. northern North America, traditional territories of indigenous people comprise some of the highest 41. priority areas for conservation (Oviedo et al. 2000), making self-determination in resource 42. management an otherwise unavailable engine for improved resource stewardship and conservation (e.g., 43. Delcourt 1987; Saleh 1998; Schwartzman & Zimmerman 2005; Xu et al. 2005; Nepstadt et al. 2006; 44. Filardi et al. 2012). 45. Opportunities for these conservation gains are particularly relevant in Canada, where First Nations 46. are rapidly regaining sovereignty in resource management. Long embedded in Canada’s 47. Constitution Act of 1982, and increasingly empowered by landmark court decisions, the legal notion 48. of aboriginal rights and title provides indigenous people considerable authority in resource 49. management within their territories (reviews in Dalton 2006; Sullivan 2006; Wyatt 2008). One way 50. this transition has been operationalized is via a process termed “co-management”, 51. broadly referring to power- and responsibility-sharing between federal or provincial government and 52. indigenous people. The nature of these arrangements varies from limited local consultation as a part 53. of government or academic research to local indigenous governments regaining substantial 54. self-management capacity and authority (Notze 1995). 55. Ultimately, the fullest transfer of authority (to self-determination) moves beyond an administrative 56. process to include a fundamental shift in the value systems and institutional cultures that govern 57. resource management. Western philosophies emphasize linear, positivistic or teleological notions, 58. often optimizing use of individual resources. Common management prescriptions such as 59. “maximum sustainable yield” in fisheries or forestry illustrate these approaches in 60. practice. In contrast, abundant evidence suggests that non-teleological indigenous approaches to 61. resource management can be characterized by respect and reciprocity at the scale of ecosystems or 62. landscapes; relationships among species and between human and non-human life are emphasized (for 63. examples see Castree 2003, Cajete 2000, Tuhiwai Smith 1999, Turnbull 1993-4, and Nelson 1986). In a 64. mutually reinforcing way, First Nations perspectives on entities like “wildlife” or 65. “timber” influence the way in which resources are treated and managed by aboriginal 66. people. 67. These different philosophical approaches have generally clashed (e.g. see Price et al. 2009). 68. Typically, western perspectives dominate, driving what has been called “green 69. imperialism”. This phenomenom occurs when science-based, non-aboriginal approaches trump 70. meaningful indigenous participation in resource management (Grove 1995, Dowie 2009). One consequence 71. of this conflict is a continued under-appreciation of the potential synergies between these 72. disparate worldviews and a general failure to integrate coherently the knowledge and tools 73. associated with each. 74. There is growing evidence, however, that integration across science-based management perspectives 75. and those of other cultures can improve conservation outcomes (e.g. Cash et al 2003 and references 76. therein). Specifically, science-based knowledge can be effectively incorporated into aboriginal 77. management settings when it is respectful of multiple knowledge sources, acknowledging so called 78. “legitimate knowledge” (Clark and Holliday 2006). Learning how to integrate these 79. worldviews and practices, however, requires careful consideration. To this end, we examine here a 80. “bear-salmon-human” system in Heiltsuk Territory (in what is now referred to as coastal Ecology and Society - ES-2012-5316 3

81. British Columbia [BC], Canada; Fig. 1). 82. Bear-salmon-human systems: a social-ecological crucible within Heiltsuk Territory 83. For their entire existence, the Heiltsuk People have lived among and interacted with grizzly bears 84. (Ursus arctos) and salmon (Oncorhynchus spp.). In fact, where the three still co-occur, interactions 85. among bears, people, and salmon represent some of the most ancient and enduring confluences between 86. ecology and human culture in North America (e.g. Clarke and Slocombe 2009). Along the Pacific coast, 87. salmon are posited to have spawned societies of great social and ecological resilience (Trosper 88. 2003). In a similar way, coastal grizzly bear diet and demography are largely driven by salmon 89. abundance (e.g. Hildebrand et al 1999, Gende and Quinn 2004; Levi et al 2012). Humans and bears 90. certainly interacted on spawning streams, with the activities of one undoubtedly influencing the 91. other. Accordingly, this long-term legacy of interaction provides a strong social-ecological 92. framework to support the conservation of grizzlies and salmon by groups like the Heiltsuk, who still 93. live with these natural assets and who are re-asserting their management rights. 94. Efforts to re-establish management authority, however, come at a challenging time for 95. bear-salmon-human systems. Across BC, myriad human stressors, including climate change, habitat 96. loss, pollution, hatcheries, and over-exploitation since European colonization have caused 97. widespread extirpation and run declines of up to 50% or more of historic abundances (Slaney et al. 98. 1996; Northcote & Atagi 1997; Price et al. 2008; Darimont et al. 2010). Unpublished data from 99. Heiltsuk Fisheries reveal the same pattern of decline across Heiltsuk Territory. 100. Although grizzly bears are expected to show similarly broad and significant declines in the face of 101. salmon reductions, relevant data are few. Moreover, as we explain below, attention from conventional 102. management agencies is limited. In neighboring Oweekeno/Wuikinuxv Territory, however, recent work 103. sponsored by the provincial government detected grizzly declines associated with the collapse of a 104. sockeye salmon (O. nerka) run over a period of three years (Boulanger et al 2004). This sockeye 105. system remains collapsed. Neither the provincial government, which manages terrestrial wildlife, nor 106. the federal government, which manages fish, have responded with a conservation strategy or plan. 107. Clearly, to detect and address similar problems in Heiltsuk Territory, leadership from diverse 108. sectors of society, including the Heiltsuk themselves, is required. 109. Recognizing these gaps, and the regional and local relevance of improved scientific knowledge about 110. natural systems within their traditional territory, resource management interests within the 111. Heiltsuk community partnered to create Coastwatch in 2006. As a research arm of the Qqs Projects 112. Society (www.qqsprojects.org), Coastwatch envisioned, designed, and leads a grizzly bear monitoring 113. program. Qqs also recognizes and values the human dimensions of grizzly bear monitoring, noting that 114. increasing human presence in parts of Heiltsuk Territory has recently led to increased human-bear 115. interactions (WGH pers. obs). As a response to all these potential stressors, Coastwatch’s 116. monitoring program sought to improve understanding of bear activity relative to salmon abundance and 117. human use within the heavily used and highly valued Koeye watershed, a recently formed Conservancy 118. (protected area) and salmon stronghold in Heiltsuk Territory (Fig. 1). 119. Coastwatch bear monitoring activities focus primarily on non-invasive hair-capture techniques during 120. autumn salmon spawning. Recent advances in molecular methods to estimate grizzly populations from 121. hair samples (Woods et al. 1999, Mowat and Strobeck 2000, Mowat et al. 2005, Boulanger and McLellan 122. 2001, Boulanger et al. 2001, Poole et al. 2001, Boulanger et al. 2002, Proctor et al 2010) offered a 123. timely opportunity for the Heiltsuk. These methods are easily implemented in the field and do not 124. require the capture or marking of individual bears, enabling a culturally acceptable and 125. analytically powerful means to estimate demographic trends in bear populations. The method also 126. enables users to identify any potential causal factors behind changes in bear numbers, should they 127. be detected (review in Proctor et al. 2010). 128. Our objectives for this paper are multifold. Scientifically, we seek to answer basic ecological 129. questions: What are the demographic trends for Koeye bears and are they related to salmon 130. availability? And, what source geography supplies bear aggregations during Koeye salmon runs? Ecology and Society - ES-2012-5316 4

131. Additionally, and importantly, we also explore how scientific results, and the scientific process 132. itself, are relevant to the Heiltsuk people and locally-driven, science-based management of the 133. Koeye Conservancy. We reveal the conservation potential of First Nations driving the full life-cycle 134. of applied conservation science within their traditional territories. In doing so, we highlight 135. broader implications of science-based indigenous stewardship during an era where this leadership is 136. urgently required. 137.

METHODS Study area 138. Along what is now known as the central coast of British Columbia, the Heiltsuk People comprise the 139. largest First Nation community (~2200 people). The traditional territory spans from outer coastal 140. archipelagos up into the high alpine divides of the Coast Ranges, encompassing nearly four million 141. hectares of the last intact coastal wilderness in western Canada (Fig. 1). Within this territory, 142. the Koeye watershed (51 °77’ N, 127°89’ W; Fig. 1) encompasses 18,000 ha of 143. temperate rainforest approximately 110 km north of Vancouver Island on the mainland coast. The area 144. is almost entirely roadless, with the exception of a service road (<1 km) associated with a small 145. lodge on a hill above the river mouth. The only human presence includes a year-round caretaker and a 146. six-week period of youth camps during July and August of each year. Notably, this watershed hosted a 147. significant Heiltsuk population prior to European contact, and remains of village sites are easily 148. observed today. 149. Most of the low elevation forest in this region is within the Coastal Western Hemlock biogeoclimatic 150. zone (Pojar &Mackinnon, 1994). The Koeye drainage has a large estuary, tidal meadows, freestone 151. river and stream systems, and several large lakes along its short (23.1 km) course to the sea. 152. Along the lower main stem, from estuary to Koeye Lake (12.6 km; Fig. 1), major aggregations of 153. spawning salmon occur, and include pink (Onchorynchus gorbuscha) and chum (O. keta). Relatively 154. large runs of coho (O. kisutch) access many feeder streams along this section, while sockeye (O. 155. nerka) utilize the lake and tributaries further up the drainage. Throughout the study period and 156. amidst considerable variation in salmon returns, salmon biomass (estimated as annual return numbers 157. multiplied by mean mass of each sex, assuming a 50:50 sex ratio [Darimont et al. 2008]) in the Koeye 158. was significantly greater than in any neighboring watersheds (Fig. 2). 159. Field methods 160. To collect grizzly bear DNA, we used barbed-wire snares to capture hair samples. Hair snares 161. consisted of a single 30 m strand encircling three to six trees at a height of ~50 cm, baited with 162. scent lure (Woods et al., 1999, Kendall et al 2009). Our sampling focused along the main stem of the 163. Koeye, from the estuary to Lake (Fig. 1), and coincided with peak salmon abundance 164. (September-October). From 2007-2009, we collected hair samples from baited snares distributed 165. systematically every ~500 m along the river. Snares were set on alternating sides of the river where 166. possible. We also included data from a pilot season in 2006 involving passive snares (i.e. barbed 167. wire strands across trails and wire on rub trees) located along paths frequently used by grizzlies 168. ((Boulanger et al. [2004]). 169. Sampling sessions were each approximately 10 days in length and involved 16 snares. Because sampling 170. of snares was limited by weather events, sessions were pooled within seasons to account for 171. heterogeneity of detection probabilities created due to unequal per session sampling coverage (Table 172. 1). We sampled the same area each year, though the number of sessions was varied; two, four, three, 173. and five sessions for 2006-2009 respectively. We report “snare-days” (the cumulative 174. number of days that all snares were available for bears during a given year) and “mean number 175. of snares” (the average number of snares available each session; Table 1). 176. To relate grizzly bear populations and movements to salmon availability, we simultaneously counted 177. salmon and assessed their availability to bears. Although salmon spawning (i.e. escapement) is often 178. used to estimate resources available to bears, escapement does not necessarily reflect salmon Ecology and Society - ES-2012-5316 5

179. availability, because water levels and other factors can influence grizzly fishing success. 180. Therefore, we combined salmon count estimates during standard stream-walk surveys with a field 181. assessment of water flow and visibility to provide an index of salmon availability (Boulanger et al. 182. 2004). Availability was ranked on a scale from 1 to 3 for each sampling session. 183. Sampling effort and genetic analysis 184. We collected 781 hair samples from 2006-2009. Samples were excluded from genetic testing based on 185. inadequate genetic material for extraction (113 samples; 14.5%) and non-grizzly appearance (47 186. samples; 6%). Additionally, eighty-two samples from 2007 were not analyzed due to budgetary 187. constraints. For the remaining 529 samples, 344 (65%) were successfully genotyped. Twenty-four 188. samples (4.5%) containing DNA from >1 bear and were excluded from analyses. 189. Species, individual identity, and gender of bears were determined through analysis of DNA extracted 190. from the hair samples (Woods et al. 1999). Seven nuclear microsatellite loci were used to define 191. unique individuals (Paetkau et al.1995). Rigorous data-checking procedures were followed to 192. eliminate genotyping errors (Paetkau 2003, Kendall et al. 2009). Multidimensional cluster analysis 193. based on similarity of 7-locus genotypes provided unambiguous species assignment for all 194. individuals. Gender was assigned using the sex-linked amelogenin marker (Ennis and Gallagher 1994). 195. Estimation of demographic parameters and population trends 196. To estimate demographic parameters and population trends, we used the Pradel model robust design 197. (Pradel 1996) with the Huggins closed N model (Huggins 1991) in program MARK (White and Burnham 198. 1999) to model both demography and estimate superpopulation size (i.e. cumulative number of bears 199. that traversed the Koeye watershed during sampling) for each year that was surveyed. Superpopulation 200. size and detection probability (p*) were estimated for each year using the Huggins closed population 201. size model (Huggins 1991). 202. The change in population size (), as well as apparent survival () and rates of additions between 203. years (f), were estimated using the Pradel model. Apparent survival () is the probability that a 204. bear that was in the sampling area in one year (i.e. 2006) would still be in the sampling area in 205. the subsequent year (i.e. 2007), encompassing both deaths and emigration from the sampling area. 206. Rates of addition, (f), is the number of new bears in the sampling area in a given year per bear in 207. the area during sampling the previous year. It encompasses both births and immigration. Apparent 208. survival and rates of addition are summed to estimate change in population size () between each 209. year. Finally, population rate of change is equivalent to the population size for a given sampling

210. period divided by the population size in the previous sampling period (=Nt+1/Nt). Accordingly, 211. estimates of will be 1 with a stable population, less than 1 if the population is declining and 212. greater than 1 if the population is increasing. 213. Models were introduced into the analysis that tested for sex-specific, session-specific, and 214. year-specific variation in demographic and detection probability parameters. In particular, we were 215. interested in the relative contribution of apparent survival (θ and/or rates of additions (f) 216. to population trend (λ in the study area. We estimated the relative contribution of θand f 217. to λby introducing models that held either θor f constant while varying the other 218. parameter for males, females, or both sexes pooled. For example, if a model with f varying each 219. year, while apparent survival was held constant was more supported, then it would suggest that 220. yearly variation in f was influencing trend more than apparent survival (Schwarz 2001, Nichols and 221. Hines 2002). Once we determined a base model we added the mean salmon availability for each year as 222. a temporal covariate to determine if salmon availability would influence demography. For example, a 223. year with high salmon availability might result in higher apparent survival (more bears from the 224. previous year being present) or the addition of new bears (due to either increased reproduction or 225. immigration from other areas). 226. The fit of models was evaluated using the Akaike Information Criterion (AIC) index. The model with 227. the lowest AICc score (adjusted for low sample size) was considered the most parsimonious, thus 228. minimizing estimate bias and optimizing precision (Burnham and Anderson 1998). The difference in Ecology and Society - ES-2012-5316 6

229. AICc values between the most supported model and other models (∆ICc) was also used to evaluate 230. the relative value of models when their AICc scores were close. In general, any model with a

231. ∆ICc score of less than 2 was worthy of consideration. Akaike weights (wi), which reflect the 232. proportional support for each model, were also estimated and averaged across the top model set to, 233. support robust estimates from multi-model inference. 234. Source Geography 235. In 2010 and 2011, a larger grid-based study of grizzly bear populations overlapped the Koeye study 236. area and extended north along the mainland coast and proximal islands (C. Darimont et al., 237. unpublished data). By sampling a broader geography during the spring emergence from denning sites, 238. samples from this companion study provided an opportunity to begin gathering information about the 239. potential source geography for autumn bear aggregations in the Koeye and to determine travel 240. distances between capture locations. We identified genetically-unique individuals detected on both 241. scales and measured the distances between their sampling locations using spatial analysis tools in a 242. geographic information system (GIS). 243.

RESULTS Numbers of bears detected 244. We detected a total of 57 individual bears in the study area with annual detections ranging from 245. four in 2006 to 41 in 2008. Detections (counts of unique bears) progressively increased until 2008, 246. then decreased in 2009 despite similar sampling effort (Table 1). After 2008, the majority of bears 247. detected in the watershed were recaptures from previous years suggesting high fidelity and a 248. relatively low number of bears entering the watershed among years. In 2009, only three individuals 249. were newly detected, with the remainder (16) being recaptures from previous years. Approximately 250. equal numbers of male and female bears were detected and recaptured in most years. 251. Demography and population trends 252. The Pradel analysis suggested that a model with linear decreasing trends in apparent survival 253. (θ for both sexes, and rates of additions (f) influenced by salmon availability for female 254. bears (f constant for male bears) was most supported (Table 2, model 1). Other supported models 255. included a constant f each year (model 2), and models with salmon abundance influencing θof 256. both male and female bears (models 3-6). Models that had linear decreasing survival trends for male 257. and female bears showed more support than models with survival influenced by salmon availability 258. (models 1-6). Models that assumed constant values for apparent survival and additions (model 18) or 259. equal year-specific trends (model 13) were less supported. The Huggins closed model for each 260. within-year sampling session assumed different capture probabilities for each year, but constant 261. capture probabilities within each session. Models with capture probabilities varying as a function 262. of sampling effort were less supported. 263. Model-averaged demographic parameter estimates suggested higher apparent survival (θ with low 264. rates of addition for most years (f; Table 3). Notable increases in rates of addition were in the 265. 2007 - 2008 interval; notable decreases in apparent survival were in the 2008 - 2009 interval. The 266. rate of change (λ, which is the sum of apparent survival and rates of addition, was below 1, 267. implying a declining superpopulation of bears for all years except for females between 2007 and 268. 2008. Estimates of were imprecise, presumably due to the shorter time sequence of years sampled 269. (Table 3). 270. Given that θestimates were greater than f estimates in all years of the study for both sexes, 271. apparent survival was a more dominant driver of population trend. This suggests that survival and 272. fidelity drove population trend in the area, as opposed to reproduction and new bears entering the 273. watershed (Fig. 3). Rates of addition (f) increased in 2008, especially for female bears, which was 274. associated with increases in salmon availability. The increase in additions in 2008 caused a 275. positive trend (λ1) in female superpopulation size. Increased rates of addition could have been Ecology and Society - ES-2012-5316 7

276. due to either new adult bears in the study area or a surge of productivity (cubs or yearling bears). 277. A large decrease in θ and as a result , occurred between 2008 and 2009 for both females and 278. males. 279. Estimates of per session detection probability were combined to estimate p*, the probability that a 280. bear that was detected would be captured at least once during all of the sessions of sampling (Table 281. 4). In this context, p* is equivalent to the proportion of the super population of bears that was 282. sampled each year. Estimates of p* were low for 2006 which resulted in highly imprecise estimates. 283. Estimates of p* increased each year with resulting gains in the precision (CV) of superpopulation 284. estimates (Table 4) 285. Trends in superpopulation estimates suggested a declining superpopulation of males, and an 286. increasing (2006-8) and then decreasing superpopulation (2008-9) of females (Fig. 4). The estimates 287. of superpopulation from 2006 were very imprecise and, therefore, the most definitive estimates 288. occurred from 2007-9. The same general estimates of trend (i.e. declining) were also evident from 289. estimates of λ(Table 3). 290. Source geography for autumn aggregations of bears in Koeye 291. Eight individuals detected during our study were detected the following spring in neighbouring 292. watersheds (Fig. 5). The majority were males (75%), which were located farther from the Koeye 293. (range: 2.8 – 75.6 km; mean = 33.4, SD = 29.7.0) than females (7.1 and 32.4 km from their 294. capture locations within Koeye). 295.

DISCUSSION The process of implementing a First Nations-driven non-invasive grizzly bear monitoring 296. study has yielded insight into not only grizzly-salmon interactions in one particular watershed, but 297. also into the relationships among wildlife and indigenous people that define the cultural context of 298. conservation in much of coastal British Columbia and beyond. For the Heiltsuk, this study is not 299. just about science; it is about respecting the grizzly bear, the salmon, the land, and ancient 300. connections that have existed for generations. Scientific bear monitoring by Heiltsuk people has 301. fostered rekindling of deeply held values that reflect, and are reflected in, traditional knowledge 302. in order to empower the impact of science on conservation outcomes. Notably, our bear work was 303. conducted independently of any government or educational institution. Scientific results are both 304. acutely applied in the context of Heiltsuk stewardship and relevant to a continent-wide shift in 305. resource management authority from colonial (back) to aboriginal stewards. In this way, we offer 306. here a touchstone system within Heiltsuk Territory and a social-ecological crucible for First 307. Nations conservation practice. 308. In keeping with a deep inter-generational history of intimacy with bears across traditional 309. territories (Rockwell 1991), the context of Heiltsuk scientific efforts reflects broader struggles 310. among indigenous communities to regain management authority within remaining intact bear-salmon 311. systems. Despite synergies between the ecology of bears and the interests of First Nations across 312. broad North American geographies, to our knowledge no scientific studies of this kind have been 313. directly framed and implemented by First Nations who share traditional territories with bears. Thus, 314. this study provides a novel indication of the social, ecological, and management implications of 315. First Nation driven resource management science. 316. Heiltsuk understanding of the Koeye grizzly aggregation 317. In this study, we coupled Heiltsuk societal and cultural values with a non-invasive scientific 318. approach to provide detailed ecological information to inform Heiltsuk decisions regarding use and 319. management of an important watershed and its natural assets. Lessons learned here directly flow to 320. the newly formed resource management agency of the nation, the Heiltsuk Integrated Resource 321. Management Department (HIRMD). Had this work been done outside of the Heiltsuk community, 322. communication to HIRMD would have been far less direct or persistent. What follows are our Ecology and Society - ES-2012-5316 8

323. interpretations of these results, which are relevant not only to bear-salmon-human relationships in 324. Heitsuk Territory but also to other social and ecological contexts in which aboriginal people are 325. managing resources again. 326. One of the primary lessons learned was contrast between the sexes in their use of the Koeye. Males 327. appear to spend less time within the watershed during salmon spawning, while females were more 328. likely to be observed across multiple sampling sessions. Moreover, females were observed moving 329. greater distances within the watershed across more continual time intervals than males. We infer 330. from these patterns that females may be moving more at local scales with relatively high within- and 331. among-season fidelity. Accordingly, the locations of females with cubs – which can demand 332. extra caution from people using the Koeye – might be hard to predict from week to week. In 333. contrast, males on average appear to cover much larger geographic areas in their seasonal movements; 334. many individuals might only be using the Koeye when other regional resources are scarce. 335. Accordingly, considerations of human safety might be particularly important during low salmon years, 336. when local resources are relatively scarce and local bear density relatively high. 337. Data across all years allow the Heiltsuk to assess the local value of the Koeye to grizzly-salmon 338. systems. The high numbers of bears we detected, the geographic data from migrants and data showing a 339. superabundance of salmon at Koeye relative to nearby streams collectively suggest the Koeye supports 340. a regionally large bear-salmon aggregation. In contrast, the provincial government’s habitat 341. quality model, which incorporates a suite of landscape and vegetative features (Fuhr and Demarchi 342. 1990; MacHutchon 2007), categorizes the relatively flat outer coastal habitat of the Koeye as 343. “low” or “very low” quality. The model used remote sensing and other GIS 344. tools but did not incorporate salmon density data. Our data and project, thus, underscore the value 345. of field-based inquiry, initiated and conducted by local people. Notably, however, long preceding 346. GIS, and even colonial governments, the Heiltsuk have long recognized the Koeye as a high density 347. grizzly system (WGH unpublished orally transmitted knowledge). 348. Even greater geographic relevance is evident by invoking a broad spatial and temporal perspective 349. that considers the decline or loss of grizzles and salmon elsewhere in western North America. We 350. assert that the Koeye hosts a significant and, likely southernmost, remaining aggregation of its 351. kind in western North America; grizzlies have been extirpated from nearby Howe Sound to the south 352. all the way down to their former range in Northern Mexico (Labierte and Ripple 2009); salmon have 353. been either likewise exterminated or dramatically diminished in watersheds to the south along the 354. coast (Quinn 2005; Northcote & Atagi 1997; Slaney et al. 1996; Gresh et al. 2000; Price et al. 355. 2008). Accordingly, the Heiltsuk recognize and accept a continental-scale responsibility to manage 356. this vestigial grizzly-salmon system, noting that it might contribute a source population to 357. beleaguered grizzly populations to the south. In this way, resource management leadership by local 358. people can affect conservation outcomes beyond territorial borders. 359. Data suggest that the future of the Koeye bear population will depend in large part on salmon 360. availability. Rates of addition were very low in most years but tended to correlate with salmon 361. availability. This suggests low immigration, and likely, low reproduction of bears. It may be that 362. cubs are less likely to be detected by hair snares in their first year; however, there is little 363. reason to believe yearlings should not have reasonable capture rates. If this is so, rates of 364. addition would reflect immigration and the previous year’s reproduction (if family groups 365. stayed in the Koeye, which observational evidence and result here suggest, WGH, CEF pers. obs.). 366. Thus we speculate that low reproductive rates may play a role in the observed declines. Available 367. salmon biomass declined up to 2008, which supports this hypothesis. When salmon availability is low, 368. both physiological (i.e. nutritional; Boulanger et al. 2004; Belant et al. 2006) and social (i.e. 369. dominancy hierarchies; Gende and Quinn [2004]) factors have been implicated in lower reproductive 370. output. This coupling between salmon and grizzly abundance is consistent with observations 371. (Hilderbrand et al. 1999a,b; Jacoby et al. 1999;) and modeling (Levi et al. 2012) across larger, 372. cross-population spatial scales. 373. Similar to rates of addition, apparent survival was low, especially in the 2008-9 interval. This Ecology and Society - ES-2012-5316 9

374. could potentially be due to emigration, higher mortality or a combination thereof. A coupled 375. increase in salmon in adjacent watersheds in 2009 might have caused bears that were present in Koeye 376. in 2008, when regional returns were very low, to emigrate. Alternatively, or interacting, following 377. low returns in 2008, bears might have sought human food resources, which is known to lead to 378. human-caused mortality. When hungry bears seek alternative foods near human habituation there is 379. often increased conflict (Knight et al. 1998; Gunther et al. 2004). Following the precipitous 380. decline in sockeye in the nearby Oweekeno/Rivers Inlet system in 1999, at least ten starving 381. grizzlies were killed by Conservation Officers in a remote village in a single month (Associated 382. Press 1999). Males would be particularly at risk. Larger bodied, and particularly large in coastal 383. areas, males find it more difficult to meet metabolic demands when salmon are in short supply (Rode 384. et al. 2001; Robbins et al. 2004) and likely take additional risks to find food. Finally, trophy 385. hunting of males might be influencing these rates of addition estimates. Although the Heitsuk 386. prohibit grizzly hunting at the Koeye, it occurs every year in adjacent watersheds where our 387. movement data suggest individuals travel (Fig 5). Males might be especially vulnerable during 388. periods of low salmon, when foraging bouts that expose them to hunters might be more frequent and 389. longer. 390. One important assumption of our analyses is that the number of grizzly bears identified on salmon 391. streams is indicative of the overall size and status of grizzly bear numbers in the Koeye area. This 392. assumption could be violated if other resources such as abundant berry crops draw bears away from 393. streamside snares. Given the value of salmon to fitness (above), we suspect that bears would not 394. abandon opportunities to investigate salmon, making it unlikely that other food resources are 395. driving these patterns. 396. Overall, our preliminary findings highlight the need for continued monitoring of Koeye bears to 397. better determine the drivers of annual and inter-annual population trends. Longer time series of 398. salmon availability and bear population trend data are also critical to better understanding these 399. dynamics on the temporal scale at which they most strongly interact. Moreover, these early patterns 400. and hypotheses they generate argue for investigation on larger geographic scales that reflect the 401. source geography of bears identified in our results. This geographic scope is critical to Heiltsuk 402. management but was unapparent prior to this study. Notably, these data have instigated the Heiltsuk 403. to lead a multi-First Nation bear management strategy, a social-ecological endeavor that recognizes 404. that bear movements transcend territorial jurisdictions. We suspect that such multi-nation 405. integration will be a common pattern with other mobile species as management authority is regained 406. by other nations. 407. Social context and First Nations science 408. Similar to relationships between special resources or places and other aboriginal nations, the 409. Heiltsuk recognize a fundamental bond and interaction among the Koeye, its people, salmon, and 410. bears. As stories and archaeological data suggest (Heiltsuk Integrated Resource Management 411. Department; Heiltsuk Cultural Education Centre; unpublished interview and survey data), the Heiltsuk 412. are an enduring component of this area’s ecology, realized through thousands of years of 413. occupation as well as use and interaction with its living resources. The Heiltsuk and grizzly bears 414. are linked by participation in ecological processes that influence each as well as the wider 415. ecosystem. Our time in the field made these connections more clear. We observed bears acting as 416. coastal ‘gardeners’ by distributing salmon nutrients to stream-side forests. This 417. process can increase plant growth, shift plant communities and eventually fuel aquatic productivity, 418. all of which support subsequent generations of salmon (Reimchen 2000; Hocking and Reynolds 2011). 419. Similarly, according to Heiltsuk stories, the Heitsuk have themselves historically cultivated 420. productive patches of berries, such as salmonberry (Rubus spectabilis,) through fertilization with 421. salmon carcasses (see also Turner 2008). Given – and affirming – this rich history of 422. interaction, self-directed research to increase the understanding of contemporary bear ecology 423. reconnects the Heiltsuk with their land and resources. It also provides a uniquely powerful engine 424. for conservation impact. Ecology and Society - ES-2012-5316 10

425. Modern scientific methods used in ways that are consistent with cultural values enabled significant 426. reconnection by Heiltsuk people with bear-salmon systems. Often, western scientific approaches 427. employ tools that place individual animals under the dominion of researchers, such as 428. radio-telemetry collars or physical markings. Such activity, which can affect the welfare of 429. individuals (e.g. Cattet et al. 2009), is increasingly criticized or prohibited by indigenous people 430. (Darimont et al. 2008b)) as well as scholars on grounds of scientific bias (e.g. Saraux et al. 431. 2011). For this study, the Heiltsuk rejected invasive research methods, and instead harnessed a 432. non-invasive approach. We suspect a suite of similarly non-invasive methods will characterize 433. resource management programs that First Nations or indigenous people lead and can add to improved 434. integration of scientific and indigenous approaches. 435.

CONCLUSION In an overarching way, this study - which couples society, culture, and ecology - 436. exemplifies an engine for conservation action that is largely unavailable to practitioners outside 437. of indigenous communities. This locally led and executed project illustrates how the Heiltsuk First 438. Nation values natural systems with respect and reciprocity in a manner that impacts decision-making. 439. Embodied in what Heiltsuk call Gvi'ilas, this ancient system acknowledges that the Heiltsuk are 440. deeply connected with natural resources defined within their territory. These assets are 441. additionally respected because they sustain people physically and spiritually, not only because they 442. can be traded for money. Embedded within this view is an emphasis on limiting resource use and, 443. ideally, enhancing the resource should there be appropriate opportunity. This perspective is at the 444. heart of why the Heiltsuk sought to learn more about the bears and salmon on the Koeye; not to 445. exploit them more, but rather with the aim of sustaining them and the Nation's relationship with the 446. full breadth of biological diversity that has defined their culture for millennia. 447. More broadly, research can empower and legitimize the unique, geographically-rooted epistemologies 448. that characterize many indigenous communities and in so doing so enable an interweaving of the 449. analytical power of science with concepts such as Gvi'ilas. Legitimate union between high-quality 450. science and First Nations perspectives on resource use represents a key advance in conservation 451. practice that moves us away from a history of conflict between First Nations values and wisdom on 452. the one hand, and scientific knowledge and conservation interests on the other. In this way, the 453. work reported here involves one foot firmly rooted in the past and another stepping into the future. 454. Connecting the Heiltsuk to the past is a sacred watershed in which many thousands of hours of 455. fieldwork occurred; these experiences maintained an enduring intimacy with place. Whereas the Koeye 456. might never again host a large village site, this project is an important process in maintaining, 457. and translating, ancient Heiltsuk intimacy with traditional lands, reasserting a presence, and 458. guiding contemporary resource stewardship. Ultimately, successful resource management by indigenous 459. people will require approaches like this one, in which science-based management is embedded within a 460. socially and culturally appropriate framework for action. Such a strategy can maintain unique, 461. ancient intimacy with traditional lands and resources representing a rich element of our collective 462. humanity. And, the context of indigenous resource management or co-management that is now so often 463. crippled by conflict, the approach presented here can also provide a powerful engine for 464. conservation. 465.

LITERATURE CITED 466. Alcorn, J. B., and A. G. Royo. 2007. Conservation’s engagement with human rights-traction, 467. slippage, or avoidance? Policy Matters 15:115-139. 468. Apps, C. and A. Hamilton. 2011. Summary and assessment of the Kimsquit and Dean Rivers grizzly bear 469. survey: 1998-2010. Ministry of Environment, Victoria, British Columbia, Canada. 470. Associated Press. 1999. Starving Grizzlies Killed in Canada. [online] URL: 471. http://www.apnewsarchive.com/1999/Starving-Grizzlies-Killed-in-Canada/id-c6375b6f76a7672a0f20f753cd84fb23. Ecology and Society - ES-2012-5316 11

472. Boulanger, J., G. Stenhouse, and R. Munro. 2004. Sources of heterogeneity bias when DNA 473. mark-recapture sampling methods are applied to grizzly bear (Ursus arctos) populations. Journal of 474. Mammalogy 85:618-624. 475. Boulanger, J., S. Himmer, and C. Swan. 2004. Monitoring of grizzly bear population trend and 476. demography using DNA mark-recapture methods in the Owikeno Lake area of British Columbia. Canadian 477. Journal of Zoology 82:1267-1277. 478. Boulanger, J., J. Woods, B. N. McLellan, M. F. Proctor, and C. Strobeck. 2004. Sampling design and 479. capture probability bias in DNA based mark-recapture estimates of grizzly bear populations. Journal 480. of Wildlife Management 68:457–469. 481. Boulanger, J., and B. McLellan. 2001. Closure violation in DNA-based mark-recapture estimation of 482. grizzly bear populations. Canadian Journal of Zoology 79:642-651. 483. Boulanger, J., G. C. White, B. N. McLellan, J. G. Woods, M. F. Proctor, and S. Himmer. 2002. A 484. meta-analysis of grizzly bear DNA mark-recapture projects in British Columbia. Ursus 485. 13:137–152. 486. Burnham, K. P., and D. R. Anderson. 1998. Model selection and inference: A practical information 487. theoretic approach. Springer, New York, New York, USA. 488. Cajete, G. 2000. Native Science. Clear Light Publishers, Santa Fe, New Mexico, USA. 489. Cash, D. W., W. C. Clark, F. Alcock, N. M. Dickson, N. Eckley, D. Guston, J. Jäger, and R. 490. Mitchell. 2003. Knowledge systems for sustainable development. Proceedings of the National Academy 491. of Sciences of the United States of America 100:8086-8091. 492. Castree, N. 2003. Place: Connections and boundaries in an interdependent world. Pages 165-185 in S. 493. L. Halloway, S. P. Rice, and G. Valentine, editors, Key Concepts in Geography. Sage, London, UK. 494. Cattet M. R. L., J. Boulanger, G. Stenhouse, R. A. Powell, and M. J. Reynolds-Hogland. 2008. An 495. evaluation of long- term capture effects in ursids: Implications for wildlife welfare and research. 496. American Society of Mammalogists 89:973–990. 497. Cattet, M. R. L., K. Christison, N. A. Caulkett, and G. B. Stenhouse. 2003. Physiologic responses of 498. grizzly bears to different methods of capture. Journal of Wildlife Diseases. 39(3):649-654. 499. Chapin, M. 2004. A Challenge to Conservationists. Worldwatch 17:17-31. 500. Clark, D. A., and D. S. Slocombe. 2009. Respect for grizzly bear: an Aboriginal approach for 501. co-existence and resilience. Ecology and Society 14(1):42. 502. Clark, W., and L. Holliday. 2006. Linking knowledge with action for sustainable development – 503. summary of a workshop. National Research Council: Roundtable on Science and Technology for 504. Sustainability. The National Academic Press, Washington, D.C., USA. 505. Dalton, J. E. 2006. Aboriginal Self-Determination in Canada: Protections Afforded by the Judiciary 506. and Government. Canadian Journal of Law and Society 21:11-37. 507. Darimont, C. T., P. C. Paquet, and T. E. Reimchen. 2008a. Spawning salmon disrupt tight trophic 508. coupling between wolves and ungulate prey in coastal British Columbia. BMC Ecology 2008, 8:14. 509. Darimont, C. T., T. E. Reimchen, H. Bryan, and P. C. Paquet. 2008b. Faecal-centric approaches to 510. wildlife ecology and conservation; methods, data and ethics. Wildlife Biology in Practice 4:73-87. 511. Darimont, C.T., H.M. Bryan, S.M. Carlson, M.D. Hocking, M. MacDuffee, P.C. Paquet, M.H.H. Price, 512. T.E. Reimchen, J.D. Reynolds and C.C. Wilmers. 2010. Salmon for terrestrial protected areas. 513. Conservation Letters 3:379-389. 514. Delcourt P. A. and H. R. Delcourt. 1987. Long-term forest dynamics of the temperate zone. A case Ecology and Society - ES-2012-5316 12

515. study of late-Quaternary forests in eastern North America. Springer-Verlag, New York, New York, USA. 516. Dowie, M. 2009. Conservation refugees: the hundred-year conflict between global conservation and 517. native peoples. MIT Press, Cambridge, Massachusetts, USA. 518. Ennis, S., and T. F. Gallagher. 1994. A PCR-based sex-determination assay in cattle based on the 519. bovine amelogenin locus. Animal Genetics 25:425-427. 520. Filardi, C., J. Brown, E. J. Sterling, and R. Jeo. 2012. On the Ethics and Effectiveness of 521. Conservation Partnerships. Conservation Biology, in review. 522. Fuhr, B., and D. A. Demarchi. 1990. A methodology for grizzly bear habitat assessment in British 523. Columbia. Wildlife Bulletin B-67. British Columbia Ministry of Environment, Lands and Parks, 524. Victoria, British Columbia, Canada. 525. Gende, S. M., and T. P. Quinn. 2004. The relative importance of prey density and social dominance in 526. determining energy intake by bears feeding on Pacific salmon. Canadian Journal of Zoology 82:75-85. 527. Gresh, T., J. Lichatowich, and P. Shoonmaker. 2000. An estimation of historic and current levels of 528. salmon production in the northeast Pacific ecosystem: evidence of a nutrient deficit in the 529. freshwater systems of the Pacific Northwest. Fisheries 25:15-21. 530. Grove, R. 1995. Green Imperialism: Colonial Expansion, Tropical Island Edens and the Origins of 531. Environmentalism, 1600-1860. Cambridge University Press, Cambridge, England. 532. Gunther, K. A., M. A. Haroldson, K. Frey, S. L. Cain, J. Copeland, and C. C. Schwartz. 2004. Grizzly 533. bear–human conflicts in the Greater Yellowstone ecosystem, 1992–2000. Ursus 15:10-22. 534. Hilderbrand, C. C., C. C. Schwartz, C. T. Robbins, M. E. Jacoby, T. A. Hanley, S. M. Arthur, and C. 535. Servheen. 1999. The importance of meat, particularly salmon, to body size, population productivity, 536. and conservation of North American brown bears. Canadian Journal of Zoology 77:132-138. 537. Hines, J. E., and J. D. Nichols. 2002. Investigations of potential bias in the estimate of lambda 538. using Pradel's (1996) model for capture-recapture data. Journal of Applied Statistics 29:573-587. 539. Hocking, M. D., and J. D. Reynolds. 2011. Impacts of salmon on riparian plant diversity. Science 540. 331:1609-1612. 541. Huggins, R. M. 1991. Some practical aspects of a conditional likelihood approach to capture 542. experiments. Biometrics 47:725-732. 543. Jacoby, M.E., G.V. Hilderbrand, C. Servheen, C.C. Schwartz, S.M. Arthur, T.A. Hanley, C.T. Robbins, 544. and R. Michener. 1999. Trophic relations of brown and black bears in several western North American 545. ecosystems. Journal of Wildlife Management 63:921–929. 546. Kendall, W. L. 1999. Robustness of closed capture-recapture methods to violations of the closure 547. assumption. Ecology 80:2517-2525. 548. Kendall, K.C., J.B. Stetz, J. Boulanger, A.C. Macleod, D. Paetkau, and G.C. White. 2009. 549. Demography and genetic structure of a recovering grizzly bear population. Journal of Wildlife 550. Management 73:3–17. 551. Whittaker, D. and R. L. Knight. 1998. Understanding wildlife responses to humans. Wildlife Society 552. Bulletin 26:312–317. 553. Lertzman, D. A. and H. Vredenburg. 2005. Indigenous Peoples, Resource Extraction and Sustainable 554. Development: An Ethical Approach. Journal of Business Ethics 56: 239-254, 555. MacHutchon, A.G. 2007. Coastal grizzly bear habitat mapping methods, draft 2. B.C. Ministry of 556. Environment, Victoria and Black Creek, B.C., Canada. 557. Mowat, G., and D. C. Heard. 2006. Major components of grizzly bear diet across North America. 558. Canadian Journal of Zoology 84:473-489. Ecology and Society - ES-2012-5316 13

559. Mowat, G., and C. Strobeck. 2000. Estimating population size of grizzly bears using hair capture, 560. DNA profiling, and mark-recapture analysis. The Journal of Wildlife Management 64:183-193. 561. Mowat, G., Heard, D. C., Seip, D. R., Poole, K. G., Stenhouse, G. and Paetkau, D. W. 2005. Grizzly 562. Ursus arctos and black bear U. americanus densities in the interior mountains of North America. 563. Wildlife Biology 11: 31-48. 564. Nelson, R.K. 1986. Hunters of the northern forest. University of Chicago Press, Chicago, USA. 565. Nepstad, D., S. Schwartzman, B. Bamberger, M. Santilli, and D. Ray D. 2006. Inhibition of Amazon 566. deforestation and fire by parks and indigenous lands. Conservation Biology 20: 65–73. 567. Nichols, J. D., and J. E. Hines. 2002. Approaches for the direct estimation of lambda, and 568. demographic contributions to lambda, using capture-recapture data. Journal of Applied Statistics 569. 29:539-568. 570. Notze, C. 1995. A New Perspective in Aboriginal Natural Resource Management: Co- 571. management. Geoforum 26(2):187-209. 572. Laliberte, AS and Ripple, WJ 2004 Range contractions of North American carnivores 573. and ungulates. BioScience 54:123-158. 574. Levi T., C.T. Darimont, M. MacDuffee, M. Mangel, P. Paquet, et al. 2012. Using Grizzly Bears 575. toAssess Harvest-Ecosystem Tradeoffs in Salmon Fisheries. Public Library of Science Biology 576. 10(4):e1001303. 577. Oviedo, G., L. Maffi, and P.B. Larsen. 2000. Indigenous and traditional peoples of the world and 578. ecoregion conservation, an integrated approach to conserving the world’s biological and 579. cultural diversity. WWF International, Gland, Switzerland. 580. Paetkau D., W. Calvert, I. Stirling, and C. Strobeck. 1995. Microsatellite analysis of population 581. structure in Canadian polar bears. Molecular Ecology 4:347. 582. Paetkau, D. 2003. An empirical exploration of data quality in DNA-based population inventories. 583. Molecular Ecology 12:1375-1387. 584. Pojar, J., and A. Mackinnon. 1994. Plants of the Pacific Northwest Coast: Washington, Oregon, 585. British Columbia & Alaska. Lone Line Publishing, Renton, Washington, USA. 586. Poole, G. C., and C. H. Berman. 2001. An ecological perspective on in-stream temperature: Natural 587. heat dynamics and mechanisms of human-caused thermal degradation. Environmental Management. 588. 27(6):787–802. 589. Poole, G., J. Dunham, M. Hicks, D. Keenan, J. Lockwood, E. Materna, D. McCullough, C.Mebane, J. 590. Risley, S. Sauter, S. Spalding, and S. Sturdevant. 2001. Scientific issues relating to temperature 591. criteria for salmon, trout, and char native to the Pacific Northwest. A summary report submitted to 592. the policy workgroup of the U.S. EPA Region 10 Water Temperature Criteria Guidance Project. EPA 593. 910-R-01-007. 594. Pradel, R. 1996. Utilization of mark-recapture for the study of recruitment and population growth 595. rate. Biometrics 52:703-709. 596. Price, K., A. Roburn, and A. MacKinnon. 2009. Ecosystem-based management in the Great Bear 597. Rainforest. Forest Ecology and Management 258:495-503. 598. Proctor, M., B. N. McLellan, J. Boulanger, C. D. Apps, G. Stenhouse, D. Paetkau, and G. Mowat. 2010. 599. Ecological investigations of grizzly bears in Canada using DNA from hair: 1995-2005: a review of 600. methods and progress. Ursus 21:169-188. 601. Quinn, T. P. 2005. The behavior and ecology of pacific salmon and trout. University of Washington 602. Press, Seattle, Washington, USA. Ecology and Society - ES-2012-5316 14

603. Reimchen, T. E. 2000. Some ecological and evolutionary aspects of bear - salmon interactions 604. in coastal British Columbia. Can. J. Zool. 78: 448-457 605. Robbins, C.T., C.C. Schwartz, and L.A. Felicetti. 2004. Nutritional ecology of ursids: a review of 606. newer methods and management implications. Ursus 15(2):161–171. 607. Rockwell, D. 1991. Giving voice to bear: North American Indian rituals, myths, and images of the 608. bear. Roberts Rinehart, Niwot, Colorado, USA. 609. Rode, K. D., C. T. Robbins, and L. A. Shipley. Constraints on herbivory by grizzly bears. Oecologia 610. 128:62-91. 611. Saleh, M. A. E. 1998. Alternative land management approaches in the highlands of south western 612. Saudi Arabia. Environmental Conservation 25:295304. 613. Saraux, C, C. Le Bohec, J.M. Durant, V.A. Viblanc, M. Gauthier-Clerc, D. Beaune, YH Park, N.G. 614. Yoccoz, N.C. Stenseth & Y Le Maho. 2011. Reliability of flipper-banded penguins as indicators 615. of climate change. Nature 469:203–206. 616. Schwarz, C. J. 2001. The Jolly-Seber model: More than just abundance. Journal of Agricultural, 617. Biological, and Environmental Statistics 6:195-205. 618. Schwarz, C.C, M.A. Haroldson, and C. Dickinson. 2002. Grizzly bear body composition. Pages 619. 43–44 in C.C. Schwartz and M.A. Haroldson, editors. Yellowstone grizzly bear investigations: 620. annual report of the Interagency Study Team, 2001. U.S. Geological Survey, Bozeman, Montana, USA. 621. Shwartzman, S., and B. Zimmerman. 2005. Conservation alliances with indigenous peoples of the 622. Amazon. Conservation Biology 19:721-727. 623. Slaney T.L., K.D. Hyatt, T.G. Northcote, and R.J. Fielden. 1996. Status of anadromous salmon and 624. trout in British Columbia and Yukon. Fisheries 21:20-35. 625. Trosper, R. L., 2003. Resilience in pre-contact Pacific Northwest social ecological systems. 626. Conservation Ecology 7(3):6. 627. Tuhiwai-Smith, L. 1999. Decolonizing methodologies: Research and indigenous peoples. Zed Books, 628. London, UK. 629. Turnbull, D. 1993, Maps Are Territories; Science is an Atlas, Chicago University Press, Chicago, 630. Illinois, USA. 631. Turner, N. J. and S. Peacock. 2005. Solving the perennial paradox: ethnobotanical evidence for plant 632. resource management on the Northwest Coast. Pages 101-149 in D. Deur, N. J. Turner, editors. 633. “Keeping it living”: traditional plant tending and cultivation on the Northwest Coast. 634. University of Washington Press, Seattle, Washington, USA. 635. White, G. C., and K. P. Burnham. 1999. Program MARK: survival estimation from populations of marked 636. animals. Bird Study 46:S120-S139. 637. Woods, J.G., D. Paetkau, D. Lewis, B.N. McLellan, M. Proctor, and C. Strobeck. 1999. Genetic tagging 638. of free-ranging black and brown bears. Wildlife Society Bulletin 27, 616–627. 639. Xu, J., E.T. Ma, D. Tashi, Y. Fu, Z. Lu, and D. Melick. 2005. Integrating sacred knowledge for 640. conservation: cultures and landscapes in southwest China. Ecology and Society 10(2):7. Ecology and Society - ES-2012-5316 15

Table 1. Table 1. Summary of sampling effort for Koeye grizzly bear DNA mark-recapture analysis 2006-2009. Salmon availability numbers are observational indices calculated in the field during each session (see text). Effort is presented as snare days/average snares set. The number of unique bears detected each year is given along with whether they were new bears or recaptures. The number of recaptures in the subsequent years is shown for bears detected in each year. The number of female bears (from the total bears listed) is given in parenthesis. For example, in 2006, 4 bears were detected of which 1 was a female. Recaptures for each of the three years subsequent to the first sampling period (2006) are divided by year in the three columns adjacent to the total recaptures.

Salmon Availability Capture Summary Year Sessions Effort Mean SE Detections New Recaps 2007 2008 2009 2006 2 209/20 2.0 4 (1) 4 (1) 3 (1) 2 (1) 1 (0) 2007 4 468/10.5 1.78 0.28 30 (14) 27 (13) 3 (1) 19 (10) 10 (4) 2008 3 773/20 2.0 0.32 41 (23) 22 (13) 19 (10) 14 (6) 2009 5 658/14 1.8 0.40 19 (9) 3 (2) 16 (7) Ecology and Society - ES-2012-5316 16

Table 2. Table 2. Pradel model selection results for the Koeye grizzy bear DNA mark-recapture analysis 2006-2009. A model with yearly detection probabilities was used for all models. Akaike Information Criteria (AICc), the difference in AICc values between the ith model and the model with the lowest AICc value (∆i), Akaike weights (wi), number of parameters (K) and model deviance are presented.

No Survival (θ Additions (f) AICc ∆ICc wi K Deviance 1 TrendA Salmon(F)B 661.4 0.00 0.17 8 644.3 2 Trend ConstantC 661.7 0.28 0.15 7 646.8 3 Sex*Trend Salmon 662.5 1.07 0.10 10 640.7 4 Trend Sex+salmon 662.7 1.35 0.09 8 645.6 5 Sex*Trend Salmon(F) 662.9 1.53 0.08 10 641.2 6 Trend Salmon(M) 663.2 1.80 0.07 8 646.1 7 Year Constant 663.6 2.26 0.06 8 646.5 8 Trend Salmon 663.7 2.33 0.05 8 646.6 9 Trend Year 663.8 2.44 0.05 9 644.4 10 Sex*Trend Sex+salmon 663.9 2.57 0.05 10 642.2 11 Trend+salmon Salmon(F) 664.9 3.53 0.03 9 645.5 12 Sex*Trend Sex+salmon 665.3 3.89 0.02 11 641.2 13 Year Year 665.8 4.37 0.02 10 644.0 14 Sex+year 665.9 4.54 0.02 9 646.5 15 Sex*salmon Salmon 666.1 4.72 0.02 9 646.7 16 Sex+salmon Salmon 666.5 5.14 0.01 9 647.1 17 Salmon Salmon(F) 668.1 6.71 0.01 7 653.2 18 Constant Constant 670.5 9.16 0.00 6 657.9 19 Constant Year 670.9 9.53 0.00 8 653.8 20 Sex Sex 673.8 12.42 0.00 8 656.7 19 Year*sex Year*sex 720.2 58.83 0.00 40 607.1 AA linear trend in the given parameter was assumed BSalmon availability was assumed to influence the parameter for females (F), males (M) or both sexes pooled if no sex is specified. CThe parameter was held constant meaning that it did not change in value for the duration of the study. Ecology and Society - ES-2012-5316 17

Table 3. Table 3. Model averaged demographic parameter estimates for males and females for the Koeye grizzy bear DNA mark-recapture analysis 2006-2009. Estimates of apparent survival (θ), rates of addition (f) and population rate of change (λ) are displayed. Models used for estimates are listed in Table 2.

Female Year Estimate SE LCI UCI CV θ006-7 0.95 0.14 0.04 1.00 15.0% 2007-8 0.88 0.12 0.44 0.99 13.3% 2008-9 0.36 0.10 0.20 0.57 27.4% f 2006-7 0.03 0.06 0.00 0.56 183.6% 2007-8 0.20 0.26 0.01 0.87 134.6% 2008-9 0.04 0.06 0.00 0.52 165.2% λ006-7 0.98 0.15 0.00 1.28 15.6% 2007-8 1.08 0.29 0.51 1.65 27.0% 2008-9 0.40 0.11 0.21 0.63 28.6% Year Estimate SE LCI UCI Male CV θ006-7 0.91 0.17 0.14 1.00 18.1% 2007-8 0.81 0.13 0.45 0.96 16.1% 2008-9 0.41 0.11 0.22 0.64 27.5% f 2006-7 0.01 0.03 0.00 0.07 342.1% 2007-8 0.08 0.18 0.00 0.92 233.0% 2008-9 0.01 0.03 0.00 0.07 339.9% λ006-7 0.92 0.17 0.10 1.25 18.3% 2007-8 0.89 0.20 0.15 1.27 22.1% 2008-9 0.42 0.11 0.22 0.64 27.2% Ecology and Society - ES-2012-5316 18

Table 4. Table 4. The number of unique bears detected (Mt+1), estimates of detection probability (p*), and corresponding superpopulation estimates for males and females for the Koeye River DNA grizzly bear DNA mark-recapture project 2006-2009. Confidence intervals (CI; upper/lower) and coefficient of variation (CV) are also shown.

Detection probability Superpopulation Estimates

(Mt+1) CI CI CV Year p* Estimate SE Males 2006 3 0.06 0.02/0.17 46 37.15 13/189 80.2% 2007 16 0.56 0.37/0.72 29 6.45 21/49 22.2% 2008 18 0.73 0.56/0.85 25 3.68 20/36 14.9% 2009 10 0.87 0.72/0.95 11 1.48 10/18 13.0%

Females 2006 1 0.06 0.02/0.18 15 17.55 3/94 113.7% 2007 14 0.56 0.38/0.72 25 5.87 18/44 23.1% 2008 23 0.73 0.58/0.86 32 4.35 26/45 13.8% 2009 9 0.87 0.73/0.96 10 1.39 9/16 13.5% Ecology and Society - ES-2012-5316 19

Fig. 1. Figure 1. Study area and major spawning areas in the Koeye River, Heiltsuk Territory (British Columbia, Canada) and surrounding watersheds. Ecology and Society - ES-2012-5316 20

Fig. 2. Figure 2. Total biomass of salmon returning to spawn for Koeye and adjacent watersheds over the decade between 1999 and 2009. Ecology and Society - ES-2012-5316 21

Fig. 3. Fig. 3a&b. Model averaged estimates of rates of addition of new bears shown with estimates of salmon availability for female (A.) and male (B.) bears in the Koeye River study area 2006-2009. Ecology and Society - ES-2012-5316 22

Fig. 4. Figure 4. Trends in superpopulation estimates for male and female bears for the Koeye River, Heiltsuk Territory (British Columbia, Canada) 2006-2009. The upper confidence limit for the male superpopulation estimate in 2006 was 189 (not shown). Points are staggered to ease interpretation of confidence limits. Ecology and Society - ES-2012-5316 23

Fig. 5. Figure 5. Location of hair snare stations where individual bears were originally identified in Koye watershed during this study (circles) and then recaptured during independent spring grid-based* sampling (triangles) on a large spatial scale in Heiltsuk Territory (British Columbia, Canada). Lines represent minimum distances traveled between snares by female (dashed) and male (solid) bears. * 7-km grid, snares placed in suitable habitat within each grid cell, established in spring 2010 (see text).