seismic survey design and impacts to maternal …...seismic survey design and impacts to maternal...

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16 September 2019 1 Ryan R. Wilson 2 U.S. Fish and Wildlife Service 3 1011 E. Tudor Rd. 4 MS341 5 Anchorage, AK 99504 6 (907-786-3830) 7 [email protected] 8 9 RH: Wilson and Durner • Seismic Survey Design 10

Seismic survey design and impacts to maternal polar bear dens 11

RYAN R. WILSON,1 U.S. Fish and Wildlife Service, 1011 E. Tudor Rd., Anchorage, AK, 99503, 12

USA 13

GEORGE M. DURNER, U.S. Geological Survey, Alaska Science Center, 4210 University Dr., 14

Anchorage, AK 99508, USA 15

ABSTRACT Large-scale industrial activities can have negative impacts on wildlife populations, 16

however, some of these impacts can be largely reduced with effective planning prior to any 17

activities occurring. The coastal plain of the Arctic National Wildlife Refuge, in northeastern 18

Alaska is an important maternal denning area for polar bears (Ursus maritimus). Recent 19

legislation has opened the area for potential oil and gas development. As a result, there is 20

interest in conducting winter seismic surveys across the area which could disturb denning 21

females and lead to decreased cub survival. We sought to demonstrate how different seismic 22

survey designs, with and without aerial den detection surveys, could affect the level of potential 23

impact on denning polar bears. We developed five hypothetical seismic survey designs for a 24

portion of the coastal plain ranging from no spatial or temporal restrictions on activities to 25

explicit consideration of when and where operations can occur. Survey design had a large effect 26

on the estimated number of dens that could be disturbed, with the scenario having the highest 27

1 Email: [email protected]


spatial and temporal specificity reducing the number of dens disturbed by >90% compared to the 28

scenario with no restrictions on when and where activity could occur. The use of an aerial den 29

detection survey prior to seismic activity further reduced the number of dens disturbed by 70% 30

across all scenarios. However, the scenario with highest spatial and temporal specificity always 31

had the lowest level of disturbance for all scenarios with and without the aerial survey included. 32

Our study suggests that large reductions in the probability of disturbance can occur through 33

careful planning on the timing and distribution of proposed activities even when surveys are 34

planned in areas with a high density of polar bear dens. 35

KEYWORDS 1002 Area, Arctic National Wildlife Refuge, coastal plain, FLIR, denning, 36

disturbance, polar bear, seismic survey, Ursus maritimus. 37

Reducing disturbance to wildlife from human activities is important for lessening 38

potential negative effects to wildlife (Northrup and Wittemyer 2013). While mitigation 39

measures to reduce disturbance can be effective when applied after development occurs (e.g., 40

Seidler et al. 2018), effective planning before development activities begin can reduce the need 41

for future mitigation measures (e.g., Copeland et al. 2009, Katzner et al. 2012, Suzuki and Parker 42

2019, Wilson et al. 2013). Failing to consider or account for the importance of an area to 43

wildlife populations and how a future industrial activities could impact those areas can 44

potentially have significant population-level effects (e.g., Sawyer et al. 2009, Beckmann et al. 45

2012, Seidler et al. 2015). For example, Green et al. (2017) found that between 1984 and 2008, 46

there was a 2.5% annual reduction in lek attendance by sage grouse (Centrocercus urophasianus) 47

as a result of oil and gas facilities being placed adjacent to lekking areas, providing evidence of 48

population-level effects of energy development on the species. Although the scientific literature 49

is replete with retrospective analyses of impacts of industrial activities to wildlife (Northrup and 50


Wittemyer 2013, Green et al. 2016, Sawyer et al. in press) many negative consequences resulting 51

from human actions could have been prevented or reduced with sufficient pre-development 52

planning. 53

The Arctic Ocean coastline in northern Alaska includes the Arctic National Wildlife 54

Refuge (ANWR), where its northcentral and northwest coastal plain includes 6070 km2 55

recognized by Congress in 1980 for its high potential of recoverable hydrocarbons (Clough et al. 56

1987). Known as the 1002 Area (Fig. 1), this region has received limited activities associated 57

with oil and gas exploration (National Research Council 2003), and none since 1985 (Jorgenson 58

et al. 2010). The recent passage of the Tax Cuts and Jobs Act of 2017 (Public Law 115-97; 59

https://www.congress.gov/bill/115th-congress/house-bill/1), however, has authorized oil and gas 60

leasing to occur in the 1002 Area, thereby creating the potential for disturbance to wildlife 61

inhabiting the region. 62

One of the most extensive forms of activity associated with oil and gas exploration are 63

seismic surveys used to identify underground oil and natural gas reserves (National Research 64

Council 2003, Dabros et al. 2018). In the Arctic, winter seismic activity can consist of >50 65

vehicles, numerous sleds hauling the camp for workers, and air strips, and can progress 24 hours 66

per day, with camps and supply trains moving approximately every 2-5 days (SAExploration 67

2018). Whereas previous seismic surveys in the 1002 Area were at a relatively low density (i.e., 68

a total of ~ 2000 km in survey transects arranged as a grid in 5 × 20 km parcels; Emers et al. 69

1995), contemporary seismic operations can cover wide areas and have intensive human activity, 70

with seismic lines occurring at densities ranging from 1.5-10 km/km2 and often separated by 71

distances of 50-100 m (Dabros et al. 2018). While efforts have been made over the past decades 72


to minimize environmental impacts of these surveys (Dabros et al. 2018), the density of activity 73

could lead to significant disturbance to wildlife. 74

The Arctic Coastal Plain of northern Alaska is an important maternal denning area for 75

polar bears (Ursus maritimus) of the Southern Beaufort Sea (SBS) population (Amstrup and 76

Gardner 1994). Nearly 55% of parturient bears of this population make winter dens in snow 77

banks on land, with the proportion of bears denning on land increasing over the past two decades 78

due to changing sea ice conditions (Fischbach et al. 2007, Olson et al. 2017). While denning can 79

occur anywhere along the Arctic Coastal Plain of northern Alaska, SBS polar bears 80

disproportionately den within the 1002 Area (Amstrup 1993, Durner et al. 2010). Amstrup 81

(1993) found that 34% of land-based dens in the range of the SBS population occurred inside the 82

1002 Area, even though it only represents 10% of the mainland coastline where bears can den. A 83

total of 3163 km of potential denning habitat (based on terrain capable of capturing snow 84

suitable for denning) is distributed throughout the area with 38% more present in the 1002 Area 85

than areas to the west (Durner et al. 2006, 2011). Because of the relatively high proportion of 86

polar bear maternal dens and denning habitat compared to elsewhere in northern Alaska, 77 % of 87

the 1002 Area has been designated as critical denning habitat (U.S. Fish and Wildlife Service 88

2010). 89

Because seismic surveys in Arctic regions occur in winter so that potential impacts to 90

tundra are minimized (National Research Council 2003), they overlap temporally with the period 91

when female polar bears are in maternal dens giving birth and raising altricial young (Rode et al. 92

2018). Disturbance to denning females before giving birth is not thought to cause significant 93

effects to fitness because bears can re-den elsewhere (Amstrup 1993, Linnell et al. 2000). Once 94

cubs are born (i.e., typically by mid-December to January; Messier et al. 1994, Franz Van de 95


Velde et al. 2003) the consequences can be more severe given the importance of the den in 96

sheltering cubs from the harsh winter environment before they are capable of effective 97

thermoregulation (Blix and Lentfer 1979). The consequences of disturbance post-birth can cause 98

den abandonment or early emergence, leading to decreased cub survival (Elowe and Dodge 99

1989, Amstrup and Gardner 1994, Rode et al. 2018). Conversely, in the absence of 100

abandonment, a severely disturbed denning bear may experience a prolonged (i.e., 2-3 weeks) 101

elevated heart rate, which could increase energetic costs (Evans et al. 2016), and thereby reduce 102

maternal energy stores necessary for cub production (Atkinson and Ramsay, 1995). A recent 103

study by Rode et al. (2018) found that females, observed < 100 days post den emergence with 104

cubs, emerged from dens on average 15 days later than females observed without cubs during the 105

same period. The overall denning duration of females observed with cubs was also 15 days 106

longer than females observed without cubs, and was related to differences in emergence dates as 107

there was no difference in the average date females observed with and without cubs entered dens 108

(Rode et al. 2018). Rode et al. (2018) also found that only 44% of females that spent < 100 days 109

in maternal dens were later observed with cubs. Conversely, 78% of females that had denning 110

durations > 100 days were later observed with cubs. Of those females that denned through the 111

end of March, all were later observed with cubs. These results highlight the importance to cub 112

survival of remaining in maternal dens for even seemingly short additional periods of time. 113

Polar bears are protected under the Marine Mammal Protection Act (MMPA; 16 U.S.C. 114

1361; https://www.mmc.gov/wp-content/uploads/MMPA_Aug2017.pdf) from all forms of take, 115

where “take” means to harasses, hunt, capture, or kill, or attempt to harass, hunt, capture, or kill. 116

In some circumstances, however, authorizations can be granted for the incidental, but not 117

intentional taking, of polar bears from specific activities in specific geographic regions. The 118


Secretary of the Interior is instructed, under the MMPA, to allow for the incidental taking of 119

polar bears if they can reach specific findings, one of which is that the take will have a negligible 120

impact on the species or stock (i.e., population). Under the MMPA negligible impact is defined 121

as an impact resulting from the specified activity that cannot be reasonably expected to, and is 122

not reasonably likely to, adversely affect the species or stock through effects on annual rates of 123

recruitment or survival. One metric that can be used to assess negligible impact is potential 124

biological removal (PBR) which is defined as the maximum number of animals, not including 125

natural mortalities, that may be removed from a marine mammal stock while allowing that stock 126

to reach or maintain its optimum sustainable population, the management goal as defined under 127

the MMPA. For the SBS polar bear population, PBR is estimated to be 14 animals per year 128

(U.S. Fish and Wildlife Service 2017). Given that subsistence take for the SBS population 129

already exceeds PBR (U.S. Fish and Wildlife Service 2017), any additional takes due to seismic 130

surveys would not be able to be authorized without impacting the ability of the SBS polar bears 131

to reach or maintain its optimum sustainable population. Thus, there is a need for seismic 132

surveys to be conducted in such a way that the probability of take is reduced to an insignificant 133

level. 134

Given the potential intensity of seismic surveys that could occur in the 1002 Area during 135

denning and in an area with a high density of dens, it is important that the design of surveys 136

sufficiently reduces the probability of disturbing dens and potentially leading to reduced cub 137

survival. Climate change is recognized as the primary threat to global polar bear populations 138

(Amstrup et al. 2010, Atwood et al. 2016), however, the Conservation Management Plan (CMP) 139

developed for polar bears under the Endangered Species Act and MMPA specifies that a primary 140

goal of polar bear conservation should be a focus on management actions that ensures polar bear 141


survival until such a time that climate change is abated and the species can recover (U.S. Fish 142

and Wildlife Service 2016a). The CMP also lists as one of its fundamental goals a desire to 143

achieve polar bear conservation while reducing restrictions to economic development. Thus, 144

there is a clear need to find the best ways for seismic surveys to occur while also reducing 145

negative impacts to polar bears. 146

We sought to demonstrate how different seismic survey designs, with and without the 147

inclusion of an aerial survey to detect dens with forward looking infrared (FLIR), could affect 148

the level of impact hydrocarbon exploration could have on denning polar bears. Our goal was to 149

inform seismic operators and wildlife managers that temporal and spatial considerations in 150

seismic survey designs relative to the likely timing and distribution of polar bear maternal 151

denning may be used to lower the impact of industrial activities. As such, we developed five 152

hypothetical seismic survey designs for a portion of the 1002 Area relative to the likely timing 153

and distribution of polar bear dens. The hypothetical designs ranged from no spatial or temporal 154

restrictions on activities to explicit consideration of when and where operations can occur. We 155

then determined how many maternal polar bear dens would likely be disturbed under each 156

scenario with and without a FLIR survey prior to the initiation of seismic activity. 157

STUDY AREA 158

The Tax Cuts and Jobs Act of 2017 limits the amount of surface development in the 1002 159

Area to ~8 km2. We assumed that the oil and gas industry will be most interested in obtaining 160

seismic data in the regions of the study area with the highest oil and gas potential. We therefore 161

defined our study area as the region of the 1002 Area identified by the Bureau of Land 162

Management as having medium or high hydrocarbon potential (Bureau of Land Management 163

2018) representing an area of 4,816 km2 (Fig. 1). 164


The vegetation, terrain and climate of the 1002 Area has been extensively described in 165

Pearce et al. (2018). In brief, vegetation within the 1002 Area is typically <0.3 m in height and 166

is predominantly composed of wet to moist graminoid and tussock tundra (59.5 % of total area) 167

and prostrate to dwarf shrubs (33.2 % of total area). Remaining proportions of the 1002 Area 168

surface are north-flowing rivers, lakes, and offshore waters (4.0 % of total area), bare or scarcely 169

vegetated ground (3.4 % of total area), and tall scrub (<0.1 % of total area). Lagoons and lakes 170

begin to freeze in September and the surface ground remains frozen until June. Additionally, sea 171

ice begins to reform near shore beginning in October. Ninety-nine percent of the 1002 Area is 172

classified as wetlands. Major terrain types include foothills (< 381 m; ~45 % of total area), 173

floodplains (~25 % of total area), hilly coastal plains (>22 % of total area), thaw-lake plains (~3 174

% of total area), and mountains (>600 m; ~0.05 % of total area). 175

METHODS 176

Seismic Footprint 177

Land-based seismic surveys in northern Alaska often consist of a truck-mounted surface 178

vibrator (e.g., AHV-IV™ Commander) that transmit seismic waves into the ground which are 179

then detected by a set of receivers set out in an array. Vibrator source vehicles can weigh 180

>27,000 kg and have a width up to 3.4 m 181

(https://d1cvtcw7p7ix4u.cloudfront.net/images2/downloads/AHV-IV-Commander-182

Datasheet.pdf?mtime=20181108112155; accessed 19 Jun 2019). The primary footprint 183

associated with terrestrial seismic surveys is the placement of source and receiver lines. Source 184

lines consist of transects where seismic energy source points are located. For vibrator sources, 185

the vibrator source vehicles traverse along the source lines and produce the source of seismic 186

waves. Geophones are placed along receiver lines to measure the seismic waves produced by the 187


seismic source (e.g., vibrators). For arctic acquisitions, tundra-permitted vehicles, such as 188

tracked vehicles (e.g., Tucker Sno CatsTM http://www.sno-cat.com/docs/1644-6-Passenger-189

Tucker-Terra-Flyer.pdf; accessed 19 Jun 2019), are typically driven along the receiver lines to 190

assist with the deployment of geophones. When vibrators are used, vibrator trucks drive along 191

the source lines periodically transmitting the seismic energy. Proposed seismic surveys in the 192

1002 Area state that receiver and source lines will be spaced at intervals of 200 m 193

(SAExploration 2018), similar to that proposed for the National Petroleum Reserve-Alaska 194

(Bureau of Land Management 2012). Receiver lines would run north to south across the area. 195

Conversely, source lines would run east to west and run perpendicular (Dabros et al. 2018, 196

SAExploration 2018). This pattern would continue across the entire study area, leading to a 197

maximum footprint depicted by a 200 m x 200 m grid (Fig. 1 inset). We assumed that support 198

vehicles and equipment for seismic operations (e.g., camps; SAExploration 2018:17) would be 199

moved along paths (i.e., existing source and receiver lines) created during the seismic survey. 200

We therefore did not consider additional disturbance associated with those activities. 201

Den Simulation 202

We developed a kernel density map of terrestrial polar bear dens in the 1002 Area 203

(discovered between 1984 – 2014) in program R (R Core Development Team 2017) using 204

package ‘adehabitatHR’ (Calenge 2006) based on den locations (n=33) discovered by tracking 205

VHF-radio telemetry and GPS-collared females (Durner et al. 2010, Supporting Information; 206

Fig. 1). We used an ad-hoc method (similar to Berger and Gese 2007) for determining the 207

bandwidth parameterization that resulted in a density map that was not over- or under-smoothed. 208

The commonly-used reference bandwidth parameter can over-smooth multimodal distributions, 209

such as our denning data (Kernohan et al. 2001). Conversely, the ad-hoc method minimizes 210


over-smoothing across a range of sample sizes and species (Schuler et al. 2014) and was shown 211

to outperform other commonly-used approaches (Kie 2013). The final bandwidth used was the 212

reference bandwidth (Worton 1995) value multiplied by 0.5. 213

We calculated that 20 dens could be present in the 1002 Area during any given winter 214

(Appendix A). We only allowed simulated dens to occur on suitable den habitat identified by 215

Durner et al. (2006). For each iteration of the model, we randomly distributed the dens across 216

the 1002 Area in areas identified as denning habitat (Durner et al. 2006), with the probability of a 217

den occurring at a given location being proportional to the density of dens predicted by the 218

kernel density map. We then determined the number of dens during each model iteration inside 219

the study area. 220

We assigned each simulated den an emergence date based on the emergence dates of 221

land-based denning bears in the SBS population (Rode et al. 2018, U.S. Geological Survey 222

2018). For each den, we drew a random emergence date from empirical den emergence dates of 223

land-based denning females in the SBS population (Rode et al. 2018, U.S. Geological Survey 224

2018). 225

Seismic Scenarios 226

We simulated the potential impacts to denning polar bears under five hypothetical 227

seismic survey designs, ranging from no spatial or temporal restrictions on survey efforts to 228

explicit times different regions of the 1002 Area could be surveyed. The range of scenarios also 229

have different levels of tradeoff for seismic operators. We assumed that two seismic crews 230

(which could consist of multiple vibe trucks) would operate 24 hours per day under each 231

scenario and that they could survey the entire study area between 1 Feb and 15 May. This would 232

allow for seismic activity to begin after any polar bear denning surveys were completed (e.g., 233


Amstrup et al. 2004) and before snow conditions deteriorated to an extent that vehicle travel was 234

no longer possible. 235

For Scenario 1 we imposed no spatial or temporal restrictions on when or where surveys 236

could occur. Under this scenario, it was assumed that seismic surveys could occur anywhere 237

across the study area at any time between 1 Feb and 15 May. From the perspective of seismic 238

operators, this scenario would provide the most flexibility in accomplishing a given survey and 239

allow for the entire study area to be surveyed. Decisions on where the survey progressed could 240

be made on the fly in relation to snow conditions or other logistical constraints. This scenario, 241

however, does not consider where polar bear dens are distributed or the timing of when polar 242

bears are likely to emerge from their dens, so will lead to larger levels of impact than more 243

restrictive survey designs. 244

To ensure that progression across the study area was not completely random (and 245

therefore more realistic), we divided the study area into 28 approximately-equal blocks (Fig. 2C, 246

D), corresponding to the area that a single seismic crew could cover in a week (~ 170 km2). We 247

then randomly-assigned each of the two seismic crews a block to begin their activity, with each 248

subsequent block surveyed being the closest un-surveyed block. For each iteration of the model, 249

a new progression across the study area was simulated to account for the complete uncertainty in 250

where activity could occur. 251

Scenario 2 restricted seismic surveys from occurring within 8 km of the coastline within 252

the study area, where most of the highest density of polar bear dens was visually-assessed to 253

occur (Fig. 2A). Outside of the coastal buffer, seismic surveys could occur anywhere and at any 254

time between 1 February and 15 May. We, therefore, followed the same approach taken for 255

Scenario 1 to simulate the seismic survey’s progression across the study area, but with fewer 1-256


week blocks (n=16) due to the reduced survey area (Fig. 2A). This scenario would help to 257

ensure that the areas with the highest density of dens in the 1002 Area would not be disturbed 258

due to seismic surveys. From the seismic operator’s perspective, however, the scenario would 259

not allow for the entire study area to be surveyed, possibly leading to loss of data in areas with 260

high potential for oil. The scenario would allow operators flexibility on how the survey 261

progressed outside of the coastal region. 262

Scenario 3 restricted seismic surveys from occurring in the area surrounding the two 263

highest density polar bear denning regions (Fig. 2B) of the study area until after 6 Mar (the date 264

of peak polar bear den emergence). Other areas were allowed to be surveyed beginning 1 Feb. 265

As in Scenarios 1 and 2, no restrictions were put on where activity occurred outside of the core 266

denning area or within the core denning area after 6 Mar. So, we took the same approach as 267

detailed for Scenarios 1 and 2 to allow for realistic progression of seismic surveys across the 268

study area, but that accounted for the uncertainty in where and when activity would occur. This 269

scenario allows survey operators to access the entire study area, but places restrictions on when 270

they can enter high-density polar denning region. If surveys are delayed for some reason, 271

operators might miss an opportunity to survey northern areas of the study area with high oil 272

potential. Similarly, if snow conditions deteriorated early in the season, those areas could miss 273

being surveyed. This scenario, however, does allow operators flexibility on how surveys 274

progress across the landscape aside from the start date restriction of the central and northwest 275

region of the study area. 276

For Scenarios 4 and 5, the 28 survey blocks were assigned specific dates that seismic 277

activity could begin. We attempted to assign dates later in the survey period to blocks with high 278

polar bear den density to increase the chances that dens would have emerged (and, therefore, not 279


be disturbed) by the time survey crews arrived. While these were subjectively assigned, this is a 280

process by which seismic operators and wildlife managers could utilize to develop potential 281

seismic survey designs in polar bear denning habitat. Scenario 4 assumed that all blocks would 282

be surveyed during a single winter, with block start dates ranging from 1 February to 3 May (Fig. 283

2C). Under Scenario 5, we assumed that seismic surveys would occur over the course of two 284

winters which allowed a later start date each winter, and thus more opportunity for emergence 285

from dens prior to the initiation of surveys. During the assumed two years of activity under 286

Scenario 5, block start dates ranged from 22 March to 3 May (Fig. 2D). Scenarios 4 and 5 allow 287

seismic operators to access the entire study area, but puts the most restrictions on the timing of 288

when activity can occur across the study area. This could be problematic if snow conditions 289

deteriorated earlier in the season that access was allowed for a given region of the study area or 290

some other logistical constraint occurred that kept crews from accessing an area at its assigned 291

time. Scenario 5 has the benefit of allowing a company to spread their resources across two 292

seasons. The later start date for operations, however, could be problematic if snow conditions 293

deteriorated early in either year. 294

Den Detection 295

As part of existing regulations in northern Alaska, the U.S. Fish and Wildlife Service 296

requires that oil and gas companies attempt to identify the location of polar bear dens prior to on-297

the-ground activities during winter (U.S. Fish and Wildlife Service 2016b). Forward-looking 298

infrared (FLIR) imagery is one tool that is commonly used to accomplish this task (Amstrup et 299

al. 2004). To obtain FLIR imagery, aerial surveys are conducted in December and January with 300

FLIR sensors mounted to either helicopters or airplanes along polar bear denning habitat (e.g., 301

Durner et al. 2006) in a region of interest. Imagery is monitored real-time and through post-hoc 302


review for “hot-spots” that have characteristics consistent with a polar bear den (Amstrup et al. 303

2004). Once dens are identified, a 1.6 km activity exclusion zone is placed around them (U.S. 304

Fish and Wildlife Service 2016b). Under optimal weather conditions (i.e., surface wind speeds 305

less than 11 km/hr; dew point-ambient temperature spread of > 3.0 ºC, and no visible moisture 306

such as fog or precipitation), detection of known polar bear dens has been estimated to approach 307

90% (Amstrup et al. 2004). Based on weather data from the community of Kaktovik, Alaska 308

(the closest community to the 1002 Area) during December and January (2013 – 2017; 309

https://www.ncdc.noaa.gov/cdo-web/datatools/lcd), optimal conditions for FLIR flights were 310

only present an average of 4.4% (SD=3.6%) of the time. 311

Estimates of FLIR efficacy also only reflect those dens that are available to be detected. 312

Depth of snow covering a den can significantly affect the probability that FLIR will be able to 313

detect a den (Robinson et al. 2014). Using artificial dens of varying depth, Robinson et al. 314

(2014) observed that dens with snow depth > 100 cm were not detectable with hand-held FLIR 315

devices. Interestingly, while Amstrup et al. (2004) was able to detect all dens at least once 316

during their multiple surveys, all dens surveyed had snow depths < 100 cm. 317

Because FLIR is likely to be used prior to any seismic surveys, we wanted to consider 318

what additional reduction in den disturbance could be achieved through a single FLIR survey 319

across the study area in addition to the different scenarios for seismic survey design. We 320

assumed that the FLIR survey occurred after all bears had entered maternal dens but prior to any 321

seismic survey activity was initiated. 322

Estimates for FLIR detection probability were published by Amstrup et al. (2004), but 323

only allow for estimates of detection under specific combinations of weather variables. For our 324

study, we required an estimate of average probability of detection under weather conditions 325


when surveys would occur. Figure 3 in Amstrup et al. (2004) summarizes the detections/non-326

detections of 23 known dens across surveys and provide sufficient data to calculate an average 327

probability of detecting a den. 328

We estimated the detection rate for dens “available” to be detected by FLIR (i.e., having 329

a den wall less than 100 cm). We used data from Figure 3 in Amstrup et al. (2004) and restricted 330

data to on those surveys that occurred in darkness or civil twilight as daylight leads to an 331

inability to detect dens with FLIR. Amstrup et al. (2004) stated that during 8 den detection 332

attempts, daylight was present and that none of these dens were detected. However, Amstrup et 333

al. (2004) did not indicate which dens were surveyed during periods of daylight. Therefore, to 334

account for this uncertainty in the data, we took a multiple imputation approach (Gelman et al. 335

2004) to iteratively assign, and remove from the analysis, which non-detections (n=8) in the data 336

were the result of a survey with daylight (see Supporting Information for R code used to perform 337

the multiple imputation). With the imputated data, we estimated the overall probability, p, that a 338

den was detected during a single survey in a Bayesian framework with the following model: 339

ni~Binomial(p, Ni) where ni was the number of times den i was observed across Ni surveys. We 340

gave p an uniform prior distribution of: p~Uniform(0,1). For the Bayesian model, we allowed a 341

burn-in period of 50,000 iterations. We then obtained 50,000 iterations from the model, and 342

thinned those by 50, resulting in a total of 1,000 samples from the posterior distribution. We 343

used the package ‘rjags’ (Plummer 2018) in program R (R Core Development Team 2017) to 344

conduct the Bayesian analysis (Supporting Information). 345

As discussed above, not all dens are available to be detected by FLIR due to snow depth. 346

Durner et al. (2003) found that the average depth of snow above the main chamber of actual dens 347

was 72 cm (SD=87). We therefore used the mean and standard deviation reported by Durner et 348


al. (2003) to generate a gamma distribution using the method of moments to derive the shape and 349

scale parameters. The shape parameter equaled 722/872 and the scale parameter equaled 72/872. 350

We then sampled from this gamma distribution to obtain the snow depth above each simulated 351

den and assumed that any den with a depth > 100 cm could not be detected with FLIR. 352

For each iteration of seismic model (below), we randomly sampled one value from the posterior 353

distribution of FLIR detection probability to determine the probability that available dens would 354

be detected during the simulated FLIR survey. 355

Modeling 356

For each of the above scenarios, we used Monte Carlo simulation, with 1,000 iterations to 357

account for variation in the distribution of dens across the 1002 Area, den emergence dates, den 358

snow depth, probability of den detection with FLIR, and survey progression (for Scenarios 1-3). 359

We assumed that the locations of seismic lines (i.e., source and receiver lines) were fixed and, 360

therefore, did not vary between model iterations. For each iteration of the model, we determined 361

the number of dens that were within the area of proposed activity of a given scenario and the 362

number of dens that were within 1.6 km of seismic activity (i.e., potentially disturbed). Thus, 363

even if a den was outside of the area of proposed activity for a given scenario, it could still be 364

disturbed if it was within 1.6 km of activity. The choice of a 1.6 km disturbance buffer is the 365

same used by the U.S. Fish and Wildlife Service in Incidental Take Regulations that have been 366

issued under the Marine Mammal Protection Act based on research by MacGillivray et al. 367

(2003). We, therefore, used it in our analysis to be consistent with current management practices 368

of the agency. 369

We assumed that denning bears could emerge prior to survey activities occurring near 370

them based on a den’s simulated den emergence date. Thus, only those dens that had not 371


emerged prior to seismic activity coming within 1.6 km were considered potentially disturbed. 372

While bears can remain at dens for up to two weeks post emergence (Smith et al. 2007), no 373

studies have documented a negative demographic effect of disturbance post-emergence (although 374

this does not mean that they do not exist), so we did not consider bears at dens post-emergence to 375

be disturbed as part of our denning analysis. For each iteration of the model, we also measured 376

the distance between dens and the closest seismic activity that occurred to them. Finally, during 377

each iteration, we recorded the number of active dens (i.e., those that had not yet emerged) 378

within the 3 m footprint of seismic vehicles operating along seismic lines. See Supporting 379

Information for all modeling code. 380

RESULTS 381

We estimated that the probability of an “available” den (i.e., with snow depth < 100 cm) 382

being detected with a single FLIR survey was 0.74 (95% Credible Interval: 0.62 – 0.84). Across 383

the 1,000 iterations of the model, nearly all of the 20 dens simulated inside the 1002 Area were 384

located within the study area (�̅�𝑥 = 19.4; 95% Confidence Interval 18 – 20). The total footprint of 385

activity associated with source and receiver lines (i.e., directly under vehicles associated with the 386

seismic survey) was 145 km2, representing 3% of the total study area. The total footprint of 387

potential disturbance, assuming bears would be disturbed within 1.6 km of activity, covered 388

100% of the study area given the short spacing between source and receiver line arrays. 389

Without FLIR surveys, Scenario 1 had the highest number of dens estimated to 390

potentially be disturbed, followed by Scenarios 2 and 3 (Table 1). Given the lack of spatial or 391

temporal specificity of activities simulated in Scenario 1, a larger number of dens within the 392

study area could potentially be exposed, as well as increased uncertainty in the number of dens 393

exposed (Table 1). Even though Scenario 3 restricted activity in high density denning areas until 394


after peak emergence, by definition, over half of dens had yet to emerge, and were therefore 395

highly likely to occur in that area and be exposed to subsequent disturbance. While the spatial 396

restrictions along the coast imposed under Scenario 2 reduced the number of dens disturbed from 397

Scenario 1, it still resulted in an average of >5 dens being disturbed (Table 1). Scenarios 4 and 5 398

had the lowest number of dens potentially exposed to disturbance, with Scenario 5 having the 399

lowest levels of disturbance recorded across scenarios. Scenario 5 led to a >90% decline in the 400

average number of dens potentially exposed to seismic activity compared to Scenario 1 (Table 401

1). 402

The average distance to activity was similarly variable across scenarios, with Scenario 2 403

having the shortest average distance to activity and Scenario 5 having the longest (Table 1). 404

Scenario 5 resulted in a >300% increase in the average distance between dens and seismic 405

activity compared to Scenario 2. Across all scenarios, the average number of dens directly 406

overlapped by seismic activity during a given iteration of the model was <1 (Table 1). The 407

probability that ≥1 den would overlap with a simulated seismic survey footprint varied across the 408

5 scenarios. Scenario 1 had the highest probability of activity overlapping a den (0.21), followed 409

by Scenario 3 (0.17), Scenarios 2 and 4 (0.14), and Scenario 5 (0.01). 410

When allowing a single FLIR survey prior to seismic activities, the pattern of which 411

scenarios led to the lowest level of potential disturbance to dens was the same. Forward looking 412

infrared surveys, however, reduced the potential for disturbance to polar bear dens. Across all 413

scenarios, there was approximately a 70% reduction in the number of dens estimated to be 414

potentially disturbed by seismic activities (Table 1). The probabilities of activity overlapping a 415

den was similarly reduced (Scenario 1: 0.07; Scenario 2: 0.03; Scenario 3: 0.05; Scenario 4: 416


0.04; Scenario 5: 0.00). Even with FLIR, Scenarios 1-4 still had potential levels of disturbance 417

higher than estimated for Scenario 5 without a FLIR survey (Table 1). 418

DISCUSSION 419

Our study showed that large reductions in disturbance to denning polar bears can occur 420

through strategic planning relative to the timing and distribution of proposed seismic activities, 421

even when surveys are planned in areas with a high density of polar bear dens. Our results 422

highlight that seismic activity can take place across large areas while still ensuring that 423

disturbance to denning polar bears is kept to low levels. Scenarios with no temporal restrictions 424

(Scenarios 1 and 2) or minimal temporal restrictions (Scenario 3) on where surveys could occur 425

had the highest levels of impact to polar bears. In an attempt to make progression across the 426

study as realistic as possible, we allowed activity to progress in a systematic fashion. This 427

allowed for consideration of emergence from dens prior to activity occurring adjacent to them. 428

However, from the perspective of a management agency trying to understand the potential level 429

of impact to denning bears, not knowing when or where activity could occur requires the 430

assumption that activity could encounter any den at any time during the survey period. This 431

limitation highlights the value of coordinated approaches between industry and resource 432

management agencies when developing proactive conservation plans (Hebblewhite 2017). Even 433

based on the approach we took for simulating survey progression, Scenarios 1-3 tended to have 434

higher levels of uncertainty in parameter estimates (Table 1) which would likely require a more 435

conservative approach by the management agency in charge of permitting the seismic survey. 436

For example, even though under Scenario 1 (without FLIR), the mean number of dens disturbed 437

was 8 (Table 1), the upper value of the 95% CI was 14, and the maximum recorded from the 438

1000 iterations of the model was 16 (i.e., 80% of simulated dens in the 1002 Area). 439


The addition of a single FLIR survey prior to seismic activity substantially reduced 440

(70%) the number of dens estimated to be disturbed under all scenarios. Similar to the results 441

without FLIR, however, Scenario 5 was the only one that had an estimate of the numbers of dens 442

disturbed < 1 with FLIR. This highlights the importance of considering how a seismic survey 443

progresses across a landscape during the denning period and not solely relying on other 444

mitigation measures, such as FLIR, to obtain the desired outcome of minimizing disturbance to 445

denning polar bears. Due to a lack of information, we made a number of assumptions related to 446

FLIR efficacy that could alter the results with additional data. First, data in Amstrup et al. 447

(2004) were obtained from known dens which likely led to a positive bias in detection rates for 448

dens. Similarly, Amstrup et al. (2004) used a helicopter for their surveys rather than a fixed-449

wing aircraft which is more typically used by industry. The use of a helicopter also likely 450

increased the probability of detection because it allowed observers on board greater ability to 451

view a potential den from different angles or remain stationary to more thoroughly assess the 452

hotspot. Conversely, the data from Amstrup et al. (2004) are nearly 20 years old, so 453

technological advances could potentially have led to more sensitive sensors that could have 454

higher rates of detection. Additionally, we used a 100 cm threshold to assign a den as being 455

available or unavailable for detection with FLIR. It is more likely that a functional relationship 456

exists between snow depth and detection with FLIR, where dens with snow depth >100 cm have 457

some declining probability of detection > 0%. While there is clearly uncertainty surrounding 458

FLIR’s effectiveness at detecting polar bear dens, the data we used are currently the best 459

available information that exist which is the standard required for the U.S. Fish and Wildlife 460

Service to use information in developing regulations. 461


For our analysis, we assumed that seismic grids would be spaced at intervals of 200 m, 462

which has been proposed for the 1002 Area (SAExploration 2018). Operators conducting 3D 463

seismic surveys, however, can have spacing varying from 50 m (Dabros et al. 2018) to 400 m 464

(Bureau of Land Management 2012). Thus, our choice was within the range of distances 465

typically used. For distances shorter than 200 m, the only portion of our results that would differ 466

significantly would be the probability of a den being within the footprint of the seismic survey. 467

Only if seismic line spacing was >1.6 km would our estimates of the number of dens disturbed 468

by seismic activity begin to decrease. Even then, the relative differences between surveys would 469

remain similar to our present analysis. 470

Our analysis makes the implicit assumption that any pre-emerged den within 1.6 km of a 471

survey will experience disturbance, and as a result, could suffer reduced cub survival (Rode et al. 472

2018). This is likely an over-estimate of impact given that a den that is disturbed a month earlier 473

than its intended emergence is treated as having the same impact to cub survival as one that is 474

disturbed one day prior to its intended emergence. By the time cubs emerge in April, they have 475

well-developed fur for insulation, so any additional time in the den is unlikely to have the same 476

effect on survival as earlier in winter when cubs only have modest thermoregulatory abilities and 477

rely on the den’s insulation and their mother for warmth (Blix and Lentfer 1979). Unfortunately, 478

such a relationship has yet to be estimated for polar bears, so we could not use it to inform our 479

analysis. While this is an important point to consider when trying to estimate the actual level of 480

disturbance to bears of a proposed survey, the results of our analysis should remain unchanged, 481

given that the goal was to highlight the relative differences across scenarios. A benefit of our 482

modeling approach is that once this type of information becomes available, the model can be 483

easily updated to account for the new information. 484


The actual distances maternal denning polar bears respond to disturbance from seismic 485

activity and the magnitude of their response are variable (Amstrup 1993) and not well-486

understood. The U.S. Fish and Wildlife Service uses a 1.6 km buffer around detected dens 487

adjacent to industrial activity to mitigate potential disturbance. This arose from a study that 488

found noise and vibrations from seismic surveys could be detected inside artificial dens up to 2 489

km away (MacGillivray et al. 2003). Whether stimuli at these distances would result in 490

abandonment or early emergence is not known. Thus, if the threshold distance at which 491

disturbance can occur is lower than the 1.6 km used here, the magnitude of differences we 492

observed across the different survey designs could be biased high. 493

The current level of lethal polar bear takes from sources such as subsistence harvest by 494

Alaska Natives does not allow any additional lethal take under the MMPA from other sources, 495

such as those that could occur during seismic surveys. Given the documented negative effects to 496

cub survival of early den emergence (Rode et al. 2018), nearly all dens need to remain 497

undisturbed for seismic surveys to meet the requirements of the MMPA. Even with detection of 498

dens with FLIR, Scenario 1 could still lead to disturbance of an average of 2.4 dens (Table 1), 499

which could mean an average of 4.8 cubs could emerge early (assuming a litter size of two cubs) 500

and suffer reduced survival. The only scenario that had an average of ≤ 1 cub suffering reduced 501

survival as a result of early den emergence was Scenario 5, with and without a FLIR survey. 502

These results highlight the importance of incorporating spatial and temporal considerations into 503

survey designs, in combination with other mitigation measures. 504

Our analysis did not provide a final answer to seismic operators on how surveys need to 505

be designed given our lack of intimate or proprietary knowledge of financial or logistical 506

limitations companies face. However, our results provide seismic operators guidance on initial 507


survey design considerations to increase the chances, and reduce the time required, to develop a 508

final plan that will meet regulatory requirements. By identifying designs and mitigations 509

measures that reduce impacts to bears, while still allowing proposed activities to occur, the time 510

between when seismic operators seek approval for their activities and when permits are issued 511

can be reduced, thereby meeting the goals of the CMP for polar bear conservation and 512

minimizing the economic impact on seismic operations. 513

MANAGEMENT IMPLICATIONS 514

Our study highlights that with sufficient planning and effective mitigation measures, the 515

effects to denning bears could likely be reduced sufficiently to allow seismic operators to 516

complete their work over large areas. Seismic operators and wildlife managers should consider 517

design differences when planning future surveys as starting points to help achieve desired levels 518

of protection for denning polar bears. The use of analytical models, such as ours, have been 519

shown to be important tools for helping to inform land-management decisions prior to the 520

initiation of human activities (Copeland et al. 2009, Katzner et al. 2012, Suzuki and Parker 2019, 521

Wilson et al. 2013). While our model was designed for denning polar bears in the 1002 Area, its 522

general structure can be used as a template for polar bear studies elsewhere throughout their 523

range or by others attempting to minimize disturbance of human activities on wildlife. 524

ACKNOWLEDGMENTS 525

We would like to thank D. Gustine, A. Derocher, T. Atwood, G. Hildebrand, M. 526

Colligan, P. Lemons, C. Krenz, B. Taras, D. Scheidler, J. Pearce, F. van Manen, K. Lewis, and 527

an anonymous reviewer for providing comments on an earlier version of this manuscript. P. 528

Lemons, K. Klein, C. Putnam, and M. Colligan provided valuable insights during the 529

development of the model used in this analysis. P. Lemons and M. Colligan provided 530


considerable support during the publication process and provided background on the MMPA for 531

the article. This article has been peer-reviewed and approved by USGS under their Fundamental 532

Science Practices policy (http://pubs.usgs.gov/circ/1367). Any use of trade, product or firm 533

names is for descriptive purposes only and does not imply endorsement by the U.S. Government. 534

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Associate Editor:690


Figure captions 691

Figure 1. Overview of the study area, depicting the 1002 Area (black outline on main map) 692

within the Arctic National Wildlife Refuge (ANWR) in northeastern Alaska. The non-shaded 693

region (i.e., non-grayed out area) of the main map represents the combined area with high and 694

medium hydrocarbon potential identified by the Bureau of Land Management. The underlying 695

heat map depicts the relative density of polar bear dens derived from a kernel density estimate 696

based on the known polar bear dens (triangles; discovered between 1984 – 2014). Yellow linear 697

features represent potential denning habitat identified from topographic features capable of 698

capturing sufficient snow for polar bears to excavate maternal dens. The inset in the lower right 699

shows the simulated layout of the source and receiver lines for the seismic survey. This pattern 700

is repeated across the entire non-shaded study area. Given the density of the lines, it was not 701

possible to depict the simulated seismic lines across the entire study area. 702

Figure 2. Schematics of showing detail of the simulated seismic conditions for Scenarios 2-5 703

across the study area. All maps show an underlying depiction of the relative polar bear den 704

density in the study area, ranging from high density (brown) to low density (purple). Each map 705

also contains blocks (blocks outlined by solid black) representing areas that could be surveyed 706

during a one week period. Scenario 2 (A) shows a 8 km coastal buffer (i.e., hashed area of the 707

map) within which seismic surveys would not be allowed. Activity would be allowed to occur at 708

any time after 1 Feb in any of the identified blocks. Scenario 3 (B) shows a region (i.e., hashed 709

area of the map) within which activity could not begin until 6 Mar. After 6 Mar, activity could 710

occur in any of those blocks. Activity could occur in any of the remaining blocks after 1 Feb. 711

Scenarios 4 (C) and 5 (D) give specific dates that seismic activity could start in each block, with 712


Scenario 5 (D) allowing for activity to occur during two winters rather than one in Scenario 4 713

(C). 714


Table 1. Summary statistics (i.e., mean and 95% confidence intervals) of the impacts to denning

polar bears of winter seismic surveys in the 1002 Area of the Arctic National Wildlife Refuge,

Alaska, under five different survey designs (Scenarios) with and without a single forward-

looking infrared (FLIR) survey prior to seismic activity; labeled as FLIR and No FLIR,

respectively. Scenarios range from no spatial or temporal restrictions on seismic activities

(Scenario 1) to high spatial and temporal specificity (Scenario 5). Each scenario used Monte

Carlo simulation and was run for a total of 1,000 iterations. The number of dens disturbed

summarizes the number of dens that had not yet emerged and were within 1.6 km (1 mi) or

seismic survey lines. Distance to activity provides the overall average of the average distance of

dens to seismic activity prior to emergence for each iteration of the model. Dens overlapped

represents the mean number of dens that overlapped with the physical footprint of seismic

vehicles across model iterations for each scenario. These dens can be viewed as those that are

run over and potentially crushed by vehicles associated with seismic surveys.


Summary for online Table of Contents: The design of winter seismic surveys can lead to large

differences in the number of polar bear dens disturbed. Strategic pre-planning may therefore be

necessary to reduce disturbance and potential negative impacts to polar bears.

Metric

Dens Disturbed

(n)

Distance to Activity (km) Dens Overlapped (n)

Scenario �̅�𝑥 95% CI �̅�𝑥 95% CI �̅�𝑥 95% CI

1–No FLIR 8.0 3 – 14 14.7 4.3 – 33.7 0.21 0 – 1

1–FLIR 2.4 0 – 6 15.3 4.8 – 33.6 0.07 0 – 1

2–No FLIR 5.9 2 – 10 10.6 4.4 – 21.8 0.14 0 – 1

2–FLIR 1.8 0 – 5 10.7 4.5 – 21.9 0.03 0 – 1

3–No FLIR 5.9 2 – 10 18.7 7.5 – 38.0 0.17 0 – 1

3–FLIR 1.7 0 – 4 19.5 7.9 – 39.7 0.05 0 – 1

4–No FLIR 4.5 1 – 9 14.0 8.6 – 38.0 0.14 0 – 1

4–FLIR 1.4 0 – 4 14.2 9.2 – 19.5 0.05 0 – 1

5–No FLIR 0.5 0 – 2 42.2 20.7 – 65.1 0.01 0 – 1

5–FLIR 0.2 0 – 1 42.6 19.1 – 68.0 0.00 0 – 0


Summary:

Large reductions in the probability of disturbance can occur through careful planning on the

timing and distribution of proposed activities even when surveys are planned in areas with a high

density of polar bear dens. Even with additional mitigation measures, such as aerial infrared

surveys, seismic survey design led to the largest reductions in potential disturbance to polar bear

dens.


APPENDIX A. CALCULATION OF THE EXPECTED NUMBER OF DENS DURING

WINTER IN THE 1002 AREA OF THE ARCTIC NATIONAL WILDLIFE REFUGE,

ALASKA.

We developed a framework with which to estimate how many polar bear dens might be disturbed

by seismic activity that is planned for the 1002 Area in winter. This first required an estimate of

the potential number of dens that could occur in a given year within the 1002 Area derived from

peer-reviewed studies. While there have been no formal analyses to estimate the number of polar

bears that form maternal dens in the 1002 Area, a number of studies have published parameters

that can be used to develop such an estimate. The parameters required to develop an estimate of

the number of dens include:

• Estimated population size (Bromaghin et al. 2015)

• Proportion of adult females in the population (Bromaghin et al. 2015)

• Breeding probability of adult females (Regehr et al. 2010)

• Proportion of dens that occur on land vs. sea ice (Olson et al. 2017)

• Proportion of dens that occur on land in the 1002 Area (Durner et al. 2010)

Bromaghin et al. (2015) estimated the size of the SBS subpopulation to be 907 polar

bears (90 percent Confidence Interval: 606 to 1212) in 2010. Additionally, Bromaghin et al.

(2015) provided information on the number of adult females that were captured each year from

2001 to 2010. These data indicated that, on average, the population was composed of 35.1

percent adult females (SD=3.8). Using these data to determine the percent of adult females

(PAF) in the population assumes that captured individuals comprised a representative sample of

the population.


Regehr et al. (2010) provides estimates of the breeding probability for adult females in

the SBS subpopulation. This includes two components; 1) the probability of a female without

cubs breeding and producing a litter, and 2) a female that has a litter loses her cubs and rebreeds

in a given year. Regehr et al. (2010) reports the estimates of these parameters to be 0.437

(Pbreed0; 90 percent CI: 0.33 to 0.56) and 0.104 (Pbreed1; 90 percent CI: 0.02 to 0.38),

respectively.

Based on collar data from SBS bears from 2007 to 2013, Olson et al. (2017) found that

55.2%(16 of 29) of adult females denned on land versus sea ice (Pland = 0.55). The proportion of

dens that occur in the 1002 Area was derived from the U.S. Geological Survey database of all

known dens for polar bears in the SBS subpopulation from 1910 to 2010 (Durner et al. 2010).

We restricted these data to only dens from 2000 to 2010 that were detected by satellite radio

collars. This ensured that den observations were not skewed towards areas with industrial

activity or communities, where dens might be more readily observed. There were a total of 39

dens that occurred on land, and of those, 9 occurred in the 1002 Area, resulting in an estimate of

23.1 percent of land-based SBS polar bear dens occurring in the 1002 Area in any given year

(PCoastal Plain=0.23). This estimate assumes that the den data obtained from VHF and satellite

radio collars are representative of the entire population, and not just those in the area where bears

are available to be captured and collared.

From this information, the number of dens in the 1002 Area was derived from the following

calculations. First, we obtained the estimated number of adult females (NAF) in the population:

NAF=N2010×PAF=907×0.35=317.5.

Then, we estimated the number of adult females that bred (Nbreed) in a given year:

Nbreed=NAF×Pbreed0+NAF×Pbreed0×Pbreed1=(317.5×0.437)+(317.5×0.437×0.104)=153.2.


We next estimated the number of denning females that occur on land (Nland):

Nland=Nbreed×Pland=153.2×0.552=84.5.

Finally, we estimated the total number of land dens in the 1002 Area in a given year

(NCoastal Plain): NCoastal Plain=Nland×PCoastal Plain=84.5×0.231=19.5.

The total number of polar bear dens in the 1002 Area in a given year was calculated to be 19.5.

As it is not possible to have a partial den, we rounded this number up to 20 dens as a

conservative estimate of the total number of dens expected to occur in the 1002 Area in any one

year.

Bromaghin, J.F., T.L. McDonald, I. Stirling, A.E. Derocher, E.S. Richardson, E.V. Regehr, D.C.

Douglas, G.M. Durner, T. Atwood, S.C. Amstrup. 2015. Polar bear population dynamics

in the southern Beaufort Sea during a period of sea ice decline. Ecological Application

25:634-651.

Durner, G.M., Fischbach, A.S., Amstrup, S.C., and Douglas, D.C., 2010. Catalogue of polar bear

(Ursus maritimus) maternal den locations in the Beaufort Sea and neighboring regions,

Alaska, 1910–2010: U.S. Geological Survey Data Series 568. U.S. Geological Survey,

Reston, Virginia, USA.

Olson, J.W., K.D. Rode, D.L. Eggett, T.S. Smith, R.R. Wilson, G.M. Durner, A.S. Fischbach,

T.C. Atwood, and D.C. Douglas. 2017. Collar temperature sensor data reveal long-term

patterns in southern Beaufort Sea polar bear den distribution on pack ice and land.

Marine Ecology Progress Series. 564:211-224.

Regehr, E.V., C.M. Hunter, H. Caswell, S.C. Amstrup, and I. Stirling. 2010. Survival and

breeding of polar bears in the southern Beaufort Sea in relation to sea ice. Journal of

Animal Ecology 79:117-127.


SUPPORTING INFORMATION

We have included an R workspace (“analysis.RData”) that contains all of the files and output

from the analysis. We also include annotated R code required to run the analysis

(“analysis_code.R”). The files “missed.dens.funcAnalysis.R”, “survey.func.R”, and

“survey.func.R” are all files that will need to uploaded into the R workspace, but the code for

doing that is included in “analysis_code.R”. The file “FLIR_Code.R” is an R script to run the

Bayesian analysis to estimate the probability of FLIR detecting a den, and “detec.prob.R” is the

JAGS model code for the model used in “FLIR_Code.R”. The program JAGS (http://mcmc-

jags.sourceforge.net/) will need to be installed on your computer before you can run the Bayesian

analysis code. Finally, we include all of the dens used for the development of the den density

map “dens_1002.csv”.

This software is preliminary or provisional and is subject to revision. It is being provided

to meet the need for timely best science. The software has not received final approval by the U.S.

Geological Survey (USGS). No warranty, expressed or implied, is made by the USGS or the U.S.

Government as to the functionality of the software and related material nor shall the fact of

release constitute any such warranty. The software is provided on the condition that neither the

USGS nor the U.S. Government shall be held liable for any damages resulting from the

authorized or unauthorized use of the software.

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