Tempo-spatial patterns of PM2.5 measured using a portable particulate monitor around a mine complex in Canada's Arctic.

Mining activities in Canada's pristine Arctic (e.g., driving on unpacked roads, blasts, rock grinding, diesel combustion, and garbage incineration) could add local sources of airborne fine particulate matter with a diameter of < 2.5 µm (PM2.5) to their surrounding area. The increase in PM2.5 above the background level around a mine represents a potential disturbance to caribou. To quantify the spatial distribution of the elevated PM2.5, we investigated three different sampling schemes to measure PM2.5 concentration using a portable monitor. We found that the best sampling scheme was to use the regional background PM2.5 as the reference and analyze the anomaly of PM2.5 measured at sites around the mine complex from the background level. The regional background PM2.5 values were measured at the Daring Lake Tundra Research Station during 2018 and 2019. Our results indicated that the background PM2.5 was not a low and constant value but varied with rain events, wind direction, and the impacts of forest fire smoke. After excluding periods affected by forest fires smokes, we found the background PM2.5 was close to 0 µg m-3 for the first few hours after rain, and then increased logistically with the time after rain (tar) to the maximum of 5 (or 10) µg m-3 when the wind came from the north (or south) of the NW-SE axis. The NW-SE axis in western Canada divides the tundra north with few anthropogenic PM2.5 sources from the forested south with many PM2.5 sources from forest fire smokes and human activities. Analyses of PM2.5 anomaly from the background (i.e., PM2.5 measured at a site around the mining complex-the background level at the corresponding tar and wind direction) revealed that the zone of elevated PM2.5 around the mine (Zepm) expanded with tar. In the first few hours after rain, PM2.5 was close to 0 everywhere except within meters of a source (e.g., a truck exhaust) in the downwind direction. During tar = 6 to 96 h, Zepm expanded to 6.3 km in the downwind direction when the wind came from south of the NW-SE axis. A similar result was found in the downwind direction when the wind came from north of the NW-SE axis, with Zepm = 4.4 km. In the upwind direction, the value of Zepm was much smaller, being 0.7 km (or 1.0 km) when the wind came from the north (or south) of the NW-SE axis. For the period of tar between 96 and 192 hours, Zepm further expanded to 21.2 km when the wind from the south of the NW-SE axis. The results from this study indicated that this reference paradigm that uses the regional background PM2.5 as the reference in combination with a portable PM2.5 monitor worked well for quantifying the tempo-spatial patterns of PM2.5 at locations in remote and mostly pristine Arctic. However, their effectiveness for other regions needs further investigation.

Using bear rub data and spatial capture-recapture models to estimate trend in a brown bear population.

Trends in population abundance can be challenging to quantify during range expansion and contraction, when there is spatial variation in trend, or the conservation area is large. We used genetic detection data from natural bear rubbing sites and spatial capture-recapture (SCR) modeling to estimate local density and population growth rates in a grizzly bear population in northwestern Montana, USA. We visited bear rubs to collect hair in 2004, 2009-2012 (3,579-4,802 rubs) and detected 249-355 individual bears each year. We estimated the finite annual population rate of change 2004-2012 was 1.043 (95% CI = 1.017-1.069). Population density shifted from being concentrated in the north in 2004 to a more even distribution across the ecosystem by 2012. Our genetic detection sampling approach coupled with SCR modeling allowed us to estimate spatially variable growth rates of an expanding grizzly bear population and provided insight into how those patterns developed. The ability of SCR to utilize unstructured data and produce spatially explicit maps that indicate where population change is occurring promises to facilitate the monitoring of difficult-to-study species across large spatial areas.

Using spatial mark-recapture for conservation monitoring of grizzly bear populations in Alberta.

One of the challenges in conservation is determining patterns and responses in population density and distribution as it relates to habitat and changes in anthropogenic activities. We applied spatially explicit capture recapture (SECR) methods, combined with density surface modelling from five grizzly bear (Ursus arctos) management areas (BMAs) in Alberta, Canada, to assess SECR methods and to explore factors influencing bear distribution. Here we used models of grizzly bear habitat and mortality risk to test local density associations using density surface modelling. Results demonstrated BMA-specific factors influenced density, as well as the effects of habitat and topography on detections and movements of bears. Estimates from SECR were similar to those from closed population models and telemetry data, but with similar or higher levels of precision. Habitat was most associated with areas of higher bear density in the north, whereas mortality risk was most associated (negatively) with density of bears in the south. Comparisons of the distribution of mortality risk and habitat revealed differences by BMA that in turn influenced local abundance of bears. Combining SECR methods with density surface modelling increases the resolution of mark-recapture methods by directly inferring the effect of spatial factors on regulating local densities of animals.

Can concentrations of steroid hormones in brown bear hair reveal age class?

Although combining genetic and endocrine data from non-invasively collected hair samples has potential to improve the conservation of threatened mammals, few studies have evaluated this opportunity. In this study, we determined if steroid hormone (testosterone, progesterone, estradiol and cortisol) concentration profiles in 169 hair samples collected from free-ranging brown bears (Ursus arctos) could be used to accurately discriminate between immature and adult bears within each sex. Because hair samples were acquired opportunistically, we also needed to establish if interactions between hormones and several non-hormone factors (ordinal day, year, contact method, study area) were associated with age class. For each sex, we first compared a suite of candidate models by Akaike Information Criteria model selection, using different adult-age thresholds (3, 4 and 5 years), to determine the most supported adult age. Because hair hormone levels better reflect the endocrine state at an earlier time, possibly during the previous year, then at the time of sampling, we re-analysed the data, excluding the records for bears at the adult-age threshold, to establish if classification accuracy improved. For both sexes, candidate models were most supported based on a 3-year-old adult-age threshold. Classification accuracy did not improve with the 3-year-old bear data excluded. Male age class was predicted with a high degree of accuracy (88.4%) based on the concomitant concentrations of all four hormones. Female age class was predicted with less accuracy (77.1%) based only on testosterone and cortisol. Accuracy was reduced for females, primarily because we had poor success in correctly classifying immature bears (60%) whereas classification success for adult females was similar to that for males (84.5%). Given the small and unbalanced sample used in this study, our findings should be viewed as preliminary, but they should also provide a basis for more comprehensive future studies.

The quantification of reproductive hormones in the hair of captive adult brown bears and their application as indicators of sex and reproductive state.

Recognizing the potential value of steroid hormone measurements to augment non-invasive genetic sampling, we developed procedures based on enzyme-linked immunoassays to quantify reproductive steroid hormone concentrations in brown bear (Ursus arctos) hair. Then, using 94 hair samples collected from eight captive adult bears over a 2-year period, we evaluated (i) associations between hair concentrations of testosterone, progesterone, estradiol and cortisol; (ii) the effect of collecting by shaving vs. plucking; and (iii) the utility of reproductive hormone profiles to differentiate sex and reproductive state. Sample requirements (125 mg of guard hair) to assay all hormones exceeded amounts typically obtained by non-invasive sampling. Thus, broad application of this approach will require modification of non-invasive techniques to collect larger samples, use of mixed (guard and undercoat) hair samples and/or application of more sensitive laboratory procedures. Concentrations of hormones were highly correlated suggesting their sequestration in hair reflects underlying physiological processes. Marked changes in hair hormone levels during the quiescent phase of the hair cycle, coupled with the finding that progesterone concentrations, and their association with testosterone levels, differed markedly between plucked and shaved hair samples, suggests steroids sequestered in hair were likely derived from various sources, including skin. Changes in hair hormone concentrations over time, and in conjunction with key reproductive events, were similar to what has been reported concerning hormonal changes in the blood serum of brown bears. Thus, potential for the measurement of hair reproductive hormone levels to augment non-invasive genetic sampling appears compelling. Nonetheless, we are conducting additional validation studies on hair collected from free-ranging bears, representative of all sex, age and reproductive classes, to fully evaluate the utility of this approach for brown bear conservation and research.

Development and application of an antibody-based protein microarray to assess physiological stress in grizzly bears (Ursus arctos).

A novel antibody-based protein microarray was developed that simultaneously determines expression of 31 stress-associated proteins in skin samples collected from free-ranging grizzly bears (Ursus arctos) in Alberta, Canada. The microarray determines proteins belonging to four broad functional categories associated with stress physiology: hypothalamic-pituitary-adrenal axis proteins, apoptosis/cell cycle proteins, cellular stress/proteotoxicity proteins and oxidative stress/inflammation proteins. Small skin samples (50-100 mg) were collected from captured bears using biopsy punches. Proteins were isolated and labelled with fluorescent dyes, with labelled protein homogenates loaded onto microarrays to hybridize with antibodies. Relative protein expression was determined by comparison with a pooled standard skin sample. The assay was sensitive, requiring 80 µg of protein per sample to be run in triplicate on the microarray. Intra-array and inter-array coefficients of variation for individual proteins were generally <10 and <15%, respectively. With one exception, there were no significant differences in protein expression among skin samples collected from the neck, forelimb, hindlimb and ear in a subsample of n = 4 bears. This suggests that remotely delivered biopsy darts could be used in future sampling. Using generalized linear mixed models, certain proteins within each functional category demonstrated altered expression with respect to differences in year, season, geographical sampling location within Alberta and bear biological parameters, suggesting that these general variables may influence expression of specific proteins in the microarray. Our goal is to apply the protein microarray as a conservation physiology tool that can detect, evaluate and monitor physiological stress in grizzly bears and other species at risk over time in response to environmental change.

The impact of roads on the demography of grizzly bears in Alberta.

One of the principal factors that have reduced grizzly bear populations has been the creation of human access into grizzly bear habitat by roads built for resource extraction. Past studies have documented mortality and distributional changes of bears relative to roads but none have attempted to estimate the direct demographic impact of roads in terms of both survival rates, reproductive rates, and the interaction of reproductive state of female bears with survival rate. We applied a combination of survival and reproductive models to estimate demographic parameters for threatened grizzly bear populations in Alberta. Instead of attempting to estimate mean trend we explored factors which caused biological and spatial variation in population trend. We found that sex and age class survival was related to road density with subadult bears being most vulnerable to road-based mortality. A multi-state reproduction model found that females accompanied by cubs of the year and/or yearling cubs had lower survival rates compared to females with two year olds or no cubs. A demographic model found strong spatial gradients in population trend based upon road density. Threshold road densities needed to ensure population stability were estimated to further refine targets for population recovery of grizzly bears in Alberta. Models that considered lowered survival of females with dependant offspring resulted in lower road density thresholds to ensure stable bear populations. Our results demonstrate likely spatial variation in population trend and provide an example how demographic analysis can be used to refine and direct conservation measures for threatened species.

Environmental, biological and anthropogenic effects on grizzly bear body size: temporal and spatial considerations.

BACKGROUND: Individual body growth is controlled in large part by the spatial and temporal heterogeneity of, and competition for, resources. Grizzly bears (Ursus arctos L.) are an excellent species for studying the effects of resource heterogeneity and maternal effects (i.e. silver spoon) on life history traits such as body size because their habitats are highly variable in space and time. Here, we evaluated influences on body size of grizzly bears in Alberta, Canada by testing six factors that accounted for spatial and temporal heterogeneity in environments during maternal, natal and 'capture' (recent) environments. After accounting for intrinsic biological factors (age, sex), we examined how body size, measured in mass, length and body condition, was influenced by: (a) population density; (b) regional habitat productivity; (c) inter-annual variability in productivity (including silver spoon effects); (d) local habitat quality; (e) human footprint (disturbances); and (f) landscape change. RESULTS: We found sex and age explained the most variance in body mass, condition and length (R(2) from 0.48-0.64). Inter-annual variability in climate the year before and of birth (silver spoon effects) had detectable effects on the three-body size metrics (R(2) from 0.04-0.07); both maternal (year before birth) and natal (year of birth) effects of precipitation and temperature were related with body size. Local heterogeneity in habitat quality also explained variance in body mass and condition (R(2) from 0.01-0.08), while annual rate of landscape change explained additional variance in body length (R(2) of 0.03). Human footprint and population density had no observed effect on body size. CONCLUSIONS: These results illustrated that body size patterns of grizzly bears, while largely affected by basic biological characteristics (age and sex), were also influenced by regional environmental gradients the year before, and of, the individual's birth thus illustrating silver spoon effects. The magnitude of the silver spoon effects was on par with the influence of contemporary regional habitat productivity, which showed that both temporal and spatial influences explain in part body size patterns in grizzly bears. Because smaller bears were found in colder and less-productive environments, we hypothesize that warming global temperatures may positively affect body mass of interior bears.

Multiple data sources improve DNA-based mark-recapture population estimates of grizzly bears.

A fundamental challenge to estimating population size with mark-recapture methods is heterogeneous capture probabilities and subsequent bias of population estimates. Confronting this problem usually requires substantial sampling effort that can be difficult to achieve for some species, such as carnivores. We developed a methodology that uses two data sources to deal with heterogeneity and applied this to DNA mark-recapture data from grizzly bears (Ursus arctos). We improved population estimates by incorporating additional DNA "captures" of grizzly bears obtained by collecting hair from unbaited bear rub trees concurrently with baited, grid-based, hair snag sampling. We consider a Lincoln-Petersen estimator with hair snag captures as the initial session and rub tree captures as the recapture session and develop an estimator in program MARK that treats hair snag and rub tree samples as successive sessions. Using empirical data from a large-scale project in the greater Glacier National Park, Montana, USA, area and simulation modeling we evaluate these methods and compare the results to hair-snag-only estimates. Empirical results indicate that, compared with hair-snag-only data, the joint hair-snag-rub-tree methods produce similar but more precise estimates if capture and recapture rates are reasonably high for both methods. Simulation results suggest that estimators are potentially affected by correlation of capture probabilities between sample types in the presence of heterogeneity. Overall, closed population Huggins-Pledger estimators showed the highest precision and were most robust to sparse data, heterogeneity, and capture probability correlation among sampling types. Results also indicate that these estimators can be used when a segment of the population has zero capture probability for one of the methods. We propose that this general methodology may be useful for other species in which mark-recapture data are available from multiple sources.

Demography of northern flying squirrels informs ecosystem management of western interior forests.

We studied northern flying squirrel (Glaucomys sabrinus) demography in the eastern Washington Cascade Range to test hypotheses about regional and local abundance patterns and to inform managers of the possible effects of fire and fuels management on flying squirrels. We quantified habitat characteristics and squirrel density, population trends, and demography in three typical forest cover types over a four-year period. We had 2034 captures of flying squirrels over 41 000 trap nights from 1997 through 2000 and marked 879 squirrels for mark-recapture population analysis. Ponderosa pine (Pinus ponderosa) forest appeared to be poorer habitat for flying squirrels than young or mature mixed-conifer forest. About 35% fewer individuals were captured in open pine forest than in dry mixed-conifer Douglas-fir (Pseudotsuga menziesii) and grand fir (Abies grandis) forests. Home ranges were 85% larger in pine forest (4.6 ha) than in mixed-conifer forests (2.5 ha). Similarly, population density (Huggins estimator) in ponderosa pine forest was half (1.1 squirrels/ha) that of mixed-conifer forest (2.2 squirrels/ha). Tree canopy cover was the single best correlate of squirrel density (r = 0.77), with an apparent threshold of 55% canopy cover separating stands with low- from high-density populations. Pradel estimates of annual recruitment were lower in open pine (0.28) than in young (0.35) and mature (0.37) forest. High recruitment was most strongly associated with high understory plant species richness and truffle biomass. Annual survival rates ranged from 45% to 59% and did not vary among cover types. Survival was most strongly associated with understory species richness and forage lichen biomass. Maximum snow depth had a strong negative effect on survival. Rate of per capita increase showed a density-dependent response. Thinning and prescribed burning in ponderosa pine and dry mixed conifer forests to restore stable fire regimes and forest structure might reduce flying squirrel densities at stand levels by reducing forest canopy, woody debris, and the diversity or biomass of understory plants, truffles, and lichens. Those impacts might be ameliorated by patchy harvesting and the retention of large trees, woody debris, and mistletoe brooms. Negative stand-level impacts would be traded for increased resistance and resilience of dry-forest landscapes to now-common, large-scale stand replacement fires.