Spatiotemporal patterns of paralytic shellfish toxins and their relationships with environmental variables in British Columbia, Canada from 2002 to 2012.

BACKGROUND: Harmful algal blooms produce paralytic shellfish toxins that accumulate in the tissues of filter feeding shellfish. Ingestion of these toxic shellfish can cause a serious and potentially fatal condition known as paralytic shellfish poisoning (PSP). The coast of British Columbia is routinely monitored for shellfish toxicity, and this study uses data from the monitoring program to identify spatiotemporal patterns in shellfish toxicity events and their relationships with environmental variables. METHODS: The dinoflagellate genus Alexandrium produces the most potent paralytic shellfish toxin, saxitoxin (STX). Data on all STX measurements were obtained from 49 different shellfish monitoring sites along the coast of British Columbia for 2002-2012, and monthly toxicity events were identified. We performed hierarchical cluster analysis to group sites that had events in similar areas with similar timing. Machine learning techniques were used to model the complex relationships between toxicity events and environmental variables in each group. RESULTS: The Strait of Georgia and the west coast of Vancouver Island had unique toxicity regimes. Out of the seven environmental variables used, toxicity in each cluster could be described by multivariable models including monthly sea surface temperature, air temperature, sea surface salinity, freshwater discharge, upwelling, and photosynthetically active radiation. The sea surface salinity and freshwater discharge variables produced the strongest univariate models for both geographic areas. CONCLUSIONS: Applying these methods in coastal regions could allow for the prediction of shellfish toxicity events by environmental conditions. This has the potential to optimize biotoxin monitoring, improve public health surveillance, and engage the shellfish industry in helping to reduce the risk of PSP.

Evaluation of different radon guideline values based on characterization of ecological risk and visualization of lung cancer mortality trends in British Columbia, Canada.

BACKGROUND: There is no safe concentration of radon gas, but guideline values provide threshold concentrations that are used to map areas at higher risk. These values vary between different regions, countries, and organizations, which can lead to differential classification of risk. For example the World Health Organization suggests a 100 Bq m(-3)value, while Health Canada recommends 200 Bq m(-3). Our objective was to describe how different thresholds characterized ecological radon risk and their visual association with lung cancer mortality trends in British Columbia, Canada. METHODS: Eight threshold values between 50 and 600 Bq m(-3) were identified, and classes of radon vulnerability were defined based on whether the observed 95(th) percentile radon concentration was above or below each value. A balanced random forest algorithm was used to model vulnerability, and the results were mapped. We compared high vulnerability areas, their estimated populations, and differences in lung cancer mortality trends stratified by smoking prevalence and sex. RESULTS: Classification accuracy improved as the threshold concentrations decreased and the area classified as high vulnerability increased. Majority of the population lived within areas of lower vulnerability regardless of the threshold value. Thresholds as low as 50 Bq m(-3) were associated with higher lung cancer mortality, even in areas with low smoking prevalence. Temporal trends in lung cancer mortality were increasing for women, while decreasing for men. CONCLUSIONS: Radon contributes to lung cancer in British Columbia. The results of the study contribute evidence supporting the use of a reference level lower than the current guideline of 200 Bq m(-3) for the province.

A critical examination of indices of dynamic interaction for wildlife telemetry studies.

Wildlife scientists continue to be interested in studying ways to quantify how the movements of animals are interdependent - dynamic interaction. While a number of applied studies of dynamic interaction exist, little is known about the comparative effectiveness and applicability of available methods used for quantifying interactions between animals. We highlight the formulation, implementation and interpretation of a suite of eight currently available indices of dynamic interaction. Point- and path-based approaches are contrasted to demonstrate differences between methods and underlying assumptions on telemetry data. Correlated and biased correlated random walks were simulated at a range of sampling resolutions to generate scenarios with dynamic interaction present and absent. We evaluate the effectiveness of each index at identifying different types of interactive behaviour at each sampling resolution. Each index is then applied to an empirical telemetry data set of three white-tailed deer (Odocoileus virginianus) dyads. Results from the simulated data show that three indices of dynamic interaction reliant on statistical testing procedures are susceptible to Type I error, which increases at fine sampling resolutions. In the white-tailed deer examples, a recently developed index for quantifying local-level cohesive movement behaviour (the di index) provides revealing information on the presence of infrequent and varying interactions in space and time. Point-based approaches implemented with finely sampled telemetry data overestimate the presence of interactions (Type I errors). Indices producing only a single global statistic (7 of the 8 indices) are unable to quantify infrequent and varying interactions through time. The quantification of infrequent and variable interactive behaviour has important implications for the spread of disease and the prevalence of social behaviour in wildlife. Guidelines are presented to inform researchers wishing to study dynamic interaction patterns in their own telemetry data sets. Finally, we make our code openly available, in the statistical software R, for computing each index of dynamic interaction presented herein.

Erratum to "Branching out: Feasibility of examining the effects of greenspace on mental health after traumatic brain injury" [Dialogues in Health, Volume 2, 2023, 100129].

[This corrects the article DOI: 10.1016/j.dialog.2023.100129.].

Exploring the ecological processes driving geographical patterns of breeding bird richness in British Columbia, Canada.

British Columbia (BC), Canada, has a diverse landscape that provides breeding habitat for > 300 avian species, and the recent development of the BC Breeding Bird Atlas data set presents key information for exploring the landscape conditions which lead to biological richness. We used the volunteer-collected raw breeding bird evidence data set to analyze the effects of sampling biases on spatial distribution of observed breeding bird species and implemented regression tree analysis (Random Forests) to examine the influence of productivity, ambient energy, and habitat heterogeneity on independently measured breeding bird richness. Results indicated that total breeding species richness is correlated with total survey effort (alpha < 0.001). By stratifying species richness by survey effort, we observed that ambient energy is the top-ranked environmental predictor of breeding bird richness across BC, which, when used in combination with a number of other environmental variables, explains -40% of the variation in richness. Using our modeled relationships, we predicted breeding bird species richness in the areas of BC not presently surveyed between three and six hours. The majority of the productive Boreal Plains, the southern portion of the Taiga Plains region, the lowlands of the Southern and Central Interior, along the Rocky Mountain Trench, and the coastal areas of the Georgia Depression are predicted to have the highest categories of breeding richness (35-57 unique species). Our results support ongoing species diversity gradient research, which identifies ambient energy as an important factor influencing species diversity distributions in the Northern Hemisphere. By linking breeding bird richness to environmental data derived from remotely sensed data and systematically collected climate data, we demonstrate the potential to monitor shifts in ambient energy as a surrogate for vertebrate habitat condition affecting population levels. By analyzing the influence of survey effort on species richness metrics, we also highlight the need to consider adding attributes to the raw breeding bird data set to describe observer experience, such as hours or seasons spent surveying, and provide survey dates to allow greater flexibility for removing survey bias. These additions can increase the utility of atlas data for species richness studies useful for conservation planning.

Ecosystem classifications based on summer and winter conditions.

Ecosystem classifications map an area into relatively homogenous units for environmental research, monitoring, and management. However, their effectiveness is rarely tested. Here, three classifications are (1) defined and characterized for Canada along summertime productivity (moderate-resolution imaging spectrometer fraction of absorbed photosynthetically active radiation) and wintertime snow conditions (special sensor microwave/imager snow water equivalent), independently and in combination, and (2) comparatively evaluated to determine the ability of each classification to represent the spatial and environmental patterns of alternative schemes, including the Canadian ecozone framework. All classifications depicted similar patterns across Canada, but detailed class distributions differed. Class spatial characteristics varied with environmental conditions within classifications, but were comparable between classifications. There was moderate correspondence between classifications. The strongest association was between productivity classes and ecozones. The classification along both productivity and snow balanced these two sets of variables, yielding intermediate levels of association in all pairwise comparisons. Despite relatively low spatial agreement between classifications, they successfully captured patterns of the environmental conditions underlying alternate schemes (e.g., snow classes explained variation in productivity and vice versa). The performance of ecosystem classifications and the relevance of their input variables depend on the environmental patterns and processes used for applications and evaluation. Productivity or snow regimes, as constructed here, may be desirable when summarizing patterns controlled by summer- or wintertime conditions, respectively, or of climate change responses. General purpose ecosystem classifications should include both sets of drivers. Classifications should be carefully, quantitatively, and comparatively evaluated relative to a particular application prior to their implementation as monitoring and assessment frameworks.

A framework for modern time geography: emphasizing diverse constraints on accessibility.

Time geography is widely used by geographers as a model for understanding accessibility. Recent changes in how access is created, an increasing awareness of the need to better understand individual variability in access, and growing availability of detailed spatial and mobility data have created an opportunity to build more flexible time geography models. Our goal is to outline a research agenda for a modern time geography that allows new modes of access and a variety of data to flexibly represent the complexity of the relationship between time and access. A modern time geography is more able to nuance individual experience and creates a pathway for monitoring progress toward inclusion. We lean on the original work by Hägerstrand and the field of movement GIScience to develop both a framework and research roadmap that, if addressed, can enhance the flexibility of time geography to help ensure time geography will continue as a cornerstone of accessibility research. The proposed framework emphasizes the individual and differentiates access based on how individuals experience internal, external, and structural factors. To enhance nuanced representation of inclusion and exclusion, we propose research needs, focusing efforts on implementing flexible space-time constraints, inclusion of definitive variables, addressing mechanisms for representing and including relative variables, and addressing the need to link between individual and population scales of analysis. The accelerated digitalization of society, including availability of new forms of digital spatial data, combined with a focus on understanding how access varies across race, income, sexual identity, and physical limitations requires new consideration for how we include constraints in our studies of access. It is an exciting era for time geography and there are massive opportunities for all geographers to consider how to incorporate new realities and research priorities into time geography models, which have had a long tradition of supporting theory and implementation of accessibility research.

Branching out: Feasibility of examining the effects of greenspace on mental health after traumatic brain injury.

Aim: This pilot study's aim was to determine the feasibility of examining the effects of an environmental variable (i.e., tree canopy coverage) on mental health after sustaining a brain injury. Methods: A secondary data analysis was conducted leveraging existing information on mental health after moderate to severe traumatic brain injury (TBI) from the TBI Model System. Mental health was measured using PHQ-9 (depression) and GAD-7 (anxiety) scores. The data were compared with data on tree canopy coverage in the state of Texas that was obtained from the Multi-Resolution Land Characteristics (MRLC) Consortium using GIS analysis. Tree canopy coverage as an indicator of neighborhood socioeconomic status was also examined using the Neighborhood SES Index. Results: Tree canopy coverage had weak and non-significant correlations with anxiety and depression scores, as well as neighborhood socioeconomic status. Data analysis was limited by small sample size. However, there is a higher percentage (18.8%) of participants who reported moderate to severe depression symptoms in areas with less than 30% tree canopy coverage, compared with 6.6% of participants who endorsed moderate to severe depression symptoms and live in areas with more than 30% tree canopy coverage (there was no difference in anxiety scores). Conclusion: Our work confirms the feasibility of measuring the effects of tree canopy coverage on mental health after brain injury and warrants further investigation into examining tree canopy coverage and depression after TBI. Future work will include nationwide analyses to potentially detect significant relationships, as well as examine differences in geographic location.

Mobile phone-based infectious disease surveillance system, Sri Lanka.

Because many infectious diseases are emerging in animals in low-income and middle-income countries, surveillance of animal health in these areas may be needed for forecasting disease risks to humans. We present an overview of a mobile phone-based frontline surveillance system developed and implemented in Sri Lanka. Field veterinarians reported animal health information by using mobile phones. Submissions increased steadily over 9 months, with ≈4,000 interactions between field veterinarians and reports on the animal population received by the system. Development of human resources and increased communication between local stakeholders (groups and persons whose actions are affected by emerging infectious diseases and animal health) were instrumental for successful implementation. The primary lesson learned was that mobile phone-based surveillance of animal populations is acceptable and feasible in lower-resource settings. However, any system implementation plan must consider the time needed to garner support for novel surveillance methods among users and stakeholders.

Review of software for space-time disease surveillance.

Disease surveillance makes use of information technology at almost every stage of the process, from data collection and collation, through to analysis and dissemination. Automated data collection systems enable near-real time analysis of incoming data. This context places a heavy burden on software used for space-time surveillance. In this paper, we review software programs capable of space-time disease surveillance analysis, and outline some of their salient features, shortcomings, and usability. Programs with space-time methods were selected for inclusion, limiting our review to ClusterSeer, SaTScan, GeoSurveillance and the Surveillance package for R. We structure the review around stages of analysis: preprocessing, analysis, technical issues, and output. Simulated data were used to review each of the software packages. SaTScan was found to be the best equipped package for use in an automated surveillance system. ClusterSeer is more suited to data exploration, and learning about the different methods of statistical surveillance.

Determination of the compositional change (1999-2006) in the pine forests of British Columbia due to mountain pine beetle infestation.

The current mountain pine beetle (Dendroctonus ponderosae Hopkins) outbreak in British Columbia and Alberta is the largest recorded forest pest infestation in Canadian history. We integrate a spatial hierarchy of mountain pine beetle and forest health monitoring data, collected between 1999 and 2006, with provincial forest inventory data, and generate three information products representing 2006 forest conditions in British Columbia: cumulative percentage of pine infested by mountain pine beetle, percentage of pine uninfested, and the change in the percentage of pine on the landscape. All input data were formatted to a standardized spatial representation (1 ha minimum mapping unit), with preference given to the most detailed monitoring data available at a given location for characterizing mountain pine beetle infestation conditions. The presence or absence of mountain pine beetle attack was validated using field data (n = 2054). The true positive rate for locations of red attack damage over all years was 92%. Classification of attack severity was validated using the Kruskal gamma statistic (gamma = 0.49). Error between the survey data and field data was explored using spatial autoregressive (SAR) models, which indicated that percentage pine and year of infestation were significant predictors of survey error at alpha = 0.05. Through the integration of forest inventory and infestation survey data, the total area of pine infested is estimated to be between 2.89 and 4.14 million hectares. The generated outputs add value to existing monitoring data and provide information to support management and modeling applications.

Multiuse trail intersection safety analysis: A crowdsourced data perspective.

Real and perceived concerns about cycling safety are a barrier to increased ridership in many cities. Many people prefer to bike on facilities separated from motor vehicles, such as multiuse trails. However, due to underreporting, cities lack data on bike collisions, especially along greenways and multiuse paths. We used a crowdsourced cycling incident dataset (2005-2016) from BikeMaps.org for the Capital Regional District (CRD), BC, Canada. Our goal was to identify design characteristics associated with unsafe intersections between multiuse trails and roads. 92.8% of mapped incidents occurred between 2014 and 2016. We extracted both collision and near miss incidents at intersections from BikeMaps.org. We conducted site observations at 32 intersections where a major multiuse trail intersected with roads. We compared attributes of reported incidents at multiuse trail-road intersections to those at road-road intersections. We then used negative binomial regression to model the relationship between the number of incidents and the infrastructure characteristics at multiuse trail-road intersections. We found a higher proportion of collisions (38%, or 17/45 total reports) at multiuse trail-road intersections compared to road-road intersections (23%, or 62/268 total reports). A higher proportion of incidents resulted in an injury at multiuse trail-road intersections compared to road-road intersections (33% versus 15%). Cycling volumes, vehicle volumes, and trail sight distance were all associated with incident frequency at multiuse trail-road intersections. Supplementing traditional crash records with crowdsourced cycling incident data provides valuable evidence on cycling safety at intersections between multiuse trails and roads, and more generally, when conflicts occur between diverse transportation modes.

A geospatial approach to the prediction of indoor radon vulnerability in British Columbia, Canada.

Radon is a carcinogenic radioactive gas produced by the decay of uranium. Accumulation of radon in residential structures contributes to lung cancer mortality. The goal of this research is to predict residential radon vulnerability classes for the province of British Columbia (BC) at aggregated spatial units. Spatially referenced indoor radon concentration data were partitioned into low, medium, and high classes of radon vulnerability. Radon vulnerability classes were then linked to environmental and housing data derived from existing geospatial datasets. A Balanced Random Forests algorithm was used to model environmental predictors of indoor radon vulnerability and values at un-sampled locations across BC. A model was generated and evaluated using accuracy, precision, and kappa statistics. The influence of predictor variables was investigated through variable importance and partial dependence plots. The model performed 34% better than a random classifier. Increased probabilities of high vulnerability were associated with cold and dry winters, close proximity to major river systems, and fluvioglacial and colluvial soil parent materials. The Kootenays and Columbia-Shuswap regions were most at risk. Here, we present a novel method for predictive radon mapping that is broadly applicable to regions throughout the world.

Intertidal resource use over millennia enhances forest productivity.

Human occupation is usually associated with degraded landscapes but 13,000 years of repeated occupation by British Columbia's coastal First Nations has had the opposite effect, enhancing temperate rainforest productivity. This is particularly the case over the last 6,000 years when intensified intertidal shellfish usage resulted in the accumulation of substantial shell middens. We show that soils at habitation sites are higher in calcium and phosphorous. Both of these are limiting factors in coastal temperate rainforests. Western redcedar (Thuja plicata) trees growing on the middens were found to be taller, have higher wood calcium, greater radial growth and exhibit less top die-back. Coastal British Columbia is the first known example of long-term intertidal resource use enhancing forest productivity and we expect this pattern to occur at archaeological sites along coastlines globally.

A Review of the Statistical and Quantitative Methods Used to Study Alcohol-Attributable Crime.

Modelling the relationship between alcohol consumption and crime generates new knowledge for crime prevention strategies. Advances in data, particularly data with spatial and temporal attributes, have led to a growing suite of applied methods for modelling. In support of alcohol and crime researchers we synthesized and critiqued existing methods of spatially and quantitatively modelling the effects of alcohol exposure on crime to aid method selection, and identify new opportunities for analysis strategies. We searched the alcohol-crime literature from 1950 to January 2014. Analyses that statistically evaluated or mapped the association between alcohol and crime were included. For modelling purposes, crime data were most often derived from generalized police reports, aggregated to large spatial units such as census tracts or postal codes, and standardized by residential population data. Sixty-eight of the 90 selected studies included geospatial data of which 48 used cross-sectional datasets. Regression was the prominent modelling choice (n = 78) though dependent on data many variations existed. There are opportunities to improve information for alcohol-attributable crime prevention by using alternative population data to standardize crime rates, sourcing crime information from non-traditional platforms (social media), increasing the number of panel studies, and conducting analysis at the local level (neighbourhood, block, or point). Due to the spatio-temporal advances in crime data, we expect a continued uptake of flexible Bayesian hierarchical modelling, a greater inclusion of spatial-temporal point pattern analysis, and shift toward prospective (forecast) modelling over small areas (e.g., blocks).

A Review of Existing Studies Reporting the Negative Effects of Alcohol Access and Positive Effects of Alcohol Control Policies on Interpersonal Violence.

Alcohol consumption often leads to elevated rates of violence yet alcohol access policies continue to relax across the globe. Our review establishes the extent alcohol policy can moderate violent crime through alcohol availability restrictions. Results were informed from comprehensive selection of peer-reviewed journals from 1950 to October 2015. Our search identified 87 relevant studies on alcohol access and violence conducted across 12 countries. Seventeen studies included quasi-control design, and 23 conducted intervention analysis. Seventy-one (82%) reported a significant relationship between alcohol access and violent offenses. Alcohol outlet studies reported the greatest percentage of significant results (93%), with trading hours (63%), and alcohol price following (58%). Results from baseline studies indicated the effectiveness of increasing the price of commonly consumed alcohol, restricting the hours of alcohol trading, and limiting the number of alcohol outlets per region to prevent violent offenses. Unclear are the effects of tax reductions, restriction of on-premises re-entry, and different outlet types on violent crime. Further, the generalization of statistics over broad areas and the low number of control/intervention studies poses some concern for confounding or correlated effects on study results, and amount of information for local-level prevention of interpersonal violence. Future studies should focus on gathering longitudinal data, validating models, limiting crime data to peak drinking days and times, and wherever possible collecting the joint distribution between violent crime, intoxication, and place. A greater uptake of local-level analysis will benefit studies comparing the influence of multiple alcohol establishment types by relating the location of a crime to establishment proximity. Despite, some uncertainties particular studies showed that even modest policy changes, such as 1% increases in alcohol price, 1 h changes to closing times, and limiting establishment densities to <25 outlets per postal code substantively reduce violent crime.

BikeMaps.org: A Global Tool for Collision and Near Miss Mapping.

There are many public health benefits to cycling, such as chronic disease reduction and improved air quality. Real and perceived concerns about safety are primary barriers to new ridership. Due to limited forums for official reporting of cycling incidents, lack of comprehensive data is limiting our ability to study cycling safety and conduct surveillance. Our goal is to introduce BikeMaps.org, a new website developed by the authors for crowd-source mapping of cycling collisions and near misses. BikeMaps.org is a global mapping system that allows citizens to map locations of cycling incidents and report on the nature of the event. Attributes collected are designed for spatial modeling research on predictors of safety and risk, and to aid surveillance and planning. Released in October 2014, within 2 months the website had more than 14,000 visitors and mapping in 14 countries. Collisions represent 38% of reports (134/356) and near misses 62% (222/356). In our pilot city, Victoria, Canada, citizens mapped data equivalent to about 1 year of official cycling collision reports within 2 months via BikeMaps.org. Using report completeness as an indicator, early reports indicate that data are of high quality with 50% being fully attributed and another 10% having only one missing attribute. We are advancing this technology, with the development of a mobile App, improved data visualization, real-time altering of hazard reports, and automated open-source tools for data sharing. Researchers and citizens interested in utilizing the BikeMaps.org technology can get involved by encouraging citizen mapping in their region.

Mapping areas of spatial-temporal overlap from wildlife tracking data.

BACKGROUND: The study of inter-individual interactions (often termed spatial-temporal interactions, or dynamic interactions) from remote tracking data has focused primarily on identifying the presence of such interactions. New datasets and methods offer opportunity to answer more nuanced questions, such as where on the landscape interactions occur. In this paper, we provide a new approach for mapping areas of spatial-temporal overlap in wildlife from remote tracking data. The method, termed the joint potential path area (jPPA) builds from the time-geographic movement model, originally proposed for studying human movement patterns. RESULTS: The jPPA approach can be used to delineate sub-areas of the home range where inter-individual interaction was possible. Maps of jPPA regions can be integrated with existing geographic data to explore landscape conditions and habitat associated with spatial temporal-interactions in wildlife. We apply the jPPA approach to simulated biased correlated random walks to demonstrate the method under known conditions. The jPPA method is then applied to three dyads, consisting of fine resolution (15 minute sampling interval) GPS tracking data of white-tailed deer (Odocoileus virginianus) collected in Oklahoma, USA. Our results demonstrate the ability of the jPPA to identify and map jPPA sub-areas of the home range. We show how jPPA maps can be used to identify habitat differences (using percent tree canopy cover as a habitat indicator) between areas of spatial-temporal overlap and the overall home range in each of the three deer dyads. CONCLUSIONS: The value of the jPPA approach within current wildlife habitat analysis workflows is highlighted along with its simple and straightforward implementation and interpretation. Given the current emphasis on remote tracking in wildlife movement and habitat research, new approaches capable of leveraging both the spatial and temporal information content contained within these data are warranted. We make code (in the statistical software R) for implementing the jPPA approach openly available for other researchers.

Environmental factors and habitat use influence body condition of individuals in a species at risk, the grizzly bear.

Metrics used to quantify the condition or physiological states of individuals provide proactive mechanisms for understanding population dynamics in the context of environmental factors. Our study examined how anthropogenic disturbance, habitat characteristics and hair cortisol concentrations interpreted as a sex-specific indicator of potential habitat net-energy demand affect the body condition of grizzly bears (n = 163) in a threatened population in Alberta, Canada. We quantified environmental variables by modelling spatial patterns of individual habitat use based on global positioning system telemetry data. After controlling for gender, age and capture effects, we assessed the influence of biological and environmental variables on body condition using linear mixed-effects models in an information theoretical approach. Our strongest model suggested that body condition was improved when patterns of habitat use included greater vegetation productivity, increased influence of forest harvest blocks and oil and gas well sites, and a higher percentage of regenerating and coniferous forest. However, body condition was negatively affected by habitat use in close proximity to roads and in areas where potential energetic demands were high. Poor body condition was also associated with increased selection of parks and protected areas and greater seasonal vegetation productivity. Adult females, females with cubs-of-year, juvenile females and juvenile males were in poorer body condition compared with adult males, suggesting that intra-specific competition and differences in habitat use based on gender and age may influence body condition dynamics. Habitat net-energy demand also tended to be higher in areas used by females which, combined with observed trends in body condition, could affect reproductive success in this threatened population. Our results highlight the importance of considering spatiotemporal variability in environmental factors and habitat use when assessing the body condition of individuals. Long-term and large-scale monitoring of the physiological state of individuals provides a more comprehensive approach to support management and conservation of species at risk.

Spatial analysis of factors influencing long-term stress in the grizzly bear (Ursus arctos) population of Alberta, Canada.

Non-invasive measures for assessing long-term stress in free ranging mammals are an increasingly important approach for understanding physiological responses to landscape conditions. Using a spatially and temporally expansive dataset of hair cortisol concentrations (HCC) generated from a threatened grizzly bear (Ursus arctos) population in Alberta, Canada, we quantified how variables representing habitat conditions and anthropogenic disturbance impact long-term stress in grizzly bears. We characterized spatial variability in male and female HCC point data using kernel density estimation and quantified variable influence on spatial patterns of male and female HCC stress surfaces using random forests. Separate models were developed for regions inside and outside of parks and protected areas to account for substantial differences in anthropogenic activity and disturbance within the study area. Variance explained in the random forest models ranged from 55.34% to 74.96% for males and 58.15% to 68.46% for females. Predicted HCC levels were higher for females compared to males. Generally, high spatially continuous female HCC levels were associated with parks and protected areas while low-to-moderate levels were associated with increased anthropogenic disturbance. In contrast, male HCC levels were low in parks and protected areas and low-to-moderate in areas with increased anthropogenic disturbance. Spatial variability in gender-specific HCC levels reveal that the type and intensity of external stressors are not uniform across the landscape and that male and female grizzly bears may be exposed to, or perceive, potential stressors differently. We suggest observed spatial patterns of long-term stress may be the result of the availability and distribution of foods related to disturbance features, potential sexual segregation in available habitat selection, and may not be influenced by sources of mortality which represent acute traumas. In this wildlife system and others, conservation and management efforts can benefit by understanding spatial- and gender-based stress responses to landscape conditions.