Little Brown Myotis (Myotis lucifugus) is one of the most common and widely distributed mammals in Canada and has been recorded to live over 30 years in the wild. As part of a long-term bat research project in Cypress Hills Interprovincial Park, Saskatchewan, we recaptured a male Little Brown Bat in a mist net over Battle Creek on 12 June 2021. The bat was recaptured within 100 m of where it was first captured and banded as an adult in 1993, indicating that this bat was at least 29 years old and exhibited repeated use of the same summer flying, foraging, and drinking site. The bat was not caught in the intervening years; therefore, its frequency of use of this site is unknown. In eastern North America, this species has declined because of high mortality rates associated with White-nose Syndrome (WNS). WNS has been moving westward and has now been detected in eastern and western Saskatchewan. Understanding aspects of the natural history of Little Brown Bat, including longevity, is important before WNS is detected in a region and leads us to advocate continued marking of individuals (e.g., banding, PIT tagging) to continue learning about bat longevity and survival before and after WNS infection.

Landscape ecology has mainly been integrated in aquatic science to describe patterns and processes in stream networks, but many lakes are connected through their tributaries and are also impacted by their position and connectivity within the watershed. This information on lake characteristics can be used by inland fisheries managers that oversee large landscapes comprising many waterbodies to predict (i) species composition; (ii) population dynamics and productivity; (iii) recreational fishing pressure; and (iv) overall conservation concern. We developed a methodology to assess these four items for the rainbow trout (Oncorhynchus mykiss) fishery of British Columbia by presenting a case study focused on the Clearwater and North Thompson watersheds using the following: the connectivity of lakes within the stream network to predict rainbow trout presence, stream order and lake area to estimate habitat availability and predict population dynamics and productivity (supply), and travel time from population centres to predict recreational fishing pressure (demand). By incorporating connectivity and environmental proxies of habitat, we explore patterns in population dynamics that can be used by fisheries managers to identify populations sensitive to overfishing or disturbance.

Understanding and assessing landscape connectivity is often a primary goal when studying patchy or spatially structured populations. It is commonly accepted that the matrix plays a role in determining connectivity; however, it is not clear how the process of assessing connectivity is impacted by different ways in which the matrix may be represented, particularly if matrix structure is generalized to expedite analysis. We conducted a controlled experiment using computer simulations to evaluate the impact of increasing levels of matrix generalization on connectivity assessment using a constant arrangement of habitat patches. We varied matrix generalization for six simulated landscape patterns by adjusting the number of classes and level of pattern grain in 16 ways to yield sets of landscapes for which the matrix ranged from not generalized (i.e., heterogeneous) to completely generalized (i.e., homogeneous) while habitat placement was held constant. Least-cost paths were calculated for each landscape, and a spatial interaction model (SIM) was implemented to model the counts of patch inflows (immigration) and pairwise exchange. Applying a SIM allowed us to generate absolute outputs and explicitly compare the effect of changes to matrix generalization on connectivity. We found that both assessment of connections (i.e., measured distance and spatial delineation of least-cost paths) and patch inflows/pairwise exchange were highly sensitive to matrix generalization and that effects were inconsistent and unpredictable across the range of matrix representations, especially when estimating connectivity for individual patches. We conclude that matrix pattern may have an underappreciated effect on connectivity and that least-cost path delineation and connectivity assessment may be very sensitive to generalizations of the matrix. We suggest that sensitivity analysis of the matrix representation should be performed when conducting connectivity analyses.

Assessments of connectivity are subject to the limitations imposed by the technique used to model species movement. Least-cost path analysis is one such commonly applied technique that has a number of associated limitations that are often discounted, such as the assumption of individual omniscience or symmetrical movement between patches. We contend that not accounting for methodological limitations may lead to inaccurate assessments of connectivity, and thus there is a need for more robust and adaptable approaches. Using simulated data and in a case study on Ord’s kangaroo rat (Dipodomys ordii), we present an approach that uses effective distance, in this case calculated from least-cost paths, in combination with a spatial interaction model (SIM), which allows one to incorporate additional landscape characteristics and interactions influencing movement, thereby overcoming key assumptions and limitations associated with the least-cost framework. We show how various factors influencing connectivity can be incorporated, how outputs from the SIM can be used to quantify connectivity, how outputs from different models may be compared, and, importantly, that in both a simulated and empirical case study application, the assessment of functional connectivity is sensitive to small changes to the model.

Given climate change, species' climatically suitable habitats are increasingly expected to shift poleward. Some imperilled populations towards the poleward edge of their species' range might therefore conceivably benefit from climate change. Interactions between climate and population dynamics may be complex, however, with climate exerting effects both indirectly via influence over food availability and more directly, via effects on physiology and its implications for survival and reproduction. A thorough understanding of these interactions is critical for effective conservation management. We therefore examine the relationship between climate, survival and reproduction in Canadian black-tailed prairie dogs, a threatened keystone species in an imperilled ecosystem at the northern edge of the species' range. Our analyses considered 8 years of annual mark-recapture data (2007-2014) in relation to growing degree days, precipitation, drought status and winter severity, as well as year, sex, age and body mass. Survival was strongly influenced by the interaction of drought and body mass class, and winter temperature severity. Female reproductive status was associated with the interaction of growing degree days and growing season precipitation, with spring precipitation and with winter temperature severity. Results related to body mass suggested that climatic variables exerted their effects via regulation of food availability with potential linked effects of food quality, immunological and behavioural implications, and predation risk. Predictions of future increases in drought conditions in North America's grassland ecosystems have raised concerns for the outlook of Canadian black-tailed prairie dogs. Insights gained from the analyses, however, point to mitigating species management options targeted at decoupling the mechanisms by which climate exerts its negative influence. Our approach highlights the importance of understanding the interaction between climate and population dynamics in peripheral populations whose viability might ultimately determine their species' ability to track climatically suitable space.

Habitat quality is a fundamental driver of species distributions and population outcomes but is often difficult to measure and compare alongside measures of habitat amount and fragmentation. Consequently, habitat quality is often omitted from many landscape-level habitat analyses or more indirectly or subjectively represented in resulting habitat management or conservation planning. Yet, the implications of this conceptual and planning omission are poorly understood. We lack general theory that identifies the conditions under which habitat quality is expected to play a vital role in characterizing local and regional population responses. Using a factorial simulation design, we examined the independent contributions of habitat quality, amount, and fragmentation to population persistence to identify the conditions under which habitat quality might be expected to play a more important role than those of habitat amount or fragmentation. We generated a wide range of fractal landscapes, independently varying in habitat amount, fragmentation, and quality in QRule. We simulated interactive animal movement, habitat selection, and persistence for r and K strategist species with short and long dispersal abilities using spatially explicit individual-based models developed in HexSim. Population abundance and extinction risk were recorded through time for each landscape-species combination and used to quantify the relative influence of habitat amount, fragmentation, and landscape quality on population outcomes. We found that habitat degradation influenced extinction risk through a wide range of landscape conditions and species attributes. The most severe extinction responses were observed in scenarios of combined habitat loss and degradation, suggesting that the interactive effects of these variables may greatly affect persistence. Landscape quality modified extinction risks associated with habitat amount-fragmentation thresholds, and we found evidence for quality-based extinction thresholds as habitat was degraded. The strength of landscape-level quality on extinction risk outcomes suggests that habitat degradation should be further investigated as a major driver of population responses to landscape change. A more inclusive paradigm may be required to elucidate the general influences landscape change on population extinction. Habitat degradation, along with habitat loss and fragmentation, should be explicitly considered when assessing the implications of landscape change on population extinction. (C) 2016 Elsevier B.V. All rights reserved.

In Canada, pronghorn (Antilocapra americana) are primarily considered a native prairie obligate because of their reliance on open grassland vegetation communities, although an assessment of local ecological knowledge suggests that pronghorn in Alberta select a variety of habitat from native prairie to cultivated lands. The primary objective of our study was to assess whether pronghorn in Alberta and Saskatchewan are native prairie obligates. Specifically, we addressed the following questions: 1) do individual pronghorn show similar selection patterns for native prairie and, therefore, support the notion that they are prairie obligates; 2) do pronghorn show consistent resource selection patterns at multiple scales (landscape and within-seasonal range); and 3) to what extent are selection patterns of pronghorn influenced by highways and roads. Within Alberta, we captured, collared, and monitored for one year individual female pronghorn in December 2003 (n = 24), March 2005 (n = 25), and March 2006 (n = 25). A detrended correspondence analysis of patterns of habitat selection revealed three distinct groups of pronghorn (r2 = 0.96, n = 55) that we labeled native, cultivated, and mixed, referring to the dominant land cover in their parturition ranges. We used logistic regression to model resource selection patterns of the three groups of pronghorn during the parturition and winter periods at the landscape and within-seasonal range scales. At the landscape scale, each group of pronghorn had top models consisting of the variables land cover, landform, distance to express highways, distance to arterial roads, and distance to collector roads for both periods. The native and mixed groups were less likely to use annual and perennial cropland than native prairie habitats, whereas the cultivated group was more likely to use annual and perennial cropland. At the within-seasonal range scale, the top models for each group in both seasons consisted of one or more road variables, but the top models exhibited poor model fit. Our results do not show a clear association for native prairie, which we would have expected if pronghorn were native prairie obligates, suggestive of plasticity in behavior. We acknowledge that patterns of habitat selection do not indicate habitat quality or fitness; therefore, to understand the individualand population-level consequences of selecting sub-optimal habitats, such as agricultural landscapes, further research is needed.

Species responses are influenced by processes operating at multiple scales, yet many conservation studies and management actions are focused on a single scale. Although landscape-level habitat conditions (i.e., habitat amount, fragmentation and landscape quality) are likely to drive the regional persistence of spatially structured populations, patch-level factors (i.e., patch size, isolation, and quality) may also be important. To determine the spatial scales at which habitat factors influence the regional persistence of endangered Ord's kangaroo rats (Dipodomys ordii) in Alberta, Canada, we simulated population dynamics under a range of habitat conditions. Using a spatially-explicit population model, we removed groups of habitat patches based on their characteristics and measured the resulting time to extinction. We used proportional hazards models to rank the influence of landscape and interacting patch-level variables. Landscape quality was the most influential variable followed by patch quality, with both outweighing landscape- and patch-level measures of habitat quantity and fragmentation/proximity. Although habitat conservation and restoration priorities for this population should be in maximizing the overall quality of the landscape, population persistence depends on how this goal is achieved. Patch quality exerted a significant influence on regional persistence, with the removal of low quality road margin patches (sinks) reducing the risk of regional extinction. Strategies for maximizing overall landscape quality that omit patch-level considerations may produce suboptimal or detrimental results for regional population persistence, particularly where complex local population dynamics (e.g., source-sink dynamics) exist. This study contributes to a growing body literature that suggests that the prediction of species responses and future conservation actions may best be assessed with a multi-scale approach that considers habitat quality and that the success of conservation actions may depend on assessing the influences of habitat factors at multiple scales.

Population sinks present unique conservation challenges. The loss of individuals in sinks can compromise persistence; but conversely, sinks can improve viability by improving connectivity and facilitating the recolonization of vacant sources. To assess the contribution of sinks to regional population persistence of declining populations, we simulated source-sink dynamics for 3 very different endangered species: Black-capped Vireos (Vireo atricapilla) at Fort Hood, Texas, Ord's kangaroo rats (Dipodomys ordii) in Alberta, and Northern Spotted Owls (Strix occidentalis caurina) in the northwestern United States. We used empirical data from these case studies to parameterize spatially explicit individual-based models. We then used the models to quantify population abundance and persistence with and without long-term sinks. The contributions of sink habitats varied widely. Sinks were detrimental, particularly when they functioned as strong sinks with few emigrants in declining populations (e.g., Alberta's Ord's kangaroo rat) and benign in robust populations (e.g., Black-capped Vireos) when Brown-headed Cowbird (Molothrus ater) parasitism was controlled. Sinks, including ecological traps, were also crucial in delaying declines when there were few sources (e.g., in Black-capped Vireo populations with no Cowbird control). Sink contributions were also nuanced. For example, sinks that supported large, variable populations were subject to greater extinction risk (e.g., Northern Spotted Owls). In each of our case studies, new context-dependent sinks emerged, underscoring the dynamic nature of sources and sinks and the need for frequent re-assessment. Our results imply that management actions based on assumptions that sink habitats are generally harmful or helpful risk undermining conservation efforts for declining populations.

Hydrologic Units Calwater Subbasins --(Planning Watersheds) 139,425 Acres 1801011

Relative to their cultivated surroundings, sandhills of the Canadian prairies represent intact, heterogeneous ecosystems. These extensive tracts of sand dunes and native prairie are biodiversity hotspots, which act as refugia for a variety of specialized wildlife species. However, due to changes in climate and suppression of natural disturbance, the dunes have experienced drastic rates of stabilization over the past 200 years, such that the proportion of open sand in the region is currently less than 1%. This continuing trend is resulting in a gradual loss of sparsely vegetated, sandy habitat for many uncommon, specialist species, including a number that are considered to be at risk of extirpation or extinction by COSEWIC (Canada's list agency). Without management to conserve active sandhill habitat the future long-term survival of rare and imperilled dune-dependent plants and animals is questionable. In this article we propose that the re-introduction of disturbance to southern Canadian prairie sandhills, specifically sandhill use by bison, might be effective in restoring and sustaining actively-eroding sandhill habitat to support some threatened and endangered species. We outline several lines of evidence (geological, geomorphological, archaeological, and historical accounts) indicating bison occupied sandhills and actively modified these ecosystems until European settlement of the prairies. We argue that bison were attracted to sandhills for a number of reasons, and that in great numbers they had considerable influence on sandhills ecosystem functions. Behaviours such as grazing, trailing, wallowing, horning, and trampling created a patchwork mosaic of disturbance effects. We hypothesize that it may be beneficial to reintroduce bison to sandhills ecosystems in the Canadian prairies to restore biodiversity at all levels.

Predictive modeling is an important tool for identifying areas for conservation prioritization. But the reliability of any model depends on how well its predictions can be generalized beyond the area surveyed. Recent work points to the potential for enhancing predictive power by incorporating such spatial processes as autocorrelation or the influence of location, so this study addressed two questions: (1) what affect does model complexity, spatial autocorrelation and spatial location have on model accuracy? (2) how generalizable are different methods when applied to new geographic test regions? On average, predictive power declined 22.7% +/- 2.7% SE when models were used to predict occurrences in "unsampled" geographic test regions. Overall variability in performance depended on the method used. AUTO and GAM models tended to be amongst the least variable, but results depended upon species. Our results suggest that models with complex functional relationships between the response and predictor variables (such as GAMs fit with up to 5 knots) tended to either improve accuracy, or perform more consistently across species, but not both at the same time. In general, it is very difficult to accurately extrapolate model predictions into unsampled geographic areas. However, we found that habitat specialists such as the Sedge Wren were consistently well predicted, regardless of method, and that autocorrelated regression (using a Gibbs sampler and simulation of presence/absence) could be more reliably generalized for species showing strong social structure (e.g., patchiness). GWR was especially sensitive to the plots used to train the model.

Sandhills are islands of biodiversity in the southern Canadian prairies that sustain habitat for many rare and endangered species. These unique areas consist of large expanses of dune fields now mostly stabilized by grassland vegetation. Historically, the number of active dunes has decreased significantly due to vegetation stabilization, resulting in a dramatic decline of open-sand habitat for a variety of dune-dependent species. Without a certain level of wind erosion, opportunities for establishment of early-stage, species-rich vegetation types are diminished and open-sand habitat decreases by encroachment of the surrounding grassland vegetation. The current trend of dune stabilization, however, implies that wind erosion is decreasing, thereby threatening the continued existence of a variety of dune-dependent plants, arthropods and vertebrates, as well as other less-specialized species that benefit indirectly from these habitats. By reviewing factors contributing to the historical decline of active dunes, as well as the ecological implications of dune stabilization, the aim of this paper is to establish the biophysical context for new land management strategies that conserve valued landscape components, such as active dunes, and the processes therein. As dune stabilization continues management interventions will be required to sustain or re-establish open sand and the species that rely on these habitats.

A principal challenge of species conservation is to identify the specific habitats that are essential for long-term persistence or recovery of imperiled species. However, many commonly used approaches to identify important habitats do not provide direct insight into the contribution of those habitats to population persistence. To assess how habitats contribute to overall population viability and characterize their relative importance, a spatially-explicit population viability model was used to integrate a species occurrence model with habitat quality and demographic information to simulate the population dynamics of the Ord’s kangaroo rat (Dipodomys ordii) in Alberta, Canada. Long-term productivity (births–deaths) in each patch was simulated and iterative patch removal experiments were conducted to generate estimates of the relative contribution of habitat types to overall population viability. Our results indicated that natural dune habitats are crucial for population viability, while disturbed/human-created habitats make a minor contribution to population persistence. The results also suggest that the habitats currently available to Ord’s kangaroo rats in Alberta are unlikely to support long-term persistence. Our approach was useful for identifying habitats that did not contribute to population viability. A large proportion of habitat (39%) represented sinks and their removal increased estimated population viability. The integration of population dynamics with habitat quality and occurrence data can be invaluable when assessing critical habitat, particularly in regions with variable habitat quality. Approaches that do not incorporate population dynamics may undermine conservation efforts by under- or over-estimating the value of habitats, erroneously protecting sink habitats, or failing to prioritize key source habitats.

The importance of landscape heterogeneity for the abundance and distribution of wildlife is well recognized. General relationships have been developed to link landscape pattern to demographic processes, although these relations are best demonstrated for species with specialized habitat requirements and often in landscapes that can be generalized to a simple habitat-matrix structure. Habitat generalists may interact in more complex ways with a mosaic of landscape features. A novel method for quantifying the habitat relationships of generalist species using thematic vegetation maps was proposed by Brotons et al. (2005) and based on a theoretical model by Andren, Delin, and Seiler (1997). We tested the efficacy of this approach on moose (Alces alces) distribution in the heterogeneous landscapes of the Foothills Natural Region, Alberta, Canada, using 8 broad vegetation types. Fecal pellet group data, an index of moose occurrence, was compared across pre-selected sites. Sites were selected to represent the variable amounts and combinations of the different vegetation types available in the study area. Moose habitat preference was determined using a Chi-square test and Bonferroni confidence intervals. Moose preferred shrublands and deciduous forests. Shrubland was considered primary moose habitat as it had the highest observed proportion of pellet groups of the preferred habitats. Each vegetation type was assessed regarding its role in habitat amount, habitat compensation, supplementation, complementation, and fragmentation models using general linear modelling. Habitat amount and fragmentation were related to moose pellet occurrence. However, there was no indication of supplementation, compensation, or complementation. This mosaic approach effectively revealed habitat relationships and the potential impacts of habitat change for a generalist species at the landscape scale.

Environmental models are a critical tool for identifying where organisms occur by estimating the relationship among species occurrence and important environmental factors. To date, the overwhelming majority of predictive occurrence models disregard both the impact of spatial autocorrelation (interaction between neighbouring points) as well as the possibility that model relationships may vary depending on geographic location. To address this gap, we measured their impact on five bird species observed during seven years of the North American Breeding Bird Survey. We first built traditional occurrence models (of varying functional complexity) using logistic regressions and generalized additive models (GAMs). We then compared model accuracy and goodness-of-fit to those incorporating spatial autocorrelation (ALOG) and spatial dependence (via geographically weighted regression, GWR). Environmental variables included aspects of land cover, climate, and topography. A residual analysis indicated that spatial autocorrelation persisted within even the most complex traditional models. In contrast, not only did ALOG models incorporate this effect (as indicated by a lack of residual autocorrelation), but also offered better predictive power for some species (+0.118 in the case of the American Crow, relative to the best GAM model). From an information-theoretic perspective, ALOG models were consistent improvements over traditional models. Adoption of GWR models also improved predictive accuracy (ranging from +0.078 for the American Crow and +0.008 for the Purple Finch). However, comparison of their evidence ratios with ALOG models indicated that ALOG models were generally superior. While we were unable to determine why geographic location influenced species' responses to environmental conditions, evidence from generalized estimating equations (GEES) revealed significant within-route correlation (rho = 0.54 +/- 0.26 SE), and implicated an observer effect. A combination of broad-scale and fine-scale factors were important for predicting occurrence, but we demonstrate that the incorporation of spatial factors offers the potential to measure the spatially explicit outcomes of infra-specific interactions, and regional differences in resource usage. We recommend that these methods be considered, particularly when evidence points to spatially autocorrelated errors or when there are a priori reasons to suspect geographic variability in resource selection.

Summary Roads can act as barriers to animal movement, which may reduce population persistence by reducing recolonization of empty habitats and limiting immigration. Appropriate mitigation of this barrier effect (e.g. seasonal road closures, location and design of wildlife over‐ or underpasses) depends upon whether the animals avoid the road itself or the traffic on the road. Empirical studies of road avoidance to date do not generally differentiate between these. We conducted short‐ and long‐distance translocations and trapping studies of white‐footed mice ( Peromyscus leucopus ) and eastern chipmunks ( Tamias striatus ) near two‐lane paved roads, which differed widely in traffic amount, from 47 to 15 433 vehicles per day. In the trapping study (13 sites) only five animals moved across a road, in comparison to 36 animals that moved the same distance without an intervening road ( P < 0·0001). In the short‐distance translocations (15 sites), 51% of the small mammals that were translocated across roads returned, in comparison to a return rate of 77% of animals that were translocated a similar distance with no intervening road ( P = 0·009). In the long‐distance translocation study (24 sites) we found that each intervening road reduced the probability of successful return by about 50%. We found no significant effects of traffic amount on return rates in either the short‐distance or the long‐distance translocations studies. Small mammal densities were not lower near roads and we found no evidence for a decrease in density near roads with increasing traffic amount. Synthesis and applications. Our results suggest that small mammals avoid the road itself, and not emissions such as noise from the traffic on the roads. Our results imply that the barrier effect of roads on these species cannot be mitigated by measures aimed at reducing traffic amount; other measures such as wildlife passages would be needed.