Integrating data types to estimate spatial patterns of avian migration across the Western Hemisphere.

For many avian species, spatial migration patterns remain largely undescribed, especially across hemispheric extents. Recent advancements in tracking technologies and high-resolution species distribution models (i.e., eBird Status and Trends products) provide new insights into migratory bird movements and offer a promising opportunity for integrating independent data sources to describe avian migration. Here, we present a three-stage modeling framework for estimating spatial patterns of avian migration. First, we integrate tracking and band re-encounter data to quantify migratory connectivity, defined as the relative proportions of individuals migrating between breeding and nonbreeding regions. Next, we use estimated connectivity proportions along with eBird occurrence probabilities to produce probabilistic least-cost path (LCP) indices. In a final step, we use generalized additive mixed models (GAMMs) both to evaluate the ability of LCP indices to accurately predict (i.e., as a covariate) observed locations derived from tracking and band re-encounter data sets versus pseudo-absence locations during migratory periods and to create a fully integrated (i.e., eBird occurrence, LCP, and tracking/band re-encounter data) spatial prediction index for mapping species-specific seasonal migrations. To illustrate this approach, we apply this framework to describe seasonal migrations of 12 bird species across the Western Hemisphere during pre- and postbreeding migratory periods (i.e., spring and fall, respectively). We found that including LCP indices with eBird occurrence in GAMMs generally improved the ability to accurately predict observed migratory locations compared to models with eBird occurrence alone. Using three performance metrics, the eBird + LCP model demonstrated equivalent or superior fit relative to the eBird-only model for 22 of 24 species-season GAMMs. In particular, the integrated index filled in spatial gaps for species with over-water movements and those that migrated over land where there were few eBird sightings and, thus, low predictive ability of eBird occurrence probabilities (e.g., Amazonian rainforest in South America). This methodology of combining individual-based seasonal movement data with temporally dynamic species distribution models provides a comprehensive approach to integrating multiple data types to describe broad-scale spatial patterns of animal movement. Further development and customization of this approach will continue to advance knowledge about the full annual cycle and conservation of migratory birds.

Habitat loss on the breeding grounds is a major contributor to population declines in a long-distance migratory songbird.

Many migratory species are declining and for most, the proximate causes of their declines remain unknown. For many long-distance Neotropical migratory songbirds, it is assumed that habitat loss on breeding or non-breeding grounds is a primary driver of population declines. We integrated data collected from tracking technology, community science and remote sensing data to quantify migratory connectivity (MC), population trends and habitat loss. We quantified the correlation between forest change throughout the annual cycle and population declines of a long-distance migratory songbird, the Connecticut warbler (Oporornis agilis, observed decline: -8.99% yr-1). MC, the geographic link between populations during two or more phases of the annual cycle, was stronger between breeding and autumn migration routes (MC = 0.24 ± 0.23) than between breeding and non-breeding locations (MC = -0.2 ± 0.14). Different Connecticut warbler populations tended to have population-specific fall migration routes but overlapped almost completely within the northern Gran Chaco ecoregion in South America. Cumulative forest loss within 50 km of breeding locations and the resulting decline in the largest forested patch index was correlated more strongly with population declines than forest loss on migratory stopover regions or on wintering locations in South America, suggesting that habitat loss during the breeding season is a driver of observed population declines for the Connecticut warbler. Land-use practices that retain large, forested patches within landscapes will likely benefit breeding populations of this declining songbird, but further research is needed to help inform land-use practices across the full annual cycle to minimize the impacts to migratory songbirds and abate ongoing population declines.

Can you hear me now? The effect of signal degradation on perceived predator threat in black-capped chickadees (Poecile atricapillus).

Avian predators vary in their degree-of-threat to chickadees; for example, smaller owls and hawks are of higher threat to chickadees as they can easily maneuver through the trees, while larger predators cannot. We conducted an operant go/no-go discrimination task to investigate the effect of signal degradation on perceived threat. Chickadees were trained to respond to high-threat northern saw-whet owl (NSWO) or low-threat great horned owl (GHOW) calls that were recorded at short distances, and then tested with high- and low-threat owl calls that were rebroadcast and re-recorded across six distances (25 m, 50 m, 75 m, 100 m, 150 m, and 200 m). Subjects were further tested with high-threat and low-threat synthetic tones produced to mimic the natural calls across the six distances. We predicted that birds would perceive and respond to: (1) high-threat predator calls at longer distances compared to low-threat predator calls, and (2) synthetic tones similarly compared to the stimuli that they were designed to mimic. We believed chickadees would continue to perceive and respond to predators that pose a high threat at further distances; however, only responding to low-threat stimuli was consistent across distance recordings. Synthetic tones were treated similarly to natural stimuli but at lower response levels. Thus, the results of this study provide insights into how chickadees perceive threat.

Acoustic discrimination of predators by black-capped chickadees (Poecile atricapillus).

Smaller owls and hawks are high-threat predators to small songbirds, like chickadees, in comparison to larger avian predators due to smaller raptors' agility (Templeton et al. in Proc Natl Acad Sci 104:5479-5482, 2005). The current literature focuses only on high- and low-threat predators. We propose that there may be a continuum in threat perception. In the current study, we conducted an operant go/no-go experiment investigating black-capped chickadees' acoustic discrimination of predator threat. After obtaining eight hawk and eight owl species' calls, we assigned each species as: (1) large, low-threat, (2) mid-sized, unknown-threat and (3) small-, high-threat predators, according to wingspan and body size. Black-capped chickadees were either trained to respond ('go') to high-threat predator calls or respond to low-threat predator calls. When either low-threat predator calls were not reinforced or high-threat predator calls were not reinforced the birds were to withhold responding ('no-go') to those stimuli. We then tested transfer of training with additional small and large predator calls, as well as with the calls of several mid-sized predators. We confirmed that chickadees can discriminate between high- and low-threat predator calls. We further investigated how chickadees categorize mid-sized species' calls by assessing transfer of training to previously non-differentially reinforced (i.e., pretraining) calls. Specifically, transfer test results suggest that mid-sized broad-winged hawks were perceived to be of high threat whereas mid-sized short-eared owls were perceived to be of low threat. However, mid-sized Cooper's hawks and northern hawk owls were not significantly differentially responded to, suggesting that they are of medium threat which supports the notion that perception of threat is along a continuum rather than distinct categories of high or low threat.

Validation prediction: a flexible protocol to increase efficiency of automated acoustic processing for wildlife research.

Automated recognition is increasingly used to extract species detections from audio recordings; however, the time required to manually review each detection can be prohibitive. We developed a flexible protocol called "validation prediction" that uses machine learning to predict whether recognizer detections are true or false positives and can be applied to any recognizer type, ecological application, or analytical approach. Validation prediction uses a predictable relationship between recognizer score and the energy of an acoustic signal but can also incorporate any other ecological or spectral predictors (e.g., time of day, dominant frequency) that will help separate true from false-positive recognizer detections. First, we documented the relationship between recognizer score and the energy of an acoustic signal for two different recognizer algorithm types (hidden Markov models and convolutional neural networks). Next, we demonstrated our protocol using a case study of two species, the Common Nighthawk (Chordeiles minor) and Ovenbird (Seiurus aurocapilla). We reduced the number of detections that required validation by 75.7% and 42.9%, respectively, while retaining at least 98% of the true-positive detections. Validation prediction substantially improves the efficiency of using automated recognition on acoustic data sets. Our method can be of use to wildlife monitoring and research programs and will facilitate using automated recognition to mine bioacoustic data sets.

Phenotypic Plasticity and Local Adaptation in a Wild Hibernator Evaluated through Reciprocal Translocation.

Phenological shifts are the most commonly reported ecological responses to climate change and can be produced rapidly by phenotypic plasticity. However, both the limits of plasticity and whether it will be sufficient to maintain local adaptation (or even lead to maladaptation) are less clear. Increased winter precipitation has been shown to lead to phenological delays and corresponding annual decreases in fitness in Columbian ground squirrels (Urocitellus columbianus). We took advantage of natural phenological variation (across elevations) in this species to better assess the extent of phenotypic plasticity in emergence dates and the relationships between emergence dates and individual annual fitness. We coupled a reciprocal translocation experiment with natural monitoring across two populations separated by ∼500 m in elevation. Individuals in both populations responded plastically to both spring temperature and winter precipitation. Translocated individuals adjusted their emergence dates to approach those of individuals in their adoptive populations but did differ significantly in their emergence dates from residents. There were no differences in annual fitness among treatment groups nor selection on emergence date within a year. Phenotypic plasticity is thus sufficient to allow individuals to respond to broad environmental gradients, but the influence of variation in emergence dates on annual fitness requires further investigation.

Additive and interactive cumulative effects on boreal landbirds: winners and losers in a multi-stressor landscape.

Stressors created by multiple resource industries can result in cumulative effects over time and space. Many studies have evaluated single stressors and assumed that cumulative effects can be understood by adding stressors together. However, there is growing evidence that interactive effects are important in structuring biological communities. We evaluated whether the effects of multiple stressors in the boreal forest (linear features, energy, forestry) combine additively or interactively by testing a candidate model set of 12 cumulative effects models of abundance for 27 landbird species. We fitted paired additive and interactive Generalized Additive Models and examined model predictions in the Athabasca Oil Sands Area of Alberta, Canada, and a theoretical no-disturbance version of the study area. Of the 27 species examined, an additive disturbance model was the best for nine species, while an interactive disturbance model was the best for 11 species. In the current study area, disturbance models predicted strong increases in abundance for species associated with deciduous forest and open habitats (winning species) and moderate decreases for species associated with conifer forest (losing species). We found a 15% change in landbird community composition between the current study area, with 8.4% disturbance, and the theoretical no-disturbance study area. Complex synergistic and antagonistic interactions among stressors were observed for 39% of landbird species, with the majority of interactions observed being synergistic. Stressors with relatively small disturbance areas, such as narrow linear disturbances, frequently interacted with other stressors to affect species' responses, and energy sector stressors often had additive or interactive effects with forestry stressors. Interactive cumulative effects from multiple sectors will make it increasingly difficult for industry and land managers to manage impacts unless interactions among stressors are incorporated into cumulative effects assessments and regional land use planning processes.

Using vertebrate prey capture locations to identify cover type selection patterns of nocturnally foraging Burrowing Owls.

Studies of habitat selection often measure an animal's use of space via radiotelemetry or GPS-based technologies. Such data tend to be analyzed using a resource selection function, despite the fact that the actual resources acquired are typically not recorded. Without explicit proof of resource use, conclusions from RSF models are based on assumptions regarding an animal's behavior and the resources gained. Conservation initiatives are often based on space-use models, and could be detrimental to the target species if these assumptions are incorrect. We used GPS dataloggers and digital video recorders to determine precise locations where nocturnally foraging Burrowing Owls acquired food resources (vertebrate prey). We compared land cover type selection patterns using a presence-only resource selection function (RSF) to a model that incorporated prey capture locations (CRSF). We also compared net prey returns in each cover type to better measure reward relative to foraging effort. The RSF method did not reflect prey capture patterns and cover-type rankings from this model were quite different from models that used only locations where prey was known to have been obtained. Burrowing Owls successfully foraged across all cover types; however, return vs. effort models indicate that different cover types were of higher quality than those identified using resource selection functions. Conclusions about the type of resources acquired should not be made from RSF-style models without evidence that the actual resource of interest was acquired. Conservation efforts based on RSF models alone may be ineffective or detrimental to the target species if the limiting resource and where it is acquired are not properly identified.

A framework for adaptive monitoring of the cumulative effects of human footprint on biodiversity.

Effective ecological monitoring is imperative in a human-dominated world, as our ability to manage functioning ecosystems will depend on understanding biodiversity responses to anthropogenic impacts. Yet, most monitoring efforts have either been narrowly focused on particular sites, species and stressors - thus inadequately considering the cumulative effects of multiple, interacting impacts at scales of management relevance - or too unfocused to provide specific guidance. We propose a cumulative effects monitoring framework that integrates multi-scaled surveillance of trends in biodiversity and land cover with targeted evaluation of hypothesized drivers of change. The framework is grounded in a flexible conceptual model and uses monitoring to generate and test empirical models that relate the status of diverse taxonomic groups to the nature and extent of human "footprint" and other landscape attributes. An adaptive cycle of standardized sampling, model development, and model evaluation provides a means to learn about the system and guide management. Additional benefits of the framework include standardized data on status and trend for a wide variety of biodiversity elements, spatially explicit models for regional planning and scenario evaluation, and identification of knowledge gaps for complementary research. We describe efforts to implement the framework in Alberta, Canada, through the Alberta Biodiversity Monitoring Institute, and identify key challenges to be addressed.

Behaviour and landscape contexts determine the effects of artificial light on two crepuscular bird species.

Context: Artificial light at night (ALAN) is increasing worldwide, with many ecological effects. Aerial insectivores may benefit from foraging on insects congregating at light sources. However, ALAN could negatively impact them by increasing nest visibility and predation risk, especially for ground-nesting species like nightjars (Caprimulgidae). Objectives: We tested predictions based on these two alternative hypotheses, potential foraging benefits vs potential predation costs of ALAN, for two nightjar species in British Columbia: Common Nighthawks (Chordeiles minor) and Common Poorwills (Phalaenoptilus nuttallii). Methods: We modeled the relationship between ALAN and relative abundance using count data from the Canadian Nightjar Survey. We distinguished territorial from extra-territorial Common Nighthawks based on their wingboom behaviour. Results: We found limited support for the foraging benefit hypothesis: there was an increase in relative abundance of extra-territorial Common Nighthawks in areas with higher ALAN but only in areas with little to no urban land cover. Common Nighthawks' association with ALAN became negative in areas with 18% or more urban land cover. We found support for the nest predation hypothesis: the were strong negative associations with ALAN for both Common Poorwills and territorial Common Nighthawks. Conclusions: The positive effects of ALAN on foraging nightjars may be limited to species that can forage outside their nesting territory and to non-urban areas, while the negative effects of ALAN on nesting nightjars may persist across species and landscape contexts. Reducing light pollution in breeding habitat may be important for nightjars and other bird species that nest on the ground. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-024-01875-3.

Individual identification in acoustic recordings.

Recent advances in bioacoustics combined with acoustic individual identification (AIID) could open frontiers for ecological and evolutionary research because traditional methods of identifying individuals are invasive, expensive, labor-intensive, and potentially biased. Despite overwhelming evidence that most taxa have individual acoustic signatures, the application of AIID remains challenging and uncommon. Furthermore, the methods most commonly used for AIID are not compatible with many potential AIID applications. Deep learning in adjacent disciplines suggests opportunities to advance AIID, but such progress is limited by training data. We suggest that broadscale implementation of AIID is achievable, but researchers should prioritize methods that maximize the potential applications of AIID, and develop case studies with easy taxa at smaller spatiotemporal scales before progressing to more difficult scenarios.

Simultaneous estimation of the temporal and spatial extent of animal migration using step lengths and turning angles.

BACKGROUND: Animals of many different species, trophic levels, and life history strategies migrate, and the improvement of animal tracking technology allows ecologists to collect increasing amounts of detailed data on these movements. Understanding when animals migrate is important for managing their populations, but is still difficult despite modelling advancements. METHODS: We designed a model that parametrically estimates the timing of migration from animal tracking data. Our model identifies the beginning and end of migratory movements as signaled by change-points in step length and turning angle distributions. To this end, we can also use the model to estimate how an animal's movement changes when it begins migrating. In addition to a thorough simulation analysis, we tested our model on three datasets: migratory ferruginous hawks (Buteo regalis) in the Great Plains, barren-ground caribou (Rangifer tarandus groenlandicus) in northern Canada, and non-migratory brown bears (Ursus arctos) from the Canadian Arctic. RESULTS: Our simulation analysis suggests that our model is most useful for datasets where an increase in movement speed or directional autocorrelation is clearly detectable. We estimated the beginning and end of migration in caribou and hawks to the nearest day, while confirming a lack of migratory behaviour in the brown bears. In addition to estimating when caribou and ferruginous hawks migrated, our model also identified differences in how they migrated; ferruginous hawks achieved efficient migrations by drastically increasing their movement rates while caribou migration was achieved through significant increases in directional persistence. CONCLUSIONS: Our approach is applicable to many animal movement studies and includes parameters that can facilitate comparison between different species or datasets. We hope that rigorous assessment of migration metrics will aid understanding of both how and why animals move.

Gharial (Gavialis gangeticus) conservation in Bardia National Park, Nepal: Assessing population structure and habitat characteristics along the river channel amidst infrastructure development.

Nepal initiated numerous hydropower and irrigation-related infrastructure projects to enhance and promote green energy, water security, and agricultural productivity. However, these projects may pose risks to natural habitats and the well-being of aquatic fauna, leading to significant effects on delicate ecosystems. To understand these potential impacts, it is crucial to gather reliable baseline data on the population status and habitat characteristics of species. This study specifically focuses on Gharials (Gavialis gangeticus), a critically endangered species. We recorded data on pre-determined habitat variables at stations spaced 500 m apart along the two major river streams of Bardia National Park, as well as at locations where Gharials were sighted between February and March 2023. We used binary logistic regression with a logit link function to investigate the habitat characteristics related to the occurrence of Gharials. The presence/absence of Gharials at sampling points served as the dependent variable, while 10 other predetermined variables (ecological variables and disturbance variables) served as independent variables. Our study recorded 23 Gharials, comprising 14 adults, six sub-adults, and three juveniles, with a sex ratio of 55.56 males per 100 females. Most individuals (83%) were found basking. Among the 10 habitat predictors, three variables (mid-river depth, river width, and water temperature) were significantly correlated (p < .05) with the probability of Gharial occurrence. The model shows that Gharial detection probability increases with greater mid-river depth and width and lower water temperature. This study establishes a population baseline for Gharials within the river system before the construction of large infrastructure projects, such as dams and irrigation canals. It also recommends continuous monitoring of Gharial populations after water release and/or diversion to evaluate the impact of large infrastructure projects on the population and their associated habitat characteristics. This will help enable more informed and targeted conservation efforts.

Domains of scale in cumulative effects of energy sector development on boreal birds.

Context: Industrial development in Canada's boreal forest creates cumulative environmental effects on biodiversity. Some effects may be scale-dependent, creating uncertainty in understanding and hindering effective management. Objectives: We estimated cumulative effects of energy sector development on distributions of sixteen migratory songbird species at multiple spatial scales within the boreal region of Alberta, Canada, and evaluated evidence for scale domains in species responses. Methods: We used a hierarchical, multi-scale sampling and modelling framework to compare effects of oil and gas footprint on songbirds at five spatial scales. We used Bayesian Lasso to facilitate direct comparison of parameter estimates across scales, and tested for differences in grouped parameter estimates among species. Results: We found consistent scale-dependent patterns across species, showing variable responses to development occurring at the smallest scale, little effect at intermediate scales, and stronger, mainly positive effects at the largest scales. Differences in grouped parameter estimates across scales showed strong evidence for scale domains in the response of songbirds to energy sector development. Conclusions: We concluded that variable effects at the smallest scale represented individual habitat selection, while larger scale positive effects reflected expanding distributions of open habitat- and disturbance-associated species in areas of high oil and gas footprint. Our results show that single-scale analyses do not reflect population processes occurring at other scales. Future research on linking patterns at different scales is required to fully understand cumulative effects of land use change on wildlife populations. Supplementary Information: The online version contains supplementary material available at 10.1007/s10980-023-01779-8.

Topographic and vegetation drivers of thermal heterogeneity along the boreal-grassland transition zone in western Canada: Implications for climate change refugia.

Climate change refugia are areas that are relatively buffered from contemporary climate change and may be important safe havens for wildlife and plants under anthropogenic climate change. Topographic variation is an important driver of thermal heterogeneity, but it is limited in relatively flat landscapes, such as the boreal plain and prairie regions of western Canada. Topographic variation within this region is mostly restricted to river valleys and hill systems, and their effects on local climates are not well documented. We sought to quantify thermal heterogeneity as a function of topography and vegetation cover within major valleys and hill systems across the boreal-grassland transition zone. Using iButton data loggers, we monitored local temperature at four hills and 12 river valley systems that comprised a wide range of habitats and ecosystems in Alberta, Canada (N = 240), between 2014 and 2020. We then modeled monthly temperature by season as a function of topography and different vegetation cover types using general linear mixed effect models. Summer maximum temperatures (T max) varied nearly 6°C across the elevation gradient sampled. Local summer mean (T mean) and maximum (T max) temperatures on steep, north-facing slopes (i.e., low levels of potential solar radiation) were up to 0.70°C and 2.90°C cooler than highly exposed areas, respectively. T max in incised valleys was between 0.26 and 0.28°C cooler than other landforms, whereas areas with greater terrain roughness experienced maximum temperatures that were up to 1.62°C cooler. We also found that forest cover buffered temperatures locally, with coniferous and mixedwood forests decreasing summer T mean from 0.23 to 0.72°C and increasing winter T min by up to 2°C, relative to non-forested areas. Spatial predictions of temperatures from iButton data loggers were similar to a gridded climate product (ClimateNA), but the difference between them increased with potential solar radiation, vegetation cover, and terrain roughness. Species that can track their climate niche may be able to compensate for regional climate warming through local migrations to cooler microsites. Topographic and vegetation characteristics that are related to cooler local climates should be considered in the evaluation of future climate change impacts and to identify potential refugia from climate change.

A synthetic review of terrestrial biological research from the Alberta oil sands region: 10 years of published literature.

In the past decade, a large volume of peer-reviewed papers has examined the potential impacts of oil and gas resource extraction in the Canadian oil sands (OS). A large proportion focuses on terrestrial biology: wildlife, birds, and vegetation. We provide a qualitative synthesis of the condition of the environment in the oil sands region (OSR) from 2009 to 2020 to identify gaps and progress cumulative effects assessments. Our objectives were to (1) qualitatively synthesize and critically review knowledge from the OSR; (2) identify consistent trends and generalizable conclusions; and (3) pinpoint gaps in need of greater monitoring or research effort. We visualize knowledge and terrestrial monitoring foci by allocating papers to a conceptual model for the OS. Despite a recent increase in publications, focus has remained concentrated on a few key stressors, especially landscape disturbance, and a few taxa of interest. Stressor and response monitoring is well represented, but direct monitoring of pathways (linkages between stressors and responses) is limited. Important knowledge gaps include understanding effects at multiple spatial scales, mammal health effects monitoring, focused monitoring of local resources important to Indigenous communities, and geospatial coverage and availability, including higher attribute resolution in human footprint, comprehensive land cover mapping, and up-to-date LiDAR coverage. Causal attribution based on spatial proximity to operations or spatial orientation of monitoring in the region is common but may be limited in the strength of inference that it provides. Integr Environ Assess Manag 2022;18:388-406. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Comparing sea ice habitat fragmentation metrics using integrated step selection analysis.

Habitat fragmentation occurs when continuous habitat gets broken up as a result of ecosystem change. While commonly studied in terrestrial ecosystems, Arctic sea ice ecosystems also experience fragmentation, but are rarely studied in this context. Most fragmentation analyses are conducted using patch-based metrics, which are potentially less suitable for sea ice that has gradual changes between sea ice cover, than distinct "long-term" patches. Using an integrated step selection analysis, we compared the descriptive power of a patch-based metric to a more novel metric, the variation in local spatial autocorrelation over time. We used satellite telemetry data from 39 adult female polar bears (Ursus maritimus) in Hudson Bay to examine their sea ice habitat using Advanced Microwave Scanning Radiometer 2 data during sea ice breakup in May through July from 2013-2018. Spatial autocorrelation resulted in better model fits across 64% of individuals, although both metrics were more effective in describing movement patterns than habitat selection. Variation in local spatial autocorrelation allows for the visualization of sea ice habitat at complex spatial and temporal scales, condensing a targeted time period of habitat that would otherwise have to be analyzed daily.

Ecological insights from three decades of animal movement tracking across a changing Arctic.

The Arctic is entering a new ecological state, with alarming consequences for humanity. Animal-borne sensors offer a window into these changes. Although substantial animal tracking data from the Arctic and subarctic exist, most are difficult to discover and access. Here, we present the new Arctic Animal Movement Archive (AAMA), a growing collection of more than 200 standardized terrestrial and marine animal tracking studies from 1991 to the present. The AAMA supports public data discovery, preserves fundamental baseline data for the future, and facilitates efficient, collaborative data analysis. With AAMA-based case studies, we document climatic influences on the migration phenology of eagles, geographic differences in the adaptive response of caribou reproductive phenology to climate change, and species-specific changes in terrestrial mammal movement rates in response to increasing temperature.

Genetic structure of invasive earthworms Dendrobaena octaedra in the boreal forest of Alberta: insights into introduction mechanisms.

Population genetic studies can help to determine whether invasive species are established via single vs. multiple introduction events and also to distinguish among various colonization scenarios. We used this approach to investigate the introduction of Dendrobaena octaedra, a non-native earthworm species, to the boreal forest of northern Alberta. The spread of non-native earthworms in forested systems is not well understood, although bait abandonment and vehicular transport are believed to be important. Mitochondrial DNA sequencing revealed that multiple introductions of this species have occurred in northern Alberta, although individual populations may have been established by either single or multiple invaders introduced on one or more occasions. There was no relationship between genetic distances and either geographical distances or distances along road networks, suggesting that human-mediated jump dispersal is more common than diffusive spread via road networks or via active dispersal. As well, genetic diversity was significantly greater at boat launches than roads, indicating that multiple introductions may be more likely to occur at those locations. Focusing management efforts on areas where multiple introductions are likely to occur may help to reduce invasive species' potential for adaptive evolution and subsequent rapid spread.

Impacts of chronic anthropogenic noise from energy-sector activity on abundance of songbirds in the boreal forest.

The effects of human activities in forests are often examined in the context of habitat conversion. Changes in habitat structure and composition are also associated with increases in the activity of people with vehicles and equipment, which results in increases in anthropogenic noise. Anthropogenic noise may reduce habitat quality for many species, particularly those that rely on acoustic signals for communication. We compared the density and occupancy rate of forest passerines close to versus far from noise-generating compressor stations and noiseless well pads in the boreal forest of Alberta, Canada. Using distance-based sampling, we found that areas near noiseless energy facilities had a total passerine density 1.5 times higher than areas near noise-producing energy sites. The White-throated Sparrow (Zonotrichia albicollis), Yellow-rumped Warbler (Dendroica coronata), and Red-eyed Vireo (Vireo olivaceus) were less dense in noisy areas. We used repeat sampling to estimate occupancy rate for 23 additional species. Seven had lower conditional or unconditional occupancy rates near noise-generating facilities. One-third of the species examined showed patterns that supported the hypothesis that abundance is influenced by anthropogenic noise. An additional 4 species responded negatively to edge effects. To mitigate existing noise impacts on birds would require approximately $175 million. The merits of such an effort relative to other reclamation actions are discussed. Nevertheless, given the $100 billion energy-sector investment planned for the boreal forest in the next 10 years, including noise suppression technology at the outset of construction, makes noise mitigation a cost-effective best-management practice that might help conserve high-quality habitat for boreal birds.