Automated signal recognition software is increasingly used to extract species detection data from acoustic recordings collected using autonomous recording units (ARUs), but there is little practical guidance available for ecologists on the application of this technology. Performance evaluation is an important part of employing automated acoustic recognition technology because the resulting data quality can vary with a variety of factors. We reviewed the bioacoustic literature to summarize performance evaluation and found little consistency in evaluation, metrics employed, or terminology used. We also found that few studies examined how score threshold, i.e., cutoff for the level of confidence in target species classification, affected performance, but those that did showed a strong impact of score threshold on performance. We used the lessons learned from our literature review and best practices from the field of machine learning to evaluate the performance of five readily-available automated signal recognition programs. We used the Common Nighthawk (Chordeiles minor) as our model species because it has simple, consistent, and frequent vocalizations. We found that automated signal recognition was effective for determining Common Nighthawk presence-absence and call rate, particularly at low score thresholds, but that occupancy estimates from the data processed with recognizers were consistently lower than from data generated by human listening and became unstable at high score thresholds. Of the five programs evaluated, our convolutional neural network (CNN) recognizer performed best, with recognizers built in Song Scope and MonitoR also performing well. The RavenPro and Kaleidoscope recognizers were moderately effective, but produced more false positives than the other recognizers. Finally, we synthesized six general recommendations for ecologists who employ automated signal recognition software, including what to use as a test benchmark, how to incorporate score threshold, what metrics to use, and how to evaluate efficiency. Future studies should consider our recommendations to build a body of literature on the effectiveness of this technology for avian research and monitoring. Recommandations pour l'évaluation des performances de reconnaissance acoustique et application à cinq programmes courants de reconnaissance automatisée de signaux sonores RÉSUMÉ. Les logiciels de reconnaissance automatisée de signaux sonores sont de plus en plus utilisés pour extraire les données de détection des espèces d'enregistrements acoustiques récoltés au moyen d'unités d'enregistrement autonomes (ARU en anglais), mais il existe peu d'instructions pratiques sur l'utilisation de cette technologie pour les écologistes. L'évaluation de la performance est une étape importante dans l'utilisation d'une technologie de reconnaissance acoustique automatisée parce que la qualité des résultats peut varier en fonction de divers facteurs. Nous avons passé en revue la littérature sur la bioacoustique afin de résumer les critères d'évaluation de ...

Much of Canada's terrestrial biodiversity is supported by boreal forests. Natural resource development in boreal forests poses risks to this biodiversity. This paper reviews the scientific literature to assess the effects of natural resource development on terrestrial biodiversity in Canadian boreal forests. We address four questions: (1) To what extent have Canadian boreal forests changed due to natural resource development? (2) How has biodiversity responded to these changes? (3) Will the biodiversity of second-growth forests converge with that of primary boreal forests? (4) Are we losing species from boreal forests? We focus on trees, understory plants, insects, fungi, selected mammals, and songbirds because these groups have been most studied. We review more than 600 studies and found that changes in community composition are prevalent in response to large-scale conversion of forest types, changes in stand structures and age distributions, and altered landscape structure resulting from forest management and habitat loss associated with other developments such as oil and gas, hydroelectric, and mining. The southern boreal forest has been more highly impacted than the north due to more extensive forest management and the cumulative effects of multiple forms of development. There is abundant evidence that most species are not in danger of being extirpated from the boreal forest due to these anthropogenic changes. A few species, including woodland caribou (Rangifer tarandus) and grizzly bear (Ursus arctos), have, however, undergone long-term range contractions. Significant gaps in our ability to assess the effects of natural resource development on biodiversity in the boreal zone are the lack of long-term spatial and population data to monitor the impact of forest changes on ecosystems and species.Résumé : Une bonne partie de la biodiversité du Canada se retrouve en forêt boréale. Le développement des ressources naturelles dans des forêts boréales présente des risques pour cette biodiversité. Les auteurs présentent une revue de la littérature pour évaluer les effets du développement des ressources naturelles sur la biodiversité terrestre dans les forêts boréales canadiennes. Ils ont soulevé quatre questions : (1) jusqu'à quel point les forêts boréales canadiennes se sont vues modifiées par le développe-ment des ressources naturelles ? (2) Comment la biodiversité a-t-elle réagi à ces changements ? (3) Y aura-t-il convergence de la biodiversité des forêts de seconde venue avec celle des forêts boréales primaires ? (4) Subissons-nous des pertes d'espèces en forêts boréales ? Les auteurs se sont intéressés en particulier aux arbres, aux plantes de sous-bois, aux insectes, aux champignons, à des mammifères et oiseaux chanteurs sélectionnés, car ces groupes ont été les plus étudiés. Ils ont suivi plus de 600 espèces et ont constaté que les changements de composition prévalent en réaction à des modifications à grande échelle des types forestiers, des changements de la structure, des classes d'âge, des modifications aux ...

For climate change projections to be useful, the magnitude of change must be understood relative to the magnitude of uncertainty in model predictions. We quantified the signal-to-noise ratio in projected distributional responses of boreal birds to climate change, and compared sources of uncertainty. Boosted regression tree models of abundance were generated for 80 boreal-breeding bird species using a comprehensive data set of standardized avian point counts (349,629 surveys at 122,202 unique locations) and 4-km climate, land use, and topographic data. For projected changes in abundance, we calculated signal-to-noise ratios and examined variance components related to choice of global climate model (GCM) and two sources of species distribution model (SDM) uncertainty: sampling error and variable selection. We also evaluated spatial, temporal, and interspecific variation in these sources of uncertainty. The mean signal-to-noise ratio across species increased over time to 2.87 by the end of the 21st century, with the signal greater than the noise for 88% of species. Across species, climate change represented the largest component (0.44) of variance in projected abundance change. Among sources of uncertainty evaluated, choice of GCM (mean variance component = 0.17) was most important for 66% of species, sampling error (mean= 0.12) for 29% of species, and variable selection (mean =0.05) for 5% of species. Increasing the number of GCMs from four to 19 had minor effects on these results. The range of projected changes and uncertainty characteristics across species differed markedly, reinforcing the individuality of species' responses to climate change and the challenges of one-size-fits-all approaches to climate change adaptation. We discuss the usefulness of different conservation approaches depending on the strength of the climate change signal relative to the noise, as well as the dominant source of prediction uncertainty.

Climate‐induced vegetation change may be delayed in the absence of disturbance catalysts. However, increases in wildfire activity may accelerate these transitions in many areas, including the western boreal region of Canada. To better understand factors influencing decadal‐scale changes in upland boreal forest vegetation, we developed a hybrid modeling approach that constrains projections of climate‐driven vegetation change based on topo‐edaphic conditions coupled with weather‐ and fuel‐based simulations of future wildfires using Burn‐P3, a spatial fire simulation model. We evaluated eighteen scenarios based on all possible combinations of three fuel assumptions (static, fire‐mediated, and climate‐driven), two fire‐regime assumptions (constrained and unconstrained), and three global climate models. We simulated scenarios of fire‐mediated change in forest composition over the next century, concluding that, even under conservative assumptions about future fire regimes, wildfire activity could hasten the conversion of approximately half of Alberta's upland mixedwood and conifer forest to more climatically suited deciduous woodland and grassland by 2100. When fire‐regime parameter inputs (number of fire ignitions and duration of burning) were modified based on future fire weather projections, the simulated area burned was almost enough to facilitate a complete transition to climate‐predicted vegetation types. However, when fire‐regime parameters were held constant at their current values, the rate of increase in fire probability diminished, suggesting a negative feedback by which a short‐term increase in less‐flammable deciduous forest leads to a long‐term reduction in area burned. Our spatially explicit simulations of fire‐mediated vegetation change provide managers with scenarios that can be used to plan for a range of alternative landscape conditions.

The vast boreal biome plays an important role in the global carbon cycle but is experiencing particularly rapid climate warming, threatening the integrity of valued ecosystems and their component species. We developed a framework and taxonomy to identify climate‐change refugia potential in the North American boreal region, summarizing current knowledge regarding mechanisms, geographic distribution, and landscape indicators. While “terrain‐mediated” refugia will mostly be limited to coastal and mountain regions, the ecological inertia (resistance to external fluctuations) contained in some boreal ecosystems may provide more extensive buffering against climate change, resulting in “ecosystem‐protected” refugia. A notable example is boreal peatlands, which can retain high surface soil moisture and water tables even in the face of drought. Refugia from wildfire are also especially important in the boreal region, which is characterized by active disturbance regimes. Our framework will help identify areas of high refugia potential, and inform ecosystem management and conservation planning in light of climate change.