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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). KEY POINTS: We provide a qualitative synthesis of the condition of the environment in the Canadian oil sands region (OSR) in northeastern Alberta from 2009 to 2020 to identify gaps and progress cumulative effects assessments. Despite a recent increase in publications, focus has remained concentrated on a few key stressors and a few taxa of interest, for which monitoring is well represented, though direct monitoring of pathways (linkages between stressors and responses) is limited. Important gaps include a lack of understanding of effects at multiple spatial scales, a lack of focused monitoring of local resources important to Indigenous communities, and geospatial data resolution and availability. Causal attribution based on spatial proximity to oil sands operations or spatial orientation of monitoring in the OSR is common but may be limited in the strength of inference that it provides. [ABSTRACT FROM AUTHOR]

Understanding the functional significance of bird sounds can provide valuable insight into the behavior and how birds use habitat. We show that the Common Nighthawk (Chordeiles minor) wing-boom display is a territorial signal associated with the nest location that can be used to identify territorial habitat use. In other words, the Common Nighthawk wing-boom display can be considered analogous to song due to its potential function in territoriality. We captured, tagged, and tracked 21 male Common Nighthawks in northeastern Alberta to confirm the functional significance of the wing-boom display and describe Common Nighthawk territoriality. Mean wing-boom use density (hereafter “area”) size was 10.2 ha (SD = 11.7 ha). We found minimal overlap in the wing-boom area (5 of 15 neighboring male pairs, 0.2–4.5% overlap), suggesting the wing-boom display represents an exclusive territory. Comparison of wing-boom locations and random points within the wing-boom area confirmed that male Common Nighthawks select areas near the nest to perform wing-boom displays. There was high wing-boom area overlap for the same individual between years. Differences between years reflected shifts in nest location, suggesting that the wing-boom display is a good indicator of the nest location and territory. Future Common Nighthawk surveys should record the type of acoustic signal observed to differentiate territorial habitat use from other functions. Many taxa that produce non-vocal sounds as part of breeding displays could similarly benefit from a functional understanding to provide insight into habitat use. [ABSTRACT FROM AUTHOR]

Kant's Second Analogy attempts to prove a causal principle, which is best interpreted as arguing that successions of appearances or events cannot be objects of experience or objects of representations unless they occur according to a rule. The Second Analogy does not present Kant's complete theory of causation, but includes only those aspects needed to make experience possible, those that come under the transcendental proof. Therefore, requirements for repeatability and necessary order are not included in the causal principle of the Second Analogy.

Distance sampling is widely used to estimate animal population densities by accounting for imperfect detection of individuals with increasing distance from an observer. Distance sampling assumes that distances are measured without error; however, it is often applied to human estimated distances, which are known to be inconsistent, inaccurate, and biased. We present an objective technique for estimating distance to vocalizing individuals that relies on the relative sound level (RSL) of the vocalization extracted from autonomous recording unit (ARU) recordings and show the error is less than human estimated error extracted from a literature case study. RSL predicted distances can be obtained by manual measurement in sound viewing software, or automatically with automated signal recognition software. We built calibration datasets of Ovenbirds (Seiurus aurocapilla) and Common Nighthawks (Chordeiles minor) recorded at known distances and used regression of RSL from those recordings to predict distance. There was no error bias of RSL predicted distances when compared to known distances for Common Nighthawk, minimal error bias for Ovenbird, and error from all RSL predicted distances was less than human estimated error extracted from the literature. We then simulated ARU point count surveys with a known density and estimated that density with distance sampling to test whether RSL distance prediction does not violate the assumption that distances are measured without error. There was no difference in density estimates from known distance and density estimates obtained from RSL predicted distance, while density estimates contaminated with human estimated error were significantly lower than density estimates from known distance. We found that a calibration dataset of approximately 300 vocalizations was suitable to minimize error for both species, and so conclude that RSL distance prediction is an accessible method of improving distance estimates relative to human estimation. We provide general recommendations on how to collect calibration recordings for the application of RSL distance prediction to other species and areas. [ABSTRACT FROM AUTHOR]