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Aim: The rapidly changing Arctic is ideal for investigating uncertainties in climate projections. Despite the challenges of collecting data in this region, an unprecedented large‐scale survey of shorebirds has been conducted over the last 30 years. Our study aimed to (1) develop probabilistic estimates for the change in suitable habitat for 10 Arctic shorebird species in Canada by 2075 and (2) assess the contribution of modelling decisions to the uncertainty in these estimates. Location: Arctic Canada. Methods: To evaluate uncertainty, we considered six classes of modelling decisions, yielding 216 unique projections for each species. We tested three decisions that are less commonly explored − the pool of candidate variables, a method for selecting variables, and the maximum distance of tree line dispersal, as well as the modelling algorithm, carbon emissions scenario, and global circulation model. We used a bootstrapping approach, creating a probability distribution for the proportional change in suitable habitat for each species. Results: Our findings indicated a substantial risk for 8/10 species to lose over half of their suitable breeding habitat, but this projection is much less certain than has been described previously. While much uncertainty is unexplained, we were surprised that the largest source of uncertainty among our modelling decisions was from our choice of methods for variable selection, that the other modelling decisions were relatively small sources of uncertainty, overshadowing other modelling decisions. Main Conclusions: While most scenarios predict a northward shift and significant habitat loss for Arctic‐breeding shorebirds, the Arctic Archipelago of Canada will remain an important refuge because in many other Arctic regions, there is no land farther north for these species to shift into. A comprehensive understanding of uncertainty is important for deciding if future projections can or should be used when planning climate‐resilient protected area networks. [ABSTRACT FROM AUTHOR]

The Eastern Canada (ECA) Flocks data set consists of manually annotated images from the Common Eider (COEI, Somateria mollissima) Winter Survey and the Greater Snow Geese (GSGO, Anser caerulescens atlanticus) Spring Survey. The images were taken in eastern Canada using fixed‐wing aircraft and manually annotated with ImageJ's Cell counter plugins. We selected and annotated the ECA Flocks images in order to test the precision of the CountEm flock size estimation method. ECA Flocks includes 179 COEI and 99 GSGO single flock images. We cut each image manually to a rectangle that excluded large parts of the image with no birds. Both versions (original and cut) of each image are available in the data set. We manually annotated 637,555 (124,309 COEI and 514,235 GSGO) bird positions in the cut images from both surveys. Each bird has an associated "Type," which refers to species and/or sex. Sex identification was only possible for adult common eiders, because females and immature males are brown birds, whereas adult males have mainly white plumage. In the COEI images 64,484 males and 58,029 females, as well as 1,796 birds of other species, were identified. In the GSGO images 504,891 Snow Geese and 9,344 birds of other species were labeled. A.csv file including all annotated bird positions and types is available for each image. The COEI and GSGO photos of the ECA Flocks data set were taken in the years 2006 and 2018 and 2016–2018, respectively. We selected these photos in order to include images with different quality and resolution. COEI and GSGO flock sizes range from 6 to 4,154 and from 43 to 36,241 respectively. There is high variability in light conditions, backgrounds, and number and spatial arrangement of birds across the images. The data set is therefore potentially useful to test the precision of methods for analyzing imagery to estimate the abundance of animals by directly detecting, identifying, and counting individuals. We release these data into the public domain under a Creative Commons Zero license waiver. When you use the data in your publication, cite this data paper. Should ECA Flocks be a major part of the data analyzed in your study, you should consider inviting the ECA Flocks originators as collaborators. If you plan to use the ECA Flocks data set, we request that you contact the ECA Flocks core team to learn whether updates are available, and whether similar analyses are already ongoing. [ABSTRACT FROM AUTHOR]

Field biology courses provide the ultimate experiential education as students discover the links between theory and practice in ecology and evolution directly in nature. During the spring and summer of 2020, the COVID‐19 pandemic led to the cancelation of face‐to‐face classes in almost every university in Canada. Whereas traditional university courses were mostly transferred online, the online transition for field biology courses was not so common. Here, I provide an account of a successful transition from traditional field biology course to an online "backyard biology" field course with a small class size of 10 students. While the online field course may not provide the same level of interpersonal benefits of the traditional field course experience, the model outlined here demonstrates that an online field course that incorporates direct experience with the natural environment is possible and should no longer be considered an oxymoron. [ABSTRACT FROM AUTHOR]

The article offers information on the history of fisheries management, forest management, and range management. It mentions traditional wisdom in Christian Europe stated that species do not become extinct, because that would indicate that God was imperfect in his creations; and also mentions American bison lived in gigantic herds easily observed on American prairies and plains.