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In 2015, The Truth and Reconciliation Report (TRC) was released in Canada, outlining 94 Calls to Action which, include pushing Canadian post-secondary institutions to ethically engage Indigenous communities and knowledge systems. This paper seeks to respond to the TRC by offering a spatial analysis of the differences, broadly conceived, between Indigenous and western ontological structures. We consider these differences in terms of 'circles and lines' through a novice, settler understanding of how Mi'kmaw concepts of etuaptmumk (two-eyed seeing), netukulimk (conservation laws) and m'sɨt No'kmaq (all our relations) can be brought to support decolonial teaching and learning about such important and urgent matters as climate change. A related goal in this paper is pedagogic: we hope our own ambivalent learning here can be used as an example to reflect deeply on how settlers like us might/should/can't work with the ethical, political, and practical challenges of responding to the TRC in our research, involving, and considering Indigenous ways of knowing and being. [ABSTRACT FROM AUTHOR]

This collaborative paper explores the interconnections between climate change and the mental health and well‐being of Indigenous women in Western Canada. As the impacts of climate change intensify globally, vulnerable populations, particularly Indigenous communities, face disproportionate and multifaceted challenges. Centering on Indigenous women in Western Canada, this study explores how the climate crisis magnifies Indigenous communities' mental health disparities. Drawing from the Indigenist feminist research approach, the investigation focuses on Indigenous women's lived experiences, perceptions, and land‐based coping strategies amidst climate challenges, while simultaneously addressing the unique social, cultural, and historical factors influencing their mental health vulnerabilities within the context of climate change. The findings shed light on the complex relationships between environmental degradation, ongoing colonial impacts on traditional practices, and the mental well‐being of Indigenous women. Concluding with implications for policy and community‐led interventions, this research contributes to the discourse on the intersectionality of climate change impacts and mental health, particularly focusing on Indigenous women in Western Canada. [ABSTRACT FROM AUTHOR]

This paper explores how politicians respond to the public salience of policy issues when determining which topics to publicly address. Using new data and state-of-the-art methodology, our study provides a fresh perspective on this fundamental question. We focus on a multi-party parliamentary system, specifically the Canadian House of Commons, with a specific emphasis on the issue of climate change. To assess the attention given by political parties to various policy issues, we analyze transcripts from the Question Period spanning from April 2006 to June 2021. To gauge the public's level of concern for these issues, we incorporate data obtained from Google Trends. Employing an instrumental variable estimation strategy, our study causally estimates the extent to which the public salience of climate change influences elite attention. Our findings reveal that the public salience of climate change significantly influences the attention given to this issue by parties, albeit with noticeable partisan variations. Moreover, our research highlights the effectiveness of the Question Period in compelling the government to address challenging or potentially embarrassing issues. Lastly, we uncover evidence suggesting that the Liberal Party of Canada successfully increased the public salience of climate change during its tenure in government. [ABSTRACT FROM AUTHOR]

Climate change has facilitated the introduction, establishment, and movement of invasive species in northern regions, enabling the colonization of previously unsuitable areas. While the responses of insects to these changes have been increasingly studied, our understanding of how such alterations impact trophic interactions still requires further research to make reliable predictions about the spread of diseases in a warming world. Phytoplasmas, a group of obligate parasitic unculturable Mollicutes, primarily rely on leafhoppers (Hemiptera: Cicadellidae) for transmission, spread, and survival. Phytoplasmas are associated with over 600 diseases affecting more than 1,000 plant species, including berries, grapevines, and other small fruits. In North America, diseases such as grapevine yellows, blueberry stunt, and strawberry green petal diseases have been linked to phytoplasma strains transmitted by known leafhopper species. However, the number of phytoplasma diseases has significantly increased in North America over the past decade, suggesting the presence of unidentified vectors or an abundance of leafhopper vectors. This short review provides an overview of the current knowledge on leafhoppers as vectors of phytoplasmas to berries, focusing on the last decade's research in Canada. This paper also explores the potential implications of climate change on this pathosystem, including the anticipated range expansion of leafhopper species, changes in phytoplasma acquisition and transmission, and the risk of new leafhopper-transmitted plant-pathogen introductions through the arrival of new leafhopper species. [ABSTRACT FROM AUTHOR]

The fate of the carbon stored in frozen peatlands in Canada's Hudson Bay Lowlands (HBL) depends strongly on water, with wetter conditions favoring long-term storage. Dynamic surface water products generated from historical Landsat data exist to inform surface water trends in the HBL based on binary classifications of land vs water at 30 m spatial resolution. However, the HBL contains many water features smaller than 30 m, including streams and patterned fens that require a sub-pixel mapping approach to fully capture their dynamics. In this paper, we leverage an existing binary dynamic surface water product to generate a spatially and temporally comprehensive Landsat sub-pixel surface water time-series over the HBL. We first generate Landsat Red, NIR and SWIR composites from 1985 to 2021 and evaluate data-driven machine learning and physical models to derive sub-30 m water fractions across the entire mapping domain. Data-driven models were calibrated on 30 m water fractions obtained from 16 of 17 WorldView scene water fraction maps and assessed on the 17th held-out scene in a jackknife validation. Data-driven models were also calibrated by relating scaled Landsat reflectance to water fractions obtained from binary water masks at corresponding scales from 90 to 270 m. Physical models involved simple linear unmixing using a new approach that samples land endmembers in the vicinity of each pixel to represent land reflectance, and a global water endmember sampled beneath permanent water in each image. The assumption of linear scaling was verified at sub-30 m to 270 m resolution for NIR, SWIR and NDVI, which were all highly correlated with water fraction and had no significant differences among water fraction – spectral feature relationships across the full range of scales. Each of 11 different methods and input spectral features were evaluated against WorldView water fractions and ranked based on nine criteria. We found that machine learning using all spectral features including local NIR land endmembers performed best among data-driven approaches, and linear unmixing of the NIR band using local land endmembers performed best among physical. Both best-performing methods were applied to the entire time-series and surface water area trends were calculated and compared with trends obtained from binary water masks. All three methods agree on the direction of surface water change towards wetting, with sub-pixel inter-annual variation agreeing with stream discharge noted in other studies. • Physical and data-driven Landsat water fraction methods tested in the Hudson Bay Lowlands. • Physical methods perform linear unmixing between local land and global water endmembers. • Data-driven methods consist of machine learning calibrated using high-resolution water. • Best methods applied to 1985–2021 Landsat time-series reveal overall wetting trends. • Spatial trends generally suggest drying in bogs and wetting in fens. [ABSTRACT FROM AUTHOR]