Isumaqatigingniq: Building a Transformational Science Education Model to Engage the Next Generation of Inuit and Western Scientific Investigators

Inuit Qaujimajatuqangit (IQ), “the Inuit way of knowing,” and science each approach observation of the natural and physical world from shared yet different epistemologies. Studies that integrate IQ and science demonstrate the inherent value of using observations and findings from both to understand Arctic systems. Yet holders of IQ and scientists often do not fully comprehend the practice of the other because they think and approach observation and knowledge differently. Using the concept of Isumaqatigingniq, or “thinking together,” we will form an educational program, Isumaqatigingniq-Science, Technology, Engineering and Mathematics, (I-STEM), that will highlight and integrate studies of the narwhal and the Arctic environment undertaken with contributions from IQ and science. Program outreach will target high school students from both Inuit and non-Inuit backgrounds. Understanding existing efforts that combine these knowledge frames will hopefully inspire future collaborations by these groups. Learning through I-STEM will better equip students to address scientific themes that design, optimize, and implement collaborative observation systems. Inuit and scientific research efforts are essential for a deeper understanding of the Arctic environment. Implementing an active educational program that engages high school youth to understand the value of incorporating these two ways of knowing will help foster a future educational environment of collaboration. The educational I-STEM model will bring a new Inuit perspective to formal scientific education programs and share perspectives of science and Inuit knowledge within Inuit educational programs. Isumaqatigingniq can continue growing, incorporating new perspectives on Arctic observations and knowledge.

The immune response and diving: conservation considerations for belugas (Delphinapterus leucas) in a changing Arctic environment

Diving is a critical behaviour of marine mammals, including belugas, which dive to forage and travel under Arctic sea ice. While the limitations of dive behaviour and physiological dive adaptations have been the focus of several studies, cellular adaptations, particularly those of the immune system, have been little considered. However, diving itself presents several challenges that can impact immune responses, leading to disease or injury. As beluga dive their behaviour changes in response to human activity or environmental shifts. It is necessary to better understand how the beluga’s immune system functions during diving. This review provides a brief overview of what is known about beluga’s diving behaviour and physiology and discusses the first efforts to understand the link between diving and health via immune function in belugas. This new area of research is an important consideration regarding potential sub-lethal impacts of a rapidly changing Arctic environment on beluga’s diving behaviour, health and disease susceptibility.

Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data

As a result of the warming observed at high latitudes, there is significant potential for the balance of ecosystem processes to change, i.e., the balance between carbon sequestration and respiration may be altered, giving rise to the release of soil carbon through elevated ecosystem respiration. Gross ecosystem productivity and ecosystem respiration vary in relation to the pattern of vegetation community type and associated biophysical traits (e.g., percent cover, biomass, chlorophyll concentration, etc.). In an arctic environment where vegetation is highly variable across the landscape, the use of high spatial resolution imagery can assist in discerning complex patterns of vegetation and biophysical variables. The research presented here examines the relationship between ecological and spectral variables in order to generate an ecologically meaningful vegetation classification from high spatial resolution remote sensing data. Our methodology integrates ordination and image classifications techniques for two non-overlapping Arctic sites across a 5° latitudinal gradient (approximately 70° to 75°N). Ordination techniques were applied to determine the arrangement of sample sites, in relation to environmental variables, followed by cluster analysis to create ecological classes. The derived classes were then used to classify high spatial resolution IKONOS multispectral data. The results demonstrate moderate levels of success. Classifications had overall accuracies between 69%–79% and Kappa values of 0.54–0.69. Vegetation classes were generally distinct at each site with the exception of sedge wetlands. Based on the results presented here, the combination of ecological and remote sensing techniques can produce classifications that have ecological meaning and are spectrally separable in an arctic environment. These classification schemes are critical for modeling ecosystem processes.

Arctic Ecological Classifications Derived from Vegetation Community and Satellite Spectral Data

As a result of the warming observed at high latitudes, there is significant potential for the balance of ecosystem processes to change, i.e., the balance between carbon sequestration and respiration may be altered, giving rise to the release of soil carbon through elevated ecosystem respiration. Gross ecosystem productivity and ecosystem respiration vary in relation to the pattern of vegetation community type and associated biophysical traits (e.g., percent cover, biomass, chlorophyll concentration, etc.). In an arctic environment where vegetation is highly variable across the landscape, the use of high spatial resolution imagery can assist in discerning complex patterns of vegetation and biophysical variables. The research presented here examines the relationship between ecological and spectral variables in order to generate an ecologically meaningful vegetation classification from high spatial resolution remote sensing data. Our methodology integrates ordination and image classifications techniques for two non-overlapping Arctic sites across a 5° latitudinal gradient (approximately 70° to 75°N). Ordination techniques were applied to determine the arrangement of sample sites, in relation to environmental variables, followed by cluster analysis to create ecological classes. The derived classes were then used to classify high spatial resolution IKONOS multispectral data. The results demonstrate moderate levels of success. Classifications had overall accuracies between 69%–79% and Kappa values of 0.54–0.69. Vegetation classes were generally distinct at each site with the exception of sedge wetlands. Based on the results presented here, the combination of ecological and remote sensing techniques can produce classifications that have ecological meaning and are spectrally separable in an arctic environment. These classification schemes are critical for modeling ecosystem processes.

Airborne fungi in Longyearbyen area (Svalbard, Norway) — case study

Studies on the presence of atmospheric fungi in both Arctic and Antarctic polar areas are rare, and many of them were carried out briefly. Currently, when climate change is a fact, polar areas may be subject to various changes and fluctuations, negatively affecting sensitive polar ecosystems. The paper presents the results of tests on presence of fungi in the air over 30 years after the last investigations at the Svalbard Archipelago. A total of fifteen taxa of fungi were isolated in area of Longyearbyen, the majority of which were saprotrophic fungi of the genus Cladosporium that are associated with dead organic matter. Therefore, the presence of this taxon may be a good bioindicator of changes occurring in the Arctic environment, indirectly indicating the melting of glaciers and exposing increasingly larger areas inhabited by microorganisms, including fungi, which increase in number in the air. Additionally, the number of tourists visiting Longyearbyen is increasing, which may significantly affect the number and type of fungi in the air.