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Abstract Arctic rodents influence tundra plant communities by altering species diversity, structure, and nutrient dynamics. These dynamics are intensified during rodent population peaks. Plants are known to induce defenses in response to rodent herbivory. However, changes in plant tissue digestibility may also play a role in deterring rodents or impacting their survival. This study presents a first look at the impacts of rodent herbivory on crude protein (CP) and acid detergent fiber (ADF) of three of the most common graminoid species (Calamagrostis sp.,Carex nigraandDeschampsia cespitosa) in the tundra meadows of the Varanger Peninsula, Norway. We selected 32 experimental plots representing both rodent-disturbed and adjacent, undisturbed control graminoid patches. During a rodent population peak, the disturbed plots had higher ADF (28.5%) values than less disturbed ones (26.6%), controlling for plant species. We also found differences between species, withCarex nigrahaving the lowest fiber content (24.3%, ADF) and highest protein content (18.2% CP) – making it the most palatable species. These results show that rodent activity can potentially alter plant food quality, suggesting that increased fiber content may be a defensive adaptation against herbivory. 

Abstract. The Arctic poses many challenges for Earth system and snow physics models, which are commonly unable to simulate crucial Arctic snowpack processes,such as vapour gradients and rain-on-snow-induced ice layers. These limitations raise concerns about the current understanding of Arctic warming and its impact on biodiversity, livelihoods, permafrost, and the global carbon budget. Recognizing that models are shaped by human choices, 18 Arctic researchers were interviewed to delve into the decision-making process behind model construction. Although data availability, issues of scale, internal model consistency, and historical and numerical model legacies were cited as obstacles to developing an Arctic snowpack model, no opinion was unanimous. Divergences were not merely scientific disagreements about the Arctic snowpack but reflected the broader research context. Inadequate and insufficient resources, partly driven by short-term priorities dominating research landscapes, impeded progress. Nevertheless, modellers were found to be both adaptable to shifting strategic research priorities – an adaptability demonstrated by the fact that interdisciplinary collaborations were the key motivation for model development – and anchored in the past. This anchoring and non-epistemic values led to diverging opinions about whether existing models were “good enough” and whether investing time and effort to build a new model was a useful strategy when addressing pressing research challenges. Moving forward, we recommend that both stakeholders and modellers be involved in future snow model intercomparison projects in order to drive developments that address snow model limitations currently impeding progress in various disciplines. We also argue for more transparency about the contextual factors that shape research decisions. Otherwise, the reality of our scientific process will remain hidden, limiting the changes necessary to our research practice. 

Abstract Science, engineering, and society increasingly require integrative thinking about emerging problems in complex systems, a notion referred to as convergence science. Due to the concurrent pressures of two main stressors—rapid climate change and industrialization, Arctic research demands such a paradigm of scientific inquiry. This perspective represents a synthesis of a vision for its application in Arctic system studies, developed by a group of disciplinary experts consisting of social and earth system scientists, ecologists, and engineers. Our objective is to demonstrate how convergence research questions can be developed via a holistic view of system interactions that are then parsed into material links and concrete inquiries of disciplinary and interdisciplinary nature. We illustrate the application of the convergence science paradigm to several forms of Arctic stressors using the Yamal Peninsula of the Russian Arctic as a representative natural laboratory with a biogeographic gradient from the forest‐tundra ecotone to the high Arctic.