As Arctic environments warm, it is expected that Arctic lakes will undergo changes to their chemical makeup and temperature regimes, with these changes then having effects on lake productivity. Because Arctic lakes represent a substantial source of methane into the atmosphere through microbial respiration, and this respiration will increase with increasing productivity, projecting future carbon fluxes from these lakes under warming conditions is an important facet of projections of the Arctic carbon budget (Bulínová et al., 2025). 

While it is relatively simple to map the abundance of lakes across the landscape through the use of remote sensing, mapped products which only detect water presence (e.g. multispectral water detection, such as Verpoorter et al., 2012) do not distinguish between differing types of lakes. Studies of individual lakes, and lakes within differing environmental conditions of the Arctic, have shown marked differences in chemical and thermal characteristics, productivity, and ways in which they are responding to warming (Larsen et al., 2017). Therefore, in order to make a statement about the likely methane contribution of warming lakes, they cannot be treated as monolithic.

Two potential methods of differentiating Arctic lakes are through a landscape-based classification system, either through manual identification of lakes, or through existing mapped products, such as surficial geology maps. Both of these methods operate under the basis that lake characteristics are functions of the landscapes surrounding them, such as basin morphology (affecting depth and thermal stratification) as a function of geological/geomorphic history (Coulombe et al., 2022), and water chemistry as a function of the surrounding catchment which it receives water from (Larsen et al., 2017; Stolpmann et al., 2021).

Previous work has been performed to develop a methodology for lake classification on a manual, per-lake basis (see Kokelj et al., 2023), which is limited in spatial scale due to the need for manual interpretation. Lake classification via surficial geology has also been performed, with correlation to lake chemistry shown (Larsen et al., 2017). 

 The goals of my analyses are 1) to determine whether a manual, geomorphic classification of lakes may be used as a meaningful predictor of lake chemistry and 2) to determine whether variation in lake chemistry may also be captured by classification of lakes from existing mapped data (i.e. surficial geology products). Either of the geomorphological and geological methods of lake classification, if successful in meaningfully distinguishing lake chemistry, would allow for more accurate estimates of lake productivity across large areas, as well as more effective, targeted sampling campaigns of Arctic lakes to fill gaps in data.