Recommendations

In ecosystems characterized by low accessibility and challenging terrain, including the Arctic tundra, remote sensing observations provide the only practical approach for observing, monitoring, and quantifying changes in vegetation structure, function, and distribution. However, to make the best use of these data and provide useful information for ecological research and specifically process modeling requires converting the remotely sensed observations (e.g., surface radiance or reflectance) to derived biophysical or functional quantities of interest (e.g., leaf area index, leaf functional traits). A range of approaches have been used to convert spectroscopic measurements to plant properties (Cawse-Nicholson et al., 2021; J. A. Gamon et al., 2019; Serbin & Townsend, 2020). However, the distinctive characteristics of the Arctic as described above requires separate approaches, differing from algorithms trained using data from temperate or tropical regions. Thus, developing effective scaling approaches to allow for mapping Arctic vegetation composition and function is a critical need and challenge.
To address this challenge, we recommend that a multi-scale approach (Table 2), including a mix of observations from laboratory, field, and novel platform studies (e.g., UAS, tower-mounted, sensor network including SpecNet) is used in coordination with satellite overpasses when possible. These observations must then be assessed cohesively, together with appropriate statistical and radiative transfer modeling (Figure 9, Table 2). Leaf-scale and controlled laboratory studies are often used to identify fundamental, underlying drivers of variation in leaf optical properties to aid in the development of algorithms for estimating leaf functional traits or evaluating leaf stress (e.g., Féret et al., 2011; J. A. Gamon et al., 1997; Hunt & Rock, 1989). However, such work has historically been limited in the Arctic in comparison with other ecosystems, suggesting that considerable uncertainty will remain through efforts to tie spectral observations to vegetation function. To efficiently address this issue, future spectroscopy campaigns should engage with laboratory and field studies to determine where multi-scale observations could be established.