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.