As global observations of solar-induced chlorophyll fluorescence (SIF) have become available from multiple satellite platforms, SIF is increasingly used as a proxy for photosynthetic activity and ecosystem productivity. Because the relationship between SIF and gross primary productivity (GPP) depends on a variety of factors including ecosystem type and environmental conditions, it is necessary to study SIF observations across various spatiotemporal scales and ecosystems. To explore how SIF signals relate to productivity over a temperate deciduous forest, we deployed a PhotoSpec spectrometer system at the University of Michigan Biological Station AmeriFlux site (US-UMB) in the northern Lower Peninsula of Michigan during the 2018 and 2019 growing seasons. The PhotoSpec system consisted of two narrowband spectrometers, for the retrieval of SIF in the red (680-686 nm) and far-red (745-758 nm) regions of the electromagnetic spectrum, and a broadband spectrometer for the assessment of vegetation indices. We found that SIF correlated with GPP across diurnal and seasonal cycles, but that SIF irradiances were more strongly related to downwelling radiation than GPP. However, while this dependence of SIF on radiation obscured drought signals in SIF itself, we demonstrate that a SIF response to severe drought was apparent as a decrease in relative SIF. These results highlight the potential of SIF for detecting stress-induced losses in forest productivity. Additionally, we found that the red:far-red SIF ratio did not exhibit a response to drought stress, but was largely driven by seasonal and interannual changes in canopy structure, as well as by synoptic changes in downwelling radiation.

Observing the environment in the vast inaccessible regions of Earth through remote sensing platforms provides the tools to measure ecological dynamics. The Arctic tundra biome, one of the largest inaccessible terrestrial biomes on Earth, requires remote sensing across multiple spatial and temporal scales, from towers to satellites, particularly those equipped for imaging spectroscopy (IS). We describe a rationale for using IS derived from advances in our understanding of Arctic tundra vegetation communities and their interaction with the environment. To best leverage ongoing and forthcoming IS resources, including NASA’s Surface Biology and Geology mission, we identify a series of opportunities and challenges based on intrinsic spectral dimensionality analysis and a review of current data and literature that illustrates the unique attributes of the Arctic tundra biome. These opportunities and challenges include thematic vegetation mapping, complicated by low-stature plants and very fine-scale surface composition heterogeneity; development of scalable algorithms for retrieval of canopy and leaf traits; nuanced variation in vegetation growth and composition that complicates detection of long-term trends; and rapid phenological changes across brief growing seasons that may go undetected due to low revisit frequency or be obscured by snow cover and clouds. We recommend improvements to future field campaigns and satellite missions, advocating for research that combines multi-scale spectroscopy, from lab studies to satellites that enable frequent and continuous long term monitoring, to inform statistical and biophysical approaches to model vegetation dynamics.