506
The functional traits are used to estimate parameters and state variables in terrestrial ecosystem models controlling growth, turnover, and microbial respiration.
As such they are key to Earth system prediction and simulation of future carbon
cycling. They also define specific ecosystem characteristics. For example, chlorophyll is linked to absorption of sunlight and so affects albedo and the surface energy
balance (Bonan 2016). Lignin and nitrogen content affect the palatability of forage
for herbivores (Hobbs et al. 1991), thus influencing higher trophic levels, and xanthophyll indices have been proposed as leading to improved models of carbon flux
(Garbulsky et al. 2010). Nitrogen additionally scales with the photosynthetic
enzyme concentration of plants and therefore is a widely used indicator of photosynthetic capacity (Chapin 2003). LMA is indicative of relative investment by a
plant in photosynthesis, leaf structure and/or leaf longevity and is strongly correlated with photosynthetic capacity (Poorter et al. 2009). The local diversity of plant
functional traits has also been used as a predictor of plant species richness (Féret
and Asner 2014) as well as for mapping functionally different plant communities
(Asner et al. 2017).
The set of traits called for in the National Academies (2018) report includes plant
characteristics long known to be useful for ecosystem studies (Schimel et al. 1991a),
ecosystem modeling (Melillo et al. 1982), and studies of higher trophic levels
(Hobbs et al. 1991). More recently, these same functional traits have been used in
Earth system models (Verheijen et al. 2015) and studies of global biogeography
(Butler et al. 2017; Moreno-Martínez et al. 2018). In many cases, particular species
with distinct spectral characteristics can be mapped (see National Academies 2018
for a review), and phylogenetic relationships have been mapped based on spectral
similarity (Cavender-Bares et al. 2016).
As a result of the studies mentioned above and many others, the National Academies
(2018) report identified an imaging spectrometer with global coverage as a high priority and designated it for inclusion in NASA’s next decadal program (2017–2027). This
instrument, provisionally dubbed Surface Biology and Geology (SBG), is the first
instrument planned for flight in the 2020s as a result of the 2018 decadal survey and
could fly mid-decade. As well, the European Space Agency is proceeding with planning for the similar CHIME (Copernicus Hyperspectral Imaging Mission for the
Environment) global imaging spectrometer (Rast et al. 2019).
19.2 Characteristics and Objectives for a Global Imaging
Spectrometer
A number of IS instruments have been used for ecological studies over the years,
starting with the AIS (the Airborne Imaging Spectrometer, Wessman et al. 1988)
and including a number of airborne and spaceborne instruments. These instruments
have all covered some part of the visible and shortwave infrared spectrum between
350 and 2500 nm, usually with spectral resolutions of 10–40 nm. Over the evolution
of this technology, the signal-to-noise performance has systematically improved, so
that ever-subtler spectral features could be resolved. Many other performance charD. Schimel et al.
The functional traits are used to estimate parameters and state variables in terrestrial ecosystem models controlling growth, turnover, and microbial respiration.
As such they are key to Earth system prediction and simulation of future carbon
cycling. They also define specific ecosystem characteristics. For example, chlorophyll is linked to absorption of sunlight and so affects albedo and the surface energy
balance (Bonan 2016). Lignin and nitrogen content affect the palatability of forage
for herbivores (Hobbs et al. 1991), thus influencing higher trophic levels, and xanthophyll indices have been proposed as leading to improved models of carbon flux
(Garbulsky et al. 2010). Nitrogen additionally scales with the photosynthetic
enzyme concentration of plants and therefore is a widely used indicator of photosynthetic capacity (Chapin 2003). LMA is indicative of relative investment by a
plant in photosynthesis, leaf structure and/or leaf longevity and is strongly correlated with photosynthetic capacity (Poorter et al. 2009). The local diversity of plant
functional traits has also been used as a predictor of plant species richness (Féret
and Asner 2014) as well as for mapping functionally different plant communities
(Asner et al. 2017).
The set of traits called for in the National Academies (2018) report includes plant
characteristics long known to be useful for ecosystem studies (Schimel et al. 1991a),
ecosystem modeling (Melillo et al. 1982), and studies of higher trophic levels
(Hobbs et al. 1991). More recently, these same functional traits have been used in
Earth system models (Verheijen et al. 2015) and studies of global biogeography
(Butler et al. 2017; Moreno-Martínez et al. 2018). In many cases, particular species
with distinct spectral characteristics can be mapped (see National Academies 2018
for a review), and phylogenetic relationships have been mapped based on spectral
similarity (Cavender-Bares et al. 2016).
As a result of the studies mentioned above and many others, the National Academies
(2018) report identified an imaging spectrometer with global coverage as a high priority and designated it for inclusion in NASA’s next decadal program (2017–2027). This
instrument, provisionally dubbed Surface Biology and Geology (SBG), is the first
instrument planned for flight in the 2020s as a result of the 2018 decadal survey and
could fly mid-decade. As well, the European Space Agency is proceeding with planning for the similar CHIME (Copernicus Hyperspectral Imaging Mission for the
Environment) global imaging spectrometer (Rast et al. 2019).
19.2 Characteristics and Objectives for a Global Imaging
Spectrometer
A number of IS instruments have been used for ecological studies over the years,
starting with the AIS (the Airborne Imaging Spectrometer, Wessman et al. 1988)
and including a number of airborne and spaceborne instruments. These instruments
have all covered some part of the visible and shortwave infrared spectrum between
350 and 2500 nm, usually with spectral resolutions of 10–40 nm. Over the evolution
of this technology, the signal-to-noise performance has systematically improved, so
that ever-subtler spectral features could be resolved. Many other performance charD. Schimel et al.