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5.3.3 Spectranomics for Biodiversity Mapping
The Spectranomics fieldwork pointed toward two particular forecasts. First,
Spectranomics suggested that spectral mapping from current aircraft and future satellites will reveal where whole forest communities are functionally similar and
where they are unique. Second, Spectranomics suggested that spectral RS will
reveal the presence and patterning of specific canopy species, within communities
and across environmental gradients, based on their functional trait “signatures.”
Both forecasts were subsequently proven correct during mapping studies.
Numerous landscape-scale studies now show that location of particular forest canopy species and their evolved canopy functional traits mirror soil nutrient resources
mediated by topography, parent material, and climate (Higgins et al. 2014; Chadwick
and Asner 2016; Balzotti et al. 2016). These findings demonstrate that Spectranomics
directly connects plants to ecosystem processes such as biogeochemical cycles,
which form an essential link to the rest of the Earth system. At a larger scale, a 2016
report on Andean and Amazonian forests mapped with airborne imaging spectroscopy confirmed the forecasted ecological shifts in forest canopy functional composition, sorted geographically by large-scale environmental factors including
elevation, geology, soils, and climate (Fig. 5.2b, c; Asner et al. 2017). While the
Spectranomics database provided a field-based preview of how communities of species would differ from one another, the mapping step provided a first synoptic view
of the geographic distribution. Importantly, the mapping phase also revealed numerous new combinations of functional traits that had not been detected in the field
program. The new canopy functional trait maps are a key stepping-stone to biogeographic assembly, not only of the functional diversity of the Andes-to-Amazon but
also of the biological diversity of the region. The approach from Peru is currently
being applied in Ecuador as well as Malaysian Borneo.
The second forecast from Spectranomics—which coexisting species within
communities can maintain relatively unique canopy functional traits and spectral
properties—has been explored and confirmed in a series of studies using airborne
and space-based imaging spectroscopy. From Hawaii to Panama, and from Africa to
the Amazon, hundreds of target species have been mapped based on their spectral
signatures, underpinned by a knowledge of their functional traits (Fig. 5.3; Carlson
et al. 2007; Papeş et al. 2010; Colgan et al. 2012; Baldeck and Asner 2014; Baldeck
et al. 2015; Graves et al. 2016). Further, the new concept of “spectral species” was
developed to map species richness (alpha diversity) and compositional turnover
(beta diversity) in forest landscapes without the need to detect individual species
(Féret and Asner 2014).The separability of the spectral species is determined by
their canopy functional traits.
More broadly, Spectranomics has enabled a different kind of interaction between
field or laboratory studies of plants and RS of functional and biological diversity of
ecosystems. The forecasting capability made possible with the Spectranomics
database has been central to planning whether and how to undertake spectral mapping activities in different regions and under what environmental conditions the RS
technology will yield new insight. In turn, this has transformed the interaction
5 Lessons Learned from Spectranomics: Wet Tropical Forests
5.3.3 Spectranomics for Biodiversity Mapping
The Spectranomics fieldwork pointed toward two particular forecasts. First,
Spectranomics suggested that spectral mapping from current aircraft and future satellites will reveal where whole forest communities are functionally similar and
where they are unique. Second, Spectranomics suggested that spectral RS will
reveal the presence and patterning of specific canopy species, within communities
and across environmental gradients, based on their functional trait “signatures.”
Both forecasts were subsequently proven correct during mapping studies.
Numerous landscape-scale studies now show that location of particular forest canopy species and their evolved canopy functional traits mirror soil nutrient resources
mediated by topography, parent material, and climate (Higgins et al. 2014; Chadwick
and Asner 2016; Balzotti et al. 2016). These findings demonstrate that Spectranomics
directly connects plants to ecosystem processes such as biogeochemical cycles,
which form an essential link to the rest of the Earth system. At a larger scale, a 2016
report on Andean and Amazonian forests mapped with airborne imaging spectroscopy confirmed the forecasted ecological shifts in forest canopy functional composition, sorted geographically by large-scale environmental factors including
elevation, geology, soils, and climate (Fig. 5.2b, c; Asner et al. 2017). While the
Spectranomics database provided a field-based preview of how communities of species would differ from one another, the mapping step provided a first synoptic view
of the geographic distribution. Importantly, the mapping phase also revealed numerous new combinations of functional traits that had not been detected in the field
program. The new canopy functional trait maps are a key stepping-stone to biogeographic assembly, not only of the functional diversity of the Andes-to-Amazon but
also of the biological diversity of the region. The approach from Peru is currently
being applied in Ecuador as well as Malaysian Borneo.
The second forecast from Spectranomics—which coexisting species within
communities can maintain relatively unique canopy functional traits and spectral
properties—has been explored and confirmed in a series of studies using airborne
and space-based imaging spectroscopy. From Hawaii to Panama, and from Africa to
the Amazon, hundreds of target species have been mapped based on their spectral
signatures, underpinned by a knowledge of their functional traits (Fig. 5.3; Carlson
et al. 2007; Papeş et al. 2010; Colgan et al. 2012; Baldeck and Asner 2014; Baldeck
et al. 2015; Graves et al. 2016). Further, the new concept of “spectral species” was
developed to map species richness (alpha diversity) and compositional turnover
(beta diversity) in forest landscapes without the need to detect individual species
(Féret and Asner 2014).The separability of the spectral species is determined by
their canopy functional traits.
More broadly, Spectranomics has enabled a different kind of interaction between
field or laboratory studies of plants and RS of functional and biological diversity of
ecosystems. The forecasting capability made possible with the Spectranomics
database has been central to planning whether and how to undertake spectral mapping activities in different regions and under what environmental conditions the RS
technology will yield new insight. In turn, this has transformed the interaction
5 Lessons Learned from Spectranomics: Wet Tropical Forests