23
of evolutionary constraints and innovations due to legacies of their biogeographic
origins and the environmental conditions in which they evolved (Cavender-Bares
et al. 2016a; Pinto-Ledezma et al. 2018a). Historical contingencies play a role in
which lineages can take advantage of opportunities to diversify following climate
change or other disturbances and environmental transitions. The rate of species
range expansion and contraction and the evolution of species functional traits that
allow species to establish and persist in some regions or under particular environmental conditions but not elsewhere are shaped by biogeographic history (Moore
et al. 2018). For example, when species from two distinct lineages—one that
evolved in tropical climates and the other that evolved in temperate climates—colonize a new environment, they are predicted to persist in contrasting microhabitats as
a consequence of niche conservatism (Ackerly 2003; Harrison 2010; CavenderBares et al. 2016a). These evolutionary legacies—collectively referred to as “historical factors” (Ricklefs and Schluter 1993)—operate at different spatial and
temporal scales that leave their imprints on species current functional attributes and
distributions and consequently on ecosystem function itself (Fig. 2.4c, CavenderBares et al. 2016a). RS approaches can help reveal how the deep past has influenced
current biodiversity patterns and ecosystem function by decoupling climate and
geological setting from ecosystem function. Current and forthcoming RS instruments (Lausch et al., Chap. 13; Schimel et al., Chap. 19) enable the monitoring of
plant productivity, dynamics of vegetation growth, seasonal changes in chemical
composition, and other ecosystem properties independently of climate and geology.
These technologies thus provide opportunities to detect how biodiversity is sorted
across the globe and to determine how variable ecosystem functions can be in the
same geological and environmental setting. Both are important for developing
robust predictive models of how lineages respond to current and future environmental conditions with important consequences for managing ecosystems in the
Anthropocene.
2.7 Quantifying Multiple Dimensions of Biodiversity
Several major dimensions of biodiversity have emerged in the literature that capture
different aspects of the variation of life. Taxonomic diversity focuses on differences
between species or between higher-order clades, such as genera or families.
Estimating the numbers and/or abundances of different taxa across units of area
captures this variation. Phylogenetic diversity captures the evolutionary distances
between species or individuals, represented in terms of millions of years since
divergence from a common ancestor or molecular distances based on accumulated
mutations since divergence. Functional diversity focuses on the variation among
species as a consequence of measured differences in their functional traits, frequently calculated as a multivariate metric but also calculated for individual trait
variation. Spectral diversity captures the variability in spectral reflectance from vegetation (or from other surfaces), either measured and calculated among individual
2 Applying Remote Sensing to Biodiversity Science
of evolutionary constraints and innovations due to legacies of their biogeographic
origins and the environmental conditions in which they evolved (Cavender-Bares
et al. 2016a; Pinto-Ledezma et al. 2018a). Historical contingencies play a role in
which lineages can take advantage of opportunities to diversify following climate
change or other disturbances and environmental transitions. The rate of species
range expansion and contraction and the evolution of species functional traits that
allow species to establish and persist in some regions or under particular environmental conditions but not elsewhere are shaped by biogeographic history (Moore
et al. 2018). For example, when species from two distinct lineages—one that
evolved in tropical climates and the other that evolved in temperate climates—colonize a new environment, they are predicted to persist in contrasting microhabitats as
a consequence of niche conservatism (Ackerly 2003; Harrison 2010; CavenderBares et al. 2016a). These evolutionary legacies—collectively referred to as “historical factors” (Ricklefs and Schluter 1993)—operate at different spatial and
temporal scales that leave their imprints on species current functional attributes and
distributions and consequently on ecosystem function itself (Fig. 2.4c, CavenderBares et al. 2016a). RS approaches can help reveal how the deep past has influenced
current biodiversity patterns and ecosystem function by decoupling climate and
geological setting from ecosystem function. Current and forthcoming RS instruments (Lausch et al., Chap. 13; Schimel et al., Chap. 19) enable the monitoring of
plant productivity, dynamics of vegetation growth, seasonal changes in chemical
composition, and other ecosystem properties independently of climate and geology.
These technologies thus provide opportunities to detect how biodiversity is sorted
across the globe and to determine how variable ecosystem functions can be in the
same geological and environmental setting. Both are important for developing
robust predictive models of how lineages respond to current and future environmental conditions with important consequences for managing ecosystems in the
Anthropocene.
2.7 Quantifying Multiple Dimensions of Biodiversity
Several major dimensions of biodiversity have emerged in the literature that capture
different aspects of the variation of life. Taxonomic diversity focuses on differences
between species or between higher-order clades, such as genera or families.
Estimating the numbers and/or abundances of different taxa across units of area
captures this variation. Phylogenetic diversity captures the evolutionary distances
between species or individuals, represented in terms of millions of years since
divergence from a common ancestor or molecular distances based on accumulated
mutations since divergence. Functional diversity focuses on the variation among
species as a consequence of measured differences in their functional traits, frequently calculated as a multivariate metric but also calculated for individual trait
variation. Spectral diversity captures the variability in spectral reflectance from vegetation (or from other surfaces), either measured and calculated among individual
2 Applying Remote Sensing to Biodiversity Science