45
evidence for detection in the literature relate to plant allocation strategies (e.g.,
starch and sugar content) or defense compounds, such as phenolics (e.g., Asner
et al. 2015; Kokaly and Skidmore 2015; Couture et al. 2016; Ely et al. 2019).
Despite the importance of characterizing leaf and plant functional traits across
global biomes, the plasticity and high functional diversity of these traits makes this
apparently simple goal extremely challenging (Reich et al. 1997; Wu et al. 2017;
Osnas et al. 2018), and as such global coverage has been historically limited to specific biomes (Schimel et al. 2015). Leaf traits can vary strongly within and across
species (Serbin et al. 2014; Osnas et al. 2018) and are strongly mediated by an array
of biotic and abiotic factors (Díaz et al. 2015; Neyret et al. 2016; Butler et al. 2017).
Within a canopy, for example, functional traits typically show high variation with
average light condition and quality (Niinemets 2007; Neyret et al. 2016) where
lower canopy leaves tend to be thinner and have lower photosynthetic rates and
altered pigment pools to account for the lower light quality. Plant traits can also
change across local resource gradients, including with variations in water, nutrient
availability, and disturbance legacy (Singh et al. 2015; Butler et al. 2017; Enquist
et al. 2017). Importantly, this pattern can be confounded by species composition,
which is generally the strongest driver of trait variation.
RS has provided new avenues to explore trait variation at larger scales and continuously across landscapes (Fig. 3.1). For example, Dahlin et al. (2013) observed
that leaf functional traits were more strongly mediated by plant community composition than environment across a water-limited Mediterranean ecosystem, explaining 46–61% of the variation on the landscape. Likewise, McNeil et al. (2008) found
that 93% of variation in nutrient cycling in northern hardwood forests of the US
Adirondacks could be explained by species identity. Yet the presence or absence of
specific plant species is, in part, a consequence of habitat sorting processes and the
adaptive mechanisms of plants that influence the environments in which they can
persist, including their modification of traits in response to local conditions (Reich
et al. 2003). Mapping species or communities to infer traits is impractical at anything other than the local scale due to the presence of more than 200,000 plant species on Earth. Dispersal and other stochastic processes also play a role. Across
broad environmental gradients, traits display much larger variation, where climate,
topography, and edaphic conditions drive changes in plant community composition
and structure, which, in turn, drive the patterns of potential and realized plant traits
in any one location (Díaz et al. 2015; Butler et al. 2017). Finally, factors such as
convergent evolution may make some species spectrally similar, while phenology
and phenotypic variation may make the same species look different across locations.
Temporal regulation of traits is a key factor driving changes in functional properties and the resulting functioning of the ecosystem. Seasonal changes in traits can
be significant (e.g., Yang et al. 2016) and can strongly regulate vegetation functioning (e.g., Wong and Gamon 2015). Moreover, during the lifetime of a leaf, traits can
change significantly (e.g., Wilson et al. 2001; Niinemets 2016), and in evergreen
species, leaf age has been shown to be a strong covariate with functional trait values
(e.g., Chavana-Bryant et al. 2017; Wu et al. 2017). Age-dependent and phenological
changes in leaf traits can, in turn, have significant impacts on ecosystem functioning
3 Scaling Functional Traits from Leaves to Canopies
evidence for detection in the literature relate to plant allocation strategies (e.g.,
starch and sugar content) or defense compounds, such as phenolics (e.g., Asner
et al. 2015; Kokaly and Skidmore 2015; Couture et al. 2016; Ely et al. 2019).
Despite the importance of characterizing leaf and plant functional traits across
global biomes, the plasticity and high functional diversity of these traits makes this
apparently simple goal extremely challenging (Reich et al. 1997; Wu et al. 2017;
Osnas et al. 2018), and as such global coverage has been historically limited to specific biomes (Schimel et al. 2015). Leaf traits can vary strongly within and across
species (Serbin et al. 2014; Osnas et al. 2018) and are strongly mediated by an array
of biotic and abiotic factors (Díaz et al. 2015; Neyret et al. 2016; Butler et al. 2017).
Within a canopy, for example, functional traits typically show high variation with
average light condition and quality (Niinemets 2007; Neyret et al. 2016) where
lower canopy leaves tend to be thinner and have lower photosynthetic rates and
altered pigment pools to account for the lower light quality. Plant traits can also
change across local resource gradients, including with variations in water, nutrient
availability, and disturbance legacy (Singh et al. 2015; Butler et al. 2017; Enquist
et al. 2017). Importantly, this pattern can be confounded by species composition,
which is generally the strongest driver of trait variation.
RS has provided new avenues to explore trait variation at larger scales and continuously across landscapes (Fig. 3.1). For example, Dahlin et al. (2013) observed
that leaf functional traits were more strongly mediated by plant community composition than environment across a water-limited Mediterranean ecosystem, explaining 46–61% of the variation on the landscape. Likewise, McNeil et al. (2008) found
that 93% of variation in nutrient cycling in northern hardwood forests of the US
Adirondacks could be explained by species identity. Yet the presence or absence of
specific plant species is, in part, a consequence of habitat sorting processes and the
adaptive mechanisms of plants that influence the environments in which they can
persist, including their modification of traits in response to local conditions (Reich
et al. 2003). Mapping species or communities to infer traits is impractical at anything other than the local scale due to the presence of more than 200,000 plant species on Earth. Dispersal and other stochastic processes also play a role. Across
broad environmental gradients, traits display much larger variation, where climate,
topography, and edaphic conditions drive changes in plant community composition
and structure, which, in turn, drive the patterns of potential and realized plant traits
in any one location (Díaz et al. 2015; Butler et al. 2017). Finally, factors such as
convergent evolution may make some species spectrally similar, while phenology
and phenotypic variation may make the same species look different across locations.
Temporal regulation of traits is a key factor driving changes in functional properties and the resulting functioning of the ecosystem. Seasonal changes in traits can
be significant (e.g., Yang et al. 2016) and can strongly regulate vegetation functioning (e.g., Wong and Gamon 2015). Moreover, during the lifetime of a leaf, traits can
change significantly (e.g., Wilson et al. 2001; Niinemets 2016), and in evergreen
species, leaf age has been shown to be a strong covariate with functional trait values
(e.g., Chavana-Bryant et al. 2017; Wu et al. 2017). Age-dependent and phenological
changes in leaf traits can, in turn, have significant impacts on ecosystem functioning
3 Scaling Functional Traits from Leaves to Canopies