Abstract
AbstractIn this chapter, we begin by exploring the relationship between plant functional traits and functional diversity and how this relates to the characterization and monitoring of global plant biodiversity. We then discuss the connection between leaf functional traits and their resulting optical properties (i.e., reflectance, transmittance, and absorption) and how this related to remote sensing (RS) of functional diversity. Building on this, we briefly discuss the history of RS of functional traits using spectroscopy and imaging spectroscopy data. We include a discussion of the key considerations with the use of imaging spectroscopy data for scaling and mapping plant functional traits across diverse landscapes. From here we provide a review of the general methods for scaling and mapping functional traits, including empirical and radiative transfer model (RTM) approaches. We complete the chapter with a discussion of other key considerations, such as field sampling protocols, as well as current caveats and future opportunities.
Highlights
Fossil energy use and land use change are the dominant drivers of the accelerating increase in atmospheric CO2 concentration and the principal causes of global climate change (IPCC 2018; IPBES 2018)
ACategories of functional characterization are for organizational purposes only: Primary refers to compounds that are critical to photosynthetic metabolism; Physical refers to non-metabolic attributes that are important indicators of photosynthetic activity and plant resource allocation; Metabolism refers to measurements used to describe rate limits on photosynthesis; and Secondary refers compounds that are not directly related to plant growth, but indirectly related to plant function through associations with nutrient cycling, decomposition, community dynamics, and stress responses economics spectrum (Wright et al 2004), and the development of global-scale foliar trait databases (Kattge et al 2011)
These models provide enhanced detail in the modeling of vegetation canopies but are necessarily more complex. Often these models require additional information to model vegetation “scenes,” which can include information on tree crown shape, stem location, and other properties in addition to leaf optical properties, sun-sensor geometry, and leaf area index (LAI). These models range from 3-D Monte Carlo ray-tracing models, such as FLIGHT (North 1996) and FLiES (Kobayashi and Iwabuchi 2008), to analytical and hybrid approaches using a variety of canopy structure schemes including geometric optical (GO) representation of individual plants where tree placement follows a statistical distribution and leaf and stem scattering elements are homogenously distributed (e.g., Kuusk and Nilson 2000; Nilson et al 2003)
Summary
Fossil energy use and land use change are the dominant drivers of the accelerating increase in atmospheric CO2 concentration and the principal causes of global climate change (IPCC 2018; IPBES 2018). The impact of our changing climate and altered disturbance regimes on terrestrial ecosystems is a major focus of a number of disciplines, including the biodiversity, remote sensing (RS), and global change research communities. We provide an overview of approaches to scale and map plant functional traits and diversity across landscapes with a focus on current approaches, leveraging on best practices provided by Schweiger 15), benefits and issues with general techniques for linking and scaling traits and spectra, and other key considerations that need to be addressed when utilizing RS observations to infer plant functional traits across diverse landscapes.
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