Abstract
We present the R package bigleaf (version 0.6.5), an open source toolset for the derivation of meteorological, aerodynamic, and physiological ecosystem properties from eddy covariance (EC) flux observations and concurrent meteorological measurements. A ‘big-leaf’ framework, in which vegetation is represented as a single, uniform layer, is employed to infer bulk ecosystem characteristics top-down from the measured fluxes. Central to the package is the calculation of a bulk surface/canopy conductance (Gs/Gc) and a bulk aerodynamic conductance (Ga), with the latter including formulations for the turbulent and canopy boundary layer components. The derivation of physical land surface characteristics such as surface roughness parameters, wind profile, aerodynamic and radiometric surface temperature, surface vapor pressure deficit (VPD), potential evapotranspiration (ET), imposed and equilibrium ET, as well as vegetation-atmosphere decoupling coefficients, is described. The package further provides calculation routines for physiological ecosytem properties (stomatal slope parameters, stomatal sensitivity to VPD, bulk intercellular CO2 concentration, canopy photosynthetic capacity), energy balance characteristics (closure, biochemical energy), ancillary meteorological variables (psychrometric constant, saturation vapor pressure, air density, etc.), customary unit interconversions and data filtering. The target variables can be calculated with a different degree of complexity, depending on the amount of available site-specific information. The utilities of the package are demonstrated for three single-level (above-canopy) eddy covariance sites representing a temperate grassland, a temperate needle-leaf forest, and a Mediterranean evergreen broadleaf forest. The routines are further tested for a two-level EC site (tree and grass layer) located in a Mediterranean oak savanna. The limitations and the ecophysiological interpretation of the derived ecosystem properties are discussed and practical guidelines are given. The package provides the basis for a consistent, physically sound, and reproducible characterization of biometeorological conditions and ecosystem physiology, and is applicable to EC sites across vegetation types and climatic conditions with minimal ancillary data requirements.
Highlights
The eddy covariance (EC) technique provides direct and continuous measurements of the exchange of heat, water vapor, carbon dioxide, and other trace gases between the surface and the lower atmosphere [1, 2]
The method has significantly contributed to our understanding of how this mass and energy exchange is controlled by environmental drivers such as radiation [3, 4], temperature, vapor pressure deficit (VPD) [5, 6], or soil water stress [7], and how it is modulated by meteorological extreme events such as heatwaves [8, 9]
All calculations implemented in the bigleaf package are based on the ‘big-leaf’ framework [35, 44], which reduces the ecosystem to a single, uniform plane (Fig 1)
Summary
The eddy covariance (EC) technique provides direct and continuous measurements of the exchange of heat, water vapor, carbon dioxide, and other trace gases between the surface and the lower atmosphere [1, 2]. The function roughness.parameters() provides three options: 1) an empirical approach assuming d and z0m as constant fractions of canopy height zh (by default d = 0.7zh and z0m = 0.1zh), 2) a semi-empirical approach estimating both z0m and d based on zh and leaf area index (LAI) according to [51] for data presented in [52], and 3) an approach that calculates z0m from the logarithmic wind profile equation with a prescribed d. Computations in the bigleaf package are fast, e.g. with a state-of-the-art PC it takes < 0.1 seconds to calculate Gs for 10 site years and 2-3 seconds to calculate all properties as shown in Tables 2 and 3
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