Wood carbon (C) concentration is a key wood trait that varies widely among tree species, but our understanding of the factors governing this trait is limited, despite reason to hypothesize that wood C varies systematically across environmental gradients. We compiled a novel database of 1145 geo‐referenced wood C observations from 415 species, to elucidate climate correlates of wood C concentrations, and test if these relationships differ across tissue types and major taxonomic divisions (i.e. angiosperms vs gymnosperms). Climate variables, including mean annual temperature (MAT) and precipitation and temperature seasonality, are significantly correlated with wood C concentrations. Relationships between wood C and these variables differ across tissue types and taxonomic divisions, yet there is a negative relationship between wood C and MAT that exists across all tissues and species groups. Wood C concentrations in trees are influenced by climate, with experimental evidence (albeit scant) indicating that climate‐driven changes in lignin concentrations likely govern these relationships. Our study presents among the first lines of evidence indicating that wood C concentrations are correlated with environmental conditions, thereby enhancing our understanding of the potential adaptive significance of wood C variation in trees.
Woody tissue carbon (C) concentration is a key wood trait necessary for accurately estimating forest C stocks and fluxes, which also varies widely across species and biomes. However, coarse approximations of woody tissue C (e.g., 50%) remain commonplace in forest C estimation and reporting protocols, despite leading to substantial errors in forest C estimates. Here, we describe the Global Woody Tissue Carbon Concentration Database (GLOWCAD): a database containing 3,676 individual records of woody tissue C concentrations from 864 tree species. Woody tissue C concentration data—i.e., the mass of C per unit dry mass—were obtained from live and dead woody tissues from 130 peer-reviewed sources published between 1980–2020. Auxiliary data for each observation include tissue type, as well as decay class and size characteristics for dead wood. In GLOWCAD, 1,242 data points are associated with geographic coordinates, and are therefore presented alongside 46 standardized bioclimatic variables extracted from climate databases. GLOWCAD represents the largest available woody tissue C concentration database, and informs studies on forest C estimation, as well as analyses evaluating the extent, causes, and consequences of inter- and intraspecific variation in wood chemical traits.
Variability in traits forming the Leaf Economics Spectrum (LES) among and within crop species play a key role in governing agroecosystem processes. However, studies evaluating the extent, causes, and consequences of within-species variation in LES traits for some of the world’s most common crops remain limited. We quantified variation in nine leaf traits measured across 90 vines of five wine grape (Vitis vinifera) varieties at two ontogenetic stages. Grape traits covary along an intraspecific LES, in patterns similar to those documented in wild plants. Across varieties, high rates of photosynthesis (A), and leaf nitrogen (N) concentrations, are coupled with low leaf mass per area (LMA), while the opposite suite of traits defines the “resource conserving end” of this intraspecific LES in grape. Variety identity predicted of leaf physiological (A) and morphological traits (i.e., leaf area and leaf mass), while leaf chemical traits and LMA were best explained by ontogenetic stage. All varieties expressed greater resource conserving trait syndromes (i.e., higher LMA, lower N, lower Amass) later in the growing season. Traits related to leaf hydraulics, including instantaneous water-use efficiency (WUE), were unrelated to LES and other resource capture traits, and were better explained by spatial location. Our results highlight the relative contributions of genetic vs. phenotypic factors in structuring this variation and point to a key role of domestication in governing trait relationships in the world’s crops.
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