The GenTree Leaf Collection: Inter‐ and intraspecific leaf variation in seven forest tree species in Europe

Abstract

Motivation Trait variation within species can reveal plastic and/or genetic responses to environmental gradients, and may indicate where local adaptation has occurred. Here, we present a dataset of rangewide variation in leaf traits from seven of the most ecologically and economically important tree species in Europe. Sample collection and trait assessment are embedded in the GenTree project (EU‐Horizon 2020), which aims at characterizing the genetic and phenotypic variability of forest tree species to optimize the management and sustainable use of forest genetic resources. Our dataset captures substantial intra‐ and interspecific leaf phenotypic variability, and provides valuable information for studying the relationship between ecosystem functioning and trait variability of individuals, and the response and resilience of species to environmental changes. Main types of variable contained We chose morphological and chemical characters linked to trade‐offs between acquisition and conservation of resources and water use, namely specific leaf area, leaf size, carbon and nitrogen content and their ratio, and the isotopic signature of stable isotope 13C and 15N in leaves. Spatial location and grain We surveyed between 18 and 22 populations per species, 141 in total, across Europe. Time period Leaf sampling took place between 2016 and 2017. Major taxa and level of measurement We sampled at least 25 individuals in each population, 3,569 trees in total, and measured traits in 35,755 leaves from seven European tree species, i.e. the conifers Picea abies, Pinus pinaster and Pinus sylvestris, and the broadleaves Betula pendula, Fagus sylvatica, Populus nigra and Quercus petraea. Software format The data files are in ASCII text, tab delimited, not compressed.

Phenotypes of Pinus sylvestris are more coordinated under local harsher conditions across Europe

“…Specifically, in the field we measured tree height (H, m); diameter at breast height (DBH, cm); crown size, calculated with two perpendicular diameters of the crown projection (CP, m 2 ); bark thickness (Brk, mm), as the average of three to five measurements using a bark thickness gauge (Haglöf Barktax, Sweden); and trunk straightness (TSt) following the scale: (a) moderate or strong bends, (b) slight to moderate bend in different directions, (c) fairly straight (in one direction slightly crooked) and (d) absolutely straight (Opgenoorth et al., 2020). In addition, one wood core was extracted at breast height (1.3 m), perpendicular to the slope direction to avoid reaction wood, to assess wood density (WD, g/cm 3 ; Martínez‐Sancho et al., 2019, 2020) and one branch from the top of the crown to assess leaf traits (Benavides et al., 2021). For the latter, we collected ten needles of the last complete growing season from each branch (totalling 5,110 needles), scanned them and measured their projected area (LA, mm 2 ) using WinFOLIA (Regent Instruments Inc., Canada), considered a proxy of the total leaf area (Pérez‐Harguindeguy et al., 2013).…”

“…They were then oven‐dried at 60°C for 72 hr and weighed for dry mass, and we estimated SLA (mm 2 /mg). We obtained leaf morphological trait per tree averaging the figures of the 10 individual needles (Benavides et al., 2020).…”

“…Leaf collection, storage, processing and morphological trait measurement followed Pérez‐Harguindeguy et al. (2013), while the chemical analyses were carried out using gas chromatography‐combustion isotope ratio mass spectrometry (GC‐C‐IRMS) at the UC Davis Stable Isotope Facility (https://stableisotopefacility.ucdavis.edu/; Benavides et al., , 2021). Two of the leaf traits, SLA and LNC, are directly related to the leaf economics spectrum (acquisition and conservation of resources trade‐off), while the other two, LA and δ 13 C, reflect aspects related to gas exchange in leaves and water use efficiency, respectively.…”

“…Wood density, tree age (Martínez‐Sancho et al., 2019), leaf data (Benavides et al., 2020) and the rest of phenotypic and environmental data (Opgenoorth et al., 2020) are all available in figshare.…”

Island biogeography of plants and humans

“…The mean seed mass of exotic species increased with levels of human occupation, except for wind-dispersed species. One explanation for this relationship is that species that produce heavier seeds, also produce larger fruits (Benavides et al 2021), which are sought preferentially in agriculture and horticulture. Garden escapes also increase with human habitation (Sullivan et al 2005), and popular garden species typically have larger seeds than other exotics (Hodkinson and Thompson 1997).…”