DOI: 10.6084/m9.figshare.29967493
title: Data: Intraspecific trait variation drives functional shifts in grass communities under grazing in the Scottish uplands

description: Data associated with Eshelman et al (2026) "Intraspecific trait variation drives functional shifts in grass communities under grazing in the Scottish uplands", <i>Journal of Vegetation Science</i> (DOI: 10.1111/jvs.70117).AbstractQuestions: Shifting grazing regimes across Europe are altering temperate grasslands, affecting biodiversity and ecosystem services. While grazing influences the structure of these grasslands, and thus the distribution of functional traits, the relative role of species turnover versus intraspecific variation (ITV) in governing trait variation of temperate grasslands is poorly understood. We investigated the impacts of grazing on grass community composition and structure within a 20-year landscape-level grazing experiment in the Scottish Uplands to determine if differences in grass community functional composition are driven by ITV.Location: Glen Finglas, Scotland, UKMethods: We exploited the design of the experiment to contrast three levels of sheep grazing across three plot locations and two drainage positions (upslope and downslope). Grass composition and seven grass functional traits representative of grazing adaptations were measured. Multivariate abundance models assessed the effect of grazing treatment, location, and plot drainage position on grass community composition, while phylogenetic linear mixed models (PLMM) tested for trait differences between plots. Grass community trait variation was then decomposed to quantify the relative contributions of species turnover and ITV in trait responses to grazing and environmental variables.Results: Compositional differences between plots were largely driven by plot location, with a marginal effect of grazing treatment. Increased grazing shifted grasses towards combinations of avoidance (e.g., thick leaves), resistance (e.g., small stature) and tolerance traits (e.g., high SLA). ITV accounted for most trait variation in response to grazing, indicating that community-level functional trait changes occur primarily through within-species trait adjustments rather than species turnover.Conclusions: The high ITV observed in our results suggests that these grasslands exhibit community resilience to grazing disturbances. Recognising the role of ITV in grass community responses will improve predictions of how changes in grazing management impact Scottish grassy ecosystems, informing grassland management and conservation strategies.Description of dataExperimental design:In 2003, the now James Hutton Institute, with support from the Scottish Government, established a grazing management experiment that has now been implemented continuously for 23 years. The experiment comprises three blocks that represent different catchments and various aspects within the same larger watershed (AB, CD, EF). Each block is divided into uphill (B, C, F) and downhill (A, D, E) subblocks. Each subblock contains four 3.3 hectare plots, resulting in a total of 24 plots. When the experiment was established, each plot within a subblock was randomly assigned to one of four grazing treatments: (1) high-intensity grazing, reflecting profit-driven management with nine sheep per plot (2.7 sheep/hectare); (2) continuation grazing, maintaining historical stocking rates of 3 sheep per plot (0.9 sheep/hectare) representing low-intensity grazing, and acted as a control (reference condition) for the experiment; (3) no grazing, to mimic agricultural abandonment; and (4) mixed grazing, consisting of 2 cows for 4 weeks in the autumn and 2 sheep during the full grazing period (0.6 sheep/hectare). Grazing occurred from May to November annually, with livestock removed from December to April and briefly during routine farming operations. For each treatment, there are six replicates based on the design.Surveys included in this dataset were conducted in July and August 2023, during the mid to late growing season. We surveyed grass species and traits in the high-intensity, continuation, and no-grazing treatments, with randomised subblocks and plot survey orders to minimise sampling bias. Within each plot, there were 25 fixed points marked on the intersections of a 40m-interval squared grid, such that N<sub>total</sub>, the total points for all treatments of the experiment, equals 600 (25 points x 24 plots). We surveyed ten randomly selected fixed points per plot, such that N<sub>study, </sub>total number of points surveyed in this study, totalled 180 across 18 plots. Compositional data:Associated file: GFGrassCompData_2023.xlsxFor this analysis, we used a subset of the compositional data collected by the James Hutton Institute in July and August 2023, during the mid- to late-growing season (Fielding et al., 2024). Grass species abundance was assessed at ten fixed points within a plot using a five-pin vertical pin-frame. The pin-frame was lowered through the vegetation, and all species touching a pin were identified and recorded. Species taxonomy follows Stace (2010). Species abundances were quantified as the total number of vegetation contacts per species across all 50 pins per plot, giving plot-level abundance per species. All composition surveys were conducted consistently downhill from the fixed point.Functional Trait data:Associated file: GFGrassCompData_2023.xlsxAt each surveyed fixed point, we measured seven traits selected based on their ecological significance in influencing plant survival, growth, and competition ability under grazing pressures and relevance to the grazing avoidance, resistance, and tolerance adaptation axes (Archibald et al., 2019): (1) <i>inflorescence height</i> (cm), (2) <i>culm diameter</i> (mm), (3) <i>leaf thickness</i> (mm), (4) <i>leaf dry mass</i> (mg), (5) <i>leaf area</i> (cm2), (6) <i>specific leaf area</i> (SLA; g/cm2), and (7) <i>leaf carbon-to-nitrogen ratio</i> (leaf C:N). Measurements for each trait followed the protocols presented in Wigley et al. (2020) and Pérez-Harguindeguy et al. (2013). We measured one individual of each grass species present within a 2 m semi-circle uphill of each fixed point across 18 plots. For each individual, inflorescence height and culm diameter were measured <i>in situ</i> before harvesting the entire individual. Samples were then stored in a cool box with ice packs in the field for transport to the lab for processing.Variable names, measuring units, and additional information are provided within the README.md file.References:Archibald, S., Hempson, G. P., & Lehmann, C. (2019). A unified framework for plant life-history strategies shaped by fire and herbivory. <i>New Phytologist</i>, <i>224</i>(4), 1490–1503. https://doi.org/10.1111/nph.15986Fielding, D.A., Everts, L., Littlewood, N.A., Pakeman, R., 2024. Data from: Long-term impacts of changed grazing regimes on the vegetation of heterogeneous upland grasslands. https://doi.org/10.5061/DRYAD.DR554M2Pakeman, R. J., Fielding, D. A., Everts, L., & Littlewood, N. A. (2019). Long-term impacts of changed grazing regimes on the vegetation of heterogeneous upland grasslands. <i>Journal of Applied Ecology</i>, <i>56</i>(7), 1794–1805. https://doi.org/10.1111/1365-2664.13420Pérez-Harguindeguy, N., Díaz, S., Garnier, E., Lavorel, S., Poorter, H., Jaureguiberry, P., Bret-Harte, M.S., Cornwell, W.K., Craine, J.M., Gurvich, D.E., Urcelay, C., Veneklaas, E.J., Reich, P.B., Poorter, L., Wright, I.J., Ray, P., Enrico, L., Pausas, J.G., De Vos, A.C., Buchmann, N., Funes, G., Quétier, F., Hodgson, J.G., Thompson, K., Morgan, H.D., Ter Steege, H., Van Der Heijden, M.G.A., Sack, L., Blonder, B., Poschlod, P., Vaieretti, M.V., Conti, G., Staver, A.C., Aquino, S., Cornelissen, J.H.C., 2013. New handbook for standardised measurement of plant functional traits worldwide. Aust. J. Bot. 61, 167–234. https://doi.org/10.1071/BT12225Stace, C., 2010. New flora of the British Isles (3rd ed.). Cambridge university press, Cambridge, UK.Wigley, B.J., Hempson, G.P., Stevens, N., Tebeest, M., Archibald, S., Bond, W.J., Bunney, K., Coetsee, C., Donaldson, J., Fidelis, A., Gao, X., Gignoux, J., Lehmann, C., Massad, T.J., Midgley, J.J., Millan, M., Schwilk, D., Siebert, F., Solofondranohatra, C., Staver, A.C., Zhou, Y., Kruger, L.M., 2020. A handbook for the standardised sampling of plant functional traits in disturbance-prone ecosystems, with a focus on open ecosystems.Related worksDatasetFielding, D.A., Everts, L., Littlewood, N.A., Pakeman, R., 2024. Data from: Long-term impacts of changed grazing regimes on the vegetation of heterogeneous upland grasslands. https://doi.org/10.5061/DRYAD.DR554M2<br>