Despite increasing use of trait-based approaches in community ecology, most studies do not account for intraspecific variability of functional traits. Although numerous studies investigated functional traits of species with high economic value, the intraspecific and interspecific (caused by species identity) trait variability of forest understory herbs is still poorly understood. We aimed to assess the variability of specific leaf area (SLA), total leaf area, aboveground biomass and leaf mass fraction among 167 forest understory plant species, and the level of variability explained by species identity and collection site. We hypothesized that the level of intraspecific variability of SLA is underestimated in commonly used trait databases and that the interspecific variability (caused by species identity) is greater than intraspecific variability (site-specific). Our study revealed higher interspecific than intraspecific variability of the traits studied. We also confirmed that level of intraspecific variability available in the LEDA database is underestimated. We confirmed that species identity was the main factor determining the values of all the traits studied, and site-specific random effects explained lower amounts of variation in traits. Use of trait values from databases not acknowledging intraspecific variability is biased by uncertainty about this variability. For that reason, our analysis used mean trait values to reduce uncertainty of the results in the study conducted to assess human impacts on ecosystems. Thus, our study might support the assumption that level of intraspecific variability of functional traits is lower than interspecific variability.

Juglans regia L. is a species of great importance for environmental management due to attractive wood and nutritious fruits, but also high invasive potential. Thus, uncertainties connected with its range shift are essential for environmental management. We aimed to predict the future climatic optimum of J. regia in Europe under changing climate, to assess the most important climatic factors that determine its potential distribution, and to compare the results obtained among three different global circulation models (GCMs). We used distribution data from the Global Biodiversity Information Facility and completed it with data from the literature. Using the MaxEnt algorithm, we prepared a species distribution model for the years 2061–2080 using 19 bioclimatic variables. We applied three emission scenarios, expressed by representative concentration pathways (RCPs): RCP2.6, RCP4.5, and RCP8.5 and three GCMs: HadGEM2-ES, IPSL-CM5A-LR, and MPI-SM-LR. Our study predicted northward shift of the species, with simultaneous distribution loss at the southern edge of the current range, driven by increasing climate seasonality. Temperature seasonality and temperature annual range were the predictors of highest importance. General trends are common for the projections presented, but the variability of our projections among the GCMs or RCPs applied (predicted range will contract from 17.4 to 84.6% of the current distribution area) shows that caution should be maintained while managing J. regia populations. Adaptive measures should focus on maintaining genetic resources and assisted migration at the southern range edge, due to range contraction. Simultaneously, at the northern edge of the range, J. regia turns into an invasive species, which may need risk assessments and control of unintended spread.

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