DOI: 10.5061/dryad.612jm645g
title: Increasing abundance of an invasive C4 grass is associated with larger community changes away than at home

description: Aim: We evaluated the stands of the invasive grass, Sporobolus cryptandrus
 in its native North American and non-native European range, where it is a
 recent invader. Our aim was to reveal how the species’ increasing
 abundance affects functional diversity and ecosystem service provisioning
 capacities of plant communities in both ranges. Location: Sand grasslands
 in the Kiskunság, Hungary, and in Montana, USA. Methods: All vascular
 plant species and their relative abundances were recorded in a stratified
 random manner in 1m×1m plots in each range, using the following cover
 categories of Sporobolus as strata: 1–25%, 26–50%, 50–75%, and
 75–100%. The functional characteristics of the plant communities
 of the two continents were compared. We performed the comparisons of the
 communities both with and without including Sporobolus. Results:
 Increasing Sporobolus cover resulted in a lower functional diversity and
 species richness, reduced average specific leaf area, and increased height
 of the whole plant communities in both ranges but these effects were
 significantly stronger in the non-native stands. Sporobolus also
 negatively affected the cover of insect-pollinated plant species and the
 proportion of native perennials, switching the rest of the community from
 perennial-dominated to annual-dominated. In the plant communities without
 Sporobolus, increasing Sporobolus cover led to higher specific leaf area
 and seed mass in both ranges, but average height was decreasing along the
 Sporobolus abundance gradient in the native range, while it was increasing
 in the non-native range. Conclusions: The spread of Sporobolus, away from
 its native range, leads to the impoverishment of host communities and
 compromises the biomass and floral resource provisioning capacity of the
 vegetation to higher trophic levels. Tackling the spread of this new
 invader should therefore be a priority task.
description: We selected four sites both in
 the native (Montana, USA) and non-native (Kiskunság, Hungary)
 <em>Sporobolus</em> cryptandrus habitats between July and
 September 2019. We established 1 m × 1 m plots in each site in a
 stratified random manner, using the following cover gradient categories of
 <em>S. cryptandrus</em> as strata: 1–25%, 26–50%, 50–75%, and
 75–100%. We aimed to select ten plots for each cover category in all
 sites; however, as some categories were underrepresented, we obtained a
 total of 101 plots in the USA and 153 plots in Hungary. We recorded the
 percentage cover of all vascular plant species in the plots, including
 <em>S. cryptandrus. </em>
 Since the functional role of
 organisms in ecosystems depends on their traits rather than on their
 taxonomical affiliation, we used a trait-based approach to study the
 effects of increasing <em>S. cryptandrus</em> cover on the
 vegetation. We considered a wide range of traits, encompassing the entire
 life history of the species and their ecosystem-level effects (Table 1).
 LHS (Leaf–Height–Seed) traits, including leaf area (LA), specific leaf
 area (SLA), vegetative plant height, and thousand-seed mass (hereafter
 seed mass) provide information on interspecific interactions (Westoby,
 1998; Klimešová & Pyšek 2011); SLA also correlates with
 photosynthetic efficacy and palatable biomass for herbivores (Wilson et
 al. 1999). Pollination type, complemented with the mean range of flowering
 period makes a link between plants and pollinators by providing
 information about floral resources. We used growth form (a simplified
 version of the original Raunkiaer’s life forms; Raunkiaer, 1934) as a
 proxy to describe the general appearance of the vegetation. In the case of
 species missing from the available databases, we used trait values of the
 most closely related, morphologically similar species published in the
 database. If multiple records were provided for a species, we used the
 average value.  Data analyses
 To characterize the diversity
 of the surveyed grasslands, we used plot-level species richness and Rao’s
 quadratic entropy, including all the collected traits in the analysis. The
 latter is a measure of functional diversity, expressing the mean
 functional distance between two randomly chosen species in the plots,
 while also accounting for the abundances of the species (Botta-Dukát,
 2005). For the continuous traits, we calculated community-weighted means
 (CWMs) for each plot, while for categorical variables we used the
 cumulative cover of each category without any transformation. We prepared
 linear mixed-effect models to quantify the effects of <em>S.
 cryptandrus</em> cover, region (i.e. Montana and Hungary) and their
 interaction on the vegetation descriptors. We used site identity within a
 region as a random factor. The values of the response variables and the
 cover values of <em>S. cryptandrus</em> were scaled prior to
 fitting the linear mixed-effect models. We involved traits that are widely
 used to trace community-level changes or responses, and supposedly reflect
 ecosystem functions. Ecosystem functions are determined by whole plant
 communities but the direct effects of <em>S. cryptandrus</em>
 may be better understood if scrutinizing only the rest of the vegetation
 along the <em>S. cryptandrus</em> cover gradient. Therefore,
 we performed the analysis in two ways: (i) using whole vegetation datasets
 together with <em>S. cryptandrus</em>, and (ii) reduced
 datasets by omitting <em>S.
 cryptandrus</em>. All analyses were performed in R version 4.0.3.
 (R Core Team 2020). Rao's quadratic entropy and CWMs were calculated
 with the ‘dbFD’ function of the FD package (Laliberté et al. 2014). We
 used the ‘lmer’ function of the lme4 package (Bates et al. 2015) to build
 the linear mixed-effect models, and the ‘Anova’ function of the car
 package (Fox & Weisberg 2019) to test the effect of the
 predictors. We used the ‘rsq’ function of the ‘rsq’ package (Zhang, 2021)
 to obtain marginal R2 values, which represent the proportion of variation
 explained by the fixed-effects factors.
description: Labels of spreadsheet 'Plot Records' are supposed to be
 evident after reading the 'Methods'. For additional information
 on the content of spreadsheet 'Traits x Spp', see 'Read
 Me'.