DOI: 10.5061/dryad.hqbzkh1kp
title: Data for: Invasion by an exotic grass species homogenises native freshwater plant communities

description: A growing body of evidence has shown that biological invasions cause
 shifts in species composition of communities in space and time. Although
 biological invasions are considered a major driver of biotic
 homogenisation worldwide, most previous studies are conducted at small
 spatial scales and over short time periods, which may have underestimated
 the impacts of exotic species on native communities. Using a unique
 dataset of aquatic plants sampled in 235 sites over 12 years (2007–2010
 and 2015–2019) in a large reservoir (Itaipu Reservoir; 1,350 km²), we
 analyzed how the invasion of a non-native grass (Urochloa arrecta) affects
 the species richness, ecological uniqueness (i.e., local contribution to
 beta diversity – LCBD) and temporal β–diversity of native plant
 communities. From 3,934 surveyed plant communities, U. arrecta was
 recorded in 2,888 samples and it was absent from 1,046 samples. Overall,
 species richness and ecological uniqueness of native plant communities
 were markedly lower in sites invaded than non-invaded by U. arrecta. From
 2007 to 2019, the ecological uniqueness of native plants was 60% lower in
 the invaded than non-invaded sites.     
 Whereas in invaded sites the species loss was the dominant mechanism
 driving native communities over time, in non–invaded sites the gain of new
 native species was the primary mechanism underlying community
 trajectories. Moreover, comparing native plant communities before and
 after the invasion of U. arrecta, species richness, ecological uniqueness
 and species gains of native plant communities decreased, whereas species
 losses increased after the invasion of U. arrecta. Finally, the positive
 relationship between native biodiversity and precipitation was stronger in
 sites non-invaded than invaded by U. arrecta. Synthesis: Our findings
 provide comprehensive evidence that an invasive plant is decreasing the
 spatial and temporal β–diversity of native plant communities through
 declining species richness, rather than simply correlating with them. This
 suggests that U. arrecta is driving native plants to become less diverse
 and homogeneous after the invasion, both spatially and temporally. Our
 findings illustrate that at broad scales, aquatic plant communities may
 become increasingly homogeneous with the increasing number of biological
 invasion events taking place worldwide. 
description: We analysed a 12-years data set (2007–2010 and 2015–2019) with
 presence-absence data for aquatic plants recorded in the Brazilian
 shoreline of the Itaipu Reservoir, a large water body filled in 1982 and
 located in the frontier between Brazil and Paraguay (24º15’–25º33’ S and
 54º00’–54º37’ W; Figure 1). This reservoir covers an area of 1,350 km²,
 has a mean depth of 22 m and its arms (the sampled sites) vary from
 oligotrophic to eutrophic (Thomaz et al., 2009). The local mean annual
 temperature is 22 ºC and the mean annual rainfall is 1,400 mm. More
 detailed information on environmental data can be found in Thomaz et al.
 (2003) and Pulzatto et al. (2019). It is not certain when <em>U.
 arrecta</em> first colonized this reservoir, but this species has
 been recorded since the first sampling carried out in Itaipu in 1996 (S.
 M. Thomaz, unpublished).             We used aquatic
 plant data collected between 2007 and 2010 as well as between 2015 and
 2019 in 235 sites located in the Reservoir arms, totalling 12 years of
 sampling (2007–2019). Reservoir sites were surveyed during the Aquatic
 Macrophytes Monitoring Program of the Itaipu Reservoir, which was designed
 to include sites in a wide range of environmental conditions. To provide a
 comprehensive assessment of aquatic plants, samplings were performed
 during the dry and wet seasons in each of the 235 geo-referenced sites
 (except in 2008, when only one sampling was conducted). In particular, the
 235 sites were distributed along eight arms (flooded tributaries) of the
 Itaipu Reservoir, with the number of sampling sites within each arm
 (26–30) being proportional to its total area (Fig. 1). In total (between
 2007 and 2019), there were 3,934 samples. The survey followed a
 standardized sampling protocol with the same sampling effort across all
 sites. Specifically, plant species occurrence in each site was assessed by
 three observers on a boat moving at a slow and constant velocity (Thomaz
 et al., 2009). These observers recorded plant species present along a ca.
 100–m stretch from the shoreline of each site. To do so, the emergent
 vegetation was inspected visually and used a rake with a 4–m pole to
 collect submerged plants. Species not immediately recognized in the field
 were collected for identification in the laboratory (see Thomaz et al.
 2009 for further details). <em>Invaded and
 non-invaded sites</em> Across the 235 sites, we
 considered all sites where <em>U. arrecta</em> was present as
 invaded sites, while other sites where <em>U. arrecta</em> was
 not present were considered non-invaded. Considering that each of the 235
 sites was monitored over 12 years, this allowed us to analyse how the
 invasion of <em>U. arrecta</em> changed at these sites over
 time. For instance, whether a given site was not invaded by <em>U.
 arrecta</em> at a time (t<sub>1</sub>), this site was
 then considered not invaded at this time. However, if the same site was
 invaded by <em>U. arrecta</em> at another time
 (t<sub>2</sub>), then this site was considered invaded at this
 time point. Therefore, the same site may have become invaded or not
 invaded by <em>U. arrecta</em> over time. The opposite was
 also true; that is, if at a location at a time (t<sub>1</sub>)
 <em>U. arrecta</em> was present, then this site was considered
 invaded, but if at this same location at time (t<sub>2</sub>)
 <em>U. arrecta</em> was absent, this site was considered
 non-invaded. <em>Climate
 predictors</em>             Daily total
 precipitation (i.e., the sum of rainfall volume
 (Kg/m<sup>2</sup>/s)) and daily mean temperature (ºC) values
 were obtained for each sampling site and extracted from the RNCEP package
 in R (Kemp et al., 2012). The RNCEP database has a spatial resolution of
 2.5 x 2.5o and a temporal resolution of 6 h (Kemp et al. 2012).