Small seed bank in grasslands and tree plantations in former grassland sites in the South Brazilian highlands
Cite this dataset
Vieira, Mariana; Overbeck, Gerhard (2020). Small seed bank in grasslands and tree plantations in former grassland sites in the South Brazilian highlands [Dataset]. Dryad. https://doi.org/10.5061/dryad.n2z34tmsw
The soil seed bank can be an important source for vegetation regeneration, and data on the similarity between aboveground vegetation and the seed bank can provide information about successional pathways after disturbances or land-use change. We conducted this study in natural grasslands in the subtropical highland region in southern Brazil. We evaluated the effect of silviculture on richness, density, and composition of the seed bank at former grassland sites converted to pine plantations 25 years ago. We worked at six grassland sites and three pine plantation sites and used the seedling emergence method. Seed bank density and richness in grasslands was lower than those reported in similar environments in other regions. Species richness and density varied considerably within each vegetation type therefore, richness and density were not statistically significant, while composition varied among vegetation types. In terms of species, the pine plantation seed bank was a small subset of the grassland seed bank. Seeds of typical grassland species were missing in the pine plantation, but also had only low abundances in the grassland, and similarity of seed bank and vegetation was low (less than 20%). The low seed density found in this study, including in grasslands areas, indicates that regeneration of species from the soil seed bank likely is of a limited role for the maintenance of plant populations after disturbances in this system. Our data further suggest that natural regeneration after tree planting in grasslands is reduced due to seed limitation.
STUDY AREA—Our study sites are located in the highland grassland region in the southern part of Brazil’s Atlantic Forest domain (29°04’12’’ S, 50°00’49’’ W). Regional climate is Cfb according to Köppen climate classification, and altitude approximately 1000 m. Mean annual temperature is 15°C and mean annual precipitation is 1881 mm (climate-data.org). The region is a plateau formed by basalt, rhyolite and rhyodacit rocks of Serra Geral formation. Soils are classified as Cambisoils according to FAO, 1997 (Cambissolos in the Brazilian classification; Embrapa 2013). Natural vegetation in the region is composed of mosaics of Araucaria forest, cloud forest and grasslands (Leite & Klein 1990). These highland grasslands have been used for livestock grazing since European colonization. However, the presence of large herbivores – today extinct – even before the arrival of native American people is confirmed by the fossil record in the region (Scherer et al. 2007). Based on charcoal records from peat bogs, we know that fire has been rare during the Glacial maximum but became more frequent at the beginning of the Holocene (Behling & Pillar 2006). Today, fire, usually every other year, is used as a management tool to remove accumulated biomass to stimulate young leaf regrowth after winter. In terms of their floristic composition, the highland grasslands are dominated by C4 tussock grasses such as Andropogon lateralis Nees, Sorgastrum scaberrimum (Nees) Herter, Axonopus pellitus (Nees ex Trin.) Hitchc. & Chase and a high representation of Fabaceae family (Andrade et al. 2019). The region encompasses two important national parks, Aparados da Serra and Serra Geral, and other state and private protected areas. In the region, we find vast areas of pine plantations, with single planting cycles of 30 years on average, causing loss and fragmentation of natural areas (Hermann et al. 2016).
For this study, we chose six well conserved grasslands, four located in Serra Geral National Park and two in Aparados da Serra National Park (Fig.1), and three pine plantations established in former grasslands areas. Two of them were in the buffer zone of the National parks, and one of them at the edge of the park. Pine plantations were initiated about 25 years ago. Sites were situated in three blocks, each with one pine plantation and two natural grassland areas, with the same history and similar floristic composition of grasslands. Distance of blocks varied from 2 to 20 km, and areas within each block had distances of 500 to 2000 m (see Fig. 1 for scheme of study design).
VEGETATION SAMPLING—Quantitative vegetation sampling at the grassland sites was conducted in December 2014, in 10 plots of 1 m², randomly allocated, per grassland area. Distance between plots was approx. 50 m. Cover of all vascular species was recorded using the Londo decimal scale (Londo, 1976). In the pine plantation areas, no vegetation survey was conducted, as ground layer vegetation was completely absent.
SEED BANK SAMPLING AND ASSESSMENT—The seed bank study was carried out using the seedling emergence method, which evaluates only the viable seeds in the soil (Thompson & Grime 1979). Soil samples for the seed bank study were collected in grasslands and current pine plantations. Samples were collected in two seasons (spring and autumn) with the intention of accessing both the transient seed bank and persistent seed bank (Thompson & Grime 1979). We used five sampling points in each study area, totaling 30 samples from grassland and 15 from pine plantations (five per area). Distances between sampling points were approx. 50 m. Soil samples were collected with an auger (diameter: 5 cm; depth: 10 cm). At each sample point we collected four sub-samples which were mixed, resulting in one composite sample per point. All sample points were randomly selected.
For seedling emergence, we used 50% of the soil collected in the field. Soil was mixed with vermiculite (50:50), to maintain humidity, and spread in trays (soil depth: 2-3 cm). Samples were kept in a greenhouse with irrigation for one year and were monitored weekly. Trays with sterilized soil were distributed among the soil samples from the grasslands to control possible contaminations by plants dispersed close to the experimental facilities. Emerging seedlings were identified, counted, and removed as soon as possible. For species that could not be identified right away, at least one specimen was transplanted into a larger container for development of the reproductive phase, for later identification. Most taxa (83%) were identified to the species level and 92% to the genera level. Some individuals died in the trays or transplanted pots before identification was possible, or there was little development of individuals impeding identification.
DATA ANALYSIS—Data of seeds per sampling point unit were converted to density (seeds per square meter) with the aim of facilitating comparison with other studies. We averaged seed density data from the two seasons together for each sampling point. For statistical analysis, mean values of each studied area were considered, resulting in six average values for the grassland areas and three average values for the Pinus areas. For all analyses, we used randomization tests, with 10.000 iterations. This method (also referred to as permutation test), based on resampling, is also adequate for multivariate data sets, such as compositional data, and has been proposed specifically for vegetation data (details in Pillar & Orlóci 1996). Another advantage is that it does not require normal distribution of data, while preventing robust test results (Pillar & Orlóci 1996); this also makes the method especially appropriate for our data set. For analysis of richness and density data, we used Euclidean distance as dissimilarity measure and for analysis of the seed bank composition chord distance as dissimilarity measure. We analyzed composition similarities among pine plantations soil seed bank, grassland seed bank and aboveground vegetation on grassland areas with Sørensen’s Index (2a/2a + b + c), where a = number of species common to both seed banks, b = number of species unique to the first seed bank, and c = number of species unique to the second seed bank, considering all the data set of the seed bank (two seasons). Principal Coordinate Analysis was conducted to visualize difference in seed bank composition between the grasslands and pine plantations, using chord distance as the similarity measure. For all analyses, we used the software MULTIV (Pillar, 2006). We used alpha = 0.05 as significance level.
National Council for Scientific and Technological Development, Award: 477618/2013-8