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Dryad

Functional traits and their plasticity shift from tolerant to avoidant under extreme drought

Cite this dataset

Kramp, Rosa Elisabeth et al. (2022). Functional traits and their plasticity shift from tolerant to avoidant under extreme drought [Dataset]. Dryad. https://doi.org/10.5061/dryad.qfttdz0kg

Abstract

Under climate change, extreme droughts will limit water availability for plants. However, the species-specific responses make it difficult to draw general conclusions. We hypothesized that changes in species’ abundance in response to extreme drought can be best explained by a set of water economic traits under ambient conditions in combination with the ability to adjust these traits towards higher drought resistance. We conducted a four-year field experiment in temperate grasslands using rainout shelters with 30% and 50% rainfall reduction. We quantified the response as the change in species abundance between ambient conditions and the rainfall reduction. Abundance response to extreme drought was best explained by a combination of traits in ambient conditions and their functional adjustment, most likely reflecting plasticity. Smaller leaved species decreased less in abundance under drought. With increasing drought intensity, we observed a shift from drought tolerance, i.e. an increase leaf dry matter content, to avoidance, i.e. a less negative turgor loss point (TLP) in ambient conditions and a constancy in TLP under drought. We stress the importance of using a multidimensional approach of variation in multiple traits and the importance of considering a range of drought intensities to improve predictions of species’ response to climate change.

Methods

Study system

The experiment was set up in four sites on the Swabian Alb, southern Germany (Appendix S1: Table S3). Mean annual precipitation in the region is 784 mm (1861-2016; missing data for 1862 and 1866). During the timeframe of the experiment, mean annual precipitation varied between 546 mm and 849 mm, mean annual temperature varied between 9.4 °C and 10.4 °C, with average monthly temperatures in January at 1 °C and in July at 19 °C (DWD 2020). The plant communities are temperate mesic grasslands of the Arrhenatherum elatioris (classified after Wilmanns 1993). They contain on average 22 species of vascular plants per square meter. In most of Central and Western Europe, open grasslands are conditioned by mowing and/or grazing management, which is centuries old and results in grasslands with stabilized species composition. To sustain the original ecosystem and mimic the traditional management, experimental grasslands were mown once a year in early July (Site KB) or twice a year in June and September (sites GW, FP, SC). The mowing dates during the experiment were set up to be synchronous with the common management practice.

Experimental design

In March and April 2017, rainout shelters were set up and after four years of experimental manipulation (in 2020), abundance and trait data were collected . Rainfall manipulation aimed to represent two different extreme droughts. A reduction in precipitation of 30% corresponded to a 25-year interval. In 2020, this resulted in the reduction in annual precipitation down to 512 mm. A reduction in precipitation of 50% corresponded to a 555-year interval. In 2020, this resulted in reduction in annual precipitation down to 366 mm. Each treatment (ambient conditions, 30% rainfall reduction and 50% rainfall reduction) was replicated twice per study site, resulting into a total of 24 plots (4 sites × 3 treatments × 2 plots). Treatments were randomly assigned to the plots which were placed 8-10 m apart. The rainout shelters covered a surface of 6 × 6 m. To minimize the edge effects, only the inner 4 × 4 m were considered for data sampling and this area was further divided into 16 subplots of 1 × 1 m. Shelter design minimized unintended effects on microclimate (see Appendix S1: Section S1, Appendix S1: Figure S1, Appendix S1: Table S1 and Appendix S1: Table S2 for more information on rainout shelters and minimized artifacts).

Species selection

The target species were selected per treatment and site based on the following criteria: (1) minimum abundance of each species of 2% to enable enough plant material for trait collection, and (2) cumulative abundance of at least 80% of total plant cover to ensure that these species represent well the studied communities (Májeková et al. 2016). These criteria yielded 14 common plant species comprising grasses and forbs in a balanced ratio characteristic for the mesic temperate grasslands (Appendix S1: Table S3). All plants were perennials with a C3 photosynthetic pathway.

Species abundance

Vegetation survey was conducted at the peak of the vegetation season in July 2020, approximately one month after the mowing was applied at each site. Nested within each plot, four subplots were semi-randomly assigned to the vegetation survey (Latin Square design). Species abundance was measured as a visual estimate [% of cover]. Percentages were recorded for total abundance, with values approximated in 10% increments when coverage exceeded 10%. Total coverage could exceed 100% and was later back calculated to relative abundance.

Leaf functional traits

 Four key plant functional traits were selected: leaf area (LA; cm2), specific leaf area (SLA; m2 kg-1), leaf-dry-matter content (LDMC; mg g-1), and turgor loss point (TLP; MPa). Trait measurements were performed on plant individuals with fully developed and undamaged leaves following the standardized protocols of Pérez-Harguindeguy et al. (2013) for LA, SLA, and LDMC, and of Májeková et al. (2019) for TLP (see Appendix S1: Section S2 for detailed information on trait sampling and measurements). For further analyses, absolute values of TLP were used, where higher values indicate higher osmotic concentration in leaf cells, delayed stomatal closure and higher drought tolerance.

Mean abundance was calculated over 8 subplots (4 subplots × 2 plots per site and treatment) and mean traits values were averaged over 10 (five for TLP) individuals collected in per site and treatment.

Funding

Baden-Württemberg Ministry of Science, Research and Arts