Summary Of Proposed Research
Global drought not only affects the world agriculture and economics, but interactively affects the phenotypic trait of plants across a different diversity gradient. Nevertheless, plants are able to adapt themselves to the drought environment by changing their phenotypic trait. From previous research at Jena Drought Experiment, in Germany, the results show that diversity not only has the capability to increase community’s resistance to drought, but also to increase community’s recovery ability after drought. On the other hand, the results show that the drought environment makes a strong selection on both, the plant phylogeny and functional trait. Yet, the mechanism underlying these selections, especially the phenotypic variation among plants under repeated drought across a different diversity gradient, remains unclear.
I have organized my paper into three main parts: Part A, Part B, and Part C. To achieve the overall goal, I have introduced the main hypothesis of the experiment: trait selection can be dependent on diversity and drought histories (Part A). Furthermore, the paper also has two sub-hypotheses: the first, selection for drought resistance may lead to greater recovery after drought (Part B): the second, community selection might be crucial for increased complimentarily and reduced competitiveness through traits for the community- wide resistance and resilience to drought (Part C).
The researchers will use seeds collected from five selected plots at Jena Drought Experiment, of which every seed comes from communities established 8 years ago. In Part A, by re-growing the seeds in a glass house, the research aims at finding out the different trait selection base for plants, according to their mother plants’ diversity and drought histories. For example, a plant with a drought history might be tending to make a trade-off on smaller leaf area to reduce a water loss. After the plant establishment, our team will harvest the selection and allow some time to prepare for the drought experiment. In Part B, by applying the drought experiment, the researchers aim at finding out, if the plants with the drought history have a better resistance and a greater recovery after the drought. In Part C, by analyzing the data from the drought experiment, we plan to investigate, whether a plant with a drought history has better complementarities, compared to a controlled plant.
Since the experiment will take place at a glasshouse, the researchers are prepared to take measurements on the plants’ morphology, specific leaf areas and Chlorophyll content. Data will be analyzed with linear models, analysis of variance on the functional trait community weighted mean and mean pairwise difference, as well as multivariate analysis to detect the overall variation in traits, among drought and across diversity histories.
Together, the proposed research should contribute to a better understanding of the major question, how different plant species and their community can adjust to the global drought situation.
2.1 Current State of Research in the Field. Since anthropogenic climate change and global warming will affect our ecosystem in the future (Solomen et al., Romm et al.), a sound understanding of, how plant species and their community responds to such anthropogenic climate change, is of utmost importance. Due to a global precipitation change, drought becomes a more crucial problem, basically caused by anthropogenic climate change. Respected previous studies show that drought will decrease the plant productivity in the future (Sala et al., Tailman et al.). On the other hand, the plant community diversity has a positive relationship with resistance to drought (Craven et al., Isbell et al.). Yet, the evolutionary phenotypic variation base on plant diversity and drought history still needs to be found out.
Diversity has a strong effect on ecosystem stability (Isbell et al.); it provides more space for a community to buffer the effect of perturbation, such as drought. In the same way, an insurance hypothesis states that increased species’ richness in ecosystem will add insurance to the system against perturbation (Yachi et al.). Previous drought experiment done at Jena, in Germany, also found out that the species richness has a strong stabilizing effect on plant productivity (Wagg et al.). Species richness has a positive effect on both the resistance to summer drought and recovery in the following season (Wagg et al.). Moreover, drought makes selection on both the plant phylogeny and functional trait (Vogel et al.). Nonetheless, whether a plant with a drought history would have a better adaptation to drought environment remains unclear.
Compared to monoculture, a mix-culture community is able to reduce intraspecific competition and have complementarities and facilitation between the species. Moreover, a plant community under stressful condition tends to increase in complementarities and facilitation among species (Callaway et al.). Previously, with a selection for niche differentiation, Debra and Bernhard’s research from our institution found out that plants with a diversity history have significant increase in complementarity, compared to plants without diversity history (Zuppinger-Dingley et. al). Yet, will a plant with drought history exhibit more significant result in increasing of complementarity and facilitation, remains unclear.
The current Master Thesis, aims at investigating three main research questions: 1) What are the phenotypic variation among plants or trait selection, depending on diversity and drought histories, 2) Will a plant with a drought history have a better resistance to drought and faster recovery after the drought; 3) Is there any community selection for increased complementarity and reduced competitiveness through traits for increased community- wide resistance and resilience to drought? I attempt at using selected seeds from a long-term drought experiment at Jena, from which their mother plant has been growing in a different environmental condition and diversity for 7 years.
Detailed Research Plan
2.2.1 Introduction and Objectives. Based on a previous Jena Drought Experiment, the researchers collected the seeds from five different selected plots, with each species’ richness level 2, 4, 8 and 16, during the summer 2016. We will re-grow them in a controlled environment at the Department of Evolutionary Biology and Environmental Studies’ glasshouse.
The experiment will aim at the following objective:
a. Phenotypic variation among different plant species, with and without drought histories, will be identified, after 4 months of plant establishment.
b. After harvest and data collection from Part A, we will apply drought treatment and test the resistance and recovery, between different species, with and without drought histories.
c. In the last part of our experiment, we will focus on complementarity in a mix-culture plant community treatment, examining both the drought and control plots.
For Part A of the experiment, we hypothesize that a plant with a drought history will have different phenotype, compared to a plant without drought history. For example, drought will make selection for a smaller leaf area to avoid water loss. For Part B of the experiment, we hypothesize that a plant with the drought history will have a better resistance to the drought and faster recovery after the drought. For Part C of the experiment, we hypothesize that a plant with the drought history will have increase in complementarity or facilitation, or reduced competition, between species.
2.2.2 Experiment Design and Model System. Seedlings will be grown in groups of four, or as a single plant in pot, under three-plant community treatment (single plant, monoculture, two species mix-culture). We assign the seed to a low and high diversity history level (2 in low; 4, 8, 16 in high), and two-drought treatment (drought and control). With 8 species and 4-replica block we use R program to generate every possible combination; the research will end up with 176 pots per block, in total yields of 704 total pots. All the Pots will be arranged by a randomized complete block design.
2.2.3 Measurements and Data Arrangement. After set-up of the experiment, a plant will be monitored monthly, during 4 months of the establishment time. We will mainly focus on shoot height, number of leaves, chlorophyll content, and stomatal conductance. For chlorophyll content measurement, the researchers will use Konica Minolta Chlorophyll Meter SPAD-502, but for stomatal conductance measurement we aim to be using Decagon SC-1 Leaf Porometer. This will allow the researchers to compare the phenotypic variation, between a plant with the drought history, and a plant without the drought history, in a uniform environment. Next, we will harvest a plant from 4cm above ground and collect data for the shoot biomass, leaf area, leaf number, specific leaf area, and the maximum shoot height.
Subsequently, a plant will be allowed to re-grow for 1 month, then we will apply the drought treatment; during the drought experiment, only a minimum amount of water will be added in order to maintain the soil moisture. After 1 month of drought experiment, we will harvest the plant again from 4cm above the ground and collect data. This will allow us to test the plant resistance to drought and determine the complementarity between species.
Consequently, we will give the plant another month to recover from the drought, at the end of the month; we will harvest again and collect data. The last part of experiment will allow us to test, how the plant with the drought history recovers differently from the plant without the drought history, and again to determine complementarity between species.
2.2.4 Data Analysis and Statistical Model. Data will be collected and analyzed in R software. In Part A of our experiment, the researchers are going to use linear model to justify the phenotypic variation. For example with biomass, lm (biomass ~ species + drought + diversity + species: drought + species: diversity + drought: diversity + species: drought: diversity).
In Part B and Part C of our experiment, we will be using ANOVA (Analysis Of Variance) on the functional trait community-weighted means and ANOVA (Analysis Of Variance) on the functional trait mean pairwise difference. For a better illustration in the end, we will use multivariate analyses (PCA) to show the overall variation in traits, among drought and diversity histories, as well as the differences among species.
2.3 Time Schedule. We will be planting in the beginning of February 2017; plants will take 4 months to establish. After the first harvest at Jun 2017, we will let them re-grow for one month. In the beginning of July 2017, we will apply drought treatment to the plants. After the second harvest at the end of August 2017, we will give plants one month to recover from drought. At the end of the September 2017, we will make the final harvest. Finally, we will start the final data analysis and writing of Thesis. Final Master Thesis will be handed in on 19th November, 2017.
2.4 Significance of the Proposed Study. In the current field of research, the researchers lack understanding of, how plant species and their community will shift under anthropogenic climate change, especially drought. Since the climate change is going to accelerate in the future, it is advised to make a simulation experiment, first in the glasshouse, to study how plant species and their community will respond to such an environmental change.
The proposed research will be based on number of previous experiments from Jena Experiment, this Institution, and my supervisors’ full experience. By combining all results and experience from these pioneers, we will have a better foundation to investigate our questions of research.