DOI: 10.5061/dryad.612jm64bj
title: Data from: Spatiotemporal interaction of risk-spreading strategies for a seed-dimorphic plant

description: For plants, the risk of stress-induced reproductive failure can be spread
 temporally and spatially by increasing the variation in stress tolerance
 and dispersibility, respectively. Yet, we have limited understanding on
 how intraspecific stress tolerance can be interactively adjusted by these
 two risk-spreading strategies. Seed-dimorphic plants, which are
 frequently found in stressful and fluctuating environments, can produce
 dimorphic offspring with different stress tolerances and dispersibilities.
 Using a seed-dimorphic Asteraceae, Synedrella nodiflora, we illustrated
 how maternal-drought-induced changes in drought tolerance and
 dispersibility may interactively increase intraspecific drought tolerance
 variation, and thus potentially improve adaptation to various water
 conditions. Maternal drought stress increased the mean or
 variation of drought tolerance of the less-dispersible (R-type) offspring,
 whereas it had variable effects on the drought tolerance of the
 more-dispersible (D-type) offspring depending on maternal seed morph
 (R-type vs. D-type) and habitat (dry vs. wet). Because the relative
 abundances of these two types of offspring remained largely unchanged by
 maternal drought, there was an overall increase in the intraspecific mean
 and variation of drought tolerance under maternal drought stress, driven
 by the changes in the less-dispersible offspring. Synthesis. Our results
 indicate a strong interaction between stress tolerance variation and seed
 dispersibility in seed-dimorphic plant species. Using drought tolerance as
 an indicator, we demonstrate a potential pathway for the adaptive
 evolution of seed-dimorphic plants that may contribute to their wide
 distribution. More importantly, our findings highlight the ecological
 significance of seed dimorphism and the variation of stress tolerance to
 avoid reproductive failure under various environmental conditions.
  
description: <strong>1. Experimental data</strong>
 (1) Seed collection in field The mature seeds
 of<em> </em><em>Synedrella</em> from two distinct
 natural habitats in Guangzhou and Zhuhai, China, were collected in January
 and February 2018 (see details in supporting information Table S1). While
 both habitats were beneath trees along roadsides, one had a relatively dry
 environment with a <em>Synedrella</em> monoculture (hereafter
 the dry habitat), while the other was close to a stream hosting a
 species-diverse plant community (hereafter the wet habitat). In each
 habitat, we collected seeds from four individuals (F0) of similar size.
 The collected seeds were carefully separated by seed morphs, which were
 then air-dried and stored in paper bags at room temperature (approximately
 20 ℃) for about four months prior to the greenhouse experiment. In total,
 we collected 16 replicated seed sources (2 seed morphs × 4 F0 individuals
 × 2 habitats). (2) Greenhouse experiment
 A greenhouse experiment was conducted at Sun Yat-sen University,
 Guangzhou, China (23°03ʹN, 113°11′E). The
 mature <em>Synedrella</em> seeds collected in the field of
 maternal plants of generation F0 were surface sterilized by soaking in 1%
 sodium hypochlorite solution for 15 min and then incubated on moist
 double-layer filter paper in Petri dishes in a growth chamber (25 ℃ 12 h
 day / 20 ℃ 12 h night). Germinated seeds were transplanted into seedlings
 trays. In June 2018, four individuals of similar size were selected and
 transplanted into 3 L pots with one plant per pot (i.e., F1 generation).
 These 3 L pots were filled with a 1:1 mixture of horticultural sand: peat
 with 8 g of slow-release fertilizer per pot (Osmocote 5#, Scotts,
 Marysville, OH, United States, with a 14N: 13P: 13K elemental ratio,
 duration 5-6 months). Before soil water manipulations, all seedlings
 received adequate watering for one week with 45% soil moisture by volume
 (equivalent to 100% field capacity). Then, two of the four individuals
 from each original source (2 seed morphs × 4 F0 individuals × 2 habitats)
 were randomly assigned to well-watered and drought-stressed treatments
 (Fig. S1). For well-watered treatment, the pots were regularly watered
 twice a day to keep soil moisture saturated, when soil moisture by volume
 was maintained at 45%. The drought-stressed treatment was manipulated by
 not watering the plants for about one week until their leaves appeared
 wilt, when the soil moisture by volume dropped to about 9% (equivalent to
 soil relative water content of 20%). The soil moisture for the
 drought-treated pots was then maintained by weighing the pots and
 supplementing the water losses every day. As a result, a total of 64
 parental plants (2 replicates × 2 maternal seed morphs × 4 F0 individuals
 × 2 habitats × 2 water treatments; Fig. S1) were grown to reproductive
 maturity. The positions of the plants were shuffled weekly. Manual
 pollination was carried out between the two replicated parental plants to
 ensure a high fertilization percentage. The mature seeds detached from
 withered seed heads were collected in October 2018 (120 days after
 germination), when the plants began to senesce. All seeds were air-dried
 and stored at room temperature (approximately 20 ℃) until further
 experiment. The dimorphic seeds were separated, weighted and counted for
 each F1-generation plant. In October 2020, mature seeds
 of the F1 generation were germinated using the same protocol as those of
 the F0 generation. Three days after germination, 5 pairs of these
 F2-generation seedlings of similar sizes, a total of 640 seedlings, were
 transplanted into seedling trays filled with a 1:1 mixture of
 horticultural sand: peat. Seedlings received adequate watering with 45%
 soil moisture by volume (equivalent to 100% field capacity) for 48 h. Then
 half of the F2-generation seedlings were subjected to well-watered
 treatment, while the other half were subjected to drought treatment. Both
 soil water treatments were manipulated using the same protocol as that for
 the F1 generation. For these F2-generation plants, they were grown for 21
 days (Sultan et al., 2009). Due to mortality from drought stress, only 591
 seedlings were harvested at the end of experiment. The individuals were
 oven-dried at 72 ℃ for 3 days and weighed. (3)
 Calculation of drought tolerance For each
 drought-stressed seedling from each combination of maternal seed morph,
 maternal individual, and habitat, its drought tolerance was calculated
 following the equation by Valliere et al. (2019):
 Drought Tolerance = (Total
 Biomass <sub>drought</sub> – Mean Total
 Biomass <sub>well-watered</sub>) / Mean Total
 Biomass <sub>well-watered</sub> Here, Total
 Biomass <sub>drought</sub> is the total biomass of focal
 drought-stressed seedling, and Mean Total
 Biomass <sub>well-watered</sub> is the averaged biomass of all
 well-watered seedlings from the same combination of maternal seed morph,
 maternal plant, and habitat. A high negative value corresponds with a weak
 drought tolerance, while a low negative value corresponds with a strong
 drought tolerance. Sometimes, a positive value occurred, indicating that
 the seedling performs better under drought than in well-watered
 condition. For each seed morph of each maternal plant,
 its mean and variation of drought tolerance were calculated as the mean
 and standard deviation (SD) of the five replicated drought-stressed
 seedlings. <strong>2. Simulation
 data</strong> Given the ubiquitous spatial
 heterogeneity of water conditions,
 some <em>Synedrella</em> maternal plants may experience
 drought stress while the rest may live in well-watered conditions. Because
 different maternal environments may result in differential reproductive
 patterns in terms of dimorphic offspring production, the intraspecific
 mean and variation of drought tolerance are likely to change in response
 to the altered spatial frequency of maternal drought stress. Thus, we
 generated a simulated dataset of offspring drought tolerance to determine
 the intraspecific mean and variation of drought tolerance along a gradient
 where different proportions of maternal plants were exposed to drought
 stress. Under the assumption that all seeds will successfully germinate,
 we simply manipulated the abundance of dimorphic seeds based on: (1) the
 numbers of the D- and R-type seeds produced under well-watered and
 drought-stressed treatments by each maternal plant from the focal
 population; and (2) the presumed proportions of maternal plants that would
 be exposed to drought stress (i.e., 80%, 75%, 67%, 50%, 33%, 25%,
 20%). Step by step simulation of intraspecific drought
 tolerance along a gradient of spatial frequency of drought stress is as
 follows: (1) Determine the data distribution of
 offspring drought tolerance for simulation Basing on
 the experimental data of dimorphic offspring drought tolerance, we first
 calculated the mean and standard deviation of offspring drought tolerance.
 Since we have a total of 32 combinations between F0 habitat (dry vs. wet)
 x F0 plant ID (1-4) x F1 environment (drought vs. well-watered) x F1 seed
 morph (R- vs. D-type), we calculated the mean and standard deviation of
 offspring drought tolerance for each combination. For each combination, we
 assumed that the drought tolerance of all D- and R-type offspring produced
 by this combination followed a normal distribution defined by the mean and
 standard deviation quantified using the above-mentioned
 equations. (2) Determine the numbers of dimorphic
 offspring used for each simulation scenario Because the
 numbers of dimorphic offspring produced by each combination differed under
 different simulation scenarios, we need to determine the numbers of
 dimorphic offspring used for each simulation scenario. Basing on the
 experimental data of dimorphic offspring production by each maternal plant
 under drought-stressed and well-watered treatment, we first determined the
 numbers of dimorphic offspring used for each simulation scenario. For
 instance, for the scenario of 50% probability of maternal drought stress,
 we assigned 50% of maternal plants to drought treatment. For the scenario
 of 20% probability of maternal drought stress, we assigned 20% of maternal
 plants to drought treatment. For convenience, we assign an ID to each
 combination: the combinations associated with maternal drought-stressed
 treatment were assigned as combinations 1-16, while those associated with
 maternal well-watered treatment were assigned as combinations 17-32. When
 <em>x</em>% of F1 maternal plants were assigned to drought
 treatment, the relative proportion of each type of dimorphic offspring
 produced by the
 <em>i<sup>t</sup></em><sup>h</sup>
 combination of can be calculated using the following equation:
 <em>Seed Number <sub>D-type</sub></em> =
 <em>x%</em><em>×</em><em>Seed Number
 <sub>D-type, drought-stressed</sub></em> +
 (1-<em>x%</em>)× <em>Seed Number <sub>D-type,
 well-watered</sub></em>       (Eq. 1)
 <em>Seed Number <sub>R-type</sub></em> =
 <em>x%</em><em>×</em><em>Seed Number
 <sub>R-type, drought-stressed</sub></em> +
 (1-<em>x%</em>)× <em>Seed Number <sub>R-type,
 well-watered </sub></em>      (Eq. 2) Total
 Seed Number = <em>Seed Number
 <sub>D-type</sub></em> +<em> Seed Number
 <sub>R-type</sub></em>      (Eq. 3)
 For i between 1 and 16: <em>Proportion
 <sub>D-type,i</sub> </em>=
 <em>x%</em><em>×</em><em>Seed Number
 <sub>D-type, i</sub></em>/<em>Total Seed
 Number</em>      (Eq. 4) <em>Proportion
 <sub>R-type,i</sub> </em>=
 <em>x%</em><em>×</em><em>Seed Number
 <sub>R-type, i</sub></em>/<em>Total Seed
 Number</em>      (Eq. 5) For i between 17 and
 32: <em>Proportion
 <sub>D-type,i</sub> </em>=
 (1-<em>x%</em>)<em>×</em><em>Seed Number
 <sub>D-type, i</sub></em>/<em>Total Seed
 Number</em>      (Eq. 6) <em>Proportion
 <sub>R-type,i</sub> </em>=
 (1-<em>x%</em>)<em>×</em><em>Seed Number
 <sub>R-type, i</sub></em>/<em>Total Seed
 Number</em>      (Eq. 7) where <em>Seed
 Number <sub>D-type</sub></em>, <em>Seed Number
 <sub>R-type</sub></em> and <em>Total Seed
 Number</em> represent the total numbers of D-type, R-type and both
 types of seeds produced, respectively. <em>Seed Number
 <sub>D-type,i</sub></em> and <em>Seed Number
 <sub>R-type,i</sub></em> represent the numbers of D- and
 R-type seeds produced by the
 <em>i</em><sup>th</sup> combination.
 <em>Proportion <sub>D-type,i</sub></em> and
 <em>Proportion <sub>R-type,i</sub></em> represent
 the relative proportion of D- and R-type seeds produced by the
 <em>i</em><sup>th</sup> combination, respectively.
 Then, under the assumption that a total of 1,000,000 offspring will be
 produced in each scenario, the numbers of dimorphic offspring used for the
 scenario when <em>x</em>% of F1 maternal plants were exposed
 to drought stress can be calculated as follows:
 <em>Offspring Number <sub>D-type,i</sub>
 </em>= <em>Proportion
 <sub>D-type,i</sub></em> ×1,000,000    (Eq. 8)
 <em>Offspring Number <sub>R-type,i</sub>
 </em>= <em>Proportion
 <sub>R-type,i</sub></em> ×1,000,000    (Eq. 9)
 where <em>Offspring Number
 <sub>D-type,i</sub></em> and <em>Offspring Number
 <sub>R-type,i</sub></em> represent the numbers of D- and
 R-type offspring for the <em>i</em><sup>th</sup>
 combination that would be used for data simulation,
 respectively. (3) Data simulation
 For the <em>i</em><sup>th</sup>
 combinations, we used Python version 3.0 (van Rossum & Drake,
 2009) to randomly draw a drought tolerance value from the corresponding
 normal distribution defined by step 1 and repeated the process for the
 corresponding number of times defined by step 2. This process was repeated
 for all 32 combinations to get the drought tolerance data for all
 1,000,000 offspring individuals. Since there were seven different
 scenarios (i.e., meternal drought probabilities of 20%, 25%, 33%, 50%,
 67%, 75% and 80%), we assigned x to 20, 25, 33, 50, 67, 75 and 80, and
 repeated the simulation process for each x value. As a result, we
 obstained seven datasets, each containing 1,000,000 offspring drought
 tolerance values.
description: # Spatiotemporal interaction of risk-spreading strategies for a
 seed-dimorphic plant
 [https://doi.org/10.5061/dryad.612jm64bj](https://doi.org/10.5061/dryad.612jm64bj) ## Description of the data and file structure **1. Seed mass of maternal plants.csv** Dataset for the dry mass of seeds collected from field. Population = population origin Seed morph = seed morph Maternal family ID = ID of the maternal family Seed mass per grain (mg) = seed mass per grain (mg) **2. Offspring drought tolerance.csv** Dataset for the drought tolerance of F2 generation. Population = population origin Maternal seed morph = seed morph of the maternal individual Maternal family ID = ID of the maternal family Maternal environment = the water treatment imposed on the maternal individual Offspring seed morph = seed morph of the offspring individual Total biomass under drought-stressed treatment (mg) = offspring total biomass under drought-stressed treatment (mg) Total biomass under well-watered treatment (mg) = offspring total biomass under well-watered treatment (mg) Mean total biomass under well-watered treatment (mg) = mean total biomass across offspring of each combination of F0 maternal plant habitat (dry vs. wet) x F0 maternal plant ID (1-4) x F1 maternal environment (drought vs. well-watered) x F1 seed morph (R- vs. D-type) x F2 seed morph (R- vs. D-type) under well-watered treatment (mg) Drought tolerance = offspring drought tolerance Missing data code- NA **3. Offspring drought tolerance and seed number for data simulation** The mean, standard deviation, and seed number for each combination of F0 maternal plant habitat (dry vs. wet) x F0 maternal plant ID (1-4) x F1 maternal environment (drought vs. well-watered) x F1 seed morph (R- vs. D-type) x F2 seed morph (R- vs. D-type). Population = population origin MS = maternal seed morph (seed morph of the maternal individual) ME = maternal environment (the water treatment imposed on the maternal individual) OS = offspring seed morph (seed morph of the offspring individual) Family = ID of the maternal family Mean = mean drought tolerance SD = standard deviation of drought tolerance SN = seed number **4. Species-level drought tolerance simulation** Datasets for species-level drought tolerance simulation. This file contains seven tabs corresponding to seven presumed proportions of maternal plants that would be exposed to drought stress (i.e., 20%, 25%, 33%, 50%, 67%, 75%, 80%). File structures are the same for all tabs. Population = population origin MS = maternal seed morph (seed morph of the maternal individual) ME = maternal environment (the water treatment imposed on the maternal individual) OS = offspring seed morph (seed morph of the offspring individual) Family = ID of the maternal family Simulation #1-#5 = the five replicates of data simulations