Do Not Keep It in the Dark: How Shading and Other On-farm Management Decisions Influence Seed Production and Quality of Asclepias tuberosa L.

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Sarah Tevlin Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Maria Teresa Davidson Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Jena Osmani Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Héctor E. Pérez Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Abstract

Demand for butterfly milkweed (Asclepias tuberosa L.) has increased in recent years. However, seed production practices are not well-defined. We partnered with a wildflower seed producer to investigate the effects of weed barrier cloth, plot shading, mature follicle harvest timing, and dry–cold stratification on seed production and germination. Weed cloth had no impact on seed production. However, shading decreased the number of seeds produced by 1.2- to 9.6-fold. Seeds harvested in July and August showed 2.9- and 2.3-fold improvements in total germination and more uniform and rapid germination compared with September-collected seeds. Conversely, seeds exposed to dry–cold stratification displayed a 3.0-fold reduction in the germination rate compared with nonstratified seeds. Our results indicate that the production system significantly impacts seed production and quality of A. tuberosa. Seed producers can use weed barrier cloth to facilitate seed collection from shattering follicles and suppress weeds without a considerable loss of seed production. However, plants should not be grown under conditions of additional shade. Furthermore, high-quality A. tuberosa seeds can be collected earlier in the year, but they should not be subjected to dry–cold stratification.

The United Nation’s Decade on Ecosystem Restoration placed habitat recovery in the global spotlight and contributed to an increased demand for native species used in revegetation (McCormick et al. 2021). Seed-based propagation is often the preferred method of producing plants for restoration and revegetation programs (Elzenga et al. 2019; Kauth and Pérez 2011; White and Dabbs 2016). However, the supply of native seeds available for this is often severely limited. Cultivating native species on specialized seed production farms is widely recognized as a solution to current supply limitations. However, a dearth of information regarding on-farm production practices and their relationship to the seed biology of many native species has seriously restricted the growth of this industry in many regions (Ladouceur et al. 2018).

On-farm production decisions such as plot placement, weed control methods, harvest timing, and postharvest seed treatments can directly or indirectly influence the ultimate seed lot quality and germination performance. Seed quality is a multidimensional property composed of factors such as seed fill and viability, seed vigor, and seed health. Germination performance comprises the percentage and rate of germination within a seed lot. Seed quality and germination performance are known to improve or decline over a seed production season as the on-plant maturation process progresses (Bewley et al. 2013; Dogra and Dani 2019; Ellis 2019; Halmer 2006). Therefore, growers can directly influence the seed lot quality and germination performance by strategically planning harvests (Copeland and Loeffler 2006). Similarly, by controlling weeds, farmers reduce competition and may free resources that the maternal plant can subsequently allocate to developing seeds, thereby indirectly influencing seed lot quality (Copeland and Loeffler 2006). Despite these generalizations, a more thorough, species-specific understanding of how on-farm production factors influence seed quality is necessary to improve the native plant seed supply.

Unfortunately, biotic and abiotic components underlying seed quality and germination performance of many native species are poorly understood (Elzenga et al. 2019). Both traits are generally influenced by several interrelated factors, including pollination efficiency, weather conditions during seed development, resource availability and competition during the growth of mother plants, disease pressure throughout the developmental period, and degree of seed maturation at harvest (Copeland and Loeffler 2006). For many species, germination performance is further complicated by seed dormancy. Dormancy is an inherent seed trait that prevents germination even when external conditions may be permissible for germination to occur. After dormancy is alleviated, seeds may germinate when environmental conditions are suitable. In nature, dormancy is broken after seeds sense necessary environmental conditions for species-specific durations (Baskin and Baskin 2014). Dormancy in a production setting is often alleviated by presowing treatments, including stratification, scarification, after-ripening, and application of exogenous chemicals such as plant hormones (Footit and Holdsworth 2006). Cold stratification, one of the more common dormancy-breaking treatments, involves placing imbibed seeds in a moisture-holding matrix (e.g., moist sand) and then moving the matrix to cold (approximately 5 °C) conditions for a set length of time (Gosling 2006). The method of stratification is well-known. However, the duration at which seeds of a particular species must remain imbibed under cold temperatures requires investigation to identify periods that promote high levels of germination. Furthermore, cold stratification is often a universal recommendation even though seeds of congeneric species may not require this type of treatment. Consequently, these knowledge gaps complicate efforts among native seed growers to produce high-quality seed lots and seedlings.

One species currently undergoing review for increased cultivation is Asclepias tuberosa L. (Apocynaceae, butterfly weed, butterfly milkweed). Asclepias tuberosa is an herbaceous perennial commonly found throughout eastern North America in high-light environments with dry, well-drained soils. The native distribution of the species extends from Ontario to Newfoundland in Canada, south to Florida, and west to Colorado. It is perhaps best known for the vital role it plays as a forage source for larval monarch (Danaus plexippus L.) butterflies (Hutchings 1923; Lewis et al. 2020). Additionally, A. tuberosa is highly drought-tolerant and possesses a prolonged flowering and seed production season (Lewis et al. 2020). These attributes make it highly desirable for use in restoration and landscaping. Subsequently, the demand for A. tuberosa seeds and mature plants has greatly increased in recent years. However, studies that investigated on-farm production methods appropriate for the species are lacking.

Much of what is known about A. tuberosa production stems from generalizations made for the genus (Lewis et al. 2020). Moreover, existing research predominantly originates from A. tuberosa populations in the northern portion of its range. For example, members of Asclepias are presumed to possess physiological dormancy broken by cold stratification (Baskin and Baskin 1977; Farmer et al. 1986; Finch et al. 2019; Oegema and Fletcher 1972). Additional anecdotal evidence suggests that placing dry seeds in cold conditions also improves germination performance (Diboll 2008; Prairie Nursery 2019). This process, referred to here as dry–cold stratification following the terminology frequently encountered by consumers, is commonly recommended by commercial seed retailers (Bewley et al. 2006; Diboll 2008; Prairie Nursery 2019). However, current information related to production practices or seed dormancy break for plants occurring in the northern part of the A. tuberosa range may not be suitable for growers attempting to cultivate the species for seed or seedling production in southern regions. Therefore, we partnered with a native wildflower seed producer in Alachua, FL, to narrow the knowledge gap by examining the effects of three priority on-farm production factors. Specifically, in collaboration with our farmer partner, we studied the influence of weed barrier cloth on seed production. We also investigated the impact of harvest timing and dry–cold stratification on germination performance. Subsequently, a re-examination of our seed count data led to assessing the consequences of supplemental shading on seed production.

Materials and Methods

Plant materials and experimental plot layout.

Nursery workers collected A. tuberosa cuttings from plants occurring in natural stands located throughout north Florida (Alachua to Leon counties). They allowed these to grow to reproductive maturity. Then, workers collected seeds to produce the seedlings used in this study. The nursery provided seedlings to our farmer partner in 2020 in 236-mL pots (i.e., standard 2-inch, 32 pot trays). We established our experimental plot at an existing research site on our partner farmer’s property in Alachua while the A. tuberosa seedlings were grown. The following plot layout and experimental design was selected according to our farmer partner’s preferred production practices. The experimental plot measured 7.3 × 31.7 m (0.02 ha). The long side was oriented in a north–south direction. We divided the plot using a randomized complete block design to account for slight elevational changes along a southeast to northwest gradient. We used two blocks because of space constraints. We established a 0.6-m bare-ground buffer around the experimental plot and a 1.8-m bare-ground buffer between blocks to minimize edge effects. Each block measured 3.7 × 30.5 m (0.01 ha). The entire experimental plot was covered with black polystyrene bird netting (NET-STR-100; Bird-X, Elmhurst, IL, USA) to prevent monarch caterpillar herbivory. The bird netting provided ∼90% light transmittance.

Seed production and weed barrier cloth.

Our production method experiment consisted of applying weed barrier ground cloth and control treatments. We pinned one layer of black polypropylene cloth (SBLT3300; DeWitt, Sikeston, MO, USA) to the ground with sod staples in the weed barrier treatment plots. The control treatment consisted of bare soil with no weed control cloth. We randomly assigned treatments to each block. We maintained a 60-mm gap between runs of weed barrier cloth to facilitate seedling planting and simplify subsequent seed harvest. We pinned drip tape (TLCV6–12025; Netafim, Fresno, CA, USA) along each planting row within the plots.

Then, we randomly assigned 150 seedlings to each treatment during the Spring 2020. These were distributed among three rows with 50 seedlings in each row planted at 300-mm intervals to coincide with irrigation emitters along the drip tape. We provided irrigation daily during transplant establishment and flowering. Otherwise, irrigation was only provided once during severe drought when the loss of nearby crops appeared likely. We applied one tablespoon per plant of slow-release fertilizer (24.0N–0.0P–11.0K) once before the flowering season began (early April). We periodically removed weeds by hand from any bare ground within the experimental plot and allowed plants to acclimate for 1 year before experimentation.

Follicle harvest date and germination.

In north-central Florida, the fruit production season for A. tuberosa occurs from May through September. We visited the plots weekly starting in May 2021, to monitor follicle development. We placed white organza bags (76.2 × 101.6 mm; OP-01-WHITE; Crafty Arts Market, Irving, TX, USA) over follicles to prevent seed loss from dehiscing fruits as these reached maturity between visits. All individual plants continuously produced mature follicles during the July to September harvest period. We harvested follicles when these dehisced. Then, we removed seeds from fruits and pappus from seeds in the laboratory.

Seed yield.

We counted the total number of mature seeds harvested within each production method (i.e., presence or absence of weed barrier cloth) and block. We pooled seed counts across harvest months but maintained separation of the seeds produced within each treatment by storing these in paper envelopes labeled according to the month of harvest. Then, we stored envelopes on the laboratory bench at room temperature (approximately 24 °C, 50% relative humidity) until stratification experiments commenced approximately 2 to 10 weeks later, depending on the harvest date.

Dry–cold seed stratification versus no stratification.

Because of differences in seed availability between the harvest months, equal replicates were not possible. Instead, we counted 40 to 120 seeds collected during the harvest months of July, August, and September. The seeds from each month were subdivided into sets of 20 and re-packaged into labeled envelopes (Fig. 1). We continued to maintain separation by harvest month. A total of 280 seeds distributed between 14 envelopes were counted and placed in the treatments described. The envelopes were numbered, and four were randomly selected using a random number generator (Fig. 1). Although general guidelines for dry–cold stratification recommend that seeds should remain exposed to cold conditions for at least 30 d, we maintained our seeds at 5 °C and approximately 10% relative humidity for 7 d (i.e., dry–cold stratification). We reduced the time of seed exposure to cold conditions to account for the warm winters present at our study area. The remaining 10 seed envelopes stayed at room temperature on the laboratory bench. Seeds from all 14 of the envelopes remained unimbibed for the duration of the treatments (Fig. 1).

Fig. 1.
Fig. 1.

Workflow depicting seed handling from initial storage to the germination experiment. Step 1 represents the conditions in which the seeds were maintained before the beginning of the experiment. Steps 2a and 2b show the random assignment of seed envelopes to the dry–cold and room temperature treatments, respectively. Step 3 displays germination testing conditions. The red numbers distinguish each sample of seeds.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

Germination assays.

We sowed seeds on two layers of steam-sterilized (40 min, 121 °C, 117 kPa; Amoco® 3011; Steris, Dublin, Ireland) blotter paper (Blue Steel; Anchor Paper, St. Paul, MN, USA) placed within polystyrene germination boxes (156C; Hoffman Manufacturing, Inc., Corvallis, OR, USA). We transferred all boxes to an incubator (130VL; Percival Scientific Inc., Perry, IA, USA) set to a constant 25 °C with a 12-h photoperiod. We irrigated all boxes as needed with a 0.2% solution of Plant Preservative Mixture™ (Plant Cell Technologies, Washington, DC, USA) to minimize the risk of fungal contamination. We monitored seed germination daily for 28 d. Our germination criterion was radicle protrusion to 2 mm. We removed germinated seeds daily. After 28 d, the remaining nongerminated seeds were tested for viability using the tetrazolium staining procedure outlined by Peters (2000) for the Apocynaceae.

Data analysis.

We analyzed seed count data with chi-square goodness of fit tests and assessed planned comparisons at adjusted α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors (Sheskin 2000). We also used goodness of fit tests to evaluate the number of germinated seeds during the harvest date and stratification experiments. However, we used the Marascuilo procedure (Marascuilo and McSweeney 1967) to compare proportions of germinated seeds between treatments. We calculated Cohen’s w index to estimate effect sizes when appropriate (Cohen 1988).

We found a significant block effect when analyzing the impacts of weed barrier cloth on seed production. This prompted further examination of our plot layout. We observed that a tree line occurring to the northeast and north of the research plot cast a shadow on portions of the plots at certain times of the day and during certain seasons. This additional shading was not apparent during plot construction. Nonetheless, the difference between our least and most shaded treatments was approximately 4 h of additional daylight during the reproductive season. Therefore, based on this progression, we re-classified each treatment and block combination with one of four durations of shading. The new classifications consisted of 0, 1.5, 2, or 4 h of additional shading (Fig. 2). We analyzed data in this structure as stated previously.

Fig. 2.
Fig. 2.

Progression of tree-induced shading across Asclepias tuberosa research plots.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

We used nonparametric time-to-event analyses to evaluate temporal patterns of germination and calculate germination parameters (Allison 2010; McNair et al. 2012; Pérez and Kettner 2013). We generated Kaplan-Meier estimates of survivor functions for all germination data. We stratified survivor functions by harvest month or stratification treatment and then used the log-rank statistic to test the null hypothesis that temporal patterns of germination (i.e., survivor functions) were the same between harvest months or stratification treatments. We assessed significant differences using multiple pairwise comparisons with Bonferroni correction (α = 0.05) when appropriate. We calculated the first-quartile germination times (t25) from the product-limit survival estimates output or used t20 when survivor functions did not decrease to less than a probability of 0.75. These values correspond to the smallest germination event times given that the probability of not germinating was more than 0.25 or 0.20. We computed the germination rate as the inverse of these germination times because of limited germination in some treatments. We used statistical software (SAS version 9.4; SAS Institute Inc., Cary, NC, USA) to conduct all analyses other than the Marasculio procedure, which was completed using a spreadsheet (Microsoft Excel 365 version 2211; Microsoft Corp., Redmond, WA, USA).

Results

Seed production and weed barrier cloth.

Asclepias tuberosa plants grown with weed barrier fabric produced 17 more mature seeds over the 3-month collection period compared with plants grown in bare ground (Fig. 3). The slight difference in seed production between the two systems was not significant (χ21 = 0.11; P = 0.74). However, the analysis revealed a significant (χ21 = 79.29; P < 0.0001) block effect that we attributed to additional shading provided by mature trees approximately 9 m to the north and 8 m to the east of the research plot.

Fig. 3.
Fig. 3.

Comparison of the total number of mature seeds produced by plants grown with and without weed barrier cloth. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

Effect of shading on seed production.

Plants growing in the southwestern block did not receive additional tree line shading (Fig. 2) and produced 1195 mature seeds. However, seed production decreased by 1.2- to 9.6-fold as the duration of additional shading increased (Fig. 4). The difference in seed production between the duration of shade categories was significant (χ21 = 1142.92; P < 0.0001). Plants grown in the plot with no additional shading produced the most seeds, and the effect size (Cohen’s w = 0.66) of shading on seed production was large (Fig. 4).

Fig. 4.
Fig. 4.

Comparison of the total number of mature seeds produced after exposure to additional hours of tree-induced shading. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

Effect of follicle harvest date on germination.

Temporal patterns of germination indicated that seeds harvested in July and August germinated more rapidly and completely than seeds harvested in September (Fig. 5). For example, the probability of not germinating decreased to less than 0.35 for seeds harvested in July and August, but it did not decrease to less than 0.70 for seeds harvested in September. The germination rate was 2.0- to 2.8-fold more rapid for seeds harvested in July and August compared with seeds harvested in September. The log-rank test detected significant differences (χ21 = 24.4; P < 0.001) between temporal germination patterns for harvest months. Multiple comparisons revealed that temporal patterns for September-harvested seeds differed in seeds from the remaining harvest months (P < 0.0001), but no statistical differences (P = 0.51) were evident in patterns of seeds collected in July or August.

Fig. 5.
Fig. 5.

Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds harvested in July, August, and September. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

Viability-adjusted germination reached 100% for seeds harvested during all three months. However, total germination reached 80%, 61%, and 25% for seeds harvested in July, August, and September, respectively. This represented a 2.4- to 3.3-fold improvement in total germination compared with September-collected seeds. The goodness of fit test detected a significant difference in total germination (χ22 = 28.2; P < 0.01). Comparisons of total germination between harvest months showed no statistical difference between seeds collected in July and August; however, the germination of September seeds was significantly reduced compared with the germination of seeds from previous months (Table 1). The effect of the harvest month on total germination (Cohen’s w = 0.41) was moderate.

Table 1.

Results of the Marascuilo procedure for comparing Asclepias tuberosa germination proportions by harvest month.

Table 1.

Germination after dry–cold stratification.

Seeds exposed to dry–cold stratification displayed considerably different temporal germination patterns compared with nonstratified seeds stored on the laboratory bench (Fig. 6). The probability of not germinating remained more than 0.75 for stratified seeds, but it decreased to 0.45 for nonstratified seeds. The germination rate for stratified seeds was nearly 3.0-fold slower compared with nonstratified seeds. The differences in temporal germination patterns between stratified and nonstratified seeds were significant according to the log-rank test (χ21 = 22.7; P < 0.001).

Fig. 6.
Fig. 6.

Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds exposed to cold stratification (5 °C) or no stratification (24 °C) for 7 d. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

Citation: HortScience 58, 6; 10.21273/HORTSCI17091-23

Seeds exposed to dry–cold stratification also exhibited a significant (χ21 = 13.1; P < 0.01) 2.6-fold reduction in total germination compared to seeds that did not undergo cold treatment. However, there was no significant difference in germination when adjusted for viability (96% for the dry–cold stratification treatment vs 100%). Accordingly, we attributed the difference in total germination between the two treatments to the fact that September-harvested seeds, which exhibited reduced viability compared to seeds from the other two harvest months (see Effect of follicle harvest date on germination), comprised a larger proportion of the dry–cold stratification treatment than the nonstratified treatment.

Discussion

The production of high-quality seeds is of paramount importance to address limitations in the native plant supply chain, especially in the context of restoration and revegetation programs. However, seed production methods are often lacking or not well-defined for many important native species. We examined the influence of weed barrier cloth, shading, harvest month, and dry–cold stratification on seed yield and germination of Asclepias tuberosa, a species currently confronted with increasing demand for seeds but limited seed production information.

Seed production.

Weed barrier cloth did not affect seed production at our north-central Florida farm. However, farmers should consider their soils before implementing weed barrier cloth on a large scale. Asclepias tuberosa is a drought-tolerant species with a long taproot that is prone to rotting under wet conditions (White and Dabbs 2016). In locations with dry sandy soils, the modest increases in soil moisture retention promoted by weed barrier cloth (Geyer 1981; Kainrath et al. 2022; Nyberg and Haley 2014) are unlikely to result in a negative impact. However, producers growing A. tuberosa on wetter sites should use caution.

In contrast, shading significantly reduced seed production. Further research needs to be conducted to determine the mode through which shading interferes. One anecdotal report suggested that A. tuberosa produces fewer flowers when placed in shaded conditions (White and Dabbs 2016). Other hypotheses include reduced photosynthesis resulting in fewer stored reserves available for seed production (Alvarado-Miller 2018) and lower insect visitation rates, resulting in reduced pollination (Ivey et al. 2003; Jennersten and Morse 1991). Regardless, growers interested in seed production should position their plots to receive full sun.

Germination.

Seed germination behavior is among the most critical aspects to understand when seeking to use a species for cultivation (Pita Villamil et al. 2002). Germination ability varies because of genetic and phenotypic factors and is particularly influenced by the conditions under which seeds have matured (Bewley et al. 2013; Ellis 2019; Gutterman 1980). Accordingly, we suggest two modes through which harvest timing may be impacting germination in A. tuberosa: through seasonal changes in environmental conditions that occur as the seed production period progresses or through life cycle changes in the maternal plants. The effects of seasonal environmental changes on seed development of many species are well-documented. Factors such as photoperiodic daylength, mean minimum and maximum temperatures, mean evaporation rates, and precipitation vary through time. These factors influence the amount of water and stored reserves available for seed development (Galloway 2002; Gutterman 1992). For example, from the beginning of July to the end of September, daylength at our study site decreased by 2 h. Declining daylength over our three harvest months may have contributed to the decrease in germination performance because seeds produced under shorter daylength conditions often possess less stored nutritive tissue and smaller embryos (Cavers and Steel 1984; Galloway 2001, 2002; Gutterman 1992).

Similarly, the availability of resources allocated to seed development varies as a function of the life cycle of the maternal plant (Pita Villamil et al. 2002). Asclepias tuberosa is a perennial species that undergoes senescence of its above-ground structures during late fall (Gopal and Witsen 2015). In preparation, as the season progresses, the maternal plant diverts increasingly greater amounts of resources from reproduction toward the development of its perennating structure, the tuberous root, for which the species is named. Consequently, seeds produced during the later portion of the seed production season receive fewer resources for development. Similarly, reproduction in A. tuberosa is modular because new flowers and fruits are initiated while the development of previously established fruits is still ongoing (Pita Villamil et al. 2002). Therefore, as the reproductive season progresses, maternal resources are increasingly divided not only between senescence and reproduction but also between a growing number of reproductive structures (Galloway 2002; Pita Villamil et al. 2002). By reducing resources available for seed development, both mechanisms negatively impact the quality of seeds collected later in the harvest season and offer an additional explanation for our observed decreases in germination performance from late-harvested seeds.

A reduction in germination performance caused by the acquisition of dormancy in seeds produced toward the end, but not the start, of a production season provides a third explanation. This mechanism has been documented for other species (Baskin and Baskin 1985; Baskin and Baskin 2014). However, we do not believe this is applicable in this case. Viability testing after the harvest date germination experiment revealed that none of the remaining nongerminated seeds stained positive.

Furthermore, the results of our dry–cold seed stratification experiment do not support the theory that dormancy reduced germination performance. Although members of Asclepias are generally presumed to possess physiological dormancy broken by cold stratification (Baskin and Baskin 1977; Farmer et al. 1986; Finch et al. 2019; Oegema and Fletcher 1972), the reduced germination performance exhibited by seeds that underwent dry–cold stratification indicated that dormancy may be absent from our population. This is in agreement with findings by other researchers who have noted population-specific dormancy-breaking requirements and even nondormancy in seeds of other Asclepias species (Finch et al. 2019; Kaye et al. 2018). Similarly, seeds may not express dormancy mechanisms because of the relatively benign environmental conditions at our study location (Baskin and Baskin 2014). In northeastern Florida, seed development and shedding phenology (June–September) of A. tuberosa do not coincide with conditions (e.g., cold, wet) that would justify cold stratification as a dormancy-breaking treatment.

Finally, it is worth noting that although we used it here in deference to the terminology many A. tuberosa consumers will encounter, we believe the use of the term “dry–cold stratification” creates confusion. Stratification, by definition, can be conducted only for imbibed seeds. Imbibition restores physiological activity to seeds. Dry seeds, with limited physiological activity, may not sense dormancy-breaking triggers such as cold temperatures (Baskin and Baskin 2014). Accordingly, the more appropriate term for seeds that are placed in cold conditions while dry is “cold storage.”

Conclusions

Asclepias tuberosa is highly desirable for use in restoration and landscaping. Recently, the demand for seeds of this species has increased. Native seed growers interested in cultivating A. tuberosa for commercial sale can manipulate their on-farm management decisions to maximize seed production and germination performance. Growers in the southeastern region of the range of A. tuberosa may use weed barrier cloth without negatively impacting seed yield. However, plots should be positioned to minimize plant shading. Furthermore, seeds harvested during the first half of the production season are likely to exhibit greater germination performance than seeds harvested later in the season. However, dry–cold stratification is unnecessary for seeds from this region and may result in reduced germination rates.

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    • Export Citation
  • Gutterman Y. 1992 Influences of daylength and red or far-red light during the storage of ripe Cucumis prophetarum fruits, on seed-germination in light J Arid Environ.23 4 443449 https://doi.org/10.1016/S0140-1963(18)30617-7

    • Search Google Scholar
    • Export Citation
  • Halmer P. 2006 Quality 567 Black M, Bewley JD & Halmer P The encyclopedia of seeds: Science, technology and uses.CABI Cambridge, MA, USA

  • Hutchings CB. 1923 A note of the monarch or milkweed butterfly with special reference to its migratory habits Can Field Nat.37 150

  • Ivey CT, Martinez P & Wyatt R. 2003 Variation in pollinator effectiveness in swamp milkweed, Asclepias incarnata (Apocynaceae) Am J Bot.90 2 214225 https://doi.org/10.3732/ajb.90.2.214

    • Search Google Scholar
    • Export Citation
  • Jennersten O & Morse DH. 1991 The quality of pollination by diurnal and nocturnal insects visiting common milkweed, Asclepias syriaca Am Midl Nat.125 1 1828 https://doi.org/10.2307/2426365

    • Search Google Scholar
    • Export Citation
  • Kainrath NB, Dijkstra P, Gehring CA, Updike C & Grady KC. 2022 Water as the key to sagebrush restoration success in cheatgrass-invaded ecosystems Restor Ecol.30 7 11 https://doi.org/10.1111/rec.13473

    • Search Google Scholar
    • Export Citation
  • Kauth PJ & Pérez HE. 2011 Industry survey of the native wildflower market in Florida HortTechnology.21 6 779788 https://doi.org/10.21273/HORTTECH.21.6.779

    • Search Google Scholar
    • Export Citation
  • Kaye TN, Sandlin IJ & Bahm MA. 2018 Seed dormancy and germination vary within and among species of milkweeds AoB Plants.10 2 13 https://doi.org/10.1093/aobpla/ply018

    • Search Google Scholar
    • Export Citation
  • Ladouceur E, Jimenez-Alfaro B, Marin M, De Vitis M, Abbandonato H, Iannetta PPM, Bonomi C & Pritchard HW. 2018 Native seed supply and the restoration species pool Conserv Lett.11 2 9 https://doi.org/10.1111/conl.12381

    • Search Google Scholar
    • Export Citation
  • Lewis M, Chappell M, Thomas PA, Zhang D & Greyvenstein O. 2020 Development of a vegetative propagation protocol for Asclepias tuberosa Native Plants J.21 1 2734 https://doi.org/10.3368/npj.21.1.27

    • Search Google Scholar
    • Export Citation
  • Marascuilo LA & McSweeney M. 1967 Nonparametric post hoc comparisons for trend Psychol Bull.67 6 401412 https://psycnet.apa.org/doi/10.1037/h0020421

    • Search Google Scholar
    • Export Citation
  • McCormick ML, Carr AN, Massatti R, Winkler DE, De Angelis P & Olwell P. 2021 How to increase the supply of native seed to improve restoration success: The US native seed development process Restor Ecol.29 8 9 https://doi.org/10.1111/rec.13499

    • Search Google Scholar
    • Export Citation
  • McNair JN, Sunkara A & Frobish D. 2012 How to analyse seed germination data using statistical time-to-event analysis: Non-parametric and semi-parametric methods Seed Sci Res.22 2 7795 https://doi.org/10.1017/S0960258511000547

    • Search Google Scholar
    • Export Citation
  • Nyberg A & Haley H. 2014 Restoring midwestern Viola species for regal fritillary butterfly recovery Native Plants J.15 2 129133 https://doi.org/10.3368/npj.15.2.129

    • Search Google Scholar
    • Export Citation
  • Oegema T & Fletcher RA. 1972 Factors that influence dormancy in milkweed seeds Can J of Bot.50 4 713& https://doi.org/10.1139/b72-088

  • Pérez HE & Kettner K. 2013 Characterizing Ipomopsis rubra (Polemoniaceae) germination under various thermal scenarios with non-parametric and semi-parametric statistical methods Planta.238 4 771784 https://doi.org/10.1007/s00425-013-1935-8

    • Search Google Scholar
    • Export Citation
  • Peters J. 2000 Tetrazolium testing handbook 1st ed Association of Official Seed Analysts

  • Pita Villamil JM, Pérez-García F & Martínez-Laborde JB. 2002 Time of seed collection and germination in rocket, Erucavesicaria (L.) Cav. (Brassicaceae) Genet Resources Crop Evol.49 1 4751 https://doi.org/10.1023/A:1013875614186

    • Search Google Scholar
    • Export Citation
  • Prairie Nurser 2019 Seed Propagation Information https://www.prairienursery.com/media/pdf/seed-propagation.pdf. [accessed 15 Sep 2022]

  • Sheskin DJ. 2000 Handbook of parametric and non-parametric statistical procedures 2nd ed Chapman & Hall/CRC Boca Raton, FL, USA

  • White SA & Dabbs AL. 2016 Rain Garden Plants: Asclepias tuberosa - Butterfly Milkweed SC Waterways. https://dc.statelibrary.sc.gov/bitstream/handle/10827/43851/CU_ES_H2O_329_2016-02.pdf?sequence=1. [accessed 15 Sep 2022]

    • Search Google Scholar
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  • Fig. 1.

    Workflow depicting seed handling from initial storage to the germination experiment. Step 1 represents the conditions in which the seeds were maintained before the beginning of the experiment. Steps 2a and 2b show the random assignment of seed envelopes to the dry–cold and room temperature treatments, respectively. Step 3 displays germination testing conditions. The red numbers distinguish each sample of seeds.

  • Fig. 2.

    Progression of tree-induced shading across Asclepias tuberosa research plots.

  • Fig. 3.

    Comparison of the total number of mature seeds produced by plants grown with and without weed barrier cloth. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

  • Fig. 4.

    Comparison of the total number of mature seeds produced after exposure to additional hours of tree-induced shading. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

  • Fig. 5.

    Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds harvested in July, August, and September. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

  • Fig. 6.

    Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds exposed to cold stratification (5 °C) or no stratification (24 °C) for 7 d. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

  • Allison PD. 2010 Survival analysis using SAS: A practical guide 2nd ed SAS Institute Inc. Cary, NC, USA

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  • Farmer JM, Price SC & Bell CR. 1986 Population, temperature, and substrate influences on common milkweed (Asclepias syriaca) seed germination Weed Sci.34 4 525528 https://doi.org/10.1017/S0043174500067369

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  • Finch J, Walck JL, Hidayati SN, Kramer AT, Lason V & Havens K. 2019 Germination niche breadth varies inconsistently among three Asclepias congeners along a latitudinal gradient Plant Biol.21 3 425438 https://doi.org/10.1111/plb.12843

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  • Footit S & Holdsworth M. 2006 Dormancy breaking 203204 Black M, Bewley JD & Halmer P The encyclopedia of seeds: Science, technology and uses.CABI Cambridge, MA, USA

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  • Galloway LF. 2001 The effect of maternal and paternal environments on seed characters in the herbaceous plant Campanula americana (Campanulaceae) Am J Bot.88 5 832840 https://doi.org/10.2307/2657035

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  • Galloway LF. 2002 The effect of maternal phenology on offspring characters in the herbaceous plant Campanula americana J Ecol.90 5 851858 https://doi.org/10.1046/j.1365-2745.2002.00714.x

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  • Gopal N & Witsen J. 2015 Decline in milkweed (Asclepias syriaca) populations in central New Jersey over a one year period World J Agric Res.3 4 119122 https://doi.org/10.12691/wjar-3-4-1

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  • Gosling P. 2006 Stratification 681 Black M, Bewley JD & Halmer P The encyclopedia of seeds: Science, technology and uses.CABI Cambridge, MA, USA

  • Gutterman Y. 1980 Influences on seed germinability - phenotypic maternal effects during seed maturation Isr J Bot.29 1-4 105117 https://doi.org/10.1080/0021213X.1980.10676881

    • Search Google Scholar
    • Export Citation
  • Gutterman Y. 1992 Influences of daylength and red or far-red light during the storage of ripe Cucumis prophetarum fruits, on seed-germination in light J Arid Environ.23 4 443449 https://doi.org/10.1016/S0140-1963(18)30617-7

    • Search Google Scholar
    • Export Citation
  • Halmer P. 2006 Quality 567 Black M, Bewley JD & Halmer P The encyclopedia of seeds: Science, technology and uses.CABI Cambridge, MA, USA

  • Hutchings CB. 1923 A note of the monarch or milkweed butterfly with special reference to its migratory habits Can Field Nat.37 150

  • Ivey CT, Martinez P & Wyatt R. 2003 Variation in pollinator effectiveness in swamp milkweed, Asclepias incarnata (Apocynaceae) Am J Bot.90 2 214225 https://doi.org/10.3732/ajb.90.2.214

    • Search Google Scholar
    • Export Citation
  • Jennersten O & Morse DH. 1991 The quality of pollination by diurnal and nocturnal insects visiting common milkweed, Asclepias syriaca Am Midl Nat.125 1 1828 https://doi.org/10.2307/2426365

    • Search Google Scholar
    • Export Citation
  • Kainrath NB, Dijkstra P, Gehring CA, Updike C & Grady KC. 2022 Water as the key to sagebrush restoration success in cheatgrass-invaded ecosystems Restor Ecol.30 7 11 https://doi.org/10.1111/rec.13473

    • Search Google Scholar
    • Export Citation
  • Kauth PJ & Pérez HE. 2011 Industry survey of the native wildflower market in Florida HortTechnology.21 6 779788 https://doi.org/10.21273/HORTTECH.21.6.779

    • Search Google Scholar
    • Export Citation
  • Kaye TN, Sandlin IJ & Bahm MA. 2018 Seed dormancy and germination vary within and among species of milkweeds AoB Plants.10 2 13 https://doi.org/10.1093/aobpla/ply018

    • Search Google Scholar
    • Export Citation
  • Ladouceur E, Jimenez-Alfaro B, Marin M, De Vitis M, Abbandonato H, Iannetta PPM, Bonomi C & Pritchard HW. 2018 Native seed supply and the restoration species pool Conserv Lett.11 2 9 https://doi.org/10.1111/conl.12381

    • Search Google Scholar
    • Export Citation
  • Lewis M, Chappell M, Thomas PA, Zhang D & Greyvenstein O. 2020 Development of a vegetative propagation protocol for Asclepias tuberosa Native Plants J.21 1 2734 https://doi.org/10.3368/npj.21.1.27

    • Search Google Scholar
    • Export Citation
  • Marascuilo LA & McSweeney M. 1967 Nonparametric post hoc comparisons for trend Psychol Bull.67 6 401412 https://psycnet.apa.org/doi/10.1037/h0020421

    • Search Google Scholar
    • Export Citation
  • McCormick ML, Carr AN, Massatti R, Winkler DE, De Angelis P & Olwell P. 2021 How to increase the supply of native seed to improve restoration success: The US native seed development process Restor Ecol.29 8 9 https://doi.org/10.1111/rec.13499

    • Search Google Scholar
    • Export Citation
  • McNair JN, Sunkara A & Frobish D. 2012 How to analyse seed germination data using statistical time-to-event analysis: Non-parametric and semi-parametric methods Seed Sci Res.22 2 7795 https://doi.org/10.1017/S0960258511000547

    • Search Google Scholar
    • Export Citation
  • Nyberg A & Haley H. 2014 Restoring midwestern Viola species for regal fritillary butterfly recovery Native Plants J.15 2 129133 https://doi.org/10.3368/npj.15.2.129

    • Search Google Scholar
    • Export Citation
  • Oegema T & Fletcher RA. 1972 Factors that influence dormancy in milkweed seeds Can J of Bot.50 4 713& https://doi.org/10.1139/b72-088

  • Pérez HE & Kettner K. 2013 Characterizing Ipomopsis rubra (Polemoniaceae) germination under various thermal scenarios with non-parametric and semi-parametric statistical methods Planta.238 4 771784 https://doi.org/10.1007/s00425-013-1935-8

    • Search Google Scholar
    • Export Citation
  • Peters J. 2000 Tetrazolium testing handbook 1st ed Association of Official Seed Analysts

  • Pita Villamil JM, Pérez-García F & Martínez-Laborde JB. 2002 Time of seed collection and germination in rocket, Erucavesicaria (L.) Cav. (Brassicaceae) Genet Resources Crop Evol.49 1 4751 https://doi.org/10.1023/A:1013875614186

    • Search Google Scholar
    • Export Citation
  • Prairie Nurser 2019 Seed Propagation Information https://www.prairienursery.com/media/pdf/seed-propagation.pdf. [accessed 15 Sep 2022]

  • Sheskin DJ. 2000 Handbook of parametric and non-parametric statistical procedures 2nd ed Chapman & Hall/CRC Boca Raton, FL, USA

  • White SA & Dabbs AL. 2016 Rain Garden Plants: Asclepias tuberosa - Butterfly Milkweed SC Waterways. https://dc.statelibrary.sc.gov/bitstream/handle/10827/43851/CU_ES_H2O_329_2016-02.pdf?sequence=1. [accessed 15 Sep 2022]

    • Search Google Scholar
    • Export Citation
Sarah Tevlin Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Maria Teresa Davidson Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Jena Osmani Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Héctor E. Pérez Department of Environmental Horticulture, University of Florida, 2047 IFAS Research Drive, Gainesville, FL 32611, USA

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Contributor Notes

We thank Terry Zinn for providing seed material and logistical support. We also acknowledge Marc Godts and April McClain for sharing their production expertise.

This project was financially supported by NIFA-USDA, through the Southern Sustainable Agriculture Research and Education program under grant number LS19-315, USDA Multistate Project W4168, and The Gary Henry Endowment for the Study of Florida Native Wildflowers.

H.E.P. is the corresponding author. E-mail: heperez@ufl.edu.

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  • Fig. 1.

    Workflow depicting seed handling from initial storage to the germination experiment. Step 1 represents the conditions in which the seeds were maintained before the beginning of the experiment. Steps 2a and 2b show the random assignment of seed envelopes to the dry–cold and room temperature treatments, respectively. Step 3 displays germination testing conditions. The red numbers distinguish each sample of seeds.

  • Fig. 2.

    Progression of tree-induced shading across Asclepias tuberosa research plots.

  • Fig. 3.

    Comparison of the total number of mature seeds produced by plants grown with and without weed barrier cloth. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

  • Fig. 4.

    Comparison of the total number of mature seeds produced after exposure to additional hours of tree-induced shading. Planned comparisons were adjusted at α levels of 0.025 and 0.01 to reduce the likelihood of committing type 1 errors. Bars with the same letters are not statistically different.

  • Fig. 5.

    Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds harvested in July, August, and September. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

  • Fig. 6.

    Kaplan-Meier estimates of survivor functions for Asclepias tuberosa seeds exposed to cold stratification (5 °C) or no stratification (24 °C) for 7 d. The decreasing step function indicates germination occurring. Values closer to zero represent higher germination percentage. Pointwise 95% confidence intervals were omitted for clarity. Circles represent censored observations.

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