Ex situ germination of European acorns: data from 93 batches of 12 Quercus species

Abstract

Key message

We provide data on seedlot germination potential—a key trait related to regeneration—of 12 oak species. Germination was tested at the University of Granada following international protocols with 8985 acorns from 93 batches and 16 countries across Europe. Data on germination probability, acorn origin, mass, and moisture content measured on another 4544 acorns are available at https://doiorg.publicaciones.saludcastillayleon.es/10.30827/Digibug.87318. Associated metadata are available at https://metadata-afs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/a742c6d8-bc37-4ca2-8b81-2447c5a8858d.

1 Background

Quercus L. is one of the most extended tree genera in the Northern Hemisphere. Oaks dominate forests, savannas, and shrublands and are also present as secondary species in many ecosystems (Madrigal-Gonzalez et al. 2017). Oak-dominated forests are widespread in Eurasia and North America, and they support high biodiversity and provide important ecosystem services (Johnson et al. 2019). Additionally, oak forests, due to their high resilience to disturbance and environmental stress, offer a promising alternative for inclusion into management plans to address increasingly common extreme weather events (Harvey et al. 2020). In Europe, there are about 22 species of oaks, which include some widely distributed shrubs and trees that contribute to ecosystem structure, composition, and function (Campos et al. 2013) and ultimately to the provision of a plethora of ecosystem services. The success of natural and assisted regeneration of oaks hinges upon the probability of transition among plant life stages (Pulido and Díaz 2005), including the germination of acorns. The germination in oak species is influenced by environmental conditions, as acorns are highly susceptible to desiccation (Xia et al. 2012) and predation (Birkedal et al. 2009). Some studies, both under controlled and field conditions, indicate that germination varies among oak species (Reyes and Casal 2006; Urbieta et al. 2008) and depends on acorn characteristics such as size, morphology, and composition. Many field studies provide data on seedling emergence from seeded acorns (e.g., (Urbieta et al. 2008; Lázaro-González et al. 2023)), yet comparable data on germination potential under controlled conditions remain scarce and dispersed.

As part of a European-scale, collaborative experiment to assess the effectiveness of seeding and planting with European oaks (Leverkus et al. 2021), we conducted a germination test of 93 seed batches from 12 species from different sites across Europe. The acorn batches were sent from 16 countries across Europe to the University of Granada (Spain), where different acorn subsets were weighed or monitored for germination in growth chambers.

This publication aims to provide data that allows to:

• 1) Assess the germination success of different Quercus species from across Europe; and

• 2) Estimate the variability among populations within a given species in germination success, acorn size, and moisture content.

2 Methods

2.1 Acorn collection sites

We collected acorns at multiple European locations as part of a collaborative experiment on assisted regeneration. Initially, the members of the PEN-CAFoRR COST Action (http://www.pen-caforr.org/) were invited to collaborate, yet the invitation to participate was later extended to researchers from across Europe following the publication of a study protocol that established the conditions for participation (Leverkus et al. 2021). The protocol describes an experiment in which participants would establish a field site near their home institution to monitor the success of revegetation with one or more local oak species. Whereas that experiment is not the target of the present dataset, its protocol established that the collection of acorns would be made “as close as possible” to the field site. The 93 acorn batches resulting from this procedure were collected at 76 sites in 16 countries (Fig. 1). They belonged to 12 native or naturalized oak species (Table 1). Hereafter, we refer to the collaborators who joined the study by collecting and sending acorn batches as “participants” and to the members of the group at the University of Granada who conducted the germination tests as the “coordinating team.”

Fig. 1

Map with the sites of collection of the acorn batches and the species identified by colors. The coordinates and further characteristics are identified in the database (Map data ©2024 Google)

Table 1 Number of batches analyzed for germination in the dataset per species

2.2 Acorn collection procedure

The protocol for acorn collection required participants to identify a source population of native or naturalized, locally growing oak species. A minimum of 500 mature, healthy-looking acorns were collected from the branches preferably, including a similar number of acorns from each of at least 10 mother trees to avoid overrepresentation of individual trees in the acorn batch. Local acorn collection was not possible at some sites due to low amounts or absence of acorn crops; in these cases, the geographical origin of the acorn batch is indicated in the database. Most acorn batches were collected in 2021 and a few only in 2022. In some cases, they were collected over these two consecutive years, resulting in two batches from the same location and species but different years. The collected acorns were stored and subjected to a selection procedure (see below).

2.3 Acorn selection

The first selection was made in the field, where the acorns were inspected for signs of injury. Only mature and healthy-looking acorns (i.e., without signs of insect or fungal damage) were collected. The second selection was through the flotation method (Gribko and Jones 1995), where the collected acorns are immersed in water and the floating acorns are sorted out, as these usually contain insect larvae feeding on the cotyledons or have dried out in the field. This produced the ultimate seed batches, from which a random subset of 150 acorns was sent to the University of Granada. In some cases (5/93 batches), fewer acorns were sent due to the inability to obtain more healthy acorns.

2.4 Acorn storage and shipping

Upon collection, the selected acorns were left to dry for 24 h at laboratory temperature. Then, they were stored in zip polyethylene plastic bags with a thickness of 50 μm and refrigerated between 1 and 4 °C. The bags were provided to all participants by the coordinating team. Acorns were inspected periodically during storage for early detection of possible rottenness, in which case affected acorns were discarded. If any acorn germinated, it was kept for the field or nursery, but not for shipment. The bags were stored open and not stacked to facilitate gas exchange. As soon as possible, the acorn bags were posted to the University of Granada by express courier service. They were posted inside the aforementioned polyethylene zip bags and cushioned to avoid mechanical damage.

2.5 Acorn weighing

Upon reception at the University of Granada, the batches consisting of 150 acorns were visually inspected and refrigerated until the start of the germination testing. From each batch, 50 acorns were used to measure fresh and dry acorn weight. If fewer acorns had been sent, the germination test was prioritized. Before measuring fresh weight, the acorns were soaked in water for 24 h, externally dried with a paper towel, and weighed to obtain the fresh mass of the whole set of 50 acorns. Then, they were dried for a minimum of 3 days in a stove at 65 °C until constant weight, after which their dry weight was assessed. This allowed us to obtain, for each acorn batch, (a) the mean acorn fresh weight, (b) the mean acorn dry weight, (c) the standard deviation of acorn dry weight, and (d) the mean acorn moisture content.

2.6 Germination test

From each batch, 100 acorns were used for the germination test, for which we followed the recommendations from the International Seed Testing Association (ISTA 2010). First, the acorns were soaked in water for 48 h. Then, we covered trays (of 23.5 × 30 × 4 cm) in silica sand with an approximate depth of 2–3 cm and placed 50 acorns per sub-batch in each tray, with about 2/3 of each acorn buried sideways in the sand. The trays (hereafter referred to as sub-batches) were then placed in growth chambers at a constant temperature of 20 °C and monitored for 8 weeks (twice as long as recommended by the above-cited ISTA protocol). The sub-batches were randomly allocated to one of five growth chambers, yet the two sub-batches from each batch were always placed in different chambers. The specifications of the chambers are:

• (1) Ing. Climas, model “GROW 600/HR,” Barcelona (Spain)—two chambers (identified in the database as “SA” and “SB”);

• (2) Liebherr, model “FKS 5000” (adapted for heat), Bulle (Switzerland)—two chambers (identified as “M10” and “M11”);

• (3) Hedera helix, model “FN-70P-L-NI,” Bizkaia (Spain)—one chamber (identified as “T”).

The trays with sand and the acorns were initially soaked in water and thereafter irrigated with 250 mL of water three times per week. Every week, we registered the number of newly germinated acorns for each sub-batch and marked the corresponding acorns to avoid double-counting. An acorn was considered germinated when the radicle had emerged. If necessary, the acorns were manually rotated to check if they had germinated. Although acorns were posted prior to germination, some germinated during shipping. This was accounted for in 40 of the sub-batches (7 of which had germinated acorns, indicated in “week 0”), and in the other sub-batches, they are included in week 1.

3 Access to the data and metadata description

The database is organized at the sub-batch level. It consists of 186 rows, with two rows per acorn batch. The columns with data specific to each row, and therefore to the sub-batch, are as follows: Sub_batch_ID, Observations, Date_start, Chamber_id, and the germination data (Week_0 – W8, Total_germinated, Total_N_tested, Germination_percentage). The last 7 columns (N_weighed, Fresh_weight_g, Dry_weight_g, Mean_fresh_weight, Mean_dry_weight, SD_dry_weight, Moisture_content) are the data for the weighed acorns (i.e., a different subset from the batch than the one used for germination), so the information can only be found in the first row of each batch to avoid the repetition of data. All the remaining columns contain data collected at the level of the entire acorn batch and this information can be found in both rows, even if it is the same data, to facilitate analysis. This allows one to group numerical values based on different characteristics, such as the country of the acorns or the species.

“Sub_batch_id” and “Batch_id” identify each sub-batch and each batch, respectively. The subsequent 12 columns contain information about the batch, namely, the year of acorn collection (“Year”; either 2021 or 2022), the code of the site from which they were sent (“Site_id”; identified with a number), the specific epithet of the species involved (“Species”; genus is Quercus in all cases), the subspecies if applicable (“Subspecies”), the country where the acorns were collected (“Country”), how the acorns were obtained (“Origin”; Collected if they were collected personally by a participant following the protocol, or Obtained if they were purchased or obtained from third parties), the location of the population from which the acorns were obtained (“Collection_location”), and the coordinates of acorn collection (“Coordinate_long” and “Coordinate_lat”). In cases where the acorns were obtained from third parties (29 batches), extra information includes the reason for non-collection by the participant (“Reason_non_collection”) and the supplier of the acorns (“Supplier”). The name of the participant responsible for obtaining and posting each acorn batch is indicated in “Contact_person” and any deviation from protocol or relevant comment to the batch or sub-batch in “Observations.

The dates include that of acorn collection (“Date_collected”), shipping (“Date_shipment”), reception at the University of Granada (“Date_received”), and the beginning of the germination test (“Date_start”).

The next columns are specific to the germination test, namely: the identification of the chamber where the test was performed (“Chamber_id”; SA and SB for Ing. Climas growth chambers, M10 and M11 for Liebherr growth chambers, and T for the Hedera helix growth chamber, respectively), 9 columns indicating the number of acorns that germinated in a given week (“Week_0” to “W8,” where “Week_0” stands for those acorns germinated before starting the germination test, although this is not available for all the sub-batches), the cumulative number of acorns germinated after 8 weeks (“Total_germinated”), the number of acorns tested (“Total_N_tested”), and the percentage of germination (“Germination_percentage,” which is calculated with the previous two columns).

Finally, the weight data is only found in the first row of each batch. This includes the number of acorns weighed (“N_weighed”), the fresh weight of those acorns in g (“Fresh_weight_g”), the dry weight of the acorns in g (“Dry_weight_g”), the acorn-level mean fresh weight (“Mean_fresh_weight”), the acorn-level mean dry weight (“Mean_dry_weight”), and the standard deviation of the dry weight (“SD_dry_weight”). In addition, we calculated moisture content in “Moisture_content” according to Bonner (1981) as $((''Mean\_fresh\_weight''-''Mean\_dry\_weight'')/''Mean\_dry\_weight'')\times100$.

The database is available in csv format at Digibug digital repository (Sampere-Medina et al, 2024 ): https://doiorg.publicaciones.saludcastillayleon.es/10.30827/Digibug.87318. The associated metadata is available at https://metadataafs.nancy.inra.fr/geonetwork/srv/fre/catalog.search#/metadata/a742c6d8-bc37-4ca2-8b81-2447c5a8858d.

4 Technical validation

As described before, we tested the germination potential of each acorn batch in two sub-batches, which were placed in different growth chambers to avoid potential bias related to the choice of the chamber. When using the germination data, the chamber ID can be used to account for potential effects of the chamber. Furthermore, within each chamber, we systematically rotated the sub-batches every week, bringing each tray one level down and the trays from the bottom to the top of the chamber (there were 3–5 levels in each chamber) to avoid potential bias related to the position of the tray within the chamber.

5 Reuse potential and limits

This database can be freely downloaded and used for any purpose, citing its source.

The database focuses on the ex situ germination success of Quercus spp., comprising data from 93 batches of acorns sourced across Europe. Germination—the transition from seed to seedling—constitutes a key demographic transition in the process of regeneration and reproduction (Reyes and Casal 2006). The original purpose of the database was to compare the results of seeding in the field with the intrinsic germination capacity of acorns from the same batches and, therefore, to assess the limitation on germination imposed by environmental factors in an ongoing experiment (Leverkus et al. 2021). However, this database may also prove valuable for other studies, for instance to analyze the differences in germination potential between species (Fig. 2a) or populations and the effects of acorn weight and moisture content on germination probability. It is also possible to calculate new variables from the data, such as the mean germination time (Fig. 2b), which is calculated as ∑(germination day x number of seeds germinated on that day)/total seeds germinated (Bewley et al. 2013). Additionally, for direct-seeding operations in the field or sowing in the nursery, data on germination potential may help estimate the quantity of acorns required to obtain a certain number of seedlings. The dataset may also aid in identifying acorn origin populations with higher germination potential, thereby supporting efforts to optimize seedling production in nurseries or other controlled settings. Also, it can help to develop predictive models for seedling production, based on correlations between germination success and seed traits such as weight and moisture content. The dataset may additionally be used in future meta-analyses (e.g., Maleki et al. 2024) or integrated in plant trait databases such as TRY (Kattge et al. 2020), thereby leveraging its reuse potential in future studies in biogeography, evolutionary ecology, community ecology, applied ecology, and functional ecology (Jiménez-Alfaro et al. 2016; Saatkamp et al. 2019).

Fig. 2

a Germination rate (%) of the different oak species. The “N” corresponds to the number of sub-batches analyzed. b Correlation between mean germination time in days and the germination rate (%). The colors of the points indicate the different species, and they correspond with the colors of the map in Fig. 1. Each point is the data from one sub-batch

One limitation of our dataset is that some of the seed batches were obtained from different suppliers due to the lack of local acorns in the years of the study, and we therefore lack some information about seed collection methods. Such situations are specified in the database, including the location of collection by the suppliers. Furthermore, one of the germination chambers had a technical failure at a given point and all the acorns that were inside were lost (11 sub-batches in total); for those acorn batches, we used replacement acorns, which were fortunately available in all cases, albeit in some batches only at small numbers. The number of acorns from which we estimated acorn weight and germination is always indicated in the database. Additionally, due to the need to post the acorn batches to conduct the germination tests under the same controlled conditions, the time spans between collection and the beginning of the test varied among batches. On average, the time between the acorn collection and the start of the germination test in Granada was 65.13 (± 38.57) days. To be able to account for such variability, we provide the dates of collection, shipment, reception, and the beginning of the germination tests. Despite these drawbacks, all the germination tests were carried out in the same place under the same conditions and the identified sources of variability are indicated in the database.