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Article

Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species

by
María Trujillo-Ríos
1,
Antonio Gazol
2,
José Ignacio Seco
1 and
Juan Carlos Linares
1,*
1
Departamento de Sistemas Físicos, Químicos y Naturales, Universidad Pablo de Olavide, Crta. Utrera km. 1, 41013 Sevilla, Spain
2
Instituto Pirenaico de Ecología (IPE-CSIC), 50059 Zaragoza, Spain
*
Author to whom correspondence should be addressed.
Forests 2025, 16(2), 252; https://doi.org/10.3390/f16020252
Submission received: 22 December 2024 / Revised: 24 January 2025 / Accepted: 27 January 2025 / Published: 29 January 2025
(This article belongs to the Special Issue Production in Forest Nurseries, Field Performance of Seedlings and Natural Regeneration in the Context of Climate Change)
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Abstract

:
The intraspecific trait variations in the reproductive structures and early growth of seedlings may be critical in determining further regeneration. However, modularly built organisms, such as trees, challenge our notion of the phenotype concept, as the arrays of nonidentical homologous organs, such as seed-bearing cone scales and seeds, depending on the individual capacity to produce phenotypically variable arrangements, but they also reflect abiotic selective effects. We investigated the variability in cone scale morphology, seed traits, and germination dynamics in coexisting fir (Abies marocana) and cedar (Cedrus atlantica) trees from northern Morocco. We quantified the degree of trait overlap in two co-occurring populations of both species, as a measure of population/species functional similarity. Cone scale size and seedling growth rate were species-dependent traits, as 70%–80% of the variance was explained by the species, while only 0%–2% was explained by the population. Conversely, seed weight was a tree-dependent trait, as 70% of the variation was observed among trees, while the species only explained 20% of the variation, and the contribution of the population was negligible. Species and populations showed the same characteristics in the correlations between variables, supporting different magnitudes but a constant relationship. Substantial variations in seed weight and early seedling growth occur concurrently among cones of a single tree, independently of the tree species or population. Further studies should consider both phenotype selection and inheritance of traits’ variance on the establishment, survival, and growth of seedlings in A. marocana and C. atlantica in nurseries and reforestation sites to improve adaptive capacity to changing environmental conditions.

1. Introduction

Understanding how drought-sensitive tree species might be adapting to changing environmental conditions caused by climate change sets a significant challenge [1,2]. Despite previous attempts to predict future forest distribution, assuming that species were comprised of genetically similar populations, it is now widely recognized that within-species variability plays a fundamental role in their ability to respond to climate change [3]. Several studies indicate that populations have undergone phenotype selection in response to environmental changes, while they also pointed out that differences in phenotypic plasticity among populations are common (revised by ref. [4]). Ongoing climate change imposes strong selection pressures on traits important for fitness [5]. Such climate-mediated selection is likely a suitable mechanism for mitigating the negative consequences of globally rising temperatures and enhancing drought stress on forest trees [2].
Although the distinction between genetic (evolutionary) and phenotypic (including a non-genetic plastic component) is not always straightforward [6], the available evidence mainly points to environmentally induced plastic responses rather than genetic adaptations [7,8]. This finding enhances the interest in investigating morphological and physiological intraspecific variability in important functional traits [9,10,11]. Among these likely relevant traits able to express alternative phenotypes in response to environmental variation, the reproductive structures of tree species, such as seed variability, may determine seedling performance and further regeneration [12,13,14]. Indeed, the percentage of seeds that successfully develop into seedlings and survive over the first year may be less than 1% in drought-sensitive trees [14,15]. These high mortality rates, which far exceed those of adult tree mortality, could lead to intense selective processes in the early stages of development that influence adaptation throughout the entire life cycle of trees [16,17]. Specifically, characteristics such as larger seeds, earlier germination, and faster growth seem to be favored in drought-prone forest ecosystems [12,13,18,19].
Gymnosperm seeds are developed on integrated structures formed by multiple parts that constitute the characteristic cone of conifers (Figure 1). It is largely unknown if the phenotypic plasticity of these reproductive structures is related to the growth over the early stages of trees. Furthermore, this variability might rely on a hierarchical variance partitioning including within-individual, among–populations, or among-species differences [20,21]. Functional coordination to produce cones, disseminate seeds, and promote seedlings germination and establishment might be expected. Cones may be plastic in response to inter-annual resource availability. However, the environmental-induced modification of cone traits may imperil the correct functioning of the entire structure and diminish the fitness of the plastic phenotype. To keep its functionality, the plasticity of cones would thus require the concerted changes of all their parts and the production of a new fully integrated phenotype. This abrupt multivariate plasticity is nevertheless unlikely because the developmental requirements to produce any new complex structure constrain the ability to respond to immediate environmental changes [22,23]. Consequently, gymnosperm cones might exhibit higher developmental canalization and express plasticity less frequently than other plant traits.
Gymnosperm cones have evolved, resulting in a vast array of sizes and scale and seed morphologies, not so clearly matching environmental selective pressures. The environmental modifications of cone morphology might influence the plasticity of further key processes, such the seed germination, although this hypothesis is still unexplored. Conifer cone scales (Figure 1) have been identified as a morphological character with taxonomic significance [24], as well as to identify fossil remains [25]. Within Pinaceae, the cone scales of Cedrus (Trew) closely resemble those of Abies (Mill.) (Figure 1). Further, we hypothesize that the morphological variability in cone scales could be related to functional traits, such as germination and further seedling establishment success. Hence, by combining cone scale and seed morphology with seedling emergence, we aimed to investigate the occurrence of multivariate within-individual cone variation in Abies marocana (Trab.) and Cedrus atlantica ((Endl.) Manetti ex Carrière) populations. Specifically, we aimed to investigate if morphological traits changes between these two coexisting species and between two different populations of each, affecting seed weight, seed germination, and seedling cotyledons emergence and early growth.

2. Materials and Methods

2.1. The Female Cone of Conifers and the Cone Scale Morphology

Conifer (Fam. Pinaceae) cones are characterized by seed-bearing organs of ovoid to globular shape with individual woody plates called scales around a central axis (Figure 1a). Seed cones of Pinaceae exhibit two mechanisms of seed release. In species such as pines (genus Pinus L.), the cone scales remain attached to the central axis (rachis) while flexing and separating from each other to release the seeds (flexors cones). In the Abies and Cedrus genera, the cone scales are shed from the axis, with the seeds either remaining attached to the scale or becoming detached (shedders cones). Within Pinaceae, the cone scales of Cedrus closely resemble those of Abies (Figure 1c). The size of the cone scales presents large variation within one cone, while the biggest cone scales are in the middle part. Thus, we sampled all the cone scales from the middle part of the cones to achieve comparable measurements. Also, being the largest in size, these scales should be the most developed and, therefore, have morphological stability [25].

2.2. Study Area, Tree Species, and Field Sampling

The field sampling was carried out in the Talassemtane National Park (see ref. [26] and references therein). The Moroccan fir (Abies marocana Trab.) is endemic to the calcareous western Rif Mountains, where it grows between 1400 and 2000 m a.s.l. We investigated the two main populations of A. marocana, located in the Tazaot range (35.25 N, −5.09 W, around 1760 m a.s.l.), covering about 300 ha, mostly on northern and northeastern slopes, and the Talassemtane range (35.14 N, −5.14 W, around 1730 m a.s.l.), covering about 3760 ha, on northern, northeastern, and northwestern slopes. The Talassemtane range has been referred as hosting the subspecies Abies pinsapo marocana (Trab.) Emb. & Maire, while the Tazaot range has been referred to as hosting the subspecies Abies pinsapo tazaotana (Cózar ex Villar) Govaerts [24]. Here we are not assuming genetic differences between both Moroccan fir populations [27,28,29]. The Atlas cedar (Cedrus atlantica (Endl.) Manetti ex Carrière) is endemic to north Morocco and Algeria. In the study area, C. atlantica grows generally above 1600 m, forming mixed forests with A. marocana [26].
Soils are formed over calcareous and dolomitic substrates, mainly Cambisols (brown forest soil), Rendzic and Mollic Leptosols (dark organic matter, rich in calcium and magnesium carbonates), and Luvisols (fersiallitic reddish soils, characterized by a horizon of clay resulting from leaching). The climate is typical of Mediterranean coastal mountains, characterized by relatively mild temperatures and orographic rainfalls that largely exceed the surrounding precipitation average [26,29]. Specifically, for the study area, the mean annual temperature ranges between 12 and 14 °C, the mean of the maximum temperature of the hottest month (usually August) is about 26.5 °C, and the mean of the minimum temperature of the coldest month (usually January) is about −1.3 °C. The mean total annual precipitation is around 1400 mm, but it may exceed 2000 mm at the highest elevations (see refs. [26,29] and references therein). Rainfall accumulates mainly in late autumn and winter, while the drought season extends from late June to September. The minima temperatures in Tazaot are about 0.5 °C, which is hotter than in Talassemtane, while the maxima temperatures are about 0.5 °C milder in Tazaot than in Talassemtane, likely due to coastal buffering. Total annual precipitation is about 100 mm lower in Tazaot than in Talassemtane, likely due to a stronger orographic effect within the Talassemtane range (maximum elevation is 1829 m a.s.l. (Jbel Tazaout) in Tazaot and 2156 m a.s.l. (Jbel Lakraâ) in Talassemtane, respectively).
Microclimatic conditions were monitored for two years at the Talassemtane study site using one datalogger (HOBO sensors, Onset Co., Bourne, MA, USA). Air temperature, (T, °C), relative air humidity, (RH, %), and soil water content, (SWC, % vol), were monitored hourly. T-RH sensors were located at 1 m above the ground while four SWC probes were buried at 0.30 m. Vapor pressure deficit (VPD, kPa) was estimated using T and RH data. According to these data, the mean annual temperature was 10.8 °C, the maximum temperature of the hottest month (August) was 33.9 °C, and the minimum temperature of the coldest month (February) was −6.2 °C. SWC was about 40% from late-autumn to spring, while it decreased to less than 30% from July to September. Maximum VPD, (roughly 1.5 kPa) was recorded during July and August (Supplementary Materials, Table S1).
Mature cones were sampled in late October for both species and populations. The cones of both C. atlantica and A. marocana mature in autumn of the second year (authors’ personal observation, [26]). Mature cones were identified in the field as they shed easily from the axis. Each cone was individualized by tree in paper bags, providing disaggregated information about among-cones variability within a tree, among-trees variability within the population, between-populations variability within the species, and between-species variability. Field sampling was performed starting from a point randomly selected within each study area, then, the nearest tree with mature cones in the upper third of the crown was sampled using a telescopic pruner or climbing to the tree. Further trees were randomly selected among the suitable individuals at least 100 m apart. Tree diameter was measured at 1.3 m from the ground using a tape, while tree height was measured using a clinometer (Suunto PM-5/360 PC, Vantaa, Finland). We sampled four to six trees per species, five cones per tree, and eight to fourteen scales per cone (fifty cone scales per tree in most cases) (Table 1). Cone scales of each individual cone were shed from the cone axis by hand in the laboratory and scanned at 600 dots per inch (dpi) (Epson Scan, Lide 120, Tokyo, Japan). Quantitative morphometric measurements of the scales (Supplementary Materials, Table S2) were obtained using the software ImageJ 1.45 (Wayne Rasband and contributors, National Institutes of Health, Bethesda, MD, USA).

2.3. Seed Weight, Seed Germination, and Seedling Cotyledons Emergence and Growth

The seeds within each individual cone were separated from the cone scales by hand in the laboratory. We sampled an aliquot of ten packs containing eight seeds randomly selected from each tree to calculate the average seed fresh weight (mg) and the percentage of water content (%) by drying the seeds in an oven at 70 °C until constant weight.
Seeds were germinated in a greenhouse at the University of Pablo de Olavide (Sevilla, Spain; 37.36 N, −5.94 W). Microclimatic conditions (T, RH) were monitored hourly during the experiment using three dataloggers (HOBO sensors, Onset Co., Bourne, MA, USA) inside the greenhouse. T was between 16.5 and 18.4 °C and RH was between 61.3 and 69.4%. Photosynthetic photon flux at plant height was about 325 μmol m–2 s–1. The germination pots were PVC cylinders (0.86 L volume, 20 cm height, 7.4 cm diameter), filled with sand and perlite 1:1 as growing medium. Each pot was fertilized at the onset of the experiment with 170 mg of commercial NPK fertilizer (BASF, Ludwigshafen, Germany), including 20.4 mg of total N, 20.4 mg of P2O5, 28.9 mg of K2O, 3.4 mg of MgO, 25.5 mg of SO3, 0.034 mg of total B, and 0.017 mg of total Zn. Three seeds were planted in each pot, burying them slightly in the growing medium; the pots were randomly arranged, including seeds from both species and populations. Watering was scheduled to provide a growing medium water content of about 37% (v/v), based on a previous irrigation trial. Irrigation was applied by mist nozzles for six minutes once every hour. We used a non-limiting watering schedule because the germination period (namely May to June) in their natural area is typically mild, and the soil moisture is still non-limiting for seed germination and seedling early growth (Supplementary Materials, Table S1). Nonetheless, the temperature is much lower in the Talassemtane range compared to our greenhouse. However, given that the main limiting factor for seedling emergence should be water availability, we consider that our growing conditions are non-limiting, while initial seedlings’ growth in nature must be slower, due to less thermal energy (lower rate of growing degree days addition in natural conditions). All pots were monitored from the sowing date (February) to the end of the survey (April), three times each week for twelve weeks. Germination time was measured as the difference (days) between the sowing date and the date of seedling emergence. Cotyledons emergence time was measured as the difference (days) between the germination date and the date of full cotyledons spread. Seedling height (mm) was measured from the emergence in all the germinated seedlings using a ruler, while growth rate was estimated as seedling height divided by the time (days) since emergence. On average, germination took place roughly four weeks after the sowing date, cotyledons emergence took place roughly one week after the germination date, and growth was monitored in all the germinated seedlings for about eight weeks from the germination date (Table 1). Additionally, the percentage of germination was estimated considering the total number of sown seeds (Table 1). Significant mortality or damping off was not observed in the seedlings over the survey (Supplementary Materials, Figure S1).
The data has a fully nested structure. In the case of cone scale traits, between 4 and 6 cones were selected in the 4–6 trees chosen in each of the two populations of the two species. For each cone, between 8 and 12 cone scales were collected and measured (minimum and maximum diameter, area, and perimeter). In the case of seed weight and germination, 20 seeds were collected and measured in the 4–6 trees of each of the two populations of the two species (Table 1). The cone scale dimensions, seed characteristics, and germination rates were investigated including within-tree, among trees, between populations, and between species variability, respectively (Table 2).

2.4. Statistical Analysis and Modeling

The data analysis and modeling were focused on testing the following questions:
Q1. 
How do cone scale dimensions, seed weight, and growth rate vary between species and populations?
Q2. 
What is the relationship between cone scale dimensions and seed weight and germination? What is more important: centrality or variability?
Q3. 
How does seed weight determine further seedling development and growth rate?

2.4.1. Q1. How Do Cone Scale Dimensions, Seed Weight, and Growth Rate Vary Between Species and Populations?

To decompose the variation of cone scale dimensions, seed weight, and growth rate across levels (from species to cones), we used the method proposed by Messier et al. (2010) [30]. Since the data are represented by a fully hierarchical structure, we fitted a general linear model to the variance across four hierarchical levels, nested one into another: cone, tree, population, and species. Correlation analyses and normality tests were performed before the modeling to avoid multicollinearity and to achieve normality assumptions. In the case of growth rate, data were normalized by log10 transformations (log(x + 1)) to achieve normality assumptions. In general terms, in a nested ANOVA, the variance components represent the variances around the means. Thus, we proposed a linear mixed effect model [31] with the intercept as the only fixed effect and the fully nested structure as random effects. Models were fitted using a restricted maximum likelihood (REML) method. The nlme package [32] was used to fit the models in the lme function of R (version 2.6.1) and variance component analyses were performed on this model using the ape package [33]. All analyses were performed in the R environment [34].

2.4.2. Q2. What Is the Relationship Between Cone Scale Dimensions and Seed Weight and Germination? What Is More Important: Centrality or Variability?

We used a linear mixed effect model (lme) to test for the relationship between cone scale dimensions and seed weight and growth rate. As explained above, cone scales and seeds were collected for the same trees in each population of each species. Thus, we averaged cone scale characteristics across trees as a measure of centrality and calculated the coefficient of variation (standard deviation divided by the mean) across trees as a measure of variability. For each tree, cone scale dimensions (either centrality or variability) were related to seed weight and seedling growth rate by means of linear mixed-effect models. We aimed to test whether the mean cone scale area or its coefficient of variation influenced seed weight and seedling growth rate. Thus, separate models were created for seed weight and growth rate. As fixed effects, we included the area and coefficient of variation of the cone scale area. The random effect was constructed with a population nested in species. The growth rate was log-transformed (log(x + 1)) prior to the analyses.
Since we are interested in deciphering whether the cone scale area mean of its coefficient of variation exerts a strong influence on seed weight and seedling growth rate, we compared these models by means of Akaike’s Information Criterion (AIC) [35]. Specifically, we compared the AIC of the model with intercept only, the model with the mean, and the model with the coefficient of variation in cone scale area. We selected the model with the lowest information AIC as the most parsimonious one if the difference between that model and the intercept-only model was higher than two AIC units. Linear mixed-effect models were fitted with the lme package and model selection was performed with the MuMln package [36] in the R environment [34].

2.4.3. Q3. How Does Seed Weight Determine Seedling Development and Growth Rate?

We fitted structural equation models to study the path in which seed weight determines germination and cotyledons emergence time and thus, influences growth rate. Path analyses are powerful statistical techniques that allow direct and indirect relationships of variables to be studied based on correlation [37]. We proposed a model in which germination time depends on seed weight. Germination determines cotyledons emergence time, and both (cotyledons emergence and germination time) determine the growth rate of the seedling (Figure 2). It is generally accepted that larger seeds give rise to seedlings with better performance [12]. We hypothesize a positive relationship between seed weight and survival by assuming that larger seeds have more energy reserves to generate viable seedlings [38,39,40]. The model was fitted using a multi-model approach (e.g., Grace, 2006 [41]) to study if there is a relationship between variables across groups (i.e., species and populations). That is, the analyses test the relationships between the variables but also if they are constant, or by contrast, vary between groups.

3. Results

3.1. Cone Scales, Seed Weight, and Growth Rate

The cone scale area was selected to characterize the cone scale dimension because we found a strong correlation between this variable and the cone scale perimeter and maximum and minimum diameter (Supplementary Materials, Table S3). In the case of germination characteristics, the selected variables were the seed weight and seedling growth rate. The variability in the cone scale area was mainly due to differences between species whereas populations played a less important role (Supplementary Materials, Table S4). Higher values were found in C. atlantica than in A. marocana (Figure 3). In this respect, 83% of the variability in scale area was explained by the species and only 2% was explained by the population. The tree explained 8% of the variability, whereas the cone explained less than 1%. Similar results were obtained when the cone scale perimeter and maximum and minimum diameter were analyzed (Figure 4).
For all the measured variables of the cone scales (area, perimeter, maximum diameter, minimum diameter), it was found that the species explains the highest variance. The individual also exhibited a significant component of phenotypic plasticity for these variables, compared to the variability observed between populations or among cones, while the variance within each cone was also noticeable (Figure 4).
Regarding seed weight, the tree factor was highly significant (Supplementary Materials, Table S5), and it exhibits the highest variability. However, variability in growth rate was mainly determined by the species (Figure 5). The variability in seed weight was stronger within trees and among trees, compared to between populations (Figure 6a). The species only explained 20% of the variation, whereas the contribution of the population was irrelevant. Conversely, the tree factor accounted for about 70% of the variation.
There is also a wider range of variability in seed weight among the Moroccan fir populations, where seed weights in the Talassemtane population (AT) range from around 50 mg for the smallest seeds to 200 mg for the largest seeds, while seed weights in the Tazaot population (AZ) range from 50 mg for the smallest seeds to 250 mg for the largest seeds. Conversely, the cedars of Tazaot (CZ) show greater variability in seed weight, ranging from 50 mg to 130 mg (approximately), while the seeds of the Talassemtane cedars (CT) exhibit less variability in weight, ranging from 70 mg to 120 mg (approximately) (Figure 6b). Seed weight was markedly higher in A. marocana than in C. atlantica (Figure 6). Contrastingly, the variability in seedling growth varied considerably between species (Figure 5; Figure 7), which accounted for 72% of the variance, whereas the population (0%) and tree effect (3%) were almost irrelevant. In summary, both the variability in cone scale size and growth rate were species-dependent traits, while seed weight was a tree-dependent trait.

3.2. Cone Scale Area and Seed Weight Relationship

The model including cone scale area as a fixed effect was selected over the model including the cone scale area coefficient of variation based on AIC (AIC = 1718 and 1772, respectively). The two models were better than the intercept-only model (AIC = 1785.8). There was a positive relationship between cone scale area and seed weight (Figure 8). The effect of cone scale area on seed weight was significant (19.18 ± 2.03; t = 9.45; p < 0.05) as well as that of the coefficient of variation (−342.72 ± 84.18; t = −4.07; p <0.05). In the case of seedling growth rate, neither the cone scale area (0.01 ± 0.006; t = 1.89; p = 0.06) nor its coefficient of variation (0.32 ± 0.19; t = 1.66; p = 0.10) exerted significant influences. One could assume that, within each species, larger scales are related to seeds with greater weight (Figure 8). Overall, there is a positive relationship between cone scale area and seed weight which seems to be consistent between species and across populations.

3.3. Structural Equation Modeling of Seed Weight, Germination, and Growth

When the structural equation model was fitted, allowing the coefficients to vary between species, the proposed model did not deviate significantly from reality (χ2 = 0.48; p = 0.787; df = 2). When the regression coefficients were kept constant between species, the fit of the model was also satisfactory (χ2 = 8.13; p = 0.321; df = 7). Conversely, when the intercepts of the variables were kept constant between groups, the fit of the model failed (χ2 = 136.97; p = 0.000; df = 10). In other words, there are differences in the values of growth rate, germination, and cotyledons emergence time between populations but not in the relationship between variables. The model showed that the influence of seed weight on germination time was not significant, whereas germination time was negatively linked to cotyledons emergence time (Figure 9). Growth rate depended significantly on cotyledons emergence time and seed weight (both with a positive impact) whereas germination time had no significant impact on growth rate. The model only accounted for 3% of the variation in cotyledons emergence time and 17% of the variation in growth rate.
When the structural equation model was fitted allowing the coefficients to vary between populations (four groups), the proposed model did not deviate significantly from reality (χ2 = 4.53; p = 0.339; df = 4). When the regression coefficients were kept constant between species the fit of the model was also satisfactory (χ2 = 22.44; p = 0.263; df = 19). Conversely, when the intercepts of the variables were kept constant between groups the fit of the model failed (χ2 = 181.707; p = 0.000; df = 28). That is, the results were as observed at the species level. As observed at the species level, seed weight did not affect germination time significantly, but there was a negative significant relationship between germination and cotyledons emergence time (Figure 9). The growth rate depended positively on cotyledons emergence time with no significant impact of germination time and seed weight. The model only accounted for 2% of the variation in cotyledons emergence time and 33% of the variation in growth rate, respectively.
In the case of species (Figure 9a), there is a negative correlation between seed weight and germination time. In other words, the greater the weight of the seed, the shorter the germination time. There is also a negative correlation between germination time and cotyledons emergence time, so, faster germination was related to longer cotyledons emergence time. Seed weight and cotyledons emergence time were positively related to growth rate. Regarding the population level (Figure 9b), the correlations between variables showed a similar pattern to that of the species level.

4. Discussion

Estimating accurately the vulnerability of species to climate change requires a more detailed understanding of functional traits that make some species prone to decline under shifting climates [11]. Measurements of species’ morphological and physiological functional traits related to growth, reproduction, and survival strategies have developed rapidly in recent decades [42]. These databases have been used to identify species traits associated with recent range shifts, as well as to establish the species and areas most vulnerable to future exposure to climate change [43,44]. Comparably less focus has been on how the intraspecific variation in functional traits may be modulating individual responses to changing climate, and their consequences for populations, species, and community dynamics [11,45].
A. marocana and C. atlantica inhabit Mediterranean mountainous landscapes, where complex orography creates spatially varying selection pressure that potentially affects several traits simultaneously across different life stages [46,47]. Processes affecting organismal performance in shifting climates, such as seed weight and germination rate, should be assessed to strengthen inferences of vulnerability. Seedling morphology, growth, and phenology traits may be determined by maternal phenotypic differences [12,48], including neutral, adaptive, and/or plastic processes [46]. In the face of rapid climate dryness, drought-induced mortality of seedlings is one of the main limitations for the regeneration of several tree species [15,49,50].
It is commonly assumed that larger seeds give rise to seedlings with better performance, especially within tree species with determinate growth [51], such as cedars and firs, which are characterized by a single leaf flush. The positive relationship between seed size and survival under drought conditions has been primarily attributed to the fact that larger seeds possess greater reserves to generate seedlings with increased growth and/or deeper roots [12,38,39,40]. In general, it has been observed that heavier seeds, which contain more reserves, have a higher likelihood of achieving successful embryonic development and germination [13,51,52]. However, some studies suggest that the germination and emergence of seedlings, as well as other early-life phenotypic traits, may be also strongly influenced by the local climate [16,53,54]. Hence, multiple genetic and environmental mechanisms are likely involved in the potential effect of seed size on seedling germination and emergence success, which hinders sometimes the presence of consistent associations.
In this study, by combining morphological and seedling developmental approaches, we demonstrate the occurrence of significant intraspecific seed weight variability in A. marocana and C. atlantica that modulates subsequent germination and growth, likely related to further seedling establishment success [55,56,57]. Cone scales showed important differences between species considering all the computed dimensions. Hence, the species factor accounted for more than 60% of the variation, with very little effect of the population factor, suggesting that variability between the two populations (Talassemtane vs. Tazaot) is inconsequential, compared to the variation among trees or cones (Figure 4). Variation in growth rate seems to be also mainly explained by the species factor (Figure 5). In contrast, regarding seed weight, the species factor explained only about 20% of the variance, while the variation was mostly due to the among-trees variability (Figure 6). This result is very relevant considering that seed weight shows usually a marked influence on subsequent seedling height growth and survival [13,51].
The negative relationship obtained between seed weight and the coefficient of variation in the cone scale area suggests that more variability did not increase seed performance, that is, in populations in which the cone scale area was more variable, resulting in overall smaller seeds. As a result, centrality seems to affect performance more than variability regarding seed weight. This suggests that variability does not translate into enhanced growth rate, as only seeds originating from cones with average larger cone scale areas grow faster than seeds originating from cones with all-sized cone scales. Thus, this separates morphological variability from performance. Despite variations in magnitude (i.e., size) there were no differences in the most likely relationships obtained among the variables (Figure 9). The effect of the mean cone scale area on seed weight was not very important (explaining about 26% of the variation), while the variation in cone scale area occurs mostly at the species level.
The path models showed that the variation explained for growth rate was 16% and 33% for the species-level and population-level models, respectively (Figure 9). Interestingly, the models indicate that relationships remain constant between groups (either species-level or populations-level) but not the intercepts. This was related to the fact that there were large differences in the growth rate and cone scale characteristics between both species. However, the regression appears to have minor variations between groups. That is, the form varies but the function remains constant.
Cone scale area variability was similar between firs and cedars, while the mean size was consistently wider in cedar trees (Figure 3a). Conversely, seed weight variability was higher in the firs compared to the cedars, and larger on average (Figure 3b). No differences related to the respective populations (Talassemtane vs. Tazaot) were observed within species. Maternal plants control the amount of resources invested per seed to the extent that first-year seedling performance seems to be a maternal trait, while indirectly associated with seed size [12]. If the size that the seed attains is mainly determined genetically by the maternal plant [12,58], differences in seed mass among trees might be attributable to genetic effects [59,60]. This hypothesis was consistently supported by our results, as the tree effect accounted for the highest percentage of variance regarding seed weight (Figure 5 and Figure 6). Notwithstanding, it should be noted that the sample size (number of trees, cones, and seeds by species and population) was here too limited to generalize the results of our study, mainly as regards the inference of likely effects of genetic diversity.
However, regarding seedling growth rate, the observed pattern was the contrary, as the variability in seedlings’ growth rate was higher in the cedar, compared to the fir, and higher on average (Figure 7). Furthermore, the species effect rather than the tree effect accounted for the highest percentage of variance regarding seedling growth (Figure 5). This result might reflect that the genotype of the embryo may also influence the size that the seedling attains [58]. In addition to selection, findings reporting inheritance of trait variance highlight the interest of phenotype variability in the framework of adaptive capacity to changing environmental conditions. Further studies should investigate to what extent phenotype selection and inheritance of traits’ variance are adaptive across the measured seed and seedling traits under contrasting environments. Hence, long-term studies are required to be performed in the field, including contrasting environments and genotyped individuals, to disentangle maternal and environmental effects on the demographic and evolutionary dynamics of these relict forests.
The timing of emergence and early growth rates have far-reaching implications for seedling performance [12,13,18,19]. Our results support that early seedling growth rate proved to be related to cotyledons emergence time, suggesting that early resource acquisition by the seedling boosts further plant development, as revealed both by species-level and population-level path analyses (Figure 9). Early emergence has been related to a higher probability of survival, as well as improved growth in Pinus sylvestris L. seedlings under experimental field conditions [13]. In this study, summer water shortage was the main environmental stressor, while early emergence determined establishment success, irrespective of the intensity of drought. In drought-prone environments, such as the Mediterranean mountain forests, the advantage conferred by earlier growth might be mainly related to a faster elongation of the root system during the growing season, reaching deeper soil moisture [13,14,19]. Thus, this early root growth and cotyledons emergence may enable seedlings to increase soil water and nutrient uptake, as well as photosynthates, prior to drought, which may delay the carbohydrate depletion and hydraulic failure driving seedling mortality under drought [61]. Our results illustrate that substantial variations in seed weight and early seedling growth occur concurrently among cones of a single tree, considering different tree species and populations. Although several investigations focused on the effects of either seed size or emergence time on seedling performance, few studies have considered the relative importance of hierarchical within-tree variability. Furthermore, our results suggest a positive selection for heavier seeds, which may be particularly important under warm and dry conditions, and also for emergence time and growth rates [62].
Identifying species traits that predict vulnerability to climate change is a research priority [11]. Long-living modularly built organisms, such as trees, challenge our notion of the phenotype concept [63]. The arrays of nonidentical homologous organs, such as seeds, depend on the abiotic selective environments, but they also reflect the individual capacity to produce phenotypically variable arrangements, which are ultimately subjected to selection [59,60]. This individual variability may be reflecting genetic diversity, but also ontogenetic effects, or the inability of a genotype to produce homologous organs, such as seeds, with a constant phenotype due to developmental noise [64]. Despite firs and cedars being tree species with determinate growth, individuals express different architectures. This plasticity in the shape and position of the tree structures results from complex trade-offs between resource acquisition and constraints, including light intercept, apical growth, and, in our case, the formation of reproductive structures [65,66]. As a result, seed weight and further seedling growth rate may reflect the effect of shifting ontogenetic structures and allometry during tree ontogeny. Therefore, it is predominantly observed at the level of the within-individual tree variation, rather than across populations or species. We illustrate how trait variability within individual trees must be considered as an element of the phenotype, in addition to the trait mean. Within-trees variation in seed weight may reflect developmental instability, but it may be adaptive by yielding phenotypically diverse offspring [64,65,66]. Hence, individual differences in the within-tree seed variability might be associated with genetic characteristics, which may be key in the phenotypic selection but also may be largely influenced by environmental constraints through tree life history, or it may reflect developmental instability.

5. Conclusions

Global warming and shifting precipitation regimes have boosted interest in predicting how intraspecific variation in functional traits offers reliable responses to changing climate. Both A. marocana and C. atlantica are threatened and relict trees, with outstanding biodiversity conservation value in the context of the forests of northern Africa. Seedling performance might be one of the key components affecting the success of restoration programs of these drought-sensitive tree species. Seedling mortality in the field is mainly associated with drought, while other factors should be also considered, such as competition, herbivory, or nurse effects over diverse regeneration microsites.
We explored the use of the coefficient of variation (standard deviation divided by the mean) across trees as a measure of variability, in addition to the averaged characteristics, to explore evidence of significant selection on within-tree variability. Despite obtaining, at the species level, similar between-populations trait means and variability under a common non-limiting environment, the ability of a genotype to yield different phenotypes probably stands out when exposed to harsh environmental conditions. Thus, contrasting field conditions must entail different phenotypic selection pressures, probably enhancing the differences among individuals and populations, including genetic correlations with some fitness traits. Nevertheless, we conclude that larger seeds give rise to seedlings with better performance in A. marocana and C. atlantica.
Given that maternal plants control the amount of resources invested per seed, early seedling performance may be considered a maternal trait linked to genetic variability. As a result, seed weight and further seedling performance obtained in nurseries may be partially determined by the genetic variability of the sampled trees. Thus, considering the practical applications of this study, to yield A. marocana and C. atlantica plants in forest nurseries, the field sampling should be performed covering the entire range of the species, including elevation-, aspect- and soil-related gradients. Further, as we pointed out above, our sample size was too limited to generalize the results of this study, mainly as regards the inference of likely effects of genetic diversity. Therefore, regarding plant production and further experimental studies, the number of trees used to collect cones should be wide, as the tree effect accounted for the highest percentage of variance regarding seed weight.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/f16020252/s1, Figure S1: Germinated seedlings of Abies marocana after the growth experiment (twelve weeks) in the greenhouse of the Ecology Area at the University Pablo de Olavide; Table S1: Microclimatic conditions measured at the Talassemtane study site. Mean (T), maximum (TM), and minimum (Tm) monthly air temperature (°C). Mean monthly relative air humidity, (RH, %). Mean monthly soil water content, (SWC, vol%). Mean monthly vapor pressure deficit (VPD, kPa); Table S2: Calculation of the variables used to characterize cone scale morphology; Table S3: Correlation matrix for cone scale dimensions, seed weight, and early seedling development (germination, cotyledons emergence, and growth). See variable units and abbreviations in Table 1. Significant values, p < 0.05, are highlighted in red; Table S4: Main effects ANOVA for cone scale dimensions. See variable units and abbreviations in Table 1; Table S5: Main effects ANOVA for seed weight and early seedling development (germination, cotyledons emergence, and growth). See variable units and abbreviations in Table 1.

Author Contributions

Conceptualization, J.C.L. and A.G.; Formal analysis, M.T.-R. and J.I.S.; Funding acquisition, J.C.L. and A.G.; Investigation, J.C.L., A.G., J.I.S. and M.T.-R.; Resources, J.C.L., J.I.S. and A.G.; Writing—original draft, M.T.-R.; Writing—review and editing, M.T.-R., A.G., J.I.S. and J.C.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by Junta de Andalucía, grant number PAIDI, P18-RT-1170, and by the Spanish Ministry of Science and Innovation, grant numbers TED2021-129770B-C22, and PID2021-123675OB-C44.

Data Availability Statement

The original contributions presented in this study are included in the article and Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

The authors gratefully acknowledge J. G. P. Rodríguez-Sánchez for the technical assistance. We thank V. Lechuga for microclimatic data and field assistance. We thank the Editor, as well as three anonymous reviewers, whose comments and corrections have greatly improved the quality of this study.

Conflicts of Interest

The authors declare no conflicts of interest.

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Forests 16 00252 g001
Figure 1. (a) Anatomy of female conifer cone showing the scales and winged seeds around a central axis (rachis). (b) Cone scales from Cedrus atlantica and Abies marocana sampled trees in Talassemtane and Tazaot populations (North Morocco). Scale bar is 5 mm. Cedrus atlantica mature cones shedding (c) and seedlings (d). Abies pinsapo Boiss., maturing cones (e) and seedlings (f). Photographs and illustrations J. C. Linares.
Figure 1. (a) Anatomy of female conifer cone showing the scales and winged seeds around a central axis (rachis). (b) Cone scales from Cedrus atlantica and Abies marocana sampled trees in Talassemtane and Tazaot populations (North Morocco). Scale bar is 5 mm. Cedrus atlantica mature cones shedding (c) and seedlings (d). Abies pinsapo Boiss., maturing cones (e) and seedlings (f). Photographs and illustrations J. C. Linares.
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Figure 2. Theoretical path model to study the influence of seed weight on growth rate and how this relationship varies between species and populations. Boxes represent measured variables, and arrows (paths) represent direct positive (black) or negative (red) effects of the variables.
Figure 2. Theoretical path model to study the influence of seed weight on growth rate and how this relationship varies between species and populations. Boxes represent measured variables, and arrows (paths) represent direct positive (black) or negative (red) effects of the variables.
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Figure 3. Variation in cone scale area (a) and seed weight (b) between species (Cedrus atlantica and Abies marocana) and populations (Talassemtane and Tazaot).
Figure 3. Variation in cone scale area (a) and seed weight (b) between species (Cedrus atlantica and Abies marocana) and populations (Talassemtane and Tazaot).
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Figure 4. Decomposition of the variation in cone scale dimensions (area, perimeter, and maximum and minimum diameter) into hierarchical components.
Figure 4. Decomposition of the variation in cone scale dimensions (area, perimeter, and maximum and minimum diameter) into hierarchical components.
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Figure 5. Decomposition of the variation in seed weight (n = 420) and growth rate (n = 195) into hierarchical components.
Figure 5. Decomposition of the variation in seed weight (n = 420) and growth rate (n = 195) into hierarchical components.
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Figure 6. Decomposition of the variation in seed weight between hierarchical levels from the species to the tree scale. The proportion of variance explained for each level (a) according to linear mixed-effect model. The mean values and variability in seed weight (b) are indicated for the Moroccan fir (A-) and the Atlas cedar (C-) in Talassemtane (-T) and Tazaot (-Z) populations, respectively.
Figure 6. Decomposition of the variation in seed weight between hierarchical levels from the species to the tree scale. The proportion of variance explained for each level (a) according to linear mixed-effect model. The mean values and variability in seed weight (b) are indicated for the Moroccan fir (A-) and the Atlas cedar (C-) in Talassemtane (-T) and Tazaot (-Z) populations, respectively.
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Figure 7. Variation in seedling growth rate between species (Cedrus atlantica and Abies marocana) and populations (Talassemtane and Tazaot).
Figure 7. Variation in seedling growth rate between species (Cedrus atlantica and Abies marocana) and populations (Talassemtane and Tazaot).
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Figure 8. Linear mixed-effects model fit by maximum likelihood for the relationship between seed weight and mean cone scale area, using the species as random factor. Cedrus atlantica (orange), Abies marocana (green). The straight line represents the maximum likelihood linear regression; dotted lines represent the 95% confidence intervals. Full model R2 = 0.89.
Figure 8. Linear mixed-effects model fit by maximum likelihood for the relationship between seed weight and mean cone scale area, using the species as random factor. Cedrus atlantica (orange), Abies marocana (green). The straight line represents the maximum likelihood linear regression; dotted lines represent the 95% confidence intervals. Full model R2 = 0.89.
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Figure 9. Path coefficients according to the model proposed to explain the impact of seed weight and germination and cotyledons emergence time on growth rate for the two species (a) and four populations (b). Boxes represent measured variables and arrows (paths) represent direct positive (black) or negative (red) effects of the variables. Path coefficients, indicating the strength of the direct effect of one variable on another appear next to the arrows; * symbol indicates significant (p < 0.05) associated probability values.
Figure 9. Path coefficients according to the model proposed to explain the impact of seed weight and germination and cotyledons emergence time on growth rate for the two species (a) and four populations (b). Boxes represent measured variables and arrows (paths) represent direct positive (black) or negative (red) effects of the variables. Path coefficients, indicating the strength of the direct effect of one variable on another appear next to the arrows; * symbol indicates significant (p < 0.05) associated probability values.
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Table 1. Characteristics of trees, cones, scales per cone, seeds, and seedlings sampled in Abies marocana (A) and Cedrus atlantica (C) in Talassemtane (T) and Tazaot (Z) populations, respectively. * 10 cones were measured for the first tree only. ** 10 measures were taken in the vast majority (95 out of 105) of the cones.
Table 1. Characteristics of trees, cones, scales per cone, seeds, and seedlings sampled in Abies marocana (A) and Cedrus atlantica (C) in Talassemtane (T) and Tazaot (Z) populations, respectively. * 10 cones were measured for the first tree only. ** 10 measures were taken in the vast majority (95 out of 105) of the cones.
SpeciesCedrus atlanticaAbies marocana
PopulationCTCZATAZ
Trees4556
Mean DBH (cm)48.6750.0540.7819.69
Mean height (m)7.7510.278.326.15
Cones5 (10 *)555
Cone scales per cone10–14 ** (total 330)10–12 ** (total 328)9–11 ** (total 322)8–14 ** (total 389)
Measured seeds200200200240
Sown seeds100100100120
Seed dry weight (mg; mean ± standard error)79.42 ± 0.9266.11 ± 4.8989.40 ± 7.9780.88 ± 8.58
Germination (days since sow date)30.93 ± 14.58, n = 7326.08 ± 12.50, n = 8731.34 ± 8.82, n = 6930.23 ± 8.81, n = 82
Cotyledons emergence (days since germination date)4.13 ± 0.40, n = 715.22 ± 0.36, n = 876.05 ± 0.28, n = 656.41 ± 0.34, n = 78
Seedling height (mm) after 12 weeks (mean ± standard error)83.62 ± 4.87, n = 7189.67 ± 4.51, n = 8738.57 ± 1.30, n = 6533.33 ± 0.82, n = 78
Table 2. Variables, units, and abbreviations used for morphometric measurements of cone scales, seeds, and seedlings.
Table 2. Variables, units, and abbreviations used for morphometric measurements of cone scales, seeds, and seedlings.
Variable (Units)Abbreviation
Seed weight (mg)Sw
Germination rate (%)Ger_rat
Germination time (days)Ger_tim
Cotyledons emergence (days)Cot_tim
Seedling size (cm)Sling_siz
Growth rate (mm day−1)G_rat
Cone scale area (cm2)Scal_are
Cone scale perimeter (cm)Scal_per
Cone scale diameter_max (cm)Scal_dmax
Cone scale diameter_min (cm)Scal_dmin
Cone scale area CV (cm2)Scal_areCV
Cone scale perimeter CV (cm)Scal_perCV
Cone scale diameter_max CV (cm)Scal_dmax CV
Cone scale diameter_min CV (cm)Scal_dminCV
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MDPI and ACS Style

Trujillo-Ríos, M.; Gazol, A.; Seco, J.I.; Linares, J.C. Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species. Forests 2025, 16, 252. https://doi.org/10.3390/f16020252

AMA Style

Trujillo-Ríos M, Gazol A, Seco JI, Linares JC. Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species. Forests. 2025; 16(2):252. https://doi.org/10.3390/f16020252

Chicago/Turabian Style

Trujillo-Ríos, María, Antonio Gazol, José Ignacio Seco, and Juan Carlos Linares. 2025. "Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species" Forests 16, no. 2: 252. https://doi.org/10.3390/f16020252

APA Style

Trujillo-Ríos, M., Gazol, A., Seco, J. I., & Linares, J. C. (2025). Phenotypic Variation in Cone Scales and Seeds as Drivers of Seedling Germination Dynamics of Co-Occurring Cedar and Fir Species. Forests, 16(2), 252. https://doi.org/10.3390/f16020252

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