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Reproductive Biology |
Departamento de Biología Vegetal, Universidad Politécnica de Madrid, Ciudad Universitaria, E-28040, Madrid, Spain
Received for publication September 27, 2001. Accepted for publication February 1, 2002.
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ABSTRACT |
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 TOP ABSTRACT INTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Key Words: Antirrhinum microphyllum • breeding system • conservation • endangered species • flowering phenology • Scrophulariaceae • self-incompatibility • structural equation modeling
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INTRODUCTION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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). Many of these factors increase the vulnerability of the species by lowering reproductive success. Consequently, the study of the factors that critically affect reproductive success needs to be considered in the design of conservation strategies (Godt and Hamrick, 1995
).
Female reproductive success depends on numerous factors that control the process of flower, fruit, and seed production (Primack, 1987
). Among these factors, it has been shown that plant size (Bishop and Schemske, 1998
) and phenological traits (Sobrevila, 1988
; English-Loeb and Karban, 1992
; Gómez, 1993
; Kudo, 1993
) have a relevant effect in many plant species. Moreover, female reproductive success is also conditioned by the breeding system of the species (Byers and Meagher, 1992
; DeMauro, 1993
), which also affects the structure of genetic diversity (Loveless and Hamrick, 1984
; Hamrick and Godt, 1990
; Les, Reinartz, and Esselman, 1991
) and the fitness of individuals (Kittelson and Maron, 2000
).
Most studies of the relationships between flowering phenology, plant size, and reproductive success have analyzed the effect of each variable by correlation or multiple regression (Schmitt, 1983
; Farris and Lechowicz, 1990
; Dieringer, 1991
). However, these approaches do not take into account the simultaneous effect of all factors, or the interdependence relationships among factors, which makes it difficult to assess the main factors that determine fruit production.
Structural equation modeling (SEM) is a powerful alternative tool in exploring and contrasting complex hypotheses on causal relationships among variables using observational data (Mitchell, 1992
). It is especially useful in conservation studies of small populations for which the implementation of specific treatments may have negative effects on population viability (Albert, Escudero, and Iriondo, 2001
). The most noticeable advantages of SEM are the global perspective provided in the study of complex problems, the ability to discern the essential from the accessory, and the possibility of evaluating one's own hypotheses (Batista and Coenders, 2000
).
In this study we used SEM to assess the reproductive success of Antirrhinum microphyllum Rothm. (Scrophulariaceae), a perennial snapdragon that grows in the cracks of vertical dolomitic cliffs. The only four populations presently known (Entrepeñas, Bolarque, Buendía, and Anguix) are located in the north of Sierra de Altomira, Guadalajara, Central Spain (Fig. 1). The extent of its total known range is an area of approximately 30 km2. This species has been classified as "vulnerable" according to IUCN criteria (VV.AA., 2000
) and is protected by the regional legislation of Junta de Comunidades de Castilla—La Mancha (Anonymous, 1998
).
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This paper is part of a research project in which the genetic structure of the populations of A. microphyllum was also studied as well as the main ecological features of their habitats. The general purpose of the project was to obtain an accurate diagnosis of the status of the species through an integrated approach and to establish the main factors that determine the viability of the populations.
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MATERIALS AND METHODS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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) was used to compare the fruit set of the different pollination treatments.
Flowering phenology
The monitoring of flowering phenology was conducted in the Bolarque and Entrepeñas populations in 1997. Before anthesis, we randomly tagged 50 individuals at Bolarque and 100 individuals at Entrepeñas and measured the size of each plant. The distance to the three nearest A. microphyllum plants was also measured. On each census day, we recorded the total number of individuals in flower and the number of open flowers and fruits on each individual.
We summarized individual phenologies using the following four variables: (1) first flowering date, (2) flowering peak date, (3) flowering duration, and (4) flowering synchrony. We calculated first flowering date for each individual as the number of days between 1 January and the day that its first flower was produced. Similarly, flowering peak date was defined as the number of days between 1 January and the day that the maximum number of open flowers was reached. Flowering duration was estimated as the number of days the plant remained in bloom. Finally, for flowering synchrony, we estimated the number of days that the flowering of one individual overlapped with the flowering of the rest of the plants in the sample (Gómez, 1993
). This variable was calculated as follows:
Normality of all phenological variables was examined by Kolmogorov tests. Means between populations were compared by t tests or the Mann-Whitney test when necessary. Skewness of the curves of percentage of flowering plants and number of flowers per day was computed as g1 (Sokal and Rohlf, 1995
).
To study the effect of climatic conditions on flowering, we analyzed data of mean temperatures and rainfall at Bolarque daily from 1 January to 31 July. We also compared the mean monthly temperature and total rainfall with the mean of these variables for the period 1967–1997. An ombrothermic climatic diagram (Emberger et al., 1963
) was also made to assess the periods of water deficit.
Female reproductive success
As previously mentioned, the number of open flowers and the number of developed fruits were counted for every plant sampled on each census day. The percentage of flowers producing fruits (fruit set) was calculated for each plant as an estimator of fruiting efficiency. To estimate female reproductive success we calculated total seed production per plant by multiplying the mean number of fruits per plant by the mean number of seeds per fruit (Dafni, 1992
). The number of seeds per fruit was determined by taking a random sample of 100 fruits (1 fruit per plant) and counting the number of seeds per fruit. The fruits were collected in both populations before they were open.
Structural equation modeling analysis
The potential relationships among individual plant size, phenological traits, distance to other plants, and reproductive success were investigated using structural equation modeling. The structure of these relationships is illustrated in the path diagram of Fig. 2, in which an arrow indicates the causal effect of one variable on another. There are six dependent variables (number of flowers, first flowering date, flowering duration, flowering synchrony, fruit set, and number of fruits) and two independent variables (plant size and mean nearest-neighbor distance). The hypotheses of causal relationships between variables were formulated according to our previous experience with the species and existing literature on the reproductive biology of other species.
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; Garwood and Horvitz, 1985
; Dieringer, 1991
). Furthermore, if the onset of flowering in A. microphyllum depends on reaching a resource threshold (Lacey, 1986
), larger plants would also have an earlier flowering date and a longer flowering duration (Schmitt, 1983
). Flower production is also likely to be influenced by external environmental factors, such as temperature or moisture availability, and internal physiological factors, such as a specific balance of growth regulators. So, the sooner the appropriate external and internal conditions for flowering were reached (first flowering date), the more flowers the plant would have a chance to produce in the season.
We expected plants with a greater flower production to have a greater fruit set since they could be more attractive to pollinators. However, intensive flowering could also favor geitonogamy and reduce the rate at which flowers produce fruits if it were a self-incompatible species (Augspurger, 1980
; Klinkhamer, De Jong, and De Bruyn, 1989
; De Jong et al., 1992
; Díaz-Lifante, 1996
). In addition to number of flowers, both flowering synchrony and flowering duration would influence fruit set, because the number of days that the flowering of one individual overlaps with the flowering of the rest of the plants and the number of days that it is in bloom condition the probability of being visited by pollinators. Another factor that may affect fruit set is the mean distance to the nearest neighbors. This variable is relevant in allogamous species, especially in the case of self-incompatible plants where pollination with pollen from a different plant is needed for a successful fruit set.
Finally, we considered that the total number of fruits developed by a plant would strictly depend on the total number of flowers produced by the plant and the efficiency with which flowers are changed into fruits (fruit set).
Structural equation modeling analysis was performed with the CALIS procedure of the SAS statistical software package (SAS Institute, 1990
). The model was evaluated separately in each population. We estimated standardized partial regression coefficients (path coefficients) for each independent variable using the maximum likelihood method. Previously, we calculated variance inflation factors (VIFs) to detect if there was collinearity between predictor variables (Petraitis, Dunham, and Niewiarowski, 1996
). All VIFs were less than ten, a value suggested by Myers (1990)
as the limit to maintain a variable. We also tested variables for deviation from normality. Only flowering synchrony had a normal distribution. Flowering duration and number of flowers and fruits were log transformed (t = log(x + 1)). Since no transformations were able to normalize the distribution of plant size, first flowering date, fruit set, and mean distance to the nearest neighbors, these variables were left unaltered. A matrix of correlation coefficients between all variables included in SEM analysis is available at the American Journal of Botany's website (http://ajbsupp.botany.org/v89/torres.doc).
We did not allow estimation of the path coefficients for the effect of fruit set on fruit number but instead fixed their values to their standardized partial regression coefficients. This was necessary because fruit set was not measured independently, but calculated from number of flowers and number of fruits, and allowing these path coefficients to be freely estimated would artificially increase the model fit (Loehlin, 1987
).
We used the multisample analysis procedure to find out whether the relationships between variables in both populations could be explained by a single model. The analysis was carried out by imposing cross-group constraints on the path models, in which the path coefficients were constrained to be equal in both groups (Bishop and Schemske, 1998
). Next, a Lagrange multiplier test was used to identify the set of constraints that, simultaneously released, would result in a significantly better model (Bentler, 1989
).
The goodness of fit of the model was contrasted through three different statistics (1) 
2 goodness of fit; (2) Bentler-Bonett normed fit index (NFI) (Bentler and Bonett, 1980
); and (3) goodness of fit index (GFI) (Jöreskog and Sörbom, 1985
). The significance of individual path coefficients was assessed by a multivariate Wald test (P < 0.05).
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RESULTS |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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Climatic conditions during flowering interval
The patterns of mean daily temperature and precipitation at Bolarque during the first half of 1997 are shown in Fig. 4a and b, respectively. Spring 1997 was quite typical in terms of rainfall, with a total precipitation of 102.3 mm and 17 rainy days in April and May, at the peak of flower production. These values were similar to the average of these variables for the previous 30 yr (1967–1997: 102.8 mm and 18 d). According to the ombrothermic diagram (Fig. 4c), there was no water deficit during the flowering season.
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2 test (2 = 39.27, df = 14, P < 0.001). Similarly, the model of Bolarque had GFI and NFI values of 0.92 and 0.96, respectively, and significant differences were also detected with the 2 test (2 = 15.02, df = 15, P < 0.001). The path diagrams in Fig. 2 illustrate the direction and magnitude of direct effects for the Entrepeñas and Bolarque populations. More than 97% of the variation in the total number of fruits was explained by the model in Entrepeñas. Both number of flowers and fruit set had a significant direct effect on fruit production, with number of flowers being the variable with the greatest path coefficient. The indirect effects of plant size (0.62) and first flowering date (–0.58) were also relevant. In Bolarque, 99% of the variation in the total number of fruits was explained by the model. Number of flowers was the most important variable, followed by plant size (Table 4).
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2 value (Table 5). The populations differed primarily in the paths from fruit set and number of flowers to number of fruits and from first flowering date to flowering synchrony.
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DISCUSSION |
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TOPABSTRACTINTRODUCTIONMATERIALS AND METHODSRESULTSDISCUSSIONLITERATURE CITED |
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) and early studies showed that self-incompatibility in Antirrhinum is determined by a multiallelic S locus with gametophytic control of pollen compatibility (Gruber, 1932
; Sherman, 1939
). Self-incompatibility mechanisms have arisen in evolution as a way of promoting within-population diversity by enhancing cross-pollination events against self-pollination (Richards, 1986
). As expected in an allogamous breeding system, genetic studies performed on A. microphyllum populations through isozyme and RAPD (random amplified polymorphic DNA) markers have shown a high level of within-population genetic diversity (Torres, 1999
).
Reproductive success may be reduced in self-incompatible species with small populations (Les, Reinartz, and Esselman, 1991
; Byers and Meagher, 1992
), as self-incompatibility restricts mate availability and conditions fruit set to pollinator activity. Nevertheless, fruit set values in both Bolarque and Entrepeñas populations were very high (Table 3) and similar to those obtained in the greenhouse from hand cross-pollinations, suggesting that reproductive success of A. microphyllum is not limited by pollinator activity or by the number of self-incompatibility alleles.
Although outbreeding depression has been observed in several species where genetic differentiation between populations was significant (Fischer and Matthies, 1997
; Montalvo and Ellstrand, 2001
), it was not detected in A. microphyllum, where the experimental crossings with pollen originating from different populations did not yield a lower fruit set (Table 1).
Flowering phenology
The extended blooming period observed in A. microphyllum increases the individual's chance of having a large number of mates both as pollen donor and recipient. Furthermore, it reduces the risk of reproductive failure resulting from bad weather or lack of pollinators (Bawa, 1983
), which may be adaptive under continental Mediterranean climate conditions, with extreme temperatures and low and erratic precipitation during the reproductive season (Fig. 4). On the other hand, the flowering peak overlaps with the period of activity of Rhodanthidium sticticum, a solitary bee that is the main pollinator of A. microphyllum (Torres et al., 2001
).
The symmetric curve of plants in flower through time, along with the skewness to the right in the flower production curve, indicates that early-flowering individuals produce more flowers than late-flowering individuals. This phenological pattern has also been documented in other studies (Dieringer, 1991
), and it has been suggested that it may be an adaptive response to attract pollinators that usually visit other species (Thomson, 1980
). The only rupicolous species that flowers at the same time as A. microphyllum is Sarcocapnos enneaphylla and we occasionally observed R. sticticum collecting nectar of S. enneaphylla flowers. This flowering pattern may be partially mediated by plant size. The negative effect of plant size on first flowering date and the positive effect of plant size on number of flowers observed in both populations (Fig. 2) promote the formation of an asymmetric and positively skewed flower production curve.
Flowering synchrony values obtained in both populations mean that on an average day each plant can exchange genes with only one half of the population. According to Rathcke and Lacey (1985)
some degree of asynchronous flowering in a population has the benefit of promoting outcrossing by forcing pollinators to move between individuals. The matching degrees of synchrony within and between populations suggest that the sites have similar habitat conditions and that pollen-mediated gene flow is feasible between the populations. However, in practice, gene flow is probably very low as the existing geographic distance (15 km) is too long when compared with the average flight distance of the main pollinator.
Female reproductive success
Production of high number of seeds has also been reported in other Antirrhinum species (Juan, Pastor, and Fernández, 1996
). This strategy is especially advantageous in a rupicolous habitat, like in A. microphyllum, where ecological niche availability is limited and a great proportion of seeds do not find a suitable habitat after dispersal.
Reproductive output can decline considerably when climatic conditions are not appropriate. A large number of cloudy or rainy days during the flowering season may limit pollination since R. sticticum is not active under these climatic conditions. Nevertheless, limitations to seed production in any single year are unlikely to lead to bottlenecks in the populations, given that most individuals are long lived (80% of the individuals sampled in 1997 were still present in 1999). Moreover, the large proportion of flowering plants observed (96.7%) means that the adult stage is achieved in a short time, a feature that favors the viability of the populations. This conclusion is supported by experimental studies that have shown that seeds sown in fall produce plants that bear flowers in the following spring (M. Gris, Universidad Politécnica de Madrid, unpublished data).
Analysis of reproductive success
Both models had GFI and NFI 
0.90 indicating an excellent fit between the models and the observed data when compared to a null model that assumes independence among all variables. However, the models had significant 2 values. The rejection of the models by the 2 test should be interpreted with caution due to the lack of robustness of this test statistic to violations of its assumptions (Tanaka, 1987
; Mitchell, 1993
). This test assumes a large sample of independent observations, multinormality of all variables, and no missing or categorical data (Petraitis, Dunham, and Niewiarowski, 1996
). Since our data may violate the assumption of multivariate normality (see MATERIALS AND METHODS) and sample sizes are on the low range for the 2 test, we consider that the results obtained are due to a departure from the required assumptions. Therefore, we conclude that the models are acceptable.
Both Entrepeñas and Bolarque models have a similar general framework in which number of flowers and plant size are the main factors that affect fruit production, followed by first flowering date and fruit set (Table 4). The number of flowers and the efficiency by which flowers develop into fruits through pollination and fecundation (fruit set) are components of the reproductive process that lead to fruit production and obviously have an impact on this variable. In both populations, variation in the number of flowers had a much greater effect than variation in fruit set on final fruit production.
Positive relationships between plant size and fecundity have also been observed in many other species (Schmitt, 1983
; Farris and Lechowicz, 1990
; Dieringer, 1991
). If plant size is a measure of stored resources available for reproduction (Weiner, 1988
), large plants should produce more flowers and fruits than small plants because they have accumulated more nutrients. A similar argument can be used to explain the positive effect of plant size on flowering duration (Widén, 1991
). Finally, the negative effect of plant size on first flowering date may indicate that a critical size and a threshold of nutrients must be reached by the plant before it starts flowering. Nevertheless, plant size is only partially responsible for variation in flowering onset (R2 = 0.04–0.06). Other factors not included in the model, such as genetic differences, soil moisture, temperature and light, must play a more significant role (Jackson, 1966
; Edwards and Goldenberg, 1976
; Widén, 1991
; Tarasjev, 1997
).
The effect of first flowering date was much more relevant than the effects of flowering synchrony and flowering duration. The negative path coefficients from first flowering date to number of flowers and fruit set indicate that A. microphyllum plants that flower at the end of the season have a lower fruit production than plants that flower earlier. This effect of seasonality on flower and fruit production is consistent with other studies (Sobrevila, 1988
; Dieringer, 1991
) and can be explained by the variation of environmental factors (rainfall and temperature) through the flowering season as well as the presence of adequate pollinators. Early-flowering plants start blooming in April and May, which correspond with the months of maximum precipitation and to the peak of activity of R. sticticum. However, late-flowering plants start blooming in June, when water stress limits flower and fruit production and pollinator activity is less intense.
The models also show a positive effect of flowering synchrony on fruit set. This was expected in a strictly self-incompatible plant since under these circumstances fruit set critically depends on successful pollination between two plants that flower simultaneously. However, the effect of this factor was low because most plants had synchrony values that did not limit the availability of compatible mates.
Finally, the mean nearest neighbor distance had a significant positive effect on fruit set at Entrepeñas but not at Bolarque. Why should fruit set values improve when the mean distance to the nearest neighbors increase? A possible answer lies in the self-incompatible system and the existence of genetic neighborhoods in the spatial structure of A. microphyllum, probably as a consequence of the lack of specialized seed dispersal mechanisms and the territorial behavior of R. sticticum (Torres, 1999
). Thus, when the distance to the nearest neighbors is short, it is more likely that most pollen transport is between plants that are genetically related and share self-incompatibility alleles. Under some circumstances (e.g., low flowering synchrony or lack of genetically distinct individuals in the neighborhood), this may significantly affect fruit set. In addition to the self-incompatibility system, early postfertilization abortion due to biparental inbreeding depression could also affect fruit set. Reduction of reproductive fitness components due to inbreeding in genetically structured populations has been observed in other allogamous species (Oostermeijer, Altenburg, and Den Nijs, 1995
). The lack of a significant effect of mean nearest neighbor distance on fruit set in Bolarque may be due to the lower statistical power of the data set in Bolarque or to differences in the spatial structure of individuals between the two populations.
Differences between populations
Significant differences in flowering peak date, flowering synchrony, and fruit set were detected between populations. In Bolarque, flowering synchrony and fruit set were higher, whereas the flowering peak was later than in Entrepeñas (Table 2 and Table 3).
Although most relationships between the variables considered for the study seem to follow similar schemes in both populations, several differences between models were detected. In Entrepeñas, significant path coefficients from plant size to first flowering date, from first flowering date to flowering synchrony and to fruit set, and from mean nearest neighbor distance to fruit set were obtained (Fig. 2a), whereas these path coefficients were not significant in Bolarque (Fig. 2b). It can be argued that these differences are due to the lower statistical power of the Bolarque data set as it has fewer observations. Nevertheless, multisample analyses showed that five constrained paths produced a significant increase in the 2 when the Entrepeñas data was used in the Bolarque model. Four of these paths also produced a significant increase in the 2 when the Bolarque data was used in the Entrepeñas model (Table 5). In addition to the paths from mean nearest neighbor distance to fruit set and first flowering date to flowering synchrony already mentioned, these analyses detected significant departures between models in the paths from number of flowers and fruit set to number of fruits.
In Entrepeñas, the spatial genetic structure of the population may be indirectly affecting fruit set values through incompatibility reactions and/or inbreeding depression mechanisms. Differences in fruit set can also be consequence of a lower pollinator abundance in this population, at least at the end of flowering season. The lower effect of fruit set on the number of fruits observed in Bolarque can probably be explained by its higher and more uniform fruit set values.
Vulnerability of the species and implications for conservation and management
The viability of the studied populations of A. microphyllum is not presently limited by the flowering or fruiting process. However, this taxon is self-incompatible and depends on the availability of compatible mates for reproduction. Any incidence that drastically reduces density or size of the populations may have an important effect on reproductive success. This fact must be taken into account in conservation and management plans for the species, being especially critical in any possible future reintroduction or reinforcement scenarios. In such cases, individuals should be genetically unrelated to prevent biparental inbreeding and should be distributed at distances that guarantee interplant movements. Moreover, the perdurance of the main pollinator, Rhodanthidium sticticum, is essential for the reproductive success of A. microphyllum, and conservation strategies should include actions to protect these pollinators from human impact. Since phenological factors also play an important role as determinants of reproductive success, long-term changes in climatic conditions may indirectly influence the reproduction of this species through changes in its phenological features and those of its pollinators.
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FOOTNOTES |
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2 Author for reprint requests (iriondo{at}ccupm.upm.es
)
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LITERATURE CITED |
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Anonymous. 1998 Decreto 33/1998, 5 de mayo, por el que se crea el Catálogo Regional de Especies Amenazadas de Castilla-La Mancha. Diario Oficial de Castilla-La Mancha 22: 3391-3398
Augspurger C. K. 1980 Mass-flowering of a tropical shrub (Hybanthus prunifolius): influence on pollinator attraction and movement. Evolution 34: 475-488[CrossRef][ISI]
Batista J. M. B. Coenders 2000 Modelos de ecuaciones estructurales. La Muralla, Madrid, Spain
Bawa K. S. 1983 Patterns of flowering in tropical plants. In C. E. Jones and R. J. Little [eds.], Handbook of experimental pollination biology, 394–410. Scientific & Academic Editions, New York, New York, USA
Bentler P. M. 1989 EQS structural equations program manual. BMDP Statistical Software, Los Angeles, California, USA
Bentler P. M. D. G. Bonett 1980 Significance tests and goodness of fit in the analysis of covariance structures. Psychometrika 45: 289-308[CrossRef][ISI]
Bishop J. G. D. W. Schemske 1998 Variation in flowering phenology and its consequences for lupines colonizing Mount St. Helens. Ecology 79: 534-546[CrossRef][ISI]
Byers D. L. T. R. Meagher 1992 Mate availability in small populations of plant species with homomorphic sporophytic self-incompatibility. Heredity 68: 353-359[ISI]
Dafni A. 1992 Pollination ecology. A practical approach. Oxford University Press, New York, New York, USA
De Jong T. J. N. M. Waser M. V. Price R. M. Ring 1992 Plant size, geitonogamy and seed set in Ipomopsis aggregata. Oecologia 89: 310-315[ISI]
Demauro M. M. 1993 Relationship of breeding system to rarity in the lakeside daisy (Hymenoxys acaulis var. glabra). Conservation Biology 7: 542-550[CrossRef][ISI]
Díaz-Lifante Z. 1996 Reproductive biology of Asphodelus aestivus (Asphodelaceae). Plant Systematics and Evolution 200: 177-191[CrossRef][ISI]
Dieringer G. 1991 Variation in individual flowering time and reproductive success of Agalinis strictifolia (Scrophulariaceae). American Journal of Botany 78: 497-503[CrossRef][ISI]
Edwards K. J. R. J. B. Goldenberg 1976 A temperate effect on the expression of genotypic differences in flowering induction in Antirrhinum majus. Annals of Botany 40: 1277-1283
Emberger C. H. Gaussen M. Kassas A. Dephilippis 1963 Bioclimatic map of the Mediterranean Zone, explanatory notes. UNESCO-FAO, Paris, France
English-Loeb G. M. R. Karban 1992 Consequences of variation in flowering phenology for seed head herbivory and reproductive success in Erigeron glaucus (Compositae). Oecologia 89: 588-595[ISI]
Farris M. A. M. J. Lechowicz 1990 Functional interactions among traits that determine reproductive success in a native annual plant. Ecology 71: 548-557[CrossRef][ISI]
Fischer M. D. Matthies 1997 Mating structure and inbreeding and outbreeding depression in the rare plant Gentianella germanica (Gentianaceae). American Journal of Botany 84: 1685-1692[Abstract]
Garwood N. C. C. C. Horvitz 1985 Factors limiting fruit and seed production of a temperate shrub, Staphylea trifolia L. (Staphyleaceae). American Journal of Botany 72: 453-466[CrossRef][ISI]
Godt M. J. W. J. L. Hamrick 1995 The mating system of Liatris helleri (Asteraceae), a threatened plant species. Heredity 75: 398-404[ISI]
Gómez J. M. 1993 Phenotypic selection on flowering synchrony in a high mountain plant, Hormathophylla spinosa (Cruciferae). Journal of Ecology 81: 605-613[CrossRef]
Gruber F. 1932 Über die Verträglichkeitsverhältnisse bei einigen selbststerilen wildsippen von Antirrhinum und über eine selbstfertile mutante. Zeitschrift fuer Induktive Abstammungsund Vererbungslehre 62: 426-462
Hamrick J. L. M. J. W. Godt 1990 Allozyme diversity in plant species. In A. H. D. Brown, M. T. Clegg, A. L. Kahler, and B. S. Weir [eds.], Plant population genetics, breeding and genetic resources, 43–63. Sinauer, Sunderland, Massachusetts, USA
Jackson M. T. 1966 Effects of microclimate on spring flowering phenology. Ecology 47: 407-415[CrossRef][ISI]
Jöreskog K. G. D. Sörbom 1985 LISREL VI: analysis of linear structural relationship by maximum likelihood, instrumental variables, and least squares. University of Uppsala, Uppsala, Sweden
Juan R. J. Pastor I. Fernández 1996 Estudio de microcaracteres en frutos y semillas de Antirrhinum L. (Scrophulariaceae). Acta Botanica Gallica 143: 181-190[ISI]
Kittelson P. M. J. L. Maron 2000 Outcrossing rate and inbreeding depression in the perennial yellow bush lupine, Lupinus arboreus (Fabaceae). American Journal of Botany 87: 652-660
Klinkhamer P. G. L. T. J. De Jong G.-J. De Bruyn 1989 Plant size and pollinator visitation in Cynoglossum officinale. OIKOS 54: 201-204
Kudo G. 1993 Relationship between flowering time and fruit set of the entomophilous alpine shrub, Rhododendron aureum (Ericaceae), inhabiting snow patches. American Journal of Botany 80: 1300-1304[CrossRef][ISI]
Lacey E. P. 1986 Onset of reproduction in plants: size-versus age-dependency. Trends in Ecology and Evolution 1: 72-76
Les D. H. J. A. Reinartz E. J. Esselman 1991 Genetic consequences of rarity in Aster furcatus (Asteraceae), a threatened, self-incompatible plant. Evolution 45: 1641-1650[CrossRef][ISI]
Loehlin J. 1987 Latent variable models. Lawrence Erlbaum, Mahwah, New Jersey, USA
Loveless M. D. J. L. Hamrick 1984 Ecological determinants of genetic structure in plant populations. Annual Review of Ecology and Systematics 15: 65-95
Mitchell R. J. 1992 Testing evolutionary and ecological hypotheses using path analysis and structural equation modelling. Functional Ecology 6: 123-129
Mitchell R. J. 1993 Path analysis: pollination. In S. M. Scheiner, and J. Gurevitch [eds.], Design and analysis of ecological experiments, 211–231. Chapman & Hall, New York, New York, USA
Montalvo A. M. N. C. Ellstrand 2001 Nonlocal transplantation and outbreeding depression in the subshrub Lotus scoparius (Fabaceae). American Journal of Botany 88: 258-269
Myers R. H. 1990 Classical and modern regression with applications. PWS Kent, Boston, Massachusetts, USA
Oostermeijer J. G. B. R. G. M. Altenburg H. C. M. Den Nijs 1995 Effects of outcrossing distance and selfing on fitness components in the rare Gentiana pneumonanthe (Gentianaceae). Acta Botanica Neerlandica 44: 257-268
Petraitis P. S. A. E. Dunham P. H. Niewiarowski 1996 Inferring multiple causality: the limitations of path analysis. Functional Ecology 10: 421-431[CrossRef][ISI]
Primack R. B. 1987 Relationships among flowers, fruits, and seeds. Annual Review of Ecology and Systematics 18: 409-430
Rathcke B. E. P. Lacey 1985 Phenological patterns of terrestrial plants. Annual Review of Ecology and Systematics 16: 179-214[CrossRef][ISI]
Richards A. J. 1986 Plant breeding system. Unwin Hyman, London, UK
SAS Institute. 1990 SAS/STAT user's guide. Release 6.04. SAS Institute, Cary, North Carolina, USA
Schemske D. W. B. C. Husband M. H. Ruckelshaus C. Goodwillie I. M. Parker J. G. Bishop 1994 Evaluating approaches to the conservation of rare and endangered plants. Ecology 75: 584-606[CrossRef][ISI]
Schmitt J. 1983 Individual flowering phenology, plant size, and reproductive success in Linanthus androsaceus, a California annual. Oecologia 59: 135-140
Sherman M. 1939 The inheritance of self-sterility in certain species of Antirrhinum. Zeitschrift fuer Induktive Abstammungsund Vererbungslehre 77: 1-17[CrossRef]
Sobrevila C. 1988 Effects of distance between pollen donor and pollen recipient on fitness components in Espeletia schultzii. American Journal of Botany 75: 701-724[CrossRef][ISI]
Sokal R. R. F. J. Rohlf 1995 Biometry: the principles and practice of statistics in biological research. W.H. Freeman, New York, New York, USA
Tanaka J. S. 1987 "How big is big enough?": sample size and goodness of fit in structural equation models with latent variables. Child Development 58: 134-146[CrossRef][ISI]
Tarasjev A. 1997 Flowering phenology in natural populations of Iris pumila. Ecography 20: 48-54[CrossRef][ISI]
Thomson J. D. 1980 Skewed flowering distributions and pollinator attraction. Ecology 61: 572-579[CrossRef][ISI]
Torres M. E. 1999 Estudio de la ecología, biología reproductiva y diversidad genética de Antirrhinum microphyllum. Evaluación del estado actual de conservación. Ph.D. dissertation, Escuela Técnica Superior de Ingenieros Agrónomos, Universidad Politécnica de Madrid, Madrid, Spain
Torres M. E. C. Ruiz J. M. Iriondo C. Pérez 2001 Pollination ecology of Antirrhinum microphyllum Rothm. (Scrophulariaceae). Bocconea 13: 543-547
VV.AA. 2000 Lista roja de flora vascular española (valoración según las categorías UICN). Conservación Vegetal 6: 11-38
Weiner J. 1988 The influence of competition on plant reproduction. In J. L. Doust and L. L. Doust [eds.], Plant reproductive ecology: patterns and strategies, 228–245. Oxford University Press, New York, New York, USA
Widén B. 1991 Environmental and genetic influences on phenology and plant size in a perennial herb, Senecio integrifolius. Canadian Journal of Botany 69: 209-217
Xue Y. R. Carpenter H. G. Dickinson E. S. Coen 1996 Origin of allelic diversity in Antirrhinum S Locus RNases. Plant Cell 8: 805-814[Abstract]
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Bolarque represents the model constrained by Bolarque path coefficients fitted to Entrepeñas plant data. Bolarque