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ABSTRACT: Inequality in reproductive success has important implications for ecological and evolutionary dynamics, but lifetime reproductive success is challenging to measure in long-lived species such as forest trees. While seed production is often used as a proxy for overall reproductive success, high mortality of seeds and the potential for trade-offs between seed number and quality draw this assumption into question. Parentage analyses of established seedlings can bring us one step closer to understanding the causes and consequences of variation in reproductive success. In this paper we demonstrate a new method for estimating individual seedling production and average percentage germination, using data from two mixed-species populations of red oaks (Quercus rubra, Q. velutina, Q. falcata, and Q. coccinea). We use these estimates to examine the distribution of female reproductive success and to test the relationship between seedling number and individual seed production, age, and growth rate. We show that both seed and seedling production are highly skewed, roughly conforming to zero-inflated lognormal distributions, rather than to the Poisson or negative-binomial distributions often assumed by population genetics analyses. While the number of established offspring is positively associated with mean annual seed production, a lower proportion of seeds from highly fecund individuals become seedlings. Our red oak populations also show evidence of trade-offs between growth rate and reproductive success. The high degree of inequality in seedling production shown here for red oaks, and by previous studies in other species, suggests that many trees may be more vulnerable to genetic drift than previously thought, if immigration in limited by fragmentation or other environmental changes.
Ecology 05/2012; 93(5):1082-94. · 4.85 Impact Factor
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ABSTRACT: Nut-bearing trees, including oaks (Quercus spp.), are considered to be highly dispersal limited, leading to concerns about their ability to colonize new sites or migrate in response to climate change. However, estimating seed dispersal is challenging in species that are secondarily dispersed by animals, and differences in disperser abundance or behavior could lead to large spatio-temporal variation in dispersal ability. Parentage and dispersal analyses combining genetic and ecological data provide accurate estimates of current dispersal, while spatial genetic structure (SGS) can shed light on past patterns of dispersal and establishment.
In this study, we estimate seed and pollen dispersal and parentage for two mixed-species red oak populations using a hierarchical bayesian approach. We compare these results to those of a genetic ML parentage model. We also test whether observed patterns of SGS in three size cohorts are consistent with known site history and current dispersal patterns. We find that, while pollen dispersal is extensive at both sites, the scale of seed dispersal differs substantially. Parentage results differ between models due to additional data included in bayesian model and differing genotyping error assumptions, but both indicate between-site dispersal differences. Patterns of SGS in large adults, small adults, and seedlings are consistent with known site history (farmed vs. selectively harvested), and with long-term differences in seed dispersal. This difference is consistent with predator/disperser satiation due to higher acorn production at the low-dispersal site. While this site-to-site variation results in substantial differences in asymptotic spread rates, dispersal for both sites is substantially lower than required to track latitudinal temperature shifts.
Animal-dispersed trees can exhibit considerable spatial variation in seed dispersal, although patterns may be surprisingly constant over time. However, even under favorable conditions, migration in heavy-seeded species is likely to lag contemporary climate change.
PLoS ONE 01/2012; 7(5):e36492. · 4.09 Impact Factor
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ABSTRACT: • Premise of the study: Hybridization is pervasive in many plant taxa, with consequences for species taxonomy, local adaptation, and management. Oaks (Quercus spp.) are thought to hybridize readily yet retain distinct traits, drawing into question the biological species concept for such taxa, but the true extent of gene flow is controversial. Genetic data are beginning to shed new light on this issue, but red oaks (section Lobatae), an important component of North American forests, have largely been neglected. Moreover, gene flow estimates may be sensitive to the choice of life stage, marker type, or genetic structure statistic. • Methods: We coupled genetic structure data with parentage analyses for two mixed-species stands in North Carolina. Genetic structure analyses of adults (including F(ST), R(ST), G'(ST), and structure) reflect long-term patterns of gene flow, while the percentage of seedlings with parents of two different species reflect current levels of gene flow. • Key results: Genetic structure analyses revealed low differentiation in microsatellite allele frequencies between co-occurring species, suggesting past gene flow. However, methods differed in their sensitivity to differentiation, indicating a need for caution when drawing conclusions from a single method. Parentage analyses identifed >20% of seedlings as potential hybrids. The species examined exhibit distinct morphologies, suggesting selection against intermediate phenotypes. • Conclusions: Our results suggest that hybridization between co-occurring red oaks occurs, but that selection may limit introgression, especially at functional loci. However, by providing a source of genetic variation, hybridization could influence the response of oaks and other hybridizing taxa to environmental change.
American Journal of Botany 12/2011; 99(1):92-100. · 2.66 Impact Factor
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ABSTRACT: The scale of seed and pollen movement in plants has a critical influence on population dynamics and interspecific interactions, as well as on their capacity to respond to environmental change through migration or local adaptation. However, dispersal can be challenging to quantify. Here, we present a Bayesian model that integrates genetic and ecological data to simultaneously estimate effective seed and pollen dispersal parameters and the parentage of sampled seedlings. This model is the first developed for monoecious plants that accounts for genotyping error and treats dispersal from within and beyond a plot in a fully consistent manner. The flexible Bayesian framework allows the incorporation of a variety of ecological variables, including individual variation in seed production, as well as multiple sources of uncertainty. We illustrate the method using data from a mixed population of red oak (Quercus rubra, Q. velutina, Q. falcata) in the NC piedmont. For simulated test data sets, the model successfully recovered the simulated dispersal parameters and pedigrees. Pollen dispersal in the example population was extensive, with an average father-mother distance of 178 m. Estimated seed dispersal distances at the piedmont site were substantially longer than previous estimates based on seed-trap data (average 128 m vs. 9.3 m), suggesting that, under some circumstances, oaks may be less dispersal-limited than is commonly thought, with a greater potential for range shifts in response to climate change.
Molecular Ecology 02/2011; 20(6):1248-62. · 5.52 Impact Factor
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ABSTRACT: Forests are one of Earth's critical biomes. They have been shown to respond strongly to many of the drivers that are predicted to change natural systems over this century, including climate, introduced species, and other anthropogenic influences. Predicting how different tree species might respond to this complex of forces remains a daunting challenge for forest ecologists. Yet shifts in species composition and abundance can radically influence hydrological and atmospheric systems, plant and animal ranges, and human populations, making this challenge an important one to address. Forest ecologists have gathered a great deal of data over the past decades and are now using novel quantitative and computational tools to translate those data into predictions about the fate of forests. Here, after a brief review of the threats to forests over the next century, one of the more promising approaches to making ecological predictions is described: using hierarchical Bayesian methods to model forest demography and simulating future forests from those models. This approach captures complex processes, such as seed dispersal and mortality, and incorporates uncertainty due to unknown mechanisms, data problems, and parameter uncertainty. After describing the approach, an example by simulating drought for a southeastern forest is offered. Finally, there is a discussion of how this approach and others need to be cast within a framework of prediction that strives to answer the important questions posed to environmental scientists, but does so with a respect for the challenges inherent in predicting the future of a complex biological system.
Annals of the New York Academy of Sciences 05/2009; 1162:221-36. · 3.15 Impact Factor
