Emily V. Moran

High‐dimensional coexistence based on individual variation: a synthesis of evidence

High biodiversity of forests is not predicted by traditional models, and evidence for trade-offs those models require is limited. High-dimensional regulation (e.g., N factors to regulate N species) has long been recognized as a possible alternative explanation, but it has not be been seriously pursued, because only a few limiting resources are evident for trees, and analysis of multiple interactions is challenging. We develop a hierarchical model that allows us to synthesize data from long-term, experimental, data sets with processes that control growth, maturation, fecundity, and survival. We allow for uncertainty at all stages and variation among 26 000 individuals and over time, including 268 000 tree years, for dozens of tree species. We estimate population-level parameters that apply at the species level and the interactions among latent states, i.e., the demographic rates for each individual, every year. The former show that the traditional trade-offs used to explain diversity are not present. Demographic rates overlap among species, and they do not show trends consistent with maintenance of diversity by simple mechanisms (negative correlations and limiting similarity). However, estimates of latent states at the level of individuals and years demonstrate that species partition environmental variation. Correlations between responses to variation in time are high for individuals of the same species, but not for individuals of different species. We demonstrate that these relationships are pervasive, providing strong evidence that high- dimensional regulation is critical for biodiversity regulation.

Individual‐scale variation, species‐scale differences: inference needed to understand diversity

As ecological data are usually analysed at a scale different from the one at which the process of interest operates, interpretations can be confusing and controversial. For example, hypothesised differences between species do not operate at the species level, but concern individuals responding to environmental variation, including competition with neighbours. Aggregated data from many individuals subject to spatio-temporal variation are used to produce species-level averages, which marginalise away the relevant (process-level) scale. Paradoxically, the higher the dimensionality, the more ways there are to differ, yet the more species appear the same. The aggregate becomes increasingly irrelevant and misleading. Standard analyses can make species look the same, reverse species rankings along niche axes, make the surprising prediction that a species decreases in abundance when a competitor is removed from a model, or simply preclude parameter estimation. Aggregation explains why niche differences hidden at the species level become apparent upon disaggregation to the individual level, why models suggest that individual-level variation has a minor impact on diversity when disaggregation shows it to be important, and why literature-based synthesis can be unfruitful. We show how to identify when aggregation is the problem, where it has caused controversy, and propose three ways to address it.

Estimating seed and pollen movement in a monoecious plant: a hierarchical Bayesian approach integrating genetic and ecological data

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.

Intraspecific trait variation across scales: implications for understanding global change responses

Recognition of the importance of intraspecific variation in ecological processes has been growing, but empirical studies and models of global change have only begun to address this issue in detail. This review discusses sources and patterns of intraspecific trait variation and their consequences for understanding how ecological processes and patterns will respond to global change. We examine how current ecological models and theories incorporate intraspecific variation, review existing data sources that could help parameterize models that account for intraspecific variation in global change predictions, and discuss new data that may be needed. We provide guidelines on when it is most important to consider intraspecific variation, such as when trait variation is heritable or when nonlinear relationships are involved. We also highlight benefits and limitations of different model types and argue that many common modeling approaches such as matrix population models or global dynamic vegetation models can allow a stronger consideration of intraspecific trait variation if the necessary data are available. We recommend that existing data need to be made more accessible, though in some cases, new experiments are needed to disentangle causes of variation.

Between-Site Differences in the Scale of Dispersal and Gene Flow in Red Oak

Background 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. Methodology and Principal Findings 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. Conclusions 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.

A predictive framework to understand forest responses to global change.

Forests are one of Earths 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.

Causes and consequences of unequal seedling production in forest trees: a case study in red oaks

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.

Simulating the Interacting Effects of Intraspecific Variation, Disturbance, and Competition on Climate-Driven Range Shifts in Trees

Climate change is expected to favor shifts in plant distributions; some such shifts are already being observed along elevation gradients. However, the rate of such shifts may be limited by their ability to reach newly suitable areas and by competition from resident species. The degree of local adaptation and genetic variation may also play a role in the interaction between migrants and residents by affecting relative fitness. We used a simulation model to explore the interacting effects of dispersal, fecundity, disturbance, and genetic variation on range-edge dynamics between a pair of demographically similar tree species. Ideal climate for an individual is determined by genotype. The simulated landscape undergoes an 80-year period of climate change in which climate bands shift upslope; subsequently, climate is held constant for 300 years. The presence of a high-elevation competitor caused a significant lag in the range shift of the low-elevation species relative to competition-free scenarios. Increases in fecundity and dispersal distance both helped to speed up the replacement of the high-elevation species by the low-elevation species at their range boundary. While some disturbance scenarios facilitated this transition, frequent canopy disturbance inhibited colonization by removing reproductive adults and led to range contractions in both species. Differences between dispersal scenarios were more pronounced when disturbance was frequent (15 vs. 25 year return interval) and dispersal was limited. When the high-elevation species lacked genetic variation, its range was more-easily invaded by the low-elevation species, while a similar lack of variation in the low-elevation species inhibited colonization—but only when this lack of variation decreased the fitness of the affected species near the range boundary. Our model results support the importance of measuring and including dispersal/fecundity, disturbance type and frequency, and genetic variation when assessing the potential for range shifts and species vulnerability to climate change.

A Revision of Erato (Compositae: Liabeae)

Erato DC. contains five species, distributed from Costa Rica to Bolivia, with its main center of diversity in Ecuador. The revision includes a new species endemic to Costa Rica and Panama, Erato costaricensis E. Moran & V. A. Funk. Morphological and molecular data support Erato as a monophyletic group, sister to Philoglossa. The phylogenetic analysis based on morphology used Munnozia Ruiz & Pavon, Chrysactinium (H.B.K.) Wedd., and Philoglossa DC. as outgroups. The phylogeny supports the monophyly of Erato, but the relationships among the species within Erato have only weak support. The genus is believed to be a recent radiation because of the morphological similarity among the taxa and their location in some of the youngest areas of the Andes.

Population genetics and adaptation to climate along elevation gradients in invasive Solidago canadensis

Gene flow between populations may either support local adaptation by supplying genetic variation on which selection may act, or counteract it if maladapted alleles arrive faster than can be purged by selection. Although both such effects have been documented within plant species’ native ranges, how the balance of these forces influences local adaptation in invasive plant populations is less clear, in part because introduced species often have lower genetic variation initially but also tend to have good dispersal abilities. To evaluate the extent of gene flow and adaptation to local climate in invasive populations of Solidago canadensis, and the implications of this for range expansion, we compared population differentiation at microsatellite and chloroplast loci for populations across Switzerland and assessed the effect of environmental transfer distance using common gardens. We found that while patterns of differentiation at neutral genetic markers suggested that populations are connected through extensive pollen and seed movement, common-garden plants nonetheless exhibited modest adaptation to local climate conditions. Growth rate and flower production declined with climatic distance from a plants home site, with clones from colder home sites performing better at or above the range limit. Such adaptation in invasive species is likely to promote further spread, particularly under climate change, as the genotypes positioned near the range edge may be best able to take advantage of lengthening growing seasons to expand the range.