Two-Sex Demography, Sexual Niche Differentiation, and the Geographic Range Limits of Texas Bluegrass (Poa arachnifera).

AbstractUnderstanding the mechanisms that generate biogeographic range limits is a long-standing goal of ecology. It is widely hypothesized that distributional limits reflect the environmental niche, but this hypothesis is complicated by the potential for intraspecific niche heterogeneity. In dioecious species, sexual niche differentiation may cause divergence between the sexes in their limits of environmental suitability. We studied range boundary formation in Texas bluegrass (Poa arachnifera), a perennial dioecious plant, testing the alternative hypotheses that range limits reflect the niche limits of females only versus the combined contributions of females and males, including their interdependence via mating. Common garden experiments across a longitudinal aridity gradient revealed female-biased flowering approaching eastern range limits, suggesting that mate limitation may constrain the species' distribution. However, a demographic model showed that declines in λ approaching range limits were driven almost entirely by female vital rates. The dominant role of females was attributable to seed viability being robust to sex ratio variation and to low sensitivity of λ to reproductive transitions. We suggest that female-dominant range limits may be common to long-lived species with polygamous mating systems and that female responses to environmental drivers may often be sufficient for predicting range shifts in response to environmental change.

Phenotypic plasticity masks range-wide genetic differentiation for vegetative but not reproductive traits in a short-lived plant.

Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait-environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.

Lagged and dormant season climate better predict plant vital rates than climate during the growing season.

Understanding the effects of climate on the vital rates (e.g., survival, development, reproduction) and dynamics of natural populations is a long-standing quest in ecology, with ever-increasing relevance in the face of climate change. However, linking climate drivers to demographic processes requires identifying the appropriate time windows during which climate influences vital rates. Researchers often do not have access to the long-term data required to test a large number of windows, and are thus forced to make a priori choices. In this study, we first synthesize the literature to assess current a priori choices employed in studies performed on 104 plant species that link climate drivers with demographic responses. Second, we use a sliding-window approach to investigate which combination of climate drivers and temporal window have the best predictive ability for vital rates of four perennial plant species that each have over a decade of demographic data (Helianthella quinquenervis, Frasera speciosa, Cylindriopuntia imbricata, and Cryptantha flava). Our literature review shows that most studies consider time windows in only the year preceding the measurement of the vital rate(s) of interest, and focus on annual or growing season temporal scales. In contrast, our sliding-window analysis shows that in only four out of 13 vital rates the selected climate drivers have time windows that align with, or are similar to, the growing season. For many vital rates, the best window lagged more than 1 year and up to 4 years before the measurement of the vital rate. Our results demonstrate that for the vital rates of these four species, climate drivers that are lagged or outside of the growing season are the norm. Our study suggests that considering climatic predictors that fall outside of the most recent growing season will improve our understanding of how climate affects population dynamics.

The myriad of complex demographic responses of terrestrial mammals to climate change and gaps of knowledge: A global analysis.

Approximately 25% of mammals are currently threatened with extinction, a risk that is amplified under climate change. Species persistence under climate change is determined by the combined effects of climatic factors on multiple demographic rates (survival, development and reproduction), and hence, population dynamics. Thus, to quantify which species and regions on Earth are most vulnerable to climate-driven extinction, a global understanding of how different demographic rates respond to climate is urgently needed. Here, we perform a systematic review of literature on demographic responses to climate, focusing on terrestrial mammals, for which extensive demographic data are available. To assess the full spectrum of responses, we synthesize information from studies that quantitatively link climate to multiple demographic rates. We find only 106 such studies, corresponding to 87 mammal species. These 87 species constitute <1% of all terrestrial mammals. Our synthesis reveals a strong mismatch between the locations of demographic studies and the regions and taxa currently recognized as most vulnerable to climate change. Surprisingly, for most mammals and regions sensitive to climate change, holistic demographic responses to climate remain unknown. At the same time, we reveal that filling this knowledge gap is critical as the effects of climate change will operate via complex demographic mechanisms: a vast majority of mammal populations display projected increases in some demographic rates but declines in others, often depending on the specific environmental context, complicating simple projections of population fates. Assessments of population viability under climate change are in critical need to gather data that account for multiple demographic responses, and coordinated actions to assess demography holistically should be prioritized for mammals and other taxa.

Can't live with them, can't live without them? Balancing mating and competition in two-sex populations.

Two-sex populations are usually studied through frequency-dependent models that describe how sex ratio affects mating, recruitment and population growth. However, in two-sex populations, mating and recruitment should also be affected by density and by its interactions with the sex ratio. Density may have positive effects on mating (Allee effects) but negative effects on other demographic processes. In this study, we quantified how positive and negative inter-sexual interactions balance in two-sex populations. Using a dioecious grass (Poa arachnifera), we established experimental field populations that varied in density and sex ratio. We then quantified mating success (seed fertilization) and non-mating demographic performance, and integrated these responses to project population-level recruitment. Female mating success was positively density-dependent, especially at female-biased sex ratios. Other demographic processes were negatively density-dependent and, in some cases, frequency-dependent. Integrating our experimental results showed that mate-finding Allee effects dominated other types of density-dependence, giving rise to recruitment that increased with increasing density and peaked at intermediate sex ratios, reflecting tension between seed initiation (greater with more females) and seed viability (greater with more males). Our results reveal, for the first time, the balance of positive and negative inter-sexual interactions in sex-structured populations. Models that account for both density- and sex ratio dependence, particularly in mating, may be necessary for understanding and predicting two-sex population dynamics.

Genetic mixture of multiple source populations accelerates invasive range expansion.

A wealth of population genetic studies have documented that many successful biological invasions stem from multiple introductions from genetically distinct source populations. Yet, mechanistic understanding of whether and how genetic mixture promotes invasiveness has lagged behind documentation that such mixture commonly occurs. We conducted a laboratory experiment to test the influence of genetic mixture on the velocity of invasive range expansion. The mechanistic basis for effects of genetic mixture could include evolutionary responses (mixed invasions may harbour greater genetic diversity and thus elevated evolutionary potential) and/or fitness advantages of between-population mating (heterosis). If driven by evolution, positive effects of source population mixture should increase through time, as selection sculpts genetic variation. If driven by heterosis, effects of mixture should peak following first reproductive contact and then dissipate. Using a laboratory model system (beetles spreading through artificial landscapes), we quantified the velocity of range expansion for invasions initiated with one, two, four or six genetic sources over six generations. Our experiment was designed to test predictions corresponding to the evolutionary and heterosis mechanisms, asking whether any effects of genetic mixture occurred in early or later generations of range expansion. We also quantified demography and dispersal for each experimental treatment, since any effects of mixture should be manifest in one or both of these traits. Over six generations, invasions with any amount of genetic mixture (two, four and six sources) spread farther than single-source invasions. Our data suggest that heterosis provided a 'catapult effect', leaving a lasting signature on range expansion even though the benefits of outcrossing were transient. Individual-level trait data indicated that genetic mixture had positive effects on local demography (reduced extinction risk and enhanced population growth) during the initial stages of invasion but no consistent effects on dispersal ability. Our work is the first to demonstrate that genetic mixture can alter the course of spatial expansion, the stage of invasion typically associated with the greatest ecological and economic impacts. We suggest that similar effects of genetic mixture may be a common feature of biological invasions in nature, but that these effects can easily go undetected.

Functional traits explain variation in plant life history strategies.

Ecologists seek general explanations for the dramatic variation in species abundances in space and time. An increasingly popular solution is to predict species distributions, dynamics, and responses to environmental change based on easily measured anatomical and morphological traits. Trait-based approaches assume that simple functional traits influence fitness and life history evolution, but rigorous tests of this assumption are lacking, because they require quantitative information about the full lifecycles of many species representing different life histories. Here, we link a global traits database with empirical matrix population models for 222 species and report strong relationships between functional traits and plant life histories. Species with large seeds, long-lived leaves, or dense wood have slow life histories, with mean fitness (i.e., population growth rates) more strongly influenced by survival than by growth or fecundity, compared with fast life history species with small seeds, short-lived leaves, or soft wood. In contrast to measures of demographic contributions to fitness based on whole lifecycles, analyses focused on raw demographic rates may underestimate the strength of association between traits and mean fitness. Our results help establish the physiological basis for plant life history evolution and show the potential for trait-based approaches in population dynamics.

Antecedent Effect Models as an Exploratory Tool to Link Climate Drivers to Herbaceous Perennial Population Dynamics Data.

Understanding mechanisms and predicting natural population responses to climate is a key goal of Ecology. However, studies explicitly linking climate to population dynamics remain limited. Antecedent effect models are a set of statistical tools that capitalize on the evidence provided by climate and population data to select time windows correlated with a response (e.g., survival, reproduction). Thus, these models can serve as both a predictive and exploratory tool. We compare the predictive performance of antecedent effect models against simpler models and showcase their exploratory analysis potential by selecting a case study with high predictive power. We fit three antecedent effect models: (1) weighted mean models (WMM), which weigh the importance of monthly anomalies based on a Gaussian curve, (2) stochastic antecedent models (SAM), which weigh the importance of monthly anomalies using a Dirichlet process, and (3) regularized regressions using the Finnish horseshoe model (FHM), which estimate a separate effect size for each monthly anomaly. We compare these approaches to a linear model using a yearly climatic predictor and a null model with no predictors. We use demographic data from 77 natural populations of 34 plant species ranging between seven and 36 years in length. We then fit models to the asymptotic population growth rate (λ) and its underlying vital rates: survival, development, and reproduction. We find that models including climate do not consistently outperform null models. We hypothesize that the effect of yearly climate is too complex, weak, and confounded by other factors to be easily predicted using monthly precipitation and temperature data. On the other hand, in our case study, antecedent effect models show biologically sensible correlations between two precipitation anomalies and multiple vital rates. We conclude that, in temporal datasets with limited sample sizes, antecedent effect models are better suited as exploratory tools for hypothesis generation.

Demographic synthesis for global tree species conservation.

Conserving the tree species of the world requires syntheses on which tree species are most vulnerable to pressing threats, such as climate change, invasive pests and pathogens, or selective logging. Here, we review the population and forest dynamics models that, when parameterized with data from population studies, forest inventories, or tree rings, have been used for identifying life-history strategies of species and threat-related changes in population demography and dynamics. The available evidence suggests that slow-growing and/or long-lived species are the most vulnerable. However, a lack of comparative, multi-species studies still challenges more precise predictions of the vulnerability of tree species to threats. Improving data coverage for mortality and recruitment, and accounting for interactions among threats, would greatly advance vulnerability assessments for conservation prioritizations of trees worldwide.

Diversity-stability relationships across organism groups and ecosystem types become decoupled across spatial scales.

The relationship between biodiversity and stability, or its inverse, temporal variability, is multidimensional and complex. Temporal variability in aggregate properties, like total biomass or abundance, is typically lower in communities with higher species diversity (i.e., the diversity-stability relationship [DSR]). At broader spatial extents, regional-scale aggregate variability is also lower with higher regional diversity (in plant systems) and with lower spatial synchrony. However, focusing exclusively on aggregate properties of communities may overlook potentially destabilizing compositional shifts. It is not yet clear how diversity is related to different components of variability across spatial scales, nor whether regional DSRs emerge across a broad range of organisms and ecosystem types. To test these questions, we compiled a large collection of long-term metacommunity data spanning a wide range of taxonomic groups (e.g., birds, fish, plants, invertebrates) and ecosystem types (e.g., deserts, forests, oceans). We applied a newly developed quantitative framework for jointly analyzing aggregate and compositional variability across scales. We quantified DSRs for composition and aggregate variability in local communities and metacommunities. At the local scale, more diverse communities were less variable, but this effect was stronger for aggregate than compositional properties. We found no stabilizing effect of γ-diversity on metacommunity variability, but ß-diversity played a strong role in reducing compositional spatial synchrony, which reduced regional variability. Spatial synchrony differed among taxa, suggesting differences in stabilization by spatial processes. However, metacommunity variability was more strongly driven by local variability than by spatial synchrony. Across a broader range of taxa, our results suggest that high γ-diversity does not consistently stabilize aggregate properties at regional scales without sufficient spatial ß-diversity to reduce spatial synchrony.

Herbaceous perennial plants with short generation time have stronger responses to climate anomalies than those with longer generation time.

There is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesize time series of structured population models from 162 populations of 62 plants, mostly herbaceous species from temperate biomes, to link plant population growth rates (λ) to precipitation and temperature drivers. We expect: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; and (2) a higher climate sensitivity in short-lived rather than long-lived species. We find that precipitation anomalies have a nearly three-fold larger effect on λ than temperature. Species with shorter generation time have much stronger absolute responses to climate anomalies. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning.