It is unclear how environmental change influences standing genetic variation in wild populations. Here, we characterized environmental conditions that protect vs. erode polymorphic chemical defenses in Boechera stricta (Brassicaceae), a short-lived perennial wildflower. By manipulating drought and herbivory in a four-year field experiment, we measured the effects of driver variation on vital rates of genotypes varying in defense chemistry and then assessed interacting driver effects on total fitness (estimated as each genotype’s lineage growth rate, λ) using demographic models. Drought and herbivory interacted to shape vital rates, but contrasting defense genotypes had equivalent total fitness in many environments. Defense polymorphism thus may persist under a range of conditions; however, ambient field conditions fall close to the boundary of putatively polymorphic environment space, and increasing aridity may drive populations to monomorphism. Consequently, elevated intensity and/or frequency of drought under climate change may erode genetic variation for defense chemistry in B. stricta. NOTE: A previously published version of this dataset was removed due to licensing issues. Please use the updated version now available.

Theory suggests that the drivers of demographic variation and local adaptation are shared and may feedback on one other. Despite some evidence for these links in controlled settings, the relationship between local adaptation and demography remains largely unexplored in natural conditions. Using 10 years of demographic data and two reciprocal transplant experiments, we tested predictions about the relationship between the magnitude of local adaptation and demographic variation (population growth rates and their elasticities to vital rates) across 10 populations of a well-studied annual plant. In both years, we found a strong unimodal relationship between mean home-away local adaptation and stochastic population growth rates. Other predicted links were either weakly or not supported by our data. Our results suggest that declining and rapidly growing populations exhibit reduced local adaptation, potentially due to maladaptation and relaxed selection, respectively.

Life table response experiments (LTREs) decompose differences in population growth rate between environments into separate contributions from each underlying demographic rate. However, most LTRE analyses make the unrealistic assumption that the relationships between demographic rates and environmental drivers are linear and independent, which may result in diminished accuracy when these assumptions are violated. In this study, we compare the relative efficacy of linear and second-order LTRE analyses in capturing changes in population growth rate caused by environmental driver changes. To explore this question, we analyze demographic data collected for three long-lived plant species: Ardisia escallonioides (Pascarella & Horvitz, 1998), Silene acaulis, and Bistorta vivipara (Doak & Morris, 2010). This repository includes data files containing vital rate (survival, growth, reproduction) observations or models for our three case studies, as well as an R script in which we use these demographic data to calculate linear and second-order LTRE approximations of changes in population growth rate for each system and generate the figures we present in our paper.

In cooperative breeding systems, inclusive fitness theory predicts that non-breeding helpers more closely related to the breeders should be more willing to provide costly alloparental care, and thus have more impact on breeder fitness. In the red-cockaded woodpecker (Dryobates borealis), most helpers are the breeders’ earlier offspring, but helpers do vary within groups in both relatedness to the breeders (some even being unrelated) and sex, and it can be difficult to parse their separate impacts on breeder fitness. Moreover, most support for inclusive fitness theory has been positive associations between relatedness and behavior, rather than actual fitness consequences. We used functional linear models to evaluate the per capita effects of helpers of different relatedness on eight breeder fitness components measured for up to 41 years at three sites. In support of inclusive fitness theory, helpers more related to the breeding pair made greater contributions to six fitness components. However, male helpers made equal contributions to increasing pre-fledging survival regardless of relatedness. These findings suggest that both inclusive fitness benefits and other, direct benefits may underlie helping behaviors in the red-cockaded woodpecker. Our results also demonstrate the application of an underused statistical approach to disentangle a complex ecological phenomenon.

Quantifying the empirical relationships between genetic variation and population viability is important from both basic biological and applied conservation perspectives, yet few populations have been monitored with both long-term demographic and population genetics approaches. Here, we present eight years of historical demographic data from five populations of Boechera fecunda (Brassicaceae), a rare, self-compatible perennial plant endemic to Montana, USA, and use integral projection models to estimate the stochastic population growth rate (λS) and extinction risk of each population. We combine these demographic estimates with previously published metrics of genetic variation in the same populations to test whether genetic diversity within populations is linked to demographic performance. Our results show that in this predominantly inbred species, genetics and demography are not strongly correlated, suggesting that more inbred populations are not necessarily less viable or at higher extinction risk than more genetically diverse populations. Interestingly, however, a contemporary re-census revealed that, among these populations, genetic rather than demographic parameters were better predictors of current population density, with populations harboring greater genetic diversity maintaining denser populations at present. In the absence of evidence for inbreeding depression decreasing population viability in this species, we recommend conservation of distinct, potentially locally adapted populations of B. fecunda rather than alternatives such as translocations or reintroductions.

With ongoing climate change, populations are expected to exhibit shifts in demographic performance that will alter where a species can persist. This presents unique challenges for managing plant populations and may require ongoing interventions, including in-situ management or introduction into new locations. However, few studies have examined how climate change may affect plant demographic performance for a suite of species, or how effective management actions could be in mitigating climate change effects. Over the course of two experiments spanning six years and four sites across a latitudinal gradient in the Pacific Northwest, USA, we manipulated temperature, precipitation, and disturbance intensity, and quantified effects on the demography of eight native annual prairie species. Each year we planted seeds and monitored germination, survival, and reproduction. We found that disturbance strongly influenced demographic performance and that seven of the eight species had increasingly poor performance with warmer conditions. Across species and sites, we observed 11% recruitment (the proportion of seeds planted that survived to reproduction) following high disturbance, but just 3.9% and 2.3% under intermediate and low disturbance, respectively. Moreover, mean seed production following high disturbance was often more than tenfold greater than under intermediate and low disturbance. Importantly, most species exhibited precipitous declines in their population growth rates (λ) under warmer-than-ambient experimental conditions and may require more frequent disturbance intervention to sustain populations. Aristida oligantha, a C4 grass, was the only species to have λ increase with warmer conditions. These results suggest that rising temperatures may cause many native annual plant species to decline, highlighting the urgency for adaptive management practices that facilitate their restoration or introduction to newly suitable locations. Frequent and intense disturbances are critical to reduce competitors and promote native annuals’ persistence, but even such efforts may prove futile under future climate regimes.

Spatial gradients in population growth, such as across latitudinal or elevational gradients, are often assumed to primarily be driven by variation in climate, and are frequently used to infer species’ responses to climate change. Here, we use a novel demographic, mixed model approach to dissect the contributions of climate variables vs. other latitudinal or local site effects on spatiotemporal variation in population performance in three perennial bunchgrasses. For all three species, we find that performance of local populations decreases with warmer and drier conditions, despite latitudinal trends of decreasing population growth towards the cooler and wetter northern portion of each species’ range. Thus, latitudinal gradients in performance are not predictive of either local or species-wide responses to climate. This pattern could be common, as many environmental drivers, such as habitat quality or species’ interactions, are likely to vary with latitude or elevation, and thus influence or oppose climate responses.

Predicting species’ range shifts under future climate is a central goal of conservation ecology. Studying populations within and beyond multiple species’ current ranges can help identify whether demographic responses to climate change exhibit directionality, indicative of range shifts, and whether responses are uniform across a suite of species. We quantified the demographic responses of six native perennial prairie species planted within and, for two species, beyond their northern range limits to a three-year experimental manipulation of temperature and precipitation at three sites spanning a latitudinal climate gradient in the Pacific Northwest, USA. We estimated population growth rates (λ) using integral projection models and tested for opposing responses to climate in different demographic vital rates (demographic compensation). Where species successfully established reproductive populations, warming negatively affected λ at sites within species’ current ranges. Contrarily, warming and drought positively affected λ for the two species planted beyond their northern range limits. Most species failed to establish a reproductive population at one or more sites within their current ranges, due to extremely low germination and seedling survival. We found little evidence of demographic compensation buffering populations to the climate treatments. Synthesis: These results support predictions across a suite of species that ranges will need to shift with climate change as populations within current ranges become increasingly vulnerable to decline. Species capable of dispersing beyond their leading edges may be more likely to persist, as our evidence suggests that projected changes in climate may benefit such populations. If species are unable to disperse to new habitat on their own, assisted migration may need to be considered to prevent the widespread loss of vulnerable species.

1. Structured population models are among the most widely used tools in ecology and evolution. Integral projection models (IPMs) use continuous representations of how survival, reproduction, and growth change as functions of state variables such as size, requiring fewer parameters to be estimated than projection matrix models (PPMs). Yet almost all published IPMs make an important assumption: that size-dependent growth transitions are or can be transformed to be normally distributed. In fact, many organisms exhibit highly skewed size transitions. Small individuals can grow more than they can shrink, and large individuals may often shrink more dramatically than they can grow. Yet the implications of such skew for inference from IPMs has not been explored, nor have general methods been developed to incorporate skewed size transitions into IPMs, or deal with other aspects of real growth rates, including bounds on possible growth or shrinkage. 2. Here we develop a flexible approach to modeling skewed growth data using a modified beta regression model. We propose that sizes first be converted to a (0,1) interval by estimating size-dependent minimum and maximum sizes through quantile regression. Transformed data can then be modeled using beta regression with widely available statistical tools. We demonstrate the utility of this approach using demographic data for a long-lived plant, gorgonians, and an epiphytic lichen. Specifically, we compare inferences of population parameters from discrete PPMs to those from IPMs that either assume normality or incorporate skew using beta regression or, alternatively, a skewed normal model. 3. The beta and skewed normal distributions accurately capture the mean, variance, and skew of real growth distributions. Incorporating skewed growth into IPMs decreases population growth and estimated lifespan relative to IPMs that assume normally-distributed growth, and more closely approximate the parameters of PPMs that do not assume a particular growth distribution. A bounded distribution, such as the beta, also avoids the eviction problem caused by predicting some growth outside the modeled size range. 4. Incorporating biologically relevant skew in growth data has important consequences for inference from IPMs. The approaches we outline here are flexible and easy to implement with existing statistical tools.

All demographic rates were measured for two long-lived, non-clonal tundra plants (Silene acaulis and Polygonum viviparum) in multiple populations from 36 to 69 degrees N latitude, every year since populations were begun from 1995 to 2008 (depending on population) until the present. Soil temperature was also measured over the entire year in all populations since 2008.