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ABSTRACT 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. 

ABSTRACT It is unclear how environmental change influences standing genetic variation in wild populations. Here, we characterised environmental conditions that protect versus erode polymorphic chemical defences inBoechera stricta(Brassicaceae), a short‐lived perennial wildflower. By manipulating drought and herbivory in a 4‐year field experiment, we measured the effects of driver variation on vital rates of genotypes varying in defence 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 defence genotypes had equivalent total fitness in many environments. Defence 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 defence chemistry inB. stricta. 

Abstract All populations are affected by multiple environmental drivers, including climatic drivers such as temperature or precipitation and biotic drivers such as herbivory or mutualisms. The relative response of a population to each driver is critical to prioritizing threat mitigation for conservation and to understanding whether climatic or biotic drivers most strongly affect fitness. However, the importance of different drivers can vary dramatically across species and across populations of the same species. Theory suggests that the response to climatic versus biotic drivers can be affected by both the species' fundamental niche breadth and the latitude of the population at which the response is measured. However, we have few tests of how these two factors affect relative response to drivers separately, let alone tests of how niche breadth and latitude together influence responses. Here, we use a meta‐analysis of published studies on population response to climatic and biotic drivers in terrestrial plants, combined with estimates of climatic niche breadth and position within climatic niche derived from herbarium records, to show that species' niche breadth is the primary determinant of response to climatic versus biotic drivers. Namely, we find that response to climatic drivers changes only minimally with increasing niche breadth, while response to biotic drivers increases with niche breadth. We see similar relationships when considering range size instead of niche breadth. Surprisingly, we find no effects of latitude on the relative effect of climatic versus biotic drivers. Our work suggests that populations of species with small and large ranges experience similar extirpation risks due to the negative impacts of climate change. By contrast, populations of species with large (but not small) ranges may be highly susceptible to changes in densities or distributions of interacting species. 

Abstract 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. We extend regression LTREs to incorporate nonlinear (second‐order) terms and compare the accuracy of both approaches for three previously published demographic datasets. We show that the second‐order approach equals or outperforms the linear approach for all three case studies, even when all of the underlying vital rate functions are linear. Nonlinear vital rate responses to driver changes contributed most to population growth rate responses, but life history changes also made substantial contributions. Our results suggest that moving from linear to second‐order LTRE analyses could improve our understanding of population responses to changing environments. 

Abstract Populations of many species are genetically adapted to local historical climate conditions. Yet most forecasts of species’ distributions under climate change have ignored local adaptation (LA), which may paint a false picture of how species will respond across their geographic ranges. We review recent studies that have incorporated intraspecific variation, a potential proxy for LA, into distribution forecasts, assess their strengths and weaknesses, and make recommendations for how to improve forecasts in the face of LA. The three methods used so far (species distribution models, response functions, and mechanistic models) reflect a trade‐off between data availability and the ability to rigorously demonstrate LA to climate. We identify key considerations for incorporating LA into distribution forecasts that are currently missing from many published studies, including testing the spatial scale and pattern of LA, the confounding effects of LA to nonclimatic or biotic drivers, and the need to incorporate empirically based dispersal or gene flow processes. We suggest approaches to better evaluate these aspects of LA and their effects on species‐level forecasts. In particular, we highlight demographic and dynamic evolutionary models as promising approaches to better integrate LA into forecasts, and emphasize the importance of independent model validation. Finally, we urge closer examination of how LA will alter the responses of central vs. marginal populations to allow stronger generalizations about changes in distribution and abundance in the face of LA. 

Abstract 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.Here, we develop a flexible approach to modelling 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 modelled 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.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 life span 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 modelled size range.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. 

Abstract Many predictions of how climate change will impact biodiversity have focused on range shifts using species‐wide climate tolerances, an approach that ignores the demographic mechanisms that enable species to attain broad geographic distributions. But these mechanisms matter, as responses to climate change could fundamentally differ depending on the contributions of life‐history plasticity vs. local adaptation to species‐wide climate tolerances. In particular, if local adaptation to climate is strong, populations across a species’ range—not only those at the trailing range edge—could decline sharply with global climate change. Indeed, faster rates of climate change in many high latitude regions could combine with local adaptation to generate sharper declines well away from trailing edges. Combining 15 years of demographic data from field populations across North America with growth chamber warming experiments, we show that growth and survival in a widespread tundra plant show compensatory responses to warming throughout the species’ latitudinal range, buffering overall performance across a range of temperatures. However, populations also differ in their temperature responses, consistent with adaptation to local climate, especially growing season temperature. In particular, warming begins to negatively impact plant growth at cooler temperatures for plants from colder, northern populations than for those from warmer, southern populations, both in the field and in growth chambers. Furthermore, the individuals and maternal families with the fastest growth also have the lowest water use efficiency at all temperatures, suggesting that a trade‐off between growth and water use efficiency could further constrain responses to forecasted warming and drying. Taken together, these results suggest that populations throughout species’ ranges could be at risk of decline with continued climate change, and that the focus on trailing edge populations risks overlooking the largest potential impacts of climate change on species’ abundance and distribution. 

All demographic rates (survival, growth, reproduction, and recruitment) were measured for two long-lived, cold-adapted, non-clonal tundra plants (Silene acaulis and Bistorta vivipara) in multiple populations from 36 degrees N latitude (Sangre de Cristo Mountains, northern New Mexico) to 69 degrees N latitude (Alaska's North Slope), every year since populations were begun in 2001, 2007, or 2008 (depending on population) until the present (2022). Soil temperature was also measured over the entire year in all populations since 2008. The purpose of the dataset was to understand how climatic variation affects demography of the two plants and how demography differs between populations near the range edge and populations closer to the range center. The demographic census is ongoing, so new data will be added as they are collected. The data files include data on individual plants across years.