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Abstract PremiseUnderstanding how population dynamics vary in space and time is critical for understanding the basic life history and conservation needs of a species, especially for narrow endemic species whose populations are often in similar environments and therefore at increased risk of extinction under climate change. Here, we investigated the spatial and temporal variation in population dynamics ofRanunculus austro‐oreganus, a perennial buttercup endemic to fragmented prairie habitat in one county in southern Oregon. MethodsWe performed demographic surveys of three populations ofR. austro‐oreganusover 4 years (2015–2018). We used size‐structured population models and life table response experiments to investigate vital rates driving spatiotemporal variation in population growth. ResultsOverall,R. austro‐oreganushad positive or stable stochastic population growth rates, though individual vital rates and overall population growth varied substantially among sites and years. All populations had their greatest growth in the same year, suggesting potential synchrony associated with climate conditions. Differences in survival contributed most to spatial variation in population growth, while differences in reproduction contributed most to temporal variation in population growth. ConclusionsPopulations of this extremely narrow endemic appear stable, with positive growth during our study window. These results suggest that populations ofR. austro‐oreganusare able to persist if their habitat is not eliminated by land‐use change. Nonetheless, its narrow distribution and synchronous population dynamics suggest the need for continued monitoring, particularly with ongoing habitat loss and climate change. 

Divergent selection across the landscape can favor the evolution of local adaptation in populations experiencing contrasting conditions. Local adaptation is widely observed in a diversity of taxa, yet we have a surprisingly limited understanding of the mechanisms that give rise to it. For instance, few have experimentally confirmed the biotic and abiotic variables that promote local adaptation, and fewer yet have identified the phenotypic targets of selection that mediate local adaptation. Here, we highlight critical gaps in our understanding of the process of local adaptation and discuss insights emerging from in-depth investigations of the agents of selection that drive local adaptation, the phenotypes they target, and the genetic basis of these phenotypes. We review historical and contemporary methods for assessing local adaptation, explore whether local adaptation manifests differently across life history, and evaluate constraints on local adaptation. 

Although many species shift their phenology with climate change, species vary significantly in the direction and magnitude of these responses (i.e., phenological sensitivity). Studies increasingly detect early phenology or high phenological sensitivity to climate in non-native species, which may favor non-native species over natives in warming climates. Yet relatively few studies explicitly compare phenological responses to climate between native vs. non-native species or between non-native populations in the native vs. introduced range, limiting our ability to quantify the role of phenology in invasion success. Here, we review the empirical evidence for and against differences in phenology and phenological sensitivity to climate in both native vs. non-native species and native and introduced populations of non-native species. Contrary to common assumptions, native and non-native plant species did not consistently differ in mean phenology or phenological sensitivity. However, non-native plant species were often either just as or more sensitive, but rarely less sensitive, to climate as natives. Introduced populations of non-native plant species often show earlier reproduction than native populations of the same species, but there was mixed evidence for differences in phenological sensitivity between introduced and native plant populations. We found very few studies comparing native vs. invasive animal phenology. Future work should characterize phenological sensitivity to climate in native vs. non-native plant and animal species, in native vs. introduced populations of non-native species, and across different stages of invasion, and should carefully consider how differences in phenology might promote invasion success or disadvantage native species under climate change. 

This article is a Commentary onPatsiouet al. (2020),228: 525–540. 

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.