Ecological Monographs

1Climate change is expected to bring about changes in precipitation and temperature regimes that, together with rising atmospheric CO2 concentrations, will likely reorganise the functional trait composition of ecosystems. Predicting plant trait responses to emerging environmental conditions including, in particular, water availability, is a tremendous challenge, but is one that eco-evolutionary optimality theory (EEO) can help us undertake. However, most EEO approaches are based on the hypothesis that traits are selected to maximise carbon assimilation which omits the important role that size growth plays in determining fitness outcomes. Using a height-growth based EEO framework, we predict magnitude and directional shifts in four key traits: leaf mass per area, sapwood area to leaf area ratio (Huber value), wood density and sapwood-specific conductivity in response to variation in soil moisture availability, atmospheric aridity, CO2 and light availability. Consistent with empirical patterns, we predict that trait optima shift from resource-acquisitive strategies characterised by low tissue constructions costs and high rates of tissue turnover and sapwood conductivity to resource-conservative strategies - characterised by low rates of tissue turnover and greater xylem embolism resistance - as conditions become increasingly dry. The EEO model that we use here highlights the important role that both carbon assimilation and tissue construction costs jointly play in predicting the response of trait optima to the environment, laying the groundwork for future height-growth based EEO models aiming to predict shifts in the functional composition of ecosystems in response to global change.

Environmental stochasticity is a key determinant of population viability. Decades of work exploring how environmental stochasticity influences population dynamics have highlighted the ability of some natural populations to limit the negative effects of environmental stochasticity, one of these strategies being demographic buffering. Whilst various methods exist to quantify demographic buffering, we still do not know which environment factors and demographic characteristics are most responsible for the demographic buffering observed in natural populations. Here, we introduce a framework to quantify the relative effects of three key drivers of demographic buffering: environment components (e.g., temporal autocorrelation and variance), population structure, and demographic rates (e.g., progression and fertility). Using Integral Projection Models, we explore how these drivers impact the demographic buffering abilities of three plant species with different life histories and demonstrate how our approach successfully characterises a populations capacity to demographically buffer against environmental stochasticity in a changing world.

Plants differ from one another in size, architecture, water relations, and resource uptake, and these differences often lead to differences in performance. Yet within a community species that differ markedly in these traits often have similar performance. Here we use a simple model to show that when the major axes of trait covariation do not align with the axis of performance variation, large differences among species in structural traits may have similar performance, i.e., alternative designs. We further illustrate this phenomenon using trait and performance data from co-occurring Protea species in the Cape Floristic Region, South Africa. Long-term coexistence of species within a community requires both similar levels of performance, so that some species are not excluded by competition, and niche differentiation, so that multiple species can coexist. Thus, misalignment between the axis of performance variation and the major axes of trait variation may be common, just as genetic variation may be maintained within a population when the selection gradient does not align with the major axes of the genetic variance-covariance matrix.

O_LIA central question in biodiversity conservation is whether species will maintain viable population dynamics under future climate change. Assessing species extinction risk under climate warming requires demographic studies integrating vital rate responses to long-term warming throughout species life cycle. However, studies of this nature are rare. C_LIO_LIHere, we examine the demographic responses of two co-occurring herbaceous plants, Elymus nutans Griseb. and Helictotrichon tibeticum (Roshev.) Holub, after a decade (2011-2020) of in situ active warming by 2{degrees}C in the grasslands of the Tibetan Plateau. We parameterise Integral Projection Models (IPMs) to project the population dynamics under ambient and long-term warming conditions, and examine the key vital rates responsible for any potential differences in population growth rates. C_LIO_LIWarming has contrasting effects on the two functionally similar co-occurring species: warming promotes the population growth rate of H. tibeticum, but intensifies the population decline of E. nutans. Our elasticity analyses show that survival is the most important vital rate for population viability in both species under both ambient and warmed conditions. Furthermore, our retrospective Life Table Response Experiment (LTRE) analysis reveals that the contrasting fates of the two species under warming mainly arise from the different responses of adult survival, which is significantly promoted in H. tibeticum but slightly reduced in E. nutans. Individual shrinkage occurred 1.6-fold more frequently under warming than ambient conditions for both species, and made considerable negative contributions to their population growth rates in warmed plots. However, such negative effects are offset in H. tibeticum (but not E. nutans) by the positive contribution to population growth rate of the associated increased survival. C_LIO_LISynthesis. Our study illustrates that the responses to climate warming may vary considerably between similar co-occurring species, and species with a demographically compensatory strategy may avoid population collapse. Additionally, caution is needed when generalizing findings among functionally similar species, and that conservation measures should be tailored at the species level. C_LI

Lagging adaptation to historical climates places trees at risk of future population declines, increasing vulnerability as temperatures rise. We used a range-wide provenance experiment of valley oaks (Quercus lobata) to test whether tree performance reflects adaptational lag, whether its magnitude increases or declines with age or interannual climate variation, and whether phenotype-informed assisted gene flow can mitigate future maladaptation. Modeling growth and survival across climatic gradients revealed that 12-year-old trees are best adapted to temperatures cooler than their source locations and often cooler than the coldest climates currently occupied by the species. This pattern of adaptational lag was strongest in hotter years, indicating that climatic variability exacerbates maladaptation. Despite this pattern, planting high-performing individuals from multiple climatic origins was predicted to improve future population performance. Our results demonstrate persistent, climate-dependent adaptational lag in a widespread foundation tree species and highlight the potential for phenotype-informed assisted gene flow to mitigate maladaptation.

Until recently, natural selection was assumed to reduce temporal fluctuation in vital rates due to its negative effects on population dynamics - the so-called Demographic Buffering Hypothesis (DBH). After several failures to support the DBH in the two decades since it was first posited, an alternative hypothesis was suggested; the Demographic Lability Hypothesis (DLH), where population vital rates should track rather than buffer the environmental conditions. Despite the huge contribution of both hypotheses to comprehend the demographic strategies to cope the environmental stochasticity, it remains unclear if they represent two competing patterns or the extreme ends of a continuum encompassing all demographic strategies. To solve this historical debate, we unify several methods with an integrative theoretical approach where: i) using the sum of stochastic elasticity with respect to mean and variance - a first-order derivative approach - we rank species on a Buffering-Lability (DB-DL) continuum and ii) using the second-order derivative, we examine how vital rates are shaped by natural selection. Our framework, applied to 40 populations of 34 mammals, successfully placed the species on the DB-DL continuum. We could also link the species' position on the DB-DL continuum to their generation time and time to recovery. Moreover, the second-order derivative unveiled that vital rates with lower temporal variation are not necessarily under a strong pressure of stabilizing selection, as predicted by DBH and DLH. Our framework provides an important step towards unifying the different perspectives of DBH and DLH with key evolutionary concepts.

Microbial respiration is a key biotic driver of climate change. Warming boosts microbial population growth, which increases biomass and respiration. This feedback might be disrupted by adaptation in thermal performance curves (TPCs) -whose shape describes how temperature drives growth. In this study, we uncover substantial genetic variation (G) in microbial intrinsic population growth rates (r), demonstrate a causal link between G variation in r and G variation in TPC shape, and show how this variation constrains r-TPC shape evolution along specific evolutionary paths across temperatures. We also uncover Gene-by-Environment (G x E) variation in r, which results in specific signatures in TPC shape and predictable temperature-dependent rapid TPC evolution but also lower G, which could reduce future evolutionary potential. Overall, we show how temperature-dependent evolution in a linchpin of global ecosystem function--microbial TPC shape--is determined by a combination of heritable and non-heritable variation in intrinsic growth rates.

To mitigate and adapt to climate change, there is an urgent need to synthesize the state of our knowledge on plant responses to climate. The availability of open-access data, combined with our understanding of plant physiology and life history theory provide opportunities to examine quantitative generalizations regarding which biomes and species are most responsive to climate drivers. Here, we synthesized time series of structured population models from 165 populations from 62 plants around the globe to link plant population growth rates to precipitation and temperature drivers. We expected: (1) more pronounced demographic responses to precipitation than temperature, especially in arid biomes; (2) a higher climate sensitivity in short-lived rather than long-lived species; and (3) a stronger response to climate by species that reproduce more frequently. We found that precipitation anomalies have a nearly three-fold larger effect on{lambda} than temperature. Precipitation has substantially more pronounced effects in more arid sites, but large noise makes this relationship non-significant. Species with shorter generation time have much stronger absolute responses to climate anomalies, while the degree of iteroparity does not correlate with population responses to climate. We conclude that key species-level traits can predict plant population responses to climate, and discuss the relevance of this generalization for conservation planning and evolutionary theory.

O_LIIn trait-based ecology, phenotypic variation (PVar) is often quantified with measures that express average differences between populations standardized in the range 0-1. A major problem with these measures is that they disregard the within-population trait variability. In addition, most of these measures cannot be decomposed across scales. This can alter their interpretation, thus limiting their applicability. C_LIO_LITo overcome these problems, we propose a new measure, the Phenotypic Dissimilarity Index (PhD) that is insensitive to the within-population interindividual trait variability. Likewise, PhD can be used to quantify PVar between individuals in a population while accounting for the PVar within individuals. C_LIO_LIUsing simulated and real data, we showed that PhD index correctly quantifies PVar when the within-population trait variability is not negligible, as in many ecological studies. By accounting for within-population trait variability, the PhD index generally provides a more parsimonious quantification of PVar across an environmental gradient compared to other estimators. C_LIO_LITraits sampled within a species have an inherent variability. Accounting for such variability is essential to understand species phenotypic responses to environmental cues. As such, the PhD index will provide ecologists with an asset to reliably quantify and compare PVar within and between species across environmental gradients at different scales. We also provide an R function to calculate the PhD index. C_LI

Demographic buffering and lability have been identified as adaptive strategies to optimise fitness in a fluctuating environment. These are not mutually exclusive, however we lack efficient methods to measure their relative importance for a given life history. Here, we decompose the stochastic growth rate (fitness) into components arising from nonlinear responses and variance-covariance of demographic parameters to an environmental driver, which allows studying joint effects of buffering and lability. We apply this decomposition for 154 animal matrix population models under different scenarios, to explore how these main fitness components vary across life histories. Faster-living species appear more responsive to environmental fluctuations, either positively or negatively. They have the highest potential for strong adaptive demographic lability, while demographic buffering is a main strategy in slow-living species. Our decomposition provides a comprehensive framework to study how organisms adapt to variability through buffering and lability, and to predict species responses to climate change.

A fundamental assumption of functional ecology is that functional traits determine life-histories. Yet correlations between traits and life-history components are often weak, especially for long lived plants. This is because trade-offs, constraints, dynamic resource budgets and the scaling from single organs to entire plants cause complex relationships between traits and life-history. To elucidate these relationships, we present an integrated Trait-Resource-Life-History (TRL) framework that infers how functional traits affect organ-level costs and benefits of different life history components, how these costs and benefits shape the dynamics of whole-plant resource acquisition and allocation, and how these dynamics translate into life history. We illustrate this framework by developing a TRL model for a functionally diverse group of woody plants (22 species of the genus Protea from the South African Greater Cape Floristic Region). Using hierarchical Bayesian latent state-space modelling, we statistically parameterise this model from data on year-to-year variation in growth, reproduction and maternal care (serotiny) for 600 individuals. The parameterised model reveals that higher resource acquisition translates into both larger absolute resource pools and greater proportional resource allocation to reproduction. Accordingly, specific leaf area, a key trait increasing resource acquisition, is associated with larger resource pools, an earlier age of maturity as well as increased vegetative and reproductive performance at young to intermediate ages. In contrast, seed nitrogen content has opposing effects on the benefits of different organs and thus only shows weak correlations with life-history components. Importantly, the TRL model identifies trait and resource-mediated trade-offs at the level of organs, whole-plant resource budgets and life-histories. It can thus quantify key components of life-history theory that are so far largely inaccessible for long-lived plants. This permits novel insights into ecological and evolutionary mechanisms shaping life-histories. Application of the proposed framework to a broad range of plant systems should be facilitated by the increasing availability of trait and demographic data, whole-plant phenotyping and high resolution remote sensing. The integration of the TRL framework with models of biotic interactions further holds promise for a resource-based understanding of community dynamics across trophic levels and a closer integration of functional ecology, evolutionary ecology, community ecology and ecosystem science.

Functional traits are influenced by phylogenetic constraints and environmental conditions, but previous large-scale studies modeled traits either as species weighted averages or directly from the environment, precluding analyses of the relative contributions of inter- and intraspecific variation across regions. We developed a joint model integrating phylogenetic and environmental information to understand and predict the distribution of eight leaf traits across the eastern USA. This model explained 68% of trait variation, outperforming both species-only and environment-only models, with variance attributable to species alone (23%), the environment alone (13%), and their combined effects (25%). The importance of the two drivers varied by trait. Predictions for the eastern USA produced accurate estimates of intraspecific variation and deviated from both species-only and environment-only models. Predictions revealed that intraspecific variation holds information across scales, affects relationships in the leaf economic spectrum and is key for interpreting trait distributions and ecosystem processes within and across ecoregions.

The capacity of ectotherms to adjust their thermal tolerance limits through evolution or acclimation seems relatively modest and highly variable, and we lack satisfying explanations for both findings given a limited understanding of what ultimately determines an organisms thermal tolerance. Here, we test if the amount of heating an ectotherm tolerates throughout a heating event until organismal failure scales with temperatures non-linear influence on biological rates. To account for the non-linear influence of temperature on biological rates on heating tolerance, we rescaled the duration of heating events of 316 ectothermic taxa acclimated to different temperatures and describe the biological rate-corrected heating duration. This rescaling reveals that the capacity of an organism to resist a heating event is in fact remarkably constant across any acclimation temperature, enabling high-precision estimates of how organismal thermal tolerance limits vary under different thermal regimes. We also find that faster heating consistently reduces biological rate-corrected heating durations, which helps further explain why thermal tolerance limits seem so variable on absolute temperature scales. Existing paradigms are that heating tolerances and thermal tolerance limits reflect incomplete metabolic compensatory responses, are constrained by evolutionary conservatism, or index failure of systems such as membrane function; our data provide a different perspective and show that an organisms thermal tolerance emerges from the interaction between the non-linear thermal dependence of biological rates and heating durations, which is an approximately-fixed property of a species.

Ecological and evolutionary dynamics of range expansions are shaped by both dispersal and population growth. Accordingly, density-dependence in either dispersal or growth can determine whether expansions are pulled or pushed, i.e. whether expansion velocities and genetic diversity are mainly driven by recent, low-density edge populations, or by older populations closer to the core. Despite this and despite abundant evidence of dispersal evolution during expansions, the impact of density-dependent dispersal and its evolution on expansion dynamics remains understudied. Here, we used simulation models to examine the influence of individual trait variation in both dispersal capacity and dispersal density- dependence on expansions, and how it impacts the position of expansions on the pulled-pushed continuum. First, we found that knowing about the evolution of density-dependent dispersal at the range edge can greatly improve our ability to predict whether an expansion is (more) pushed or (more) pulled. Second, we found that both dispersal costs and the sources of variation in dispersal (genetic or non-genetic, in dispersal capacity versus in density- dependence) greatly influence how expansion dynamics evolve. Among other scenarios, pushed expansions tended to become more pulled with time only when density-dependence was highly heritable, dispersal costs were low and dispersal capacity could not evolve. When, on the other hand, variation in density-dependence had no genetic basis, but dispersal capacity could evolve, then pushed expansions tended to become more pushed with time, and pulled expansions more pulled. More generally, our results show that trying to predict expansion velocities and dynamics using trait information from non-expanding regions only may be problematic, that both dispersal variation and its sources play a key role in determining whether an expansion is and stays pushed, and that environmental context (here dispersal costs) cannot be neglected. Those simulations suggest new avenues of research to explore, both in terms of theoretical studies and regarding ways to empirically study pushed vs. pulled range expansions.

O_LIHigh elevation populations are expected to receive reduced snowpack, warmer temperatures, and more variable precipitation patterns, potentially putting them at risk if rates of adaptation do not keep pace with climate change. Populations from climates more closely aligned with the changing high elevation conditions may prove better suited to current climate than the current local populations. Thus, it is essential to assess 1) whether high elevation populations are locally adapted to current climate, and 2) whether fitness of lower elevation populations from warmer climates is higher than for local populations in high elevation conditions. C_LIO_LIWe conducted a common garden study with Streptanthus tortuosus at a high elevation site. Twenty-three populations from across the species range were measured weekly for mortality, and reproductive output was measured at the end of the growing season. We examined the effects of climatic distance from the site of origin on plant performance. The effects of weekly weather on mortality were also assessed. C_LIO_LIWe observed adaptational lag for high elevation populations, including the native population, but only for some life stages. Low elevation populations had higher survival through the first year and over winter. Additionally, the probability of reproducing was highest for populations from the warmest climates. Warmer ambient temperatures at the high elevation garden were also associated with higher weekly mortality across populations. However, survival to reproduction in the second year was higher in populations from climates closer to the garden, i.e. high elevation populations. Thus, adaptational lag differed among life stages. C_LIO_LISynthesis: This study highlights the importance of considering variation in life history and seasonal conditions when evaluating how species that occur across an elevational gradient may respond to climate change. This adds to a growing body of evidence that reveals warming temperatures as a threat to high elevation populations. However, unlike previous studies, this threat was not consistent across life stages. These results suggest that strategic assisted gene flow that combines the benefits of warm-adapted low elevation populations with the benefits of snow-adapted life history from high elevation populations may be beneficial in this species, and similar systems. C_LI

Climate-driven habitat shifts pose challenges for dispersal-limited, late-maturing taxa such as trees. Older trees are often the most reproductive individuals in the population, but as habitats shift, these individuals can be left behind in the trailing range edge, generating "zombie forests" that may persist long after the suitable habitat has shifted. Are these zombie forests vestiges of ecosystems past or do they play an ecological role? To understand how zombie forests affect population persistence, we developed a spatially explicit, stage-structured model of tree populations occupying a shifting habitat. Our model shows that seed dispersal from zombie forests to the range core can considerably increase the maximum rate of climate change that a population can withstand. Moreover, the entire core population can ultimately descend from recruitment-limited zombie forests, highlighting their demographic value. Our results suggest that preserving trailing-edge zombie forests can greatly increase population persistence in the face of climate change.

The space for time substitution posits that warmer locations can provide a source of genetic variation that could be adaptive for future climate change conditions. While this approximation might be useful for planning assisted gene flow, it relies on the importance of abiotic adaptations over biotic ones. Here I address this gap by assessing influence of anti-herbivore defenses, phenology, and morphology on the seed production of 146 populations of Oenothera biennis close to the plants cold range limit. Genotypes from 2.1{degrees} South of the common garden produce more seeds than most northern lineages. Adaptations across space are a suitable substitute for climate change, but there is still substantial fitness variability. These differences were best explained by bolt date, flowering time, and greater defenses against herbivores. Given the impacts of climate change, plant defenses might already be of similar adaptive importance to phenology close to northern rage limits.

An organisms life history strategy is an attempt to optimize fitness, given environmental constraints and inherent demographic tradeoffs. As such, life history helps to shape an organisms ecological and evolutionary responses to environmental change. However, life history can also be shaped by the environment, as the organisms demographic rates respond--directly or through tradeoffs--to the new conditions. This feedback between life history and environment remains poorly understood, limiting our ability to predict the outcomes of environmental change. Here, we studied the effects of environmental change - specifically altered pollination services - on four perennial plant species. We conducted a field-based demography experiment that subjected naturally occurring populations of Delphinium nuttallianum, Hydrophyllum fendleri, Potentilla pulcherrima and Erigeron speciosus to three pollination treatments: ambient (control), reduced, or increased pollination. We estimated population growth rate ({lambda}) and 11 metrics describing life history strategy and demographic resilience from an Integral Projection Model we constructed for each species and parameterized with 4-5 years of census data. Although most life history metrics responded idiosyncratically to pollination treatment, we found consistent effects of pollination on generation time, longevity and, in three of four species, recovery time. Specifically, reduced pollination led to increased longevity, generation time, and recovery time, and increased pollination led to the opposite. These changes in life history resemble shifts along the slow-fast continuum; reduced pollination led to slower lives and increased pollination led to faster lives. This is consequential because generation time and longevity influence short- and long-term population dynamics - for example, by affecting demographic stochasticity and sensitivity to environmental stochasticity, or rates of adaptation to novel conditions. Notably, these changes occurred largely independent from changes in population growth. Altogether, our results highlight changes in life history as an important but underappreciated consequence of environmental change.

1The introduction stage is usually overlooked in trait-based studies of invasiveness, implicitly assuming that species introductions are random. However, human activities promote the movement of specific types of species. Thus, species deliberately introduced for distinct purposes (e.g. gardening, forestry) or as contaminants of human commodities (e.g. stowaway) will likely show particular traits. If species with certain traits have been preferentially introduced (i.e. introduction bias), some traits may have been mistakenly linked to species invasion abilities due to their influence on introduction probability. In this work, we propose a theoretical framework with different scenarios of introduction bias. The introduction scenarios are: (1) Random introduction, independent from traits; (2) Biologically biased introduction, following the worldwide distribution of the trait; and (3) Human biased introduction, following a theoretical introduction pathway that favours the introduction of species with high values of the trait. We evaluate how the introduced trait distributions in these scenarios may affect trait distributions in naturalized and invasive species pools under different hypothesized associations between traits and the probabilities of naturalization and invasion. The aim of this work is to identify situations where ignoring introduction bias may lead to spurious correlations being found between species traits and species ability to become naturalized or invasive. Our framework strongly points to the need to evaluate the traits of species that have become naturalized or invasive along with the traits of species that have failed to do so in order to unravel any existing introduction bias that may confound the correlation between species traits and invasion success. Overlooking a possible introduction bias may lead to the overestimation of the correlation between the trait and the species invasion ability, especially in cases when the pool of introduced species shows extreme values of the trait distribution (as compared to a random introduction). Trait-based studies that deserve special attention to avoid undesired effects of introduction bias on their findings are: those that investigate naturalization using only the pool of naturalized species, and those studies that examine invasiveness by comparing invasive species with native species.

The growth rate hypothesis, a central concept of Ecological Stoichiometry, explains the frequently observed positive association between somatic growth rate and somatic phosphorus content (Psom) in organisms across a broad range of taxa. Here, we explore its potential in predicting intraspecific microevolutionary adaptation. For this, we subjected zooplankton populations to selection for fast population growth (PGR) in either a P-rich (HP) or P-poor (LP) food environment. With common garden transplant experiments we demonstrate evolution in HP populations towards increased PGR concomitant with an increase in Psom. In contrast we show that LP populations evolved higher PGR independently of Psom. We conclude that the GRH hypothesis has considerable value for predicting microevolutionary change, but that its application may be contingent on stoichiometric context. Our results highlight the potential of cryptic evolution in determining the performance response of field populations to elemental limitation of their food resources.