Using Empirical Performance Data to Source Bluebunch and Snake River Wheatgrass Plant Materials to Restoration Sites in the Eastern Great Basin, USA

To infer adaptation of plant material, restoration practitioners often consider only surrogate geographic or climatic information. However, empirical biomass data could assist in deciding what material to use where. To test this approach, we transplanted seven bluebunch wheatgrass (BBWG; Pseudoroegneria spicata) and five Snake River wheatgrass (SRWG; Elymus wawawaiensis) populations to three sites ranging from low to high precipitation (LPPT, MPPT, and HPPT). We measured establishment-year (2011) biomass at all sites and 2012-16 biomass at MPPT and HPPT. When data were standardized by site, P-7 and Anatone produced the most BBWG biomass across sites and Wahluke the least in both 2011 and 2012-16, while E-58X produced the most SRWG biomass and Secar and E-49X the least in 2011 and 2012-16, respectively. Among BBWG populations in 2011, relative performance of P-7 (G6 generation) and Goldar increased and Whitmar decreased at wetter sites, while Columbia was stable (high) and Wahluke was stable (low) over sites. Among SRWG populations in 2011, Secar, Secar78, and E-58X increased at drier sites and Discovery at wetter sites. However, once established, populations of both species were much more similar for trend. In 2012-16, trend somewhat increased for five BBWG populations from MPPT to HPPT, was stable for Wahluke, but declined for Columbia, while all five SRWG populations declined at HPPT. These results suggest that, once established, BBWG is mostly stable across sites, while SRWG is less adapted to wetter sites. In 2012-16, BBWG populations originating at drier (or wetter) sites mostly performed relatively better at MPPT (or HPPT), suggesting adaptation to site. However, in the establishment year (2011), this relationship did not hold, suggesting seedling vigor and immature growth rate play a stronger role than precipitation at the site of origin.

Inclusive Fitness May Explain Some but Not All Benefits Derived from Helping Behavior in a Cooperatively Breeding Bird

AbstractIn cooperative breeding systems, inclusive fitness theory predicts that nonbreeding 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 prefledging 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.

Modeling stress-induced responses: plasticity in continuous state space and gradual clonal evolution

Mathematical models of cancer and bacterial evolution have generally stemmed from a gene-centric framework, assuming clonal evolution via acquisition of resistance-conferring mutations and selection of their corresponding subpopulations. More recently, the role of phenotypic plasticity has been recognized and models accounting for phenotypic switching between discrete cell states (e.g., epithelial and mesenchymal) have been developed. However, seldom do models incorporate both plasticity and mutationally driven resistance, particularly when the state space is continuous and resistance evolves in a continuous fashion. In this paper, we develop a framework to model plastic and mutational mechanisms of acquiring resistance in a continuous gradual fashion. We use this framework to examine ways in which cancer and bacterial populations can respond to stress and consider implications for therapeutic strategies. Although we primarily discuss our framework in the context of cancer and bacteria, it applies broadly to any system capable of evolving via plasticity and genetic evolution.

High-resolution data are necessary to understand the effects of climate on plant population dynamics of a forest herb

Climate is assumed to strongly influence species distribution and abundance. Although the performance of many organisms is influenced by the climate in their immediate proximity, the climate data used to model their distributions often have a coarse spatial resolution. This is problematic because the local climate experienced by individuals might deviate substantially from the regional average. This problem is likely to be particularly important for sessile organisms like plants and in environments where small-scale variation in climate is large. To quantify the effect of local temperature on vital rates and population growth rates, we used temperature values measured at the local scale (in situ logger measures) and integral projection models with demographic data from 37 populations of the forest herb Lathyrus vernus across a wide latitudinal gradient in Sweden. To assess how the spatial resolution of temperature data influences assessments of climate effects, we compared effects from models using local data with models using regionally aggregated temperature data at several spatial resolutions (≥1 km). Using local temperature data, we found that spring frost reduced the asymptotic population growth rate in the first of two annual transitions and influenced survival in both transitions. Only one of the four regional estimates showed a similar negative effect of spring frost on population growth rate. Our results for a perennial forest herb show that analyses using regionally aggregated data often fail to identify the effects of climate on population dynamics. This emphasizes the importance of using organism-relevant estimates of climate when examining effects on individual performance and population dynamics, as well as when modeling species distributions. For sessile organisms that experience the environment over small spatial scales, this will require climate data at high spatial resolutions.

Responsiveness to long days for flowering is reduced in Arabidopsis by yearly variation in growing season temperatures

Conservative flowering behaviours, such as flowering during long days in summer or late flowering at a high leaf number, are often proposed to protect against variable winter and spring temperatures which lead to frost damage if premature flowering occurs. Yet, due the many factors in natural environments relative to the number of individuals compared, assessing which climate characteristics drive these flowering traits has been difficult. We applied a multidisciplinary approach to 10 winter-annual Arabidopsis thaliana populations from a wide climactic gradient in Norway. We used a variable reduction strategy to assess which of 100 climate descriptors from their home sites correlated most to their flowering behaviours when tested for responsiveness to photoperiod after saturation of vernalization; then, assessed sequence variation of 19 known environmental-response flowering genes. Photoperiod responsiveness inversely correlated with interannual variation in timing of growing season onset. Time to flowering appeared driven by growing season length, curtailed by cold fall temperatures. The distribution of FLM, TFL2 and HOS1 haplotypes, genes involved in ambient temperature response, correlated with growing-season climate. We show that long-day responsiveness and late flowering may be driven not by risk of spring frosts, but by growing season temperature and length, perhaps to opportunistically maximize growth.

Geographic-genomic and geographic-phenotypic differentiation of the Aquilegia viridiflora complex

How species diverge into different lineages is a central issue in evolutionary biology. Despite the increasing evidence indicating that such divergences do not need geographic isolation, the correlation between lineage divergence and the adaptive ecological divergence of phenotype corresponding to distribution is still unknown. In addition, gene flow has been widely detected during and through such diverging processes. We used one widely distributed Aquilegia viridiflora complex as a model system to examine genomic differentiation and corresponding phenotypic variations along geographic gradients. Our phenotypic analyses of 20 populations from northwest to northeast China identified two phenotypic groups along the geographic cline. All examined traits are distinct from each other, although a few intermediate individuals occur in their contacting regions. We further sequenced the genomes of representative individuals of each population. However, four distinct genetic lineages were detected based on nuclear genomes. In particular, we recovered numerous genetic hybrids in the contact regions of four lineages. Gene flow is widespread and continuous between four lineages but much higher between contacting lineages than geographically isolated lineages. Gene flow and natural selection might result in inconsistency between heredity and phenotype. Moreover, many genes with fast lineage-specific mutations were identified to be involved in local adaptation. Our results suggest that both geographic isolation and local selection exerted by the environment and pollinators may together create geographic distributions of phenotypic variations as well as the underlying genomic divergences in numerous lineages.

Current and lagged climate affects phenology across diverse taxonomic groups

The timing of life events (phenology) can be influenced by climate. Studies from around the world tell us that climate cues and species' responses can vary greatly. If variation in climate effects on phenology is strong within a single ecosystem, climate change could lead to ecological disruption, but detailed data from diverse taxa within a single ecosystem are rare. We collated first sighting and median activity within a high-elevation environment for plants, insects, birds, mammals and an amphibian across 45 years (1975-2020). We related 10 812 phenological events to climate data to determine the relative importance of climate effects on species' phenologies. We demonstrate significant variation in climate-phenology linkage across taxa in a single ecosystem. Both current and prior climate predicted changes in phenology. Taxa responded to some cues similarly, such as snowmelt date and spring temperatures; other cues affected phenology differently. For example, prior summer precipitation had no effect on most plants, delayed first activity of some insects, but advanced activity of the amphibian, some mammals, and birds. Comparing phenological responses of taxa at a single location, we find that important cues often differ among taxa, suggesting that changes to climate may disrupt synchrony of timing among taxa.

The role of demographic compensation in stabilising marginal tree populations in North America

Demographic compensation-the opposing responses of vital rates along environmental gradients-potentially delays anticipated species' range contraction under climate change, but no consensus exists on its actual contribution. We calculated population growth rate (λ) and demographic compensation across the distributional ranges of 81 North American tree species and examined their responses to simulated warming and tree competition. We found that 43% of species showed stable population size at both northern and southern edges. Demographic compensation was detected in 25 species, yet 15 of them still showed a potential retraction from southern edges, indicating that compensation alone cannot maintain range stability. Simulated climatic warming caused larger decreases in λ for most species and weakened the effectiveness of demographic compensation in stabilising ranges. These findings suggest that climate stress may surpass the limited capacity of demographic compensation and pose a threat to the viability of North American tree populations.

Building integral projection models with nonindependent vital rates

Population dynamics are functions of several demographic processes including survival, reproduction, somatic growth, and maturation. The rates or probabilities for these processes can vary by time, by location, and by individual. These processes can co-vary and interact to varying degrees, e.g., an animal can only reproduce when it is in a particular maturation state. Population dynamics models that treat the processes as independent may yield somewhat biased or imprecise parameter estimates, as well as predictions of population abundances or densities. However, commonly used integral projection models (IPMs) typically assume independence across these demographic processes. We examine several approaches for modelling between process dependence in IPMs and include cases where the processes co-vary as a function of time (temporal variation), co-vary within each individual (individual heterogeneity), and combinations of these (temporal variation and individual heterogeneity). We compare our methods to conventional IPMs, which treat vital rates independent, using simulations and a case study of Soay sheep (Ovis aries). In particular, our results indicate that correlation between vital rates can moderately affect variability of some population-level statistics. Therefore, including such dependent structures is generally advisable when fitting IPMs to ascertain whether or not such between vital rate dependencies exist, which in turn can have subsequent impact on population management or life-history evolution.

Intraspecific variation mediates density dependence in a genetically diverse plant species

Interactions between neighboring plants are critical for biodiversity maintenance in plant populations and communities. Intraspecific trait variation and genome duplication are common in plant species and can drive eco-evolutionary dynamics through genotype-mediated plant-plant interactions. However, few studies have examined how species-wide intraspecific variation may alter interactions between neighboring plants. We investigate how subspecies and ploidy variation in a genetically diverse species, big sagebrush (Artemisia tridentata), can alter the demographic outcomes of plant interactions. Using a replicated, long-term common garden experiment that represents range-wide diversity of A. tridentata, we ask how intraspecific variation, environment, and stand age mediate neighbor effects on plant growth and survival. Spatially explicit models revealed that ploidy variation and subspecies identity can mediate plant-plant interactions but that the effect size varied in time and across experimental sites. We found that demographic impacts of neighbor effects were strongest during early stages of stand development and in sites with greater growth rates. Within subspecies, tetraploid populations showed greater tolerance to neighbor crowding compared to their diploid variants. Our findings provide evidence that intraspecific variation related to genome size and subspecies identity impacts spatial demography in a genetically diverse plant species. Accounting for intraspecific variation in studies of conspecific density dependence will improve our understanding of how local populations will respond to novel genotypes and biotic interaction regimes. As introduction of novel genotypes into local populations becomes more common, quantifying demographic processes in genetically diverse populations will help predict long-term consequences of plant-plant interactions.

A practical guide to selecting models for exploration, inference, and prediction in ecology

Selecting among competing statistical models is a core challenge in science. However, the many possible approaches and techniques for model selection, and the conflicting recommendations for their use, can be confusing. We contend that much confusion surrounding statistical model selection results from failing to first clearly specify the purpose of the analysis. We argue that there are three distinct goals for statistical modeling in ecology: data exploration, inference, and prediction. Once the modeling goal is clearly articulated, an appropriate model selection procedure is easier to identify. We review model selection approaches and highlight their strengths and weaknesses relative to each of the three modeling goals. We then present examples of modeling for exploration, inference, and prediction using a time series of butterfly population counts. These show how a model selection approach flows naturally from the modeling goal, leading to different models selected for different purposes, even with exactly the same data set. This review illustrates best practices for ecologists and should serve as a reminder that statistical recipes cannot substitute for critical thinking or for the use of independent data to test hypotheses and validate predictions.

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.

Latitudinal gradients in population growth do not reflect demographic responses to climate

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 toward 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.

Assessing accuracy of GAP and LANDFIRE land cover datasets in winter habitats used by greater sage-grouse in Idaho and Wyoming, USA

Remotely sensed land cover datasets have been increasingly employed in studies of wildlife habitat use. However, meaningful interpretation of these datasets is dependent on how accurately they estimate habitat features that are important to wildlife. We evaluated the accuracy of the GAP dataset, which is commonly used to classify broad cover categories (e.g., vegetation communities) and LANDFIRE datasets, which classifies narrower cover categories (e.g., plant species) and structural features of vegetation. To evaluate accuracy, we compared classification of cover types and estimates of percent cover and height of sagebrush (Artemisia spp.) derived from GAP and LANDFIRE datasets to field-collected data in winter habitats used by greater sage-grouse (Centrocercus urophasianus). Accuracy was dependent on the type of dataset used as well as the spatial scale (point, 500-m, and 1-km) and biological level (community versus dominant species) investigated. GAP datasets had the highest overall classification accuracy of broad sagebrush cover types (49.8%) compared to LANDFIRE datasets for narrower cover types (39.1% community-level; 31.9% species-level). Percent cover and height were not accurately estimated in the LANDFIRE dataset. Our results suggest that researchers must be cautious when applying GAP or LANDFIRE datasets to classify narrow categories of land cover types or to predict percent cover or height of sagebrush within sagebrush-dominated landscapes. We conclude that ground-truthing is critical for successful application of land cover datasets in landscape-scale evaluations and management planning, particularly when wildlife use relatively rare habitat types compared to what is available.

Range dynamics mediated by compensatory life stage responses to experimental climate manipulations

The expectations of polar or upslope distributional shifts of species ranges in response to warming climate conditions have been recently questioned. Diverse responses of different life stages to changing temperature and moisture regimes may alter these predicted range dynamics. Furthermore, the climate driver(s) influencing demographic rates, and the contribution of each demographic rate to population growth rate (λ), may shift across a species range. We investigated these demographic effects by experimentally manipulating climate and measuring responses of λ in nine populations spanning the elevation range of an alpine plant (Ivesia lycopodioides). Populations exhibited stable growth rates (λ ~ 1) under naturally wet conditions and declining rates (λ < 1) under naturally dry conditions. However, opposing vital rate responses to experimental heating and watering lead to negligible or negative effects on population stability. These findings indicate that life stage-specific responses to changing climate can disrupt the current relationships between population stability and climate across species ranges.

Population projections of an endangered cactus suggest little impact of climate change

Population projections coupled with downscaled climate projections are a powerful tool that allows predicting future population dynamics of vulnerable plants in the face of a changing climate. Traditional approaches used to predict the vulnerability of plants to climate change (e.g. species distribution models) fail to mechanistically describe the basis of a population's dynamics and thus cannot be expected to correctly predict its temporal trends. In this study, we used a 23-year demographic dataset of the acuña cactus, an endangered species, to predict its population dynamics to the end of the century. We used integral projection models to describe its vital rates and population dynamics in relation to plant volume and key climatic variables. We used the resulting climate-driven IPM along with climatic projections to predict the population growth rates from 1991 to 2099. We found the average population growth rate of this population between 1991 and 2013 to be 0.70 (95% CI 0.61-0.79). This result confirms that the population of acuña cactus has been declining and that this decline is due to demographic structure and climate conditions. However, the projection model also predicts that, up to 2080, the population will remain relatively stable mainly due to the survival of its existing adult individuals. Notwithstanding, the long-term viability of the populations can only be achieved through the recruitment of new individuals.

The demographic effects of functional traits: an integral projection model approach reveals population-level consequences of reproduction-defence trade-offs

Quantitatively linking individual variation in functional traits to demography is a necessary step to advance our understanding of trait-based ecological processes. We constructed a population model for Asclepias syriaca to identify how functional traits affect vital rates and population growth and whether trade-offs in chemical defence and demography alter population growth. Plants with higher foliar cardenolides had lower fibre, cellulose and lignin levels, as well as decreased sexual and clonal reproduction. Average cardenolide concentrations had the strongest effect on population growth. In both the sexual and clonal pathway, the trade-off between reproduction and defence affected population growth. We found that both increasing the mean of the distribution of individual plant values for cardenolides and herbivory decreased population growth. However, increasing the variance in both defence and herbivory increased population growth. Functional traits can impact population growth and quantifying individual-level variation in traits should be included in assessments of population-level processes.

Microclimate and demography interact to shape stable population dynamics across the range of an alpine plant

Heterogeneous terrain in montane systems results in a decoupling of climatic gradients. Population dynamics across species' ranges in these heterogeneous landscapes are shaped by relationships between demographic rates and these interwoven climate gradients. Linking demography and climate variables across species' ranges refines our understanding of the underlying mechanisms of species' current and future ranges. We explored the importance of multiple microclimatic gradients in shaping individual demographic rates and population growth rates in 16 populations across the elevational distribution of an alpine plant (Ivesia lycopodioides var. scandularis). Using integral projection modeling, we ask how each rate varies across three microclimate gradients: accumulated degree-days, growing-season soil moisture, and days of snow cover. Range-wide variation in demographic rates was best explained by the combined influence of multiple microclimatic variables. Different pairs of demographic rates exhibited both similar and inverse responses to the same microclimatic gradient, and the microclimatic effects often varied with plant size. These responses resulted in range-wide projected population persistence, with no declining populations at either elevational range edge or at the extremes of the microclimate gradients. The complex relationships between topography, microclimate and demography suggest that populations across a species' range may have unique demographic pathways to stable population dynamics.

Landscape heterogeneity is key to forecasting outcomes of plant reintroduction

Conservation and restoration projects often involve starting new populations by introducing individuals into portions of their native or projected range. Such efforts can help meet many related goals, including habitat creation, ecosystem service provisioning, assisted migration, and the reintroduction of imperiled species following local extirpation. The outcomes of reintroduction efforts, however, are highly variable, with results ranging from local extinction to dramatic population growth; reasons for this variation remain unclear. Here, we ask whether population growth following plant reintroductions is governed by variation at two scales: the scale of individual habitat patches to which individuals are reintroduced, and larger among-landscape scales in which similar patches may be situated in landscapes that differ in matrix type, soil conditions, and other factors. Quantifying demographic variation at these two scales will help prioritize locations for introduction and, once introductions take place, forecast population growth. This work took place within a large-scale habitat fragmentation experiment, where individuals of two perennial forb species were reintroduced into eight replicate ~50-ha landscapes, each containing a set of five ~1-ha patches that varied in their degree of isolation (connected by habitat corridors or unconnected) and edge-to-area ratio. Using data on individual growth, survival, reproductive output, and recruitment collected one to two years after reintroduction, we developed models to forecast population growth, then compared forecasts to observed population sizes, three and six years later. Both the type of patch (connected and unconnected) and identity of the landscape to which individuals were reintroduced had effects on forecasted population growth rates, but only variation associated with landscape identity was an accurate predictor of subsequently observed population growth rates. Models that did not include landscape identity had minimal forecasting ability, revealing the key importance of variation at this scale for accurate prediction. Of the five demographic rates used to model population dynamics, seed production was the most important source of forecast error in population growth rates. Our results point to the importance of accounting for landscape-scale variation in demographic models and demonstrate how such models might assist with prioritizing particular landscapes for species reintroduction projects.

Transient LTRE analysis reveals the demographic and trait-mediated processes that buffer population growth

Temporal variation in environmental conditions affects population growth directly via its impact on vital rates, and indirectly through induced variation in demographic structure and phenotypic trait distributions. We currently know very little about how these processes jointly mediate population responses to their environment. To address this gap, we develop a general transient life table response experiment (LTRE) which partitions the contributions to population growth arising from variation in (1) survival and reproduction, (2) demographic structure, (3) trait values and (4) climatic drivers. We apply the LTRE to a population of yellow‐bellied marmots (Marmota flaviventer) to demonstrate the impact of demographic and trait‐mediated processes. Our analysis provides a new perspective on demographic buffering, which may be a more subtle phenomena than is currently assumed. The new LTRE framework presents opportunities to improve our understanding of how trait variation influences population dynamics and adaptation in stochastic environments.

Ecosystem functional response across precipitation extremes in a sagebrush steppe

Background

Precipitation is predicted to become more variable in the western United States, meaning years of above and below average precipitation will become more common. Periods of extreme precipitation are major drivers of interannual variability in ecosystem functioning in water limited communities, but how ecosystems respond to these extremes over the long-term may shift with precipitation means and variances. Long-term changes in ecosystem functional response could reflect compensatory changes in species composition or species reaching physiological thresholds at extreme precipitation levels.

Methods

We conducted a five year precipitation manipulation experiment in a sagebrush steppe ecosystem in Idaho, United States. We used drought and irrigation treatments (approximately 50% decrease/increase) to investigate whether ecosystem functional response remains consistent under sustained high or low precipitation. We recorded data on aboveground net primary productivity (ANPP), species abundance, and soil moisture. We fit a generalized linear mixed effects model to determine if the relationship between ANPP and soil moisture differed among treatments. We used nonmetric multidimensional scaling to quantify community composition over the five years.

Results

Ecosystem functional response, defined as the relationship between soil moisture and ANPP, was similar among irrigation and control treatments, but the drought treatment had a greater slope than the control treatment. However, all estimates for the effect of soil moisture on ANPP overlapped zero, indicating the relationship is weak and uncertain regardless of treatment. There was also large spatial variation in ANPP within-years, which contributes to the uncertainty of the soil moisture effect. Plant community composition was remarkably stable over the course of the experiment and did not differ among treatments.

Discussion

Despite some evidence that ecosystem functional response became more sensitive under sustained drought conditions, the response of ANPP to soil moisture was consistently weak and community composition was stable. The similarity of ecosystem functional responses across treatments was not related to compensatory shifts at the plant community level, but instead may reflect the insensitivity of the dominant species to soil moisture. These species may be successful precisely because they have evolved life history strategies that buffer them against precipitation variability.

Time-lagged effects of weather on plant demography: drought and Astragalus scaphoides

Temperature and precipitation determine the conditions where plant species can occur. Despite their significance, to date, surprisingly few demographic field studies have considered the effects of abiotic drivers. This is problematic because anticipating the effect of global climate change on plant population viability requires understanding how weather variables affect population dynamics. One possible reason for omitting the effect of weather variables in demographic studies is the difficulty in detecting tight associations between vital rates and environmental drivers. In this paper, we applied Functional Linear Models (FLMs) to long-term demographic data of the perennial wildflower, Astragalus scaphoides, and explored sensitivity of the results to reduced amounts of data. We compared models of the effect of average temperature, total precipitation, or an integrated measure of drought intensity (standardized precipitation evapotranspiration index, SPEI), on plant vital rates. We found that transitions to flowering and recruitment in year t were highest if winter/spring of year t was wet (positive effect of SPEI). Counterintuitively, if the preceding spring of year t - 1 was wet, flowering probabilities were decreased (negative effect of SPEI). Survival of vegetative plants from t - 1 to t was also negatively affected by wet weather in the spring of year t - 1 and, for large plants, even wet weather in the spring of t - 2 had a negative effect. We assessed the integrated effect of all vital rates on life history performance by fitting FLMs to the asymptotic growth rate, log(λt). Log(λt) was highest if dry conditions in year t - 1 were followed by wet conditions in the year t. Overall, the positive effects of wet years exceeded their negative effects, suggesting that increasing frequency of drought conditions would reduce population viability of A. scaphoides. The drought signal weakened when reducing the number of monitoring years. Substituting space for time did not recover the weather signal, probably because the weather variables varied little between sites. We detected the SPEI signal when the analysis included data from two sites monitored over 20 yr (2 × 20 observations), but not when analyzing data from four sites monitored over 10 yr (4 × 10 observations).

Low interannual precipitation has a greater negative effect than seedling herbivory on the population dynamics of a short-lived shrub, Schiedea obovata

Climate projections forecast more extreme interannual climate variability over time, with an increase in the severity and duration of extreme drought and rainfall events. Based on bioclimatic envelope models, it is projected that changing precipitation patterns will drastically alter the spatial distributions and density of plants and be a primary driver of biodiversity loss. However, many other underlying mechanisms can impact plant vital rates (i.e., survival, growth, and reproduction) and population dynamics. In this study, we developed a size-dependent integral projection model (IPM) to evaluate how interannual precipitation and mollusk herbivory influence the dynamics of a Hawaii endemic short-lived shrub, Schiedea obovata (Caryophyllaceae). Assessing how wet season precipitation effects population dynamics it critical, as it is the timeframe when most of the foliar growth occurs, plants flower and fruit, and seedlings establish. Temporal variation in wet season precipitation had a greater effect than mollusk herbivory on S. obovata population growth rate λ, and the impact of interannual precipitation on vital rates shifted across plant ontogeny. Furthermore, wet season precipitation influenced multiple vital rates in contrasting ways and the effect of precipitation on the survival of larger vegetative and reproductively mature individuals contributed the most to variation in the population growth rate. Among all combination of wet season precipitation and herbivory intensities, the only scenario that led to a growing population was when high wet precipitation was associated with low herbivory. Our study highlights the importance of evaluating how abiotic factors and plant-consumer interactions influence an organism across its life cycle to fully understand the underpinning mechanisms that structure its spatial and temporal distribution and abundance. Our results also illustrate that for short-lived species, like S. obovata, seedling herbivory can have less of an effect on the dynamics of plant populations than decreased interannual precipitation.

Identifying critical recruitment bottlenecks limiting seedling establishment in a degraded seagrass ecosystem

Identifying early life-stage transitions limiting seagrass recruitment could improve our ability to target demographic processes most responsive to management. Here we determine the magnitude of life-stage transitions along gradients in physical disturbance limiting seedling establishment for the marine angiosperm, Posidonia australis. Transition matrix models and sensitivity analyses were used to identify which transitions were critical for successful seedling establishment during the first year of seed recruitment and projection models were used to predict the most appropriate environments and seeding densities. Total survival probability of seedlings was low (0.001), however, transition probabilities between life-stages differed across the environmental gradients; seedling recruitment was affected by grazing and bioturbation prevailing during the first life-stage transition (1 month), and 4-6 months later during the third life-stage transition when establishing seedlings are physically removed by winter storms. Models projecting population growth from different starting seed densities showed that seeds could replace other more labour intensive and costly methods, such as transplanting adult shoots, if disturbances are moderated sufficiently and if large numbers of seed can be collected in sufficient quantity and delivered to restoration sites efficiently. These outcomes suggest that by improving management of early demographic processes, we could increase recruitment in restoration programs.

Variation in the Prevalence and Transmission of Heritable Symbionts Across Host Populations in Heterogeneous Environments

Heritable microbes are abundant in nature and influential to their hosts and the communities in which they reside. However, drivers of variability in the prevalence of heritable symbionts and their rates of transmission are poorly resolved, particularly across host populations experiencing variable biotic and abiotic environments. To fill these gaps, we surveyed 25 populations of two native grasses (Elymus virginicus and Elymus canadensis) across the southern Great Plains (USA). Both grass species host heritable endophytic fungi (genus Epichloё) and can hybridize where their ranges overlap. From a subset of hosts, we characterized endophyte genotype using genetic loci that link to bioactive alkaloid production. First, we found mean vertical transmission rates and population-level prevalence were positively correlated, specifically for E. virginicus. However, both endophyte prevalence and transmission varied substantially across populations and did not strongly correlate with abiotic variables, with one exception: endophyte prevalence decreased as drought stress decreased for E. virginicus hosts. Second, we evaluated the potential influence of biotic factors and found that, after accounting for climate, endophyte genotype explained significant variation in symbiont inheritance. We also contrasted populations where host species co-occurred in sympatry vs. allopatry. Sympatry could potentially increase interspecific hybridization, but this variable did not associate with patterns of symbiont prevalence or transmission success. Our results reveal substantial variability in symbiont prevalence and transmission across host populations and identify symbiont genotype, and to a lesser extent, the abiotic environment as sources of this variation.

The influence of herbivory and weather on the vital rates of two closely related cactus species

Herbivory has long been recognized as a significant driver of plant population dynamics, yet its effects along environmental gradients are unclear. Understanding how weather modulates plant-insect interactions can be particularly important for predicting the consequences of exotic insect invasions, and an explicit consideration of weather may help explain why the impact can vary greatly across space and time. We surveyed two native prickly pear cactus species (genus Opuntia) in the Florida panhandle, USA, and their specialist insect herbivores (the invasive South American cactus moth, Cactoblastis cactorum, and three native insect species) for five years across six sites. We used generalized linear mixed models to assess the impact of herbivory and weather on plant relative growth rate (RGR) and sexual reproduction, and we used Fisher's exact test to estimate the impact of herbivory on survival. Weather variables (precipitation and temperature) were consistently significant predictors of vital rate variation for both cactus species, in contrast to the limited and varied impacts of insect herbivory. Weather only significantly influenced the impact of herbivory on Opuntia humifusa fruit production. The relationships of RGR and fruit production with precipitation suggest that precipitation serves as a cue in determining the trade-off in the allocation of resources to growth or fruit production. The presence of the native bug explained vital rate variation for both cactus species, whereas the invasive moth explained variation only for O. stricta. Despite the inconsistent effect of herbivory across vital rates and cactus species, almost half of O. stricta plants declined in size, and the invasive insect negatively affected RGR and fruit production. Given that fruit production was strongly size-dependent, this suggests that O. stricta populations at the locations surveyed are transitioning to a size distribution of predominantly smaller sizes and with reduced sexual reproduction potential.

Linking river flow regimes to riparian plant guilds: a community-wide modeling approach

Modeling riparian plant dynamics along rivers is complicated by the fact that plants have different edaphic and hydrologic requirements at different life stages. With intensifying human demands for water and continued human alteration of rivers, there is a growing need for predicting responses of vegetation to flow alteration, including responses related to climate change and river flow management. We developed a coupled structured population model that combines stage-specific responses of plant guilds with specific attributes of river hydrologic regime. The model uses information on the vital rates of guilds as they relate to different hydrologic conditions (flood, drought, and baseflow), but deliberately omits biotic interactions from the structure (interaction neutral). Our intent was to (1) consolidate key vital rates concerning plant population dynamics and to incorporate these data into a quantitative framework, (2) determine whether complex plant stand dynamics, including biotic interactions, can be predicted from basic vital rates and river hydrology, and (3) project how altered flow regimes might affect riparian communities. We illustrated the approach using five flow-response guilds that encompass much of the river floodplain community: hydroriparian tree, xeroriparian shrub, hydroriparian shrub, mesoriparian meadow, and desert shrub. We also developed novel network-based tools for predicting community-wide effects of climate-driven shifts and deliberately altered flow regimes. The model recovered known patterns of hydroriparian tree vs. xeroriparian shrub dominance, including the relative proportion of these two guilds as a function of river flow modification. By simulating flow alteration scenarios ranging from increased drought to shifts in flood timing, the model predicted that mature hydroriparian forest should be most abundant near the observed natural flow regime. Multiguild sensitivity analysis identified substantial network connectivity (many connected nodes) and biotic linkage (strong pairwise connections between nodes) under natural flow regime conditions. Both connectivity and linkage were substantially reduced under drought and other flow-alteration scenarios, suggesting that community structure is destabilized under such conditions. This structured population modeling approach provides a useful tool for understanding the community-wide effects of altered flow regimes due to climate change and management actions that influence river flow regime.

Direct effects dominate responses to climate perturbations in grassland plant communities

Theory predicts that strong indirect effects of environmental change will impact communities when niche differences between competitors are small and variation in the direct effects experienced by competitors is large, but empirical tests are lacking. Here we estimate negative frequency dependence, a proxy for niche differences, and quantify the direct and indirect effects of climate change on each species. Consistent with theory, in four of five communities indirect effects are strongest for species showing weak negative frequency dependence. Indirect effects are also stronger in communities where there is greater variation in direct effects. Overall responses to climate perturbations are driven primarily by direct effects, suggesting that single species models may be adequate for forecasting the impacts of climate change in these communities.

From facilitation to competition: temperature-driven shift in dominant plant interactions affects population dynamics in seminatural grasslands

Biotic interactions are often ignored in assessments of climate change impacts. However, climate-related changes in species interactions, often mediated through increased dominance of certain species or functional groups, may have important implications for how species respond to climate warming and altered precipitation patterns. We examined how a dominant plant functional group affected the population dynamics of four co-occurring forb species by experimentally removing graminoids in seminatural grasslands. Specifically, we explored how the interaction between dominants and subordinates varied with climate by replicating the removal experiment across a climate grid consisting of 12 field sites spanning broad-scale temperature and precipitation gradients in southern Norway. Biotic interactions affected population growth rates of all study species, and the net outcome of interactions between dominants and subordinates switched from facilitation to competition with increasing temperature along the temperature gradient. The impacts of competitive interactions on subordinates in the warmer sites could primarily be attributed to reduced plant survival. Whereas the response to dominant removal varied with temperature, there was no overall effect of precipitation on the balance between competition and facilitation. Our findings suggest that global warming may increase the relative importance of competitive interactions in seminatural grasslands across a wide range of precipitation levels, thereby favouring highly competitive dominant species over subordinate species. As a result, seminatural grasslands may become increasingly dependent on disturbance (i.e. traditional management such as grazing and mowing) to maintain viable populations of subordinate species and thereby biodiversity under future climates. Our study highlights the importance of population-level studies replicated under different climatic conditions for understanding the underlying mechanisms of climate change impacts on plants.

Plant fitness in a rapidly changing world

Modern reliance on fossil fuels has ushered in extreme temperatures globally and abnormal precipitation patterns in many regions. Although the climate is changing rapidly, other agents of natural selection such as photoperiod remain constant. This decoupling of previously reliable environmental cues shifts adaptive landscapes, favors novel suites of traits and likely increases the extinction risk of local populations. Here, I examine the fitness consequences of changing climates. Meta-analyses demonstrate that simulated future climates depress viability and fecundity components of fitness for native plant species in the short term, which could reduce population growth rates. Contracting populations that cannot adapt or adjust plastically to new climates might not be capable of producing sufficient migrants to track changing conditions.

Bud-bank and tiller dynamics of co-occurring C3 caespitose grasses in mixed-grass prairie

PREMISE OF THE STUDY

Tiller recruitment from the belowground bud bank of caespitose grasses influences their ability to monopolize local resources and, hence, their genet fitness. Differences in bud production and outgrowth among tiller types within a genet and among species may explain co-occurrence of caespitose grasses. This study aimed to characterize genet bud-bank and tiller production and dynamics in two co-occurring species and compare their vegetative reproductive strategies.

METHODS

Bud-bank and tiller dynamics of Hesperostipa comata and Nassella viridula, dominant C3 caespitose grasses in the northern mixed-grass prairie of North America, were assessed throughout an annual cycle.

KEY RESULTS

The two species showed similar strategies, maintaining polycyclic tillers and thus creating mixed-age genet bud banks comprising multiple bud cohorts produced in different years. Vegetative tillers produced the majority of buds, whereas flowering tillers contributed little to the bud bank. Buds lived for at least 2 yr and were maintained in multiple developmental stages throughout the year. Because bud longevity rarely exceeded tiller longevity, tiller longevity drove turnover within the bud bank. Tiller population dynamics, more than bud production per tiller, determined the differential contribution of tiller types to the bud bank. Nassella viridula had higher bud production per tiller, a consistent annual tiller recruitment density, and greater longevity of buds on senesced and flowering tillers than H. comata.

CONCLUSIONS

Co-occurring C3 caespitose grasses had similar bud-bank and tiller dynamics contributing to genet persistence but differed in bud characteristics that could affect genet longevity and species coexistence.

Effects of climate change on plant population growth rate and community composition change

The impacts of climate change on forest community composition are still not well known. Although directional trends in climate change and community composition change were reported in recent years, further quantitative analyses are urgently needed. Previous studies focused on measuring population growth rates in a single time period, neglecting the development of the populations. Here we aimed to compose a method for calculating the community composition change, and to testify the impacts of climate change on community composition change within a relatively short period (several decades) based on long-term monitoring data from two plots—Dinghushan Biosphere Reserve, China (DBR) and Barro Colorado Island, Panama (BCI)—that are located in tropical and subtropical regions. We proposed a relatively more concise index, Slnλ, which refers to an overall population growth rate based on the dominant species in a community. The results indicated that the population growth rate of a majority of populations has decreased over the past few decades. This decrease was mainly caused by population development. The increasing temperature had a positive effect on population growth rates and community change rates. Our results promote understanding and explaining variations in population growth rates and community composition rates, and are helpful to predict population dynamics and population responses to climate change.

Predicting changes in the distribution and abundance of species under environmental change

Environmental changes are expected to alter both the distribution and the abundance of organisms. A disproportionate amount of past work has focused on distribution only, either documenting historical range shifts or predicting future occurrence patterns. However, simultaneous predictions of abundance and distribution across landscapes would be far more useful. To critically assess which approaches represent advances towards the goal of joint predictions of abundance and distribution, we review recent work on changing distributions and on effects of environmental drivers on single populations. Several methods have been used to predict changing distributions. Some of these can be easily modified to also predict abundance, but others cannot. In parallel, demographers have developed a much better understanding of how changing abiotic and biotic drivers will influence growth rate and abundance in single populations. However, this demographic work has rarely taken a landscape perspective and has largely ignored the effects of intraspecific density. We advocate a synthetic approach in which population models accounting for both density dependence and effects of environmental drivers are used to make integrated predictions of equilibrium abundance and distribution across entire landscapes. Such predictions would constitute an important step forward in assessing the ecological consequences of environmental changes.

Building integral projection models: a user's guide

In order to understand how changes in individual performance (growth, survival or reproduction) influence population dynamics and evolution, ecologists are increasingly using parameterized mathematical models. For continuously structured populations, where some continuous measure of individual state influences growth, survival or reproduction, integral projection models (IPMs) are commonly used. We provide a detailed description of the steps involved in constructing an IPM, explaining how to: (i) translate your study system into an IPM; (ii) implement your IPM; and (iii) diagnose potential problems with your IPM. We emphasize how the study organism's life cycle, and the timing of censuses, together determine the structure of the IPM kernel and important aspects of the statistical analysis used to parameterize an IPM using data on marked individuals. An IPM based on population studies of Soay sheep is used to illustrate the complete process of constructing, implementing and evaluating an IPM fitted to sample data. We then look at very general approaches to parameterizing an IPM, using a wide range of statistical techniques (e.g. maximum likelihood methods, generalized additive models, nonparametric kernel density estimators). Methods for selecting models for parameterizing IPMs are briefly discussed. We conclude with key recommendations and a brief overview of applications that extend the basic model. The online Supporting Information provides commented R code for all our analyses.

Separating direct and indirect effects of global change: a population dynamic modeling approach using readily available field data

Two sources of complexity make predicting plant community response to global change particularly challenging. First, realistic global change scenarios involve multiple drivers of environmental change that can interact with one another to produce non-additive effects. Second, in addition to these direct effects, global change drivers can indirectly affect plants by modifying species interactions. In order to tackle both of these challenges, we propose a novel population modeling approach, requiring only measurements of abundance and climate over time. To demonstrate the applicability of this approach, we model population dynamics of eight abundant plant species in a multifactorial global change experiment in alpine tundra where we manipulated nitrogen, precipitation, and temperature over 7 years. We test whether indirect and interactive effects are important to population dynamics and whether explicitly incorporating species interactions can change predictions when models are forecast under future climate change scenarios. For three of the eight species, population dynamics were best explained by direct effect models, for one species neither direct nor indirect effects were important, and for the other four species indirect effects mattered. Overall, global change had negative effects on species population growth, although species responded to different global change drivers, and single-factor effects were slightly more common than interactive direct effects. When the fitted population dynamic models were extrapolated under changing climatic conditions to the end of the century, forecasts of community dynamics and diversity loss were largely similar using direct effect models that do not explicitly incorporate species interactions or best-fit models; however, inclusion of species interactions was important in refining the predictions for two of the species. The modeling approach proposed here is a powerful way of analyzing readily available datasets which should be added to our toolbox to tease apart complex drivers of global change.