Tom E. X. Miller

Climate forecasts project change not only in the mean of climate variables but also in their variance. If these dual changes interact, then future ecological dynamics will be difficult to predict using current experimental approaches, which typically change the mean or impose a single extreme event, such as drought. We designed a new field experiment to factorially reduce mean precipitation and increase its interannual variability. Across 4 years, drier, more variable precipitation additively reduced aboveground primary productivity by 48%–69% and interactively reduced the dominant plant species, but had no effect on the plant species predicted to dominate in the future, which could lead to state transition. Drier, more variable precipitation also interactively reduced biodiversity more than either climate factor alone, with 37%–42% fewer plant species than under ambient conditions, a pattern that matched declining richness during the past 20 years of ongoing climate change. Drier, more variable precipitation restructured the composition and spatiotemporal variation of the plant community. Altered precipitation mean or variance affected 14% of plant species, with eight species sensitive to the mean × variance interaction. Results suggest that future forecasts of plant community structure may be inadequate if they fail to incorporate climate mean × variance interactions.

Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of inference and projection of population dynamics. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate‐demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.

Species' distributions and abundances are shifting in response to ongoing global climate change. Mutualistic microbial symbionts can provide hosts with protection from environmental stress that may promote resilience under environmental change; however, this change may also disrupt species interactions and lead to declines in hosts and/or symbionts. Symbionts preserved within natural history specimens offer a unique opportunity to quantify changes in microbial symbiosis across broad temporal and spatial scales. We asked how the prevalence of seed‐transmitted fungal symbionts of grasses ( Epichloë endophytes) has changed over time in response to climate change, and how these changes vary across host species' distributions. Specifically, we examined 2346 herbarium specimens of three grass host species ( Agrostis hyemalis , Agrostis perennans , Elymus virginicus ) collected over the past two centuries (1824–2019) for the presence or absence of Epichloë symbiosis. Analysis of an approximate Bayesian spatially varying coefficients model revealed that endophytes increased in prevalence over the last two centuries from ca. 25% to ca. 75% prevalence, on average, across three host species. Changes in seasonal climate drivers were associated with increasing endophyte prevalence. Notably, increasing precipitation during the peak growing season for Agrostis species and decreasing precipitation for E. virginicus were associated with increasing endophyte prevalence. Changes in the variability of precipitation and temperature during off‐peak seasons were also important predictors of increasing endophyte prevalence. Our model performed favorably in an out‐of‐sample predictive test with contemporary survey data from across 63 populations, a rare extra step in collections‐based research. However, there was greater local‐scale variability in endophyte prevalence in contemporary data compared to model predictions, suggesting new directions that could improve predictive accuracy. Our results provide novel evidence for a cryptic biological response to climate change that may contribute to the resilience of host‐microbe symbiosis through fitness benefits to symbiotic hosts.

Predicting the effects of climate change on plant and animal populations is an urgent challenge for understanding the fate of biodiversity under global change. At the surface, quantifying how climate drives the vital rates that underlie population dynamics appears simple, yet many decisions are required to connect climate to demographic data. Competing approaches have emerged in the literature with little consensus around best practices. Here we provide a practical guide for how to best link vital rates to climate for the purposes of population projection and forecasting. We first describe the sources of demographic and climate data underlying population models. We then focus on best practices to model the relationships between vital rates and climate, highlighting what we can learn from mechanistic and phenomenological models. Finally, we discuss the challenges of prediction and forecasting in the face of uncertainty about climate-demographic relationships as well as future climate. We conclude by suggesting ways forward to build this field of research into one that makes robust forecasts of population persistence, with opportunities for synthesis across species.

Integral projection models (IPMs) are widely used for studying continuously size‐structured populations. IPMs require a growth sub‐model that describes the probability of future size conditional on current size and any covariates. Most IPM studies assume that this distribution is Gaussian, despite calls for non‐Gaussian models that accommodate skewness and excess kurtosis. We provide a general workflow for accommodating non‐Gaussian growth patterns while retaining important covariates and random effects. Our approach emphasizes visual diagnostics from pilot Gaussian models and quantile‐based metrics of skewness and kurtosis that guide selection of a non‐Gaussian alternative, if necessary. Across six case studies, skewness and excess kurtosis were common features of growth data, and non‐Gaussian models consistently generated simulated data that were more consistent with real data than pilot Gaussian models. However, effects of “improved” growth modeling on IPM results were moderate to weak and differed in direction or magnitude between different outputs from the same model. Using tools not available when IPMs were first developed, it is now possible to fit non‐Gaussian models to growth data without sacrificing ecological complexity. Doing so, as guided by careful interrogation of the data, will result in models that better represent the populations for which they are intended.

Mast seeding, the synchronous and highly variable production of seed crops by perennial plants, is a population‐level phenomenon and has cascading effects in ecosystems. Mast seeding studies are typically conducted at the population/species level. Much less is known about synchrony in mast seeding between species because the necessary long‐term data are rarely available. To investigate synchrony between species within communities, we used long‐term data from seven forest communities in the U.S. Long‐Term Ecological Research (LTER) network, ranging from tropical rainforest to boreal forest. We focus on cross‐species synchrony and (i) quantify synchrony in reproduction overall and within LTER sites, (ii) test for relationships between synchrony with trait and phylogenetic similarity and (iii) investigate how climate conditions at sites are related to levels of synchrony. Overall, reproductive synchrony between woody plant species was greater than expected by chance, but spanned a wide range of values between species. Based on 11 functional and reproductive traits for 103 species (plus phylogenetic relatedness), cross‐species synchrony in reproduction was driven primarily by trait similarity with phylogeny being largely unimportant, and synchrony was higher in sites with greater climatic water deficit. Community‐level synchrony in masting has consequences for understanding forest regeneration dynamics and consumer‐resource interactions.

Plants display a range of temporal patterns of inter‐annual reproduction, from relatively constant seed production to “mast seeding,” the synchronized and highly variable interannual seed production of plants within a population. Previous efforts have compiled global records of seed production in long‐lived plants to gain insight into seed production, forest and animal population dynamics, and the effects of global change on masting. Existing datasets focus on seed production dynamics at the population scale but are limited in their ability to examine community‐level mast seeding dynamics across different plant species at the continental scale. We harmonized decades of plant reproduction data for 141 woody plant species across nine Long‐Term Ecological Research (LTER) or long‐term ecological monitoring sites from a wide range of habitats across the United States. Plant reproduction data are reported annually between 1957 and 2021 and based on either seed traps or seed and/or cone counts on individual trees. A wide range of woody plant species including trees, shrubs, and lianas are represented within sites allowing for direct community‐level comparisons among species. We share code for filtering of data that enables the comparison of plot and individual tree data across sites. For each species, we compiled relevant life history attributes (e.g., seed mass, dispersal syndrome, seed longevity, sexual system) that may serve as important predictors of mast seeding in future analyses. To aid in phylogenetically informed analyses, we also share a phylogeny and phylogenetic distance matrix for all species in the dataset. These data can be used to investigate continent‐scale ecological properties of seed production, including individual and population variability, synchrony within and across species, and how these properties of seed production vary in relation to plant species traits and environmental conditions. In addition, these data can be used to assess how annual variability in seed production is associated with climate conditions and how that varies across populations, species, and regions. The dataset is released under a CC0 1.0 Universal public domain license.

Symbiotic associations play a role in plant ecology and evolution, but the outcome of the interaction depends on the life‐history traits of the partners and the environmental context. Although symbiosis with vertically transmitted microorganisms should result in mutualism, it is not clear how the transmission process aligns with the outcome of the context‐dependent symbiosis. For 3 years, we sampled individuals of an annual plant species that forms symbiosis with a vertically transmitted fungal endophyte, in paired stands of two contrasting vegetation communities (humid mesophytic meadows [HMM]: productive/low stress, and humid prairies [HP]: less productive/high stress). We estimated the prevalence of symbiosis at the population level, and the fitness of the plant, the symbiotic status and vertical transmission efficiency at the individual level. Over 3 years, the prevalence of symbiosis was ≈100% in HMM and ≈75% in HP. Plant fitness was very low and high in years with precipitation below and above the yearly mean, respectively. The higher fitness of endophyte‐symbiotic plants was evident in the HMM and high precipitation years. Vertical transmission of endophytes was higher in HMM (≈96%) compared to HP (≈93%) and was not related to plant fitness. Despite transmission inefficiencies in HP, changes in prevalence within the growing season (from seeds to the final plant stand) suggest a fitness advantage for symbiotic plants. Vertical transmission is expected to promote mutualism as it aligns partners' fitness. Although symbiotic plants showed higher fitness and the probability of transmission failures was higher among low‐fitness plants, the variation in transmission efficiency between plants and vegetation communities was not related to the fitness of the individual host. Our study provides evidence that context‐dependent vertical transmission efficiency and endophyte‐mediated fitness advantages interact complexly to determine the prevalence of symbiosis in populations that occur in contrasting vegetation communities. Read the free Plain Language Summary for this article on the Journal blog.

Global warming has triggered an urgent need for predicting the reorganization of Earth’s biodiversity. Currently, the vast majority of models used to forecast population viability and range shifts in response to climate change ignore the complication of sex structure, and thus the potential for females and males to differ in their sensitivity to climate drivers. We developed demographic models of range limitation, parameterized from geographically distributed common garden experiments, with females and males of a dioecious grass species ( Poa arachnifera ) throughout and beyond its range in the south-central U.S. Female-dominant and two-sex model versions both predict that climate change will alter population viability and will induce a poleward niche shift beyond current northern limits. However, the magnitude of niche shift was underestimated by the female-dominant model, because females have broader temperature tolerance than males and become mate-limited under female-biased sex ratios. Our result illustrate how explicit accounting for both sexes could enhance population viability forecasts and conservation planning for dioecious species in response to climate change.

Species’ distributions and abundances are shifting in response to climate change. Most species harbor microbial symbionts that have the potential to influence these responses. Mutualistic microbial symbionts may provide resilience to environmental change by protecting their hosts from increasing stress. However, environmental change that disrupts these interactions may lead to declines in hosts or symbionts. Microbes preserved within herbarium specimens offer a unique opportunity to quantify changes in microbial symbiosis across broad temporal and spatial scales. We asked how the prevalence of seed-transmitted fungal symbionts of grasses (Epichloë endophytes), which can protect hosts from abiotic stress, have changed over time in response to climate change, and how these changes vary across host species’ ranges. Specifically, we analyzed 2,346 herbarium specimens of three grass host species collected over the last two centuries (1824 – 2019) for the presence or absence of endophyte symbiosis, and evaluated spatial and temporal trends in endophyte prevalence. We found that endophytes increased in prevalence over the last two centuries from ca. 25% prevalence to ca. 75% prevalence, on average, across three host species. We also found that changes in prevalence were associated with observed changes in seasonal climate drivers; notably increasing precipitation corresponding to each host species’ peak growing season and changes in off-peak season variability in precipitation. Our analysis performed favorably in an out-of-sample predictive test with contemporary data, however we identified greater local-scale variability in endophyte prevalence in contemporary data compared to historic data, suggesting that model fusion may be an important step moving forward. Our results provide novel evidence for a cryptic biological response to climate change that may contribute to the resilience of host-microbe symbiosis through context-dependent benefits that confer a fitness advantage to symbiotic hosts under environmental change.