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The encroachment of woody plants into grasslands is a global phenomenon with implications for biodiversity and ecosystem function. Understanding and predicting the pace of expansion and the underlying processes that control it are key challenges in the study and management of woody encroachment. Theory from spatial population biology predicts that the occurrence and speed of expansion should depend sensitively on the nature of conspecific density dependence. If fitness is maximized at the low‐density encroachment edge, then shrub expansion should be “pulled” forward. However, encroaching shrubs have been shown to exhibit positive feedbacks, whereby shrub establishment modifies the environment in ways that facilitate further shrub recruitment and survival. In this case there may be a fitness cost to shrubs at low density causing expansion to be “pushed” from behind the leading edge. We studied the spatial dynamics of creosotebush (Larrea tridentata), which has a history of encroachment into Chihuahuan Desert grasslands over the past century. We used demographic data from observational censuses and seedling transplant experiments to test the strength and direction of density dependence in shrub fitness along a gradient of shrub density at the grass–shrub ecotone. We also used seed‐drop experiments and wind data to construct a mechanistic seed‐dispersal kernel, then connected demography and dispersal data within a spatial integral projection model (SIPM) to predict the dynamics of shrub expansion. Contrary to expectations based on potential for positive feedbacks, the shrub encroachment wave is “pulled” by maximum fitness at the low‐density front. However, the predicted pace of expansion was strikingly slow (ca. 8 cm/year), and this prediction was supported by independent resurveys of the ecotone showing little to no change in the spatial extent of shrub cover over 12 years. Encroachment speed was acutely sensitive to seedling recruitment, suggesting that this population may be primed for pulses of expansion under conditions that are favorable for recruitment. Our integration of observations, experiments, and modeling reveals not only that this ecotone is effectively stalled under current conditions but also why that is so and how that may change as the environment changes.

Understanding mechanisms that generate range limits is central to knowing why species are found where they are and how they will respond to environmental change. There is growing awareness that biotic interactions play an important role in generating range limits. However, current theory and data overwhelmingly focus on abiotic drivers and antagonistic interactions. Here we explore the effect that mutualists have on their partner's range limits: the geographic “footprint” of mutualism. This footprint arises from two general processes: modification of a partner's niche through environment‐dependent fitness effects and, for a subset of mutualisms, dispersal opportunities that lead suitable habitats to be filled. We developed a conceptual framework that organizes different footprints of mutualism and the underlying mechanisms that shape them, and evaluated supporting empirical evidence from the primary literature. In the available literature, we found that the fitness benefits and dispersal opportunities provided by mutualism can extend species' ranges; conversely, the absence of mutualism can constrain species from otherwise suitable regions of their range. Most studies found that the footprint of mutualism is driven by changes in the frequency of mutualist partners from range core to range edge, whereas fewer found changes in interaction outcomes, the diversity of partners, or varying sensitivities of fitness to the effects of mutualists. We discuss these findings with respect to specialization, dependence, and intimacy of mutualism. Much remains unknown about the geographic footprint of mutualisms, leaving fruitful areas for future work. A particularly important future direction is to explore the role of mutualism during range shifts under global change, including the promotion of shifts at leading edges and persistence at trailing edges.

Mutualism benefits partner species, and theory predicts these partnerships can affect the abundance, diversity, and composition of partner and non‐partner species. We used 16 years of monitoring data to determine the ant partner species of tree cholla cacti (Cylindropuntia imbricata), which reward ants with extrafloral nectar in exchange for anti‐herbivore defense. These long‐term data revealed one dominant ant partner (Liometopum apiculatum) and two less common partners (Crematogaster opuntiaeandForelius pruinosus). We then used short‐term characterization of the terrestrial ant community by pitfall trapping to sample partner and non‐partner ant species across ten plots of varying cactus density. We found that the dominant ant partner tended a higher proportion cacti in plots of higher cactus density, and was also found at higher occurrence within the pitfall traps in higher density plots, suggesting a strong positive feedback that promotes ant partner occurrence where plant partners are available. Despite the strong association and increased partner occurrence, ant community‐wide effects from this mutualism appear limited. Of the common ant species, the occurrence of a single non‐partner ant species was negatively associated with cactus density and with the increased presence ofL. apiculatum. Additionally, the composition and diversity of the ant community in our plots were insensitive to cactus density variation, indicating that positive effects of the mutualism on the dominant ant partner did not have cascading impacts on the ant community. This study provides novel evidence that exclusive mutualisms, even those with a strong positive feedback, may be limited in the scope of their community‐level effects.

The effects of climate change on population viability reflect the net influence of potentially diverse responses of individual‐level demographic processes (growth, survival, regeneration) to multiple components of climate. Articulating climate–demography connections can facilitate forecasts of responses to future climate change as well as back‐casts that may reveal how populations responded to historical climate change.

Although rarely experimentally tested, biotic interactions have long been hypothesised to limit low‐elevation range boundaries of species. We tested the effects of herbivory on three alpine‐restricted plant species by transplanting plants below (novel), at the edge (limit), or in the centre (core) of their current elevational range and factorially fencing‐out above‐ and belowground mammals. Herbivore damage was greater in range limit and novel habitats than in range cores. Exclosures increased plant biomass and reproduction more in novel habitats than in range cores, suggesting demographic costs of novel interactions with herbivores. We then used demographic models to project population growth rates, which increased 5–20% more under herbivore exclosure at range limit and novel sites than in core habitats. Our results identify mammalian herbivores as key drivers of the low‐elevation range limits of alpine plants and indicate that upward encroachment of herbivores could trigger local extinctions by depressing plant population growth.

Heritable symbionts are often observed at intermediate prevalence within host populations, despite expectations that positive fitness feedbacks should drive beneficial symbionts to fixation. Intermediate prevalence may reflect neutral dynamics of symbionts with weak fitness effects, transient dynamics of symbionts trending towards fixation (or elimination), or a stable intermediate outcome determined by the balance of fitness effects and failed symbiont transmission. Theory suggests that these outcomes should depend on symbiont‐conferred demographic effects and vertical transmission efficiency, which may both depend on environmental context.

Extensive ecological research has investigated extreme climate events or long‐term changes in average climate variables, but changes in year‐to‐year (interannual) variability may also cause important biological responses, even if the mean climate is stable. The environmental stochasticity that is a hallmark of climate variability can trigger unexpected biological responses that include tipping points and state transitions, and large differences in weather between consecutive years can also propagate antecedent effects, in which current biological responses depend on responsiveness to past perturbations. However, most studies to date cannot predict ecological responses to rising variance because the study of interannual variance requires empirical platforms that generate long time series. Furthermore, the ecological consequences of increases in climate variance could depend on the mean climate in complex ways; therefore, effective ecological predictions will require determining responses to both nonstationary components of climate distributions: the mean and the variance. We introduce a new design to resolve the relative importance of, and interactions between, a drier mean climate and greater climate variance, which are dual components of ongoing climate change in the southwestern United States. The Mean × Variance Experiment (MVE) adds two novel elements to prior field infrastructure methods: (1) factorial manipulation of variance together with the climate mean and (2) the creation of realistic, stochastic precipitation regimes. Here, we demonstrate the efficacy of the experimental design, including sensor networks and PhenoCams to automate monitoring. We replicated MVE across ecosystem types at the northern edge of the Chihuahuan Desert biome as a central component of the Sevilleta Long‐Term Ecological Research Program. Soil sensors detected significant treatment effects on both the mean and interannual variability in soil moisture, and PhenoCam imagery captured change in vegetation cover. Our design advances field methods to newly compare the sensitivities of populations, communities, and ecosystem processes to climate mean × variance interactions.

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 makea priorichoices. In this study, we first synthesize the literature to assess currenta priorichoices 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, andCryptantha 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.

Population dynamics play a central role in the historical and current development of fundamental and applied ecological science. The nascent culture of open data promises to increase the value of population dynamics studies to the field of ecology. However, synthesis of population data is constrained by the difficulty in identifying relevant datasets, by the heterogeneity of available data and by access to raw (as opposed to aggregated or derived) observations.

Despite a global footprint of shifts in flowering phenology in response to climate change, the reproductive consequences of these shifts are poorly understood. Furthermore, it is unknown whether altered flowering times affect plant population viability.