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ABSTRACT A core hypothesis in invasion and community ecology is that species interaction patterns should differ between native and non‐native species due to non‐native species lacking a long evolutionary history in their resident communities. Numerous studies testing this hypothesis yield conflicting results, often focusing on mean interaction rates and overlooking the substantial within‐population variability in species interactions. We explored plant‐herbivore interactions in populations of native and established non‐native plant species by quantifying differences in mean herbivory and added a novel approach by comparing within‐population variability in herbivory. We include as covariates latitude, plant richness, plant growth form and cover. Using leaf herbivory data from the Herbivory Variability Network for 788 plant populations spanning 504 species globally distributed, we found no overall differences in mean herbivory or variability between native and non‐native plants. These results suggest native and established non‐native plants interact similarly with herbivores, indicating non‐native status is not a strong predictor of ecological roles. 

The Enemy Release Hypothesis (ERH) proposes that non-native plants escape their co-evolved herbivores and benefit from reduced herbivory in their introduced ranges. Numerous studies have tested this hypothesis, with conflicting results, but previous studies focus on average levels of herbivory and overlook the substantial within-population variability in herbivory, which may provide unique insights into the ERH. We tested differences in mean herbivory and added a novel approach to the ERH by comparing within-population variability in herbivory between native and non-native plant populations. We include several covariates that might mask an effect of enemy release, including latitude, regional plant richness, plant growth form and plant cover. We use leaf herbivory data collected by the Herbivory Variability Network for 788 plant populations (616 native range populations and 172 introduced range populations) of 503 different native and non-native species distributed worldwide. We found no overall differences in mean herbivory or herbivory variability between native and non-native plant populations. Taken together, our results indicate no evidence of enemy release for non-native plants, suggesting that enemy release is not a generalized mechanism favoring the success of non-native species. 

THE ECOLOGICAL QUESTION How have long term changes in climate affected the phenology of wildflowers growing in subalpine habitats? FOUR DIMENSIONAL ECOLOGY EDUCATION (4DEE) FRAMEWORK This is a three-part project. In part I, students research the natural history of one subalpine plant species (e.g., Delphinium nuttallianum, Erigeron speciosus, Helianthella quinquenervis, Lupinus bakeri). In part II, they are given a data set consisting of > 45 years of climate data (1976-2022) from a location where flowering of these plants has been surveyed yearly over that same time period (Rocky Mountain Biological Laboratory in Gothic, CO). The students use the data to graph and analyze trends in snow and temperature and develop hypotheses about how the phenology and fitness (e.g., interactions with pollinators) of their assigned plant species will respond to these changes. In part III, the students receive > 45 years of data on the flowering phenology of their plant species at the same site (1974-2020) and make graphs to test their hypotheses. The students communicate their findings with a written scientific report, conference-style poster, or oral presentation. 

Plants and herbivores are remarkably variable in space and time, and variability has been considered a defining feature of their interactions. Empirical research, however, has traditionally focused on understanding differences in means and overlooked the theoretically significant ecological and evolutionary roles of variability itself. We review the literature with the goal of showing how variability-explicit research expands our perspective on plant–herbivore ecology and evolution. We first clarify terminology for describing variation and then review patterns, causes, and consequences of variation in herbivory across scales of space, time, and biological organization. We consider how incorporating variability improves existing hypotheses and leads to new ones. We conclude by suggesting future work that reports full distributions, integrates effects of variation across scales, describes nonlinearities, and considers how stochastic and deterministic variation combine to determine herbivory distributions. Expected final online publication date for the Annual Review of Ecology, Evolution, and Systematics, Volume 54 is November 2023. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates. 

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. 

Abstract The Rocky Mountain Biological Laboratory (RMBL; Colorado, USA) is the site for many research projects spanning decades, taxa, and research fields from ecology to evolutionary biology to hydrology and beyond. Climate is the focus of much of this work and provides important context for the rest. There are five major sources of data on climate in the RMBL vicinity, each with unique variables, formats, and temporal coverage. These data sources include (1) RMBL resident billy barr, (2) the National Oceanic and Atmospheric Administration (NOAA), (3) the United States Geological Survey (USGS), (4) the United States Department of Agriculture (USDA), and (5) Oregon State University's PRISM Climate Group. Both the NOAA and the USGS have automated meteorological stations in Crested Butte, CO, ~10 km from the RMBL, while the USDA has an automated meteorological station on Snodgrass Mountain, ~2.5 km from the RMBL. Each of these data sets has unique spatial and temporal coverage and formats. Despite the wealth of work on climate‐related questions using data from the RMBL, previous researchers have each had to access and format their own climate records, make decisions about handling missing data, and recreate data summaries. Here we provide a single curated climate data set of daily observations covering the years 1975–2022 that blends information from all five sources and includes annotated scripts documenting decisions for handling data. These synthesized climate data will facilitate future research, reduce duplication of effort, and increase our ability to compare results across studies. The data set includes information on precipitation (water and snow), snowmelt date, temperature, wind speed, soil moisture and temperature, and stream flows, all publicly available from a combination of sources. In addition to the formatted raw data, we provide several new variables that are commonly used in ecological analyses, including growing degree days, growing season length, a cold severity index, hard frost days, an index of El Niño‐Southern Oscillation, and aridity (standardized precipitation evapotranspiration index). These new variables are calculated from the daily weather records. As appropriate, data are also presented as minima, maxima, means, residuals, and cumulative measures for various time scales including days, months, seasons, and years. The RMBL is a global research hub. Scientists on site at the RMBL come from many countries and produce about 50 peer‐reviewed publications each year. Researchers from around the world also routinely use data from the RMBL for synthetic work, and educators around the United States use data from the RMBL for teaching modules. This curated and combined data set will be useful to a wide audience. Along with the synthesized combined data set we include the raw data and the R code for cleaning the raw data and creating the monthly and yearly data sets, which facilitate adding additional years or data using the same standardized protocols. No copyright or proprietary restrictions are associated with using this data set; please cite this data paper when the data are used in publications or scientific events. 

Abstract Phenological distributions are characterized by their central tendency, breadth, and shape, and all three determine the extent to which interacting species overlap in time. Pollination mutualisms rely on temporal co‐occurrence of pollinators and their floral resources, and although much work has been done to characterize the shapes of flower phenological distributions, similar studies that include pollinators are lacking. Here, we provide the first broad assessment of skewness, a component of distribution shape, for a bee community. We compare skewness in bees to that in flowers, relate bee and flower skewness to other properties of their phenology, and quantify the potential consequences of differences in skewness between bees and flowers. Both bee and flower phenologies tend to be right‐skewed, with a more exaggerated asymmetry in bees. Early‐season species tend to be the most skewed, and this relationship is also stronger in bees than in flowers. Based on a simulation experiment, differences in bee and flower skewness could account for up to 14% of pairwise overlap differences. Given the potential for interaction loss, we argue that difference in skewness of interacting species is an underappreciated property of phenological change.