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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. 

Local density can affect individual performance by altering the strength of species interactions. Within many populations, local densities vary spatially (individuals are patchily distributed) or change across life stages, which should influence the selection and eco‐evolutionary feedback because local density variance affects mean fitness and is affected by traits of individuals. However, most studies on the evolutionary consequences of density‐dependent interactions focus on populations where local densities are relatively constant through time and space.

We investigated the influence of spatial and ontogenetic variance in local densities within an insect population by comparing a model integrating both types of local density variance with models including only spatial variance, only ontogenetic variance, or no variance. We parameterized the models with experimental data, then used elasticity and invasion analyses to characterize selection on traits that affect either the local density an individual experiences (mean clutch size) or individuals' sensitivity to density (effect of larval crowding on pupal mass).

Spatial and ontogenetic variance reduced population elasticity to effects of local density by 76% and 34% on average, respectively.

Spatial variance modified selection and adaptive dynamics by altering the tradeoff between density‐dependent and density‐independent vital rates. In models including spatial variance, strategies that maximized density‐dependent survival were favoured over fecundity‐maximizing strategies even at low population density, counter to predictions of density‐dependent selection theory. Furthermore, only models that included spatial variance, thus linking the scales of oviposition and density‐dependent larval survival, had an evolutionarily stable clutch size.

Ontogenetic variance weakened selection on mean clutch size and sensitivity to larval crowding by disrupting the relationship between trait values and performance during critical life stages.

We demonstrate that local density variance can strongly modify selection at empirically observed interaction strengths and identify mechanisms for the effects of spatial and ontogenetic variance. Our findings reveal the potential for local density variance to mediate eco‐evolutionary feedback by shaping selection on demographically important traits.

Read the freePlain Language Summaryfor this article on the Journal blog.

 

Flowering phenology can vary considerably even at fine spatial scales, potentially leading to temporal reproductive isolation among habitat patches. Climate change could alter flowering synchrony, and hence temporal isolation, if plants in different microhabitats vary in their phenological response to climate change. Despite the importance of temporal isolation in determining patterns of gene flow, and hence population genetic structure and local adaptation, little is known about how changes in climate affect temporal isolation within populations.

Here, we use flowering phenology and floral abundance data of 50 subalpine plant species over 44 years to test whether temporal isolation between habitat patches is affected by spring temperature. For each species and year, we analysed temporal separation in peak flowering and flowering overlap between habitat patches separated by 5–950 m.

Across our study species, warmer springs were associated with more temporal differentiation in flowering peaks among habitat patches, and less flowering overlap, increasing potential for temporal isolation within populations.

Synthesis. By reducing opportunities for mating among plants in nearby habitat patches, our results suggest that warmer springs may reduce opportunities for gene flow within populations, and, consequently, the capacity of plant populations to adapt to environmental changes.

 

Recent reports of insect declines have caused concern among scientists and the public. Declines in insect abundance and biomass are ubiquitous across many climatic zones and have been largely attributed to anthropogenic land use intensification and climate change. However, there are few examples of long‐term continuous data in relatively undisturbed environments, as opposed to agricultural landscapes. We sampled insects weekly from 1986 to 2020 in a protected subalpine meadow in Colorado, which is embedded in an undisturbed natural landscape. During the study period, summers became warmer, while winters became drier. Insect biomass declined by ∼47% and abundance declined by ∼61.5% over the last 35 years. Insect declines occurred in concert with changes in climate, as some climate factors were correlated with insect abundance and biomass. Specifically, insect abundance was lower during years with less summer precipitation and winter snowfall, and to a lesser degree with warmer temperatures. In subalpine systems, changes in precipitation and warmer temperatures are expected to continue under climate change; thus, continued insect declines might be expected even in relatively undisturbed habitats.

 

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.

 

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. 

Consumer‐resource interactions are often influenced by other species in the community, such as when neighbouring plants increase or reduce herbivory to a focal plant species (known as associational effects). The many studies on associational effects between a focal plant and some neighbour have shown that these effects can vary greatly in strength and direction. But because almost all of these studies measure associational effects from only one or two neighbour species, we know little about the actual range of associational effects that a plant species might encounter in a natural setting. This makes it difficult to determine how important effects of neighbours are in real field settings, and how associational effects might interact with competition and other processes to influence plant community composition.

In this study, we used a field experiment with a focal species,Solanum carolinense, and 11 common neighbour species to investigate how associational effects vary among many co‐occurring neighbour species and to test whether factors such as neighbour plant apparency, phylogenetic proximity to the focal species, or effects on focal plant defence traits help to explain interspecific variation in associational effect strength.

We found that some neighbour species affectedS. carolinensedamage and attack by specialist herbivores, but associational effects of most neighbours were weak. Associational effects increased herbivore attack on average earlier in the season (associational susceptibility) and reduced herbivore attack on average later in the season (associational resistance) relative toS. carolinensein monoculture.

We found some evidence that a neighbour's associational effect was related to its biomass and phylogenetic proximity to the focal species. While neighbour species differed in their effects on physical leaf traits of focal plants (trichome density, specific leaf area, and leaf toughness), these traits did not appear to mediate the effects of neighbours on focal plant herbivory.

Synthesis. Our results suggest that the distribution of associational effect strengths in natural communities are similar to those observed for other interaction types, and that multiple mechanisms are likely acting simultaneously to shape associational effects of different neighbour species.

 

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.