Resurrecting Historical Observations to Characterize Species-Specific Nesting Traits of Bumblebees.

AbstractIn recent years, ecological research has become increasingly synthetic, relying on revolutionary changes in data availability and accessibility. In spite of their strengths, these approaches may cause us to overlook natural history knowledge that is not part of the digitized English-language scientific record. Here, we combine historic and modern documents to quantify species-specific nesting habitat associations of bumblebees (Bombus spp. Latreille, 1802 Apidae). We compiled nest location data from 316 documents, of which 81 were non-English and 93 were published before 1950. We tested whether nesting traits show phylogenetic signal, examined relationships between habitat associations at different scales, and compared methodologies used to locate nests. We found no clear phylogenetic signals, but we found that nesting habitat associations were somewhat generalizable within subgenera. Landcover associations were related to nesting substrate associations; for example, surface-nesting species also tended to be associated with grasslands. Methodology was associated with nest locations; community scientists were most likely and researchers using nest boxes were least likely to report nests in human-dominated environments. These patterns were not apparent in past syntheses based only on the modern digital record. Our findings highlight the tremendous value of historic accounts for quantifying species' traits and other basic biological knowledge needed to interpret global-scale patterns.

Evolutionary ecology of masting: mechanisms, models, and climate change.

Many perennial plants show mast seeding, characterized by synchronous and highly variable reproduction across years. We propose a general model of masting, integrating proximate factors (environmental variation, weather cues, and resource budgets) with ultimate drivers (predator satiation and pollination efficiency). This general model shows how the relationships between masting and weather shape the diverse responses of species to climate warming, ranging from no change to lower interannual variation or reproductive failure. The role of environmental prediction as a masting driver is being reassessed; future studies need to estimate prediction accuracy and the benefits acquired. Since reproduction is central to plant adaptation to climate change, understanding how masting adapts to shifting environmental conditions is now a central question.

Caterpillar movement mediates spatially local interactions and determines the relationship between population density and contact.

BACKGROUND: While interactions in nature are inherently local, ecological models often assume homogeneity across space, allowing for generalization across systems and greater mathematical tractability. Density-dependent disease models are a prominent example of models that assume homogeneous interactions, leading to the prediction that disease transmission will scale linearly with population density. In this study, we examined how the scale of larval butterfly movement interacts with the resource landscape to influence the relationship between larval contact and population density in the Baltimore checkerspot (Euphydryas phaeton). Our study was inspired by the recent discovery of a viral pathogen that is transmitted horizontally among Baltimore checkerspot larvae. METHODS: We used multi-year larvae location data across six Baltimore checkerspot populations in the eastern U.S. to test whether larval nests are spatially clustered. We then integrated these spatial data with larval movement data in different resource contexts to investigate whether heterogeneity in spatially local interactions alters the assumed linear relationship between larval nest density and contact. We used Correlated Random Walk (CRW) models and field observations of larval movement behavior to construct Probability Distribution Functions (PDFs) of larval dispersal, and calculated the overlap in these PDFs to estimate conspecific contact within each population. RESULTS: We found that all populations exhibited significant spatial clustering in their habitat use. Subsequent larval movement rates were influenced by encounters with host plants and larval age, and under many movement scenarios, the scale of predicted larval movement was not sufficient to allow for the "homogeneous mixing" assumed in density dependent disease models. Therefore, relationships between population density and larval contact were typically non-linear. We also found that observed use of available habitat patches led to significantly greater contact than would occur if habitat use were spatially random. CONCLUSIONS: These findings strongly suggest that incorporating larval movement and spatial variation in larval interactions is critical to modeling disease outcomes in E. phaeton. Epidemiological models that assume a linear relationship between population density and larval contact have the potential to underestimate transmission rates, especially in small populations that are already vulnerable to extinction.

Novel host plant use by a specialist insect depends on geographic variation in both the host and herbivore species.

Understanding the circumstances under which insect herbivores will adopt a novel host plant is a longstanding question in basic and applied ecology. While geographic variation in host use can arise through differences in both herbivore preference and plant characteristics, there is a tendency to attribute geographic variation in host use to regional differences in herbivore preference alone. This is especially true for herbivores specialized to one or a few plant species. We compared how geographic variation in herbivore preference and host plant origin shape regional differences in host plant use by the specialized herbivore, Euphydryas phaeton. In parts of its range, E. phaeton uses only a native host, Chelone glabra, while in others, it also uses an introduced host, Plantago lanceolata. We offered female butterflies from each region the non-native host plant sourced from both regions and compared their oviposition behavior. The non-native host was almost universally rejected by butterflies in the region where only the native plant is used. In the region where butterflies use both hosts, females accepted non-native plants from their natal region twice as often as non-native plants from the other region where they are not used. Acceptance differed substantially among individual butterflies within regions but not among plants within regions. Thus, both individual preference and regional differences in both the insect and non-native host contributed to the geographic variation in different ways. These results highlight that, in addition to herbivore preference, regional differences in perceived plant suitability may be an important driver of diet breadth.

Using community science to map western monarch butterflies (Danaus plexippus) in spring.

Migratory animals follow seasonal cycles comprising linked phases often with different habitat requirements and demographic processes. Conservation of migratory species therefore must consider the full seasonal cycle to identify points limiting population viability. For western monarch butterflies, which have experienced significant declines, early spring is considered a critical period in the annual population cycle. However, records of western monarchs in early spring, when overall abundance is lowest, have historically been extremely limited. We used a community science initiative, the Western Monarch Mystery Challenge, to collect data on monarch distribution throughout the western United States between February 14th and April 22nd over 3 years. Using data from the Western Monarch Mystery Challenge and iNaturalist, we identified potential breeding habitat for western monarchs in early spring that spanned a large geographic area and several ecoregions. We observed monarchs in early spring that likely eclosed in the current year, suggesting that population expansion from overwintering sites reflects both movement and population growth. The number of records of western monarchs from early spring was higher during the Mystery Challenge (33.0/year) than earlier years (5.1/year). This study demonstrates the potential for and limitations of community science to increase our understanding of species at points in the life cycle when they are rare.

First field-based estimates of bumblebee diapause survival rates showcase high survivorship in the wild.

Abstract: Bumblebee (Bombus spp.) queens overwintered in artificial settings tend to have low survival rates, raising concerns that diapause may be a particularly sensitive life cycle stage for this ecologically and economically valuable group of pollinators. However, it remains unclear whether lab-based estimates of diapause survival are comparable to survival rates of natural populations. In this study, we monitored the survival of Bombus impatiens queens overwintering in the field in Ipswich, MA, and conducted a meta-analysis of studies that estimate queen diapause survival in the lab to compare our field-based estimates of survival to those of lab-based studies. We found that queen B. impatiens had relatively high rates of overwintering survival after about six months (> 60%), especially when compared to estimates of six-month survival from lab studies (< 10%). We also observed a trend that broadly corroborates many lab studies of bumblebees, in that overwinter survival of queens was related to colony origin. In addition to providing the first estimate of diapause survival for bumblebee queens in nature, our study emphasizes the need to verify patterns observed in the lab to field-based studies. Implications for insect conservation: Although protecting target species during sensitive life cycle stages is a fundamental goal of conservation ecology, it is first necessary to identify at what stages of the life cycle populations are most vulnerable. Our results suggest that, at least in some study systems, diapause survival of queen bumblebees in the field may be higher than suggested by lab studies. Supplementary Information: The online version contains supplementary material available at 10.1007/s10841-023-00478-8.

Ecological traits explain long-term phenological trends in solitary bees.

Across taxa, the timing of life-history events (phenology) is changing in response to warming temperatures. However, little is known about drivers of variation in phenological trends among species. We analysed 168 years of museum specimen and sighting data to evaluate the patterns of phenological change in 70 species of solitary bees that varied in three ecological traits: diet breadth (generalist or specialist), seasonality (spring, summer or fall) and nesting location (above-ground or below-ground). We estimated changes in onset, median, end and duration of each bee species' annual activity (flight duration) using quantile regression. To determine whether ecological traits could explain phenological trends, we compared average trends across species groups that differed in a single trait. We expected that specialist bees would be constrained by their host plants' phenology and would show weaker phenological change than generalist species. We expected phenological advances in spring and delays in summer and fall. Lastly, we expected stronger shifts in above-ground versus below-ground nesters. Across all species, solitary bees have advanced their phenology by 0.43 days/decade. Since 1970, this advancement has increased fourfold to 1.62 days/decade. Solitary bees have also lengthened their flight period by 0.44 days/decade. Seasonality and nesting location explained variation in trends among species. Spring- and summer-active bees tended to advance their phenology, whereas fall-active bees tended to delay. Above-ground nesting species experienced stronger advances than below-ground nesting bees in spring; however, the opposite was true in summer. Diet breadth was not associated with patterns of phenological change. Our study has two key implications. First, an increasing activity period of bees across the flight season means that bee communities will potentially provide pollination services for a longer period of time during the year. And, since phenological trends in solitary bees can be explained by some ecological traits, our study provides insight into mechanisms underpinning population viability of insect pollinators in a changing world.

The contribution of plant spatial arrangement to bumble bee flower constancy.

Floral constancy of foraging bees influences plant reproduction. Constancy as observed in nature arises from at least four distinct mechanisms frequently confounded in the literature: context-independent preferences for particular plant species, preferential visitation to the same species as the previous plant visited (simple constancy), the spatial arrangement of plants, and the relative abundances of co-flowering species. To disentangle these mechanisms, we followed individual bee flight paths within patches where all flowering plants were mapped, and we used step selection models to estimate how each mechanism influences the probability of selecting any particular plant given the available plants in a multi-species community. We found that simple constancy was positive: bees preferred to visit the same species sequentially. In addition, bees preferred to travel short distances and maintain their direction of travel between plants. After accounting for distance, we found no significant effect of site-level plant relative abundances on bee foraging choices. To explore the importance of the spatial arrangement of plants for bee foraging choices, we compared our full model containing all parameters to one with spatial arrangement removed. Due to bees' tendency to select nearby plants, combined with strong intraspecific plant clumping, spatial arrangement was responsible for about 50% of the total observed constancy. Our results suggest that floral constancy may be overestimated in studies that do not account for the spatial arrangement of plants, especially in systems with intraspecific plant clumping. Plant spatial patterns at within-site scales are important for pollinator foraging behavior and pollination success.

Phenotypic plasticity masks range-wide genetic differentiation for vegetative but not reproductive traits in a short-lived plant.

Genetic differentiation and phenotypic plasticity jointly shape intraspecific trait variation, but their roles differ among traits. In short-lived plants, reproductive traits may be more genetically determined due to their impact on fitness, whereas vegetative traits may show higher plasticity to buffer short-term perturbations. Combining a multi-treatment greenhouse experiment with observational field data throughout the range of a widespread short-lived herb, Plantago lanceolata, we (1) disentangled genetic and plastic responses of functional traits to a set of environmental drivers and (2) assessed how genetic differentiation and plasticity shape observational trait-environment relationships. Reproductive traits showed distinct genetic differentiation that largely determined observational patterns, but only when correcting traits for differences in biomass. Vegetative traits showed higher plasticity and opposite genetic and plastic responses, masking the genetic component underlying field-observed trait variation. Our study suggests that genetic differentiation may be inferred from observational data only for the traits most closely related to fitness.

Resilience or Catastrophe? A possible state change for monarch butterflies in western North America.

In the western United States, the population of migratory monarch butterflies is on the brink of collapse, having dropped from several million butterflies in the 1980s to ~2000 butterflies in the winter of 2020-2021. At the same time, a resident (non-migratory) monarch butterfly population in urban gardens has been growing in abundance. The new resident population is not sufficient to make up for the loss of the migratory population; there are still orders of magnitude fewer butterflies now than in the recent past. The resident population also probably lacks the demographic capacity to expand its range inland during summer months. Nonetheless, the resident population may have the capacity to persist. This sudden change emphasises the extent to which environmental change can have unexpected consequences, and how quickly these changes can happen. We hope it will provoke discussion about how we define resilience and viability in changing environments.

Larger workers outperform smaller workers across resource environments: An evaluation of demographic data using functional linear models.

Behavior and organization of social groups is thought to be vital to the functioning of societies, yet the contributions of various roles within social groups toward population growth and dynamics have been difficult to quantify. A common approach to quantifying these role-based contributions is evaluating the number of individuals conducting certain roles, which ignores how behavior might scale up to effects at the population-level. Manipulative experiments are another common approach to determine population-level effects, but they often ignore potential feedbacks associated with these various roles.Here, we evaluate the effects of worker size distribution in bumblebee colonies on worker production in 24 observational colonies across three environments, using functional linear models. Functional linear models are an underused correlative technique that has been used to assess lag effects of environmental drivers on plant performance. We demonstrate potential applications of this technique for exploring high-dimensional ecological systems, such as the contributions of individuals with different traits to colony dynamics.We found that more larger workers had mostly positive effects and more smaller workers had negative effects on worker production. Most of these effects were only detected under low or fluctuating resource environments suggesting that the advantage of colonies with larger-bodied workers becomes more apparent under stressful conditions.We also demonstrate the wider ecological application of functional linear models. We highlight the advantages and limitations when considering these models, and how they are a valuable complement to many of these performance-based and manipulative experiments.

Comparing demography inferred from age vs. stage in a perennial plant.

Life history theories analyze and predict variation in vital rates, such as survival and reproduction, based on age. The age-from-stage method to derive age-specific vital rates from stage data was developed because age-specific data are rarely obtained for plants. Age-specific vital rates derived by this method might underestimate effects of age on vital rates, because the models assume that vital rates do not vary within stage classes. Consequently, population models and life history summaries relying on these vital rates could be biased against detecting senescence. Here, we perform a comparative study of methods to estimate age-specific vital rates using monitoring data with known age and stage. We derived age-, stage-, and age-and-stage-specific vital rates with demographic data from a long-lived perennial, Silene spaldingii. Then, we derived three age-specific population matrix models (age, age-from-stage, and age-and-stage). For each model, we derived life history summaries commonly used in ecology: population growth rate, net reproductive value, relative reproductive values, stable age distribution, generation time, and sensitivity and elasticity of population growth rate. Many vital rates depended on both age and stage in S. spaldingii. However, this species does not senesce; in fact, the number of flowers increased with age. As expected, the age-from-stage method was not able to accurately recreate the age dependence in some life history summaries, such as relative reproductive value. The age-from-stage model suggested faster reproductive dynamics in S. spaldingii than the models based on known age, i.e., plants started to reproduce earlier, and fertility remained constant thereafter, which may lead to biased predictions about evolutionary consequences of age-dependent life history traits. However, population growth rate, generation time, and net reproductive rate did not differ significantly among the models. Our study demonstrated that some metrics are robust to imprecision in model structure, while others are more sensitive. In spite of these biases, this case study provides another example of the diversity of aging patterns in plants. Age can be essential information when studying senescence in plants, but demographic metrics that were not about age per se were similar across model structures.

Using the right tool for the job: the difference between unsupervised and supervised analyses of multivariate ecological data.

Ecologists often collect data with the aim of determining which of many variables are associated with a particular cause or consequence. Unsupervised analyses (e.g. principal components analysis, PCA) summarize variation in the data, without regard to the response. Supervised analyses (e.g., partial least squares, PLS) evaluate the variables to find the combination that best explain a causal relationship. These approaches are not interchangeable, especially when the variables most responsible for a causal relationship are not the greatest source of overall variation in the data-a situation that ecologists are likely to encounter. To illustrate the differences between unsupervised and supervised techniques, we analyze a published dataset using both PCA and PLS and compare the questions and answers associated with each method. We also use simulated datasets representing situations that further illustrate differences between unsupervised and supervised analyses. For simulated data with many correlated variables that were unrelated to the response, PLS was better than PCA at identifying which variables were associated with the response. There are many applications for both unsupervised and supervised approaches in ecology. However, PCA is currently overused, at least in part because supervised approaches, such as PLS, are less familiar.

Changes in flight period predict trends in abundance of Massachusetts butterflies.

Phenological shifts are well-documented in the ecological literature. However, their significance for changes in demography and abundance is less clear. We used 27 years of citizen science monitoring to quantify trends in phenology and relative abundance across 89 butterfly species. We calculated shifts in phenology using quantile regression and shifts in relative abundance using list length analysis and counts from field trips. Elongated activity periods within a year were the strongest predictor of increases in relative abundance. These changes may be driven in part by changes in voltinism, as this association was stronger in multivoltine species. Some species appear to be adding a late-season generation, whereas other species appear to be adding a spring generation, revealing a possible shift from vagrant to resident. Our results emphasise the importance of evaluating phenological changes throughout species' flight period and understanding the consequences for such climate-related changes on viability or population dynamics.

Flowering synchrony drives reproductive success in a wind-pollinated tree.

Synchronised and quasi-periodic production of seeds by plant populations, known as masting, is implicated in many ecological processes, but how it arises remains poorly understood. Flowering and pollination dynamics are hypothesised to provide the mechanistic link for the observed relationship between weather and population-level seed production. We report the first experimental test of the phenological synchrony hypotheses as a driver of pollen limitation in mast seeding oaks (Quercus ilex). Higher flowering synchrony yielded greater pollination efficiency, which resulted in 2-fold greater seed set in highly synchronised oaks compared to asynchronous individuals. Pollen addition removed the negative effect of asynchronous flowering on seed set. Because phenological synchrony operates through environmental variation, this result suggests that oak masting is synchronised by exogenous rather than endogenous factors. It also points to a mechanism by which changes in flowering phenology can affect plant reproduction of mast-seeding plants, with subsequent implications for community dynamics.

Does masting scale with plant size? High reproductive variability and low synchrony in small and unproductive individuals.

BACKGROUND AND AIMS: In a range of plant species, the distribution of individual mean fecundity is skewed and dominated by a few highly fecund individuals. Larger plants produce greater seed crops, but the exact nature of the relationship between size and reproductive patterns is poorly understood. This is especially clear in plants that reproduce by exhibiting synchronized quasi-periodic variation in fruit production, a process called masting. METHODS: We investigated covariation of plant size and fecundity with individual-plant-level masting patterns and seed predation in 12 mast-seeding species: Pinus pinea, Astragalus scaphoides, Sorbus aucuparia, Quercus ilex, Q. humilis, Q. rubra, Q. alba, Q. montana, Chionochloa pallens, C. macra, Celmisia lyallii and Phormium tenax. KEY RESULTS: Fecundity was non-linearly related to masting patterns. Small and unproductive plants frequently failed to produce any seeds, which elevated their annual variation and decreased synchrony. Above a low fecundity threshold, plants had similar variability and synchrony, regardless of their size and productivity. CONCLUSIONS: Our study shows that within-species variation in masting patterns is correlated with variation in fecundity, which in turn is related to plant size. Low synchrony of low-fertility plants shows that the failure years were idiosyncratic to each small plant, which in turn implies that the small plants fail to reproduce because of plant-specific factors (e.g. internal resource limits). Thus, the behaviour of these sub-producers is apparently the result of trade-offs in resource allocation and environmental limits with which the small plants cannot cope. Plant size and especially fecundity and propensity for mast failure years play a major role in determining the variability and synchrony of reproduction in plants.

Global gene flow releases invasive plants from environmental constraints on genetic diversity.

When plants establish outside their native range, their ability to adapt to the new environment is influenced by both demography and dispersal. However, the relative importance of these two factors is poorly understood. To quantify the influence of demography and dispersal on patterns of genetic diversity underlying adaptation, we used data from a globally distributed demographic research network comprising 35 native and 18 nonnative populations of Plantago lanceolata Species-specific simulation experiments showed that dispersal would dilute demographic influences on genetic diversity at local scales. Populations in the native European range had strong spatial genetic structure associated with geographic distance and precipitation seasonality. In contrast, nonnative populations had weaker spatial genetic structure that was not associated with environmental gradients but with higher within-population genetic diversity. Our findings show that dispersal caused by repeated, long-distance, human-mediated introductions has allowed invasive plant populations to overcome environmental constraints on genetic diversity, even without strong demographic changes. The impact of invasive plants may, therefore, increase with repeated introductions, highlighting the need to constrain future introductions of species even if they already exist in an area.

Developmental trap or demographic bonanza? Opposing consequences of earlier phenology in a changing climate for a multivoltine butterfly.

A rapidly changing climate has the potential to interfere with the timing of environmental cues that ectothermic organisms rely on to initiate and regulate life history events. Short-lived ectotherms that exhibit plasticity in their life history could increase the number of generations per year under warming climate. If many individuals successfully complete an additional generation, the population experiences an additional opportunity to grow, and a warming climate could lead to a demographic bonanza. However, these plastic responses could become maladaptive in temperate regions, where a warmer climate could trigger a developmental pathway that cannot be completed within the growing season, referred to as a developmental trap. Here we incorporated detailed demography into commonly used photothermal models to evaluate these demographic consequences of phenological shifts due to a warming climate on the formerly widespread, multivoltine butterfly (Pieris oleracea). Using species-specific temperature- and photoperiod-sensitive vital rates, we estimated the number of generations per year and population growth rate over the set of climate conditions experienced during the past 38 years. We predicted that populations in the southern portion of its range have added a fourth generation in recent years, resulting in higher annual population growth rates (demographic bonanzas). We predicted that populations in the Northeast United States have experienced developmental traps, where increases in the thermal window initially caused mortality of the final generation and reduced growth rates. These populations may recover if more growing degree days are added to the year. Our framework for incorporating detailed demography into commonly used photothermal models demonstrates the importance of using both demography and phenology to predict consequences of phenological shifts.

Why are monarch butterflies declining in the West? Understanding the importance of multiple correlated drivers.

Understanding the factors associated with declines of at-risk species is an important first step in setting management and recovery targets. This step can be challenging when multiple aspects of climate and land use are changing simultaneously, and any or all could be contributing to population declines. We analyzed population trends of monarch butterflies in western North America in relation to likely environmental drivers. Unlike the larger eastern monarch population, past analyses of western monarchs have only evaluated the importance of climate (i.e., not land use) factors as drivers of abundance. We used partial least squares regression (PLSR) to evaluate the potential importance of changes in land use and climate variables. Trends in western monarch abundance were more strongly associated with land use variables than climate variables. Conclusions about importance of climate and land use variables were robust to changes in PLSR model structure. However, individual variables were too collinear to unambiguously separate their effects. We compared these conclusions to the more widely used technique of multiple regression, followed by multi-model inference (MRMI). Naïve interpretation of MRMI results could be misleading, if collinearity were not taken into account. MRMI was also highly sensitive to variation in model construction. Our results suggest a two-pronged approach to monarch conservation, specifically, starting efforts now to restore habitat, while also using experiments to more clearly delineate separate effects of climate and land use factors. They also demonstrate the utility of PLSR, a technique that is growing in use but is still relatively under-appreciated in conservation biology.