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Self-efficacy is an important measure in science education as it is predictive of persistence and success in science, technology, engineering, and mathematics (STEM) courses and is an influential factor in students’ decisions to major in STEM fields. It is unclear what effect active teaching strategies have on students’ self-efficacy, which is typically measured with a pretest at the beginning of the semester and a post-test at the end of the semester. To better understand what happens to self-efficacy over the course of an actively taught physics class, in addition to the typical pretest and post-test, we used a reflective pretest. At the end of the semester, we asked students to reflect on their abilities at the beginning of the semester and we compared this “reflective” self-efficacy to both their presemester and postsemester self-efficacy. We found that students’ reflective self-efficacy was systematically lower than their self-efficacy at the beginning of the semester. Interviews reveal that discrepancies between presemester self-efficacy and reflective self-efficacy are the result of response-shift bias. Because of students’ limited experience with active learning environments, response-shift bias makes it difficult to accurately measure students’ change in self-efficacy over the semester of an actively taught physics course. We conclude that reflective pretests in combination with interviews can help educators and researchers understand if changes in self-efficacy are being masked by response-shift bias.

No contexto das disciplinas introdutórias de Física em nível superior, o modelo de transmissão de informação em aulas expositivas continua predominante, apesar de seus resultados inferiores, em comparação a metodologias ativas de ensino. No presente artigo, apresentamos uma metodologia ativa vinculada à Aprendizagem Baseada em Projetos, criada no contexto da disciplina Applied Physics 50 (AP50) da Universidade de Harvard, explicitando seus princípios pedagógicos, técnicas e estratégias como estímulo para reflexão sobre possibilidades de reinvenção do ensino de Física em nível introdutório, consideradas as especificidades de cada contexto educacional.

Self-efficacy represents an individual’s belief that he or she can perform a particular task in a given domain. It is a strong predictor for performance and persistence in STEM education. Research shows that there is a large and persistent gender gap in student self-efficacy in STEM academic disciplines. In some cases, active teaching strategies have been shown to positively affect physics self-efficacy but it is unclear how this impact differs between men and women. In this study, we investigate the impact of a physics class taught with active teaching strategies on students’ self-reported physics self-efficacy and how this impact varies across gender lines. We measured the change in physics self-efficacy over four different dimensions; conceptual understanding, problem-solving, lab and hands-on activities, and collaborative work. We report three main findings. First, the initial physics self-efficacy gender gap disappeared by the end of the semester. Second, female students’ self-efficacy improved significantly, whereas there was no significant change in the self-efficacy of the male students. Third, the gender gaps in the conceptual understanding and problem-solving dimensions in particular, were significantly reduced. This study represents an initial step towards understanding the influence of active teaching strategies can have on reducing the self-efficacy gender gap.

Although confusion is generally perceived to be negative, educators dating as far back as Socrates, who asked students to question assumptions and wrestle with ideas, have challenged this notion. Can confusion be productive? How should instructors interpret student expressions of confusion? During two semesters of introductory physics that involved Just-in-Time Teaching (JiTT) and research-based reading materials, we evaluated performance on reading assignments while simultaneously measuring students’ self-assessment of their confusion over the preclass reading material (N=137; N_{fall}=106, N_{spring}=88). We examined the relationship between confusion and correctness, confidence in reasoning, and (in the spring) precourse self-efficacy. We find that student expressions of confusion before coming to class are negatively related to correctness on preclass content-related questions, confidence in reasoning on those questions, and self-efficacy, but weakly positively related to final grade when controlling for these factors (β=0.23, p=0.03).

Agricultural habitats are frequently disturbed, and disturbances could have major effects on species in upper trophic levels such as hymenopteran parasitoids that are important for biological control. A strategy for conservation biological control is to provide a diversified agricultural landscape which increases the availability of resources such as sugar required by parasitoid biological control agents. Here, we ask whether parasitoids occurring in agriculture benefit from sugar resources more or less than parasitoids occurring in natural habitats surrounding agricultural fields. We collected parasitoids from agricultural alfalfa fields, field margins, and natural prairies, and in the lab we randomly divided them into two treatments: half were given a constant supply of a sugar source to test their residual lifespan, and half were given neither sugar nor water to test their hardiness. Collected individuals were monitored daily and their day of death recorded. Parasitoids receiving a sugar source lived substantially longer than those without. Parasitoids collected in prairies lived longer than those from alfalfa fields in both the residual lifespan and hardiness treatments, with parasitoids from field margins being intermediate between them. Furthermore, the benefits of a sugar source to increase longevity was lower for parasitoids collected in agriculture than in natural habitats. This suggests that, even though parasitoid biological control agents benefit from sugar resources, their short lifespans make the benefit of sugar resources small compared to parasitoids that occur in natural habitats and have longer lifespans, and are adapted to consistent sugar sources., (© 2024 The Author(s). Ecological Applications published by Wiley Periodicals LLC on behalf of The Ecological Society of America.)

Competing species may show positive correlations in abundance through time and space if they rely on a shared resource. Such positive correlations might obscure resource partitioning that facilitates competitor coexistence. Here, we examine the potential for resource partitioning between two ecologically similar midge species (Diptera: Chironomidae) in Lake Mývatn, Iceland. Tanytarsus gracilentus and Chironomus islandicus show large, roughly synchronized population fluctuations, implying potential reliance on a shared fluctuating resource and thereby posing the question of how these species coexist at high larval abundances. We first considered spatial partitioning of larvae. Abundances of both species were positively correlated in space; thus, spatial partitioning across different sites in the lake did not appear to be strong. We then inferred differences in dietary resources with stable carbon isotopes. T. gracilentus larvae had significantly higher δ 13 C values than C. islandicus, suggesting interspecific differences in resource use. Differences in resource selectivity, tube-building behavior, and feeding styles may facilitate resource partitioning between these species. Relative to surface sediments, T. gracilentus had higher δ 13 C values, suggesting that they selectively graze on 13 C-enriched resources such as productive algae from the surface of their tubes. In contrast, C. islandicus had lower δ 13 C values than surface sediments, suggesting reliance on 13 C-depleted resources that may include detrital organic matter and associated microbes that larvae selectively consume from the sediment surface or within their burrow walls. Overall, our study illustrates that coexisting and ecologically similar species may show positive correlations in space and time while using different resources at fine spatial scales., (© 2024. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.)

Ecological and evolutionary predictions are being increasingly employed to inform decision-makers confronted with intensifying pressures on biodiversity. For these efforts to effectively guide conservation actions, knowing the limit of predictability is pivotal. In this study, we provide realistic expectations for the enterprise of predicting changes in ecological and evolutionary observations through time. We begin with an intuitive explanation of predictability (the extent to which predictions are possible) employing an easy-to-use metric, predictive power PP ( t ). To illustrate the challenge of forecasting, we then show that among insects, birds, fishes and mammals, (i) 50% of the populations are predictable at most 1 year in advance and (ii) the median 1-year-ahead predictive power corresponds to a prediction R 2 of only 20%. Predictability is not an immutable property of ecological systems. For example, different harvesting strategies can impact the predictability of exploited populations to varying degrees. Moreover, incorporating explanatory variables, accounting for time trends and considering multivariate time series can enhance predictability. To effectively address the challenge of biodiversity loss, researchers and practitioners must be aware of the information within the available data that can be used for prediction and explore efficient ways to leverage this knowledge for environmental stewardship.

Nonbiting midges (family Chironomidae) are found throughout the world in a diverse array of aquatic and terrestrial habitats, can often tolerate harsh conditions such as hypoxia or desiccation, and have consistently compact genomes. Yet we know little about the shared molecular basis for these attributes and how they have evolved across the family. Here, we address these questions by first creating high-quality, annotated reference assemblies for Tanytarsus gracilentus (subfamily Chironominae, tribe Tanytarsini) and Parochlus steinenii (subfamily Podonominae). Using these and other publicly available assemblies, we created a time-calibrated phylogenomic tree for family Chironomidae with outgroups from order Diptera. We used this phylogeny to test for features associated with compact genomes, as well as examining patterns of gene family evolution and positive selection that may underlie chironomid habitat tolerances. Our results suggest that compact genomes evolved in the common ancestor of Chironomidae and Ceratopogonidae and that this occurred mainly through reductions in noncoding regions (introns, intergenic sequences, and repeat elements). Significantly expanded gene families in Chironomidae included biological processes that may relate to tolerance of stressful environments, such as temperature homeostasis, carbohydrate transport, melanization defense response, and trehalose transport. We identified several positively selected genes in Chironomidae, notably sulfonylurea receptor, CREB-binding protein, and protein kinase D. Our results improve our understanding of the evolution of small genomes and extreme habitat use in this widely distributed group., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)

When ecological and evolutionary dynamics occur on comparable timescales, persistence of the ensuing eco-evolutionary dynamics requires both ecological and evolutionary stability. This unites key questions in ecology and evolution: How do species coexist, and what maintains genetic variation in a population? In this work, we investigated a host-parasitoid system in which pea aphid hosts rapidly evolve resistance to Aphidius ervi parasitoids. Field data and mathematical simulations showed that heterogeneity in parasitoid dispersal can generate variation in parasitism-mediated selection on hosts through time and space. Experiments showed how evolutionary trade-offs plus moderate host dispersal across this selection mosaic cause host-parasitoid coexistence and maintenance of genetic variation in host resistance. Our results show how dispersal can stabilize both the ecological and evolutionary components of eco-evolutionary dynamics.

While climate warming is widely predicted to reduce body size of ectotherms, evidence for this trend is mixed. Body size depends not only on temperature but also on other factors, such as food quality and intraspecific competition. Because temperature trends or other long-term environmental factors may affect population size and food sources, attributing trends in average body size to temperature requires the separation of potentially confounding effects. We evaluated trends in the body size of the midge Tanytarsus gracilentus and potential drivers (water temperature, population size, and food quality) between 1977 and 2015 at Lake Mývatn, Iceland. Although temperatures increased at Mývatn over this period, there was only a slight (non-significant) decrease in midge adult body size, contrary to theoretical expectations. Using a state-space model including multiple predictors, body size was negatively associated with both water temperature and midge population abundance, and it was positively associated with 13 C enrichment of midges (an indicator of favorable food conditions). The magnitude of these effects were similar, such that simultaneous changes in temperature, abundance, and carbon stable isotopic signature could counteract each other in the long-term body size trend. Our results illustrate how multiple factors, all of which could be influenced by global change, interact to affect average ectotherm body size., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

AbstractIn January 2018, Sharon Strauss, then president of the American Society of Naturalists, organized a debate on the following topic: does evolutionary history inform the current functioning of ecological communities? The debaters-Ives, Lau, Mayfield, and Tobias-presented pro and con arguments, caricatured in standard debating format. Numerous examples show that both recent microevolutionary and longer-term macroevolutionary history are important to the ecological functioning of communities. On the other hand, many other examples illustrate that the evolutionary history of communities or community members does not influence ecological function, or at least not very much. This article aims to provide a provocative discussion of the consistent and conflicting patterns that emerge in the study of contemporary and historical evolutionary influences on community function, as well as to identify questions for further study. It is intended as a thought-provoking exercise to explore this complex field, specifically addressing (1) key assumptions and how they can lead us astray and (2) issues that need additional study. The debaters all agree that evolutionary history can inform us about at least some aspects of community function. The underlying question at the root of the debate, however, is how the fields of ecology and evolution can most profitably collaborate to provide a deeper and broader understanding of ecological communities.

During the COVID-19 pandemic, many quantitative approaches were employed to predict the course of disease spread. However, forecasting faces the challenge of inherently unpredictable spread dynamics, setting a limit to the accuracy of all models. Here, we analyze COVID-19 data from the USA to explain variation among jurisdictions in disease spread predictability (that is, the extent to which predictions are possible), using a combination of statistical and simulation models. We show that for half the counties and states the spread rate of COVID-19, r(t), was predictable at most 9 weeks and 8 weeks ahead, respectively, corresponding to at most 40% and 35% of an average cycle length of 23 weeks and 26 weeks. High predictability was associated with high cyclicity of r(t) and negatively associated with R 0 values from the pandemic's onset. Our statistical evidence suggests the following explanation: jurisdictions with a severe initial outbreak, and where individuals and authorities took strong and sustained protective measures against COVID-19, successfully curbed subsequent waves of disease spread, but at the same time unintentionally decreased its predictability. Decreased predictability of disease spread should be viewed as a by-product of positive and sustained steps that people take to protect themselves and others., (© 2023. Springer Nature Limited.)

Grassland ecosystems cover up to 40% of the global land area and provide many ecosystem services directly supporting the livelihoods of over 1 billion people. Monitoring long-term changes in grasslands is crucial for food security, biodiversity conservation, achieving Land Degradation Neutrality goals, and modeling the global carbon budget. Although long-term grassland monitoring using remote sensing is extensive, it is typically based on a single vegetation index and does not account for temporal and spatial autocorrelation, which means that some trends are falsely identified while others are missed. Our goal was to analyze trends in grasslands in Eurasia, the largest continuous grassland ecosystems on Earth. To do so, we calculated Cumulative Endmember Fractions (annual sums of monthly ground cover fractions) derived from MODIS 2002-2020 time series, and applied a new statistical approach PARTS that explicitly accounts for temporal and spatial autocorrelation in trends. We examined trends in green vegetation, non-photosynthetic vegetation, and soil ground cover fractions considering their independent change trajectories and relations among fractions over time. We derived temporally uncorrelated pixel-based trend maps and statistically tested whether observed trends could be explained by elevation, land cover, SPEI3, climate, country, and their combinations, all while accounting for spatial autocorrelation. We found no statistical evidence for a decrease in vegetation cover in grasslands in Eurasia. Instead, there was a significant map-level increase in non-photosynthetic vegetation across the region and local increases in green vegetation with a concomitant decrease in soil fraction. Independent environmental variables affected trends significantly, but effects varied by region. Overall, our analyses show in a statistically robust manner that Eurasian grasslands have changed considerably over the past two decades. Our approach enhances remote sensing-based monitoring of trends in grasslands so that underlying processes can be discerned., (© 2023 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)

AbstractUncovering the demographic basis of population fluctuations is a central goal of population biology. This is particularly challenging for spatially structured populations, which require disentangling synchrony in demographic rates from coupling via movement between locations. In this study, we fit a stage-structured metapopulation model to a 29-year time series of threespine stickleback abundance in the heterogeneous and productive Lake Mývatn, Iceland. The lake comprises two basins (North and South) connected by a channel through which the stickleback disperse. The model includes time-varying demographic rates, allowing us to assess the potential contributions of recruitment and survival, spatial coupling via movement, and demographic transience to the population's large fluctuations in abundance. Our analyses indicate that recruitment was only modestly synchronized between the two basins, whereas survival probabilities of adults were more strongly synchronized, contributing to cyclic fluctuations in the lake-wide population size with a period of approximately 6 years. The analyses further show that the two basins were coupled through movement, with the North Basin subsidizing the South Basin and playing a dominant role in driving the lake-wide dynamics. Our results show that cyclic fluctuations of a metapopulation can be explained in terms of the combined effects of synchronized demographic rates and spatial coupling.

Population cycles can be caused by consumer-resource interactions. Confirming the role of consumer-resource interactions, however, can be challenging due to an absence of data for the resource candidate. For example, interactions between midge larvae and benthic algae likely govern the high-amplitude population fluctuations of Tanytarsus gracilentus in Lake Mývatn, Iceland, but there are no records of benthic resources concurrent with adult midge population counts. Here, we investigate consumer population dynamics using the carbon stable isotope signatures of archived T. gracilentus specimens collected from 1977 to 2015, under the assumption that midge δ 13 C values reflect those of resources they consumed as larvae. We used the time series for population abundance and δ 13 C to estimate interactions between midges and resources while accounting for measurement error and possible preservation effects on isotope values. Results were consistent with consumer-resource interactions: high δ 13 C values preceded peaks in the midge population, and δ 13 C values tended to decline after midges reached high abundance. One interpretation of this dynamic coupling is that midge isotope signatures reflect temporal variation in benthic algal δ 13 C values, which we expected to mirror primary production. Following from this explanation, high benthic production (enriched δ 13 C values) would contribute to increased midge abundance, and high midge abundance would result in declining benthic production (depleted δ 13 C values). An additional and related explanation is that midges deplete benthic algal abundance once they reach peak densities, causing midges to increase their relative reliance on other resources including detritus and associated microorganisms. Such a shift in resource use would be consistent with the subsequent decline in midge δ 13 C values. Our study adds evidence that midge-resource interactions drive T. gracilentus fluctuations and demonstrates a novel application of stable isotope time-series data to understand consumer population dynamics., (© 2022 The Ecological Society of America.)

Large sets of autocorrelated data are common in fields such as remote sensing and genomics. For example, remote sensing can produce maps of information for millions of pixels, and the information from nearby pixels will likely be spatially autocorrelated. Although there are well-established statistical methods for testing hypotheses using autocorrelated data, these methods become computationally impractical for large datasets. • The method developed here makes it feasible to perform F -tests, likelihood ratio tests, and t -tests for large autocorrelated datasets. The method involves subsetting the dataset into partitions, analyzing each partition separately, and then combining the separate tests to give an overall test. • The separate statistical tests on partitions are non-independent, because the points in different partitions are not independent. Therefore, combining separate analyses of partitions requires accounting for the non-independence of the test statistics among partitions. • The methods can be applied to a wide range of data, including not only purely spatial data but also spatiotemporal data. For spatiotemporal data, it is possible to estimate coefficients from time-series models at different spatial locations and then analyze the spatial distribution of the estimates. The spatial analysis can be simplified by estimating spatial autocorrelation directly from the spatial autocorrelation among time series., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2022 Published by Elsevier B.V.)

Plant functional traits often show strong latitudinal trends. To explain these trends, studies have often focused on environmental variables, correlations with other traits that themselves show latitudinal trends, and phylogenetic conservatism. However, few studies have systematically disentangled the relative contributions of these factors. Using a dataset consisting of 9,370 plant species from Southwest China, we investigated factors affecting fruit type (fleshy vs. dry): plant growth form, environmental constraints (summarized by climate region), and phylogenetic conservatism. Growth form and climate region are often cited in the literature as important explanations for the higher proportion of fleshy fruited species in the tropics. Nonetheless, in our analyses using partial R 2 , growth form and climate region explained only 1.7% and 0.3%, respectively, of the variance in fruit type in a model including phylogeny, while phylogenetic conservatism explained 79.5%. Furthermore, phylogenetic conservatism was evenly distributed along the phylogeny, implying that fruit type reflects both ancient and recent phylogenetic relationships. Our findings illustrate the value of parsing out the contributions of explanatory variables and phylogeny to the variance in species' traits. Methods using phylogenies that calculate partial R 2 give a more informative tool than traditional methods to explore the phylogenetic patterns of functional traits., (© 2021 by the Ecological Society of America.)

AbstractTrade-offs and constraints are inherent to life, and studies of these phenomena play a central role in both organismal and evolutionary biology. Trade-offs can be defined, categorized, and studied in at least six, not mutually exclusive, ways. (1) Allocation constraints are caused by a limited resource (e.g., energy, time, space, essential nutrients), such that increasing allocation to one component necessarily requires a decrease in another (if only two components are involved, this is referred to as the Y-model, e.g., energy devoted to size versus number of offspring). (2) Functional conflicts occur when features that enhance performance of one task decrease performance of another (e.g., relative lengths of in-levers and out-levers, force-velocity trade-offs related to muscle fiber type composition). (3) Shared biochemical pathways, often involving integrator molecules (e.g., hormones, neurotransmitters, transcription factors), can simultaneously affect multiple traits, with some effects being beneficial for one or more components of Darwinian fitness (e.g., survival, age at first reproduction, fecundity) and others detrimental. (4) Antagonistic pleiotropy describes genetic variants that increase one component of fitness (or a lower-level trait) while simultaneously decreasing another. (5) Ecological circumstances (or selective regime) may impose trade-offs, such as when foraging behavior increases energy availability yet also decreases survival. (6) Sexual selection may lead to the elaboration of (usually male) secondary sexual characters that improve mating success but handicap survival and/or impose energetic costs that reduce other fitness components. Empirical studies of trade-offs often search for negative correlations between two traits that are the expected outcomes of the trade-offs, but this will generally be inadequate if more than two traits are involved and especially for complex physiological networks of interacting traits. Moreover, trade-offs often occur only in populations that are experiencing harsh environmental conditions or energetic challenges at the extremes of phenotypic distributions, such as among individuals or species that have exceptional athletic abilities. Trade-offs may be (partially) circumvented through various compensatory mechanisms, depending on the timescale involved, ranging from acute to evolutionary. Going forward, a pluralistic view of trade-offs and constraints, combined with integrative analyses that cross levels of biological organization and traditional boundaries among disciplines, will enhance the study of evolutionary organismal biology.

Ecosystem engineers have large impacts on the communities in which they live, and these impacts may feed back to populations of engineers themselves. In this study, we assessed the effect of ecosystem engineering on density-dependent feedbacks for midges in Lake Mývatn, Iceland. The midge larvae reside in the sediment and build silk tubes that provide a substrate for algal growth, thereby elevating benthic primary production. Benthic algae are in turn the primary food source for the midge larvae, setting the stage for the effects of engineering to feed back to the midges themselves. Using a field mesocosm experiment manipulating larval midge densities, we found a generally positive but nonlinear relationship between density and benthic production. Furthermore, adult emergence increased with the primary production per midge larva. By combining these two relationships in a simple model, we found that the positive effect of midges on benthic production weakened negative density dependence at low to intermediate larval densities. However, this benefit disappeared at high densities when midge consumption of primary producers exceeded their positive effects on primary production through ecosystem engineering. Our results illustrate how ecosystem engineering can alter density-dependent feedbacks for engineer populations., (© 2021 by the Ecological Society of America.)

Single-trait eco-evolutionary models of arms races between consumers and their resource species often show inhibition rather than promotion of community diversification. In contrast, modelling arms races involving multiple traits, we found that arms races can promote diversification when trade-off costs among traits make simultaneous investment in multiple traits either more beneficial or more costly. Coevolution between resource and consumer species generates an adaptive landscape for each, with the configuration giving predictable suites of consumer and resource species. Nonetheless, the adaptive landscape contains multiple alternative stable states, and which stable community is reached depends on small stochastic differences occurring along evolutionary pathways. Our results may solve a puzzling conflict between eco-evolutionary theory that predicts community diversification via consumer-resource interactions will be rare, and empirical research that has uncovered real cases. Furthermore, our results suggest that these real cases might be just a subset of alternative stable communities., (© 2020 John Wiley & Sons Ltd.)

The basic reproduction number, R 0 , determines the rate of spread of a communicable disease and therefore gives fundamental information needed to plan public health interventions. Using mortality records, we estimated the rate of spread of COVID-19 among 160 counties and county-aggregates in the USA at the start of the epidemic. We show that most of the high among-county variance is explained by four factors (R 2  = 0.70): the timing of outbreak, population size, population density, and spatial location. For predictions of future spread, population density and spatial location are important, and for the latter we show that SARS-CoV-2 strains containing the G614 mutation to the spike gene are associated with higher rates of spread. Finally, the high predictability of R 0 allows extending estimates to all 3109 counties in the conterminous 48 states. The high variation of R 0 argues for public health policies enacted at the county level for controlling COVID-19.

Ecological and evolutionary processes may become intertwined when they operate on similar time scales. Here we show ecological-evolutionary dynamics between parasitoids and aphids containing heritable symbionts that confer resistance against parasitism. In a large-scale field experiment, we manipulated the aphid's host plant to create ecological conditions that either favoured or disfavoured the parasitoid. The result was rapid evolutionary divergence of aphid resistance between treatment populations. Consistent with ecological-evolutionary dynamics, the resistant aphid populations then had reduced parasitism and increased population growth rates. We fit a model to quantify costs (reduced intrinsic rates of increase) and benefits of resistance. We also performed genetic assays on 5 years of field samples that showed persistent but highly variable frequencies of aphid clones containing protective symbionts; these patterns were consistent with simulations from the model. Our results show (1) rapid evolution that is intertwined with ecological dynamics and (2) variation in selection that prevents traits from becoming fixed, which together generate self-perpetuating ecological-evolutionary dynamics.

Many studies document negative inbreeding effects on individuals, and conservation efforts to preserve rare species routinely employ strategies to reduce inbreeding. Despite this, there are few clear examples in nature of inbreeding decreasing the growth rates of populations, and the extent of population-level effects of inbreeding in the wild remains controversial. Here, we take advantage of a long-term dataset of 26 reintroduced Alpine ibex (Capra ibex ibex) populations spanning nearly 100 years to show that inbreeding substantially reduced per capita population growth rates, particularly for populations in harsher environments. Populations with high average inbreeding (F ≈ 0.2) had population growth rates reduced by 71% compared with populations with no inbreeding. Our results show that inbreeding can have long-term demographic consequences even when environmental variation is large and deleterious alleles may have been purged during bottlenecks. Thus, efforts to guard against inbreeding effects in populations of endangered species have not been misplaced.

Many researchers want to report an $R^{2}$ to measure the variance explained by a model. When the model includes correlation among data, such as phylogenetic models and mixed models, defining an $R^{2}$ faces two conceptual problems. (i) It is unclear how to measure the variance explained by predictor (independent) variables when the model contains covariances. (ii) Researchers may want the $R^{2}$ to include the variance explained by the covariances by asking questions such as "How much of the data is explained by phylogeny?" Here, I investigated three $R^{2}$s for phylogenetic and mixed models. $R^{2}_{resid}$ is an extension of the ordinary least-squares $R^{2}$ that weights residuals by variances and covariances estimated by the model; it is closely related to $R^{2}_{glmm}$ presented by Nakagawa and Schielzeth (2013. A general and simple method for obtaining R2 from generalized linear mixed-effects models. Methods Ecol. Evol. 4:133-142). $R^{2}_{pred}$ is based on predicting each residual from the fitted model and computing the variance between observed and predicted values. $R^{2}_{lik}$ is based on the likelihood of fitted models, and therefore, reflects the amount of information that the models contain. These three $R^{2}$s are formulated as partial $R^{2}$s, making it possible to compare the contributions of predictor variables and variance components (phylogenetic signal and random effects) to the fit of models. Because partial $R^{2}$s compare a full model with a reduced model without components of the full model, they are distinct from marginal $R^{2}$s that partition additive components of the variance. I assessed the properties of the $R^{2}$s for phylogenetic models using simulations for continuous and binary response data (phylogenetic generalized least squares and phylogenetic logistic regression). Because the $R^{2}$s are designed broadly for any model for correlated data, I also compared $R^{2}$s for linear mixed models and generalized linear mixed models. $R^{2}_{resid}$, $R^{2}_{pred}$, and $R^{2}_{lik}$ all have similar performance in describing the variance explained by different components of models. However, $R^{2}_{pred}$ gives the most direct answer to the question of how much variance in the data is explained by a model. $R^{2}_{resid}$ is most appropriate for comparing models fit to different data sets, because it does not depend on sample sizes. And $R^{2}_{lik}$ is most appropriate to assess the importance of different components within the same model applied to the same data, because it is most closely associated with statistical significance tests.

Multiple abrupt and sometimes near-synchronous declines in tree populations have been detected in the temperate forests of eastern North America and Europe during the Holocene. Traditional approaches to understanding these declines focus on searching for climatic or other broad-scale extrinsic drivers. These approaches include multi-proxy studies that match reconstructed changes in tree abundance to reconstructed changes in precipitation or temperature. Although these correlative approaches are informative, they neglect the potential role of intrinsic processes, such as competition and dispersal, in shaping tree community dynamics. We developed a simple process-based community model that includes competition among tree species, density-dependent survival, and dispersal to investigate how these processes might generate abrupt changes in tree abundances even when extrinsic climatic factors do not themselves change abruptly. Specifically, a self-reinforcing (i.e., positive) feedback between abundance and survival can produce abrupt changes in tree abundance in the absence of long-term climatic changes. Furthermore, spatially correlated, short-term environmental variation and seed dispersal can increase the synchrony of abrupt changes. Using the well-studied, late-Holocene crash of Tsuga canadensis (eastern hemlock) populations as an empirical case study, we find that our model generates abrupt and quasi-synchronized crashes qualitatively similar to the observed hemlock patterns. Other tree taxa vary in the frequency and clustering of abrupt change and the proportion of increases and decreases. This complexity argues for caution in interpreting abrupt changes in species abundances as indicative of abrupt climatic changes. Nonetheless, some taxa show patterns that the model cannot produce: observed abrupt declines in hemlock abundance are more synchronized than abrupt increases, whereas the degree of synchronization is the same for abrupt decreases and increases in the model. Our results show that intrinsic processes can be significant contributing factors in abrupt tree population changes and highlight the diagnostic value of analyzing entire time series rather than single events when testing hypotheses about abrupt changes. Thus, intrinsic processes should be considered along with extrinsic drivers when seeking to explain rapid changes in community composition., (© 2019 by the Ecological Society of America.)

Reduced-representation genome sequencing such as RADseq aids the analysis of genomes by reducing the quantity of data, thereby lowering both sequencing costs and computational burdens. RADseq was initially designed for studying genetic variation across genomes at the population level, but has also proved to be suitable for interspecific phylogeny reconstruction. RADseq data pose challenges for standard phylogenomic methods, however, due to incomplete coverage of the genome and large amounts of missing data. Alignment-free methods are both efficient and accurate for phylogenetic reconstructions with whole genomes and are especially practical for nonmodel organisms; nonetheless, alignment-free methods have not been applied with reduced genome sequencing data. Here, we test a full-genome assembly- and alignment-free method, AAF, in application to RADseq data and propose two procedures for reads selection to remove reads from restriction sites that were not found in taxa being compared. We validate these methods using both simulations and real data sets. Reads selection improved the accuracy of phylogenetic construction in every simulated scenario and the two real data sets, making AAF as good or better than a comparable alignment-based method, even though AAF had much lower computational burdens. We also investigated the sources of missing data in RADseq and their effects on phylogeny reconstruction using AAF. The AAF pipeline modified for RADseq or other reduced-representation sequencing data, phyloRAD, is available on github (https://github.com/fanhuan/phyloRAD)., (© 2018 John Wiley & Sons Ltd.)

Abrupt ecological changes are, by definition, those that occur over short periods of time relative to typical rates of change for a given ecosystem. The potential for such changes is growing due to anthropogenic pressures, which challenges the resilience of societies and ecosystems. Abrupt ecological changes are difficult to diagnose because they can arise from a variety of circumstances, including rapid changes in external drivers (e.g., climate, or resource extraction), nonlinear responses to gradual changes in drivers, and interactions among multiple drivers and disturbances. We synthesize strategies for identifying causes of abrupt ecological change and highlight instances where abrupt changes are likely. Diagnosing abrupt changes and inferring causation are increasingly important as society seek to adapt to rapid, multifaceted environmental changes., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Interactions between multiple anthropogenic environmental changes can drive non-additive effects in ecological systems, and the non-additive effects can in turn be amplified or dampened by spatial covariation among environmental changes. We investigated the combined effects of night-time warming and light pollution on pea aphids and two predatory ladybeetle species. As expected, neither night-time warming nor light pollution changed the suppression of aphids by the ladybeetle species that forages effectively in darkness. However, for the more-visual predator, warming and light had non-additive effects in which together they caused much lower aphid abundances. These results are particularly relevant for agriculture near urban areas that experience both light pollution and warming from urban heat islands. Because warming and light pollution can have non-additive effects, predicting their possible combined consequences over broad spatial scales requires knowing how they co-occur. We found that night-time temperature change since 1949 covaried positively with light pollution, which has the potential to increase their non-additive effects on pea aphid control by 70% in US alfalfa. Our results highlight the importance of non-additive effects of multiple environmental factors on species and food webs, especially when these factors co-occur., (© 2017 The Author(s).)

The tropical forests of Borneo and Amazonia may each contain more tree species diversity in half a square kilometre than do all the temperate forests of Europe, North America, and Asia combined. Biologists have long been fascinated by this disparity, using it to investigate potential drivers of biodiversity. Latitudinal variation in many of these drivers is expected to create geographic differences in ecological and evolutionary processes, and evidence increasingly shows that tropical ecosystems have higher rates of diversification, clade origination, and clade dispersal. However, there is currently no evidence to link gradients in ecological processes within communities at a local scale directly to the geographic gradient in biodiversity. Here, we show geographic variation in the storage effect, an ecological mechanism that reduces the potential for competitive exclusion more strongly in the tropics than it does in temperate and boreal zones, decreasing the ratio of interspecific-to-intraspecific competition by 0.25% for each degree of latitude that an ecosystem is located closer to the Equator. Additionally, we find evidence that latitudinal variation in climate underpins these differences; longer growing seasons in the tropics reduce constraints on the seasonal timing of reproduction, permitting lower recruitment synchrony between species and thereby enhancing niche partitioning through the storage effect. Our results demonstrate that the strength of the storage effect, and therefore its impact on diversity within communities, varies latitudinally in association with climate. This finding highlights the importance of biotic interactions in shaping geographic diversity patterns, and emphasizes the need to understand the mechanisms underpinning ecological processes in greater detail than has previously been appreciated.

Phylogenetic and functional trait-based analyses inform our understanding of community composition, yet methods for quantifying the overlap in information derived from functional traits and phylogenies remain underdeveloped. Does adding traits to analyses of community composition reduce the phylogenetic signal in the residual variation? If not, then measured functional traits alone may be insufficient to explain community assembly. We propose a general statistical framework to quantify the proportion of phylogenetic pattern in community composition that remains after including measured functional traits. We then illustrate the framework with applications to two empirical data sets. Both data sets showed strong phylogenetic attraction, with related species likely to co-occur in the same communities. In one data set, including traits eliminated all phylogenetic signals in the residual variation of both abundance and presence/absence patterns. In the second data set, including traits reduced phylogenetic signal in residuals by 25% and 98% for abundance and presence/absence data, respectively. Our framework provides an explicit way to estimate how much phylogenetic community pattern remains in the residual variation after including measured functional traits. Knowing that functional traits account for most of the phylogenetic pattern should provide confidence that important traits for phylogenetic community structure have been identified. Conversely, knowing that there is unexplained residual phylogenetic information should spur the search for additional functional traits or other processes underlying community assembly., (© 2017 The Authors. New Phytologist © 2017 New Phytologist Trust.)

Individual variation in seed size and seed production is high in many plant species. How does this variation affect seed-dispersing animals and, in turn, the fitness of individual plants? In this study, we first surveyed intraspecific variation in seed mass and production in a population of a Chinese white pine, Pinus armandii. For 134 target trees investigated in 2012, there was very high variation in seed size, with mean seed mass varying among trees almost tenfold, from 0.038 to 0.361 g. Furthermore, 30 of the 134 trees produced seeds 2 years later, and for these individuals there was a correlation in seed mass of 0.59 between years, implying consistent differences among individuals. For a subset of 67 trees, we monitored the foraging preferences of scatter-hoarding rodents on a total of 15,301 seeds: 8380 were ignored, 3184 were eaten in situ, 2651 were eaten after being cached, and 395 were successfully dispersed (cached and left intact). At the scale of individual seeds, seed mass affected almost every decision that rodents made to eat, remove, and cache individual seeds. At the level of individual trees, larger seeds had increased probabilities of both predation and successful dispersal: the effects of mean seed size on costs (predation) and benefits (caching) balanced out. Thus, despite seed size affecting rodent decisions, variation among trees in dispersal success associated with mean seed size was small once seeds were harvested. This might explain, at least in part, the maintenance of high variation in mean seed mass among tree individuals.

The chironomids of Lake Mývatn show extreme population fluctuations that affect most aspects of the lake ecosystem. During periods of high chironomid densities, chironomid larvae comprise over 90% of aquatic secondary production. Here, we show that chironomid larvae substantially stimulate benthic gross primary production (GPP) and net primary production (NPP), despite consuming benthic algae. Benthic GPP in experimental mesocosms with 140,000 larvae/m 2 was 71% higher than in mesocosms with no larvae. Similarly, chlorophyll a concentrations in mesocosms increased significantly over the range of larval densities. Furthermore, larvae showed increased growth rates at higher densities, possibly due to greater benthic algal availability in these treatments. We investigated the hypothesis that larvae promote benthic algal growth by alleviating nutrient limitation, and found that (1) larvae have the potential to cycle the entire yearly external loadings of nitrogen and phosphorus during the growing season, and (2) chlorophyll a concentrations were significantly greater in close proximity to larvae (on larval tubes). The positive feedback between chironomid larvae and benthic algae generated a net mutualism between the primary consumer and primary producer trophic levels in the benthic ecosystem. Thus, our results give an example in which unexpected positive feedbacks can lead to both high primary and high secondary production., (© 2016 by the Ecological Society of America.)

Transgenic crops that express insecticide genes from Bacillus thuringiensis (Bt) are used worldwide against moth and beetle pests. Because these engineered plants can kill over 95% of susceptible larvae, they can rapidly select for resistance. Here, we use a model for a pyramid two-toxin Bt crop to explore the consequences of spatio-temporal variation in the area of Bt crop and non-Bt refuge habitat. We show that variability over time in the proportion of suitable non-Bt breeding habitat, Q, or in the total area of Bt and suitable non-Bt habitat, K, can increase the overall rate of resistance evolution by causing short-term surges of intense selection. These surges can be exacerbated when temporal variation in Q and/or K cause high larval densities in refuges that increase density-dependent mortality; this will give resistant larvae in Bt fields a relative advantage over susceptible larvae that largely depend on refuges. We address the effects of spatio-temporal variation in a management setting for two bollworm pests of cotton, Helicoverpa armigera and H. punctigera, and field data on landscape crop distributions from Australia. Even a small proportion of Bt fields available to egg-laying females when refuges are sparse may result in high exposure to Bt for just a single generation per year and cause a surge in selection. Therefore, rapid resistance evolution can occur when Bt crops are rare rather than common in the landscape. These results highlight the need to understand spatio-temporal fluctuations in the landscape composition of Bt crops and non-Bt habitats in order to design effective resistance management strategies., Competing Interests: The authors have declared that no competing interests exist.

Ecologists have long been fascinated by cyclic population fluctuations, because they suggest strong interactions between exploiter and victim species. Nonetheless, even for populations showing high-amplitude fluctuations, it is often hard to identify which species are the key drivers of the dynamics, because data are generally only available for a single species. Here, we use a paleoecological approach to investigate fluctuations in the midge population in Lake Mývatn, Iceland, which ranges over several orders of magnitude in irregular, multigeneration cycles. Previous circumstantial evidence points to consumer-resource interactions between midges and their primary food, diatoms, as the cause of these high-amplitude fluctuations. Using a pair of sediment cores from the lake, we reconstructed 26 years of dynamics of midges using egg remains and of algal groups using diagnostic pigments. We analyzed these data using statistical methods that account for both the autocorrelated nature of paleoecological data and measurement error caused by the mixing of sediment layers. The analyses revealed a signature of consumer-resource interactions in the fluctuations of midges and diatoms: diatom abundance (as inferred from biomarker pigment diatoxanthin) increased when midge abundance was low, and midge abundance (inferred from egg capsules) decreased when diatom abundance was low. Similar patterns were not found for pigments characterizing the other dominant primary producer group in the lake (cyanobacteria), subdominant algae (cryptophytes), or ubiquitous but chemically unstable biomarkers of total algal abundance (chlorophyll a); however, a significant but weaker pattern was found for the chemically stable indicator of total algal populations (β-carotene) to which diatoms are the dominant contributor. These analyses provide the first paleoecological evaluation of specific trophic interactions underlying high amplitude population fluctuations in lakes.

Unlabelled: pez is an R package that permits measurement, modelling and simulation of phylogenetic structure in ecological data. pez contains the first implementation of many methods in R, and aggregates existing data structures and methods into a single, coherent package., Availability and Implementation: pez is released under the GPL v3 open-source license, available on the Internet from CRAN (http://cran.r-project.org). The package is under active development, and the authors welcome contributions (see http://github.com/willpearse/pez)., Contact: will.pearse@gmail.com., (© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.)

Background: Next-generation sequencing technologies are rapidly generating whole-genome datasets for an increasing number of organisms. However, phylogenetic reconstruction of genomic data remains difficult because de novo assembly for non-model genomes and multi-genome alignment are challenging., Results: To greatly simplify the analysis, we present an Assembly and Alignment-Free (AAF) method ( https://sourceforge.net/projects/aaf-phylogeny ) that constructs phylogenies directly from unassembled genome sequence data, bypassing both genome assembly and alignment. Using mathematical calculations, models of sequence evolution, and simulated sequencing of published genomes, we address both evolutionary and sampling issues caused by direct reconstruction, including homoplasy, sequencing errors, and incomplete sequencing coverage. From these results, we calculate the statistical properties of the pairwise distances between genomes, allowing us to optimize parameter selection and perform bootstrapping. As a test case with real data, we successfully reconstructed the phylogeny of 12 mammals using raw sequencing reads. We also applied AAF to 21 tropical tree genome datasets with low coverage to demonstrate its effectiveness on non-model organisms., Conclusion: Our AAF method opens up phylogenomics for species without an appropriate reference genome or high sequence coverage, and rapidly creates a phylogenetic framework for further analysis of genome structure and diversity among non-model organisms.

Anecdotal evidence suggests that socioeconomic shocks strongly affect wildlife populations, but quantitative evidence is sparse. The collapse of socialism in Russia in 1991 caused a major socioeconomic shock, including a sharp increase in poverty. We analyzed population trends of 8 large mammals in Russia from 1981 to 2010 (i.e., before and after the collapse). We hypothesized that the collapse would first cause population declines, primarily due to overexploitation, and then population increases due to adaptation of wildlife to new environments following the collapse. The long-term Database of the Russian Federal Agency of Game Mammal Monitoring, consisting of up to 50,000 transects that are monitored annually, provided an exceptional data set for investigating these population trends. Three species showed strong declines in population growth rates in the decade following the collapse, while grey wolf (Canis lupus) increased by more than 150%. After 2000 some trends reversed. For example, roe deer (Capreolus spp.) abundance in 2010 was the highest of any period in our study. Likely reasons for the population declines in the 1990s include poaching and the erosion of wildlife protection enforcement. The rapid increase of the grey wolf populations is likely due to the cessation of governmental population control. In general, the widespread declines in wildlife populations after the collapse of the Soviet Union highlight the magnitude of the effects that socioeconomic shocks can have on wildlife populations and the possible need for special conservation efforts during such times., (© 2015 Society for Conservation Biology.)

Comparative approaches to the evolution of primate social behavior have typically involved two distinct lines of inquiry. One has focused on phylogenetic analyses that treat social traits as static, species-specific characteristics; the other has focused on understanding the behavioral flexibility of particular populations or species in response to local ecological or demographic variables. Here, we combine these approaches by distinguishing between constraining traits such as dispersal regimes (male, female, or bi-sexual), which are relatively invariant, and responding traits such as grouping patterns (stable, fission-fusion, sometimes fission-fusion), which can reflect rapid adjustments to current conditions. Using long-term and cross-sectional data from 29 studies of 22 species of wild primates, we confirm that dispersal regime exhibits a strong phylogenetic signal in our sample. We then show that primate species with high variation in group size and adult sex ratios exhibit variability in grouping pattern (i.e., sometimes fission-fusion) with dispersal regime constraining the grouping response. When assessing demographic variation, we found a strong positive relationship between the variability in group size over time and the number of observation years, which further illustrates the importance of long-term demographic data to interpretations of social behavior. Our approach complements other comparative efforts to understand the role of behavioral flexibility by distinguishing between constraining and responding traits, and incorporating these distinctions into analyses of social states over evolutionary and ecological time.

Plant species vary greatly in defenses against herbivores, but existing theory has struggled to explain this variation. Here, we test how phylogenetic relatedness, tradeoffs, trait syndromes, and sexual reproduction affect the macroevolution of defense. To examine the macroevolution of defenses, we studied 26 Oenothera (Onagraceae) species, combining chemistry, comparative phylogenetics and experimental assays of resistance against generalist and specialist herbivores. We detected dozens of phenolic metabolites within leaves, including ellagitannins (ETs), flavonoids, and caffeic acid derivatives (CAs). The concentration and composition of phenolics exhibited low to moderate phylogenetic signal. There were clear negative correlations between multiple traits, supporting the prediction of allocation tradeoffs. There were also positively covarying suites of traits, but these suites did not strongly predict resistance to herbivores and thus did not act as defensive syndromes. By contrast, specific metabolites did correlate with the performance of generalist and specialist herbivores. Finally, that repeated losses of sex in Oenothera was associated with the evolution of increased flavonoid diversity and altered phenolic composition. These results show that secondary chemistry has evolved rapidly during the diversification of Oenothera. This evolution has been marked by allocation tradeoffs between traits, some of which are related to herbivore performance. The repeated loss of sex appears also to have constrained the evolution of plant secondary chemistry, which may help to explain variation in defense among plants., (© 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.)

Species exist within communities of other interacting species, so an exogenous force that directly affects one species can indirectly affect all other members of the community. In the case of climate change, many species may be affected directly and subsequently initiate numerous indirect effects that propagate throughout the community. Therefore, the net effect of climate change on any one species is a function of the direct and indirect effects. We investigated the direct and indirect effects of climate warming on corn leaf aphids, a pest of corn and other grasses, by performing an experimental manipulation of temperature, predators, and two common aphid-tending ants. Although warming had a positive direct effect on aphid population growth rate, warming reduced aphid abundance when ants and predators were present. This occurred because winter ants, which aggressively defend aphids from predators under control temperatures, were less aggressive toward predators and less abundant when temperatures were increased. In contrast, warming increased the abundance of cornfield ants, but they did not protect aphids from predators with the same vigor as winter ants. Thus, warming broke down the ant-aphid mutualism and counterintuitively reduced the abundance of this agricultural pest.

1. Classical studies of succession, largely dominated by plant community studies, focus on intrinsic drivers of change in community composition, such as interspecific competition and changes to the abiotic environment. They often do not consider extrinsic drivers of colonization, such as seasonal phenology, that can affect community change. 2. We investigated both intrinsic and extrinsic drivers of succession for dipteran communities that occupy ephemeral pools, such as those in artificial containers. By initiating communities at different times in the season and following them over time, we compared the relative importance of intrinsic (i.e., habitat age) vs. extrinsic (i.e., seasonal phenology) drivers of succession. 3. We placed water-filled artificial containers in a deciduous forest with 20 containers initiated in each of three months. Containers were sampled weekly to assess community composition. Repeated-measures mixed-effects analysis of community correspondence analysis (CA) scores enabled us to partition intrinsic and extrinsic effects on succession. Covariates of temperature and precipitation were also tested. 4. Community trajectories (as defined by CA) differed significantly with habitat age and season, indicating that both intrinsic and extrinsic effects influence succession patterns. Comparisons of AICcs showed that habitat age was more important than season for species composition. Temperature and precipitation did not explain composition changes beyond those explained by habitat age and season. 5. Quantification of relative strengths of intrinsic and extrinsic effects on succession in dipteran and other ephemeral communities enables us to disentangle processes that must be understood for predicting changes in community composition.

Climate change can affect species directly and indirectly by altering interactions between species within communities. These indirect effects can ramify through a community and affect many species, including some that may not have been directly affected by the perturbation. Identifying these chains of indirect effects is difficult, and most studies only follow indirect effects across two or three species. Here, we use a factorial field experiment to demonstrate that precipitation affects spotted aphids through a complex chain of indirect interactions that are mediated by other herbivores and a generalist predator. We experimentally simulated drought, which reduced water content in alfalfa plants. While water stress in alfalfa had no direct effect on spotted aphids, it lowered the population growth rate of pea aphids, another common alfalfa pest. Because ladybeetle predators were attracted to high pea aphid densities, predator densities were lower in drought treatments. Consequently, spotted aphid densities were released from top-down control (apparent competition) in drought treatments and reached densities three times higher than spotted aphids in ambient treatments with high pea aphid densities. Thus, drought affected spotted aphids in the interaction chain: drought --> alfalfa --> pea aphids --> predators --> spotted aphids. This result illustrates the lengthy path that indirect effects of climate change may take through a community, as well as the importance of community-level experiments in determining the net effect of climate change.

Ecological networks of two interacting guilds of species, such as flowering plants and pollinators, are common in nature, and studying their structure can yield insights into their resilience to environmental disturbances. Here we develop analytical methods for exploring the strengths of interactions within bipartite networks consisting of two guilds of phylogenetically related species. We then apply these methods to investigate the resilience of a plant-pollinator community to anticipated climate change. The methods allow the statistical assessment of, for example, whether closely related pollinators are more likely to visit plants with similar relative frequencies, and whether closely related pollinators tend to visit closely related plants. The methods can also incorporate trait information, allowing us to identify which plant traits are likely responsible for attracting different pollinators. These questions are important for our study of 14 prairie plants and their 22 insect pollinators. Over the last 70 years, six of the plants have advanced their flowering, while eight have not. When we experimentally forced earlier flowering times, five of the six advanced-flowering species experienced higher pollinator visitation rates, whereas only one of the eight other species had more visits; this network thus appears resilient to climate change, because those species with advanced flowering have ample pollinators earlier in the season. Using the methods developed here, we show that advanced-flowering plants did not have a distinct pollinator community from the other eight species. Furthermore, pollinator phylogeny did not explain pollinator community composition; closely related pollinators were not more likely to visit the same plant species. However, differences among pollinator communities visiting different plants were explained by plant height, floral color, and symmetry. As a result, closely related plants attracted similar numbers of pollinators. By parsing out characteristics that explain why plants share pollinators, we can identify plant species that likely share a common fate in a changing climate.

While the area of organic crop production increases at a global scale, the potential interactions between pest management in organic and conventionally managed systems have so far received little attention. Here, we evaluate the landscape-level codependence of insecticide-based and natural enemy-based pest management using a simulation model for parasitoid-host interactions in landscapes consisting of conventionally and organically managed fields. In our simulations conventional management consists of broad-spectrum or selective insecticide application, while organic management involves no insecticides. Simulations indicate that insecticide use can easily result in lose-lose scenarios whereby both organically and conventionally managed fields suffer from increased pest loads as compared to a scenario where no insecticides are used, but that under some conditions insecticide use can be compatible with biocontrol. Simulations also suggest that the pathway to achieve the insecticide reduction without triggering additional pest pressure is not straightforward, because increasing the proportion of organically managed fields or reducing the spray frequency in conventional fields can potentially give rise to dramatic increases in pest load. The disruptive effect of insecticide use, however, can be mitigated by spatially clustering organic fields and using selective insecticides, although the effectiveness of this mitigation depends on the behavioral traits of the biocontrol agents. Poorly dispersing parasitoids and parasitoids with high attack rates required a lower amount of organically managed fields for effective pest suppression. Our findings show that the transition from a landscape dominated by conventionally managed crops to organic management has potential pitfalls; intermediate levels of organic management may lead to higher pest burdens than either low or high adoption of organic management.

Rapid transitions in ecosystem structure, or regime shifts, are a hallmark of alternative stable states (ASS). However, regime shifts can occur even when feedbacks are not strong enough to cause ASS. We investigated the potential for ASS to explain transitions between dominance of an invasive species, rusty crayfish (Orconectes rusticus), and native sunfishes (Lepomis spp.) in northern Wisconsin (USA) lakes. A rapid transition from Lepomis to rusty crayfish dominance occurred as rusty crayfish invaded Trout Lake, and the reverse transition resulted from an eight-year experimental removal of rusty crayfish from Sparkling Lake. We fit a stage-structured population model of species interactions to 31 years of time-series data from each lake. The model identified water level as an important driver, with drought conditions reducing rusty crayfish recruitment and allowing Lepomis dominance. The maximum-likelihood parameter estimates of the negative interaction between rusty crayfish and Lepomis led to ASS in the model, where each species was capable of excluding the other within a narrow range of environmental conditions. However, uncertainty in parameter estimates made it impossible to exclude the potential that rapid transitions were caused by a simpler threshold response lacking alternative equilibria. Simulated forward and backward transitions between species dominance occurred at different environmental conditions (i.e., hysteresis), even when the parameters used for simulation did not predict ASS as a result of slow species responses to environmental drivers. Thus, ASS are possible, but by no means certain, explanations for rapid transitions in this system, and our results highlight the difficulties associated with distinguishing ASS from other types of threshold responses. However, whether regime shifts are caused by ASS may be relatively unimportant in this system, as the range of conditions over which transitions occur is narrow, and under most conditions, the system is predicted to exist in only a single state.

Background: Recent studies suggest that environmental changes may tip the balance between interacting species, leading to the extinction of one or more species. While it is recognized that evolution will play a role in determining how environmental changes directly affect species, the interactions among species force us to consider the coevolutionary responses of species to environmental changes., Methodology/principle Findings: We use simple models of competition, predation, and mutualism to organize and synthesize the ways coevolution modifies species interactions when climatic changes favor one species over another. In cases where species have conflicting interests (i.e., selection for increased interspecific interaction strength on one species is detrimental to the other), we show that coevolution reduces the effects of climate change, leading to smaller changes in abundances and reduced chances of extinction. Conversely, when species have nonconflicting interests (i.e., selection for increased interspecific interaction strength on one species benefits the other), coevolution increases the effects of climate change., Conclusions/significance: Coevolution sets up feedback loops that either dampen or amplify the effect of environmental change on species abundances depending on whether coevolution has conflicting or nonconflicting effects on species interactions. Thus, gaining a better understanding of the coevolutionary processes between interacting species is critical for understanding how communities respond to a changing climate. We suggest experimental methods to determine which types of coevolution (conflicting or nonconflicting) drive species interactions, which should lead to better understanding of the effects of coevolution on species adaptation. Conducting these experiments across environmental gradients will test our predictions of the effects of environmental change and coevolution on ecological communities., Competing Interests: The authors have declared that no competing interests exist.

Data sets from ecological experiments can be difficult to analyze, due to lack of independence of experimental units and complex variance structures. In addition, information of interest may lie in complicated contrasts among treatments, rather than direct output from statistical tests. Here, we present a statistical framework for analyzing data sets containing non-independent experimental units and differences in variance among treatments (heteroscedasticity) and apply this framework to experimental data on interspecific competition among three tadpole species. Our framework involves three steps: (1) use a multilevel regression model to calculate coefficients of treatment effects on response variables; (2) combine coefficients to quantify the strength of competition (the target information of our experiment); and (3) use parametric bootstrapping to calculate significance of competition strengths. We repeated this framework using three multilevel regression models to analyze data at the level of individual tadpoles, at the replicate level, and at the replicate level accounting for heteroscedasticity. Comparing results shows the need to correctly specify the statistical model, with the model that accurately accounts for heteroscedasticity leading to different conclusions from the other two models. This approach gives a single, comprehensive analysis of experimental data that can be used to extract informative biological parameters in a statistically rigorous way.

The storage effect is a mechanism that can facilitate the coexistence of competing species through temporal fluctuations in reproductive output. Numerous natural systems have the prerequisites for the storage effect, yet it has rarely been quantitatively assessed. Here, we investigate the possible importance of the storage effect in explaining the coexistence of tree species in the diverse tropical forest on Barro Colorado Island, Panama. This tropical forest has been monitored for more than 20 years, and annual seed production is asynchronous among species, a primary requirement for the storage effect. We constructed a model of forest regeneration that includes species-specific recruitment through seed, sapling, and adult stages, and we parameterized the model using data for 28 species for which information is known about seedling germination and survival. Simulations of the model demonstrated that the storage effect alone can be a strong mechanism allowing long-term persistence of species. We also developed a metric to quantify the strength of the storage effect in a way comparable to classical resource partitioning. Applying this metric to seed production data from 108 species, the storage effect reduces the strength of pairwise interspecific competition to 11-43% of the strength of intraspecific competition, thereby demonstrating strong potential to facilitate coexistence. Finally, for a subset of 51 species whose phylogenetic relationships are known, we compared the strength of the storage effect between pairs of species to their phylogenetic similarity. The strength of the storage effect between closely related species was on average no different from distantly related species, implying that the storage effect can be important in promoting the coexistence of even closely related species.

The earlier flowering times exhibited by many plant species are a conspicuous sign of climate change. Altered phenologies have caused concern that species could suffer population declines if they flower at times when effective pollinators are unavailable. For two perennial wildflowers, Tradescantia ohiensis and Asclepias incarnata, we used an experimental approach to explore how changing phenology affects the taxonomic composition of the pollinator assemblage and the effectiveness of individual pollinator taxa. After finding in the previous year that fruit set varied with flowering time, we manipulated flowering onset in greenhouses, placed plants in the field over the span of five weeks, and measured pollinator effectiveness as the number of seeds produced after a single visit to a flower. The average effectiveness of pollinators and the expected rates of pollination success were lower for plants of both species flowering earlier than for plants flowering at historical times, suggesting there could be reproductive costs to earlier flowering. Whereas for A. incarnata, differences in average seed set among weeks were due primarily to changes in the composition of the pollinator assemblage, the differences for T. ohiensis were driven by the combined effects of compositional changes and increases over time in the effectiveness of some pollinator taxa. Both species face the possibility of temporal mismatch between the availability of the most effective pollinators and the onset of flowering, and changes in the effectiveness of individual pollinator taxa through time may add an unexpected element to the reproductive consequences of such mismatches.