Field experiments of success-breeds-success dynamics

Seemingly similar individuals often experience drastically different success trajectories, with some repeatedly failing and others consistently succeeding. One explanation is preexisting variability along unobserved fitness dimensions that is revealed gradually through differential achievement. Alternatively, positive feedback operating on arbitrary initial advantages may increasingly set apart winners from losers, producing runaway inequality. To identify social feedback in human reward systems, we conducted randomized experiments by intervening in live social environments across the domains of funding, status, endorsement, and reputation. In each system we consistently found that early success bestowed upon arbitrarily selected recipients produced significant improvements in subsequent rates of success compared with the control group of nonrecipients. However, success exhibited decreasing marginal returns, with larger initial advantages failing to produce much further differentiation. These findings suggest a lesser degree of vulnerability of reward systems to incidental or fabricated advantages and a more modest role for cumulative advantage in the explanation of social inequality than previously thought.Social scientists have long debated why we often see similar persons experience diverging trajectories of accomplishment, with some accumulating long strings of successes and others failing repeatedly. One explanation is that subtle variation along hard-to-observe dimensions of ability equips individuals with unequal a priori chances that gradually are revealed through differential achievement (1–5). A competing hypothesis states that “success breeds success” (4, 6–12). This hypothesis claims that the ultimate success of select persons may be born out of small, random initial advantages that grow ever larger through runaway positive feedback. Such cumulative advantage has been argued to produce significant, and arbitrary, inequality in many domains of human achievement (12–15). These two theoretical positions on the origins of societal inequities regularly meet in academic and public debate about whether great success is an accurate indicator of great talent (1–3, 5, 16–19).Determining the origins of success in empirical studies is made difficult by the confounding of exogenous factors with endogenous processes. For instance, although some scholars have taken the extreme variance of success distributions as a tell-tale sign of cumulative advantage (8, 11, 16, 20), critics have pointed out that various other generative mechanisms, such as the existence of a convex correspondence between fitness and success (21, 22), can generate the same empirical regularities (17, 23–28). Further, in longitudinal records of success, unobserved dimensions of fitness generate apparent bias toward past winners (3, 4, 12, 15). In these cases, the higher success rates of talented, privileged, and well-connected individuals give rise to temporal correlations between successes, which may be erroneously interpreted as a causal effect of past on future success.This problem of empirical confounding may be overcome through randomized experiments. Prior studies have used experimental methods to identify positive social feedback (13, 29–33). While these studies confirm the operation of reinforcement processes, they provide limited insight into the degree to which these processes distort the allocation of resources to individuals in various reward systems. First, the success-breeds-success hypothesis covers a much wider variety of types of success than previous experiments have investigated. In this paper we evaluate the presence of cumulative advantage by consistently applying the same experimental intervention across a diverse range of reward systems. The systems we study vary in the degree to which the rewards transferred carry immediate monetary value, affect the social status of recipients, or are of entirely ideological nature. Second, the degree to which cumulative advantage can disrupt meritocracies depends critically on whether greater initial advantages breed proportionately greater amounts of subsequent success. In our experiments we systematically vary the magnitude of the initial advantage to quantify the marginal effects on the size of the ultimate success gap.We constructed an experimental design in which we explicitly control the allocation of success (Materials and Methods). In this setup, we bestow early successes upon randomly selected members of a population, thereby ensuring that the expectations of success before intervention are equal for recipients and nonrecipients. To allow a robust test of cumulative advantage in multiple contexts, we deployed this design in four naturally occurring systems, representing distinct forms of personal success—financial gain, endorsement, social status, and social support. First, in the financial domain, we applied the design to the crowd-funding website kickstarter.com, where creators of projects in the areas of technology, arts, and entertainment compete for donations from the general public. We sampled 200 new, unfunded projects and donated a percentage of the funding goal to 100 randomly chosen projects. Second, on the website epinions.com reviewers are paid for posting written evaluations of new products, and those evaluations subsequently are rated by website visitors as “very helpful,” “helpful,” “somewhat helpful,” or “not helpful.” Reviewers are paid more for evaluations that are considered more helpful. We sampled 305 new, unrated reviews that we evaluated as being very helpful and gave a random subset of these reviews a “very helpful” rating. Our third application involved the encyclopedia website wikipedia.org, where highly productive editors receive status awards from community members in recognition of their dedication (34). We sampled 521 editors who belonged to the top 1% of most productive editors and conferred an award to a randomly chosen subset of these editors. Fourth, on the petition website change.org individuals seek support from the general public for social and political goals through signature campaigns that can be signed electronically by any named or anonymous supporter. We sampled 200 early-stage campaigns and granted a dozen signatures to 100 randomly chosen petitions. In each experiment, we kept a daily record of subsequent donations, ratings, awards, and signatures given by third parties after the treatment in both the experimental and control condition. These four interventions thus represent a range of types of success, covering resource transfers in which both source and recipients are financially affected (kickstarter.com), transfers in which the recipient benefits materially without the source incurring a cost (epinions.com), conferrals of social status (wikipedia.com), and expressions of ideological support (change.org).     

Global urban population exposure to extreme heat

Increased exposure to extreme heat from both climate change and the urban heat island effect—total urban warming—threatens the sustainability of rapidly growing urban settlements worldwide. Extreme heat exposure is highly unequal and severely impacts the urban poor. While previous studies have quantified global exposure to extreme heat, the lack of a globally accurate, fine-resolution temporal analysis of urban exposure crucially limits our ability to deploy adaptations. Here, we estimate daily urban population exposure to extreme heat for 13,115 urban settlements from 1983 to 2016. We harmonize global, fine-resolution (0.05°), daily temperature maxima and relative humidity estimates with geolocated and longitudinal global urban population data. We measure the average annual rate of increase in exposure (person-days/year⁻¹) at the global, regional, national, and municipality levels, separating the contribution to exposure trajectories from urban population growth versus total urban warming. Using a daily maximum wet bulb globe temperature threshold of 30 °C, global exposure increased nearly 200% from 1983 to 2016. Total urban warming elevated the annual increase in exposure by 52% compared to urban population growth alone. Exposure trajectories increased for 46% of urban settlements, which together in 2016 comprised 23% of the planet’s population (1.7 billion people). However, how total urban warming and population growth drove exposure trajectories is spatially heterogeneous. This study reinforces the importance of employing multiple extreme heat exposure metrics to identify local patterns and compare exposure trends across geographies. Our results suggest that previous research underestimates extreme heat exposure, highlighting the urgency for targeted adaptations and early warning systems to reduce harm from urban extreme heat exposure.

Increased exposure to extreme heat from both climate change (1–5) and the urban heat island (UHI) effect (6–9) threaten the sustainability of rapidly growing urban settlements worldwide. Exposure to dangerously high temperatures endangers urban health and development, driving reductions in labor productivity and economic output (10, 11) and increases in morbidity (1) and mortality (2, 3, 12). Within urban settlements, extreme heat exposure is highly unequal and most severely impacts the urban poor (13, 14). Despite the harmful and inequitable risks, we presently lack a globally comprehensive, fine-resolution understanding of where urban population growth intersects with increases in extreme heat (2, 6, 15). Without this knowledge, we have limited ability to tailor adaptations to reduce extreme heat exposure across the planet’s diverse urban settlements (6, 15, 16).Reducing the impacts of extreme heat exposure to urban populations requires globally consistent, accurate, and high-resolution measurement of both climate and demographic conditions that drive exposure (5, 15, 17). Such analysis provides decision makers with information to develop locally tailored interventions (7, 18, 19) and is also sufficiently broad in spatial coverage to transfer knowledge across urban geographies and climates (6). Information about exposures and interventions from diverse contexts is vital for the development of functional early warning systems (20) and can help guide risk assessments and inform future scenario planning (21). Existing global extreme heat exposure assessments (1, 2), however, do not meet these criteria (SI Appendix, Table S1) and are insufficient for decision makers. These studies are coarse grained (>0.5° spatial resolution), employ disparate or single metrics that do not capture the complexities of heat-health outcomes (22), do not separate urban from rural exposure (19), and rely on climate reanalysis products that can be substantially (∼1 to 3 °C) cooler than in situ data observations (5, 23, 24). In fact, widely cited benchmarks (25) that estimate extreme heat with the version 5 of the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (26) may greatly underestimate total global exposure to extreme heat (5, 23, 24). Using a 40.6 °C daily maximum 2-m air temperature threshold (T_max), recent analysis found that ERA5 T_max drastically underestimated the number of extreme heat days per year compared to in situ observations (23). Finally, few studies (2, 18) have assessed urban extreme heat exposure across data-sparse (23) rapidly urbanizing regions, such as sub-Saharan Africa, the Middle East, and Southern Asia (27), that may be most impacted by increased extreme heat events due to climate change (3, 5, 28).Here, we present a globally comprehensive, fine-resolution, and longitudinal estimate of urban population exposure to extreme heat––referred to henceforth as exposure––for 13,115 urban settlements from 1983 to 2016. To accomplish this, we harmonize global, fine-grained (0.05° spatial resolution) T_max estimates (23) with global urban population and spatial extent data (29). For each urban settlement, we calculate area-averaged daily wet bulb globe temperature (WBGT_max) (30) and heat index (HI_max) (31) maxima using Climate Hazards Center InfraRed Temperature with Stations Daily (CHIRTS-daily) T_max (23) and down-scaled daily minimum relative humidity (RH_min) estimates (32). CHIRTS-daily is better suited to measure urban extreme heat exposure than other gridded temperature datasets used in recent global extreme heat studies (SI Appendix, Table S1) for two reasons. First, it is more accurate, especially at long distances (refer to figure 3 in ref. 23), than widely used gridded temperature datasets to estimate urban temperature signals worldwide (SI Appendix, Figs. S1 and S2). Second, it better captures the spatial heterogeneity of T_max across diverse urban contexts (SI Appendix, Fig. S3). These factors are key for measuring extreme heat exposure in rapidly urbanizing, data-sparse regions.As discussed in refs. 23 and 24, the number of in situ temperature observations is far too low across rapidly urbanizing (27) regions to resolve spatial and temporal urban extreme heat fluctuations, which can vary dramatically over small distances and time periods. For example, of the more than 3,000 urban settlements in India (29), only 111 have reliable station observations (SI Appendix, Fig. S3). While climate reanalyses can help overcome these limitations, they are coarse grained (SI Appendix, Table S1) and suffer from mean bias, and, to a lesser degree, temporal fidelity. ERA5 has been shown to substantially underestimate the increasing frequencies of heat extremes (figure 4 in ref. 23), while Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2) fails to represent the substantial increase in recent monthly T_max values (figure 8 in ref. 24). These datasets dramatically underestimate increases in warming. CHIRTS-daily overcomes these limitations by coherently stacking information from a high-resolution (0.05°) climatology-derived surface emission temperature (24), interpolated in situ observations, and ERA5 reanalysis to produce a product that has been explicitly developed to monitor and assess temperature related hazards (23). As such, CHIRTS-daily is best suited to capture variation in exposure across urban settlements in rapidly urbanizing (27), data-sparse regions such as sub-Saharan Africa, the Middle East, and Southern Asia (SI Appendix, Fig. S3) (24).We measure exposure in person-days/year⁻¹—the number of days per year that exceed a heat exposure threshold multiplied by the total urban population exposed (5). We then estimate annual rates of increase in exposure at the global (Fig. 1), regional (SI Appendix, Table S2), national (SI Appendix, Table S3), and municipality levels from 1983 to 2016 (SI Appendix, Table S4). At each spatial scale, we separate the contribution to exposure trajectories from total urban warming and population growth (5). For clarity, total urban warming refers to the combined increase of extreme heat in urban settlements from both the UHI effect and anthropogenic climate change. We do not decouple these two forcing agents (33, 34). However, we identify which urban settlements have warmed the fastest by measuring the rate of increase in the number of days per year that exceed the two extreme heat thresholds described below (15). Our main findings use an extreme heat exposure threshold defined as WBGT_max > 30 °C, the International Standards Organization (ISO) occupational heat stress threshold for risk of heat-related illness among acclimated persons at low metabolic rates (100 to 115 W) (30). WBGT_max is a widely used heat stress metric (35) that captures the biophysical response (36) of hot temperature–humidity combinations (3, 17) that reduce labor output (36), lead to heat-related illness (36), and can cause death (23). In using a threshold WBGT_max > 30 °C, which has been associated with higher mortality rates among vulnerable populations (37), we aim to identify truly extremely hot temperature–humidity combinations (17) that can harm human health and well-being. We recognize, however, that strict exposure thresholds do not account for individual-level risks and vulnerabilities related to acclimatization, socio-economic, or health status or local infrastructure (18, 19, 38). We also note that there are a range of definitions of exposure, and we provide further analysis identifying 2-d or longer periods during which the maximum heat index (HI_max) (31) exceeded 40.6 °C (SI Appendix, Figs. S4–S6) following the US National Weather Service’s definition for an excessive heat warning (39).Open in a separate windowFig. 1.Global urban population exposure to extreme heat, defined by 1-d or longer periods when WBGT_max > 30 °C, from 1983 to 2016 (A), with the contribution from population growth (B), and total urban warming (C) decoupled.     

Negative effects of nitrogen override positive effects of phosphorus on grassland legumes worldwide

Anthropogenic nutrient enrichment is driving global biodiversity decline and modifying ecosystem functions. Theory suggests that plant functional types that fix atmospheric nitrogen have a competitive advantage in nitrogen-poor soils, but lose this advantage with increasing nitrogen supply. By contrast, the addition of phosphorus, potassium, and other nutrients may benefit such species in low-nutrient environments by enhancing their nitrogen-fixing capacity. We present a global-scale experiment confirming these predictions for nitrogen-fixing legumes (Fabaceae) across 45 grasslands on six continents. Nitrogen addition reduced legume cover, richness, and biomass, particularly in nitrogen-poor soils, while cover of non–nitrogen-fixing plants increased. The addition of phosphorous, potassium, and other nutrients enhanced legume abundance, but did not mitigate the negative effects of nitrogen addition. Increasing nitrogen supply thus has the potential to decrease the diversity and abundance of grassland legumes worldwide regardless of the availability of other nutrients, with consequences for biodiversity, food webs, ecosystem resilience, and genetic improvement of protein-rich agricultural plant species.

Anthropogenic enrichment of nitrogen (N), phosphorus (P), and other nutrients from fertilizers and fossil fuel combustion is transforming natural ecosystems worldwide (1–5), leading to increased terrestrial plant productivity (6, 7) and loss of biodiversity (8, 9). Resource competition theory proposes that the capacity of species to persist at low levels of a limiting resource is a key mechanism underpinning competitive success. Consequently, plant functional types with specialized nutrient acquisition strategies are expected to have a competitive advantage in nutrient-limited environments but also to be especially vulnerable to nutrient enrichment (10–13).Legumes (Fabaceae) are one of the largest families of flowering plants, contributing over 650 genera and 19,000 taxa to global plant diversity (14). This diversity is important for biodiversity conservation and for genetic improvement of protein-rich crops and forage species for sustainable livestock production (15–17). Furthermore, the ability to fix atmospheric N₂ is one of the most important plant functional traits for influencing ecosystem processes, conferring N-fixing legumes with a disproportionately important role in ecosystem functioning (18, 19). For example, litter produced by legumes is nitrogen-rich and more easily decomposed by soil microorganisms, leading to flow on effects to higher trophic levels, including increased complexity of food webs and resistance of soil biophysical and chemical properties to ecosystem disturbance (20). As the success of legumes often arises from this capacity for symbiotic fixation of atmospheric N₂ in N-limited environments (21, 22), atmospheric N-deposition and other pathways of anthropogenic N supply are expected to drastically reduce their competitive advantage in plant communities (1, 5, 11, 23). This is especially the case for obligate-N-fixers that cannot down-regulate N-fixation (24, 25) and hence at higher soil N are disadvantaged by the high energetic cost of N-fixation (26).While concerns about global nutrient enrichment are focused on impacts of N on biodiversity and ecosystem productivity (1, 2, 27), changes in P and potassium (K) cycles (3, 4) or altered concentrations of other nutrients, can also influence the abundance and diversity of legumes in accordance with resource competition theory (10–13). Owing to the physiological demands of N-fixation, N-fixing legumes often have higher requirements for P, K, and other nutrients [e.g., molybdenum (Mo), iron (Fe), and calcium (Ca)] than non–N-fixing plants (28–31), and increases in these nutrients can favor N-fixing over non–N-fixing species, particularly in nutrient poor soils (21, 22). However, added nutrients may have synergistic effects (6, 32), leading to uncertainties in the expected net effect of P addition on the abundance of N-fixing legumes (26). For example, the phosphatases required for P acquisition from soils are rich in N; N addition may increase phosphatase investment, conferring legumes a superior phosphorus acquisition capacity in P- and N-limited environments (25, 29). Conversely, multiple nutrient addition is expected to allow nonlegumes to compete more effectively with legume species. Resulting light limitation may suppress legume growth and reduce the survival and establishment of new legume individuals (8, 9), especially of those legumes that are unable to reduce the costs of N fixation through down-regulation (10, 11, 15, 33–35).Despite these theoretical predictions, empirical evidence for the individual and interactive effects of changes in nutrient availability on legumes in natural ecosystems is limited (29, 36–39). Some experimental studies have shown decreased legume abundance with N addition and increased with P addition, but these studies are typically conducted at a single site and show both positive and negative interactive effects among nutrients (e.g., refs. 37, 40, and 41). Furthermore, minimal evidence is available regarding the influence of K or micronutrient enrichment on legume responses (29), and the underlying mechanisms of legume responses to nutrient addition, such as soil and climatic conditions, have not been investigated at global scales (but see ref. 26 for forest ecosystems).Using data from the Nutrient Network global collaborative experiment [https://nutnet.org/ (42)], we measured the cover, richness, and biomass responses of N-fixing legumes (hereafter legumes) to standardized experimental nutrient additions in 45 grasslands across six continents (SI Appendix, Fig. S1 and Table S1). Grasslands are a globally significant biome, covering more than one-third of the Earth’s ice-free land surface, accounting for a third of terrestrial net primary production (43), and supporting the livelihoods of more than 1.3 billion people. They are subject to chronic atmospheric nitrogen deposition due to fossil fuel combustion and are likely candidates for direct nitrogen fertilization (44). While N emissions in many regions of Europe have declined leading to plateaus or reductions in deposition (45), deposition in other world grasslands, such as the Mongolian Steppe, have increased in recent decades (e.g., ref. 46). Experimental sites included temperate and anthropic grasslands that spanned a broad range of geographical locations and ecological conditions, although were mostly from temperate latitudes (39) (SI Appendix, Table S1 and Fig. S1; see Methods for details).Three nutrients (N, P, K⁺) were applied in factorial combinations, resulting in eight treatments enabling evaluation of the interactive effects of N, P, and K addition (6, 8) on legumes. Over 3 to 6 y, 10 g⋅m⁻² N, P, and K were added annually to their respective treatment plots at the beginning of each site’s growing season; other nutrients in the K⁺ treatment [sulfur (S), magnesium (Mg), and micronutrients] were applied only in the first year to avoid toxicity (42). These nutrient levels were selected to ensure they were high enough to reduce nutrient limitation at a wide diversity of sites. They are at the higher end of the range for agricultural fertilizer application rates globally (5), and higher than atmospheric nutrient deposition rates (1, 3, 41, 43). In particular, our N-addition rate was about three times maximum current N-deposition rates in European grasslands and more generally across the globe (1, 47, 48).We used a standardized protocol (6, 42) to annually measure cover, richness, and biomass of legumes, forbs, and grasses in 1-m² permanent plots (Methods), starting in the year prior to the first nutrient application (Y_initial). Across all years and sites, we recorded 170 species of N-fixing grassland legumes, comprising 50 genera (SI Appendix, Table S2). The most species-rich genera were Trifolium (25 spp.), Astragalus (12 spp.), Vicia (11 spp.), and Lupinus (11 spp.). Vicia sativa, Trifolium repens, and Vicia hirsuta were the most frequent species across our sites (9.1%, 5.1%, and 4.9% of total occurrences, respectively). Each site contained one to eight legume species (Methods and SI Appendix, Table S1). Most legume species were perennials (∼60%), including 10 woody or shrub species (∼6% of species). On average, ∼3% and 4% of total live cover comprised annual and perennial legumes, respectively.We present results of nutrient addition for the third and the last available sampling year (years 3 to 6) after starting nutrient application in each site [noting sites started applying experimental treatments in different calendar years and ran for different lengths of time (SI Appendix, Table S1)]. To measure the relative impact of N, P, and K⁺ addition on legumes, we calculated the log ratio (LR) of legume abundance and richness in the third or last year in each plot versus the initial (pretreatment) value [LR = ln (Y_final/Y_initial)]. We used the pretreatment legume abundance in the LR instead of control plots (49) to control for initial legume abundance and spatial variability among plots (8, 50). We also calculated measures of legume colonization and extinction in each plot, and evaluated the effect of initial soil nutrient concentrations, community structure, and climatic conditions as contingencies for nutrient addition effects (see Methods for details). We analyzed the data using linear mixed-effects models (51–53), with nutrient treatments (i.e., N, P, K⁺, and their interactions) as fixed effects, and blocks nested within sites as random effects. Confidence intervals for model parameters were bootstrapped as a conservative method for hypothesis testing (51, 52) (see Methods for details).     

The evolution of self-control

Cognition presents evolutionary research with one of its greatest challenges. Cognitive evolution has been explained at the proximate level by shifts in absolute and relative brain volume and at the ultimate level by differences in social and dietary complexity. However, no study has integrated the experimental and phylogenetic approach at the scale required to rigorously test these explanations. Instead, previous research has largely relied on various measures of brain size as proxies for cognitive abilities. We experimentally evaluated these major evolutionary explanations by quantitatively comparing the cognitive performance of 567 individuals representing 36 species on two problem-solving tasks measuring self-control. Phylogenetic analysis revealed that absolute brain volume best predicted performance across species and accounted for considerably more variance than brain volume controlling for body mass. This result corroborates recent advances in evolutionary neurobiology and illustrates the cognitive consequences of cortical reorganization through increases in brain volume. Within primates, dietary breadth but not social group size was a strong predictor of species differences in self-control. Our results implicate robust evolutionary relationships between dietary breadth, absolute brain volume, and self-control. These findings provide a significant first step toward quantifying the primate cognitive phenome and explaining the process of cognitive evolution.Since Darwin, understanding the evolution of cognition has been widely regarded as one of the greatest challenges for evolutionary research (1). Although researchers have identified surprising cognitive flexibility in a range of species (2–40) and potentially derived features of human psychology (41–61), we know much less about the major forces shaping cognitive evolution (62–71). With the notable exception of Bitterman’s landmark studies conducted several decades ago (63, 72–74), most research comparing cognition across species has been limited to small taxonomic samples (70, 75). With limited comparable experimental data on how cognition varies across species, previous research has largely relied on proxies for cognition (e.g., brain size) or metaanalyses when testing hypotheses about cognitive evolution (76–92). The lack of cognitive data collected with similar methods across large samples of species precludes meaningful species comparisons that can reveal the major forces shaping cognitive evolution across species, including humans (48, 70, 89, 93–98).To address these challenges we measured cognitive skills for self-control in 36 species of mammals and birds (Fig. 1 and Tables S1–S4) tested using the same experimental procedures, and evaluated the leading hypotheses for the neuroanatomical underpinnings and ecological drivers of variance in animal cognition. At the proximate level, both absolute (77, 99–107) and relative brain size (108–112) have been proposed as mechanisms supporting cognitive evolution. Evolutionary increases in brain size (both absolute and relative) and cortical reorganization are hallmarks of the human lineage and are believed to index commensurate changes in cognitive abilities (52, 105, 113–115). Further, given the high metabolic costs of brain tissue (116–121) and remarkable variance in brain size across species (108, 122), it is expected that the energetic costs of large brains are offset by the advantages of improved cognition. The cortical reorganization hypothesis suggests that selection for absolutely larger brains—and concomitant cortical reorganization—was the predominant mechanism supporting cognitive evolution (77, 91, 100–106, 120). In contrast, the encephalization hypothesis argues that an increase in brain volume relative to body size was of primary importance (108, 110, 111, 123). Both of these hypotheses have received support through analyses aggregating data from published studies of primate cognition and reports of “intelligent” behavior in nature—both of which correlate with measures of brain size (76, 77, 84, 92, 110, 124).Open in a separate windowFig. 1.A phylogeny of the species included in this study. Branch lengths are proportional to time except where long branches have been truncated by parallel diagonal lines (split between mammals and birds ∼292 Mya).With respect to selective pressures, both social and dietary complexities have been proposed as ultimate causes of cognitive evolution. The social intelligence hypothesis proposes that increased social complexity (frequently indexed by social group size) was the major selective pressure in primate cognitive evolution (6, 44, 48, 50, 87, 115, 120, 125–141). This hypothesis is supported by studies showing a positive correlation between a species’ typical group size and the neocortex ratio (80, 81, 85–87, 129, 142–145), cognitive differences between closely related species with different group sizes (130, 137, 146, 147), and evidence for cognitive convergence between highly social species (26, 31, 148–150). The foraging hypothesis posits that dietary complexity, indexed by field reports of dietary breadth and reliance on fruit (a spatiotemporally distributed resource), was the primary driver of primate cognitive evolution (151–154). This hypothesis is supported by studies linking diet quality and brain size in primates (79, 81, 86, 142, 155), and experimental studies documenting species differences in cognition that relate to feeding ecology (94, 156–166).Although each of these hypotheses has received empirical support, a comparison of the relative contributions of the different proximate and ultimate explanations requires (i) a cognitive dataset covering a large number of species tested using comparable experimental procedures; (ii) cognitive tasks that allow valid measurement across a range of species with differing morphology, perception, and temperament; (iii) a representative sample within each species to obtain accurate estimates of species-typical cognition; (iv) phylogenetic comparative methods appropriate for testing evolutionary hypotheses; and (v) unprecedented collaboration to collect these data from populations of animals around the world (70).Here, we present, to our knowledge, the first large-scale collaborative dataset and comparative analysis of this kind, focusing on the evolution of self-control. We chose to measure self-control—the ability to inhibit a prepotent but ultimately counterproductive behavior—because it is a crucial and well-studied component of executive function and is involved in diverse decision-making processes (167–169). For example, animals require self-control when avoiding feeding or mating in view of a higher-ranking individual, sharing food with kin, or searching for food in a new area rather than a previously rewarding foraging site. In humans, self-control has been linked to health, economic, social, and academic achievement, and is known to be heritable (170–172). In song sparrows, a study using one of the tasks reported here found a correlation between self-control and song repertoire size, a predictor of fitness in this species (173). In primates, performance on a series of nonsocial self-control control tasks was related to variability in social systems (174), illustrating the potential link between these skills and socioecology. Thus, tasks that quantify self-control are ideal for comparison across taxa given its robust behavioral correlates, heritable basis, and potential impact on reproductive success.In this study we tested subjects on two previously implemented self-control tasks. In the A-not-B task (27 species, n = 344), subjects were first familiarized with finding food in one location (container A) for three consecutive trials. In the test trial, subjects initially saw the food hidden in the same location (container A), but then moved to a new location (container B) before they were allowed to search (Movie S1). In the cylinder task (32 species, n = 439), subjects were first familiarized with finding a piece of food hidden inside an opaque cylinder. In the following 10 test trials, a transparent cylinder was substituted for the opaque cylinder. To successfully retrieve the food, subjects needed to inhibit the impulse to reach for the food directly (bumping into the cylinder) in favor of the detour response they had used during the familiarization phase (Movie S2).Thus, the test trials in both tasks required subjects to inhibit a prepotent motor response (searching in the previously rewarded location or reaching directly for the visible food), but the nature of the correct response varied between tasks. Specifically, in the A-not-B task subjects were required to inhibit the response that was previously successful (searching in location A) whereas in the cylinder task subjects were required to perform the same response as in familiarization trials (detour response), but in the context of novel task demands (visible food directly in front of the subject).     

From the Cover: Sea surface height evidence for long-term warming effects of tropical cyclones on the ocean

Tropical cyclones have been hypothesized to influence climate by pumping heat into the ocean, but a direct measure of this warming effect is still lacking. We quantified cyclone-induced ocean warming by directly monitoring the thermal expansion of water in the wake of cyclones, using satellite-based sea surface height data that provide a unique way of tracking the changes in ocean heat content on seasonal and longer timescales. We find that the long-term effect of cyclones is to warm the ocean at a rate of 0.32 ± 0.15 PW between 1993 and 2009, i.e., ∼23 times more efficiently per unit area than the background equatorial warming, making cyclones potentially important modulators of the climate by affecting heat transport in the ocean–atmosphere system. Furthermore, our analysis reveals that the rate of warming increases with cyclone intensity. This, together with a predicted shift in the distribution of cyclones toward higher intensities as climate warms, suggests the ocean will get even warmer, possibly leading to a positive feedback.Strong winds associated with tropical cyclones (TCs) increase air–sea heat fluxes, favoring the intensification of storms, and generate vigorous vertical mixing in the upper ocean, stirring warm surface waters with colder waters below (1–6). The wake produced by the passage of TCs is thus characterized by a surface cold anomaly and a subsurface warm anomaly (1–3, 6, 7). After the TC passage, the sea surface cold anomaly dissipates quickly (8–10), due in part to anomalous air–sea heat fluxes (9, 11), whereas the subsurface warm anomaly is believed to persist over a much longer period (12). This has led to the suggestion that the net long-term effect of TCs is to pump heat into the ocean (13–16). Such a flux of heat into the low-latitude ocean has been proposed to be an important modulator of local and remote climate (12, 17–22).During the past decade or so, several studies have been devoted to estimating the magnitude of this heating effect, using sea surface temperature (SST) data (13–16). However, owing to a lack of subsurface temperature observations, these studies relied upon many assumptions that led to large and poorly quantified uncertainties (SI Appendix, SI Results). Furthermore, it is currently highly debated how much (if any) of the estimated warming survives beyond winter season when the deepening of the mixed layer cools the upper ocean. To avoid the ideological and methodological challenges inherent in the previous work, we take a more straightforward approach that was first proposed by Emanuel (13, 23) and quantify the TC-induced warming effect on the ocean by estimating the thermal expansion of water in the wake of Northern Hemisphere TCs, using satellite-derived sea surface height (SSH) data (24) together with tropical cyclone best-track data (25, 26). Combining these two datasets allows us to track the SSH anomalies (SSHAs) around the TC-generated wake beyond the winter season and thus provides a clear picture of the temporal evolution of the TC-induced changes in the ocean heat content. Details on the data and methods are given in SI Appendix, SI Data and Methods.     

SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection

SARS-CoV-2 spillback from humans into domestic and wild animals has been well documented, and an accumulating number of studies illustrate that human-to-animal transmission is widespread in cats, mink, deer, and other species. Experimental inoculations of cats, mink, and ferrets have perpetuated transmission cycles. We sequenced full genomes of Vero cell–expanded SARS-CoV-2 inoculum and viruses recovered from cats (n = 6), dogs (n = 3), hamsters (n = 3), and a ferret (n = 1) following experimental exposure. Five nonsynonymous changes relative to the USA-WA1/2020 prototype strain were near fixation in the stock used for inoculation but had reverted to wild-type sequences at these sites in dogs, cats, and hamsters within 1- to 3-d postexposure. A total of 14 emergent variants (six in nonstructural genes, six in spike, and one each in orf8 and nucleocapsid) were detected in viruses recovered from animals. This included substitutions in spike residues H69, N501, and D614, which also vary in human lineages of concern. Even though a live virus was not cultured from dogs, substitutions in replicase genes were detected in amplified sequences. The rapid selection of SARS-CoV-2 variants in vitro and in vivo reveals residues with functional significance during host switching. These observations also illustrate the potential for spillback from animal hosts to accelerate the evolution of new viral lineages, findings of particular concern for dogs and cats living in households with COVID-19 patients. More generally, this glimpse into viral host switching reveals the unrealized rapidity and plasticity of viral evolution in experimental animal model systems.

Cross-species transmission events, which challenge pathogens to survive in new host environments, typically result in species-specific adaptations (1). These evolutionary changes can determine the pathogenicity and transmissibility of the virus in novel host species (2). Pathogen host switching resulting in epidemic disease is a rare event that is constrained by the interaction between species (3). In contrast to most species, humans move globally and regularly come into contact with domestic and peridomestic animals. Thus, when a novel virus spreads through human populations, there is an incidental risk of exposure to potentially susceptible nonhuman species.This scenario has become evident with the SARS-CoV-2 pandemic (SI Appendix, Table S1). Originally resulting from viral spillover into humans (4, 5), likely from an animal reservoir, spillback into a wide range of companion and wild animals has occurred or been shown to be plausible (6–10), and an increasing number of studies have indicated a high frequency of human-to-animal SARS-CoV-2 spillback transmission (11–18). Given the short duration of viral shedding, serologic analyses present a more accurate characterization of actual animal exposures to SARS-CoV-2. Such studies conducted in a variety of animal species have illustrated surprisingly high levels of seroconversion in cats and dogs and more recently free-ranging deer (SI Appendix, Table S1) (73–87). Other well-documented spillback events include numerous mink farms (SI Appendix, Table S1). In one of these reports, multiple feral cats living on a mink farm in the Netherlands during a SARS-CoV-2 outbreak were seropositive, likely from the direct transmission of the virus from mink to cats, as owned cats on the same farm were seronegative (19). This further illustrates that cross-species transmission chains are readily achieved. Recent surveys of free-ranging white-tailed deer in Illinois, Michigan, New York, and Pennsylvania revealed 33% seropositivity in free-ranging animals (20). Active SARS-CoV-2 infection was subsequently confirmed by PCR in a deer in Ohio (21). Together, these findings suggest the likely establishment of multiple domestic animal and wildlife reservoirs of SARS-CoV-2.The repeated interspecies transmission of a virus presents the potential for the acceleration of viral evolution and a possible source of novel strain emergence. This was demonstrated by reverse zoonosis of SARS-CoV-2 from humans to mink, followed by a selection in mink and zoonotic transmission back to humans (8). Given that reverse zoonosis has been reported repeatedly in dogs and cats from households where COVID-19 patients reside, and the fact that up to 50% of households worldwide are inhabited by these companion animals, there is potential for similar transmission chains to arise via humans and their pets (22, 23). Elucidating the viral selection and species-specific adaptation of SARS-CoV-2 in common companion animals is therefore of high interest. Furthermore, understanding viral evolutionary patterns in both companion animals and experimental animal models provides a valuable appraisal of species-specific viral variants that spotlight genomic regions for host–virus interaction.Significant attention has been directed at substrains evolving from the initial SARS-CoV-2 isolate (24), and an accumulating number of variant lineages have demonstrated increased transmission potential in humans (25, 26). The role, if any, that reverse zoonotic infections of nonhuman species and spillback may have played in the emergence of these novel variants of SARS-CoV-2 remains unknown. Documenting viral evolution following the spillover of SARS-COV-2 into new species is difficult given the unpredictability of timing of these events; therefore, experimental studies can greatly aid the understanding of SARS-CoV-2 evolution in animal species. Laboratory-based studies also provide the opportunity to determine how changes that occur during viral expansion in cell culture may influence in vivo infections. This information is highly relevant for the interpretation of in vivo and in vitro experiments using inoculum propagated in culture.We therefore assessed the evolution of SARS-CoV-2 during the three rounds of expansion of strain USA-WA1/2020 in Vero E6 cells (27), followed by measuring the variant emergence occurring during primary experimental infection in four mammalian hosts. Specifically, we compared variant proportions, insertions, and deletions occurring in genomes of SARS-CoV-2 recovered from dogs (n = 3), cats (n = 6), hamsters (n = 3), and a ferret (n = 1).     

Emerging predictable features of replicated biological invasion fronts

Biological dispersal shapes species’ distribution and affects their coexistence. The spread of organisms governs the dynamics of invasive species, the spread of pathogens, and the shifts in species ranges due to climate or environmental change. Despite its relevance for fundamental ecological processes, however, replicated experimentation on biological dispersal is lacking, and current assessments point at inherent limitations to predictability, even in the simplest ecological settings. In contrast, we show, by replicated experimentation on the spread of the ciliate Tetrahymena sp. in linear landscapes, that information on local unconstrained movement and reproduction allows us to predict reliably the existence and speed of traveling waves of invasion at the macroscopic scale. Furthermore, a theoretical approach introducing demographic stochasticity in the Fisher–Kolmogorov framework of reaction–diffusion processes captures the observed fluctuations in range expansions. Therefore, predictability of the key features of biological dispersal overcomes the inherent biological stochasticity. Our results establish a causal link from the short-term individual level to the long-term, broad-scale population patterns and may be generalized, possibly providing a general predictive framework for biological invasions in natural environments.What is the source of variance in the spread rates of biological invasions? The search for processes that affect biological dispersal and sources of variability observed in ecological range expansions is fundamental to the study of invasive species dynamics (1–10), shifts in species ranges due to climate or environmental change (11–13), and, in general, the spatial distribution of species (3, 14–16). Dispersal is the key agent that brings favorable genotypes or highly competitive species into new ranges much faster than any other ecological or evolutionary process (1, 17). Understanding the potential and realized dispersal is thus key to ecology in general (18). When organisms’ spread occurs on the timescale of multiple generations, it is the byproduct of processes that take place at finer spatial and temporal scales that are the local movement and reproduction of individuals (5, 10). The main difficulty in causally understanding dispersal is thus to upscale processes that happen at the short-term individual level to long-term and broad-scale population patterns (5, 18–20). Furthermore, the large fluctuations observed in range expansions have been claimed to reflect an intrinsic lack of predictability of the phenomenon (21). Whether the variability observed in nature or in experimental ensembles might be accounted for by systematic differences between landscapes or by demographic stochasticity affecting basic vital rates of the organisms involved is an open research question (10, 18, 21, 22).Modeling of biological dispersal established the theoretical framework of reaction–diffusion processes (1–3, 23–25), which now finds common application in dispersal ecology (5, 14, 22, 26–30) and in other fields (17, 23, 25, 31–36). Reaction–diffusion models have also been applied to model human colonization processes (31), such as the Neolithic transition in Europe (25, 37, 38). The classical prediction of reaction–diffusion models (1, 2, 24, 25) is the propagation of an invading wavefront traveling undeformed at a constant speed (Fig. 1E). Such models have been widely adopted by ecologists to describe the spread of organisms in a variety of comparative studies (5, 10, 26) and to control the dynamics of invasive species (3, 4, 6). The extensive use of these models and the good fit to observational data favored their common endorsement as a paradigm for biological dispersal (6). However, current assessments (21) point at inherent limitations to the predictability of the phenomenon, due to its intrinsic stochasticity. Therefore, single realizations of a dispersal event (as those addressed in comparative studies) might deviate significantly from the mean of the process, making replicated experimentation necessary to allow hypothesis testing, identification of causal relationships, and to potentially falsify the models’ assumptions (39).Open in a separate windowFig. 1.Schematic representation of the experiment. (A) Linear landscape. (B) Individuals of the ciliate Tetrahymena sp. move and reproduce within the landscape. (C) Examples of reconstructed trajectories of individuals (Movie S1). (D) Individuals are introduced at one end of a linear landscape and are observed to reproduce and disperse within the landscape (not to scale). (E) Illustrative representation of density profiles along the landscape at subsequent times. A wavefront is argued to propagate undeformed at a constant speed v according to the Fisher–Kolmogorov equation.Here, we provide replicated and controlled experimental support to the theory of reaction–diffusion processes for modeling biological dispersal (23–25) in a generalized context that reproduces the observed fluctuations. Firstly, we experimentally substantiate the Fisher–Kolmogorov prediction (1, 2) on the existence and the mean speed of traveling wavefronts by measuring the individual components of the process. Secondly, we manipulate the inclusion of demographic stochasticity in the model to reproduce the observed variability in range expansions. We move from the Fisher–Kolmogorov equation (Materials and Methods) to describe the spread of organisms in a linear landscape (1, 2, 24, 25). The equation couples a logistic term describing the reproduction of individuals with growth rate r and carrying capacity K and a diffusion term accounting for local movement, epitomized by the diffusion coefficient D . These species’ traits define the characteristic scales of the dispersal process. In this framework, a population initially located at one end of a linear landscape is predicted to form a wavefront of colonization invading empty space at a constant speed (1, 2, 24, 25), which we measured in our dispersal experiment (Fig. 1D and SI Text).     

Fenton chemistry at aqueous interfaces

In a fundamental process throughout nature, reduced iron unleashes the oxidative power of hydrogen peroxide into reactive intermediates. However, notwithstanding much work, the mechanism by which Fe²⁺ catalyzes H₂O₂ oxidations and the identity of the participating intermediates remain controversial. Here we report the prompt formation of O=Fe^IVCl₃⁻ and chloride-bridged di-iron O=Fe^IV·Cl·Fe^IICl₄⁻ and O=Fe^IV·Cl·Fe^IIICl₅⁻ ferryl species, in addition to Fe^IIICl₄⁻, on the surface of aqueous FeCl₂ microjets exposed to gaseous H₂O₂ or O₃ beams for <50 μs. The unambiguous identification of such species in situ via online electrospray mass spectrometry let us investigate their individual dependences on Fe²⁺, H₂O₂, O₃, and H⁺ concentrations, and their responses to tert-butanol (an ·OH scavenger) and DMSO (an O-atom acceptor) cosolutes. We found that (i) mass spectra are not affected by excess tert-butanol, i.e., the detected species are primary products whose formation does not involve ·OH radicals, and (ii) the di-iron ferryls, but not O=Fe^IVCl₃⁻, can be fully quenched by DMSO under present conditions. We infer that interfacial Fe(H₂O)_n²⁺ ions react with H₂O₂ and O₃ >10³ times faster than Fe(H₂O)₆²⁺ in bulk water via a process that favors inner-sphere two-electron O-atom over outer-sphere one-electron transfers. The higher reactivity of di-iron ferryls vs. O=Fe^IVCl₃⁻ as O-atom donors implicates the electronic coupling of mixed-valence iron centers in the weakening of the Fe^IV–O bond in poly-iron ferryl species.High-valent Fe^IV=O (ferryl) species participate in a wide range of key chemical and biological oxidations (1–4). Such species, along with ·OH radicals, have long been deemed putative intermediates in the oxidation of Fe^II by H₂O₂ (Fenton’s reaction) (5, 6), O₃, or HOCl (7, 8). The widespread availability of Fe^II and peroxides in vivo (9–12), in natural waters and soils (13), and in the atmosphere (14–18) makes Fenton chemistry and Fe^IV=O groups ubiquitous features in diverse systems (19). A lingering issue regarding Fenton’s reaction is how the relative yields of ferryls vs. ·OH radicals depend on the medium. For example, by assuming unitary ·OH radical yields, some estimates suggest that Fenton’s reaction might account for ∼30% of the ·OH radical production in fog droplets (20). Conversely, if Fenton’s reaction mostly led to Fe^IV=O species, atmospheric chemistry models predict that their steady-state concentrations would be ∼10⁴ times larger than [·OH], thereby drastically affecting the rates and course of oxidative chemistry in such media (20). Fe^IV=O centers are responsible for the versatility of the family of cytochrome P450 enzymes in catalyzing the oxidative degradation of a vast range of xenobiotics in vivo (21–28), and the selective functionalization of saturated hydrocarbons (29). The bactericidal action of antibiotics has been linked to their ability to induce Fenton chemistry in vivo (9, 30–34). Oxidative damage from exogenous Fenton chemistry likely is responsible for acute and chronic pathologies of the respiratory tract (35–38).Despite its obvious importance, the mechanism of Fenton’s reaction is not fully understood. What is at stake is how the coordination sphere of Fe²⁺ (39–46) under specific conditions affects the competition between the one-electron transfer producing ·OH radicals (the Haber–Weiss mechanism) (47), reaction R1, and the two-electron oxidation via O-atom transfer (the Bray–Gorin mechanism) into Fe^IVO²⁺, reaction R2 (6, 23, 26, 27, 45, 48–51):Ozone reacts with Fe²⁺ via analogous pathways leading to (formally) the same intermediates, reactions R3a, R3b, and R4 (8, 49, 52, 53):At present, experimental evidence about these reactions is indirect, being largely based on the analysis of reaction products in bulk water in conjunction with various assumptions. Given the complex speciation of aqueous Fe²⁺/Fe³⁺ solutions, which includes diverse poly-iron species both as reagents and products, it is not surprising that classical studies based on the identification of reaction intermediates and products via UV-absorption spectra and the use of specific scavengers have fallen short of fully unraveling the mechanism of Fenton’s reaction. Herein we address these issues, focusing particularly on the critically important interfacial Fenton chemistry that takes place at boundaries between aqueous and hydrophobic media, such as those present in atmospheric clouds (16), living tissues, biomembranes, bio-microenvironments (38, 54, 55), and nanoparticles (56, 57).We exploited the high sensitivity, surface selectivity, and unambiguous identification capabilities of a newly developed instrument based on online electrospray mass spectrometry (ES-MS) (58–62) to identify the primary products of reactions R1–R4 on aqueous FeCl₂ microjets exposed to gaseous H₂O₂ and O₃ beams under ambient conditions [in N₂(g) at 1 atm at 293 ± 2 K]. Our experiments are conducted by intersecting the continuously refreshed, uncontaminated surfaces of free-flowing aqueous microjets with reactive gas beams for τ ∼10–50 μs, immediately followed (within 100 μs; see below) by in situ detection of primary interfacial anionic products and intermediates via ES-MS (Methods, SI Text, and Figs. S1 and S2). We have previously demonstrated that online mass spectrometric sampling of liquid microjets under ambient conditions is a surface-sensitive technique (58, 62–67).     

Mantle–slab interaction and redox mechanism of diamond formation

Subduction tectonics imposes an important role in the evolution of the interior of the Earth and its global carbon cycle; however, the mechanism of the mantle–slab interaction remains unclear. Here, we demonstrate the results of high-pressure redox-gradient experiments on the interactions between Mg-Ca-carbonate and metallic iron, modeling the processes at the mantle–slab boundary; thereby, we present mechanisms of diamond formation both ahead of and behind the redox front. It is determined that, at oxidized conditions, a low-temperature Ca-rich carbonate melt is generated. This melt acts as both the carbon source and crystallization medium for diamond, whereas at reduced conditions, diamond crystallizes only from the Fe-C melt. The redox mechanism revealed in this study is used to explain the contrasting heterogeneity of natural diamonds, as seen in the composition of inclusions, carbon isotopic composition, and nitrogen impurity content.Subduction of crustal material plays an important role in the global carbon cycle (1–6). Depending on oxygen fugacity and pressure-temperature (P-T) conditions, carbon exists in the Earth''s interior in the form of carbides, diamond, graphite, hydrocarbons, carbonates, and CO₂ (7–11). In the upper mantle, the oxygen fugacity (fO₂) varies from one to five log units below the fayalite-magnetite-quartz (FMQ) buffer, with a trend of a decrease with depth (6, 12–15). At a depth of ∼250 km, mantle is reported to become metal saturated (16, 17), which holds true for all mantle regions below, including the transition zone and lower mantle. The subduction of the oxidized crustal material occurs to depths greater than 600 km (4–6). The main carbon-bearing minerals of the subducted materials are carbonates, which are thermodynamically stable up to P-T conditions of the lower mantle (10, 11, 18). As evidenced by the compositions of inclusions in diamond, which vary from strongly reduced, e.g., metallic iron and carbides (19–23), to oxidized, e.g., carbonates and CO₂ (6, 20, 24–28), carbonates may be involved in the reactions with reduced deep-seated rocks, including Fe⁰-bearing species (29–31). A scale of these reactions is determined mainly by the capacity of subducted carbonate-bearing domains. An important consequence of such an interaction is that it can produce diamond. However, studies on diamond synthesis via the reactions between oxidized and reduced phases are limited (32–35).To understand the mechanisms of the interaction of carbon-bearing oxidized- and reduced-mineral assemblages, we performed high-pressure experiments with an iron-carbonate system; an approach was used that enabled the creation of an oxygen fugacity gradient in the capsules (Materials and Methods and SI Materials and Methods).     

The vertical occipital fasciculus: A century of controversy resolved by in vivo measurements

The vertical occipital fasciculus (VOF) is the only major fiber bundle connecting dorsolateral and ventrolateral visual cortex. Only a handful of studies have examined the anatomy of the VOF or its role in cognition in the living human brain. Here, we trace the contentious history of the VOF, beginning with its original discovery in monkey by Wernicke (1881) and in human by Obersteiner (1888), to its disappearance from the literature, and recent reemergence a century later. We introduce an algorithm to identify the VOF in vivo using diffusion-weighted imaging and tractography, and show that the VOF can be found in every hemisphere (n = 74). Quantitative T1 measurements demonstrate that tissue properties, such as myelination, in the VOF differ from neighboring white-matter tracts. The terminations of the VOF are in consistent positions relative to cortical folding patterns in the dorsal and ventral visual streams. Recent findings demonstrate that these same anatomical locations also mark cytoarchitectonic and functional transitions in dorsal and ventral visual cortex. We conclude that the VOF is likely to serve a unique role in the communication of signals between regions on the ventral surface that are important for the perception of visual categories (e.g., words, faces, bodies, etc.) and regions on the dorsal surface involved in the control of eye movements, attention, and motion perception.The vertical occipital fasciculus (VOF) is the only major fiber bundle connecting dorsal and ventral regions of occipital, parietal, and temporal cortex. The signals carried by the VOF are likely to play an essential role in an array of visual and cognitive functions. Characterizing the VOF connections and tissue structure in the living human brain is important for the study of human vision and cognitive neuroscience alike.Carl Wernicke discovered the VOF (1). For the next 30 y, the VOF was included in many major neuroanatomy atlases and journal articles (1–14). However, Wernicke’s study contradicted a widely accepted principle of white-matter organization proposed by Meynert, Wernicke’s mentor. Over the subsequent decades, there emerged a camp of neuroanatomists who acknowledged Wernicke’s discovery and another group that, like Meynert, disregarded the discovery. Due to its controversial beginnings, haphazard naming convention, and the difficulty of standardizing postmortem procedures, the VOF largely disappeared from the literature for most of the next century. A century later, Yeatman et al. (15) rediscovered the VOF using diffusion magnetic resonance imaging (dMRI); they were the first to characterize the VOF cortical projections in the living, behaving, human brain.Why would such an important pathway disappear from the literature for so long? The disappearance can be traced to controversies and confusions among some of the most prominent neuroanatomists of the 19th century (1–13, 16–18). Modern, in vivo, MRI measurements and algorithms allow for precise, reproducible, scalable computations that can resolve these century-old debates and provide novel insight into the architecture of the VOF in the living human brain.This article is divided into five sections. First, we review the history of the VOF from its discovery in the late 1800s (1) through the early 1900s. Second, we link the historical images of the VOF to the first identification of the VOF in vivo (15). Third, we describe an open-source algorithm that uses dMRI data and fiber tractography to automate labeling of the VOF in human (github.com/jyeatman/AFQ/tree/master/vof). Fourth, we quantify the location and cortical projections of the VOF with respect to macroanatomical landmarks in ventral (VOT) and lateral (LOT) occipito-temporal cortices. Fifth, we report in vivo histological measurements, using quantitative T1 mapping, which differentiate VOF tissue properties from surrounding pathways. We conclude by discussing how computational neuroanatomy improves the clarity of tract definition and reproducibility of anatomical results.     

From the Cover: The evolution of parasitism from mutualism in wasps pollinating the fig,Ficus microcarpa,in Yunnan Province,China

Theory identifies factors that can undermine the evolutionary stability of mutualisms. However, theory’s relevance to mutualism stability in nature is controversial. Detailed comparative studies of parasitic species that are embedded within otherwise mutualistic taxa (e.g., fig pollinator wasps) can identify factors that potentially promote or undermine mutualism stability. We describe results from behavioral, morphological, phylogenetic, and experimental studies of two functionally distinct, but closely related, Eupristina wasp species associated with the monoecious host fig, Ficus microcarpa, in Yunnan Province, China. One (Eupristina verticillata) is a competent pollinator exhibiting morphologies and behaviors consistent with observed seed production. The other (Eupristina sp.) lacks these traits, and dramatically reduces both female and male reproductive success of its host. Furthermore, observations and experiments indicate that individuals of this parasitic species exhibit greater relative fitness than the pollinators, in both indirect competition (individual wasps in separate fig inflorescences) and direct competition (wasps of both species within the same fig). Moreover, phylogenetic analyses suggest that these two Eupristina species are sister taxa. By the strictest definition, the nonpollinating species represents a “cheater” that has descended from a beneficial pollinating mutualist. In sharp contrast to all 15 existing studies of actively pollinated figs and their wasps, the local F. microcarpa exhibit no evidence for host sanctions that effectively reduce the relative fitness of wasps that do not pollinate. We suggest that the lack of sanctions in the local hosts promotes the loss of specialized morphologies and behaviors crucial for pollination and, thereby, the evolution of cheating.

Mutualisms are defined by the net benefits that are usually provided to individuals of each interacting species. These interactions often have influences far beyond the partner species directly interacting, and commonly provide many fundamental ecosystem services (1, 2). For example, in most cases, mycorrhizal fungi provide nutrients to forest trees, pollinators help flowering plants set fruit, intestinal bacteria promote nutrient uptake across diverse animal taxa, bacteria in lucinid clams help detoxify benthic sediments, and photosynthetic algae help maintain the coral reefs that structure nearshore marine environments around the world (3–6).However, while both partners in a mutualism usually receive net benefits from the interaction, mutualisms also usually impose costs on one or both partners interacting mutualistically. In the absence of fitness-aligning mechanisms between the partners (e.g., vertical transmission of symbionts, or repeated interactions with immediate fitness benefits), theory suggests that other mechanisms are needed to maintain a mutualism’s stability. Specifically, it has been proposed that a mutualism’s long-term stability often depends on mechanisms that limit the invasion of “cheater” individuals into the populations of either partner species (2, 3, 7–14). Broadly, cheaters can be defined as individuals (or species) that do not provide a beneficial service to their partners. By not providing a potentially costly service to their partners, cheaters are thought to benefit themselves relative to “cooperating” individuals or species in the short term (12–14). Invasion by such cheaters potentially erodes the net benefits resulting from the interaction, and therefore can lead to a breakdown of the mutualism itself.Consistent with this viewpoint, data suggest that in many cases the hosts (the larger of the two partners in the mutualism) can effectively promote cooperation by selectively allocating more resources to those symbionts that provide them with greater benefits. For example, some legumes have been shown to selectively allocate more resources to nodules containing rhizobia that are better at providing fixed nitrogen (14–16). In other studies, some host plants allocate more carbon to strains of mycorrhizal fungi that provide their hosts with more phosphorus (17–19).However, other authors question the biological relevance of much of this experimental evidence to natural species interactions, the direction of cause and effect, and the actual costs for providing benefits. A central question is the degree to which evidence for cheaters, defined as receiving fitness benefits by not providing services (relative to a mutualist that does provide benefits), exist at all (12, 13, 20). Key empirical issues concern whether or not individuals with a cheating phenotype do, in fact, cheat (impose a reproductive cost on their partner, relative to a cooperating mutualist). In addition, are cheating individuals that fail to benefit their host at least as fit as cooperating (mutualistic) individuals that do? Does the host allocate relatively more resources to more beneficial partners (effectively expressing sanctions against cheaters relative to cooperators)? Ultimately, this becomes a set of specific empirical questions: What is the relative fitness of cooperators and cheaters that interact with the same partner (host)? And, does the host effectively sanction cheaters relative to cooperators, and if so, to what degree (21, 22)? At a fundamental level, the relative fitness of cheaters and cooperators is only measurable and relevant within the context of a given host’s responses to them (3, 21, 22).To resolve these questions, it is useful to study those mutualistic host–symbiont interactions in which it is straightforward to measure and experimentally manipulate both benefits and costs to each partner under natural conditions (22–32). Ideally, we should be able to comparatively assess experimental results across a diversity of host–symbiont mutualisms that differ in what theory suggests should be key metrics (e.g., strength of host sanctions, existence and relative abundance of cheaters, and so forth).The over 750 species of host figs (Ficus: Moraceae) and their obligately pollinating wasps (Agaonidae: Hymenoptera) provide such a range of both experimental and comparative options that can be exploited to address these questions (22–32) (SI Appendix, Supplementary Text and Fig. S1). Ovipositing female fig wasps deposit a drop of fluid from their poison sac into the ovules of flowers into which they lay their eggs. This fluid initiates the formation of gall tissue upon which the developing larvae feed (33) (SI Appendix). At any given site, each fig species is typically pollinated by only one or two fig wasp species (24, 26). Morphological and molecular studies broadly support coevolution between genera of pollinating wasps and their respective sections of figs, while functional studies demonstrate coadaptation between them (33–51).For example, different groups of figs are characterized by either active or passive pollination (43–45) (SI Appendix). Passive pollination does not require specialized wasp morphologies or behaviors. In contrast, active pollination requires specialized female wasp morphologies and behaviors (44). The wasps collect pollen in their natal fig using coxal combs on their forelegs and store it in pollen pockets on their thoraxes (Fig. 1). After emerging from their natal figs, female wasps use volatile chemical scent cues produced by receptive figs to identify them (35–37). Dispersal flights from the natal fig are aided by prevailing winds and routinely cover scores of kilometers (38–41). Upon finding and entering a receptive fig of an appropriate host species, the foundress wasps repeatedly remove a few grains of pollen from their pockets and place them on the stigmatic surfaces of the individual flowers on which they attempt to lay eggs. Active pollination provides clear benefits for the host fig. Pollination is more efficient in actively pollinated fig species relative to passively pollinated species. This is reflected in the dramatically lower (∼1/10) amounts of pollen that active species typically produce (43–45). Conversely, active pollination appears to be costly for the wasps in terms of specialized body structures, energy, and time (22, 42, 45).Open in a separate windowFig. 1.Receptive F. microcarpa fig and pollinating structures of E. verticillata compared with Eupristina sp. (A) A cheater wasp (Eupristina sp.) laying eggs in a receptive fig of her host F. microcarpa. Pollinator wasps (E. verticillata) (B and C) have specialized morphological structures such as pollen pockets (black arrow) on the underside of their thorax and coxal combs on their forelegs (white arrows) that facilitate pollination. Pollen is stored in the pockets and coxal combs facilitate pollen transfer (43, 44). Cheater wasps (Eupristina sp.) (D and E) retain pollen pockets (black arrow) but lack coxal combs (white arrow).The most basic mutualistic services (e.g., the wasp’s ability to pollinate) can be experimentally manipulated. By allowing or restricting the female pollinator wasps’ access to, and ability to actively collect pollen, pollinators that either do (P+) or do not (P−) carry pollen can be produced and then introduced into receptive figs (22). Furthermore, the effects on pollinator wasp fitness (i.e., lifetime reproductive success) of pollinating the host fig (or not) can be quantified by counting their relative number of offspring in naturally occurring figs (22–32). Moreover, the many existing experimental studies using the same methodologies provide context for the findings of any given experiment (22–32). In previous experiments on actively pollinated fig species, wasps that do not pollinate (P−) have lower fitness than wasps that pollinate (P+) due to increased rates of fig abortion (killing all wasp larvae) and increased larval mortality reducing the number of P− offspring that emerge. These “host sanctions” are likely caused by selective resource allocation by the tree to better-pollinated figs (28). Although pollination typically leads to a higher number of wasp offspring, pollination is not an absolute requirement for wasp offspring to develop (28). Finally, there are at least two known cases of cheating wasp species, in which species of wasps that lack both morphologies and behaviors that permit efficient, active pollination of their host co-occur with a congeneric pollinator possessing these traits. Importantly, the species that lack these traits have clearly evolved within lineages of wasps that otherwise possess these apparently costly traits that permit them to actively pollinate their host (52, 53) (SI Appendix).Here, we exploit the opportunity provided by a third case (54, 55), in which a mutualistic active pollinator and a congeneric cheater species co-occur on the same monoecious host fig. Specifically, we conducted a combination of behavioral, morphological, phylogenetic, and experimental studies to compare these wasps and the outcomes of their interactions with their shared host fig, Ficus microcarpa (subgenus Urostigma: section Urostigma: subsection Conosycea), in and near the Xishuangbanna Tropical Botanical Garden (XTBG), China. Eupristina verticillata is the described active pollinator of F. microcarpa at this location, while an undescribed coexisting wasp species (Eupristina sp.) lacks the necessary adaptation for active pollination and appears to be a cheater (54, 55).In this study, we address and answer the following questions: 1) Does the undescribed Eupristina sp. wasp associated with F. microcarpa impose a reproductive cost on its host? We find that it does, and that the cost for host reproductive success is large. 2) Does the cheater exhibit significantly higher levels of reproductive success than the pollinator in their host? Yes, in both direct and indirect competition. Combined with the reproductive loss it imposes on the host, this species meets the strictest definition of cheater. 3) Is this cheater closely related (possibly a sister species) to the mutualist pollinator of their shared host? We find that within the context of other sympatric Eupristina species associated with seven fig hosts in this area, it is. Furthermore, it represents an independent loss of pollination structures from another case previously reported in this genus. 4) Does the host (F. microcarpa) locally exhibit detectable host sanctions against wasps that do not pollinate it? In sharp contrast with all 15 other cases of actively pollinated Ficus species that have been reported (22, 29–32), we find that it does not. 5) Given that cheaters exhibit equal or greater fitness than the pollinator, how do they coexist? Although deserving further study, we suggest that regular seasonal fluctuations in the relative abundances of the two wasp species facilitate their coexistence at this site (54, 55). Seasonal changes in the prevalence of westerly winds cause regional spatial heterogeneity in source pools of pollinators and cheaters that immigrate to the local host, F. microcarpa.     

Regulation of beta-amyloid production in neurons by astrocyte-derived cholesterol

Alzheimer’s disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, tau tangles, inflammation, and loss of cognitive function. Genetic variation in a cholesterol transport protein, apolipoprotein E (apoE), is the most common genetic risk factor for sporadic AD. In vitro evidence suggests that apoE links to Aβ production through nanoscale lipid compartments (lipid clusters), but its regulation in vivo is unclear. Here, we use superresolution imaging in the mouse brain to show that apoE utilizes astrocyte-derived cholesterol to specifically traffic neuronal amyloid precursor protein (APP) in and out of lipid clusters, where it interacts with β- and γ-secretases to generate Aβ-peptide. We find that the targeted deletion of astrocyte cholesterol synthesis robustly reduces amyloid and tau burden in a mouse model of AD. Treatment with cholesterol-free apoE or knockdown of cholesterol synthesis in astrocytes decreases cholesterol levels in cultured neurons and causes APP to traffic out of lipid clusters, where it interacts with α-secretase and gives rise to soluble APP-α (sAPP-α), a neuronal protective product of APP. Changes in cellular cholesterol have no effect on α-, β-, and γ-secretase trafficking, suggesting that the ratio of Aβ to sAPP-α is regulated by the trafficking of the substrate, not the enzymes. We conclude that cholesterol is kept low in neurons, which inhibits Aβ accumulation and enables the astrocyte regulation of Aβ accumulation by cholesterol signaling.

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is characterized by the progressive loss of cognitive function and the accumulation of amyloid β (Aβ) peptide and phosphorylated tau (1). Amyloid plaques are composed of aggregates of Aβ peptide, a small hydrophobic protein excised from the transmembrane domain of amyloid precursor protein (APP) by proteases known as beta- (β-) and gamma- (γ-) secretases (SI Appendix, Fig. S1A). In high concentrations, Aβ peptide can aggregate to form Aβ plaques (2–4). The nonamyloidogenic pathway involves a third enzyme, alpha- (α-) secretase, which generates a soluble APP fragment (sAPP-α), helps set neuronal excitability in healthy individuals (5), and does not contribute to the generation of amyloid plaques. Therefore, by preventing Aβ production, α-secretase–mediated APP cleavage reduces plaque formation. Strikingly, both pathways are finely regulated by cholesterol (6) (SI Appendix, Fig. S1B).In cellular membranes, cholesterol regulates the formation of lipid clusters (also known as lipid rafts) and the affinity of proteins to lipid clusters (7), including β-secretase and γ-secretase (8–10). α-secretase does not reside in lipid clusters; rather, α-secretase is thought to reside in a region made up of disordered polyunsaturated lipids (11). The location of APP is less clear. In detergent-resistant membrane (DRM) studies, it primarily associates with lipid from the disordered region, although not exclusively (8, 10, 12–14). Endocytosis is thought to bring APP in proximity to β-secretase and γ-secretase, and this correlates with Aβ production. Cross-linking of APP with β-secretase on the plasma membrane also increases Aβ production, leading to a hypothesis that lipid clustering in the membrane contributes to APP processing (11, 14, 15) (SI Appendix, Fig. S1A). Testing this hypothesis in vivo has been hampered by the small size and transient nature of lipid clusters (often <100 nm), which is below the resolution of light microscopy.Superresolution imaging has emerged as a complimentary technique to DRMs, with the potential to interrogate cluster affinity more directly in a native cellular environment (16). We recently employed superresolution imaging to establish a membrane-mediated mechanism of general anesthesia (17). In that mechanism, cholesterol causes lipid clusters to sequester an enzyme away from its substrate. Removal of cholesterol then releases and activates the enzyme by giving it access to its substrate (SI Appendix, Fig. S1C) (7, 18). A similar mechanism has been proposed to regulate the exposure of APP to its cutting enzymes (11, 15, 19–21).Neurons are believed to be the major source of Aβ in normal and AD brains (22, 23). In the adult brain, the ability of neurons to produce cholesterol is impaired (24). Instead, astrocytes make cholesterol and transport it to neurons with apolipoprotein E (apoE) (25–27). Interestingly, apoE, specifically the e4 subtype (apoE4), is the strongest genetic risk factor associated with sporadic AD (28, 29). This led to the theory that astrocytes may be controlling Aβ accumulation through regulation of the lipid cluster function (11, 15, 19), but this has not yet been shown in the brain of an animal. Here, we show that astrocyte-derived cholesterol controls Aβ accumulation in vivo and links apoE, Aβ, and plaque formation to a single molecular pathway.     

Accounting for a mirror-image conformation as a subtle effect in protein folding

By using local (free-energy profiles along the amino acid sequence and ¹³C^α chemical shifts) and global (principal component) analyses to examine the molecular dynamics of protein-folding trajectories, generated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein A, we are able to (i) provide the main reason for formation of the mirror-image conformation of this protein, namely, a slow formation of the second loop and part of the third helix (Asp29–Asn35), caused by the presence of multiple local conformational states in this portion of the protein; (ii) show that formation of the mirror-image topology is a subtle effect resulting from local interactions; (iii) provide a mechanism for how protein A overcomes the barrier between the metastable mirror-image state and the native state; and (iv) offer a plausible reason to explain why protein A does not remain in the metastable mirror-image state even though the mirror-image and native conformations are at least energetically compatible.To perform their functions in living organisms, most proteins must fold from unfolded polypeptides into their functional, unique 3D structures. Understanding protein-folding mechanisms is crucial because misfolded proteins can cause many diseases, including neurodegenerative diseases (1) such as Alzheimer’s, Parkinson, and Huntington diseases. From theoretical and conceptual points of view, it has been suggested that a native protein exists in a thermodynamically stable state with its surroundings (2) and that a study of free-energy landscapes (FELs) holds the key to understanding how proteins fold and function (3, 4).The native structures of some proteins contain a high degree of symmetry that, in addition to the native structure, allows the existence of another, energetically very close to the native conformation, a native-like “mirror-image” structure. One of the representatives of such symmetrical proteins is the 10- to 55-residue fragment of the B domain of staphylococcal protein A [Protein Data Bank (PDB) ID: 1BDD, a three-α-helix bundle] (5). Protein A has been the subject of extensive theoretical (6–18) and experimental (19–23) studies because of its small size, fast folding kinetics, and biological importance. However, the mirror-image topology has never been a subject for discussion except for the earlier work by Olszewski et al. (7) and recent work by Noel et al. (24). The reason for this might be that it has never been detected experimentally and it was observed only in some theoretical studies (7–9, 12, 13, 15, 17, 18, 24) with different force fields. It is of interest to determine how realistic the mirror-image conformation is. Is it an artifact of the simulations or is it a conformation difficult to observe experimentally? Noel et al. (24) showed that the native and mirror-image structures have a similar enthalpic stability and are thermodynamically competitive and that the mirror image can be considered not just a computational annoyance, but as a real conformation competing with the native structure. Moreover, the mirror-image conformation is more entropically favorable than the native conformation (24). By making multiple mutations in the hydrophobic core and the first loop region, Olszewski et al. (7) found that the change in the handedness of the first loop induced by the mutations, the burial of the N cap of the second helix, and repacking of the hydrophobic core are responsible for formation of the mirror-image conformation. However, at the end, the authors stated: “… Whether the conclusion about the possible importance of turns in defining the global topology holds in general or is just specific to the three-helix bundles analyzed here requires additional investigation....” (ref. 7, p. 298).The difficulties for experiments to detect the mirror-image topology arise because the secondary structures of the mirror-image and the native conformation are identical and the native-contact interactions are similar in both conformations (details in Fig. S1 and SI Native and Mirror-Image Structures of Protein A). Hence, with an experimental technique such as circular dichroism, used to estimate the fraction of secondary-structure content, it is almost impossible to distinguish the mirror-image structure from the native structure. It would have been desirable if the mirror-image conformation and its evolution to the native structure could be detected by NMR spectroscopy. Nevertheless, by using local [¹³C^α chemical shift (25) and free-energy profiles (FEPs) along the amino acid sequence (26–28)] and global [principal component (PC) (29)] analyses (SI Materials and Methods), we examined molecular dynamics (MD) trajectories of protein A, generated with the coarse-grained united-residue (UNRES) force field (27, 30–32) (Fig. S2 and SI Materials and Methods). These analyses of the MD trajectories, in which folding from a fully unfolded conformation occurs either almost instantly or through a metastable state formed by the mirror-image topology, enabled us to elucidate the origin of the formation of a mirror-image topology and how the protein emerges from the kinetic trap and folds to the native state.The results presented in this work are based on the analysis of four pairs of MD trajectories at 270 K (in each pair, one trajectory folds directly to the native state and the other folds through the metastable mirror-image state) selected from 96 MD simulations, which we carried out in a broad range of temperatures (details in Materials and Methods). The mirror-image conformation is energetically competitive with the native conformation in the studied trajectories (an illustrative example of two trajectories is in Fig. S3), and these results are in agreement with those of earlier studies (12, 24).     

Increased variability of the western Pacific subtropical high under greenhouse warming

An anomalous strengthening in western Pacific subtropical high (WPSH) increases moisture transport from the tropics to East Asia, inducing anomalous boreal summer monsoonal rainfall, causing extreme weather events in the densely populated region. Such positive WPSH anomalies can be induced by central Pacific (CP) cold sea-surface temperature (SST) anomalies of an incipient La Niña and warm anomalies in the Indian and/or the tropical Atlantic Ocean, both promoting anticyclonic anomalies over the northwestern Pacific region. How variability of the WPSH, its extremity, and the associated mechanisms might respond to greenhouse warming remains elusive. Using outputs from 32 of the latest climate models, here we show an increase in WPSH variability translating into a 73% increase in frequency of strong WPSH events under a business-as-usual emission scenario, supported by a strong intermodel consensus. Under greenhouse warming, response of tropical atmosphere convection to CP SST anomalies increases, as does the response of the northwestern Pacific anticyclonic circulation. Thus, climate extremes such as floods in the Yangtze River Valley of East China associated with WPSH variability are likely to be more frequent and more severe.

The western Pacific subtropical high (WPSH) is an anticyclonic system hovering over the middle and lower troposphere of the northwestern Pacific, strongest in boreal summer (1, 2) (SI Appendix, Fig. S1A). The southerly winds in the west flank of the system transport moisture from the tropics to East Asia and collide with dry and cold flows from the north (2–4). These winds influence meiyu (Baiu in Japan and Changma in Korea) and an associated elongated rain belt that usually starts moving northward from southern China in May before its seasonal southward withdrawal in August, dominating variability of East Asian summer rainfall (3–6). The WPSH undergoes strong interannual variability (SI Appendix, Fig. S1B), exerting a severe impact on the boreal summer climate over the densely populated region of East Asia (2, 6–8).A strong WPSH event occurs when the WPSH undergoes a westward intensification, influencing regional climate and leading to anomalous rainfall and inducing severe floods (4, 9). For example, during the 2020 strong WPSH event, floods in the Yangtze River Valley of East China caused hundreds of deaths, millions of hectares of crops destroyed, and tens of billions in economic damage (9, 10). Further back, in 1998, a strong WPSH contributed to river floods in East China that killed thousands and affected more than 200 million people (11).Previous research examined observed WPSH variability, impact, and change over the period from 1979 to 2017 (12) or response of future climatological WPSH to greenhouse warming in models (13–17). There is an upward trend of the observed WPSH, which is expressed in a leading mode, but whether the WPSH variability above the trend has changed is not clear (12). Other studies found either a stronger or little changed mean WPSH under greenhouse warming (12–17). However, how WPSH variability that rides on the mean state, frequency of strong WPSH anomalies above the mean change, and associated mechanisms will change under future greenhouse warming remain largely unknown.Multiple processes from ocean basins affect variability of the WPSH (5, 8, 18–22). One process is an atmospheric response to sea-surface temperature (SST) variability in the central Pacific (CP) (Niño4 region, 5°S-5°N, 160°E-150°W), where cool anomalies of an incipient La Niña develop in boreal summer (June, July, and August, JJA) (23); an incipient La Niña suppresses CP local convection, generating a westward propagated atmospheric Rossby wave that strengthens the WPSH (8, 24–29). An enhanced convection over the Maritime Continent associated with the La Niña strengthens the WPSH by modulating local Hadley circulation with increased anticyclonic circulation over the northwestern Pacific (30–32). Anomalous warming of the tropical North Atlantic is also involved in driving positive WPSH anomalies by inducing CP cold SST anomalies and suppressed convection (33–35).Another process involves the Indian Ocean, where boreal summer warming induced by a previous-year El Niño triggers warm Kelvin waves emanating into the tropical western Pacific, inducing an anomalous anticyclone at the low troposphere of the northwest Pacific (36, 37). Although the Indian Ocean mechanism can operate by itself with a residual warm condition of the decaying El Niño in the equatorial Pacific, it is in part incorporated in the impact of CP SST variability as the previous-year El Niño transitions to an incipient La Niña.Because of the vast impact, how variability of the WPSH might change under greenhouse warming is an important issue. Assuming that greenhouse warming has an impact, one expects that observed WPSH variability of the past 42 y (1979 to 2020) should already be impacted. However, due to the short length of observational data and strong internal variability (38), whether change between the latter half (2000 to 2020) and former half (1979 to 1999) period has emerged out of internal variability is not clear. As such, we examine how WPSH variability might change under long-term further increasing greenhouse warming by comparing simulated WPSH variability between two 100-y periods of the 20th and 21st centuries. Over a longer period, impact of greenhouse warming is more detectable because the influence from internal variability is weaker and the climate change signal is larger (39, 40). Below we show that WPSH variability increases under long-term global warming, in turn suggesting that part of the observed change in WPSH variability is driven by greenhouse warming.     

Mutualists and antagonists drive among-population variation in selection and evolution of floral display in a perennial herb

Spatial variation in the direction of selection drives the evolution of adaptive differentiation. However, few experimental studies have examined the relative importance of different environmental factors for variation in selection and evolutionary trajectories in natural populations. Here, we combine 8 y of observational data and field experiments to assess the relative importance of mutualistic and antagonistic interactions for spatial variation in selection and short-term evolution of a genetically based floral display dimorphism in the short-lived perennial herb Primula farinosa. Natural populations of this species include two floral morphs: long-scaped plants that present their flowers well above the ground and short-scaped plants with flowers positioned close to the ground. The direction and magnitude of selection on scape morph varied among populations, and so did the frequency of the short morph (median 19%, range 0–100%; n = 69 populations). A field experiment replicated at four sites demonstrated that variation in the strength of interactions with grazers and pollinators were responsible for among-population differences in relative fitness of the two morphs. Selection exerted by grazers favored the short-scaped morph, whereas pollinator-mediated selection favored the long-scaped morph. Moreover, variation in selection among natural populations was associated with differences in morph frequency change, and the experimental removal of grazers at nine sites significantly reduced the frequency of the short-scaped morph over 8 y. The results demonstrate that spatial variation in intensity of grazing and pollination produces a selection mosaic, and that changes in biotic interactions can trigger rapid genetic changes in natural plant populations.Spatial variation in the intensity of biotic interactions is an integral part of the geographic mosaic model of coevolution (1, 2), and may result in divergent selection and the maintenance of genetic variation in traits influencing the strength and outcome of interactions (3, 4). However, few studies have presented quantitative estimates of spatiotemporal variation in selection on traits influencing the outcome of biotic interactions across more than a handful of populations. In plants, variation in the composition of the mutualist and antagonist assemblages may result in spatially varying selection on morphology, phenology, and life-history traits (e.g., 5–12). Of particular interest are traits such as floral display that may be subject to conflicting selection from mutualists and antagonists, and where the magnitude and direction of net selection should depend on the relative strength of these interactions (13–20).Experimental manipulation of environmental conditions is a powerful approach to identify agents of selection and to determine the evolutionary consequences of changes in the selection regime (21, 22). Experimental manipulation of pollen deposition (6, 23, 24) and interactions with herbivores (25–28) can be used to assess the roles of pollinators and herbivores for patterns of selection. Conflicting selection on floral traits by pollinators and herbivores have been inferred in many systems (15, 19, 20), but no study has simultaneously manipulated the intensity of both interactions to determine their relative importance for spatiotemporal variation in selection on plant traits. There is also a lack of studies experimentally examining the importance of biotic interactions for the evolutionary trajectories of natural plant populations (28, 29).Here, we combine long-term observational data and field experiments to examine causes and consequences of spatial and temporal variation in selection on floral display in the rosette-forming, short-lived, perennial herb Primula farinosa. This species offers an ideal system to examine the outcome of conflicting selection by mutualists and antagonists. It is dimorphic for scape length, with a long-scaped morph displaying the umbellate inflorescence well above the soil surface and a short-scaped morph with the inflorescence very close to the ground. The segregation of scape morphs in controlled crosses is consistent with scape morph being determined by a single biallelic locus with a dominant allele coding for short scape (SI Text, SI Segregation of Scape Morphs in Crosses and Table S1). This difference in floral display affects interactions with both pollinators and antagonists. In previous studies, we have shown that seed production in the long-scaped morph is less likely to be limited by pollen availability (14, 30, 31), whereas the short-scaped morph is less frequently attacked by seed predators (14, 18, 32, 33). The inflorescence of the long-scaped morph should also have a higher probability of being damaged by grazers compared with that of the short-scaped morph. These interactions influence plant fitness largely via fruit production, which is a key fitness component of the study species and straightforward to quantify. In P. farinosa populations in the study area, plant mortality is high, overall fitness is strongly influenced by successful seedling recruitment (34), and total seed production is significantly correlated with number of intact mature fruits produced (r = 0.838, n = 442).We documented variation in scape morph frequencies among 69 populations and asked the following questions (1): Does selection on scape length vary among populations and years? We quantified selection on scape morph in about 40 populations in each of 2 y, and in five populations across 5 y (2). What are the drivers of variation in selection on scape morph? We documented the relationship between grazing intensity and selection on scape morph, and with a field experiment, we tested the hypothesis that spatial variation in grazing pressure and pollination intensity cause among-population variation in selection on scape morph (3). Do among-population differences in selection result in different evolutionary trajectories? We used observational data to examine whether changes in scape morph frequencies were correlated with estimates of selection on scape morph, and an 8-y field experiment to test whether the exclusion of grazers resulted in a reduced frequency of the short-scaped morph.     

Catalytically powered dynamic assembly of rod-shaped nanomotors and passive tracer particles

Nano- and microscale motors powered by catalytic reactions exhibit collective behavior such as swarming, predator–prey interactions, and chemotaxis that resemble those of biological microorganisms. A quantitative understanding of the catalytically generated forces between particles that lead to these behaviors has so far been lacking. Observations and numerical simulations of pairwise interactions between gold-platinum nanorods in hydrogen peroxide solutions show that attractive and repulsive interactions arise from the catalytically generated electric field. Electrokinetic effects drive the assembly of staggered doublets and triplets of nanorods that are moving in the same direction. None of these behaviors are observed with nanorods composed of a single metal. The motors also collect tracer microparticles at their head or tail, depending on the charge of the particles, actively assembling them into close-packed rafts and aggregates of rafts. These motor–tracer particle interactions can also be understood in terms of the catalytically generated electric field around the ends of the nanorod motors.The dynamic interactions between moving objects, in particular their response to external stimuli and their communication with each other, govern their collective behavior on many length scales. Schooling of fish and flocking of birds are good examples of emergent phenomena that are orchestrated by communication between individuals in a large group. In these systems, macroscale organization is typically driven by nearest neighbor interactions that follow simple rules. To reach the level of organization seen in such living assemblies, fast and precise (in terms of distances, angles, and velocities) communication and control are required from the members. It is now straightforward to create computational models from which such dynamic structures emerge, but artificial systems that mimic behaviors as complicated as fish schooling have very rarely been realized experimentally in macroscopic engineered systems (1). On the other hand, self-assembly at the nano- and molecular levels already demonstrates a certain level of complexity and has furthered our understanding of dynamic interactions at small scales (2, 3).There are already many examples of particle assembly driven by local forces or externally applied fields. Externally applied light, magnetic, electric, and acoustic fields can drive symmetric particles into ordered arrays (4–7). Colloidal Janus particles self-assemble into complex structures by various mechanisms (8–12). However, in these examples the particle aggregates hardly approach the complexity of assemblies of living organisms; the interactions are passive responses to local forces and external fields with very limited interparticle communication or active response to the behavior of nearest neighbors.Interactions between active particles, on the other hand, can more closely mimic those of living organisms (13–17). Powered particles generate signals, typically in the forms of chemical gradients, pressure, or electric potential, which can induce responses from nearby particles. When the particle density is high, collective behaviors can emerge. For example, rotating millimeter scale objects assemble into organized patterns (1, 18). Patterns also emerge in collections of dipolar disks that are mechanically propelled along their polar axis (19). Autonomously moving nano- and micromotors (20) exhibit rich collective behavior including swarming and schooling (21–27), predator–prey interactions (25), attraction and repulsion between rotors (28, 29), spatiotemporal oscillations (21, 25), and dynamic self-assembly (29, 30). Hydrophobicity and hydrodynamic interactions can also drive the assembly of nanomotors (31, 32). Although theoretical models and numerical simulations have furthered our understanding of these systems (33–37), there is still a lack of information on the pairwise interactions of particles that result in emergent behavior. Quantifying these interactions at the level of individual microparticles should lead to better understanding of active matter (whether it is composed of synthetic and biological micromotors) and may ultimately enable the prediction, design, and application of collective behavior.Here we report dynamic intermotor interactions and particle self-assembly in systems of self-electrophoretically driven platinum–gold nanorods. These catalytic nanomotors move autonomously at ∼20 μm/s when placed in 1–2 M H₂O₂ solution (38–40). In addition to their axial movement, which is well known from previous reports, we have observed that powered nanorods dynamically associate to form staggered doublets and triplets. When the nanomotors are mixed with charged tracer particles (the sizes of the motor and tracer particles are shown in Figs. S1–S4), they collect the passive particle “cargo” at the front or back end of the rods, depending on the charge on the passive particles, and drive their assembly into close-packed 2D rafts. None of these behaviors are observed with nanorods composed of a single metal. Analysis of tracking data and numerical simulations show that all of these behaviors originate from electrokinetic and electrostatic effects in systems of powered nanorods.     

Linking function to global and local dynamics in an elevator-type transporter

Transporters cycle through large structural changes to translocate molecules across biological membranes. The temporal relationships between these changes and function, and the molecular properties setting their rates, determine transport efficiency—yet remain mostly unknown. Using single-molecule fluorescence microscopy, we compare the timing of conformational transitions and substrate uptake in the elevator-type transporter Glt_Ph. We show that the elevator-like movements of the substrate-loaded transport domain across membranes and substrate release are kinetically heterogeneous, with rates varying by orders of magnitude between individual molecules. Mutations increasing the frequency of elevator transitions and reducing substrate affinity diminish transport rate heterogeneities and boost transport efficiency. Hydrogen deuterium exchange coupled to mass spectrometry reveals destabilization of secondary structure around the substrate-binding site, suggesting that increased local dynamics leads to faster rates of global conformational changes and confers gain-of-function properties that set transport rates.

Transporters are integral membrane proteins that move solutes across lipid bilayers. They undergo concerted conformational changes, allowing alternate exposure of their substrate-binding sites to external and internal solutions (1). In each of these so-called outward- and inward-facing states (OFS and IFS, respectively), further isomerizations accompany substrate binding and release. Transport efficiency depends on the rates of these rearrangements, but linking function and structural dynamics has presented methodological challenges. Single-molecule Forster resonance energy transfer (smFRET)-based total internal reflection fluorescence (TIRF) microscopy (2–4) has been used to monitor the dynamics of the OFS to IFS transitions (5–8) and single-transporter activity (9) in the elevator-type transporter Glt_Ph and other transporters (10–18). Hydrogen–deuterium exchange followed by mass spectrometry (HDX-MS) has been used to pinpoint local changes in structural dynamics in diverse biological systems (19–21). Here, we combine these approaches to link changes in local protein dynamics to the larger-scale conformational transitions and substrate transport in wild-type (WT) and gain-of-function mutants of Glt_Ph.Glt_Ph is an extensively studied archaeal aspartate transporter that is homologous to human excitatory amino acid transporters (EAATs). Structures of Glt_Ph (7, 22–30), and archaeal and mammalian homologs (31–37), show that the transporters assemble into homotrimers via scaffold domains. Each protomer features a mobile transport domain that binds l-Aspartate (l-Asp) and three Na⁺ ions (22, 23, 28, 31, 38) and symports the solutes by an elevator mechanism, moving ∼15 Å across the membrane from an OFS to an IFS (6, 8, 23, 24, 39). During the elevator transitions, two structurally symmetric helical hairpins (HPs) 1 and 2 form the cores of the domain interfaces in the OFS and IFS, respectively (SI Appendix, Fig. S1A) (23, 24, 40). Despite symmetry, they do not have the same function. HP1 is mostly rigid, while HP2 is a conformationally plastic “master regulator” of the transporter, gating substrate in the OFS and IFS and contributing to setting the elevator transition rates (5, 23, 24, 27, 29, 36, 41–47).In this study, we use three previously characterized mutants of Glt_Ph to pinpoint the rate-limiting steps of the transport cycle and probe the protein dynamic properties that correlate with increased transport rates. A K290A mutation at the base of HP1 disrupts a salt bridge with the scaffold domain in the OFS and dramatically increases the elevator dynamics (5, 6). A triple-mutant Y204L/A345V/V366A displays a more modest increase in elevator dynamics and substantially diminished l-Asp affinity (5). Finally, a Y204L/K290A/A345V/V366A mutant combines these substitutions and their effects (5). We compared our previously obtained smFRET data on the elevator dynamics of the WT transporter and the mutants (5) to single-transporter uptake measurements. For WT Glt_Ph, these dynamics and transport measurements established transporter subpopulations that move (5, 6) and work (9) with rates differing by orders of magnitude, with slow transporters dominating the ensemble. We now show that only mutations that both reduce the population of the slow-moving transporters and weaken substrate affinity, such as Y204L/A345V/V366A, reduce the population of the slow-working transporters and confer overall gain-of-function properties. The slow-working population comprises transporters with rare elevator transitions or slow substrate release. We then used HDX-MS to explore how the Y204L/A345V/V366A mutant differed from the WT protein. We found that the mutations decreased the stability of the secondary structure around the substrate-binding site, suggesting that the increased local dynamics underlie reduced kinetic heterogeneity within the mutant transporter ensemble.