An image-computable model of how endogenous and exogenous attention differentially alter visual perception

Attention alters perception across the visual field. Typically, endogenous (voluntary) and exogenous (involuntary) attention similarly improve performance in many visual tasks, but they have differential effects in some tasks. Extant models of visual attention assume that the effects of these two types of attention are identical and consequently do not explain differences between them. Here, we develop a model of spatial resolution and attention that distinguishes between endogenous and exogenous attention. We focus on texture-based segmentation as a model system because it has revealed a clear dissociation between both attention types. For a texture for which performance peaks at parafoveal locations, endogenous attention improves performance across eccentricity, whereas exogenous attention improves performance where the resolution is low (peripheral locations) but impairs it where the resolution is high (foveal locations) for the scale of the texture. Our model emulates sensory encoding to segment figures from their background and predict behavioral performance. To explain attentional effects, endogenous and exogenous attention require separate operating regimes across visual detail (spatial frequency). Our model reproduces behavioral performance across several experiments and simultaneously resolves three unexplained phenomena: 1) the parafoveal advantage in segmentation, 2) the uniform improvements across eccentricity by endogenous attention, and 3) the peripheral improvements and foveal impairments by exogenous attention. Overall, we unveil a computational dissociation between each attention type and provide a generalizable framework for predicting their effects on perception across the visual field.

Endogenous and exogenous spatial attention prioritize subsets of visual information and facilitate their processing without concurrent eye movements (1–3). Selection by endogenous attention is goal-driven and adapts to task demands, whereas exogenous attention transiently and automatically orients to salient stimuli (1–3). In most visual tasks, both types of attention typically improve visual perception similarly [e.g., acuity (4–6), visual search (7, 8), perceived contrast (9–11)]. Consequently, models of visual attention do not distinguish between endogenous and exogenous attention (e.g., refs. 12–19). However, stark differences also exist. Each attention type differentially modulates neural responses (20, 21) and fundamental properties of visual processing, including temporal resolution (22, 23), texture sensitivity (24), sensory tuning (25), contrast sensitivity (26), and spatial resolution (27–34).The effects of endogenous and exogenous attention are dissociable during texture segmentation, a visual task constrained by spatial resolution [reviews (1–3)]. Whereas endogenous attention optimizes spatial resolution to improve the detection of an attended texture (32–34), exogenous attention reflexively enhances resolution even when detrimental to perception (27–31, 34). Extant models of attention do not explain these well-established effects.Two main hypotheses have been proposed to explain how attention alters spatial resolution. Psychophysical studies ascribe attentional effects to modulations of spatial frequency (SF) sensitivity (30, 33). Neurophysiological (13, 35, 36) and neuroimaging (37, 38) studies bolster the idea that attention modifies spatial profiles of neural receptive fields (RFs) (2). Both hypotheses provide qualitative predictions of attentional effects but do not specify their underlying neural computations.Differences between endogenous and exogenous attention are well established in segmentation tasks and thus provide an ideal model system to uncover their separate roles in altering perception. Texture-based segmentation is a fundamental process of midlevel vision that isolates regions of local structure to extract figures from their background (39–41). Successful segmentation hinges on the overlap between the visual system’s spatial resolution and the levels of detail (i.e., SF) encompassed by the texture (39, 41, 42). Consequently, the ability to distinguish between adjacent textures varies as resolution declines toward the periphery (43–46). Each attention type differentially alters texture segmentation, demonstrating that their effects shape spatial resolution [reviews (1–3)].Current models of texture segmentation do not explain performance across eccentricity and the distinct modulations by attention. Conventional models treat segmentation as a feedforward process that encodes the elementary features of an image (e.g., SF and orientation), transforms them to reflect the local structure (e.g., regions of similarly oriented bars), and then pools across space to emphasize texture-defined contours (39, 41, 47). Few of these models account for variations in resolution across eccentricity (46, 48, 49) or endogenous (but not exogenous) attentional modulations (18, 50). All others postulate that segmentation is a “preattentive” (42) operation whose underlying neural processing is impervious to attention (39, 41, 46–49).Here, we develop a computational model in which feedforward processing and attentional gain contribute to segmentation performance. We augment a conventional model of texture processing (39, 41, 47). Our model varies with eccentricity and includes contextual modulation within local regions in the stimulus via normalization (51), a canonical neural computation (52). The defining characteristic of normalization is that an individual neuron is (divisively) suppressed by the summed activity of neighboring neurons responsive to different aspects of a stimulus. We model attention as multiplicative gains [attentional gain factors (15)] that vary with eccentricity and SF. Attention shifts sensitivity toward fine or coarse spatial scales depending on the range of SFs enhanced.Our model is image-computable, which allowed us to reproduce behavior directly from grayscale images used in psychophysical experiments (6, 26, 27, 29–33). The model explains three signatures of texture segmentation hitherto unexplained within a single computational framework (Fig. 1): 1) the central performance drop (CPD) (27–34, 43–46) (Fig. 1A), that is, the parafoveal advantage of segmentation over the fovea; 2) the improvements in the periphery and impairments at foveal locations induced by exogenous attention (27–32, 34) (Fig. 1B); and 3) the equivalent improvements across eccentricity by endogenous attention (32–34) (Fig. 1C).Open in a separate windowFig. 1.Signatures of texture segmentation. (A) CPD. Shaded region depicts the magnitude of the CPD. Identical axis labels are omitted in B and C. (B) Exogenous attention modulation. Exogenous attention improves segmentation performance in the periphery and impairs it near the fovea. (C) Endogenous attention modulation. Endogenous attention improves segmentation performance across eccentricity.Whereas our analyses focused on texture segmentation, our model is general and can be applied to other visual phenomena. We show that the model predicts the effects of attention on contrast sensitivity and acuity, i.e., in tasks in which both endogenous and exogenous attention have similar or differential effects on performance. To preview our results, model comparisons revealed that normalization is necessary to elicit the CPD and that separate profiles of gain enhancement across SF (26) generate the effects of exogenous and endogenous attention on texture segmentation. A preferential high-SF enhancement reproduces the impairments by exogenous attention due to a shift in visual sensitivity toward details too fine to distinguish the target at foveal locations. The transition from impairments to improvements in the periphery results from exogenous attentional gain gradually shifting to lower SFs that are more amenable for target detection. Improvements by endogenous attention result from a uniform enhancement of SFs that encompass the target, optimizing visual sensitivity for the attended stimulus across eccentricity.     

Algorithmic amplification of politics on Twitter

Content on Twitter’s home timeline is selected and ordered by personalization algorithms. By consistently ranking certain content higher, these algorithms may amplify some messages while reducing the visibility of others. There’s been intense public and scholarly debate about the possibility that some political groups benefit more from algorithmic amplification than others. We provide quantitative evidence from a long-running, massive-scale randomized experiment on the Twitter platform that committed a randomized control group including nearly 2 million daily active accounts to a reverse-chronological content feed free of algorithmic personalization. We present two sets of findings. First, we studied tweets by elected legislators from major political parties in seven countries. Our results reveal a remarkably consistent trend: In six out of seven countries studied, the mainstream political right enjoys higher algorithmic amplification than the mainstream political left. Consistent with this overall trend, our second set of findings studying the US media landscape revealed that algorithmic amplification favors right-leaning news sources. We further looked at whether algorithms amplify far-left and far-right political groups more than moderate ones; contrary to prevailing public belief, we did not find evidence to support this hypothesis. We hope our findings will contribute to an evidence-based debate on the role personalization algorithms play in shaping political content consumption.

Political content is a major part of the public conversation on Twitter. Politicians, political organizations, and news outlets engage large audiences on Twitter. At the same time, Twitter employs algorithms that learn from data to sort content on the platform. This interplay of algorithmic content curation and political discourse has been the subject of intense scholarly debate and public scrutiny (1–15). When first established as a service, Twitter used to present individuals with content from accounts they followed, arranged in a reverse chronological feed. In 2016, Twitter introduced machine learning algorithms to render tweets on this feed called Home timeline based on a personalized relevance model (16). Individuals would now see older tweets deemed relevant to them, as well as some tweets from accounts they did not directly follow.Personalized ranking prioritizes some tweets over others on the basis of content features, social connectivity, and user activity. There is evidence that different political groups use Twitter differently to achieve political goals (17–20). What has remained a matter of debate, however, is whether or not any ranking advantage falls along established political contours, such as the left or right (2, 7), the center or the extremes (1, 3), specific parties (2, 7), or news sources of a certain political inclination (21). In this work, we provide systematic quantitative insights into this question based on a massive-scale randomized experiment on the Twitter platform.     

Link recommendation algorithms and dynamics of polarization in online social networks

The level of antagonism between political groups has risen in the past years. Supporters of a given party increasingly dislike members of the opposing group and avoid intergroup interactions, leading to homophilic social networks. While new connections offline are driven largely by human decisions, new connections on online social platforms are intermediated by link recommendation algorithms, e.g., “People you may know” or “Whom to follow” suggestions. The long-term impacts of link recommendation in polarization are unclear, particularly as exposure to opposing viewpoints has a dual effect: Connections with out-group members can lead to opinion convergence and prevent group polarization or further separate opinions. Here, we provide a complex adaptive–systems perspective on the effects of link recommendation algorithms. While several models justify polarization through rewiring based on opinion similarity, here we explain it through rewiring grounded in structural similarity—defined as similarity based on network properties. We observe that preferentially establishing links with structurally similar nodes (i.e., sharing many neighbors) results in network topologies that are amenable to opinion polarization. Hence, polarization occurs not because of a desire to shield oneself from disagreeable attitudes but, instead, due to the creation of inadvertent echo chambers. When networks are composed of nodes that react differently to out-group contacts, either converging or polarizing, we find that connecting structurally dissimilar nodes moderates opinions. Overall, our study sheds light on the impacts of social-network algorithms and unveils avenues to steer dynamics of radicalization and polarization in online social networks.

Online social networks are increasingly used to access political information (1), engage with political elites, and discuss politics (2). These new communication platforms can benefit democratic processes in several ways: They reduce barriers to information and, subsequently, increase citizen engagement, allow individuals to voice their concerns, help debunk false information, and improve accountability and transparency in political decision-making (3). In principle, individuals can use social media to access ideologically diverse viewpoints and make better-informed decisions (4, 5).At the same time, internet and online social networks reveal a dark side. There are mounting concerns over possible linkages between social media and affective polarization (6, 7). Other than healthy political deliberation, social networks can foster so-called “echo chambers” (8, 9) and “information cocoons” (3, 10) where individuals are only exposed to like-minded peers and homogeneous sources of information, which polarizes attitudes (for counterevidence, see ref. 5). As a result, social media can trigger political sectarianism (6, 7, 11–13) and fuel misinformation (14, 15). Averting the risks of online social networks for political institutions, and potentiating their advantages, requires multidisciplinary approaches and novel methods to understand long-term dynamics on social platforms.That is not an easy task. As pointed out by Woolley and Howard, “to understand contemporary political communication we must now investigate the politics of algorithms and automation” (16). While traditional media outlets are curated by humans, online social media resorts to computer algorithms to personalize contents through automatic filtering. To understand information dynamics in online social networks, one needs to take into account the interrelated subtleties of human decision making [e.g., only share specific contents (17), actively engage with other users, follow or befriend particular individuals, interact offline] and the outcomes of automated decisions (e.g., news sorting and recommendation systems) (18, 19). In this regard, much attention has been placed on the role of news filters and sorting (1, 18, 19). Shmargad and Klar (20) provide evidence that algorithms sorting news impact the way users engage with and evaluate political news, likely exacerbating political polarization. Likewise, Levy (21) notes that social media algorithms can substantially affect users’ news consumption habits.While past studies have examined how algorithms may affect which information appears on a person’s newsfeed, and subsequent polarization, social matching (22) or link recommendation (23) algorithms [also called user, contact, or people recommender systems (24, 25)] constitute another class of algorithms that can affect the way users engage in (and with) online social networks (examples of such systems in SI Appendix, Fig. S13). These algorithms are implemented to recommend new online connections—“friends” or “followees”—to social network users, based on supposed offline familiarity, likelihood of establishing a future relation, similar interests, or the potential to serve as a source of useful information. Current data provide evidence that link recommendation algorithms impact network topologies and increase network clustering: Daly et al. (26) show that an algorithm recommending friends-of-friends, in an IBM internal social network platform, increases clustering and network modularity. Su et al. (27) analyzed the Twitter graph before and after this platform implemented link recommendation algorithms and show that the “Who To Follow” feature led to a sudden increase in edge growth and the network clustering coefficient. Similarly, Zignani et al. (28) show that, on a small sample of the Facebook graph, the introduction of the “People You May Know” (PYMK) feature led to a sudden increase in the number of links and triangles [i.e., motifs comprising three nodes (A, B, C) where the links AB, AC, and BC exist] in the network. The fact that PYMK is responsible for a significant fraction of link creations is alluded to in other works (29). Furthermore, recent work shows, through experiments with real social media users (30) and simulations (31), that link recommendation algorithms can effectively be used as an intervention mechanism to increase networks’ structural diversity (30, 31) and minimize disagreements (32). It is thereby relevant to understand, 1) How do algorithmic link recommendations interplay with opinion formation? and 2) What are the long-term impacts of such algorithms on opinion polarization?Here, we tackle the previous questions from a complex adaptive–systems perspective (33), designing and analyzing a simple model where individuals interact in a dynamic social network. While several models explain the emergence of polarization through link formation based on opinion similarity (34–41) and information exchange (42), here we focus instead on rewiring based on “structural similarity,” which is defined as similarity based on common features that exclusively depend on the network structure (43). This contrasts with the broader concept of homophily, which typically refers to similarity based on common characteristics besides network properties (e.g., opinions, taste, age, background). Compared with rewiring based on homophily—which can also contribute to network fragmentation—rewiring based on structural similarity can be less restrictive in contexts where information about opinions and beliefs is not readily available to individuals before the connection is established. Furthermore, rewiring based on structural similarity is a backbone of link recommendation algorithms [e.g., “People you may know” or “Whom to follow” (25) suggestions], which rely on link prediction methods to suggest connections to users (43, 44). Importantly, our model combines three key ingredients: 1) Links are formed according to structural similarity, based on common neighbors, which is one of the simplest link prediction methods (43); this way, we do not assume a priori that individuals with similar opinions are likely to become connected [as recent works underline, sorting can be incidental to politics (45, 46)]. 2) Then, to examine opinion updating, we adapt a recent model that covers the interplay of social reinforcement and issue controversy to promote radicalization on social networks (39). 3) Last, we explicitly consider that nodes can react differently to out-group links, either converging in their opinions (10, 47) or polarizing further (48–50).We find that establishing links based on structural similarity alone [a process that is likely to be reinforced by link recommendation algorithms—see SI Appendix, Fig. S10 and previous work pointing that such algorithms affect a social network topology and increase their clustering coefficient (26–28)] contributes to opinion polarization. While our model sheds light on the effect of link recommendation algorithms on opinion formation and polarization dynamics, we also offer a justification for polarization to emerge through structural similarity-based rewiring, in the absence of explicit opinion-similarity rewiring (34, 36, 39, 51), confidence-bounds (37, 38, 40), or rewiring based on concordant messages (42).^* Second, we find that the effects of structural similarity-based rewiring are exacerbated if even moderate opinions have high social influence. Finally, we combine nodes that react differently to out-group contacts: “converging” nodes, which converge if exposed to different opinions (10, 21, 52), and “polarizing” nodes, which diverge when exposed to different viewpoints (48–50). We observe that the coexistence of both types of nodes can contribute to moderate opinions. Polarizing nodes develop radical opinions, and converging nodes, influenced by opposing viewpoints, yield more temperate ones. However, again, link recommendation algorithms impact this process: Given the existence of communities isolated to a greater degree through link recommendation, converging nodes may find it harder to access diverse viewpoints, which, in general, contributes to increasing the adoption of extreme opinions.     

Electrochemical borylation of carboxylic acids

A simple electrochemically mediated method for the conversion of alkyl carboxylic acids to their borylated congeners is presented. This protocol features an undivided cell setup with inexpensive carbon-based electrodes and exhibits a broad substrate scope and scalability in both flow and batch reactors. The use of this method in challenging contexts is exemplified with a modular formal synthesis of jawsamycin, a natural product harboring five cyclopropane rings.

Boronic acids are among the most malleable functional groups in organic chemistry as they can be converted into almost any other functionality (1–3). Aside from these versatile interconversions, their use in the pharmaceutical industry is gaining traction, resulting in approved drugs such as Velcade, Ninlaro, and Vabomere (4). It has been shown that boronic acids can be rapidly installed from simple alkyl halides (5–19) or alkyl carboxylic acids through the intermediacy of redox-active esters (RAEs) (Fig. 1A) (20–24). Our laboratory has shown that both Ni (20) and Cu (21) can facilitate this reaction. Conversely, Aggarwal and coworkers (22) and Li and coworkers (23) demonstrated photochemical variations of the same transformation. While these state-of-the-art approaches provide complementary access to alkyl boronic acids, each one poses certain challenges. For example, the requirement of excess boron source and pyrophoric MeLi under Ni catalysis is not ideal. Although more cost-effective and operationally simple, Cu-catalyzed borylation conditions can be challenging on scale due to the heterogeneity resulting from the large excess of LiOH•H₂O required. In addition to its limited scope, Li and coworkers’ protocol requires 4 equivalence of B₂pin₂ and an expensive Ir photocatalyst. The simplicity of Aggarwal and coworkers’ approach is appealing in this regard and represents an important precedent for the current study.Open in a separate windowFig. 1.(A) Prior approaches to access alkyl boronic esters from activated acids. (B) Inspiration for initiating SET events electrochemically to achieve borylation. (C) Summary of this work.At the heart of each method described above, the underlying mechanism relies on a single electron transfer (SET) event to promote decarboxylation and form an alkyl radical species. In parallel, the related borylation of aryl halides via a highly reactive aryl radical can also be promoted by SET. While numerous methods have demonstrated that light can trigger this mechanism (Fig. 1B) (16, 25–31), simple electrochemical cathodic reduction can elicit the same outcome (32–35). It was postulated that similar electrochemically driven reactivity could be translated to alkyl RAEs. The development of such a transformation would be highly enabling, as synthetic organic electrochemistry allows the direct addition or removal of electrons to a reaction, representing an incredibly efficient way to forge new bonds (36–40). This disclosure reports a mild, scalable, and operationally simple electrochemical decarboxylative borylation (Fig. 1C) not reliant on transition metals or stoichiometric reductants. In addition to mechanistic studies of this interesting transformation, applications to a variety of alkyl RAEs, comparison to known decarboxylative borylation methods, and a formal synthesis of the polycyclopropane natural product jawsamycin [(–)-FR-900848] are presented.     

Self-assembly of amphiphilic Janus dendrimers into uniform onion-like dendrimersomes with predictable size and number of bilayers

A constitutional isomeric library synthesized by a modular approach has been used to discover six amphiphilic Janus dendrimer primary structures, which self-assemble into uniform onion-like vesicles with predictable dimensions and number of internal bilayers. These vesicles, denoted onion-like dendrimersomes, are assembled by simple injection of a solution of Janus dendrimer in a water-miscible solvent into water or buffer. These dendrimersomes provide mimics of double-bilayer and multibilayer biological membranes with dimensions and number of bilayers predicted by the Janus compound concentration in water. The simple injection method of preparation is accessible without any special equipment, generating uniform vesicles, and thus provides a promising tool for fundamental studies as well as technological applications in nanomedicine and other fields.Most living organisms contain single-bilayer membranes composed of lipids, glycolipids, cholesterol, transmembrane proteins, and glycoproteins (1). Gram-negative bacteria (2, 3) and the cell nucleus (4), however, exhibit a strikingly special envelope that consists of a concentric double-bilayer membrane. More complex membranes are also encountered in cells and their various organelles, such as multivesicular structures of eukaryotic cells (5) and endosomes (6), and multibilayer structures of endoplasmic reticulum (7, 8), myelin (9, 10), and multilamellar bodies (11, 12). This diversity of biological membranes inspired corresponding biological mimics. Liposomes (Fig. 1) self-assembled from phospholipids are the first mimics of single-bilayer biological membranes (13–16), but they are polydisperse, unstable, and permeable (14). Stealth liposomes coassembled from phospholipids, cholesterol, and phospholipids conjugated with poly(ethylene glycol) exhibit improved stability, permeability, and mechanical properties (17–20). Polymersomes (21–24) assembled from amphiphilic block copolymers exhibit better mechanical properties and permeability, but are not always biocompatible and are polydisperse. Dendrimersomes (25–28) self-assembled from amphiphilic Janus dendrimers and minidendrimers (26–28) have also been elaborated to mimic single-bilayer biological membranes. Amphiphilic Janus dendrimers take advantage of multivalency both in their hydrophobic and hydrophilic parts (23, 29–32). Dendrimersomes are assembled by simple injection (33) of a solution of an amphiphilic Janus dendrimer (26) in a water-soluble solvent into water or buffer and produce uniform (34), impermeable, and stable vesicles with excellent mechanical properties. In addition, their size and properties can be predicted by their primary structure (27). Amphiphilic Janus glycodendrimers self-assemble into glycodendrimersomes that mimic the glycan ligands of biological membranes (35). They have been demonstrated to be bioactive toward biomedically relevant bacterial, plant, and human lectins, and could have numerous applications in nanomedicine (20).Open in a separate windowFig. 1.Strategies for the preparation of single-bilayer vesicles and multibilayer onion-like vesicles.More complex and functional cell mimics such as multivesicular vesicles (36, 37) and multibilayer onion-like vesicles (38–40) have also been discovered. Multivesicular vesicles compartmentalize a larger vesicle (37) whereas multibilayer onion-like vesicles consist of concentric alternating bilayers (40). Currently multibilayer vesicles are obtained by very complex and time-consuming methods that do not control their size (39) and size distribution (40) in a precise way. Here we report the discovery of “single–single” (28) amphiphilic Janus dendrimer primary structures that self-assemble into uniform multibilayer onion-like dendrimersomes (Fig. 1) with predictable size and number of bilayers by simple injection of their solution into water or buffer.     

The ecology of religious beliefs

Although ecological forces are known to shape the expression of sociality across a broad range of biological taxa, their role in shaping human behavior is currently disputed. Both comparative and experimental evidence indicate that beliefs in moralizing high gods promote cooperation among humans, a behavioral attribute known to correlate with environmental harshness in nonhuman animals. Here we combine fine-grained bioclimatic data with the latest statistical tools from ecology and the social sciences to evaluate the potential effects of environmental forces, language history, and culture on the global distribution of belief in moralizing high gods (n = 583 societies). After simultaneously accounting for potential nonindependence among societies because of shared ancestry and cultural diffusion, we find that these beliefs are more prevalent among societies that inhabit poorer environments and are more prone to ecological duress. In addition, we find that these beliefs are more likely in politically complex societies that recognize rights to movable property. Overall, our multimodel inference approach predicts the global distribution of beliefs in moralizing high gods with an accuracy of 91%, and estimates the relative importance of different potential mechanisms by which this spatial pattern may have arisen. The emerging picture is neither one of pure cultural transmission nor of simple ecological determinism, but rather a complex mixture of social, cultural, and environmental influences. Our methods and findings provide a blueprint for how the increasing wealth of ecological, linguistic, and historical data can be leveraged to understand the forces that have shaped the behavior of our own species.Ecological uncertainty has long been implicated in the expression of cooperation and conflict in animal societies (1). For example, climatic variation predicts the incidence and distribution of cooperative breeding in birds (2, 3), and ecological uncertainty is associated with group living in mammals (4). These findings suggest that ecological duress can promote sociality when the benefits of cooperating during difficult periods outweigh the potential costs during benign ones (3). Although similar ecological pressures are likely to act upon humans (5, 6), the extent to which they have shaped the development of our own sociality remains disputed and is currently unclear (7–9).Human behavior is often mediated by socially transmitted conventions—that is, cultural norms—that govern expectations and behaviors during social interactions (10, 11). In particular, religious beliefs are thought to be a powerful mechanism for the enforcement of social rules (12–15). In support of these ideas, comparative studies have shown that a belief in moralizing high gods—defined as supernatural beings believed to have created or govern all reality, intervene in human affairs, and enforce or support human morality (7)—tends to be more prevalent among societies that recognize rights to movable property (9, 16), as well as in those that exhibit higher levels of political complexity (17), subsistence productivity (17), and norm compliance (18). In addition, psychological experiments have found that moralizing high god concepts can reduce levels of cheating (14) and increase willingness to be fair (19) and to cooperate (13). Such findings have provoked speculation that the prominence of moralizing gods at the level of cultures is a better predictor of cooperation in humans than individual religious beliefs (20). However, debates persist because statistical models assessing historical and regional dependencies are rare (e.g., refs. 7 and 9), and those that exist are limited in scope (21).It has long been theorized that the global distribution of religious beliefs may be shaped by ecological factors (7–9). Recent empirical findings indicate that beliefs in moralizing high gods not only intensify (22–27), but also promote cooperation (28–33) in situations of increased environmental risk. In addition, these findings indicate that ecological threats can strengthen mechanisms of norm enforcement in human groups (34). Given the strong correlation between cooperation and ecological uncertainty in nonhuman animals (2, 3), these findings are especially suggestive of a link between ecology and religion. In particular, the similarity between the global distribution of belief in moralizing high gods (Fig. 1), and that of social cooperation in birds (see figure 1A in ref. 2), raises the possibility that the distribution of this type of religious belief might also be shaped by ecological factors. Nevertheless, the evidence for an association between religion and ecology is currently mixed. For example, prior studies have indicated that resource scarcity is both positively (8, 9) and negatively (7) associated with a belief in moralizing high gods. These apparently contradictory findings may be the product of methodological issues. Specifically, some of the studies involved (7, 8) failed to account for the nonindependence of societies as a result of spatial proximity and common ancestry [Galton’s problem (35)], whereas others were based on a relatively small sample of cultures (9) that may have been unduly influenced by a few preclassical cultures (21). In addition, all of these studies used extremely coarse metrics of ecology [e.g., subjective ratings of resource abundance in (7, 8), or indirect measures of agricultural potential in (9)] that could have led to a distorted view of the role of environmental factors in shaping the spatial variation of religious beliefs.Open in a separate windowFig. 1.Global distribution of societies that exhibit beliefs in moralizing high gods (blue) or not (i.e., atheism or beliefs in nonmoralizing deities or spirits in red). The underlying map depicts the mean values of net primary productivity (i.e., the net balance of monthly consumption relative to production of carbon dioxide by living plants) in gray scale. Darker localities reflect places with greater potential for overall plant growth.To rigorously test for an association between ecology and beliefs in moralizing high gods, we systematically modeled the effects of basic environmental variables while accounting for the effects of known covariates of religious beliefs and simultaneously adjusting for potential dependencies related to shared cultural ancestry—as measured by patterns of shared language origin (35)—and spatial diffusion—as measured by the effects of cultural traits in neighboring groups (Methods). We consider the following covariates in our models, all positively correlated with a belief in moralizing high gods: political complexity (17), practice of agriculture (17), and recognition of rights to movable property, as measured by the practice of animal husbandry (9, 16). Our analysis is based on a global cross-cultural sample of 583 human societies (36, 37) that occupy a range of different habitats and are exposed to a wide array of environmental conditions (Fig. 1). Through a comprehensive characterization of key political and cultural variables, together with a rigorous treatment of key environmental factors, we offer a systematic test for whether the global distribution of belief in moralizing high gods is associated with underlying variation in ecological parameters.     

Volcanically driven lacustrine ecosystem changes during the Carnian Pluvial Episode (Late Triassic)

The Late Triassic Carnian Pluvial Episode (CPE) saw a dramatic increase in global humidity and temperature that has been linked to the large-scale volcanism of the Wrangellia large igneous province. The climatic changes coincide with a major biological turnover on land that included the ascent of the dinosaurs and the origin of modern conifers. However, linking the disparate cause and effects of the CPE has yet to be achieved because of the lack of a detailed terrestrial record of these events. Here, we present a multidisciplinary record of volcanism and environmental change from an expanded Carnian lake succession of the Jiyuan Basin, North China. New U–Pb zircon dating, high-resolution chemostratigraphy, and palynological and sedimentological data reveal that terrestrial conditions in the region were in remarkable lockstep with the large-scale volcanism. Using the sedimentary mercury record as a proxy for eruptions reveals four discrete episodes during the CPE interval (ca. 234.0 to 232.4 Ma). Each eruptive phase correlated with large, negative C isotope excursions and major climatic changes to more humid conditions (marked by increased importance of hygrophytic plants), lake expansion, and eutrophication. Our results show that large igneous province eruptions can occur in multiple, discrete pulses, rather than showing a simple acme-and-decline history, and demonstrate their powerful ability to alter the global C cycle, cause climate change, and drive macroevolution, at least in the Triassic.

The Carnian Pluvial Episode (CPE; ca. 234 to ∼232 Ma; Late Triassic) was an interval of significant changes in global climate and biotas (1, 2). It was characterized by warming (3, 4) and enhancement of the hydrological cycle (5–7), linked to repeated C isotope fluctuations (8–11) and accompanied by increased rainfall (1), intensified continental weathering (9, 12), shutdown of carbonate platforms (13), widespread marine anoxia (4), and substantial biological turnover (1, 2, 10). Available stratigraphic data indicate that the Carnian climatic changes broadly coincide with, and could have been driven by, the emplacement of the Wrangellia large igneous province (LIP) (2, 4, 7, 8, 10, 14, 15) (Fig. 1A). It is postulated that the voluminous emission of volcanic CO₂, with consequent global warming and enhancement of a mega-monsoonal climate, was responsible for the CPE (9, 16), although the link is imprecise (2, 17) because the interval of Wrangellian eruptions have not yet been traced in the sedimentary records encompassing the CPE.Open in a separate windowFig. 1.Location and geological context for the study area. (A) Paleogeographic reconstruction for the Carnian (∼237 to 227 Ma) Stage (Late Triassic), showing locations of the study area and volcanic centers (revised after ref. 4, with volcanic data from refs. 4, 7, 49, and 50). (B) Tectono-paleogeographic map of the NCP during the Late Triassic (modified from ref. 21), showing the location of the study area. (C) Stratigraphic framework of the Upper Chunshuyao Formation (CSY) to the Lower Yangshuzhuang (YSZ) Formation from the Jiyuan Basin (modified from ref. 20). Abbreviations: LIP, Large Igneous Province; QDOB, Qingling-Dabie Orogenic Belt; S-NCP, southern NCP; SCP, South China Plate; Fm., Formation; m & s, coal, mudstone, and silty mudstone; s., sandstone; c, conglomerate; Dep. env., Depositional environment; and C.-P., Coniopteris-Phoenicopsis.The CPE was originally identified because of changes in terrestrial sedimentation, but most subsequent studies have been on marine strata (2, 4, 7–10). By contrast, much less is known about the effects of this climatic episode on terrestrial environments (2), although there were major extinctions and radiations among animals (including dinosaurs, crocodiles, turtles, and the first mammals and insects) and modern conifer families (2). Some of the new organisms may have flourished because of the spread of humid environments, such as the turtles and metoposaurids (18, 19).In this study, we have investigated terrestrial sediments from the Zuanjing-1 (ZJ-1) borehole in the Jiyuan Basin of the southern North China Plate (NCP) and use zircon U–Pb ages from two tuffaceous claystone horizons, fossil plant biostratigraphy, and organic C isotope (δ¹³C_org) and Hg chemostratigraphy to identify the CPE and volcanic activity.     

Variation in Rapa Nui (Easter Island) land use indicates production and population peaks prior to European contact

Many researchers believe that prehistoric Rapa Nui society collapsed because of centuries of unchecked population growth within a fragile environment. Recently, the notion of societal collapse has been questioned with the suggestion that extreme societal and demographic change occurred only after European contact in AD 1722. Establishing the veracity of demographic dynamics has been hindered by the lack of empirical evidence and the inability to establish a precise chronological framework. We use chronometric dates from hydrated obsidian artifacts recovered from habitation sites in regional study areas to evaluate regional land-use within Rapa Nui. The analysis suggests region-specific dynamics including precontact land use decline in some near-coastal and upland areas and postcontact increases and subsequent declines in other coastal locations. These temporal land-use patterns correlate with rainfall variation and soil quality, with poorer environmental locations declining earlier. This analysis confirms that the intensity of land use decreased substantially in some areas of the island before European contact.There is ongoing debate about the demographic trajectory of Rapa Nui (or Easter Island) from its settlement around AD 1200 (1–4) until the arrival of Jesuit missionaries in the 1860s (Fig. 1) (5). The central issue is whether the Rapa Nui population experienced significant demographic decline before European contact in AD 1722. Proponents of this “pre-contact collapse” scenario suggest that environmental degradation reduced food production, and a number of researchers have elaborated a chronological model (6) that argues for a period of warfare, population reduction, and political fragmentation in the AD 1500s (7–13) or late AD 1600s (14–16). Alternately, other researchers view the archaeological evidence as favoring socio-political continuity until Western smallpox, syphilis, and tuberculosis pathogens decimated the population after European contact (17–22).Open in a separate windowFig. 1.A map of Rapa Nui showing the three study areas (pink squares) and locations mentioned in the text. Rainfall isohyets demonstrate the rain shadow effect. Note that the area in the northwest of the island appears to be quite dry, as does the area immediately west of Poike, the peninsula on the extreme east of the island. Both these areas are, in fact, drier than elevation alone would predict. Solid purple dots represent field weather stations. The red dot represents the weather station at the Mataveri airport.There is archaeological evidence for societal change on Rapa Nui, including the manufacture of obsidian spear points, the destruction of elite dwellings, habitation in refuge caves, cannibalism, a change in burial practice, and a marked ideological shift away from ceremonial platform (ahu) structures to the formation of the Birdman (tangata manu) cult centered at Orongo (see ref. 23 for a summary). These changes have been associated with the abandonment of inland field systems and houses and decreased population levels (14–16, 24). The question is when these changes occurred. Poor chronological control over the timing of past events in all these cases makes it difficult to draw firm conclusions as to whether these changes occurred before or after European contact. Oral histories recorded in the early 20th century by Routledge (25) reflect a period of precontact societal upheaval but are shrouded in mythology.Empirical evidence for societal collapse, extensive environmental degradation (other than deforestation), or warfare that could have caused such a collapse before European contact is minimal (20). A recent analysis of radiocarbon dates from throughout Rapa Nui noted the inherent (and severe) ambiguities in radiocarbon calibrations in the time period of interest but concluded that there was demographic continuity into the postcontact era as opposed to population decline during the late precontact period (19). Additional analysis of ¹⁴C and obsidian hydration dates from a smaller study region in Hanga Ho‘onu on the northeast coast also reported continuity of settlement and agricultural activity into the period of European contact (18). For environmental degradation, there is substantial evidence for deforestation (26–30) but its timing and causes have been debated (2, 31–34). Soil erosion occurred in limited areas (i.e., on the older Poike peninsula (35–37), along a small section of the northwest coast, and on the slopes of some of the smaller volcanic cones); however, there is no evidence of widespread soil erosion that could have interfered with agricultural production (38). The assertion that the proliferation of obsidian spear points is an indicator of endemic violence is challenged by lithic use-wear analysis that shows the artifacts to be used extensively in processing vegetation (39, 40).Here we identify spatial and temporal variation in the intensity of land use across portions of Rapa Nui and relate these observations to new data on spatial variation in climate and soil fertility. We base our analysis of land use on obsidian hydration dating (OHD) of tools and flakes, using 428 obsidian hydration dates developed under revised calibrations and protocols (SI Appendix, Table S1) (41, 42). Obsidian nodules were fashioned into everyday working tools and are plentiful at many archaeological sites. We use the quantity of hydration dates as a measure of the amount of discarded material over time and as a proxy for land-use intensity.     

Decoding the information structure underlying the neural representation of concepts

The nature of the representational code underlying conceptual knowledge remains a major unsolved problem in cognitive neuroscience. We assessed the extent to which different representational systems contribute to the instantiation of lexical concepts in high-level, heteromodal cortical areas previously associated with semantic cognition. We found that lexical semantic information can be reliably decoded from a wide range of heteromodal cortical areas in the frontal, parietal, and temporal cortex. In most of these areas, we found a striking advantage for experience-based representational structures (i.e., encoding information about sensory-motor, affective, and other features of phenomenal experience), with little evidence for independent taxonomic or distributional organization. These results were found independently for object and event concepts. Our findings indicate that concept representations in the heteromodal cortex are based, at least in part, on experiential information. They also reveal that, in most heteromodal areas, event concepts have more heterogeneous representations (i.e., they are more easily decodable) than object concepts and that other areas beyond the traditional “semantic hubs” contribute to semantic cognition, particularly the posterior cingulate gyrus and the precuneus.

The capacity for conceptual knowledge is arguably one of the most defining properties of human cognition, and yet it is still unclear how concepts are represented in the brain. Recent developments in functional neuroimaging and computational linguistics have sparked renewed interest in elucidating the information structures and neural circuits underlying concept representation (1–5). Attempts to characterize the representational code for concepts typically involve information structures based on three qualitatively distinct types of information, namely, taxonomic, experiential, and distributional information. As the term implies, a taxonomic information system relies on category membership and intercategory relations. Our tendency to organize objects, events, and experiences into discrete categories has led most authors—dating back at least to Plato (6)—to take taxonomic structure as the central property of conceptual knowledge (7). The taxonomy for concepts is traditionally seen as a hierarchically structured network, with basic-level categories (e.g., “apple,” “orange”) grouped into superordinate categories (e.g., “fruit,” “food”) and subdivided into subordinate categories (e.g., “Gala apple,” “tangerine”) (8). A prominent account in cognitive science maintains that such categories are represented in the mind/brain as purely symbolic entities, whose semantic content and usefulness derive primarily from how they relate to each other (9, 10). Such representations are seen as qualitatively distinct from the sensory-motor processes through which we interact with the world, much like the distinction between software and hardware in digital computers.An experiential representational system, on the other hand, encodes information about the experiences that led to the formation of particular concepts. It is motivated by a view, often referred to as embodied, grounded, or situated semantics, in which concepts arise primarily from generalization over particular experiences, as information originating from the various modality-specific systems (e.g., visual, auditory, tactile, motor, affective) is combined and re-encoded into progressively more schematic representations that are stored in memory. Since, in this view, there is a degree of continuity between conceptual and modality-specific systems, concept representations are thought to reflect the structure of the perceptual, affective, and motor processes involved in those experiences (11–14).Finally, distributional information pertains to statistical patterns of co-occurrence between lexical concepts (i.e., concepts that are widely shared within a population and denoted by a single word) in natural language usage. As is now widely appreciated, these co-occurrence patterns encode a substantial amount of information about word meaning (15–17). Although word co-occurrence patterns primarily encode contextual associations, such as those connecting the words “cow,” “barn,” and “farmer,” semantic similarity information is indirectly encoded since words with similar meanings tend to appear in similar contexts (e.g., “cow” and “horse,” “pencil” and “pen”). This has led some authors to propose that concepts may be represented in the brain, at least in part, in terms of distributional information (15, 18).Whether, and to what extent, each of these types of information plays a role in the neural representation of conceptual knowledge is a topic of intense research and debate. A large body of evidence has emerged from behavioral studies, functional neuroimaging experiments, and neuropsychological assessments of patients with semantic deficits, with results typically interpreted in terms of taxonomic (19–24), experiential (13, 25–34), or distributional (2, 3, 5, 35, 36) accounts. However, the extent to which each of these representational systems plays a role in the neural representation of conceptual knowledge remains controversial (23, 37, 38), in part, because their representations of common lexical concepts are strongly intercorrelated. Patterns of word co-occurrence in natural language are driven in part by taxonomic and experiential similarities between the concepts to which they refer, and the taxonomy of natural categories is systematically related to the experiential attributes of the exemplars (39–41). Consequently, the empirical evidence currently available is unable to discriminate between these representational systems.Several computational models of concept representation have been proposed based on these structures. While earlier models relied heavily on hierarchical taxonomic structure (42, 43), more recent proposals have emphasized the role of experiential and/or distributional information (34, 44–46). The model by Chen and colleagues (45), for example, showed that graded taxonomic structure can emerge from the statistical coherent covariation found across experiences and exemplars without explicitly coding such taxonomic information per se. Other models propose that concepts may be formed through the combination of experiential and distributional information (44, 46), suggesting a dual representational code akin to Paivio’s dual coding theory (47).We investigated the relative contribution of each representational system by deriving quantitative predictions from each system for the similarity structure of a large set of concepts and then using representational similarity analysis (RSA) with high-resolution functional MRI (fMRI) to evaluate those predictions. Unlike the more typical cognitive subtraction technique, RSA focuses on the information structure of the pattern of neural responses to a set of stimuli (48). For a given stimulus set (e.g., words), RSA assesses how well the representational similarity structure predicted by a model matches the neural similarity structure observed from fMRI activation patterns (Fig. 1). This allowed us to directly compare, in quantitative terms, predictions derived from the three representational systems.Open in a separate windowFig. 1.Representational similarity analysis. (A) An fMRI activation map was generated for each concept presented in the study, and the activation across voxels was reshaped as a vector. (B) The neural RDM for the stimulus set was generated by computing the dissimilarity between these vectors (1 − correlation) for every pair of concepts. (C) A model-based RDM was computed from each model, and the similarity between each model’s RDM and the neural RDM was evaluated via Spearman correlation. (D) Anatomically defined ROIs. The dashed line indicates the boundary where temporal lobe ROIs were split into anterior and posterior portions (see main text for acronyms). (E) Cortical areas included in the functionally defined semantic network ROI (49).     

Microscopic origins of the crystallographically preferred growth in evaporation-induced colloidal crystals

Unlike crystalline atomic and ionic solids, texture development due to crystallographically preferred growth in colloidal crystals is less studied. Here we investigate the underlying mechanisms of the texture evolution in an evaporation-induced colloidal assembly process through experiments, modeling, and theoretical analysis. In this widely used approach to obtain large-area colloidal crystals, the colloidal particles are driven to the meniscus via the evaporation of a solvent or matrix precursor solution where they close-pack to form a face-centered cubic colloidal assembly. Via two-dimensional large-area crystallographic mapping, we show that the initial crystal orientation is dominated by the interaction of particles with the meniscus, resulting in the expected coalignment of the close-packed direction with the local meniscus geometry. By combining with crystal structure analysis at a single-particle level, we further reveal that, at the later stage of self-assembly, however, the colloidal crystal undergoes a gradual rotation facilitated by geometrically necessary dislocations (GNDs) and achieves a large-area uniform crystallographic orientation with the close-packed direction perpendicular to the meniscus and parallel to the growth direction. Classical slip analysis, finite element-based mechanical simulation, computational colloidal assembly modeling, and continuum theory unequivocally show that these GNDs result from the tensile stress field along the meniscus direction due to the constrained shrinkage of the colloidal crystal during drying. The generation of GNDs with specific slip systems within individual grains leads to crystallographic rotation to accommodate the mechanical stress. The mechanistic understanding reported here can be utilized to control crystallographic features of colloidal assemblies, and may provide further insights into crystallographically preferred growth in synthetic, biological, and geological crystals.

As an analogy to atomic crystals, colloidal crystals are highly ordered structures formed by colloidal particles with sizes ranging from 100 nm to several micrometers (1–6). In addition to engineering applications such as photonics, sensing, and catalysis (4, 5, 7, 8), colloidal crystals have also been used as model systems to study some fundamental processes in statistical mechanics and mechanical behavior of crystalline solids (9–14). Depending on the nature of interparticle interactions, many equilibrium and nonequilibrium colloidal self-assembly processes have been explored and developed (1, 4). Among them, the evaporation-induced colloidal self-assembly presents a number of advantages, such as large-size fabrication, versatility, and cost and time efficiency (3–5, 15–18). In a typical synthesis where a substrate is immersed vertically or at an angle into a colloidal suspension, the colloidal particles are driven to the meniscus by the evaporation-induced fluid flow and subsequently self-assemble to form a colloidal crystal with the face-centered cubic (fcc) lattice structure and the close-packed {111} plane parallel to the substrate (2, 3, 19–23) (see Fig. 1A for a schematic diagram of the synthetic setup).Open in a separate windowFig. 1.Evaporation-induced coassembly of colloidal crystals. (A) Schematic diagram of the evaporation-induced colloidal coassembly process. “G”, “M”, and “N” refer to “growth,” “meniscus,” and “normal” directions, respectively. The reaction solution contains silica matrix precursor (tetraethyl orthosilicate, TEOS) in addition to colloids. (B) Schematic diagram of the crystallographic system and orientations used in this work. (C and D) Optical image (Top Left) and scanning electron micrograph (SEM) (Bottom Left) of a typical large-area colloidal crystal film before (C) and after (D) calcination. (Right) SEM images of select areas (yellow rectangles) at different magnifications. Corresponding fast-Fourier transform (see Inset in Middle in C) shows the single-crystalline nature of the assembled structure. (E) The 3D reconstruction of the colloidal crystal (left) based on FIB tomography data and (right) after particle detection. (F) Top-view SEM image of the colloidal crystal with crystallographic orientations indicated.While previous research has focused on utilizing the assembled colloidal structures for different applications (4, 5, 7, 8), considerably less effort is directed to understand the self-assembly mechanism itself in this process (17, 24). In particular, despite using the term “colloidal crystals” to highlight the microstructures’ long-range order, an analogy to atomic crystals, little is known regarding the crystallographic evolution of colloidal crystals in relation to the self-assembly process (3, 22, 25). The underlying mechanisms for the puzzling—yet commonly observed—phenomenon of the preferred growth along the close-packed <110> direction in evaporation-induced colloidal crystals are currently not understood (3, 25–29). The <110> growth direction has been observed in a number of processes with a variety of particle chemistries, evaporation rates, and matrix materials (3, 25–28, 30), hinting at a universal underlying mechanism. This behavior is particularly intriguing as the colloidal particles are expected to close-pack parallel to the meniscus, which should lead to the growth along the <112> direction and perpendicular to the <110> direction (16, 26, 31)^*.Preferred growth along specific crystallographic orientations, also known as texture development, is commonly observed in crystalline atomic solids in synthetic systems, biominerals, and geological crystals. While current knowledge recognizes mechanisms such as the oriented nucleation that defines the future crystallographic orientation of the growing crystals and competitive growth in atomic crystals (32–34), the underlying principles for texture development in colloidal crystals remain elusive. Previous hypotheses based on orientation-dependent growth speed and solvent flow resistance are inadequate to provide a universal explanation for different evaporation-induced colloidal self-assembly processes (3, 25–29). A better understanding of the crystallographically preferred growth in colloidal self-assembly processes may shed new light on the crystal growth in atomic, ionic, and molecular systems (35–37). Moreover, mechanistic understanding of the self-assembly processes will allow more precise control of the lattice types, crystallography, and defects to improve the performance and functionality of colloidal assembly structures (38–40).     

Volatile-consuming reactions fracture rocks and self-accelerate fluid flow in the lithosphere

Hydration and carbonation reactions within the Earth cause an increase in solid volume by up to several tens of vol%, which can induce stress and rock fracture. Observations of naturally hydrated and carbonated peridotite suggest that permeability and fluid flow are enhanced by reaction-induced fracturing. However, permeability enhancement during solid-volume–increasing reactions has not been achieved in the laboratory, and the mechanisms of reaction-accelerated fluid flow remain largely unknown. Here, we present experimental evidence of significant permeability enhancement by volume-increasing reactions under confining pressure. The hydromechanical behavior of hydration of sintered periclase [MgO + H₂O → Mg(OH)₂] depends mainly on the initial pore-fluid connectivity. Permeability increased by three orders of magnitude for low-connectivity samples, whereas it decreased by two orders of magnitude for high-connectivity samples. Permeability enhancement was caused by hierarchical fracturing of the reacting materials, whereas a decrease was associated with homogeneous pore clogging by the reaction products. These behaviors suggest that the fluid flow rate, relative to reaction rate, is the main control on hydromechanical evolution during volume-increasing reactions. We suggest that an extremely high reaction rate and low pore-fluid connectivity lead to local stress perturbations and are essential for reaction-induced fracturing and accelerated fluid flow during hydration/carbonation.

Hydration and carbonation reactions in the crust and mantle transport H₂O and CO₂ from Earth’s surface to the interior and control volatile budgets within the Earth (1–6). These reactions are characterized by solid-volume increase, by up to several tens of vol%, which induces stress that may lead to fracturing (7–10). The driving force of such stress generation is the thermodynamic free energy released when metastable anhydrous/noncarbonate minerals react with fluids (7). The stress generated by the reaction has the potential to cause rock fracture and fragmentation (7, 11–13), thereby increasing the reactive surface area and fluid flow and further accelerating the reactions (7, 8, 14). Such chemical breaking of rocks, or reaction-induced fracturing, appears to be important in driving hydration and carbonation reactions to completion (8, 15, 16) in an otherwise self-limiting process where reaction products can clog pores and suppress fluid flow, thereby hindering the reaction (15, 17).Observations of naturally serpentinized and fractured ultramafic rocks indicate a volume increase of 20 to 60% during hydration reactions (13, 18–20), providing evidence of an accelerated supply of fluids during hydration (Fig. 1 A and B). Natural carbonation of ultramafic rocks is also associated with extensive fracture networks, and reaction-induced fracturing is considered a key process in mineral carbonation (Fig. 1C) (7, 8, 21). Numerical simulations indicate a positive feedback between volume-increasing reaction, fracturing, and fluid flow (10, 22–32). Laboratory experiments partially reproduce fracturing during peridotite carbonation, serpentinization, and periclase hydration (29, 33–36); however, hydrothermal flow-through experiments of peridotite serpentinization and carbonation show a decrease in permeability and deceleration of fluid flow and reaction rate (37–42). Observations of the natural carbonation of serpentinized peridotite indicate the decrease in permeability and reduced fluid flow and reaction rate are a consequence of pore clogging related to carbonation (43). Until now, no experimental studies have shown a clear increase in permeability during expansive fluid–rock reactions under confining pressure. As such, despite their geological and environmental importance, the evolution of expansive fluid–rock reactions remains difficult to predict, owing to the complex hydraulic–chemical–mechanical feedbacks underlying these reactions (15, 16, 44). The processes controlling the self-acceleration or deceleration of these reactions remain largely unknown.Open in a separate windowFig. 1.Reaction-induced fractures related to natural hydration/carbonation. (A) Polygonal block of serpentinite cut by planar lizardite veins, extracted from a serpentinite body, San Andreas Lake, California. (B) Photomicrograph of mesh structure in partly serpentinized peridotite, Redwood City serpentinite, California [crossed-polarized light (61)]. (C) Quartz veins in silica–carbonate rocks (i.e., listvenite, a carbonated ultramafic rock) that occur along the boundaries of serpentinite bodies, San Jose, California. ol, olivine; serp, serpentine (lizardite ± antigorite mixture); br, brucite.Here, we use the hydration of periclase to brucite [MgO + H₂O → Mg(OH)₂] as an analog for solid-volume–increasing reactions in the Earth. This reaction produces an extreme solid-volume increase of 119%, with a high reaction rate at 100 to 600 °C (45). Previous experimental studies on periclase hydration have revealed that extensive fracturing occurs under certain conditions (29, 33, 35), yet the links between fracturing experiments (periclase hydration), nonfracturing experiments (peridotite hydration/carbonation), and natural observations are unknown. On the basis of in situ observations of fluid flow during the reactions, we clearly show that fluid flow and associated permeability are strongly enhanced by solid-volume–increasing reactions under confining pressure (i.e., at simulated depth). Based on the experimental results and nondimensional parameterization, we propose that the ratio of the initial fluid flow rate to the reaction rate has a primary control on the self-acceleration and deceleration of fluid flow and reactions during hydration and carbonation within the Earth.     

Revisiting the sedimentary record of the rise of diatoms

Diatoms are a major primary producer in the modern oceans and play a critical role in the marine silica cycle. Their rise to dominance is recognized as one of the largest shifts in Cenozoic marine ecosystems, but the timing of this transition is debated. Here, we use a diagenetic model to examine the effect of sedimentation rate and temperature on the burial efficiency of biogenic silica over the past 66 million years (i.e., the Cenozoic). We find that the changing preservation potential of siliceous microfossils during that time would have overprinted the primary signal of diatom and radiolarian abundance. We generate a taphonomic null hypothesis of the diatom fossil record by assuming a constant flux of diatoms to the sea floor and having diagenetic conditions driven by observed shifts in temperature and sedimentation rate. This null hypothesis produces a late Cenozoic (∼5 Ma to 20 Ma) increase in the relative abundance of fossilized diatoms that is comparable to current empirical records. This suggests that the observed increase in diatom abundance in the sedimentary record may be driven by changing preservation potential. A late Cenozoic rise in diatoms has been causally tied to the rise of grasslands and baleen whales and to declining atmospheric CO₂ levels. Here we suggest that the similarity among these records primarily arises from a common driver—the cooling climate system—that drove enhanced diatom preservation as well as the rise of grasslands and whales, rather than a causal link among them.

Diatoms—phytoplankton that construct their shells out of silica—are critical to marine food webs and geochemical cycles. They account for ∼40% of marine primary productivity today (1), but are a relatively recent contributor to ocean ecosystems (2). Diatoms first appear in the fossil record in the Jurassic (3) and become ecologically dominant among phytoplankton during the Cenozoic (4, 5). Hypothesized explanations for their middle to late Cenozoic rise include the decline in atmospheric CO₂ concentrations over the last 40 My, sea level change, an increase in bioavailable silica reaching the ocean due to elevated continental weathering and/or the expansion of grasslands, and changes in nutrient focusing due to cooler temperatures, among others (5–9).The timing and cause of diatoms'' ascension is important beyond simply reconstructing the history of marine primary producers—it represents a major shift in Earth''s silica and carbon cycles. Diatoms are believed to have drawn down ocean silica concentrations to their lowest levels in Earth''s history (10), which, studies suggest, could have fundamentally changed climate regulation by altering marine authigenic clay formation (11, 12). A shift from calcifying to silicifying plankton also partially decouples inorganic and organic carbon and leads to a tighter coupling of organic carbon (along with nitrogen and phosphorous) to silica (3, 13, 14). In addition, the evolution of relatively large, well-protected phytoplankton lineages including diatoms, coccolithophores, and dinoflagellates, and their subsequent rise in ecological significance, is hypothesized to be the bottom-up impetus for massive ocean ecosystem restructuring in the Mesozoic and Cenozoic (15).Recent work (16–18) has called into question the classic timeline of diatoms'' increase in abundance and diversity (Fig. 1A). It has been assumed, based on fossil databases, that diatom diversity and abundance were generally very low at the beginning of the Cenozoic and increased toward the present, with a rapid rise beginning around the middle Miocene (23 Ma to 5 Ma) (8, 19, 20). Diatom abundance has, for the most part, been inferred from diatom diversity (21–23), although there is a similar increase in the relative abundance of diatoms in deep-sea sediments (5). Punctuating this long-term trend, siliceous microfossil (and radiolarian) abundance peaks in the Middle Eocene (5, 24) and is followed by a peak in diatom diversity in the latest Eocene to early Oligocene (10, 20, 21, 25, 26). Prior to the ecological rise of diatoms, radiolarians, a group of heterotrophic to mixotrophic protists, were the dominant pelagic silicifiers. As diatoms expanded, seawater silica concentrations are believed to have declined more than tenfold, leading to range contractions, reduced silicification, and reduced abundance in radiolarians and other silicifiers (11, 22, 23, 27–30). However, paired sponge and radiolarian silicon isotope work suggests roughly constant surface water silica concentrations between the latest Paleocene (60 Ma) and the Oligocene (33 Ma), at levels equivalent to modern surface ocean concentrations (<60 µM) (17) (Fig. 1). The Si isotope proxy builds from the observations that the extent of fractionation in sponges is strongly dependent on ambient dissolved Si concentration, while fractionation in radiolarians is mostly Si concentration independent (17, 31–36). In other words, these Si isotope findings suggest that any diatom-driven drawdown of silica must have occurred prior to the late Paleocene. Consistent with this alternative, Si isotope hypothesis, sponge reefs and hypersilicification in neritic sponges (indicative of high silica concentrations) disappeared in the Cretaceous to lower Paleocene (37). However, changes in Si isotope values in the Southern Ocean suggest yet another chronology, with diatom abundance increasing to near modern levels during the Eocene (10).Open in a separate windowFig. 1.Evidence for changes in the silica cycle over the Cenozoic. (A) Trends in diatom diversity according to two calculations [dotted green line, Barron Diatom Catalogue; solid green line, Neptune Database (96); both as reported in ref. 20] roughly coincide with that of whales (blue line) (97). Similarly, the expansion of terrestrial grassland ecosystems (yellow bar) (98–100) and grazers (red dots, hypsodonty index from ref. 21) coincides with an increase in the relative abundance of diatoms (orange line is 1.5-My running median relative diatom to radiolarian abundances from ref. 5; orange envelope shows interquartile range; both begin at 48 Ma, before which data are too scarce). (B) Other normalized diatom diversity curves show a much earlier peak (and then drop) (21), and δ³⁰Si from radiolarians and sponges indicate consistent ocean [Si] as far back as 61 Ma, suggesting diatoms did not increase their ecological impact since that time (17). Taxon silhouettes are from Phylopic.Here we consider whether secular change in the preservation potential of biogenic silica could reconcile this apparently conflicting evidence on diatoms and the evolution of the modern silica cycle. Two of the main factors determining whether biogenic silica makes it into the rock record are bottom-water temperature and sedimentation rate. Sedimentation rate determines how quickly silica is removed from the (diagenetically active) reactive zone beneath the sediment−water interface, and temperature determines the rates of dissolution in that zone (38). Both have changed through the Cenozoic (39–44), with declining deep-sea temperatures and increasing sedimentation rates correlated to declining atmospheric CO₂ levels, global cooling, and evolving ocean basins (45–49). Here we use a diagenetic model to investigate the effect of secular changes in deep-sea sedimentation rate and porewater temperature over the Cenozoic on opal burial efficiency (i.e., the proportion of opal rain reaching the seafloor that is permanently sequestered), and how this relates to the apparent rise of diatoms over the same interval. We generate a taphonomic null hypothesis for the fossil record of diatom abundance that explicitly assumes that there is no change in the flux of diatoms to the seafloor through the Cenozoic, and thereby quantifies and constrains the potential effect of changing diagenetic conditions on the interpretation of the siliceous microfossil record.     

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).     

A 5,000-year vegetation and fire history for tierra firme forests in the Medio Putumayo-Algodón watersheds,northeastern Peru

This paper addresses an important debate in Amazonian studies; namely, the scale, intensity, and nature of human modification of the forests in prehistory. Phytolith and charcoal analysis of terrestrial soils underneath mature tierra firme (nonflooded, nonriverine) forests in the remote Medio Putumayo-Algodón watersheds, northeastern Peru, provide a vegetation and fire history spanning at least the past 5,000 y. A tree inventory carried out in the region enables calibration of ancient phytolith records with standing vegetation and estimates of palm species densities on the landscape through time. Phytolith records show no evidence for forest clearing or agriculture with major annual seed and root crops. Frequencies of important economic palms such as Oenocarpus, Euterpe, Bactris, and Astrocaryum spp., some of which contain hyperdominant species in the modern flora, do not increase through prehistoric time. This indicates pre-Columbian occupations, if documented in the region with future research, did not significantly increase the abundance of those species through management or cultivation. Phytoliths from other arboreal and woody species similarly reflect a stable forest structure and diversity throughout the records. Charcoal ¹⁴C dates evidence local forest burning between ca. 2,800 and 1,400 y ago. Our data support previous research indicating that considerable areas of some Amazonian tierra firme forests were not significantly impacted by human activities during the prehistoric era. Rather, it appears that over the last 5,000 y, indigenous populations in this region coexisted with, and helped maintain, large expanses of relatively unmodified forest, as they continue to do today.

More than 50 y ago, prominent scholars argued that due to severe environmental constraints (e.g., poor natural resources), prehistoric cultures in the Amazon Basin were mainly small and mobile with little cultural complexity, and exerted low environmental impacts (1, 2). Contentious debates ensued and have been ongoing ever since. Empirical data accumulated during the past 10 to 20 y have made it clear that during the late Holocene beginning about 3,000 y ago dense, permanent settlements with considerable cultural complexity had developed along major watercourses and some of their tributaries, in seasonal savannas/areas of poor drainage, and in seasonally dry forest. These populations exerted significant, sometimes profound, regional-scale impacts on landscapes, including with raised agricultural fields, fish weirs, mound settlements, roads, geometric earthworks called geoglyphs, and the presence of highly modified anthropic soils, called terra pretas or “Amazonian Dark Earths” (Fig. 1) (e.g., refs. 3–15).Open in a separate windowFig. 1.Location of study region (MP-A) and other Amazonian sites discussed in the text. River names are in blue. The black numbers represent major pre-Columbian archaeological sites with extensive human alterations (1, Marajó Island; 2, Santarém; 3, Upper Xingu; 4, Central Amazon Project; 5, Bolivian sites) (3, 5–10, 14, 15). ADE, terra preta locations (e.g., refs. 19 and 20); triangles are geoglyph sites (6, 8). The white circles are terrestrial soil locations previously studied by Piperno and McMichael (29, 31–33, 54) (Ac, Acre; Am, Amacayacu; Ay, Lake Ayauchi; B, Barcelos; GP, lakes Gentry-Parker; Iq, Iquitos to Nauta; LA, Los Amigos; PVM, Porto Velho to Manaus; T, Tefe).An important, current debate that frames this paper centers not on whether some regions of the pre-Columbian Amazon supported large and complex human societies, but rather on the spatial scales, degrees, and types of cultural impacts across this continental-size landscape. Some investigators drawing largely on available archaeological data and studies of modern floristic composition of selected forests, argue that heavily modified “domesticated” landscapes were widespread across Amazonia at the end of prehistory, and these impacts significantly structure the vegetation today, even promoting higher diversity than before (e.g., refs. 14–21). It is believed that widespread forms of agroforestry with planted, orchard-like formations or other forest management strategies involving the care and possible enrichment of several dozens of economically important native species have resulted in long-term legacies left on forest composition (e.g., refs. 14–22). Some (20) propose that human influences played strong roles in the enrichment of “hyperdominant” trees, which are disproportionately common elements in the modern flora (sensu ref. 23). Some even argue that prehistoric fires and forest clearance were so spatially extensive that post-Columbian reforestation upon the tragic consequences of European contact was a principal contributor to decreasing atmospheric CO₂ levels and the onset of the “Little Ice Age” (24, 25).However, modern floristic studies are often located in the vicinity of known archaeological sites and/or near watercourses (26). Many edible trees in these studies are early successional and would not be expected to remain as significant forest elements for hundreds of years after abandonment. Historic-period impacts well-known in some regions to have been profound have been paid little attention and may be mistaken for prehistoric legacies (26–28). Moreover, existing phytolith and charcoal data from terrestrial soils underneath standing tierra firme forest in some areas of the central and western Amazon with no known archaeological occupations nearby exhibit little to no evidence for long-term human occupation, anthropic soils, agriculture, forest clearing or other significant vegetation change, or recurrent/extensive fires during the past several thousand years (Fig. 1) (29–33). Even such analyses of terrestrial soils of lake watersheds in western Amazonia known to have been occupied and farmed in prehistory revealed no spatially extensive deforestation of the watersheds, as significant human impacts most often occurred in areas closest to the lakes (Fig. 1) (34). Furthermore, vast areas have yet to be studied by archaeologists and paleoecologists, particularly the tierra firme forests that account for 95% of the land area of Amazonia.To further inform these issues, we report here a vegetation and fire history spanning 5,000 y derived from phytolith and charcoal studies of terrestrial soils underneath mature tierra firme forest in northeastern Peru. Phytoliths, the silica bodies produced by many Neotropical plants, are well preserved in terrestrial soils unlike pollen, and are deposited locally. They can be used to identify different tropical vegetational formations, such as old-growth forest, early successional vegetation typical of human disturbances including forest clearings, a number of annual seed and root crops, and trees thought to have been cultivated or managed in prehistory (e.g., refs. 29–33 and 35).     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Chirality-matched catalyst-controlled macrocyclization reactions

Macrocycles, formally defined as compounds that contain a ring with 12 or more atoms, continue to attract great interest due to their important applications in physical, pharmacological, and environmental sciences. In syntheses of macrocyclic compounds, promoting intramolecular over intermolecular reactions in the ring-closing step is often a key challenge. Furthermore, syntheses of macrocycles with stereogenic elements confer an additional challenge, while access to such macrocycles are of great interest. Herein, we report the remarkable effect peptide-based catalysts can have in promoting efficient macrocyclization reactions. We show that the chirality of the catalyst is essential for promoting favorable, matched transition-state relationships that favor macrocyclization of substrates with preexisting stereogenic elements; curiously, the chirality of the catalyst is essential for successful reactions, even though no new static (i.e., not “dynamic”) stereogenic elements are created. Control experiments involving either achiral variants of the catalyst or the enantiomeric form of the catalyst fail to deliver the macrocycles in significant quantity in head-to-head comparisons. The generality of the phenomenon, demonstrated here with a number of substrates, stimulates analogies to enzymatic catalysts that produce naturally occurring macrocycles, presumably through related, catalyst-defined peripheral interactions with their acyclic substrates.

Macrocyclic compounds are known to perform a myriad of functions in the physical and biological sciences. From cyclodextrins that mediate analyte separations (1) to porphyrin cofactors that sit in enzyme active sites (2, 3) and to potent biologically active, macrocyclic natural products (4) and synthetic variants (5–7), these structures underpin a wide variety of molecular functions (Fig. 1A). In drug development, such compounds are highly coveted, as their conformationally restricted structures can lead to higher affinity for the desired target and often confer additional metabolic stability (8–13). Accordingly, there exists an entire synthetic chemistry enterprise focused on efficient formation and functionalization of macrocycles (14–18).Open in a separate windowFig. 1.(A) Examples of macrocyclic compounds with important applications. HCV, hepatitis C virus. (B) Use of chiral ligands in metal-catalyzed or mediated stereoselective macrocyclization reactions. (C) Remote desymmetrization using guanidinylated ligands via Ullmann coupling. (D) This work: use of copper/peptidyl complexes for macrocyclization and the exploration of matched and mismatched effect.In syntheses of macrocyclic compounds, the ring-closing step is often considered the most challenging step, as competing di- and oligomerization pathways must be overcome to favor the intramolecular reaction (14). High-dilution conditions are commonly employed to favor macrocyclization of linear precursors (19). Substrate preorganization can also play a key role in overcoming otherwise high entropic barriers associated with multiple conformational states that are not suited for ring formation. Such preorganization is most often achieved in synthetic chemistry through substrate design (14, 20–22). Catalyst or reagent controls that impose conformational benefits that favor ring formation are less well known. Yet, critical precedents include templating through metal-substrate complexation (23, 24), catalysis by foldamers (25) or enzymes (26–29), or, in rare instances, by small molecules (discussed below). Characterization of biosynthetic macrocyclization also points to related mechanistic issues and attributes for efficient macrocyclizations (30–34). Coupling macrocyclization reactions to the creation of stereogenic elements is also rare (35). Metal-mediated reactions have been applied toward stereoselective macrocyclizations wherein chiral ligands transmit stereochemical information to the products (Fig. 1B). For example, atroposelective ring closure via Heck coupling has been applied in the asymmetric total synthesis of isoplagiochin D by Speicher and coworkers (36–40). Similarly, atroposelective syntheses of (+)-galeon and other diarylether heptanoid natural products were achieved via Ullman coupling using N-methyl proline by Salih and Beaudry (41). Finally, Reddy and Corey reported the enantioselective syntheses of cyclic terpenes by In-catalyzed allylation utilizing a chiral prolinol-based ligand (42). While these examples collectively illustrate the utility of chiral ligands in stereoselective macrocyclizations, such examples remain limited.We envisioned a different role for chiral catalysts when addressing intrinsically disfavored macrocyclization reactions. When unfavorable macrocyclization reactions are confronted, we hypothesized that a catalyst–substrate interaction might provide transient conformational restriction that could promote macrocyclization. To address this question, we chose to explore whether or not a chiral catalyst-controlled macrocyclization might be possible with peptidyl copper complexes. In the context of the medicinally ubiquitous diarylmethane scaffold, we had previously demonstrated the capacity for remote asymmetric induction in a series of bimolecular desymmetrizations using bifunctional, tetramethylguanidinylated peptide ligands. For example, we showed that peptidyl copper complexes were able to differentiate between the two aryl bromides during C–C, C–O, and C–N cross-coupling reactions (Fig. 1C) (43–45). Moreover, in these intermolecular desymmetrizations, a correlation between enantioselectivity and conversion was observed, revealing the catalyst’s ability to perform not only enantiotopic group discrimination but also kinetic resolution on the monocoupled product as the reaction proceeds (44). This latter observation stimulated our speculation that if an internal nucleophile were present to undergo intramolecular cross-coupling to form a macrocycle, stereochemically sensitive interactions (so-called matched and mismatched effects) (46) could be observed (Fig. 1D). Ideally, we anticipated that transition state–stabilizing interactions might even prove decisive in matched cases, and the absence of catalyst–substrate stabilizing interactions might account for the absence of macrocyclization for these otherwise intrinsically unfavorable reactions. Herein, we disclose the explicit observation of these effects in chiral catalyst-controlled macrocyclization reactions.     

Climate change and physical disturbance cause similar community shifts in biological soil crusts

Biological soil crusts (biocrusts)—communities of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface—are fundamental components of drylands worldwide, and destruction of biocrusts dramatically alters biogeochemical processes, hydrology, surface energy balance, and vegetation cover. Although there has been long-standing concern over impacts of physical disturbances on biocrusts (e.g., trampling by livestock, damage from vehicles), there is increasing concern over the potential for climate change to alter biocrust community structure. Using long-term data from the Colorado Plateau, we examined the effects of 10 y of experimental warming and altered precipitation (in full-factorial design) on biocrust communities and compared the effects of altered climate with those of long-term physical disturbance (>10 y of replicated human trampling). Surprisingly, altered climate and physical disturbance treatments had similar effects on biocrust community structure. Warming, altered precipitation frequency [an increase of small (1.2 mm) summer rainfall events], and physical disturbance from trampling all promoted early successional community states marked by dramatic declines in moss cover and increases in cyanobacteria cover, with more variable effects on lichens. Although the pace of community change varied significantly among treatments, our results suggest that multiple aspects of climate change will affect biocrusts to the same degree as physical disturbance. This is particularly disconcerting in the context of warming, as temperatures for drylands are projected to increase beyond those imposed as treatments in our study.The potential for ecological state transitions in response to global change, particularly transitions that promote feedbacks to terrestrial biogeochemical cycling, is a growing concern (1–6). Anticipating state transitions in terrestrial ecosystems largely hinges on understanding the response of primary producers to warming temperatures, altered precipitation patterns, and novel disturbance regimes (4–7). In arid and semiarid ecosystems (drylands), a substantial portion of primary production can take place in biological soil crusts (biocrusts; Fig. 1) (8, 9), which are communities of mosses, lichens, cyanobacteria, and heterotrophs living at the soil surface that can constitute up to 70% of dryland ground cover (10–12).Open in a separate windowFig. 1.Biocrusts can locally regulate ecosystem processes and cover large portions of dryland ecosystems as in A (photo by Bill Bowman). Biocrusts are sensitive to physical disturbances from vehicles and trampling by livestock or people as depicted in B, which shows an experimentally trampled plot (foreground) bordered by undisturbed biocrust (background).Biocrust organisms are adapted to limited moisture and low nutrient conditions and respond rapidly to pulsed, dynamic environmental conditions (13–16). Due to their extensive cover and rapid responses to even small inputs of moisture and nutrients, biocrusts often locally regulate soil hydrology and the cycling of soil carbon (9, 12, 17–21) and nitrogen (9, 22–27). However, the same traits that adapt biocrust organisms to pulsed environmental conditions also make them potentially vulnerable to anticipated changes in climate (28–30). Given their significant influence on ecosystem processes, understanding how biocrust communities will respond to changing climate and disturbance regimes is essential for predicting ecological state changes in drylands—which cover roughly 40% of the Earth’s terrestrial surface and hold an estimated 25% of global organic soil carbon (31).Biocrusts are bound together by filamentous strands of cyanobacteria, which glue soil particles together to form the characteristic soil shields for which the communities are renowned (10). Although this structure results in resistance to wind shear stress, it does not provide much resistance to physical disturbance. Not surprisingly, both the physical and biotic structures of biocrust are highly sensitive to a range of disturbances, such as vehicle traffic and trampling by humans and livestock (32). Disturbance-induced changes in biocrust community structure and subsequent variation across successional states are well-characterized and are remarkably similar globally: Physical disturbance typically transforms later-successional communities of lichens and mosses to early-successional communities dominated by cyanobacteria (10, 32). This successional resetting significantly impacts ecosystem processes, including large changes in carbon and nitrogen cycling (11, 24, 25, 33). Alarmingly, some experimental work suggests biocrust communities may also be highly sensitive to changing climate. Specifically, increased temperatures have been reported to reduce lichen cover in semiarid Spain (12, 34), and altered precipitation patterns promoted rapid moss mortality (35) and greater variability in cyanobacterial species composition and abundance (36, 37) in a cool desert of the Colorado Plateau. These changes in biocrusts due to climate manipulations also impact ecosystem processes (12, 35, 38).Despite concern over potential climate change-induced shifts in biocrust community structure and the impacts on ecosystem processes, available reports of biocrust responses to climate manipulations are based on relatively short experimental time spans, often less than 3 y in duration (e.g., 12, 34–36, 39). In addition to the lack of long-term data on biocrust responses to climate change, it is not yet known how climate change impacts on biocrust communities will compare with large, continued threats from physical disturbances due to development, agriculture, and other human activities (32, 40, 41). Understanding the magnitude of threats to biocrusts from both climate change scenarios and novel disturbance regimes is thus a necessary step for predicting future ecological states and developing comprehensive management plans in drylands.We compared the effects of warming temperatures and altered precipitation patterns on biocrust community structure using data from 10 y (autumn 2005 to autumn 2014) of biocrust community surveys, completed in a full-factorial climate manipulation experiment (control, warming, watering, warming + watering) on the Colorado Plateau, Utah. We simultaneously examined the impact of 15 y annual physical disturbance on biocrust community structure within a replicated human-trampling experiment in a site with vegetation and biocrust communities similar to those in our climate manipulation study (Fig. 1). Finally, we compared the effects of climate manipulation treatments and physical disturbance from trampling on the relative cover of three biotic groups that typically dominate biocrusts of our study region: cyanobacteria, mosses, and lichens. Our goals were, first, to compare the responses of biocrust communities to increased temperature versus increased frequency of small precipitation events, both of which are forecast by climate models for the Colorado Plateau (28, 29, 42) and, second, to compare the effects of climate manipulations to the effects of physical disturbance on biocrust community structure, with a focus on understanding potential variation in responses across different fractions of the community.     

INAUGURAL ARTICLE by a Recently Elected Academy Member:Lagging adaptation to warming climate in Arabidopsis thaliana

If climate change outpaces the rate of adaptive evolution within a site, populations previously well adapted to local conditions may decline or disappear, and banked seeds from those populations will be unsuitable for restoring them. However, if such adaptational lag has occurred, immigrants from historically warmer climates will outperform natives and may provide genetic potential for evolutionary rescue. We tested for lagging adaptation to warming climate using banked seeds of the annual weed Arabidopsis thaliana in common garden experiments in four sites across the species’ native European range: Valencia, Spain; Norwich, United Kingdom; Halle, Germany; and Oulu, Finland. Genotypes originating from geographic regions near the planting site had high relative fitness in each site, direct evidence for broad-scale geographic adaptation in this model species. However, genotypes originating in sites historically warmer than the planting site had higher average relative fitness than local genotypes in every site, especially at the northern range limit in Finland. This result suggests that local adaptive optima have shifted rapidly with recent warming across the species’ native range. Climatic optima also differed among seasonal germination cohorts within the Norwich site, suggesting that populations occurring where summer germination is common may have greater evolutionary potential to persist under future warming. If adaptational lag has occurred over just a few decades in banked seeds of an annual species, it may be an important consideration for managing longer-lived species, as well as for attempts to conserve threatened populations through ex situ preservation.Rapid climate change has already caused species range shifts and local extinctions (1) and is predicted to have greater future impacts (2). As the suitable climate space for a species shifts poleward (3), populations previously well adapted to the historical climate in a particular region may experience strong selection to adapt to rapidly warming local temperatures (4–10). Rapid evolutionary response to climate change has already been observed (11, 12), but it remains unclear whether evolutionary response can keep pace with rapidly changing local adaptive optima (6, 8, 13–15). If local adaptation is slower than the rate of climate change, the average fitness of local populations may decline over time (7, 14, 16, 17), possibly resulting in local extinctions and range collapse at the warmer margin. Where such lag exists, we expect that local seeds banked for conservation may no longer be well adapted to their sites of origin (18). However, such adaptational lag may be mitigated by migration or gene flow from populations in historically warmer sites if those populations are better adapted to current conditions in a site than local populations (8, 13, 19, 20). Although adaptational lag has been predicted (4–6, 8, 14, 15, 19, 21, 22), the distinctive signature of mismatch between local population performance and current climate optima has not yet been explicitly demonstrated in nature.Despite evidence for local adaptation in many organisms (23), there have been few explicit tests for the role of specific climate factors in shaping local fitness optima (4, 9, 13). Such tests require growing many genotypes from populations spanning a range of climates in common gardens across a species’ range to decouple climate of origin from geographic variation in other selective factors (4, 6, 14). If adaptation to local climate has occurred, then genotypes from climates similar to each planting site are expected to have high fitness in that site relative to genotypes from dissimilar climates (6). However, if local adaptive optima have shifted with rapid warming trends over the last 50 y, we expect that banked genotypes from historically warmer climates will have higher fitness within a site than banked genotypes of local origin (6, 21, 22).We tested for lagging adaptation to climate using Arabidopsis thaliana, a naturally inbreeding annual species that inhabits a broad climate space across its native Eurasian range (24). A. thaliana exhibits strong circumstantial evidence of climate adaptation, including geographic clines in ecologically important life-history traits (25–28) and in candidate genes associated with these traits (29, 30), as well as genome-wide associations of single nucleotide polymorphisms with climatic factors (31–34). To test explicitly for local adaptation to climate we measured the lifetime fitness of more than 230 accessions from banked seeds originating from a broad range of climates in replicated field experiments in four sites across the species’ native climate range (Fig. 1). We observed that genotypes originating in historically warmer climates outperformed local genotypes, particularly at the northern range limit.Open in a separate windowFig. 1.Map of common garden sites and sites of origin of the 241 native A. thaliana accessions represented in our experiments.