Evaluating sustainable development policies in rural coastal economies

Sustainable development (SD) policies targeting marine economic sectors, designed to alleviate poverty and conserve marine ecosystems, have proliferated in recent years. Many developing countries are providing poor fishing households with new fishing boats (fishing capital) that can be used further offshore as a means to improve incomes and relieve fishing pressure on nearshore fish stocks. These kinds of policies are a marine variant of traditional SD policies focused on agriculture. Here, we evaluate ex ante economic and environmental impacts of provisions of fishing and agricultural capital, with and without enforcement of fishing regulations that prohibit the use of larger vessels in nearshore habitats. Combining methods from development economics, natural resource economics, and marine ecology, we use a unique dataset and modeling framework to account for linkages between households, business sectors, markets, and local fish stocks. We show that the policies investing capital in local marine fisheries or agricultural sectors achieve income gains for targeted households, but knock-on effects lead to increased harvest of nearshore fish, making them unlikely to achieve conservation objectives in rural coastal economies. However, pairing an agriculture stimulus with increasing enforcement of existing fisheries’ regulations may lead to a win–win situation. While marine-based policies could be an important tool to achieve two of the United Nations Sustainable Development Goals (alleviate poverty and protect vulnerable marine resources), their success is by no means assured and requires consideration of land and marine socioeconomic linkages inherent in rural economies.

Coastal and island nations are adopting “blue growth” sustainable development (SD) policies to alleviate poverty and conserve vulnerable ocean resources. Generally speaking, SD policies manage resources and direct investments in order to meet current and future human needs and aspirations, without endangering the natural systems (1). The feasibility and potential of SD has been the focus of decades of academic research; many regard the consideration of economic, social, environmental, and institutional needs and linkages as fundamental to successful policy design and implementation (2–6). Given their novelty, what constitutes a blue growth policy is not universal (7), but like traditional SD policies that focus on land-based sectors such as agriculture, manufacturing, and energy sectors (8, 9), blue growth policies seek to achieve social, economic, and environmental goals simultaneously (10). Blue growth policies attempt to achieve these goals by supporting marine-based industries such as offshore fishing, aquaculture, shipping, and tourism (11, 12). The marine focus has reinvigorated SD efforts of international organizations (including the Global Environmental Facility, United Nations Food and Agriculture Organization, the European Union, and The World Bank) that have collectively invested hundreds of millions of dollars into the development and monitoring of blue growth programs (12–16).While small-scale artisanal fishers consider a variety of factors when making fishing decisions (17), evidence suggests allocation of time is, in part, based on relative returns to labor (18–21). Thus, some blue growth policies attempt to alter returns to fishing relative to alternative income-generating activities as a way to achieve both poverty alleviation and conservation objectives. For example, if poor fishing households are incentivized to participate in offshore fishing, it may lead to increased household incomes and reduced fishing pressure on overexploited nearshore fish stocks (22, 23). Policies enforcing and increasing the regulation of fishing activities are also considered important to achieving blue growth objectives (10, 24).Many SD policies are designed to reduce upfront costs of switching to more sustainable livelihoods. Historically, large-scale fisheries receive the majority of subsidy benefits (25), arguably to the detriment of small-scale fisheries who are often outcompeted by industrialized operations (26). Recently, however, developing countries including Kenya, the Philippines, India, Tanzania, Vietnam, and Indonesia have been investing in programs that bolster the fishing capacity of small-scale and artisanal fishermen (27–33). These programs are designed to help small-scale fishers access larger or better vessels and gear, allowing them to reach more plentiful fishing grounds, compete with commercial vessels, and relieve pressure on vulnerable nearshore fisheries.Despite the recent surge in popularity, we lack evidence that these marine-based SD policies will achieve both poverty reduction and conservation objectives when implemented in rural economies. The complexity of coupled natural–human systems makes it difficult to measure the ex post performance of SD policies, especially in marine environments (34, 35). Additionally, local market failures due to high transportation costs and poorly developed marketing infrastructure (36) can lead to locally defined prices that fluctuate with changes in local supply and demand; local prices may distort household responses to policies, leading to unintended environmental consequences (37–40). Because local market failures are more common in rural economies in developing countries, methods and lessons learned from studies of industrialized fisheries in developed countries may not be relevant. Rather, management of fisheries in rural coastal economies may be more successful if market imperfections, alternative livelihood options, and ecological feedback are considered (20, 41–47).Recent studies explore the causal impacts of land-based SD policy instruments in developing countries (48–56). A key finding of these studies is that community heterogeneity is an important factor in policy performance. However, findings from forestry research do not necessarily carry over to marine settings because fish resources are mobile and regenerate relatively quickly, and, typically, access rights to fisheries are not well defined. This study begins to address the need for research examining responses to SD policy in rural coastal economies.We use a coupled natural–human modeling framework to estimate the ex ante impacts of common SD policies. Our ex ante mechanistic approach that includes a general equilibrium local economy model captures important dynamic feedback between the economy and health of the fish stocks. Indeed, other researchers have studied the correlations between markets and ecosystems in coastal communities in developing countries (44, 57–59). However, the theoretical structure of our analysis approach allows us to examine the causal mechanisms between policy and its outcomes. Our model captures the feedback between economic sectors and households within the economy (Fig. 1, details in SI Appendix). This broad scope is necessary to estimate the extent to which policies targeting poor households in a community also impact nontargeted households (knock-on effects). For example, a policy supporting a subset of fishing households could be detrimental to other households that harvest from the same fish stocks and compete in the same input and output markets.Open in a separate windowFig. 1.A conceptual framework for the bioeconomic local general equilibrium model. Households are represented by four representative groups and may produce goods and services (e.g., agricultural, offshore and nearshore fish, retail, and restaurants) available in local, and possibly global, markets. The simulated policies provide different types of capital to poor households and may also restrict use of fishing capital.Here, we estimate the impacts of two common marine fisheries policies (provision of offshore fishing vessels and increased enforcement of fishing regulations) and an alternative agricultural policy (provision of agricultural capital) in a rural coastal economy. To estimate the impacts of these SD policies in coastal economies, we use a modeling approach that has been developed using theory from development economics, natural resource economics, and marine ecology (37, 60). Introducing new features to the framework, we develop a model of a rural economy capable of disentangling fisher participation in two distinct fishing activities and household consumption of two fish goods. We use microeconomic data collected from household and business surveys to parameterize and calibrate our model, allowing us to realistically estimate policy impacts. An inherent strength to our methodology is the ability to adjust the structure of the model to represent alternative economies. We demonstrate how the model can be used to predict policy outcomes for a typology of rural coastal economies.Although combining policies that simultaneously target marine and agricultural sectors is currently not part of the dialogue on the adoption of blue SD policies around the world (e.g., see The World Bank’s strategy document for its Blue Economy Program and PROBLUE (13)), we find that pairing policy instruments that target both sectors—increased enforcement of vessel regulations and capital investments in the agricultural sector—is better able to achieve both conservation and poverty reduction goals.Why is an agricultural policy combined with enforcement capabilities of marine fishing regulations able to achieve a win–win while marine-focused SD policies are not? Our coupled natural–human modeling framework highlights the mechanisms leading to this counterintuitive outcome. That is, investing in the agricultural sector increases the returns to agricultural labor, which in turn creates upward pressure on wages and encourages a reduction in labor allocated to nearshore fishing. At the same time, the increased wealth in the local economy due to greater agricultural productivity drives up demand for nearshore fish. Although higher prices of fish draw some labor back into the fishery, increased enforcement of vessel regulations prevents fishers from illegally using larger boats in the nearshore habitat as a means to increase harvests. Without coupling increased enforcement and agricultural subsidy, the higher demand for fish would lead to increased harvests in the nearshore environment and lower fish stocks over time.     

From the Cover: Harvesting forage fish can prevent fishing-induced population collapses of large piscivorous fish

Fisheries have reduced the abundances of large piscivores—such as gadids (cod, pollock, etc.) and tunas—in ecosystems around the world. Fisheries also target smaller species—such as herring, capelin, and sprat—that are important parts of the piscivores’ diets. It has been suggested that harvesting of these so-called forage fish will harm piscivores. Multispecies models used for fisheries assessments typically ignore important facets of fish community dynamics, such as individual-level bioenergetics and/or size structure. We test the effects of fishing for both forage fish and piscivores using a dynamic, multitrophic, size-structured, bioenergetics model of the Baltic Sea. In addition, we analyze historical patterns in piscivore-biomass declines and fishing mortalities of piscivores and forage fish using global fish-stock assessment data. Our community-dynamics model shows that piscivores benefit from harvesting of their forage fish when piscivore fishing mortality is high. With substantial harvesting of forage fish, the piscivores can withstand higher fishing mortality. On the other hand, when piscivore fishing mortality is low, piscivore biomass decreases with more fishing of the forage fish. In accordance with these predictions, our statistical analysis of global fisheries data shows a positive interaction between the fishing mortalities of forage-fish stocks and piscivore stocks on the strength of piscivore-biomass declines. While overfishing of forage fish must be prevented, our study shows that reducing fishing pressures on forage fish may have unwanted negative side effects on piscivores. In some cases, decreasing forage-fish exploitation could cause declines, or even collapses, of piscivore stocks.

Fisheries target both large piscivorous fish—such as gadids (cod, pollock, etc.) and tunas—and small planktivorous fish or forage fish—such as herring, capelin, and sprat (1). Large piscivores are generally more valued for human consumption. Yet, forage fish constitute a substantial 20 to 30% of global fisheries landings (2). Often, both forage fish and large piscivores are fished for in the same ecosystems (3, 4). Forage fish serve as a food source for large piscivores, and it is commonly understood that harvesting of forage fish may indirectly harm the large piscivores that depend on them (3, 4).The importance of an ecosystem-based, multispecies approach to fisheries management is underscored by potential indirect negative effects of forage-fish fisheries on piscivores (5, 6). Unraveling the effects of multispecies fisheries is a serious challenge due to feedbacks between fisheries, fish populations, and the fishes’ food sources (e.g., ref. 7). Understanding these effects is further complicated by nonlinearities in population-level processes (8). The effects of fishing on multiple species at different trophic levels of marine ecosystems are usually assessed by using multispecies fisheries models (4, 9). However, it has recently been argued that such models do not contain all necessary processes to predict fish-community dynamics (10, 11). Components that are considered essential in models of fish communities are: 1) fish-population size structure, 2) consistent accounting of the bioenergetic flows through fish populations and communities, and 3) size-selective predation and harvesting (10, 11).In this study, we investigate the effects of fishing for forage fish on their predators, the piscivorous fish. We do this using a published model of the central Baltic Sea community dynamics (12) that was specifically designed to investigate effects of fisheries on fish communities (10, 12). The model incorporates size-structured fish populations, size-dependent feeding interactions, and individual-level energy budgets. In addition, consumption by fish has a direct effect on their food sources, and the flows of energy throughout the system are thus accounted for consistently. Using this model, we explore the effects of fishing for both forage fish and piscivores. We first focus on the Baltic Sea because its food web is relatively simple and the exploited fish species include both piscivores (cod) and forage fish (sprat and herring) (13). Using the global Ransom A. Myers (RAM) Legacy Stock Assessment Database (14), we then statistically evaluate historical patterns in piscivore biomasses and fishing pressures on forage fish and piscivores. Our dynamic and statistical model analyses agree in demonstrating that harvesting forage fish does not always affect piscivore populations negatively. Instead, such fishing can protect large-piscivore populations from fishing-induced collapses. These results challenge the generally accepted idea that large piscivores always benefit from less fishing of their forage fish (6, 15).     

Multigenerational exposure to warming and fishing causes recruitment collapse,but size diversity and periodic cooling can aid recovery

Global warming and fisheries harvest are significantly impacting wild fish stocks, yet their interactive influence on population resilience to stress remains unclear. We explored these interactive effects on early-life development and survival by experimentally manipulating the thermal and harvest regimes in 18 zebrafish (Danio rerio) populations over six consecutive generations. Warming advanced development rates across generations, but after three generations, it caused a sudden and large (30–50%) decline in recruitment. This warming impact was most severe in populations where size-selective harvesting reduced the average size of spawners. We then explored whether our observed recruitment decline could be explained by changes in egg size, early egg and larval survival, population sex ratio, and developmental costs. We found that it was most likely driven by temperature-induced shifts in embryonic development rate and fishing-induced male-biased sex ratios. Importantly, once harvest and warming were relaxed, recruitment rates rapidly recovered. Our study suggests that the effects of warming and fishing could have strong impacts on wild stock recruitment, but this may take several generations to manifest. However, resilience of wild populations may be higher if fishing preserves sufficient body size diversity, and windows of suitable temperature periodically occur.

Global warming and harvesting are causing rapid and drastic changes to many of the Earth’s ecosystems (1, 2). These impacts are particularly prevalent in the aquatic realm where harvesting of wild fish populations can greatly exceed rates of natural mortality and where, due to the physical nature of the aquatic medium, individuals cannot readily escape warming through behavioral modulations or habitat choice (3, 4). The additive effects of warming and fishing on population size structure, reproductive output, and recovery potential post disturbance are well known (3, 5–7). Of particular concern, however, is the interaction of these forces and how they together might impact global fisheries’ sustainability. Empirical studies suggest that harvesting can amplify a fish stock’s sensitivity to environmental changes (8–11), but the mechanisms underpinning these effects, and their potential reversibility, often remain unclear.Global warming can affect fish populations by causing changes in egg size, early development, and recruitment success (12). For example, development cost theory suggests that species’ development and metabolic processes during the egg to feeding stages respond to changing temperatures at different rates (13). These differential rates determine an optimum temperature for a species’ development, which occurs when metabolism is relatively low, development is sufficiently fast, and thus the total cost of development is minimized (13). As temperature cools or warms, respectively longer development times or higher metabolic rates lead to faster use of energy reserves, poorer larval condition upon hatching, and potentially negative effects on recruitment (13, 14). Likewise, later in life, higher temperatures may lead to increased metabolic rates and energetic expenditure during maturation, which in turn can alter energetic allocation to progeny (15) and thus egg size and larval condition (16).Another way that warming might affect fish stocks is through changes in the size structure of populations (e.g., refs. 17 and 18). This effect will be particularly strong where population size structure is also impacted by harvesting (8). Moreover, warming- and fishing-induced changes in size structure can be driven not only by the direct removal or elevated mortality of large individuals, but also through plastic (e.g., temperature-size rule: refs. 19 and 20), intergenerational (maternal effects; e.g., ref. 21), and evolutionary responses (e.g., fisheries-induced evolution: ref. 22). Modified size distributions could in turn impact on stock resilience by reducing size-related reproductive output (23), population “storage effects” conferred by large individuals (24), or shifting size-related ecological interactions (25, 26). Changes in size distributions can thus increase the environmental sensitivity of populations and lead to biomass fluctuations (8, 11).Despite numerous studies focusing on how fishery stocks respond to warming or harvesting, a major question remains unclear: How do these two forces interact to impact on stocks over long-term, intergenerational timescales? Through experimentation, we know that fishes respond differently to acute or short-term warming compared to multigenerational exposure (27–29) and that fishing selection can drive long-term trait changes (22, 30). Here, we address this knowledge gap by exploring the long-term interactions of harvest and warming on the reproductive output, early life history, and recruitment of fish populations.Using a multigenerational selection experiment on the tropical freshwater zebrafish (Danio rerio), we exposed 18 independent populations to factorial combinations of two temperature treatments (control, 26 °C, and “hot,” 30 °C) and three size-based fisheries selection regimes and then measured a range of early life characteristics. Populations were acclimated for two generations to minimize any maternal effects (31), after which we imposed five generations of warming and fishing selection followed by two generations of common-garden conditions with control temperatures and random size harvesting. Our hot treatment was at the upper end of temperatures experienced by zebrafish in the wild (32), while our fisheries selection regimes imposed high but realistic levels of mortality (80% harvest imposed once the majority of individuals are mature, e.g., ref. 33) and realistic trawl and gillnet fisheries selectivity curves (sigmoid, Gaussian, and random control harvesting) (SI Appendix, Fig. S1). Our selectivity regimes were also more reflective of real-world conditions than some previous multigenerational experiments, where knife-edge selectivity was used (22, 30, 34, 35). Our temperature treatments span a realistic, short-term warming scenario (36). With this design, we tested whether there is a significant interaction of warming and size-selective fishing on reproductive output (egg size and egg size variation), early life history (survival and development rate), and survival to subadult stage, which approximates “recruitment” of wild stocks. Together, these results help identify the mechanisms underpinning fish population responses to the combined impacts of fishing and warming and facilitate prediction of population states in a warmer future with increased demand on wild fisheries (26).     

The battle between harvest and natural selection creates small and shy fish

Harvest of fish and wildlife, both commercial and recreational, is a selective force that can induce evolutionary changes to life history and behavior. Naturally selective forces may create countering selection pressures. Assessing natural fitness represents a considerable challenge in broadcast spawners. Thus, our understanding about the relative strength of natural and fisheries selection is slim. In the field, we compared the strength and shape of harvest selection to natural selection on body size over four years and behavior over one year in a natural population of a freshwater top predator, the northern pike (Esox lucius). Natural selection was approximated by relative reproductive success via parent–offspring genetic assignments over four years. Harvest selection was measured by comparing individuals susceptible to recreational angling with individuals never captured by this gear type. Individual behavior was measured by high-resolution acoustic telemetry. Harvest and natural size selection operated with equal strength but opposing directions, and harvest size selection was consistently negative in all study years. Harvest selection also had a substantial behavioral component independent of body length, while natural behavioral selection was not documented, suggesting the potential for directional harvest selection favoring inactive, timid fish. Simulations of the outcomes of different fishing regulations showed that traditional minimum size-based harvest limits are unlikely to counteract harvest selection without being completely restrictive. Our study suggests harvest selection may be inevitable and recreational fisheries may thus favor small, inactive, shy, and difficult-to-capture fish. Increasing fractions of shy fish in angling-exploited stocks would have consequences for stock assessment and all fisheries operating with hook and line.

Anticipating and preparing for future evolutionary changes within harvested populations whether by fishing or hunting is critical for sustainable natural resource management and successful conservation of ecosystems (1–6). Harvest-induced evolution is a concern for both commercial and recreational fisheries, and harvest from recreational fisheries now frequently exceeds harvest from commercial fisheries in some marine fish and most inland fish populations (7). Harvesting, firstly, elevates adult mortality which favors the evolution of life history adaptations that maximize current as opposed to future reproduction [i.e., a fast life history characterized by early reproduction at a small size and elevated reproductive effort (1, 2)]. Additionally, harvesting is trait selective. Most individuals in harvested populations are not captured or hunted randomly (8). Instead, a suite of traits elevates the probability of harvest (8–13). In fisheries, vulnerability to harvest and fish body size are positively related across most fishing gears, and the relationship is exacerbated by the widespread use of minimum landing sizes (14, 15). Consequently, the average body size of individuals within fish stocks is commonly observed to decrease (15, 16).Decreasing average body size in fish stocks first results from demographic truncation by direct removal of large individuals within a generation but may also result from evolutionary adaptation to a new fitness landscape (17). Positively size-selective harvesting alters the fitness landscape by favoring early reproduction at smaller sizes, in turn slowing down postmaturation growth due to altered allocation of energy from soma to gonads (2, 18). Additionally, reduced postmaturation growth may arise from evolutionary adaptations in energy acquisition–related behaviors [e.g., evolution of risk-sensitive foraging in response to the selective removal of bold, active, or aggressive behavioral phenotypes (19, 20)]. There is considerable debate whether any observed phenotypic changes, derived from monitoring data from wild fisheries, in life history traits such as maturation timing or growth rate are indeed evolutionary (i.e., genetic) or an effect of phenotypic plasticity (21), and a recent review concluded that no conclusive example for fisheries-induced evolution exists at the scale of wild fisheries (21).Most research on fisheries-induced selection and evolution has been focused on life history traits (2). However, fisheries can also induce adaptive changes in behavior through at least two mechanisms. First, by creating selection pressures that favor fast life histories, fisheries may indirectly alter correlated behavioral traits like aggressive and bold behaviors (22–24). Second, passive gear types such as gill nets, traps, or hooks heavily rely on a behavioral response by individual fish for successful capture (25). Fish that are able to forage more, at the expense of taking more risks, are able to grow faster and may produce more offspring (26–28), but they may also be more vulnerable to capture (10, 27) and mortality by predation (29). Accordingly, models comparing life history outcomes emerging from either purely behavioral to purely size-dependent vulnerability to capture demonstrate that behavioral selection can create the same pressures and ultimately evolutionary outcomes as size-selective capture and, depending on context, either favor bold or shy fish (30, 31). As personality traits are known to have a heritable component (32, 33) and vary consistently among individuals (34, 35), the selective capture of active, aggressive, and bold fish may ultimately promote the emergence of timid populations (10, 19, 27). Independent of life history adaptations, these changes may also disrupt the “pace-of-life” syndrome and the correlation of behavior and life history (24, 36, 37). A widespread increase in timidity implies that fish will become harder to catch (10). If this is the case, challenges in stock assessments will arise as they are built on assumptions of consistent fish availability to sampling gear over time to serve as indices of abundance (19, 38, 39).Our understanding of selective harvest’s impact on phenotypic change has not yet been able to fully explain empirical observations from fisheries in the wild (40, 41). Indeed, the rate and impacts of harvest-induced evolution continues to attract controversy despite more than 20 y of research (2, 21, 41). Models of harvest-induced life history evolution consistently underestimate rates of phenotypic change observed in empirical studies from the wild, while experimental studies in the laboratory tend to overestimate empirical rates of evolution (40–42). The discrepancy between models or laboratory studies and empirical data in the wild may partly result from plastic, rather than evolutionary, impacts on phenotypes collected in the wild (43), from inappropriate assumptions of fitness trade-offs in models (30, 31), from exaggerated fishing mortality induced in selection line experiments (44), or from inadvertent selection on other traits correlated with growth, such as behavioral traits, rather than direct selection on size (30, 31). To understand the potential for harvest-induced evolution, a key first step is to understand the selection pressures induced by exploitation in the wild (42, 45). This is because following the breeder’s equation from quantitative genetics, the selection response in any trait is a product of the selection differentials acting on a trait and the trait’s heritability (46). We focus here on estimating selection acting on adaptive traits in a wild fish population and compare the selection to natural selective forces on the same traits.In particular, the counteracting forces of natural selection must be considered to understand the total selective forces acting on a phenotype (47, 48). However, natural selection has rarely been empirically measured in the context of harvest selection in wild fisheries (45, 47–49). Meta-analyses on selection in the wild indicate that fishing is one of the few anthropogenic selective forces consistently stronger than natural selection (49). Yet, natural selection compared to size-selective fisheries has, so far, only been quantified by fitness proxies such as survival (45), growth rate, or female body size (47, 48), assumed to be positively correlated with lifetime reproductive success (RS) (50). As the RS of fish is challenging to measure in the wild, it is unclear how body size and fitness actually scale (50), and consequently it is largely unclear what natural selection on body size or other traits looks like in exploited stocks. Further, the fitness landscape of behavioral traits has rarely been assessed in the wild, although behavior commonly relates to growth (51), survival (52, 53), and RS (26, 27).Our aim was to quantify the strength and direction of harvest and natural selection in the wild using an experimentally exploited top predatory fish and to improve our understanding of whether a portion of harvest size selection is actually the result of undetected behavioral selection (54, 55). To that end, we investigated the strength and direction of harvest selection on body size and activity in northern pike, Esox lucius, measuring fitness in the context of natural selection as relative reproductive success (RRS) over four years and classification of movement behavior over one year using high-resolution acoustic telemetry (56) covering an entire natural ecosystem. We used hook and line fishing as an example of a widespread fishing gear used by both recreational and commercial fisheries. We predicted that harvest and natural size selection act in opposition in which larger fish would have higher RRS (50) but would also be more likely to be captured by angling (57, 58). Furthermore, we expected that fishing selection on size would be much stronger than natural selection (49). However, we also predicted additional harvest selection on behavior (55) because recreational fishing gear is known to be related to behavioral phenotypes (10, 55, 59–61). Finally, through simulations, we investigated how regulations could alter the relationship between harvest and natural selection and potentially counteract fishing selection considering minimum length limits and harvest slots based on established models (42).     

Stage-specific overcompensation,the hydra effect,and the failure to eradicate an invasive predator

As biological invasions continue to increase globally, eradication programs have been undertaken at significant cost, often without consideration of relevant ecological theory. Theoretical fisheries models have shown that harvest can actually increase the equilibrium size of a population, and uncontrolled studies and anecdotal reports have documented population increases in response to invasive species removal (akin to fisheries harvest). Both findings may be driven by high levels of juvenile survival associated with low adult abundance, often referred to as overcompensation. Here we show that in a coastal marine ecosystem, an eradication program resulted in stage-specific overcompensation and a 30-fold, single-year increase in the population of an introduced predator. Data collected concurrently from four adjacent regional bays without eradication efforts showed no similar population increase, indicating a local and not a regional increase. Specifically, the eradication program had inadvertently reduced the control of recruitment by adults via cannibalism, thereby facilitating the population explosion. Mesocosm experiments confirmed that adult cannibalism of recruits was size-dependent and could control recruitment. Genomic data show substantial isolation of this population and implicate internal population dynamics for the increase, rather than recruitment from other locations. More broadly, this controlled experimental demonstration of stage-specific overcompensation in an aquatic system provides an important cautionary message for eradication efforts of species with limited connectivity and similar life histories.

Theoretical population models can produce counterintuitive predictions regarding the consequences of harvest or removal of predatory species. These models show that for simple predator-prey systems, there can be positive population responses to predator mortality resulting from harvest for fisheries or population management, which can create an increased equilibrium level of that predator species (1–5). Among these mortality processes is the “hydra effect,” named after the mythical multi-headed serpent that grew two new heads for each one that was removed (6, 7). This counterintuitive outcome can be driven by a density-dependent process known as overcompensation. The hydra effect typically refers to higher equilibrium or time-averaged densities in response to increased mortality, typically involving consumer populations undergoing population cycles. Population increases in response to mortality can be the result of stage-specific overcompensation, which involves an increase in a specific life history stage or a size class following increased mortality. The first analysis of overcompensatory responses to mortality did not depend on stage specificity and was applied initially to fisheries harvests (1). Subsequent models have included stage specificity and have been applied to a broad range of systems in which species have been harvested for consumption or removed for population control of non-native species (4, 5, 8–15).Theory suggests that overcompensation in response to harvest or removal can occur for a variety of reasons, including 1) reduced competition for resources and increased adult reproduction rates, 2) faster rates of juvenile maturation or greater success in reaching the adult stage, and 3) increased juvenile or adult survival rates (1–7). An increase in reproductive output in response to reduced adult density can be the result of a reduction in resource competition (SI Appendix, Fig. S1).While there is substantial evidence that conditions that could produce density-dependent overcompensation occur frequently, evidence for overcompensation in natural populations is rare. For only a few populations do we have the long-term demographic data collected over a sufficiently long duration and for population densities over a wide enough range to detect this effect. Unfortunately, recent reviews of population increases in response to increased mortality do not include field studies with explicit controls for removals (13–17).There are examples of density-dependent overcompensation from field populations (4, 13–15), as well as a larger number of studies from the laboratory and greenhouse typically involving plant and insect populations (18–22). Among the field examples is a population control program for smallmouth bass in a lake in upstate New York, which paradoxically resulted in greater bass abundance, primarily of juveniles, after 7 y of removal efforts (23, 24). Another field study in the United Kingdom showed that perch populations responded similarly when an unidentified pathogen decimated adults (25). Other programs that attempted to remove invasive fishes, including pikeperch in England (26), brook trout in Idaho (27), and Tilapia in Australia (28), showed similar results. However, although many of these examples involved well-executed studies with substantial field data, none had explicit controls for removal, such as comparable populations without harvest (or disease). Thus, despite the support of current theory in these studies, the contribution of external factors to observed population responses to harvest remains uncertain. To date, we are unaware of any experimental studies with comparable controls in a field population that demonstrates overcompensation in a single species (13–15).     

“You” speaks to me: Effects of generic-you in creating resonance between people and ideas

Creating resonance between people and ideas is a central goal of communication. Historically, attempts to understand the factors that promote resonance have focused on altering the content of a message. Here we identify an additional route to evoking resonance that is embedded in the structure of language: the generic use of the word “you” (e.g., “You can’t understand someone until you’ve walked a mile in their shoes”). Using crowd-sourced data from the Amazon Kindle application, we demonstrate that passages that people highlighted—collectively, over a quarter of a million times—were substantially more likely to contain generic-you compared to yoked passages that they did not highlight. We also demonstrate in four experiments (n = 1,900) that ideas expressed with generic-you increased resonance. These findings illustrate how a subtle shift in language establishes a powerful sense of connection between people and ideas.

Consider the feeling evoked by watching a gripping scene in a film, hearing a moving song, or coming across a quotation that seems to be written just for you. Experiencing resonance, a sense of connection, is a pervasive human experience. Prior research examining the processes that promote this experience suggests that altering a message to evoke emotion (1–7), highlighting its applicability to a person’s life (2, 6, 8–10), or appealing to a person’s beliefs (4, 8, 11) can all contribute to an idea’s resonance. Here we examine an additional route to cultivating this experience, which is grounded in a message’s form rather than its content: the use of a linguistic device that frames an idea as applying broadly.The ability to frame an idea as general rather than specific is a universal feature of language (12–15). One frequently used device is the generic usage of the pronoun “you” (15–17). Although “you” is often used to refer to a specific person or persons (e.g., “How did you get to work today?”), in many languages, it can also be used to refer to people in general (e.g., “You avoid rush hour if you can.”). This general use of “you” is comparable to the more formal “one,” but is used much more frequently (18).Research indicates that people often use “you” in this way to generalize from their own experiences. For example, a person reflecting on getting fired from their job might say, “It makes you feel betrayed” (18). Here, we propose that using “you” to refer to people in general has additional social implications, affecting whether an idea evokes resonance.Two features of the general usage of “you” (hereafter, “generic-you”) motivate this hypothesis. First, generic-you conveys that ideas are generalizable. Rather than expressing information that applies to a particular situation (e.g., “Leo broke your heart”), generic-you expresses information that is timeless and applies across contexts (e.g., “Eventually, you recover from heartbreak”; 18–23). Second, generic-you is expressed with the same word ("you") that is used in nongeneric contexts to refer to the addressee. Thus, even when “you” is used generically, the association to its specific meaning may further pull in the addressee, heightening resonance. Together, these features suggest that generic-you should promote the resonance of an idea. We tested this hypothesis across five preregistered studies (24–28), using a combination of crowd-sourced data and online experimental paradigms. Data, code, and materials are publicly available via the Open Science Framework (https://osf.io/6J2ZC/) (29). Study 1 used publicly available data from the Amazon Kindle application. Studies 2–5 were approved by the University of Michigan Health Sciences and Behavioral Sciences institutional review board (IRB) under HUM00172473 and deemed exempt from ongoing IRB review. All participants who participated in studies 2–5 provided informed consent via a checkbox presented through the online survey platform, Qualtrics.     

From the Cover: People have shaped most of terrestrial nature for at least 12,000 years

Archaeological and paleoecological evidence shows that by 10,000 BCE, all human societies employed varying degrees of ecologically transformative land use practices, including burning, hunting, species propagation, domestication, cultivation, and others that have left long-term legacies across the terrestrial biosphere. Yet, a lingering paradigm among natural scientists, conservationists, and policymakers is that human transformation of terrestrial nature is mostly recent and inherently destructive. Here, we use the most up-to-date, spatially explicit global reconstruction of historical human populations and land use to show that this paradigm is likely wrong. Even 12,000 y ago, nearly three quarters of Earth’s land was inhabited and therefore shaped by human societies, including more than 95% of temperate and 90% of tropical woodlands. Lands now characterized as “natural,” “intact,” and “wild” generally exhibit long histories of use, as do protected areas and Indigenous lands, and current global patterns of vertebrate species richness and key biodiversity areas are more strongly associated with past patterns of land use than with present ones in regional landscapes now characterized as natural. The current biodiversity crisis can seldom be explained by the loss of uninhabited wildlands, resulting instead from the appropriation, colonization, and intensifying use of the biodiverse cultural landscapes long shaped and sustained by prior societies. Recognizing this deep cultural connection with biodiversity will therefore be essential to resolve the crisis.

Multiple studies confirm that ecosystems across most of the terrestrial biosphere, from 75 to 95% of its area, have now been reshaped to some degree by human societies (1 –3). With a few exceptions (e.g., refs. 4 –8), this global anthropogenic transformation of terrestrial nature has been described by natural scientists as mostly recent: the product of the industrial era (9 –13). This is partly because previous global reconstructions of early populations and land use systematically ignored these earlier transformations (1, 5, 14) and partly due to the conservation community’s focus on recent industrial changes (2, 3, 9, 15). There has also been a history of natural scientists and conservation practitioners interpreting terrestrial ecosystems as uninfluenced by long-sustained interactions with human societies, ignoring prior histories of land use, especially by Indigenous societies (16 –18). While this paradigm has increasingly been questioned with respect to long-term global changes in climate (19), fire regimes (20), and biodiversity (7, 8, 21), it continues to have real-world consequences, including failed policies of fire suppression, wildlife management, and ecological restoration, as well as the repression and removal of Indigenous peoples from traditional lands and waters and the erasure of their extensive knowledge of effective ecosystem management practices, thereby undermining their sovereignty over these ecosystems (17, 22 –24).Here, we examine contemporary global patterns of biodiversity and conservation in relation to the spatial history of human populations and land use over the past 12,000 y. Specifically, we use spatially explicit global datasets to visualize histories of human use in areas identified as biodiversity-rich and high-priority for conservation, including those specifically labeled as more “natural” or “wild,” and test the degree to which global patterns of land use and population at different times are associated statistically with contemporary global patterns of high biodiversity value and vertebrate species richness and threat within areas prioritized for conservation. Through this examination, we assess the early and sustained global significance of cultural landscapes as a basis for better understanding and conserving terrestrial nature.Anthropological, archaeological, and paleoecological evidence indicate that, at least since the start of the current interglacial interval 11,600 y ago, all human societies were interacting with biota and environments in ways that shaped evolutionary dynamics, ecosystems, and landscapes (25 –28). We use the term transformations to describe system-level changes in the social-ecological systems shaped by these interactions, including their initial formation by human inhabitation and the adoption of cultural practices leading to changes in ecosystem state, sensu 5, 27. While the focus is often on negative outcomes relating to these interactions, including extinctions of island endemics (29) and megafauna (21, 30, 31) with cascading ecological consequences (32), there is increasing evidence that human cultural practices can also produce sustained ecological benefits through practices that expand habitat for other species (33, 34), enhance plant diversity (17, 34 –37), increase hunting sustainability (38), provide important ecological functions like seed dispersal (39), and improve soil nutrient availability (40, 41).Hunter-gatherers, early farmers, and pastoralists often shared regional landscapes, which they shaped through a wide array of low-intensity subsistence practices, including hunting, transhumance, residential mobility, long- and short-fallow cultivation, polycropping, and tree-fallowing that created diverse, dynamic, and productive mosaics of lands and novel ecological communities in varying states of ecological succession and cultural modification (34, 37, 42). In many regions, these diverse cultural landscape mosaics were sustained for millennia (17, 24, 25, 27, 33, 34, 37, 43 –45), contrasting sharply with the more homogenous and continuously used landscapes of larger-scale agricultural societies employing annual tillage, irrigation, continuous grazing, and the extractive and colonial use of land, labor, and other resources to support elites (1, 5, 44). The emergence and spread of increasingly globalized and industrial societies only accelerated this trend toward today''s ever more intensively used and homogeneous cultural landscapes shaped by global supply chains, mechanization, chemical nutrients and pest control, leading to ecologically simplified habitats and biotic homogenization through species transported around the world intentionally and unintentionally (1, 44, 46).     

A general model of hippocampal and dorsal striatal learning and decision making

Humans and other animals use multiple strategies for making decisions. Reinforcement-learning theory distinguishes between stimulus–response (model-free; MF) learning and deliberative (model-based; MB) planning. The spatial-navigation literature presents a parallel dichotomy between navigation strategies. In “response learning,” associated with the dorsolateral striatum (DLS), decisions are anchored to an egocentric reference frame. In “place learning,” associated with the hippocampus, decisions are anchored to an allocentric reference frame. Emerging evidence suggests that the contribution of hippocampus to place learning may also underlie its contribution to MB learning by representing relational structure in a cognitive map. Here, we introduce a computational model in which hippocampus subserves place and MB learning by learning a “successor representation” of relational structure between states; DLS implements model-free response learning by learning associations between actions and egocentric representations of landmarks; and action values from either system are weighted by the reliability of its predictions. We show that this model reproduces a range of seemingly disparate behavioral findings in spatial and nonspatial decision tasks and explains the effects of lesions to DLS and hippocampus on these tasks. Furthermore, modeling place cells as driven by boundaries explains the observation that, unlike navigation guided by landmarks, navigation guided by boundaries is robust to “blocking” by prior state–reward associations due to learned associations between place cells. Our model, originally shaped by detailed constraints in the spatial literature, successfully characterizes the hippocampal–striatal system as a general system for decision making via adaptive combination of stimulus–response learning and the use of a cognitive map.

Behavioral and neuroscientific studies suggest that animals can apply multiple strategies to the problem of maximizing future reward, referred to as the reinforcement-learning (RL) problem (1, 2). One strategy is to build a model of the environment that can be used to simulate the future to plan optimal actions (3) and the past for episodic memory (4–6). An alternative, model-free (MF) approach uses trial and error to estimate a direct mapping from the animal’s state to its expected future reward, which the agent caches and looks up at decision time (7, 8), potentially supporting procedural memory (9). This computation is thought to be carried out in the brain through prediction errors signaled by phasic dopamine responses (10). These strategies are associated with different tradeoffs (2). The model-based (MB) approach is powerful and flexible, but computationally expensive and, therefore, slow at decision time. MF methods, in contrast, enable rapid action selection, but these methods learn slowly and adapt poorly to changing environments. In addition to MF and MB methods, there are intermediate solutions that rely on learning useful representations that reduce burdens on the downstream RL process (11–13).In the spatial-memory literature, a distinction has been observed between “response learning” and “place learning” (14–16). When navigating to a previously visited location, response learning involves learning a sequence of actions, each of which depends on the preceding action or sensory cue (expressed in egocentric terms). For example, one might remember a sequence of left and right turns starting from a specific landmark. An alternative place-learning strategy involves learning a flexible internal representation of the spatial layout of the environment (expressed in allocentric terms). This “cognitive map” is thought to be supported by the hippocampal formation, where there are neurons tuned to place and heading direction (17–19). Spatial navigation using this map is flexible because it can be used with arbitrary starting locations and destinations, which need not be marked by immediate sensory cues.We posit that the distinction between place and response learning is analogous to that between MB and MF RL (20). Under this view, associative reinforcement is supported by the DLS (21, 22). Indeed, there is evidence from both rodents (23–25) and humans (26, 27) that spatial-response learning relies on the same basal ganglia structures that support MF RL. Evidence also suggests an analogy between MB reasoning and hippocampus (HPC)-based place learning (28, 29). However, this equivalence is not completely straightforward. For example, in rodents, multiple hippocampal lesion and inactivation studies failed to elicit an effect on action-outcome learning, a hallmark of MB planning (30–35). Nevertheless, there are indications that HPC might contribute to a different aspect of MB RL: namely, the representation of relational structure. Tasks that require memory of the relationships between stimuli do show dependence on HPC (36–42).Here, we formalize the perspective that hippocampal contributions to MB learning and place learning are the same, as are the dorsolateral striatal contributions to MF and response learning. In our model, HPC supports flexible behavior by representing the relational structure among different allocentric states, while dorsolateral striatum (DLS) supports associative reinforcement over egocentric sensory features. The model arbitrates between the use of these systems by weighting each system’s action values by the reliability of the system, as measured by a recent average of prediction errors, following Wan Lee et al. (43). We show that HPC and DLS maintain these roles across multiple task domains, including a range of spatial and nonspatial tasks. Our model can quantitatively explain a range of seemingly disparate findings, including the choice between place and response strategies in spatial navigation (23, 44) and choices on nonspatial multistep decision tasks (45, 46). Furthermore, it explains the puzzling finding that landmark-guided navigation is sensitive to the blocking effect, whereas boundary-guided navigation is not (27), and that these are supported by the DLS and HPC, respectively (26). Thus, different RL strategies that manage competing tradeoffs can explain a longstanding body of spatial navigation and decision-making literature under a unified model.     

Testing the drift-diffusion model

The drift-diffusion model (DDM) is a model of sequential sampling with diffusion signals, where the decision maker accumulates evidence until the process hits either an upper or lower stopping boundary and then stops and chooses the alternative that corresponds to that boundary. In perceptual tasks, the drift of the process is related to which choice is objectively correct, whereas in consumption tasks, the drift is related to the relative appeal of the alternatives. The simplest version of the DDM assumes that the stopping boundaries are constant over time. More recently, a number of papers have used nonconstant boundaries to better fit the data. This paper provides a statistical test for DDMs with general, nonconstant boundaries. As a by-product, we show that the drift and the boundary are uniquely identified. We use our condition to nonparametrically estimate the drift and the boundary and construct a test statistic based on finite samples.

The drift-diffusion model (DDM) is a model of sequential sampling with diffusion (Brownian) signals, where the decision maker accumulates evidence until the process hits a stopping boundary and then stops and chooses the alternative that corresponds to that boundary. This model has been widely used in psychology, neuroeconomics, and neuroscience to explain the observed patterns of choice and response times in a range of binary-choice decision problems. One class of papers studies “perception tasks” with an objectively correct answer—e.g., “are more of the dots on the screen moving left or moving right?”; here, the drift of the process is related to which choice is objectively correct (1, 2). The other class of papers studies “consumption tasks” (otherwise known as value-based tasks, or preferential tasks), such as “which of these snacks would you rather eat?”; here, the drift is related to the relative appeal of the alternatives (3–11).The simplest version of the DDM assumes that the stopping boundaries are constant over time (12–15). More recently, a number of papers use nonconstant boundaries to better fit the data and, in particular, the observed correlation between response times and choice accuracy—i.e., that correct responses are faster than incorrect responses (16–19).Constant stopping boundaries are optimal for perception tasks, where the volatility of the signals and the flow cost of sampling are both constant, and the prior belief is that the drift of the diffusion has only two possible values, depending on which decision is correct. Even with constant volatility and costs, nonconstant boundaries are optimal for other priors—for example, when the difficulty of the task varies from trial to trial and some decision problems are harder than others. Ref. 17 shows how to computationally derive the optimal boundaries in this case. Ref. 18 characterizes the optimal boundaries for the consumption task: The decision maker is uncertain about the utility of each choice, with independent normal priors on the value of each option.This paper provides a statistical test for DDMs with general boundaries, without regard to their optimality. We first prove a characterization theorem: We find a condition on choice probabilities that is satisfied if and only if (iff) the choice probabilities are generated by some DDM. Moreover, we show that the drift and the boundary are uniquely identified. We then use our condition to nonparametrically estimate the drift and the boundary and construct a test statistic based on finite samples.Recent related work on DDM includes ref. 17, which conducted a Bayesian estimation of a collapsing boundary model, and ref. 18, which conducted a maximum-likelihood estimation. Ref. 20 estimates collapsing boundaries in a parametric class, allowing for a random nondecision time at the start. Ref. 21 estimates a version of the DDM with constant boundaries, but random starting point of the signal-accumulation process; ref. 22 estimates a similar model where other parameters are made random. Ref. 23 partially characterizes DDM with constant boundary.^*Other work on DDM-like models includes the decision-field theory of refs. 24–26, which allows the signal process to be mean-reverting. Refs. 27 and 28 study models where response time is a deterministic function of the utility difference. Refs. 29–34 study dynamic costly optimal information acquisition. Alós-Ferrer et al. show how to recover preferences from data in a random utility model where the response time is a deterministic function of the realized utilities (35).     

From the Cover: Overexpression of CD47 is associated with brain overgrowth and 16p11.2 deletion syndrome

Copy number variation (CNV) at the 16p11.2 locus is associated with neuropsychiatric disorders, such as autism spectrum disorder and schizophrenia. CNVs of the 16p gene can manifest in opposing head sizes. Carriers of 16p11.2 deletion tend to have macrocephaly (or brain enlargement), while those with 16p11.2 duplication frequently have microcephaly. Increases in both gray and white matter volume have been observed in brain imaging studies in 16p11.2 deletion carriers with macrocephaly. Here, we use human induced pluripotent stem cells (hiPSCs) derived from controls and subjects with 16p11.2 deletion and 16p11.2 duplication to understand the underlying mechanisms regulating brain overgrowth. To model both gray and white matter, we differentiated patient-derived iPSCs into neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs). In both NPCs and OPCs, we show that CD47 (a “don’t eat me” signal) is overexpressed in the 16p11.2 deletion carriers contributing to reduced phagocytosis both in vitro and in vivo. Furthermore, 16p11.2 deletion NPCs and OPCs up-regulate cell surface expression of calreticulin (a prophagocytic “eat me” signal) and its binding sites, indicating that these cells should be phagocytosed but fail to be eliminated due to elevations in CD47. Treatment of 16p11.2 deletion NPCs and OPCs with an anti-CD47 antibody to block CD47 restores phagocytosis to control levels. While the CD47 pathway is commonly implicated in cancer progression, we document a role for CD47 in psychiatric disorders associated with brain overgrowth.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by deficits in social interaction and communication. Copy number variation (CNV) at the 16p11.2 locus is associated with ASD (1–8). People who have 16p11.2 deletion syndrome tend to have larger head circumferences (macrocephaly), with disproportionate enlargement in both gray and white matter volume (8–13). Individuals with ASD and macrocephaly have more severe behavioral and cognitive problems and are less responsive to standard medical and therapeutic interventions than those with ASD and normal head circumferences (14). In addition, prior work has documented a very strong cross-sectional and temporal association between macrocephaly and ASD symptoms (8, 9, 11, 12, 14–17). These findings suggest that understanding the underlying mechanisms regulating macrocephaly could provide a window of opportunity for intervention or mitigation of symptoms.Here, we used patient-derived human induced pluripotent stem cells (hiPSCs) to interrogate the underlying mechanisms contributing to gray and white matter enlargement. We focused on individuals with intellectual disability (IQ < 70) or ASD associated with brain overgrowth in 16p11.2 deletion carriers. We differentiated the iPSCs into neural progenitor cells (NPCs) and oligodendrocyte progenitor cells (OPCs) and investigate the hypothesis that brain enlargement in 16p11.2 deletion carriers may be due to improper cellular elimination. Under normal conditions, classic “eat me” and “don’t eat me” signaling mechanisms associated with phagocytosis maintain cellular homeostasis across diverse tissue types (18, 19). CD47 (a “don’t eat me” signal) protects normal cells from getting cleared (18), but can become overexpressed in many types of cancer cells, preventing tumorigenic cells from getting engulfed or phagocytosed (20–22). In fact, CD47 plays an important role in many pathological disorders associated with an overproduction of cells and cell removal, including cancer (20–22), atherosclerosis (23), and fibrotic diseases (24). NPCs derived from iPSCs of autistic individuals with macrocephaly have increased proliferation relative to controls (25, 26). Therefore, we hypothesized that CD47 may be involved in these disorders.We find that CD47 is overexpressed in NPCs and OPCs derived from 16p11.2 deletion carriers, leading to reduced phagocytosis by macrophages and microglia. Furthermore, the 16p11.2 deletion NPCs and OPCs have increased cell surface expression of calreticulin (CRT, a prophagocytic “eat me” signal), indicating that these cells should be eliminated but are not due to high levels of CD47 (27). Importantly, treatment with a CD47 blocking antibody restores phagocytosis of 16p11.2 deletion NPCs and OPCs to control levels, particularly in 16p_del NPCs and OPCs that have increased cell surface expression of CRT, indicating that the changes in phagocytosis are mediated by cell surface expression of CD47. We thus identify a role for CD47 in 16p11.2 deletion syndrome and highlight the potential importance of blocking CD47 to promote clearance of unhealthy NPCs and OPCs in 16p11.2 deletion with brain overgrowth.     

Gender stereotypes can explain the gender-equality paradox

The so-called “gender-equality paradox” is the fact that gender segregation across occupations is more pronounced in more egalitarian and more developed countries. Some scholars have explained this paradox by the existence of deeply rooted or intrinsic gender differences in preferences that materialize more easily in countries where economic constraints are more limited. In line with a strand of research in sociology, we show instead that it can be explained by cross-country differences in essentialist gender norms regarding math aptitudes and appropriate occupational choices. To this aim, we propose a measure of the prevalence and extent of internalization of the stereotype that “math is not for girls” at the country level. This is done using individual-level data on the math attitudes of 300,000 15-y-old female and male students in 64 countries. The stereotype associating math to men is stronger in more egalitarian and developed countries. It is also strongly associated with various measures of female underrepresentation in math-intensive fields and can therefore entirely explain the gender-equality paradox. We suggest that economic development and gender equality in rights go hand-in-hand with a reshaping rather than a suppression of gender norms, with the emergence of new and more horizontal forms of social differentiation across genders.

Although women nowadays outnumber men in higher education, they remain strongly underrepresented in math-intensive fields (1, 2). This underrepresentation is a source of concern for two main reasons: It contributes substantially to gender inequality in the labor market, and it represents a loss of potential talent that could in particular help meeting the growing demand of skills related to the development of information technology and artificial intelligence (1–6).Despite these concerns, the underrepresentation of women in math-intensive fields has remained constant or even increased in most developed countries during the past two decades (7). This underrepresentation is also more pronounced in more developed countries (8–10) and in countries that are more gender equal in terms of economic and political opportunities and rights (10), a pattern that has been named the “gender-equality paradox” (10).Similar cross-country paradoxical relationships have been found with a large range of other gender gaps: more gender-egalitarian (in the sense of the Global Gender Gap Index [GGGI], which essentially captures “vertical” or “traditional” gender equality; see details below), and wealthier countries also experience higher gender gaps in basic preferences measured through laboratory experiment (11), cognitive abilities such as spatial visualization (12), self-reported personality traits (13), basic human values (14), self-esteem (15), subjective well-being (16), or depression (17). These associations have led scholars to question gender socialization theories and the gender stratification model (9, 18) according to which gender gaps in interest, performance, and choices are mainly the result of gender gaps in status and opportunities. It has been argued in particular that the gender stratification model fails to account for the fact that countries renowned for gender equality show some of the largest sex differences in interest in and pursuit of science, technology, engineering, and mathematics (STEM) degrees (19).A common explanation put forward in some recent literature for the gender-equality paradox is that in more equal and developed countries, girls and boys have more freedom and ease to express their intrinsically distinct inner preferences and interests (10–12). This explanation gets its theoretical foundations from the tradition of evolutionary psychology, which posits the existence of innate gender differences in, e.g., personality or interests (20).In this contribution, in line with a strand of research in sociology, initiated by Charles and coworkers, relating horizontal educational and occupational segregation to gender essentialism (8, 9, 21, 22), we show that the gender-equality paradox could also be explained by differences across countries in culturally constructed gender identities. To this aim, we build a country-level measure of the gender essentialist norm that “math is not for girls,” we show that this measure is larger in more developed and more egalitarian countries, and we establish that it can mediate the paradoxical relationship between economic development or traditional gender equality and the underrepresentation of women in math-related fields.To discuss the mechanisms connecting socioeconomic development or traditional gender equality to gender essentialism, we rely on previous research that highlights the multidimensional nature of gender equality (9, 23–26) and allows us to suggest possible explanations for the fact that more developed countries that are more gender egalitarian in terms of rights (as measured by the GGGI) can exhibit stronger gender norms, as well as gender inequalities in dimensions such as female representation in math-related fields. We focus primarily on mathematics, as the underrepresentation of women in STEM is large mostly in math-related fields (mathematics, physics, computer science, and engineering).     

From the Cover: Evidence from South Africa for a protracted end-Permian extinction on land

Earth’s largest biotic crisis occurred during the Permo–Triassic Transition (PTT). On land, this event witnessed a turnover from synapsid- to archosauromorph-dominated assemblages and a restructuring of terrestrial ecosystems. However, understanding extinction patterns has been limited by a lack of high-precision fossil occurrence data to resolve events on submillion-year timescales. We analyzed a unique database of 588 fossil tetrapod specimens from South Africa’s Karoo Basin, spanning ∼4 My, and 13 stratigraphic bin intervals averaging 300,000 y each. Using sample-standardized methods, we characterized faunal assemblage dynamics during the PTT. High regional extinction rates occurred through a protracted interval of ∼1 Ma, initially co-occurring with low origination rates. This resulted in declining diversity up to the acme of extinction near the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary. Regional origination rates increased abruptly above this boundary, co-occurring with high extinction rates to drive rapid turnover and an assemblage of short-lived species symptomatic of ecosystem instability. The “disaster taxon” Lystrosaurus shows a long-term trend of increasing abundance initiated in the latest Permian. Lystrosaurus comprised 54% of all specimens by the onset of mass extinction and 70% in the extinction aftermath. This early Lystrosaurus abundance suggests its expansion was facilitated by environmental changes rather than by ecological opportunity following the extinctions of other species as commonly assumed for disaster taxa. Our findings conservatively place the Karoo extinction interval closer in time, but not coeval with, the more rapid marine event and reveal key differences between the PTT extinctions on land and in the oceans.

Mass extinctions are major perturbations of the biosphere resulting from a wide range of different causes including glaciations and sea level fall (1), large igneous provinces (2), and bolide impacts (3, 4). These events caused permanent changes to Earth’s ecosystems, altering the evolutionary trajectory of life (5). However, links between the broad causal factors of mass extinctions and the biological and ecological disturbances that lead to species extinctions have been difficult to characterize. This is because ecological disturbances unfold on timescales much shorter than the typical resolution of paleontological studies (6), particularly in the terrestrial record (6–8). Coarse-resolution studies have demonstrated key mass extinction phenomena including high extinction rates and lineage turnover (7, 9), changes in species richness (10), ecosystem instability (11), and the occurrence of disaster taxa (12). However, finer time resolutions are central to determining the association and relative timings of these effects, their potential causal factors, and their interrelationships. Achieving these goals represents a key advance in understanding the ecological mechanisms of mass extinctions.The end-Permian mass extinction (ca. 251.9 Ma) was Earth’s largest biotic crisis as measured by taxon last occurrences (13–15). Large outpourings from Siberian Trap volcanism (2) are the likely trigger of calamitous climatic changes, including a runaway greenhouse effect and ocean acidification, which had profound consequences for life on land and in the oceans (16–18). An estimated 81% of marine species (19) and 89% of tetrapod genera became extinct as established Permian ecosystems gave way to those of the Triassic. In the ocean, this included the complete extinction of reef-forming tabulate and rugose corals (20, 21) and significant losses in previously diverse ammonoid, brachiopod, and crinoid families (22). On land, many nonmammalian synapsids became extinct (16), and the glossopterid-dominated floras of Gondwana also disappeared (23). Stratigraphic sequences document a global “coral gap” and “coal gap” (24, 25), suggesting reef and forest ecosystems were rare or absent for up to 5 My after the event (26). Continuous fossil-bearing deposits documenting patterns of turnover across the Permian–Triassic transition (PTT) on land (27) and in the oceans (28) are geographically widespread (29, 30), including marine and continental successions that are known from China (31, 32) and India (33). Continental successions are known from Russia (34), Australia (35), Antarctica (36), and South Africa’s Karoo Basin (Fig. 1 and 37–40), the latter providing arguably the most densely sampled and taxonomically scrutinized (41–43) continental record of the PTT. The main extinction has been proposed to occur at the boundary between two biostratigraphic zones with distinctive faunal assemblages, the Daptocephalus and Lystrosaurus declivis assemblage zones (Fig. 1), which marks the traditional placement of the Permian–Triassic geologic boundary [(37) but see ref. 44]. Considerable research has attempted to understand the anatomy of the PTT in South Africa (38, 39, 45–52) and to place it in the context of biodiversity changes across southern Gondwana (53, 54) and globally (29, 31, 32, 44, 47, 55).Open in a separate windowFig. 1.Map of South Africa depicting the distribution of the four tetrapod fossil assemblage zones (Cistecephalus, Daptocephalus, Lystrosaurus declivis, Cynognathus) and our two study sites where fossils were collected in this study (sites A and B). Regional lithostratigraphy and biostratigraphy within the study interval are shown alongside isotope dilution–thermal ionization mass spectrometry dates retrieved by Rubidge et al., Botha et al., and Gastaldo et al. (37, 44, 80). The traditional (dashed red line) and associated PTB hypotheses for the Karoo Basin (37, 44) are also shown. Although traditionally associated with the PTB, the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary is defined by first appearances of co-occurring tetrapod assemblages, so its position relative to the three PTB hypotheses is unchanged. The Ripplemead member (*) has yet to be formalized by the South African Committee for Stratigraphy.Decades of research have demonstrated the richness of South Africa’s Karoo Basin fossil record, resulting in hundreds of stratigraphically well-documented tetrapod fossils across the PTT (37, 39, 56). This wealth of data has been used qualitatively to identify three extinction phases and an apparent early postextinction recovery phase (39, 45, 51). Furthermore, studies of Karoo community structure and function have elucidated the potential role of the extinction and subsequent recovery in breaking the incumbency of previously dominant clades, including synapsids (11, 57). Nevertheless, understanding patterns of faunal turnover and recovery during the PTT has been limited by the scarcity of quantitative investigations. Previous quantitative studies used coarsely sampled data (i.e., assemblage zone scale, 2 to 3 Ma time intervals) to identify low species richness immediately after the main extinction, potentially associated with multiple “boom and bust” cycles of primary productivity based on δ¹³C variation during the first 5 My of the Triassic (41, 58). However, many details of faunal dynamics in this interval remain unknown. Here, we investigate the dynamics of this major tetrapod extinction at an unprecedented time resolution (on the order of hundreds of thousands of years), using sample-standardized methods to quantify multiple aspects of regional change across the Cistecephalus, Daptocephalus, and Lystrosaurus declivis assemblage zones.     

From the Cover: Climate shock effects and mediation in fisheries

Climate shocks can reorganize the social–ecological linkages in food-producing communities, leading to a sudden loss of key products in food systems. The extent and persistence of this reorganization are difficult to observe and summarize, but are critical aspects of predicting and rapidly assessing community vulnerability to extreme events. We apply network analysis to evaluate the impact of a climate shock—an unprecedented marine heatwave—on patterns of resource use in California fishing communities, which were severely affected through closures of the Dungeness crab fishery. The climate shock significantly modified flows of users between fishery resources during the closures. These modifications were predicted by pre-shock patterns of resource use and were associated with three strategies used by fishing community member vessels to respond to the closures: temporary exit from the food system, spillover of effort from the Dungeness crab fishery into other fisheries, and spatial shifts in where crab were landed. Regional differences in resource use patterns and vessel-level responses highlighted the Dungeness crab fishery as a seasonal “gilded trap” for northern California fishing communities. We also detected disparities in climate shock response based on vessel size, with larger vessels more likely to display spatial mobility. Our study demonstrates the importance of highly connected and decentralized networks of resource use in reducing the vulnerability of human communities to climate shocks.

Climate shocks threaten food systems around the world and are expected to increase in frequency and intensity under climate change (1–5). Distinct from climate change (e.g., long-term warming), climate shocks rapidly outstrip the capacity of a system to cope by inflicting unexpected and highly concentrated damage (6). Vulnerability of communities to climate shocks varies within and across food systems, depending on the severity of the shock and the sensitivity and adaptive capacity of community members (7). Communities that form the harvesting and processing base of food systems—especially agrarian and fishing communities—are often among the most vulnerable to climate shocks (8), as their resource-based economies operate at the interface of environment and society. Marine heatwaves represent one such climate shock of growing importance, as they impact fishing communities by compromising seafood safety, shifting species distributions, and lowering recruitment and survival of fished species (9–12).Diversifying harvest portfolios is one strategy used by fishers to manage risk (13–16). If marine heatwaves disproportionately affect a subset of species, fishers may respond by shifting participation into less affected fisheries. This response, referred to as “leakage” or “spillover” (17–21), restructures the networks that form as fishers participate in multiple fisheries (19–21). The topology of these fisheries participation networks can reveal the extent to which climate shocks lead to indirect or lasting changes in patterns of resource use within fishing communities and, by drawing on network theory, indicate the sensitivity of these communities to perturbations (18).The 2014–2016 North Pacific marine heatwave (12, 22) was a climate shock that led to a massive harmful algal bloom (HAB), contaminating Dungeness crab with biotoxins and compelling state managers to coordinate fishery closures along the entire US West Coast (23). In California, where the Dungeness crab fishery represents ∼26% of all annual fishery revenue (California Department of Fish and Wildlife; https://wildlife.ca.gov) and supports >25% of all commercial fishing vessels (Pacific Fisheries Information Network; http://pacfin.psmfc.org), the HAB significantly delayed the 2015–16 commercial Dungeness crab fishing season (24). California Dungeness crab landings for the 2015–16 season reached only 52% of the average catch from the previous 5 y, spurring Congress to appropriate >$25 million in federal disaster relief funding (25). Dungeness crab fishers reported shifting participation to alternative fisheries during the 2015–16 season to offset socioeconomic impacts (26, 27); however, to date there has been no quantitative demonstration of spillover from the Dungeness crab fishery, or analysis of how the resulting changes in fisheries participation networks may have varied geographically and persisted after the closures were lifted.Our study examined the impact of the 2015–16 Dungeness crab fishery closures (hereafter 2016 closures) on patterns of resource use in California fishing communities. We considered seven fishing communities representing a total of 2,516 individual fishing vessels (Table 1). We found significant changes in fisheries participation network topology during the 2016 closures, which corresponded with a severe reduction in fishing activity, spillover of fishing effort from the Dungeness crab fishery, and spatial variation in pre-shock network topology. Our analysis captured changing patterns of resource use during a severe climate shock, and demonstrated how this emergent social outcome in fishing communities can be predicted by pre-shock network metrics and related to the adaptive strategies of community member vessels. We discuss the implications of fishery management measures for adaptive decision making and network structure, and provide recommendations for sustainable fishery management during climate shocks.Table 1.Ports of landing and vessel counts for the seven California fishing communities included in this study

Prespacers formed during primed adaptation associate with the Cas1–Cas2 adaptation complex and the Cas3 interference nuclease–helicase

For Type I CRISPR-Cas systems, a mode of CRISPR adaptation named priming has been described. Priming allows specific and highly efficient acquisition of new spacers from DNA recognized (primed) by the Cascade-crRNA (CRISPR RNA) effector complex. Recognition of the priming protospacer by Cascade-crRNA serves as a signal for engaging the Cas3 nuclease–helicase required for both interference and primed adaptation, suggesting the existence of a primed adaptation complex (PAC) containing the Cas1–Cas2 adaptation integrase and Cas3. To detect this complex in vivo, we here performed chromatin immunoprecipitation with Cas3-specific and Cas1-specific antibodies using cells undergoing primed adaptation. We found that prespacers are bound by both Cas1 (presumably, as part of the Cas1–Cas2 integrase) and Cas3, implying direct physical association of the interference and adaptation machineries as part of PAC.

CRISPR-Cas systems of adaptive immunity provide prokaryotes with resistance against bacteriophages and plasmids (1–4). They consist of CRISPR DNA arrays and cas genes. Functionally, CRISPR defense can be subdivided into the interference and adaptation steps. The interference step involves specific recognition of regions in foreign nucleic acids, named protospacers, based on their complementarity to CRISPR arrays spacers followed by their destruction (5). The CRISPR adaptation step leads to integration of new spacers into the array (6, 7), forming inheritable memory that allows the entire lineage of cells derived from a founder that acquired a particular spacer to do away with genetic invaders carrying matching protospacers (8).Both interference and adaptation can be subdivided into multiple steps. For interference to occur, the CRISPR array is transcribed from a promoter located in the upstream leader region. The resulting pre-CRISPR RNA (pre-crRNA) is processed into short CRISPR RNAs (crRNAs), each containing a spacer flanked by repeat fragments (9). Individual crRNAs are bound by Cas proteins forming the effector complex, which is capable of recognizing sequences complementary to the spacer part of crRNA (10). Upon protospacer recognition, the target is destroyed either by a protein component of the effector complex or by additional recruitable Cas nucleases (3, 11–14). In a well-studied Type I-E CRISPR-Cas system of Escherichia coli, the effector comprises a multisubunit Cascade protein complex bound to a crRNA (11, 12, 15). The complementary interaction of Cascade-bound crRNA with a target protospacer leads to localized protospacer DNA melting and formation of an R-loop complex, where the crRNA spacer is annealed to the protospacer “target” strand, while the opposing “nontarget” strand is displaced and is present in a single-stranded form (16, 17). To avoid potentially suicidal recognition of CRISPR array spacers from which crRNAs originate, target recognition and R-loop complex formation require, in addition to complementarity with the crRNA spacer, the presence of a three-nucleotide long PAM (protospacer adjacent motif) preceding the protospacer (15, 18, 19). For E. coli type I-E system, the consensus PAM sequence is 5′-AAG-3′ on the nontarget strand. Some other trinucleotides also allow target recognition, though with decreased efficiency (15, 20). Below, we will refer to consensus PAM as “PAM^AAG.” The Cas3 nuclease-helicase is recruited to the R-loop complex and is responsible for target destruction (21–24). Cas3 first introduces a single-stranded break in the nontarget protospacer strand 11 to 15 nucleotides downstream of the PAM on the nontarget strand (25). Next, Cas3 unwinds and cleaves DNA in the 3′-5′ direction from the PAM (26–29). In vitro, Cas3-dependent degradation of DNA at the other side of the protospacer was also detected (16). Bidirectional Cas3-dependent degradation of DNA was also detected in vivo (30). The details of Cas3 “molecular gymnastics” required for such bidirectional destruction of DNA around the R-loop complex are not known.The main proteins of CRISPR adaptation are Cas1 and Cas2. In vitro, these proteins interact with each other, and the resulting complex is capable of inserting spacer-sized fragments in substrate DNA molecules containing at least one CRISPR repeat and a repeat-proximal leader region (31, 32). In the course of spacer integration, the Cas1–Cas2 complex first catalyzes a direct nucleophilic attack by the 3′-OH end of the incoming spacer at a phosphodiester bond between the leader and the first repeat in the top CRISPR strand (32, 33). This reaction proceeds via concurrent cleavage of the leader-repeat junction and covalent joining of one spacer strand to the 5′ end of the repeat. Subsequently, the 3′-OH on the second spacer strand attacks the phosphodiester bond at the repeat-spacer junction in the bottom CRISPR strand leading to full integration (32, 33). As a result, an intermediate with the newly incorporated spacer flanked by single-stranded repeat sequences is formed (32, 34). The gaps are filled in by a DNA polymerase, possibly DNA polymerase I (35).When overexpressed, E. coli Cas1 and Cas2 can integrate new spacers into the array in the absence of other Cas proteins (7, 36). During such “naive” adaptation, ∼50% of newly acquired spacers are selected from sequences flanked by the 5′-AAG-3′ trinucleotide, that is, consensus interference-proficient PAM^AAG. It thus follows that at least 50% of spacers acquired by Cas1 and Cas2 alone will be defensive during the interference step. The adaptation process must be tightly controlled, activated in the presence of the infecting mobile genetic elements, and directed toward foreign DNA, for otherwise, spacers acquired from host DNA will lead to suicidal self-interference. The details of the activation of CRISPR adaptation upon the entry of foreign DNA into the cell remain elusive. Some data indicate that active replication and/or a small size of phage or plasmid DNA may be responsible for a preferential selection of spacers from these molecules compared to selection of self-targeting spacers from host chromosomes (19). In addition, DNA repair/recombination signals present in host DNA, but lacking in foreign DNA may also increase the bias of the adaptation machinery to the latter (37).The bias of spacer acquisition machinery toward foreign DNA does not have to be significant, for acquisition of a self-targeting spacer by an infected cell will lead to the demise of such a cell in an act of altruism that would help control the spread of the infectious agent through the population. In contrast, acquisition of interference-proficient spacers from foreign DNA may allow the infected cell to survive, clear the infection, and endow its progeny with inheritable resistance—clearly an advantageous trait.To overcome CRISPR resistance, viruses and plasmids accumulate “escaper” mutations in the targeted protospacer or its PAM (36, 38). Given that the acquisition of protective spacers in infected cells is likely to be a rare event and the ease with which escaper mutations accumulate, the complex multistage CRISPR defense could become costly and ineffective (39). To increase the efficiency of CRISPR defense and counter the spread of mobile genetic elements with escaper mutations, CRISPR-Cas systems have evolved a specialized mode of spacer acquisition referred to as “primed adaptation” or “priming” (36, 40–47). Unlike the naive adaptation, in Type I CRISPR-Cas systems, priming requires, in addition to Cas1 and Cas2, a Cascade charged with crRNA recognizing the foreign target and the Cas3 nuclease–helicase. Spacers acquired during priming originate almost exclusively from DNA located in cis with the protospacer initially recognized by the effector complex (referred to hereafter as the “priming protospacer” or “PPS”). Furthermore, 90% or more of spacers acquired during priming by the I-E system of E. coli originate from protospacers with PAM^AAG and are therefore capable of efficient interference. Another hallmark of primed adaptation is the following: spacers acquired from DNA located at different sides of the PPS map to opposite DNA strands. The mapping of spacers acquired during naive adaptation shows no strand bias (48). Thus, the strand bias of spacers acquired during priming is probably related to Cas3 nuclease activity; however, exact details are lacking.The overall yield of spacers acquired during priming is increased when the PPS is imperfectly matched with a Cascade-bound crRNA spacer or when the PAM of the PPS is suboptimal (49). Thus, escaper protospacers serve as PPS, and priming initiated by inefficient recognition of such protospacers allows cells to quickly update their immunological memory by specific and efficient acquisition of additional interference-proficient spacers from mobile genetic elements that accumulated escaper mutations to earlier acquired spacers.The exact molecular mechanism of primed adaptation is not fully understood. Clearly, it should involve tight coordination between suboptimal interference against escaper targets and the spacer acquisition process. The DNA fragments produced by Cas3, a nuclease responsible for target degradation during interference, may feed primed adaptation, directly or indirectly, providing a functional link between the interference and adaptation arms of the CRISPR-Cas response. Based on results of in vitro experiments, it has been proposed that Cas3-generated degradation products may be used as substrates for the generation of prespacers (50)—DNA fragments that can be incorporated by the Cas1–Cas2 complex into arrays. However, no Cas3-generated products were detected in cells undergoing interference only, suggesting that Cas3 may degrade DNA to very short, subspacer length products (30). On the other hand, mutations abolishing the Cas3 nuclease activity lead to very little primed adaptation, indicating that priming requires the Cas3 nuclease activity (51). A possible way out from this impasse would be the existence of a “priming complex” that includes both Cas1–Cas2 and Cas3 and is responsible for the generation of prespacers by the Cas1–Cas2 complex from DNA along which Cas3 moves. Single-molecule analysis supports the existence of such a complex and even suggests that PPS-bound Cascade may be part of the priming complex (52). Here, we show that both Cas1–Cas2 and Cas3 associate with the same set of prespacers in cells undergoing primed adaptation, functionally linking CRISPR interference and adaptation machineries during priming. We also investigate the phenomenon of strand bias of spacer acquisition during priming and show that this bias does not depend on the orientation of PPS.     

From the Cover: Discovery of a body-wide photosensory array that matures in an adult-like animal and mediates eye–brain-independent movement and arousal

The ability to respond to light has profoundly shaped life. Animals with eyes overwhelmingly rely on their visual circuits for mediating light-induced coordinated movements. Building on previously reported behaviors, we report the discovery of an organized, eye-independent (extraocular), body-wide photosensory framework that allows even a head-removed animal to move like an intact animal. Despite possessing sensitive cerebral eyes and a centralized brain that controls most behaviors, head-removed planarians show acute, coordinated ultraviolet-A (UV-A) aversive phototaxis. We find this eye–brain-independent phototaxis is mediated by two noncanonical rhabdomeric opsins, the first known function for this newly classified opsin-clade. We uncover a unique array of dual-opsin–expressing photoreceptor cells that line the periphery of animal body, are proximal to a body-wide nerve net, and mediate UV-A phototaxis by engaging multiple modes of locomotion. Unlike embryonically developing cerebral eyes that are functional when animals hatch, the body-wide photosensory array matures postembryonically in “adult-like animals.” Notably, apart from head-removed phototaxis, the body-wide, extraocular sensory organization also impacts physiology of intact animals. Low-dose UV-A, but not visible light (ocular-stimulus), is able to arouse intact worms that have naturally cycled to an inactive/rest-like state. This wavelength selective, low-light arousal of resting animals is noncanonical-opsin dependent but eye independent. Our discovery of an autonomous, multifunctional, late-maturing, organized body-wide photosensory system establishes a paradigm in sensory biology and evolution of light sensing.

Light sensing has independently evolved multiple times and has profoundly shaped life. The ability to process light information in distinct ways and respond to a changing light environment can dramatically shape physiology and fitness of life forms. Movement, triggered by light, is one of the most fundamental responses in nature (1). Among metazoans, a wide variety of animals are known to show coordinated motion in response to light stimuli. So far, this is overwhelmingly known to be mediated through the animal eyes. In fact, eye-driven light sensing and taxis has been extensively studied across phyla. Interestingly, motion in metazoans can also be mediated through eye-independent or extraocular (EO) photoreception (2–5). However, our conceptual and mechanistic grasp on how coordinated movement can be triggered and controlled through EO light-sensing systems is extremely limited. Moreover, the few prominent examples of EO phototaxis have all been reported in life forms/developmental stages completely lacking eyes or possessing only rudimentary eyes (2, 5). Almost nothing is known about sensitive EO light-sensing systems capable of triggering coordinated motion that may coexist with sensitive eyes in a single organism.There are intriguing reports of photoreceptor molecules that are expressed in locations other than conventional eyes, including in unusual structures seen in polyclad flatworms, clitellate segmented worms, crustaceans, cephalopods, and fishes. However, the functions of such structures remain elusive (6–13). A single organism may indeed possess multiple, independent light-responsive systems, both eye based as well as eye independent (13–17), but the functions rarely overlap. “Nonvisual”/EO sensory systems like pineal glands and deep-brain photoreceptors across vertebrates and retinal ganglion cells in mammals (18–21) have been reported. However, these sensory systems are generally known to perform “nonvisual” functions like maintaining circadian rhythms and modulating behavior (22–25). Here, we report an EO phototactic network that can independently trigger coordinated movement just like what the eye-based (ocular) system can, while also having its own distinctive role even when the eyes are present.Do highly sensitive EO phototactic systems coexist and function in life forms that have prominent eye-based networks as well? How would such a system operate? What would be the mechanistic framework and the functional consequence of such an eye-independent light-sensory system? Planarian flatworms offer a fascinating opportunity to explore such a paradigm. Planarians are highly light aversive and have well-developed ocular cerebral eyes (eyes connected to a centralized ganglion) that process light stimuli and guide behavior like feeding, escape, and predation (26–30). In fact, the planarian ocular network is highly sensitive and capable of surprisingly complex processing (17). These eye-mediated behaviors are reliant on an organized, cephalized bilobed brain, a prominent example of a “primitive” brain in evolution (17, 31, 32). Indeed, the brain is required for most locomotive behaviors including thermotaxis, chemotaxis, and eye-mediated phototaxis including the ability to discriminate closely related light stimuli, shown by these animals (17, 32–34). However, planarians also show dramatic, eye–brain-independent light-induced movements (17, 35). Even after sudden decapitation (removal of both eyes and brain), worms are able to acutely respond to ultraviolet-A (UV-A) light and show seemingly coordinated movement away from light (17, 35). While such eye–brain-independent behavior has long fascinated biologists, almost nothing is known about how this dramatic behavior is mediated (17, 35–39). It is also not clear what would be the physiological role of such an acutely sensitive EO sensory network capable of triggering coordinated movement, especially since planarians do have a well-developed ocular network.Here, we show how such an acute response to light is mediated by an organism removed of its “primary” light-sensory organ and brain. We report the discovery of photoreceptor molecules as well as a widespread but organized network of photoreceptor cells that are required for this acute eye-independent UV-A light response. Intriguingly, this entire multiscale sensory system from photoreceptors to the network of cells arises and matures postembryonically, in an “adult-like” organism. This developmental trajectory is distinct from that of the cerebral eyes, which develop embryonically. We also demonstrate that while both the eyes as well the EO network led to coordinated movements relying on the same locomotion machinery, the physiological consequences of the ocular and EO sensory responses can be divergent. Intact planarians periodically go into “sleep-like” resting phases, in which their activity diminishes and sensory perception reduces (40). Strikingly, we find that the EO sensory system in these intact animals can override the natural “rest”-activity cycles and is able to acutely photoactivate and arouse even resting worms. This is distinct from the ocular network that becomes dormant during the “rest phase.” Our work illustrates an unprecedented level of organization and complexity in form and function of an acutely sensitive EO light-sensory system that matures and functions in parallel to the ocular network.     

Cholinergic suppression of hippocampal sharp-wave ripples impairs working memory

Learning and memory are assumed to be supported by mechanisms that involve cholinergic transmission and hippocampal theta. Using G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) with a fiber-photometric fluorescence readout in mice, we found that cholinergic signaling in the hippocampus increased in parallel with theta/gamma power during walking and REM sleep, while ACh3.0 signal reached a minimum during hippocampal sharp-wave ripples (SPW-R). Unexpectedly, memory performance was impaired in a hippocampus-dependent spontaneous alternation task by selective optogenetic stimulation of medial septal cholinergic neurons when the stimulation was applied in the delay area but not in the central (choice) arm of the maze. Parallel with the decreased performance, optogenetic stimulation decreased the incidence of SPW-Rs. These findings suggest that septo–hippocampal interactions play a task-phase–dependent dual role in the maintenance of memory performance, including not only theta mechanisms but also SPW-Rs.

The neurotransmitter acetylcholine is thought to be critical for hippocampus-dependent declarative memories (1, 2). Reduction in cholinergic neurotransmission, either in Alzheimer’s disease or in experiments with cholinergic antagonists, such as scopolamine, impairs memory function (3–8). Acetylcholine may bring about its beneficial effects on memory encoding by enhancing theta rhythm oscillations, decreasing recurrent excitation, and increasing synaptic plasticity (9–11). Conversely, drugs which activate cholinergic receptors enhance learning and, therefore, are a neuropharmacological target for the treatment of memory deficits in Alzheimer’s disease (5, 12, 13).The contribution of cholinergic mechanisms in the acquisition of long-term memories and the role of the hippocampal–entorhinal–cortical interactions are well supported by experimental data (5, 12, 13). In addition, working memory or “short-term” memory is also supported by the hippocampal–entorhinal–prefrontal cortex (14–16). Working memory in humans is postulated to be a conscious process to “keep things in mind” transiently (16). In rodents, matching to sample task, spontaneous alternation between reward locations, and the radial maze task have been suggested to function as a homolog of working memory [“working memory like” (17)].Cholinergic activity is a critical requirement for working memory (18, 19) and for sustaining theta oscillations (10, 20–22). In support of this contention, theta–gamma coupling and gamma power are significantly higher in the choice arm of the maze, compared with those in the side arms where working memory is no longer needed for correct performance (23–26). It has long been hypothesized that working memory is maintained by persistent firing of neurons, which keep the presented items in a transient store in the prefrontal cortex and hippocampal–entorhinal system (27–31), although the exact mechanisms are debated (32–37). An alternative hypothesis holds that items of working memory are stored in theta-nested gamma cycles (38). Common in these models of working memory is the need for an active, cholinergic system–dependent mechanism (39–41). However, in spontaneous alternation tasks, the animals are not moving continuously during the delay, and theta oscillations are not sustained either. During the immobility epochs, theta is replaced by intermittent sharp-wave ripples (SPW-R), yet memory performance does not deteriorate. On the contrary, artificial blockade of SPW-Rs can impair memory performance (42, 43), and prolongation of SPW-Rs improves performance (44). Under the cholinergic hypothesis of working memory, such a result is unexpected.To address the relationship between cholinergic/theta versus SPW-R mechanism in spontaneous alternation, we used a G protein–coupled receptor-activation–based acetylcholine sensor (GRAB_ACh3.0) (45) to monitor acetylcholine (ACh) activity during memory performance in mice. In addition, we optogenetically enhanced cholinergic tone, which suppresses SPW-Rs by a different mechanism than electrically or optogenetically induced silencing of neurons in the hippocampus (43, 44). We show that cholinergic signaling in the hippocampus increases in parallel with theta power/score during walking and rapid eye movement (REM) sleep and reaches a transient minimum during SPW-Rs. Selective optogenetic stimulation of medial septal cholinergic neurons decreased the incidence of SPW-Rs during non-REM sleep (46–48), as well as during the delay epoch of a working memory task and impaired memory performance. These findings demonstrate that memory performance is supported by complementary theta and SPW-R mechanisms.     

From the Cover: Phase space transport in the interaction between shocks and plasma turbulence

The interaction of collisionless shocks with fully developed plasma turbulence is numerically investigated. Hybrid kinetic simulations, where a turbulent jet is slammed against an oblique shock, are employed to address the role of upstream turbulence on plasma transport. A technique, using coarse graining of the Vlasov equation, is proposed, showing that the particle transport strongly depends on upstream turbulence properties, such as strength and coherency. These results might be relevant for the understanding of acceleration and heating processes in space plasmas.

A turbulent plasma wind flows from the sun and permeates the heliosphere, encountering several magnetic obstacles, leading to shocks that continuously interact with the incoming complex solar wind—a scenario that becomes a prototype for understanding many other systems characterized by the presence of shocks. Despite decades of research, the interaction of shocks with plasma turbulence and the subsequent energetic particle production still remain poorly understood (1, 2). Shocks are well-known efficient, natural particle accelerators (3) and have been modeled in a number of theories (4–8). Less understood is the interaction of shocks and turbulence that characterizes spectacular high-energy events, as in supernovae explosions propagating through the interstellar turbulent medium, as in the case of coronal mass ejections that stream through the turbulent solar wind, and as for the complex Earth’s bow shock environment. In many of the above examples, oblique shocks are known to generate coherent field-aligned beams (FABs), as observed at Earth’s bow shock (9). FABs are an important source of free energy throughout the interplanetary medium (10). Turbulence-generated coherent structures and waves might interact with the shock discontinuity, in an interplay that is likely to play a pivotal role in particle acceleration and plasma heating (11–13).Turbulence is populated by a variety of structures that can work effectively as particle “traps” and “corridors” that either hinder or enable their motion (14) and represents another crucial source of accelerated particles (15–18). An example of such an energization process has been observed in the patterns of local reconnection that develop in turbulence (19, 20). In order to understand such mechanisms, the transport properties need to be explored in the plasma phase space (21).Due to the difference between the spatial and temporal scales involved in accelerating particles, shocks and turbulence are often considered theoretically in isolation rather than together. However, fundamental studies have suggested that these are inextricably linked: Shocks are likely to propagate in turbulent media, and turbulence is responsible for changing fundamental aspects of shock transitions (22–27). Inspired by these studies, here we quantitatively explore the intimate relation between these two phenomena.     

Chemical mutagenesis of a GPCR ligand: Detoxifying “inflammo-attraction” to direct therapeutic stem cell migration

A transplanted stem cell’s engagement with a pathologic niche is the first step in its restoring homeostasis to that site. Inflammatory chemokines are constitutively produced in such a niche; their binding to receptors on the stem cell helps direct that cell’s “pathotropism.” Neural stem cells (NSCs), which express CXCR4, migrate to sites of CNS injury or degeneration in part because astrocytes and vasculature produce the inflammatory chemokine CXCL12. Binding of CXCL12 to CXCR4 (a G protein-coupled receptor, GPCR) triggers repair processes within the NSC. Although a tool directing NSCs to where needed has been long-sought, one would not inject this chemokine in vivo because undesirable inflammation also follows CXCL12–CXCR4 coupling. Alternatively, we chemically “mutated” CXCL12, creating a CXCR4 agonist that contained a strong pure binding motif linked to a signaling motif devoid of sequences responsible for synthetic functions. This synthetic dual-moity CXCR4 agonist not only elicited more extensive and persistent human NSC migration and distribution than did native CXCL 12, but induced no host inflammation (or other adverse effects); rather, there was predominantly reparative gene expression. When co-administered with transplanted human induced pluripotent stem cell-derived hNSCs in a mouse model of a prototypical neurodegenerative disease, the agonist enhanced migration, dissemination, and integration of donor-derived cells into the diseased cerebral cortex (including as electrophysiologically-active cortical neurons) where their secreted cross-corrective enzyme mediated a therapeutic impact unachieved by cells alone. Such a “designer” cytokine receptor-agonist peptide illustrates that treatments can be controlled and optimized by exploiting fundamental stem cell properties (e.g., “inflammo-attraction”).

A transplanted stem cell’s engagement with a pathologic niche is the first step in cell-mediated restoration of homeostasis to that region, whether by cell replacement, protection, gene delivery, milieu alteration, toxin neutralization, or remodeling (1–4). Not surprisingly, the more host terrain covered by the stem cells, the greater their impact. We and others found that a propensity for neural stem cells (NSCs) to home in vivo to acutely injured or actively degenerating central nervous system (CNS) regions—a property called “pathotropism” (1–12), now viewed as central to stem cell biology—is undergirded, at least in part, by the presence of chemokine receptors on the NSC surface, enabling them to follow concentration gradients of inflammatory cytokines constitutively elaborated by pathogenic processes and expressed by reactive astrocytes and injured vascular endothelium within the pathologic niche (5–9). This engagement of NSC receptors was first described for the prototypical chemokine receptor CXCR4 (C-X-C chemokine receptor type 4; also known as fusin or cluster of differentiation-184 [CD184]) and its unique natural cognate agonist ligand, the inflammatory chemokine CXCL12 (C-X-C motif chemokine ligand-12; also known as stromal cell-derived factor 1α [SDF-1α]) (5), but has since been described for many chemokine receptor-agonist pairings (6–9). Chemokine receptors belong to a superfamily that is characterized by seven transmembrane GDP-binding protein-coupled receptors (GPCRs) (13–21). In addition to their role in mediating inflammatory reactions and immune responses (22, 23), these receptors and their agonists are components of the regulatory axes for hematopoiesis and organogenesis in other systems (21, 24). Therefore, it is not surprising that binding of CXCL12 to CXCR4 mediates not only an inflammatory response, but also triggers within the NSC a series of intracellular processes associated with migration (as well as proliferation, differentiation, survival, and, during early brain development, proper neuronal lamination) (10).A tool directing therapeutic NSCs to where they are needed has long been sought in regenerative medicine (11, 12). While it was appealing to contemplate electively directing reparative NSCs to any desired area by emulating this chemoattractive property through the targeted injection of exogenous recombinant inflammatory cytokines, it ultimately seemed inadvisable to risk increasing toxicity in brains already characterized by excessive and usually inimical inflammation from neurotraumatic or neurodegenerative processes. However, the notion of engaging the homing function of these NSC-borne receptors without triggering that receptor’s undesirable downstream inflammatory signaling [particularly given that the NSCs themselves can exert a therapeutic antiinflammatory action in the diseased region (1, 2)] seemed a promising heretofore unexplored “workaround.”There had already been an impetus to examine the structure–function relationships of CXCR4, known to be the entry route into cells for HIV-1, in order to create CXCR4 antagonists that block viral infection (25–30). Antagonists of CXCR4 were also devised to forestall hematopoietic stem cells from homing to the bone marrow, hence prolonging their presence in the peripheral blood (31) to treat blood dyscrasias. An agonist, however, particularly one with discrete and selective actions, had not been contemplated. In other words, if CXCL12 could be stripped of its undesirable actions while preserving its tropic activity, an ideal chemoattractant would be derived.Based on the concept that CXCR4’s functions are conveyed by two distinct molecular “pockets”—one mediating binding (i.e., allowing a ligand to engage CXCR4) and the other mediating signaling (i.e., enabling a ligand, after binding, to trigger CXCR4-mediated intracellular cascades that promote not only inflammation but also migration) (13–18)—we performed chemical mutagenesis that should optimize binding while narrowing the spectrum of signaling. We created a simplified de novo peptide agonist of CXCR4 that contained a strong pure binding motif derived from CXCR4’s strongest ligand, viral macrophage inflammatory protein-II (vMIP-II) and linked it to a truncated signaling motif (only 8 amino acid residues) derived from the N terminus of native CXCL12 (19, 20). This synthetic dual-moiety CXCR4 agonist, which is devoid of a large portion of CXCL12’s native sequence (presumably responsible for undesired functions such as inflammation) not only elicited (with great specificity) more extensive and long-lasting human NSC (hNSC) migration and distribution than native CXCL12 (overcoming migratory barriers), but induced no host inflammation (or other adverse effects). Furthermore, because all of the amino acids in the binding motif were in a D-chirality, rendering the peptide resistant to enzymatic degradation, persistence of this benign synthetic agonist in vivo was prolonged. The hNSC’s gene ontology expression profile was predominantly reparative in contrast to inflammatory as promoted by native CXCL12. When coadministered with transplanted human induced pluripotent stem cell (hiPSC)-derived hNSCs (hiPSC derivatives are now known to have muted migration) in a mouse model of a prototypical neurodegenerative disease [the lethal neuropathic lysosomal storage disorder (LSD) Sandhoff disease (29), where hiPSC-hNSC migration is particularly limited], the synthetic agonist enhanced migration, dissemination, and integration of donor-derived cells into the diseased cortex (including as electrophysiologically active cortical neurons), where their secreted cross-corrective enzyme could mediate a histological and functional therapeutic impact in a manner unachieved by transplanting hiPSC-derived cells alone.In introducing such a “designer” cytokine receptor agonist, we hope to offer proof-of-concept that stem cell-mediated treatments can be controlled and optimized by exploiting fundamental stem cell properties (e.g., “inflammo-attraction”) to alter a niche and augment specific actions. Additionally, when agonists are strategically designed, the various functions of chemokine receptors (and likely other GCPRs) may be divorced. We demonstrate that such a strategy might be used safely and effectively to direct cells to needed regions and broaden their chimerism. We discuss the future implications and uses within the life sciences of such a chemical engineering approach.