Drosophila sechellia: A Genetic Model for Behavioral Evolution and Neuroecology.

Defining the mechanisms by which animals adapt to their ecological niche is an important problem bridging evolution, genetics, and neurobiology. We review the establishment of a powerful genetic model for comparative behavioral analysis and neuroecology, Drosophila sechellia. This island-endemic fly species is closely related to several cosmopolitan generalists, including Drosophila melanogaster, but has evolved extreme specialism, feeding and reproducing exclusively on the noni fruit of the tropical shrub Morinda citrifolia. We first describe the development and use of genetic approaches to facilitate genotype/phenotype associations in these drosophilids. Next, we survey the behavioral, physiological, and morphological adaptations of D. sechellia throughout its life cycle and outline our current understanding of the genetic and cellular basis of these traits. Finally, we discuss the principles this knowledge begins to establish in the context of host specialization, speciation, and the neurobiology of behavioral evolution and consider open questions and challenges in the field.

Genetic mechanisms of animal camouflage: an interdisciplinary perspective.

Camouflage is a classic example of a trait wherein animals respond to natural selection to avoid predation or attract prey. This unique phenomenon has attracted significant recent attention and the rapid development of integrative research methods is facilitating advances in our understanding of the in-depth genetic mechanisms of camouflage. In this review article, we revisit camouflage definitions and strategies and then we examine the underlying mechanisms of the two most common forms of camouflage, crypsis and masquerade, that have recently been elucidated using multiple approaches. We also discuss unresolved questions related to camouflage. Ultimately, we highlight the implications of camouflage for informing various key issues in ecology and evolution.

Positive associations fuel soil biodiversity and ecological networks worldwide.

Microbial interactions are key to maintaining soil biodiversity. However, whether negative or positive associations govern the soil microbial system at a global scale remains virtually unknown, limiting our understanding of how microbes interact to support soil biodiversity and functions. Here, we explored ecological networks among multitrophic soil organisms involving bacteria, protists, fungi, and invertebrates in a global soil survey across 20 regions of the planet and found that positive associations among both pairs and triads of soil taxa governed global soil microbial networks. We further revealed that soil networks with greater levels of positive associations supported larger soil biodiversity and resulted in lower network fragility to withstand potential perturbations of species losses. Our study provides unique evidence of the widespread positive associations between soil organisms and their crucial role in maintaining the multitrophic structure of soil biodiversity worldwide.

Transient social-ecological dynamics reveal signals of decoupling in a highly disturbed Anthropocene landscape.

Understanding the transient dynamics of interlinked social-ecological systems (SES) is imperative for assessing sustainability in the Anthropocene. However, how to identify critical transitions in real-world SES remains a formidable challenge. In this study, we present an evolutionary framework to characterize these dynamics over an extended historical timeline. Our approach leverages multidecadal rates of change in socioeconomic data, paleoenvironmental, and cutting-edge sedimentary ancient DNA records from China's Yangtze River Delta, one of the most densely populated and intensively modified landscapes on Earth. Our analysis reveals two significant social-ecological transitions characterized by contrasting interactions and feedback spanning several centuries. Initially, the regional SES exhibited a loosely connected and ecologically sustainable regime. Nevertheless, starting in the 1950s, an increasingly interconnected regime emerged, ultimately resulting in the crossing of tipping points and an unprecedented acceleration in soil erosion, water eutrophication, and ecosystem degradation. Remarkably, the second transition occurring around the 2000s, featured a notable decoupling of socioeconomic development from ecoenvironmental degradation. This decoupling phenomenon signifies a more desirable reconfiguration of the regional SES, furnishing essential insights not only for the Yangtze River Basin but also for regions worldwide grappling with similar sustainability challenges. Our extensive multidecadal empirical investigation underscores the value of coevolutionary approaches in understanding and addressing social-ecological system dynamics.

Understanding stoichiometric constraints on growth using resource use efficiency imbalances.

Growth is a function of the net accrual of resources by an organism. Energy and elemental contents of organisms are dynamically linked through their uptake and allocation to biomass production, yet we lack a full understanding of how these dynamics regulate growth rate. Here, we develop a multivariate imbalance framework, the growth efficiency hypothesis, linking organismal resource contents to growth and metabolic use efficiencies, and demonstrate its effectiveness in predicting consumer growth rates under elemental and food quantity limitation. The relative proportions of carbon (%C), nitrogen (%N), phosphorus (%P), and adenosine triphosphate (%ATP) in consumers differed markedly across resource limitation treatments. Differences in their resource composition were linked to systematic changes in stoichiometric use efficiencies, which served to maintain relatively consistent relationships between elemental and ATP content in consumer tissues and optimize biomass production. Overall, these adjustments were quantitatively linked to growth, enabling highly accurate predictions of consumer growth rates.

52,000 years of woolly rhinoceros population dynamics reveal extinction mechanisms.

The extinction of the woolly rhinoceros (Coelodonta antiquitatis) at the onset of the Holocene remains an enigma, with conflicting evidence regarding its cause and spatiotemporal dynamics. This partly reflects challenges in determining demographic responses of late Quaternary megafauna to climatic and anthropogenic causal drivers with available genetic and paleontological techniques. Here, we show that elucidating mechanisms of ancient extinctions can benefit from a detailed understanding of fine-scale metapopulation dynamics, operating over many millennia. Using an abundant fossil record, ancient DNA, and high-resolution simulation models, we untangle the ecological mechanisms and causal drivers that are likely to have been integral in the decline and later extinction of the woolly rhinoceros. Our 52,000-y reconstruction of distribution-wide metapopulation dynamics supports a pathway to extinction that began long before the Holocene, when the combination of cooling temperatures and low but sustained hunting by humans trapped woolly rhinoceroses in suboptimal habitats along the southern edge of their range. Modeling indicates that this ecological trap intensified after the end of the last ice age, preventing colonization of newly formed suitable habitats, weakening stabilizing metapopulation processes, triggering the extinction of the woolly rhinoceros in the early Holocene. Our findings suggest that fragmentation and resultant metapopulation dynamics should be explicitly considered in explanations of late Quaternary megafauna extinctions, sending a clarion call to the fragility of the remaining large-bodied grazers restricted to disjunct fragments of poor-quality habitat due to anthropogenic environmental change.

Unraveling emergent network indeterminacy in complex ecosystems: A random matrix approach.

Indeterminacy of ecological networks-the unpredictability of ecosystem responses to persistent perturbations-is an emergent property of indirect effects a species has on another through interaction chains. Thus, numerous indirect pathways in large, complex ecological communities could make forecasting the long-term outcomes of environmental changes challenging. However, a comprehensive understanding of ecological structures causing indeterminacy has not yet been reached. Here, using random matrix theory (RMT), we provide mathematical criteria determining whether network indeterminacy emerges across various ecological communities. Our analytical and simulation results show that indeterminacy intricately depends on the characteristics of species interaction. Specifically, contrary to conventional wisdom, network indeterminacy is unlikely to emerge in large competitive and mutualistic communities, while it is a common feature in top-down regulated food webs. Furthermore, we found that predictable and unpredictable perturbations can coexist in the same community and that indeterminate responses to environmental changes arise more frequently in networks where predator-prey relationships predominate than competitive and mutualistic ones. These findings highlight the importance of elucidating direct species relationships and analyzing them with an RMT perspective on two fronts: It aids in 1) determining whether the network's responses to environmental changes are ultimately indeterminate and 2) identifying the types of perturbations causing less predictable outcomes in a complex ecosystem. In addition, our framework should apply to the inverse problem of network identification, i.e., determining whether observed responses to sustained perturbations can reconstruct their proximate causalities, potentially impacting other fields such as microbial and medical sciences.

Forest mosaics, not savanna corridors, dominated in Southeast Asia during the Last Glacial Maximum.

The dominant paradigm is that large tracts of Southeast Asia's lowland rainforests were replaced with a "savanna corridor" during the cooler, more seasonal climates of the Last Glacial Maximum (LGM) (23,000 to 19,000 y ago). This interpretation has implications for understanding the resilience of Asia's tropical forests to projected climate change, implying a vulnerability to "savannization". A savanna corridor is also an important foundation for archaeological interpretations of how humans moved through and settled insular Southeast Asia and Australia. Yet an up-to-date, multiproxy, and empirical examination of the palaeoecological evidence for this corridor is lacking. We conducted qualitative and statistical analyses of 59 palaeoecological records across Southeast Asia to test the evidence for LGM savannization and clarify the relationships between methods, biogeography, and ecological change in the region from the start of Late Glacial Period (119,000 y ago) to the present. The pollen records typically show montane forest persistence during the LGM, while δ13C biomarker proxies indicate the expansion of C4-rich grasslands. We reconcile this discrepancy by hypothesizing the expansion of montane forest in the uplands and replacement of rainforest with seasonally dry tropical forest in the lowlands. We also find that smooth forest transitions between 34,000 and 2,000 y ago point to the capacity of Southeast Asia's ecosystems both to resist and recover from climate stressors, suggesting resilience to savannization. Finally, the timing of ecological change observed in our combined datasets indicates an 'early' onset of the LGM in Southeast Asia from ~30,000 y ago.

Ancient trees are essential elements for high-mountain forest conservation: Linking the longevity of trees to their ecological function.

Mature forests and their extremely old trees are rare and threatened ancient vestiges in remote European high-mountain regions. Here, we analyze the role that extremely long-living trees have in mature forests biodiversity in relation to their singular traits underlying longevity. Tree size and age determine relative growth rates, bud abortion, and the water status of long-living trees. The oldest trees suffer indefectible age-related constraints but possess singular evolutionary traits defined by fitness adaptation, modular autonomy, and a resilient metabolism that allow them to have irreplaceable roles in the ecosystem as biodiversity anchors of vulnerable lichen species like Letharia vulpina. We suggest that the role of ancient trees as unique biodiversity reservoirs is linked to their singular physiological traits associated with longevity. The set of evolutionarily plastic tools that can only be provided by centuries or millennia of longevity helps the oldest trees of mature forests drive singular ecological relationships that are irreplaceable and necessary for ecosystem dynamics.

Chaotic turnover of rare and abundant species in a strongly interacting model community.

The composition of ecological communities varies not only between different locations but also in time. Understanding the fundamental processes that drive species toward rarity or abundance is crucial to assessing ecosystem resilience and adaptation to changing environmental conditions. In plankton communities in particular, large temporal fluctuations in species abundances have been associated with chaotic dynamics. On the other hand, microbial diversity is overwhelmingly sustained by a "rare biosphere" of species with very low abundances. We consider here the possibility that interactions within a species-rich community can relate both phenomena. We use a Lotka-Volterra model with weak immigration and strong, disordered, and mostly competitive interactions between hundreds of species to bridge single-species temporal fluctuations and abundance distribution patterns. We highlight a generic chaotic regime where a few species at a time achieve dominance but are continuously overturned by the invasion of formerly rare species. We derive a focal-species model that captures the intermittent boom-and-bust dynamics that every species undergoes. Although species cannot be treated as effectively uncorrelated in their abundances, the community's effect on a focal species can nonetheless be described by a time-correlated noise characterized by a few effective parameters that can be estimated from time series. The model predicts a nonunitary exponent of the power-law abundance decay, which varies weakly with ecological parameters, consistent with observation in marine protist communities. The chaotic turnover regime is thus poised to capture relevant ecological features of species-rich microbial communities.

Social-ecological vulnerability and risk of China's marine capture fisheries to climate change.

Climate change is a new disrupter to global fisheries systems and their governance frameworks. It poses a pressing management challenge, particularly in China, which is renowned as the world's largest fishing country and seafood producer. As climate change continues to intensify in the region and climate awareness grows within the country's national policy, the need to understand China's fisheries' resilience to the escalating climate crisis becomes paramount. In this study, we conduct an interdisciplinary analysis to assess the vulnerability and risk of China's marine capture fisheries in response to climate change. This study employs a spatially explicit, indicator-based approach with a coupled social-ecological framework, focusing on 67 species and 11 coastal regions. By integrating diverse sets of climatic, ecological, economic, societal, and governance indicators and information, we elucidate the factors that could hinder climate adaptation, including a limited understanding of fish early life stages, uncertainty in seafood production, unequal allocation and accessibility of resources, and inadequate consideration of inclusive governance and adaptive management. Our results show that species, which have managed to survive the stress of overfishing, demonstrate a remarkable ability to adapt to climate change. However, collapsing stocks such as large yellow croaker face a high risk due to the synergistic effects of inherent biological traits and external management interventions. We emphasize the imperative to build institutional, scientific, and social capacity to support fisheries adaptation. The scientific insights provided by this study can inform fisheries management decisions and promote the operationalization of climate-resilient fisheries in China and other regions.

Space wandering in the rodent default mode network.

The default mode network (DMN) is a large-scale brain network known to be suppressed during a wide range of cognitive tasks. However, our comprehension of its role in naturalistic and unconstrained behaviors has remained elusive because most research on the DMN has been conducted within the restrictive confines of MRI scanners. Here, we use multisite GCaMP (a genetically encoded calcium indicator) fiber photometry with simultaneous videography to probe DMN function in awake, freely exploring rats. We examined neural dynamics in three core DMN nodes-the retrosplenial cortex, cingulate cortex, and prelimbic cortex-as well as the anterior insula node of the salience network, and their association with the rats' spatial exploration behaviors. We found that DMN nodes displayed a hierarchical functional organization during spatial exploration, characterized by stronger coupling with each other than with the anterior insula. Crucially, these DMN nodes encoded the kinematics of spatial exploration, including linear and angular velocity. Additionally, we identified latent brain states that encoded distinct patterns of time-varying exploration behaviors and found that higher linear velocity was associated with enhanced DMN activity, heightened synchronization among DMN nodes, and increased anticorrelation between the DMN and anterior insula. Our findings highlight the involvement of the DMN in collectively and dynamically encoding spatial exploration in a real-world setting. Our findings challenge the notion that the DMN is primarily a "task-negative" network disengaged from the external world. By illuminating the DMN's role in naturalistic behaviors, our study underscores the importance of investigating brain network function in ecologically valid contexts.

Mapping the timescale of suicidal thinking.

This study aims to identify the timescale of suicidal thinking, leveraging real-time monitoring data and a number of different analytic approaches. Participants were 105 adults with past week suicidal thoughts who completed a 42-d real-time monitoring study (total number of observations = 20,255). Participants completed two forms of real-time assessments: traditional real-time assessments (spaced hours apart each day) and high-frequency assessments (spaced 10 min apart over 1 h). We found that suicidal thinking changes rapidly. Both descriptive statistics and Markov-switching models indicated that elevated states of suicidal thinking lasted on average 1 to 3 h. Individuals exhibited heterogeneity in how often and for how long they reported elevated suicidal thinking, and our analyses suggest that different aspects of suicidal thinking operated on different timescales. Continuous-time autoregressive models suggest that current suicidal intent is predictive of future intent levels for 2 to 3 h, while current suicidal desire is predictive of future suicidal desire levels for 20 h. Multiple models found that elevated suicidal intent has on average shorter duration than elevated suicidal desire. Finally, inferences about the within-person dynamics of suicidal thinking on the basis of statistical modeling were shown to depend on the frequency at which data was sampled. For example, traditional real-time assessments estimated the duration of severe suicidal states of suicidal desire as 9.5 h, whereas the high-frequency assessments shifted the estimated duration to 1.4 h.

Species coexistence by wide constant size spacing.

We consider the distribution of fruit pigeons of the genera Ptilinopus and Ducula on the island of New Guinea. Of the 21 species, between six and eight coexist inside humid lowland forests. We conducted or analyzed 31 surveys at 16 different sites, resurveying some sites in different years. The species coexisting at any single site in a single year are a highly nonrandom selection of the species to which that site is geographically accessible. Their sizes are both much more widely spread and more uniformly spaced than in random sets of species drawn from the locally available species pool. We also present a detailed case study of a highly mobile species that has been recorded on every ornithologically explored island in the West Papuan island group west of New Guinea. That species' rareness on just three well-surveyed islands within the group cannot be due to an inability to reach them. Instead, its local status decreases from abundant resident to rare vagrant in parallel with increasing weight proximity of the other resident species.

Intentional release of native species undermines ecological stability.

The massive release of captive-bred native species ("intentional release") is a pervasive method to enhance wild populations of commercial and recreational species. However, such external inputs may disrupt the sensitive species interactions that allow competing species to coexist, potentially compromising long-term community stability. Here, we use theory and long-term data of stream fish communities to show that intentional release destabilizes community dynamics with limited demographic benefit to the enhanced species. Our theory predicted that intentional release intensifies interspecific competition, facilitating the competitive exclusion of unenhanced species that otherwise stably coexist. In parallel, the excessive input of captive-bred individuals suppressed the natural recruitment of the enhanced species via intensified within-species competition. Consequently, the ecological community with the intentional release is predicted to show reduced community density with unstable temporal dynamics. Consistent with this prediction, stream fish communities showed greater temporal fluctuations and fewer taxonomic richness in rivers with the intensive release of hatchery salmon-a major fishery resource worldwide. Our findings alarm that the current overreliance on intentional release may accelerate global biodiversity loss with undesired consequences for the provisioning of ecosystem services.

Range-wide differential adaptation and genomic offset in critically endangered Asian rosewoods.

In the billion-dollar global illegal wildlife trade, rosewoods have been the world's most trafficked wild product since 2005. Dalbergia cochinchinensis and Dalbergia oliveri are the most sought-after rosewoods in the Greater Mekong Subregion. They are exposed to significant genetic risks and the lack of knowledge on their adaptability limits the effectiveness of conservation efforts. Here, we present genome assemblies and range-wide genomic scans of adaptive variation, together with predictions of genomic offset to climate change. Adaptive genomic variation was differentially associated with temperature and precipitation-related variables between the species, although their natural ranges overlap. The findings are consistent with differences in pioneering ability and in drought tolerance. We predict their genomic offsets will increase over time and with increasing carbon emission pathway but at a faster pace in D. cochinchinensis than in D. oliveri. These results and the distinct gene-environment association in the eastern coastal edge of Vietnam suggest species-specific conservation actions: germplasm representation across the range in D. cochinchinensis and focused on hotspots of genomic offset in D. oliveri. We translated our genomic models into a seed source matching application, seedeR, to rapidly inform restoration efforts. Our ecological genomic research uncovering contrasting selection forces acting in sympatric rosewoods is of relevance to conserving tropical trees globally and combating risks from climate change.

Rapid monitoring of ecological persistence.

Effective conservation of ecological communities requires accurate and up-to-date information about whether species are persisting or declining to extinction. The persistence of an ecological community is supported by its underlying network of species interactions. While the persistence of the network supporting the whole community is the most relevant scale for conservation, in practice, only small subsets of these networks can be monitored. There is therefore an urgent need to establish links between the small snapshots of data conservationists can collect, and the "big picture" conclusions about ecosystem health demanded by policymakers, scientists, and societies. Here, we show that the persistence of small subnetworks (motifs) in isolation-that is, their persistence when considered separately from the larger network of which they are a part-is a reliable probabilistic indicator of the persistence of the network as a whole. Our methods show that it is easier to detect if an ecological community is not persistent than if it is persistent, allowing for rapid detection of extinction risk in endangered systems. Our results also justify the common practice of predicting ecological persistence from incomplete surveys by simulating the population dynamics of sampled subnetworks. Empirically, we show that our theoretical predictions are supported by data on invaded networks in restored and unrestored areas, even in the presence of environmental variability. Our work suggests that coordinated action to aggregate information from incomplete sampling can provide a means to rapidly assess the persistence of entire ecological networks and the expected success of restoration strategies.

Scattered differentiation of unlinked loci across the genome underlines ecological divergence of the selfing grass Brachypodium stacei.

Ecological divergence without geographic isolation, as an early speciation process that may lead finally to reproductive isolation through natural selection, remains a captivating topic in evolutionary biology. However, the pattern of genetic divergence underlying this process across the genome may vary between species and mating systems. Here, we present evidence that Brachypodium stacei, an annual and highly selfing grass model species, has undergone sympatric ecological divergence without geographic isolation. Genomic, transcriptomic, and metabolomic analyses together with lab experiments mimicking the two opposite environmental conditions suggest that diploid B. stacei populations have diverged sympatrically in two slopes characterized by distinct biomes at Evolution Canyon I (ECI), Mount Carmel, Israel. Despite ongoing gene flow, primarily facilitated by seed dispersal, the level of gene flow has progressively decreased over time. This local adaptation involves the scattered divergence of many unlinked loci across the total genome that include both coding genes and noncoding regions. Additionally, we have identified significant differential expressions of genes related to the ABA signaling pathway and contrasting metabolome composition between the arid- vs. forest-adapted B. stacei populations in ECI. These results suggest that multiple small loci involved in environmental responses act additively to account for ecological adaptations by this selfing species in contrasting environments.

Unraveling complex causal processes that affect sustainability requires more integration between empirical and modeling approaches.

Scientists seek to understand the causal processes that generate sustainability problems and determine effective solutions. Yet, causal inquiry in nature-society systems is hampered by conceptual and methodological challenges that arise from nature-society interdependencies and the complex dynamics they create. Here, we demonstrate how sustainability scientists can address these challenges and make more robust causal claims through better integration between empirical analyses and process- or agent-based modeling. To illustrate how these different epistemological traditions can be integrated, we present four studies of air pollution regulation, natural resource management, and the spread of COVID-19. The studies show how integration can improve empirical estimates of causal effects, inform future research designs and data collection, enhance understanding of the complex dynamics that underlie observed temporal patterns, and elucidate causal mechanisms and the contexts in which they operate. These advances in causal understanding can help sustainability scientists develop better theories of phenomena where social and ecological processes are dynamically intertwined and prior causal knowledge and data are limited. The improved causal understanding also enhances governance by helping scientists and practitioners choose among potential interventions, decide when and how the timing of an intervention matters, and anticipate unexpected outcomes. Methodological integration, however, requires skills and efforts of all involved to learn how members of the respective other tradition think and analyze nature-society systems.

Reduced fire severity offers near-term buffer to climate-driven declines in conifer resilience across the western United States.

Increasing fire severity and warmer, drier postfire conditions are making forests in the western United States (West) vulnerable to ecological transformation. Yet, the relative importance of and interactions between these drivers of forest change remain unresolved, particularly over upcoming decades. Here, we assess how the interactive impacts of changing climate and wildfire activity influenced conifer regeneration after 334 wildfires, using a dataset of postfire conifer regeneration from 10,230 field plots. Our findings highlight declining regeneration capacity across the West over the past four decades for the eight dominant conifer species studied. Postfire regeneration is sensitive to high-severity fire, which limits seed availability, and postfire climate, which influences seedling establishment. In the near-term, projected differences in recruitment probability between low- and high-severity fire scenarios were larger than projected climate change impacts for most species, suggesting that reductions in fire severity, and resultant impacts on seed availability, could partially offset expected climate-driven declines in postfire regeneration. Across 40 to 42% of the study area, we project postfire conifer regeneration to be likely following low-severity but not high-severity fire under future climate scenarios (2031 to 2050). However, increasingly warm, dry climate conditions are projected to eventually outweigh the influence of fire severity and seed availability. The percent of the study area considered unlikely to experience conifer regeneration, regardless of fire severity, increased from 5% in 1981 to 2000 to 26 to 31% by mid-century, highlighting a limited time window over which management actions that reduce fire severity may effectively support postfire conifer regeneration.