What drives the emergence of new species has fascinated biologists since Darwin. Reproductive barriers to gene flow are a key step in the formation of species, and recent advances have shed new light on how these are established. Genetic, genomic, and comparative techniques, together with improved theoretical frameworks, are increasing our understanding of the underlying mechanisms. They are also helping us forecast speciation and reveal the impact of human activity.

The Asia-Pacific Region (APR) encompasses a vast geographical area rich in marine biodiversity that plays critical roles in global ecological stability and climate regulation, but it also faces daunting challenges in maintaining these roles under global change. Environmental dynamics in the APR manifest regularly over a range of timescales, including storms, earthquakes, floods, and extreme heat events. Further, coastal and marine ecosystems, including extensive commercial fisheries and coral reefs, are under threat from intense resource extraction and increasingly frequent marine heatwaves. Knowledge gaps for understanding these complex systems are aggravated by substantial barriers to cross-national efforts caused by the region’s vast diversity of cultures, languages, socioeconomics, politics, and management practices. Effective management of marine resources in the APR will necessitate multidisciplinary research based on continuous, region-wide observations supported by robust collaborations. In 2023, we gathered APR researchers across disciplines to discuss these issues and find solutions during a thematic seminar and workshop program at Tohoku University in Japan. Based on the results of this program, we present a review of the current state of APR marine ecosystems, raise key questions addressable through multidisciplinary approaches, and identify future priorities for the region. We conclude that sustaining biodiversity, ecosystem functions, and climate resilience in the APR will depend on stronger interdisciplinary collaboration, better integration of biological and geophysical data, and broader access to marine observations. These efforts are both urgent and essential for supporting better science-based policy decisions to address the escalating effects of global change on marine systems across the region.

Challenges in managing multi-hazards and multi-risks within complex risk landscapes—where numerous stakeholders with different priority needs and risk perceptions interact—remain unresolved. Here we suggest ways to tackle these pressing challenges in an integrated and comprehensive manner by applying key concepts from systemic risk research to triple- and multiple-dividend approaches. The central idea is that additional dividends (i.e., economic, social, and environmental co-benefits of disaster-risk reduction that go beyond loss-reduction benefits) can be related to different system boundaries (e.g., individual systems and system of systems) through their interdependencies. This approach allows for an integrated evaluation of interventions that may be more beneficial across various scales and for corresponding threats, thus increasing synergies (or co-benefits) and decreasing asynergies (or trade-offs) of disaster-risk reduction in a systemic way. Importantly, triple and multiple dividends, along with their related tools and approaches, can be seen as part of a ‘dividend continuum’, reflecting the varying levels of interdependencies across spatial and temporal scales within complex risk landscapes. As a consequence, dividends within and across systems can be managed simultaneously, based on determining priority needs, risk perceptions, and trade-offs involved in building resilience against current and future risks.

China ranks as the first fishery nation globally in terms of its fishery production, with a total production of more than 67 million metric tons in 2022. More than 16 million people work in and earn their livelihoods from fisheries, directly or indirectly. A better understanding of the characteristics of this large group of people could lead to an improved appreciation of the human dimensions of China's fisheries. In this study, we analyze longitudinal social-survey data from 1989 to 2015 to derive several key indicators representing the socio-economic status of China's fishery population. We find that, first, the size of the fishery population is shrinking. Second, the average age of the fishery population is increasing but at a slower rate than in the total population. Third, the education levels of the fishery population are rising but remain below those of urban residents. Fourth, the incomes of the fishery population have grown considerably, albeit more slowly than those of the general rural population and the urban population. Fifth, the employment of the fishery population is exhibiting a high degree of dynamism, with high rates of occupational mobility between the fishing sector and other sectors.

The growing global demand for seafood and concerns about overfishing have spurred the rapid expansion of aquaculture. In aquaculture, managing diseases and parasites presents a critical problem, with drug-based solutions being increasingly challenged by the evolution of drug resistance. In this study, we focus on managing salmon louse in the context of open-cage salmon mariculture with potential for the evolution of drug resistance. We devise a model combining parasite dynamics and fish dynamics in a system of fish farms connected to each other by dispersive stages of the parasite and then evaluate the system-wide economic performance of different management strategies involving three parasite-control measures: drug treatment (administering medicine through fish feed), mechanical treatment (pumping fish through a system of water jets and/or soft brushes), and depopulation (emptying a whole farm prematurely). Drug treatment controls drug-sensitive lice at low cost but becomes ineffective in the presence of drug-resistant lice. Mechanical treatment can clear both types of lice but at the cost of diminished fish growth and additional fish mortality. Depopulation removes both the fish and the parasites within the farm but results in prematurely harvested fish that fetch a lower price. Our results suggest that even when the drug is used only once per production cycle and mechanical treatment and depopulation provide the main control of the parasite, the spread of drug resistance is unavoidable in an open-cage system. Furthermore, it is often not economically optimal to drive resistance to the lowest possible level by minimizing drug use: because resistant lice are assumed to have a slightly reduced fecundity, slightly fewer non-drug treatments are needed for controlling drug-resistant parasites than drug-sensitive parasites. Building on these insights, our model predicts that economically optimal parasite management in the presence of drug resistance combines all three parasite-control measures: mechanical treatment is the main measure to reduce louse infestations, depopulation allows shorter production cycles that become optimal under reduced salmon growth and survival that result from frequent mechanical treatments, and the drug is used not only to provide some parasite control but also to keep the resistant parasites prevalent. Our results thus underscore the need for effective parasite management strategies in salmon aquaculture accounting for the unavoidable prevalence of drug resistance. Notably, the economically optimal approach does not involve combating resistance but rather adapting to it and capitalizing on its positive effects.

We investigate a nonlinear integral equation derived through moment approximation from the individual-based representation of spatial logistic dynamics. The equation describes how the densities of pairs of individuals represented by points in continuous space are expected to equilibrate under spatially explicit birth–death processes characterized by constant fecundity with local natal dispersal and variable mortality determined by local competition. The equation is derived from a moment hierarchy truncated by a moment closure expressing the densities of triplets as a function of the densities of pairs. Focusing on results for individuals inhabiting two-dimensional habitats, we explore the solvability of the equation by introducing a dedicated space of functions that are integrable up to a constant. Using this function space, we establish sufficient conditions for the existence of solutions of the equation within a zero-centered ball. For illustration and further insights, we complement our analytical findings with numerical results.

Cope’s rule posits that evolution gradually increases the body size in lineages. Over the last decades, two schools of thought have fueled a debate on the applicability of Cope’s rule by reporting empirical evidence, respectively, for and against Cope’s rule. The apparent contradictions thus documented highlight the need for a comprehensive process-based synthesis through which both positions of this debate can be understood and reconciled. Here, we use a process-based community-evolution model to investigate the eco-evolutionary emergence of Cope’s rule. We report three characteristic macroevolutionary patterns, of which only two are consistent with Cope’s rule. First, we find that Cope’s rule applies when species interactions solely depend on relative differences in body size and the risk of lineage extinction is low. Second, in environments with higher risk of lineage extinction, the recurrent evolutionary elimination of top predators induces cyclic evolution toward larger body sizes, according to a macroevolutionary pattern we call the recurrent Cope’s rule. Third, when interactions between species are determined not only by their body sizes but also by their ecological niches, the recurrent Cope’s rule may get inverted, leading to cyclic evolution toward smaller body sizes. This recurrent inverse Cope’s rule is characterized by highly dynamic community evolution, involving the diversification of species with large body sizes and the extinction of species with small body sizes. To our knowledge, these results provide the first theoretical foundation for reconciling the contrasting empirical evidence reported on body-size evolution.

The epidemiology and evolution of diseases unfold in populations that are rarely homogeneous. Instead, hosts infected by pathogens often form metapopulations, in which local populations connected by the movement of hosts experience different demographic and epidemiological conditions. Here, we develop a general theory of the evolution of pathogens in heterogeneous metapopulations. We reveal the following key insights into the evolution of pathogen virulence and infectiousness: (1) When the mobility (movement rate), productivity (birth rate and carrying capacity), or immunocompetency (immunity- loss rate) differ among local populations, this variance always increases pathogen virulence and infectiousness (2) The increment of pathogen virulence caused by such heterogeneity is approximately proportional to the variance of the corresponding heterogeneous local conditions (3) This increment can be expressed as the covariance between the local selection pressures and the local reproductive values experienced by the pathogen (4) The reason why heterogeneity always increases pathogen virulence is explained by the positive correlation of local selection pressures with reproductive values (5) Combinations of multiple independent heterogeneities further increase virulence and infectiousness, even more so when their covariances are positive. Our key findings robustly hold for different epidemiological frameworks - including SI, SIS, SIR, and SIRS models, with both density- and frequency- dependent transmission as well as with superinfection. They provide insights into the risks of growing pathogen infectiousness in a world in which heterogeneity - caused, e.g., by the concentration of human populations in urban areas - is rising.

Increasing interconnectedness, along with the effects of climate change and other global risk drivers, has led to mounting systemic risks in the complex systems that characterize our world. Systemic risks, with their cascading impacts and long-term sustainability concerns, necessitate transformative approaches to manage their effects across system scales and dimensions. To date, however, an “operationalization gap” impedes translating between propositions for transformative change and policy options for addressing systemic risk. Here, we propose combining systemic risk analyses with local approaches, prominently including knowledge co-production, to achieve a more comprehensive understanding of complex systems. This combined approach can support stakeholders in designing transformative risk management and adaptation interventions that balance individual and higher-order interactions, incorporate diverse viewpoints, and thus manage systemic risks and leverage transformation potential more effectively. Furthermore, we suggest that a risk-layering approach can help differentiate, prioritize, and orchestrate these options for incremental and transformative changes.

A nonlinear integral equation arising from a parametric closure of the third spatial moment in the single-species model of logistic dynamics of U. Dieckmann and R. Law is analyzed. The case of piecewise constant kernels is studied, which is important for further computer modeling. Sufficient conditions are found that guarantee the existence of a nontrivial solution to the equilibrium equation. The use of constant kernels makes it possible to obtain more accurate results compared to earlier works, in particular, more accurate estimates for the L 1 norm of the solution and for the closure parameter are obtained.

For a vast majority of organisms, life-history processes depend on their physiological state, such as body size, as well as on their environment. Size-structured population models, or more generally, physiologically structured population models (PSPMs), have emerged as powerful tools for modelling the population dynamics of organisms, as they account for the dependences of growth, mortality, and fecundity rates on an organism’s physiological state and capture feedbacks between a population’s structure and its environment, including all types of density regulation. However, despite their widespread appeal across biological disciplines, few numerical packages exist for solving PSPMs in an accessible and computationally efficient way. The main reason for this is that PSPMs typically involve solving partial differential equations (PDEs), and no single numerical method works universally best, or even at all, for all PDEs. Here, we present libpspm, a general-purpose numerical library for solving user-defined PSPMs. libpspm provides eight different methods for solving the PDEs underlying PSPMs, including four semi-implicit solvers that can be used for solving stiff problems. Users can choose the desired method without changing the code specifying the PSPM. libpspm allows for predicting the dynamics of multiple physiologically structured or unstructured species, each of which can have its own distinct set of physiological states and demographic functions. By separating model definition from model solution, libpspm can make PSPM-based modelling accessible to non-specialists and thus promote the widespread adoption of PSPMs.

<p>Climate change is projected to cause not only higher mean temperatures but also higher climate variability. Although elevated CO2 concentrations can potentially increase the productivity of some ecosystems, higher temperatures and more frequent droughts may lead to increased respiration and mortality, possibly negating these productivity gains. The capacity of global forests to adjust to climate change depends on their functional diversity and the ecosystem’s adaptive capacity.</p><p>The Plant-FATE eco-evolutionary model describes vegetation responses to altered environmental conditions, including CO<sub>2</sub> concentrations, temperatures, and droughts. It represents functional diversity by modelling species as points in trait space and incorporates ecosystem adaptations at three levels: 1) to model acclimation of plastic traits of individual plants, we leverage the power of eco-evolutionary optimality principles, 2) to model shifts in species composition via demographic changes and species immigration, we implement a trait-size-structured demographic vegetation model, and 3) to model the long-term genetic evolution of species, we have developed new evolutionary theory for trait-size-structured communities.</p><p>First, we show that with just a few calibrated parameters, the Plant-FATE model accurately predicts the fluxes of CO2 and water, size distributions, and trait distributions for a tropical wet site in the Amazon Forest. Second, we show that under elevated CO2 conditions and in the absence of nutrient limitation, our model predictions are broadly consistent with observations, namely: an increase in leaf area, productivity and biomass, and a decrease in stomatal conductance and photosynthetic capacity. Third, we simulate the calibrated model with hypothetical future drought regimes to investigate three key features of ecosystem responses: 1) the change in species composition and ecosystem functioning in response to altered conditions, 2) the timescales of ecosystem response to new regimes, 3) the influence of functional diversity on the timescale of ecosystem adaptation and its consequences for ecosystem collapse.</p><p>Our eco-evolutionary vegetation modelling strategy presents a powerful approach to leverage the power of natural selection to simulate ecosystem dynamics under novel conditions that plants may have never experienced before.</p>

Abstract. Abrupt changes in ocean biogeochemical variables occur as a result of human-induced climate forcing as well as those which are more gradual and occur over longer timescales. These abrupt changes have not yet been identified and quantified to the same extent as the more gradual ones. We review and synthesise abrupt changes in ocean biogeochemistry under human-induced climatic forcing. We specifically address the ocean carbon and oxygen cycles because the related processes of acidification and deoxygenation provide important ecosystem hazards. Since biogeochemical cycles depend also on the physical environment, we also describe the relevant changes in warming, circulation, and sea ice. We include an overview of the reversibility or irreversibility of abrupt marine biogeochemical changes. Important implications of abrupt biogeochemical changes for ecosystems are also discussed. We conclude that there is evidence for increasing occurrence and extent of abrupt changes in ocean biogeochemistry as a consequence of rising greenhouse gas emissions.

Recent research has shown that adverse risks associated with climate and global change are becoming increasingly systemic with mounting interdependencies that will likely lead to cascading impacts. These impacts are projected to become so intolerable that standard risk management approaches alone will no longer be sufficient. Calls to consider transformational approaches to risk management and adaptation to facilitate a change towards more resilient futures are growing steadily louder. There is, however, a clear gap in terms of translating ambitions for transformational change into interventions and measures that can be directly applied in practice. To bridge this gap and help move forward with operationalising transformation in this context, we suggest harnessing ideas and insights from systemic risk research. Understanding systemic risk usually requires a careful examination of a system's components, leading to a better appreciation of how they and their interactions within a system contribute to systemic risks. Restructuring the connectivity of system elements based on this information represents a transformational change of the system and can lead to a reduction in systemic risk. From this perspective, systemic risk research and transformative risk management are closely connected disciplines, as methodological insights from the field of systemic risk research can benefit the objective of shifting climate risk management interventions towards transformative approaches that facilitate a radical and fundamental change towards more resilient futures The pluralistic views of decision-makers regarding system boundaries and responsibilities can, however, result in forced transformation. An applied systems view can avoid this and guide deliberate transformation coupled with iterative approaches that are able to track the status of such changes and steer developments in the desired direction.

Sexual size dimorphism (SSD) is caused by differences in selection pressures and life-history trade-offs faced by males and females. Proximate causes of SSD may involve sex-specific mortality, energy acquisition, and energy expenditure for maintenance, reproductive tissues, and reproductive behavior. Using a quantitative, individual-based, eco-genetic model parameterized for North Sea plaice, we explore the importance of these mechanisms for female-biased SSD, under which males are smaller and reach sexual maturity earlier than females (common among fish, but also arising in arthropods and mammals). We consider two mechanisms potentially serving as ultimate causes: (a) Male investments in male reproductive behavior might evolve to detract energy resources that would otherwise be available for somatic growth, and (b) diminishing returns on male reproductive investments might evolve to reduce energy acquisition. In general, both of these can bring about smaller male body sizes. We report the following findings. First, higher investments in male reproductive behavior alone cannot explain the North Sea plaice SSD. This is because such higher reproductive investments require increased energy acquisition, which would cause a delay in maturation, leading to male-biased SSD contrary to observations. When accounting for the observed differential (lower) male mortality, maturation is postponed even further, leading to even larger males. Second, diminishing returns on male reproductive investments alone can qualitatively account for the North Sea plaice SSD, even though the quantitative match is imperfect. Third, both mechanisms can be reconciled with, and thus provide a mechanistic basis for, the previously advanced Ghiselin-Reiss hypothesis, according to which smaller males will evolve if their reproductive success is dominated by scramble competition for fertilizing females, as males would consequently invest more in reproduction than growth, potentially implying lower survival rates, and thus relaxing male-male competition. Fourth, a good quantitative fit with the North Sea plaice SSD is achieved by combining both mechanisms while accounting for sex-specific costs males incur during their spawning season. Fifth, evolution caused by fishing is likely to have modified the North Sea plaice SSD.

The resilience of biodiverse forests to climate change depends on an interplay of adaptive processes operating at multiple temporal and organizational scales. These include short-term acclimation of physiological processes like photosynthesis and respiration, mid-term changes in forest structure due to competition, and long-term changes in community composition arising from competitive exclusion and genetic trait evolution. To investigate the roles of diversity and adaptation for forest resilience, we present Plant-FATE, a parsimonious eco-evolutionary vegetation model. Tested with data from a hyperdiverse Amazonian terra-firme forest, our model accurately predicts multiple emergent ecosystem properties characterizing forest structure and function. Under elevated CO 2 conditions, we predict an increase in productivity, leaf area, and aboveground biomass, with the magnitude of this increase declining in nutrient-deprived soils if trees allocate more carbon to the rhizosphere to overcome nutrient limitation. Furthermore, increased aboveground productivity leads to greater competition for light and drives a shift in community composition towards fast-growing but short-lived species characterized by lower wood densities. Such a transition reduces the carbon residence time of woody biomass, dampening carbon-sink strength and potentially rendering the Amazon Forest more vulnerable to future climatic extreme events.

Plant-frugivore interactions play a central role for plant persistence and spatial distribution by promoting the long-range dispersal of seeds by frugivores. However, plant-frugivore interactions are increasingly being threatened by anthropogenic activities. An important anthropogenic threat that could expose plant-frugivore systems to extinction risk is fruit harvesting. Here, we develop an individual-based and a pair-approximation model of plant-frugivore-human interactions to elucidate the effects of human harvesting of fruits on plant establishment, persistence, and spatial distribution. Our results show that frugivores strongly affect global density of plants and gradually shift their spatial distribution from aggregated to random, depending on the attack rate and dispersal efficiency of frugivores. We find that, in the absence of frugivores, plants experiencing intense fruit harvesting cannot persist even if their fecundity is high. In the presence of frugivores, fruit harvesting profoundly affects the global dispersal of seeds and thus changes the spatial distributions of plants from random to aggregated, potentially causing plant extinction. Our results demonstrate that sufficiently efficient frugivores mitigate the negative impact of fruit harvesting on plant populations and enable plant establishment precluded by harvesting. Taken together, these results draw attention to previously underappreciated impacts of fruit harvesting in plant-frugivore-human interactions.

In this paper, we analyze a system of nonlinear integral equations resulting from the three-parameter closure of the third spatial moments in the logistic dynamics model of U. Dieckmann and R. Law in the multi-species case. Specifically, the conditions under which the solution of this system is stable with respect to the closure parameters are investigated. To do this, the initial system of equations is represented as a single operator equation in a special Banach space, after which the generalized fixed point principle is applied.

The global carbon and water cycles are governed by the coupling of CO 2 and water vapour exchanges through the leaves of terrestrial plants, controlled by plant adaptations to balance carbon gains and hydraulic risks. We introduce a trait-based optimality theory that unifies the treatment of stomatal responses and biochemical acclimation of plants to environments changing on multiple timescales. Tested with experimental data from 18 species, our model successfully predicts the simultaneous decline in carbon assimilation rate, stomatal conductance, and photosynthetic capacity during progressive soil drought. It also correctly predicts the dependencies of gas exchange on atmospheric vapour pressure deficit, temperature, and CO 2 . Model predictions are also consistent with widely observed empirical patterns, such as the distribution of hydraulic strategies. Our unified theory opens new avenues for reliably modelling the interactive effects of drying soil and rising atmospheric CO 2 on global photosynthesis and transpiration.