A standard protocol for describing individual-based and agent-based models

Agent-based simulation of COVID-19 containment measures: the case of lockdowns in cities

The effectiveness and political feasibility of COVID-19 containment measures such as lockdowns, are contentious. This stems in part from an absence of tools for their rigorous evaluation. Common epidemiological models such as the SEIR model generally lack the spatial resolution required for micro-level containment actions, the visualization capabilities for communicating measures such as localized lockdowns and the scenario-testing capabilities for assessing different alternatives. We present an individual-level ABM that generates geo-social networks animated by agent-agent and agent-building interactions. The model simulates real-world contexts and is demonstrated for the city of Jerusalem. Simulation outputs yield much useful information for evaluating the effectiveness of lockdowns. These include network-generated socio-spatial contagion chains for individual agents, dynamic building level contagion processes and neighborhood-level patterns of COVID-19 imports and exports useful in identifying super-spreader neighborhoods. The policy implications afforded by these various outputs are discussed.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s12076-023-00336-w.

In Search of Proximate Triggers of Anthrax Outbreaks in Wildlife: A Hypothetical Individual-Based Model of Plasmid Transfer within Bacillus Communities

Bacillus anthracis, the causative agent of anthrax in humans, livestock, and wildlife, exists in a community with hundreds of other species of bacteria in the environment. Work on the genetics of these communities has shown that B. anthracis shares a high percentage of chromosomal genes with both B. thuringiensis and B. cereus, and that phenotypic differences among these bacteria can result from extra-chromosomal DNA in the form of plasmids. We developed a simple hypothetical individual-based model to simulate the likelihood of detecting plasmids with genes encoding anthrax toxins within bacterial communities composed of B. anthracis, B. thuringiensis, and B. cereus, and the surrounding matrix of extra-cellular polymeric substances. Simulation results suggest the horizontal transfer of plasmids with genes encoding anthrax toxins among Bacillus species persisting outside the host could function as a proximate factor triggering anthrax outbreaks.

Estimating the potential drivers of dispersal outcomes for juvenile gopher frogs (Rana capito) using agent-based models

Among mobile terrestrial animals, movement among microsites can allow individuals to behaviorally moderate their body temperatures and rates of water loss, which can have important consequences for activity times, growth, fecundity, and survival. Ground-layer vegetation can change the availability and variability of microclimates; however, gaps in our understanding of how individuals interact with the microclimates created by vegetation limit our ability to inform management actions for wildlife. Amphibians can simultaneously balance operant body temperatures and water loss and the availability of heterogeneous microclimates should moderate how effectively they are able to do so. However, relatively few studies have attempted to mechanistically demonstrate how ground vegetation-driven effects on microclimatic variation may affect amphibian performance and survival. Agent-based modeling (ABM) can incorporate behavior and other mechanisms to understand how animals interact with their environments to result in larger scale patterns. They are effective for exploring alternative scenarios and representing the uncertainty in systems. Here, we use ABMs to integrate field and laboratory measurements of movement behavior, physiology, and plant effects on near-ground microclimate to explore how ground vegetation and the availability of terrestrial refugia may affect the survival and terrestrial distributions of juvenile gopher frogs (Rana capito) under two weather regimes. We also examine how assumptions regarding micro-scale movement (< 1 m2) affect the influence of ground vegetation on survival and settlement within refugia. While all variables affected settlement and survival, our models predict that inter-annual variation in weather and the density and spatial distribution of permanent refugia likely have the greatest influence on juvenile survival. The benefit of increased ground vegetation was dependent on the reasonable assumption that gopher frogs exhibit microclimate habitat selection throughout the day and night to limit water loss. Our models suggest that vegetation would be most beneficial to amphibians under warmer weather regimes provided there is sufficient rainfall.

Comparing Control Intervention Scenarios for Raccoon Rabies in Southern Ontario between 2015 and 2025

The largest outbreak of raccoon rabies in Canada was first reported in Hamilton, Ontario, in 2015 following a probable translocation event from the United States. We used a spatially-explicit agent-based model to evaluate the effectiveness of provincial control programs in an urban-centric outbreak if control interventions were used until 2025, 2020, or never used. Calibration tests suggested that a seroprevalence of protective rabies antibodies 2.1 times higher than that inferred from seroprevalence in program assessments was required in simulations to replicate observed raccoon rabies cases. Our simulation results showed that if control interventions with an adjusted seroprevalence were used until 2025 or 2020, the probability of rabies elimination due to control intervention use was 49.2% and 42.1%, respectively. However, if controls were never used, the probability that initial rabies cases failed to establish a sustained outbreak was only 18.2%. In simulations where rabies was not successfully eliminated, using control interventions until 2025 resulted in 67% fewer new infections compared to only applying controls until 2020 and in 90% fewer new infections compared to no control intervention use. However, the model likely underestimated rabies elimination rates since we did not adjust for adaptive control strategies in response to changes in rabies distributions and case numbers, as well as extending control interventions past 2025. Our agent-based model offers a cost-effective strategy to evaluate approaches to rabies control applications.

On the road to self-sustainability: reintroduced migratory European northern bald ibises Geronticus eremita still need management interventions for population viability

The northern bald ibis Geronticus eremita disappeared from Europe in the Middle Ages. Since 2003 a migratory population has been reintroduced in Central Europe. We conducted demographic analyses of the survival and reproduction of 384 northern bald ibises over a period of 12 years (2008–2019). These data also formed the basis for a population viability analysis simulating the possible future development of the northern bald ibis population under different scenarios. We analysed life stage-specific survival rates, rearing protocols and colonies, and the influence of stochastic catastrophic events and reinforcement translocations on population growth. Life stage-specific survival probabilities were 0.64–0.78. Forty-five per cent of the mature females reproduced, with a mean fecundity of 2.15 fledglings per nest. The complementary population viability analysis indicated that the Waldrappteam population is close to self-sustainability, with an estimated population growth rate of 0.95 and a 24% extinction probability within 50 years. Of the 326 future scenarios tested, 94% reached the criteria of extinction probabilities < 5% and population growth rates > 1. Stochastic catastrophic events had only a limited effect. Despite comparatively high survival and fecundity rates the population viability analysis indicated that to achieve self-sustainability the Waldrappteam population needs further translocations to support population growth and the implementation of effective measures against major mortality threats: illegal hunting in Italy and electrocution on unsecured power poles. The findings of this study are to be implemented as part of a second European LIFE project.

Human-mediated dispersal drives the spread of the spotted lanternfly (Lycorma delicatula)

The spotted lanternfly (Lycorma delicatula) is a novel invasive insect from Asia now established and spreading throughout the United States. This species is of particular concern given its ability to decimate important crops such as grapes, fruit trees, as well as native hardwood trees. Since its initial detection in Berks County, Pennsylvania in 2014, spotted lanternfly infestations have been detected in 130 counties (87 under quarantine) within Connecticut, Delaware, Indiana, Maryland, New Jersey, New York, Ohio, Virginia, and West Virginia. Compounding this invasion is the associated proliferation and widespread distribution of the spotted lanternfly's preferred host plant, the tree-of-heaven (Ailanthus altissima). While alternate host plant species have been observed, the tree-of-heaven which thrives in disturbed and human-dominated areas (e.g., along roads and railways) is likely facilitating the population growth rates of spotted lanternfly. We simulated the population and spread dynamics of the spotted lanternfly throughout the mid-Atlantic USA to help determine areas of risk and inform continued monitoring and control efforts. We tested the prediction that spotted lanternfly spread is driven by human-mediated dispersal using agent-based models that incorporated information on its life-history traits, habitat suitability, and movement and natural dispersal behavior. Overwhelmingly, our results suggest that human-mediated dispersal (e.g., cars, trucks, and trains) is driving the observed spread dynamics and distribution of the spotted lanternfly throughout the eastern USA. Our findings should encourage future surveys to focus on human-mediated dispersal of egg masses and adult spotted lanternflies (e.g., attachment to car or transported substrates) to better monitor and control this economically and ecologically important invasive species.

Economic benefits of conservation biocontrol: A spatially explicit bioeconomic model for insect pest management in agricultural landscapes

Spatially explicit population dynamic models have been successfully used to explore management scenarios in terms of pest suppression across a wide range of systems. However, the economic implications of pest management, particularly in the case of biological control and non-crop management strategies, have not been well considered. A bioeconomic spatially explicit simulation model was developed, that integrates models of pest population dynamics, pest movement and economics of management. The utility of the model is demonstrated here using Nysius vinitor, a pest of grain crops in Australia. The model estimates the short- and long-term economic benefits of three pest management strategies: (1) in-field pesticide spray; (2) pest suppression through weed management in non-crop habitat; and (3) bolstering biocontrol through revegetation with, or maintenance of, native vegetation. Across all management types, high yield and low relative management cost resulted in a greater chance of a gross profit. The impacts of the pests themselves were shown to be non-linear, with an intermediate level of pest pressure maximizing the economic gain from management. Pest dispersal capacity influenced the profitability of management of non-crop vegetation, with lower pest dispersal resulting in a greater likelihood of benefit, as benefits from non-crop management are localized (e.g., increased beneficial insect populations). In an intensively cropped landscape, pesticide management was most profitable over the short-term. Once a 10-year horizon was reached, then the profitability of revegetation was greater and continued to increase. While weeding requirements are low, it is likely to always be profitable in the long-term to maintain or restore native vegetation in good condition to control this pest in an intensively cropped landscape. Using pesticide alongside revegetation gave some short-term gain, but the negative impact of pesticide on beneficials outweighed the benefit and in the long-term it is less profitable. These results do not hold in a low production landscape, due to increased pest pressure and costs of managing non-crop habitat. In summary, when quantified over a 10–20 year time horizon, revegetation or conserving native remnants in good (i.e., non-weedy) condition could be economically more beneficial to control an insect pest than ongoing pesticide use, in intensively cropped landscapes.

Investigating effective testing strategies for the control of Johne's disease in western Canadian cow-calf herds using an agent-based simulation model

Johne's disease is an insidious infectious disease of ruminants caused by Mycobacterium avium subspecies paratuberculosis (MAP). Johne's disease can have important implications for animal welfare and risks causing economic losses in affected herds due to reduced productivity, premature culling and replacement, and veterinary costs. Despite the limited accuracy of diagnostic tools, testing and culling is the primary option for controlling Johne's disease in beef herds. However, evidence to inform specific test and cull strategies is lacking. In this study, a stochastic, continuous-time agent-based model was developed to investigate Johne's disease and potential control options in a typical western Canadian cow-calf herd. The objective of this study was to compare different testing and culling scenarios that included varying the testing method and frequency as well as the number and risk profile of animals targeted for testing using the model. The relative effectiveness of each testing scenario was determined by the simulated prevalence of cattle shedding MAP after a 10-year testing period. A second objective was to compare the direct testing costs of each scenario to identify least-cost options that are the most effective at reducing within-herd disease prevalence. Whole herd testing with individual PCR at frequencies of 6 or 12 months were the most effective options for reducing disease prevalence. Scenarios that were also effective at reducing prevalence but with the lowest total testing costs included testing the whole herd with individual PCR every 24 months and testing the whole herd with pooled PCR every 12 months. The most effective method with the lowest annual testing cost per unit of prevalence reduction was individual PCR on the whole herd every 24 months. Individual PCR testing only cows that had not already been tested 4 times also ranked well when considering both final estimated prevalence at 10 years and cost per unit of gain. A more in-depth economic analysis is needed to compare the cost of testing to the cost of disease, taking into account costs of culling, replacements and impacts on calf crops, and to determine if testing is an economically attractive option for commercial cow-calf operations.

Population modeling to inform management and recovery efforts for lake sturgeon, Acipenser fulvescens

Lake sturgeon (Acipenser fulvescens) populations have significantly declined across their historic range, in large part due to anthropogenic impacts that have likely been exacerbated by the life-history traits of this slow-growing and long-lived species. We developed a population model to explore how Contaminants of Emerging Concern (CECs) impact lake sturgeon populations. We explored how different physiological modes of action (pMoAs) of CECs impacted population abundance and recovery and how different simulated management actions could enable recovery. We first estimated the impacts on population abundance and recovery by comparing the trajectory of an unexposed population to a population that had been exposed to a CEC with a specific pMoA after the end of the exposure. We then predicted how different management actions would impact population recovery by comparing the trajectories of an unexposed population to an exposed population for which a management action started at a fixed time without discontinuation of the exposure. Our results predicted that the individual-level pMoA of CECs has an important impact on population-level effects because different stressor's pMoA impacts the life-history traits of sturgeon differently. For example, the feeding and reproduction pMoAs caused the strongest and weakest population declines, respectively. For the same reason, pMoA also impacted recovery. For example, recovery was delayed when the pMoA was growth, maintenance, or feeding, but it was immediate when the pMoA was reproduction. We found that management actions that increased the egg survival rate or the stocking of fingerlings resulted in faster and stronger recovery than management actions that increased the juvenile or adult survival rate. This result occurred because the first two management actions immediately impacted recruitment, whereas the impact was delayed for the last two. Finally, there was greater potential for recovery when management action targeted eggs and fingerlings because these life stages have lower natural survival rates. Integr Environ Assess Manag 2022;18:1597-1608. © 2022 Society of Environmental Toxicology & Chemistry (SETAC). This article has been contributed to by US Government employees and their work is in the public domain in the USA.

Simulation of Varroa mite control in honey bee colonies without synthetic acaricides: Demonstration of Good Beekeeping Practice for Germany in the BEEHAVE model

The BEEHAVE model simulates the population dynamics and foraging activity of a single honey bee colony (Apis mellifera) in great detail. Although it still makes numerous simplifying assumptions, it appears to capture a wide range of empirical observations. It could, therefore, in principle, also be used as a tool in beekeeper education, as it allows the implementation and comparison of different management options. Here, we focus on treatments aimed at controlling the mite Varroa destructor. However, since BEEHAVE was developed in the UK, mite treatment includes the use of a synthetic acaricide, which is not part of Good Beekeeping Practice in Germany. A practice that consists of drone brood removal from April to June, treatment with formic acid in August/September, and treatment with oxalic acid in November/December. We implemented these measures, focusing on the timing, frequency, and spacing between drone brood removals. The effect of drone brood removal and acid treatment, individually or in combination, on a mite-infested colony was examined. We quantify the efficacy of Varroa mite control as the reduction of mites in treated bee colonies compared to untreated bee colonies. We found that drone brood removal was very effective, reducing mites by 90% at the end of the first simulation year after the introduction of mites. This value was significantly higher than the 50-67% reduction expected by bee experts and confirmed by empirical studies. However, literature reports varying percent reductions in mite numbers from 10 to 85% after drone brood removal. The discrepancy between model results, empirical data, and expert estimates indicate that these three sources should be reviewed and refined, as all are based on simplifying assumptions. These results and the adaptation of BEEHAVE to the Good Beekeeping Practice are a decisive step forward for the future use of BEEHAVE in beekeeper education in Germany and anywhere where organic acids and drone brood removal are utilized.

The BEEHAVEecotox Model-Integrating a Mechanistic Effect Module into the Honeybee Colony Model

Mechanistic effect models are powerful tools for extrapolating from laboratory studies to field conditions. For bees, several good models are available that can simulate colony dynamics. Controlled and reliable experimental systems are also available to estimate the inherent toxicity of pesticides to individuals. However, there is currently no systematic and mechanistic way of linking the output of experimental ecotoxicological testing to bee models for bee risk assessment. We introduce an ecotoxicological module that mechanistically links exposure with the hazard profile of a pesticide for individual honeybees so that colony effects emerge. This mechanistic link allows the translation of results from standard laboratory studies to relevant parameters and processes for simulating bee colony dynamics. The module was integrated into the state-of-the-art honeybee model BEEHAVE. For the integration, BEEHAVE was adapted to mechanistically link the exposure and effects on different cohorts to colony dynamics. The BEEHAVEecotox model was tested against semifield (tunnel) studies, which were deemed the best study type to test whether BEEHAVEecotox predicted realistic effect sizes under controlled conditions. Two pesticides used as toxic standards were chosen for this validation to represent two different modes of action: acute mortality of foragers and chronic brood effects. The ecotoxicological module was able to predict effect sizes in the tunnel studies based on information from standard laboratory tests. In conclusion, the BEEHAVEecotox model is an excellent tool to be used for honeybee risk assessment, interpretation of field and semifield studies, and exploring the efficiency of different mitigation measures. The principles for exposure and effect modules are portable and could be used for any well-constructed honeybee model. Environ Toxicol Chem 2022;41:2870-2882. © 2022 Bayer AG & Sygenta, et al. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Evolution of physical linkage between loci controlling ecological traits and mating preferences

Coupling of multiple barriers to gene-flow, such as divergent local adaptation and reproductive isolation, facilitates speciation. However, alleles at loci that contribute to barrier effects can be dissociated by recombination. Models of linkage between diverging alleles often consider elements that reduce recombination, such as chromosomal inversions and alleles that modify recombination rate between existing loci. In contrast, here, we consider the evolution of linkage due to the close proximity of loci on the same chromosome. Examples of such physical linkage exist in several species, but in other cases, strong associations are maintained without physical linkage. We use an individual-based model to study the conditions under which the physical linkage between loci controlling ecological traits and mating preferences might be expected to evolve. We modelled a single locus controlling an ecological trait that acts also as a mating cue. Mating preferences are controlled by multiple loci, formed by mutations that are randomly placed in the "genome", within varying distances from the ecological trait locus, allowing us to examine which genomic architectures spread across the population. Our model reveals that stronger physical linkage is favoured when mating preferences and selection are weaker. Under such conditions mating among divergent phenotypes is more frequent, and matching ecological trait and mating preference alleles are more likely to become dissociated by recombination, favouring the evolution of genetic linkage. While most theoretical studies on clustering of divergent loci focus on how physical linkage influences speciation, we show how physical linkage itself can arise, establishing conditions that can favour speciation.

Calibrating spatiotemporal models of microbial communities to microscopy data: A review

Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.

Assessing the impact of forest structure disturbances on the arboreal movement and energetics of orangutans—An agent-based modeling approach

Agent-based models have been developed and widely employed to assess the impact of disturbances or conservation management on animal habitat use, population development, and viability. However, the direct impacts of canopy disturbance on the arboreal movement of individual primates have been less studied. Such impacts could shed light on the cascading effects of disturbances on animal health and fitness. Orangutans are an arboreal primate that commonly encounters habitat quality deterioration due to land-use changes and related disturbances such as forest fires. Forest disturbance may, therefore, create a complex stress scenario threatening orangutan populations. Due to forest disturbances, orangutans may adapt to employ more terrestrial, as opposed to arboreal, movements potentially prolonging the search for fruiting and nesting trees. In turn, this may lead to changes in daily activity patterns (i.e., time spent traveling, feeding, and resting) and available energy budget, potentially decreasing the orangutan's fitness. We developed the agent-based simulation model BORNEO (arBOReal aNimal movEment mOdel), which explicitly describes both orangutans' arboreal and terrestrial movement in a forest habitat, depending on distances between trees and canopy structures. Orangutans in the model perform activities with a motivation to balance energy intake and expenditure through locomotion. We tested the model using forest inventory data obtained in Sebangau National Park, Central Kalimantan, Indonesia. This allowed us to construct virtual forests with real characteristics including tree connectivity, thus creating the potential to expand the environmental settings for simulation experiments. In order to parameterize the energy related processes of the orangutans described in the model, we applied a computationally intensive evolutionary algorithm and evaluated the simulation results against observed behavioral patterns of orangutans. Both the simulated variability and proportion of activity budgets including feeding, resting, and traveling time for female and male orangutans confirmed the suitability of the model for its purpose. We used the calibrated model to compare the activity patterns and energy budgets of orangutans in both natural and disturbed forests . The results confirm field observations that orangutans in the disturbed forest are more likely to experience deficit energy balance due to traveling to the detriment of feeding time. Such imbalance is more pronounced in males than in females. The finding of a threshold of forest disturbances that affects a significant change in activity and energy budgets suggests potential threats to the orangutan population. Our study introduces the first agent-based model describing the arboreal movement of primates that can serve as a tool to investigate the direct impact of forest changes and disturbances on the behavior of species such as orangutans. Moreover, it demonstrates the suitability of high-performance computing to optimize the calibration of complex agent-based models describing animal behavior at a fine spatio-temporal scale (1-m and 1-s granularity).

Chronic and Acute Effects of Imidacloprid on a Simulated BEEHAVE Honeybee Colony

Honeybees (Apis mellifera) are important pollinators for wild plants as well as for crops, but honeybee performance is threatened by several stressors including varroa mites, gaps in foraging supply, and pesticides. The consequences of bee colony longtime exposure to multiple stressors are not well understood. The vast number of possible stressor combinations and necessary study duration require research comprising field, laboratory, and simulation experiments. We simulated long-term exposure of a honeybee colony to the insecticide imidacloprid and to varroa mites carrying the deformed wing virus in landscapes with different temporal gaps in resource availability as single stressors and in combinations. Furthermore, we put a strong emphasis on chronic lethal, acute sublethal, and acute lethal effects of imidacloprid on honeybees. We have chosen conservative published values to parameterize our model (e.g., highest reported imidacloprid contamination). As expected, combinations of stressors had a stronger negative effect on bee performance than each single stressor alone, and effect sizes were larger after 3 years of exposure than after the first year. Imidacloprid-caused reduction in bee performance was almost exclusively due to chronic lethal effects because the thresholds for acute effects were rarely met in simulations. In addition, honeybee colony extinctions were observed by the last day of the first year but more pronounced on the last days of the second and third simulation year. In conclusion, our study highlights the need for more long-term studies on chronic lethal effects of pesticides on honeybees. Environ Toxicol Chem 2022;41:2318-2327. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Regional representation of wind stakeholders' end-of-life behaviors and their impact on wind blade circularity

The growing number of end-of-life (EOL) wind blades could further strain US landfills or be a valuable composite materials source, depending on stakeholders' behaviors. Technical solutions based on circular economy (CE) principles have been proposed but are not guaranteed to solve the issue of EOL management. Transitioning to CE implies changing how business models, supply chains, and behaviors deal with products and waste. A spatially resolved agent-based modeling combined with a machine-learning metamodel shows that including behavioral factors is crucial to designing effective policies. Logistical barriers and transportation costs significantly affect the results: lowering blade shredding costs by a third before transportation makes EOL blades a source of valuable materials, decreasing the 2050 cumulative landfill rate below 50%. In another scenario, parameter settings simulating policy interventions aiming at boosting early adoption incites new social norms favorable to recycling, lowering the cumulative landfill rate below 10%.

Insectivorous bats form mobile sensory networks to optimize prey localization: The case of the common noctule bat

Animals that depend on ephemeral, patchily distributed prey often use public information to locate resource patches. The use of public information can lead to the aggregation of foragers at prey patches, a mechanism known as local enhancement. However, when ephemeral resources are distributed over large areas, foragers may also need to increase search efficiency, and thus apply social strategies when sampling the landscape. While sensory networks of visually oriented animals have already been confirmed, we lack an understanding of how acoustic eavesdropping adds to the formation of sensory networks. Here we radio-tracked a total of 81 aerial-hawking bats at very high spatiotemporal resolution during five sessions over 3 y, recording up to 19 individuals simultaneously. Analyses of interactive flight behavior provide conclusive evidence that bats form temporary mobile sensory networks by adjusting their movements to neighboring conspecifics while probing the airspace for prey. Complementary agent-based simulations confirmed that the observed movement patterns can lead to the formation of mobile sensory networks, and that bats located prey faster when networking than when relying only on local enhancement or searching solitarily. However, the benefit of networking diminished with decreasing group size. The combination of empirical analyses and simulations elucidates how animal groups use acoustic information to efficiently locate unpredictable and ephemeral food patches. Our results highlight that declining local populations of social foragers may thus suffer from Allee effects that increase the risk of collapses under global change scenarios, like insect decline and habitat degradation.

Quantifying mechanisms of coexistence in disease ecology

Pathogen coexistence depends on ecological processes operating at both within and between-host scales, making it difficult to quantify which processes may promote or prevent coexistence. Here, we propose that adapting modern coexistence theory-traditionally applied in plant communities-to pathogen systems provides an exciting approach for examining mechanisms of coexistence operating across different spatial scales. We first overview modern coexistence theory and its mechanistic decomposition; we subsequently adapt the framework to quantify how spatial variation in pathogen density, host resources and immunity, and their interaction may promote pathogen coexistence. We apply this derivation to an example two pathogen, multi-scale model comparing two scenarios with generalist and strain-specific immunity: one with demographic equivalency among pathogens and one with demographic trade-offs among pathogens. We then show how host-pathogen feedbacks generate spatial heterogeneity that promote pathogen coexistence and decompose those mechanisms to quantify how each spatial heterogeneity contributes to that coexistence. Specifically, coexistence of demographically equivalent pathogens occurs due to spatial variation in host resources, immune responses, and pathogen aggregation. With a competition-colonization trade-off, the superior colonizer requires spatial heterogeneity to coexist, whereas the superior competitor does not. Finally, we suggest ways forward for linking theory and empirical tests of coexistence in disease systems.

ROBITT: A tool for assessing the risk-of-bias in studies of temporal trends in ecology

Aggregated species occurrence and abundance data from disparate sources are increasingly accessible to ecologists for the analysis of temporal trends in biodiversity. However, sampling biases relevant to any given research question are often poorly explored and infrequently reported; this can undermine statistical inference. In other disciplines, it is common for researchers to complete 'risk-of-bias' assessments to expose and document the potential for biases to undermine conclusions. The huge growth in available data, and recent controversies surrounding their use to infer temporal trends, indicate that similar assessments are urgently needed in ecology.We introduce ROBITT, a structured tool for assessing the 'Risk-Of-Bias In studies of Temporal Trends in ecology'. ROBITT has a similar format to its counterparts in other disciplines: it comprises signalling questions designed to elicit information on the potential for bias in key study domains. In answering these, users will define study inferential goal(s) and relevant statistical target populations. This information is used to assess potential sampling biases across domains relevant to the research question (e.g. geography, taxonomy, environment), and how these vary through time. If assessments indicate biases, then users must clearly describe them and/or explain what mitigating action will be taken.Everything that users need to complete a ROBITT assessment is provided: the tool, a guidance document and a worked example. Following other disciplines, the tool and guidance document were developed through a consensus-forming process across experts working in relevant areas of ecology and evidence synthesis.We propose that researchers should be strongly encouraged to include a ROBITT assessment when publishing studies of biodiversity trends, especially when using aggregated data. This will help researchers to structure their thinking, clearly acknowledge potential sampling issues, highlight where expert consultation is required and provide an opportunity to describe data checks that might go unreported. ROBITT will also enable reviewers, editors and readers to establish how well research conclusions are supported given a dataset combined with some analytical approach. In turn, it should strengthen evidence-based policy and practice, reduce differing interpretations of data and provide a clearer picture of the uncertainties associated with our understanding of reality.

Large-scale PVA modeling of insects in cultivated grasslands: The role of dispersal in mitigating the effects of management schedules under climate change

In many species, dispersal is decisive for survival in a changing climate. Simulation models for population dynamics under climate change thus need to account for this factor. Moreover, large numbers of species inhabiting agricultural landscapes are subject to disturbances induced by human land use. We included dispersal in the HiLEG model that we previously developed to study the interaction between climate change and agricultural land use in single populations. Here, the model was parameterized for the large marsh grasshopper (LMG) in cultivated grasslands of North Germany to analyze (1) the species development and dispersal success depending on the severity of climate change in subregions, (2) the additional effect of grassland cover on dispersal success, and (3) the role of dispersal in compensating for detrimental grassland mowing. Our model simulated population dynamics in 60-year periods (2020-2079) on a fine temporal (daily) and high spatial (250 × 250 m2) scale in 107 subregions, altogether encompassing a range of different grassland cover, climate change projections, and mowing schedules. We show that climate change alone would allow the LMG to thrive and expand, while grassland cover played a minor role. Some mowing schedules that were harmful to the LMG nevertheless allowed the species to moderately expand its range. Especially under minor climate change, in many subregions dispersal allowed for mowing early in the year, which is economically beneficial for farmers. More severe climate change could facilitate LMG expansion to uninhabited regions but would require suitable mowing schedules along the path. These insights can be transferred to other species, given that the LMG is considered a representative of grassland communities. For more specific predictions on the dynamics of other species affected by climate change and land use, the publicly available HiLEG model can be easily adapted to the characteristics of their life cycle.

Considering Farmers' Heterogeneity to Payment Ecosystem Services Participation: A Choice Experiment and Agent-Based Model Analysis in Xin'an River Basin, China

The concept of watershed ecological compensation is one payment for ecosystem services (PES) program that incentivizes stakeholders undertake environmental conservation activities that improve the provision of ecosystem services. Defining the heterogeneity of farmers' willingness to participate in watershed ecological compensation is critically important for fully understanding stakeholders' demands. Accordingly, we designed a choice experiment survey to analyze the heterogeneity of policy preferences and willingness to receive compensation between upstream and midstream farmers in Xin'an River basin, China. Moreover, we simulated the impact of farmers' social capitals' heterogeneity with an agent-based model. The results show that there are significant differences in the preferences of agricultural waste recycling rate and agricultural water quality between farmers in the upstream and midstream. The total willingness of farmers in the upstream and midstream to participate in ecological compensation are RMB 149.88 (USD 22.54)/month and RMB 57.40 yuan (USD 8.63)/month, respectively. Social network size has a negative effect on farmers' willingness to participate the programs. Our findings suggest that the characteristics of farmers' influence their willingness to participate in the PES program. The results of this research can be used to improve PES management policies in the future, as well as to support sustainable environmental development and rural revitalization.

Simulating the bounds of plausibility: Estimating the impact of high-risk versus population-based approaches to prevent firearm injury

BACKGROUND

Firearm violence remains a persistent public health threat. Comparing the impact of targeted high-risk versus population-based approaches to prevention may point to efficient and efficacious interventions. We used agent-based modeling to conduct a hypothetical experiment contrasting the impact of high-risk (disqualification) and population-based (price increase) approaches on firearm homicide in New York City (NYC).

METHODS

We simulated 800,000 agents reflecting a 15% sample of the adult population of NYC. Three groups were considered and disqualified from all firearm ownership for five years, grouped based on prevalence: low prevalence (psychiatric hospitalization, alcohol-related misdemeanor and felony convictions, 0.23%); moderate prevalence (drug misdemeanor convictions, domestic violence restraining orders, 1.03%); and high prevalence (all other felony/misdemeanor convictions, 2.30%). Population-level firearm ownership was impacted by increasing the price of firearms, assuming 1% price elasticity.

RESULTS

In this hypothetical scenario, to reduce firearm homicide by 5% in NYC, 25% of the moderate prevalence group, or 12% of the high prevalence group needed to be effectively disqualified; even when all of the low prevalence group was disqualified, homicide did not decrease by 5%. An 18% increase in price similarly reduced firearm homicide by 5.37% (95% CI 4.43-6.31%). Firearm homicide declined monotonically as the proportion of disqualified individuals increased and/or price increased. A combined intervention that both increased price and effectively disqualified "high-risk" groups achieved approximately double the reduction in homicide as any one intervention alone. Increasing illegal firearm ownership by 20%, a hypothetical response to price increases, did not meaningfully change results.

CONCLUSION

A key takeaway of our study is that adopting high-risk versus population-based approaches should not be an "either-or" question. When individual risk is variable and diffuse in the population, "high-risk approaches" to firearm violence need to focus on relatively prevalent groups and be highly efficacious in disarming people at elevated risk to achieve meaningful reductions in firearm homicide, though countering issues of social justice and stigma should be carefully considered. Similar reductions can be achieved with population-based approaches, such as price increases, albeit with fewer such countering issues.

An Agent-Based Model of Heterogeneous Driver Behaviour and Its Impact on Energy Consumption and Costs in Urban Space

By 2020, over 100 countries had expanded electric and plug-in hybrid electric vehicle (EV/PHEV) technologies, with global sales surpassing 7 million units. Governments are adopting cleaner vehicle technologies due to the proven environmental and health implications of internal combustion engine vehicles (ICEVs), as evidenced by the recent COP26 meeting. This article proposes an agent-based model of vehicle activity as a tool for quantifying energy consumption by simulating a fleet of EV/PHEVs within an urban street network at various spatio-temporal resolutions. Driver behaviour plays a significant role in energy consumption; thus, simulating various levels of individual behaviour and enhancing heterogeneity should provide more accurate results of potential energy demand in cities. The study found that (1) energy consumption is lowest when speed limit adherence increases (low variance in behaviour) and is highest when acceleration/deceleration patterns vary (high variance in behaviour); (2) vehicles that travel for shorter distances while abiding by speed limit rules are more energy efficient compared to those that speed and travel for longer; and (3) on average, for tested vehicles, EV/PHEVs were £233.13 cheaper to run than ICEVs across all experiment conditions. The difference in the average fuel costs (electricity and petrol) shrinks at the vehicle level as driver behaviour is less varied (more homogeneous). This research should allow policymakers to quantify the demand for energy and subsequent fuel costs in cities.

Simulating Pine Wilt Disease Dispersal With an Individual-Based Model Incorporating Individual Movement Patterns of Vector Beetles

Individual movements of the insect vector pine sawyer beetles were incorporated into an individual-based model (IBM) to elucidate the dispersal of pine wilt disease (PWD) and demonstrate the effects of control practices. The model results were compared with the spatial data of infested pine trees in the Gijang-gun area of Busan, Republic of Korea. Step functions with long- and middle-distance movements of individual beetles effectively established symptomatic and asymptomatic trees for the dispersal of PWD. Pair correlations and pairwise distances were suitable for evaluating PWD dispersal between model results and field data at short and long scales, respectively. The accordance between model and field data was observed in infestation rates at 0.08 and 0.09 and asymptomatic rates at 0.16-0.17 for disease dispersal. Eradication radii longer than 20 m would effectively control PWD dispersal for symptomatic transmission and 20-40 m for asymptomatic transmission. However, the longer eradication radii were more effective at controlling PWD. Therefore, to maximize control effects, a longer radius of at least 40 m is recommended for clear-cutting eradication. The IBM of individual movement patterns provided practical information on interlinking the levels of individuals and populations and could contribute to the monitoring and management of forest pests where individual movement is important for population dispersal.

Forecasting effects of transport infrastructure on endangered tigers: a tool for conservation planning

The rapid development of transport infrastructure is a major threat to endangered species worldwide. Roads and railways can increase animal mortality, fragment habitats, and exacerbate other threats to biodiversity. Predictive models that forecast the future impacts to endangered species can guide land-use planning in ways that proactively reduce the negative effects of transport infrastructure. Agent-based models are well suited for predictive scenario testing, yet their application to endangered species conservation is rare. Here, we developed a spatially explicit, agent-based model to forecast the effects of transport infrastructure on an isolated tiger (Panthera tigris) population in Nepal's Chitwan National Park-a global biodiversity hotspot. Specifically, our model evaluated the independent and interactive effects of two mechanisms by which transport infrastructure may affect tigers: (a) increasing tiger mortality, e.g., via collisions with vehicles, and (b) depleting prey near infrastructure. We projected potential impacts on tiger population dynamics based on the: (i) existing transportation network in and near the park, and (ii) the inclusion of a proposed railway intersecting through the park's buffer zone. Our model predicted that existing roads would kill 46 tigers over 20 years via increased mortality, and reduced the adult tiger population by 39% (133 to 81). Adding the proposed railway directly killed 10 more tigers over those 20 years; deaths that reduced the overall tiger population by 30 more individuals (81 to 51). Road-induced mortality also decreased the proportion of time a tiger occupied a given site by 5 years in the 20-year simulation. Interestingly, we found that transportation-induced depletion of prey decreased tiger occupancy by nearly 20% in sites close to roads and the railway, thereby reducing tiger exposure to transportation-induced mortality. The results of our model constitute a strong argument for taking into account prey distributions into the planning of roads and railways. Our model can promote tiger-friendly transportation development, for example, by improving Environmental Impact Assessments, identifying "no go" zones where transport infrastructure should be prohibited, and recommending alternative placement of roads and railways.

A stochastic simulation model for assessing the masking effects of road noise for wildlife, outdoor recreation, and bioacoustic monitoring

Traffic noise is one of the leading causes of reductions in animal abundances near roads. Acoustic masking of conspecific signals and adventitious cues is one mechanism that likely causes animals to abandon loud areas. However, masking effects can be difficult to document in situ and the effects of infrequent noise events may be impractical to study. Here, we present the Soundscapes model, a stochastic individual-based model that dynamically models the listening areas of animals searching for acoustic resources (“searchers"). The model also studies the masking effects of noise for human detections of the searchers. The model is set in a landscape adjacent to a road. Noise produced by vehicles traveling on that road is represented by calibrated spectra that vary with speed. Noise propagation is implemented using ISO-9613 procedures. We present demonstration simulations that quantify declines in searcher efficiency and human detection of searchers at relatively low traffic volumes, fewer than 50 vehicles per hour. Traffic noise is pervasive, and the Soundscapes model offers an extensible tool to study the effects of noise on bioacoustics monitoring, point-count surveys, the restorative value of natural soundscapes, and auditory performance in an ecological context.

Joint effects of voluntary participation and group selection on the evolution of altruistic punishment

It is puzzling how altruistic punishment of defectors can evolve in large groups of nonrelatives, since punishers should voluntarily bear individual costs of punishing to benefit those who do not pay the costs. Although two distinct mechanisms have been proposed to explain the puzzle, namely voluntary participation and group-level competition and selection, insights into their joint effects have been less clear. Here we investigated what could be combined effects of these two mechanisms on the evolution of altruistic punishment and how these effects can vary with nonparticipants’ individual payoff and group size. We modelled altruistic punishers as those who contribute to a public good and impose a fine on each defector, i.e., they are neither pure punishers nor excluders. Our simulation results show that voluntary participation has negative effects on the evolution of cooperation in small groups regardless of nonparticipants’ payoffs, while in large groups it has positive effects within only a limited range of nonparticipants’ payoff. We discuss that such asymmetric effects could be explained by evolutionary forces emerging from voluntary participation. Lastly, we suggest that insights from social science disciplines studying the exit option could enrich voluntary participation models.

Epidemiological analyses of African swine fever in the European Union: (September 2020 to August 2021)

This report provides a descriptive analysis of the African swine fever (ASF) Genotype II epidemic in the affected Member States in the EU and two neighbouring countries for the period from 1 September 2020 to 31 August 2021. ASF continued to spread in wild boar in the EU, it entered Germany in September 2020, while Belgium became free from ASF in October 2020. No ASF outbreaks in domestic pigs nor cases in wild boar have been reported in Greece since February 2020. In the Baltic States, overall, there has been a declining trend in proportions of polymerase chain reaction (PCR)-positive samples from wild boar carcasses in the last few years. In the other countries, the proportions of PCR-positive wild boar carcasses remained high, indicating continuing spread of the disease. A systematic literature review revealed that the risk factors most frequently significantly associated with ASF in domestic pigs were pig density, low levels of biosecurity and socio-economic factors. For wild boar, most significant risk factors were related to habitat, socio-economic factors and wild boar management. The effectiveness of different control options in the so-named white zones, areas where wild boar densities have been drastically reduced to avoid further spread of ASF after a new introduction, was assessed with a stochastic model. Important findings were that establishing a white zone is much more challenging when the area of ASF incursion is adjacent to an area where limited control measures are in place. Very stringent wild boar population reduction measures in the white zone are key to success. The white zone needs to be far enough away from the affected core area so that the population can be reduced in time before the disease arrives and the timing of this will depend on the wild boar density and the required population reduction target in the white zone. Finally, establishing a proactive white zone along the demarcation line of an affected area requires higher culling efforts, but has a higher chance of success to stop the spread of the disease than establishing reactive white zones after the disease has already entered in the area.

Guidance on good practice in conducting scientific assessments in animal health using modelling

The EFSA asked the Panel on Animal Health and Welfare to develop a guidance document on good practice in conducting scientific assessments in animal health using modelling. In previous opinions, the AHAW Panel has responded to two‐thirds of animal health‐related mandates using some kind of modelling. These models range from simple to complex, employing a combination of scientific, economic, socio‐economic or other types of data. Hence, there is strong interest in the development of a guidance document to integrate modelling efforts into the routine process of EFSA working groups. In this document, an ‘operating procedure' (OP) for the use of modelling within an AH working group is presented. The OP provides a detailed flowchart enabling modelling to be transparently and consistently integrated in the assessment. The OP is structured into phases. These phases combine the relevant standard operating procedures and working instructions of EFSA with the modelling process. Each phase includes roles and actions to be taken, expected output and the sequence of agreements that need to be made between all partners in the scientific assessment. In conclusion, it is expected that adherence to the OP will improve transparency of models in EFSA outputs, and it is recommended to adopt it as a standard procedure when responding to AHAW mandates.

Agent-based modelling of iron cycling bacteria provides a framework for testing alternative environmental conditions and modes of action

Iron-reducing and iron-oxidizing bacteria are of interest in a variety of environmental and industrial applications. Such bacteria often co-occur at oxic-anoxic gradients in aquatic and terrestrial habitats. In this paper, we present the first computational agent-based model of microbial iron cycling, between the anaerobic ferric iron (Fe³⁺)-reducing bacteria Shewanella spp. and the microaerophilic ferrous iron (Fe²⁺)-oxidizing bacteria Sideroxydans spp. By including the key processes of reduction/oxidation, movement, adhesion, Fe²⁺-equilibration and nanoparticle formation, we derive a core model which enables hypothesis testing and prediction for different environmental conditions including temporal cycles of oxic and anoxic conditions. We compared (i) combinations of different Fe³⁺-reducing/Fe²⁺-oxidizing modes of action of the bacteria and (ii) system behaviour for different pH values. We predicted that the beneficial effect of a high number of iron-nanoparticles on the total Fe³⁺ reduction rate of the system is not only due to the faster reduction of these iron-nanoparticles, but also to the nanoparticles' additional capacity to bind Fe²⁺ on their surfaces. Efficient iron-nanoparticle reduction is confined to pH around 6, being twice as high than at pH 7, whereas at pH 5 negligible reduction takes place. Furthermore, in accordance with experimental evidence our model showed that shorter oxic/anoxic periods exhibit a faster increase of total Fe³⁺ reduction rate than longer periods.

Economic impact of generic antiretrovirals in France for HIV patients' care: a simulation between 2019 and 2023

Background

In a context where the economic burden of HIV is increasing as HIV patients now have a close to normal lifespan, the availability of generic antiretrovirals commonly prescribed in 2017 and the imminence of patent expiration are expected to provide substantial savings in the coming years. This article aims to assess the economic impact of these generic antiretrovirals in France and specifically over a five-year period.

Methods

An agent-based model was developed to simulate patient trajectories and treatment use over a five-year period. By comparing the results of costs for trajectories simulated under different predefined scenarios, a budget impact model can be created and sensitivity analyses performed on several parameters of importance.

Results

The potential economic savings from 2019 to 2023 generated by generic antiretrovirals range from €309 million when the penetration rate of generics is set at 10% to €1.5 billion at 70%. These savings range from €984 million to €993 million as the delay between patent and generic marketing authorisation varies from 10 to 15 years, and from €965 million to €993 million as the Negotiated Price per Unit (NPU) of generics at market-entry varies from 40 to 50% of the NPU for patents.

Discussion

This economic savings simulation could help decision makers to anticipate resource allocations for further innovation in antiretrovirals therapies as well as prevention, especially by funding the Pre-Exposure Prophylaxis (PrEP) or HIV screening.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-022-07859-w.

Modeling the Future Tree Distribution in a South African Savanna Ecosystem: An Agent-Based Model Approach

Understanding the dynamics of tree species and their demography is necessary for predicting future developments in savanna ecosystems. In this contribution, elephant-tree and firewood collector-tree interactions are compared using a multiagent model. To investigate these dynamics, we compared three different tree species in two plots. The first plot is located in the protected space of Kruger National Park (KNP), South Africa, and the second plot in the rural areas of the Bushbuckridge Municipality, South Africa. The agent-based modeling approach enabled the modeling of individual trees with characteristics such as species, age class, size, damage class, and life history. A similar level of detail was applied to agents that represent elephants and firewood collectors. Particular attention was paid to modeling purposeful behavior of humans in contrast to more instinct-driven actions of elephants. The authors were able to predict future developments by simulating the time period between 2010 and 2050 with more than 500,000 individual trees. Modeling individual trees for a time span of 40 years might yield more detailed information than a simple woody mass aggregation. The results indicate a significant trend toward more and thinner trees together with a notable reduction in mature trees, while the total aboveground biomass appears to stay more or less constant. Furthermore, the KNP scenarios show an increase in young Combretum apiculatum, which may correspond to bush encroachment.

Model-based extrapolation of ecological systems under future climate scenarios: The example of Ixodes ricinus ticks

Models can be applied to extrapolate consequences of climate change for complex ecological systems in the future. The acknowledged systems' behaviour at present is projected into the future considering climate projection data. Such an approach can be used to addresses the future activity and density of the castor bean tick Ixodes ricinus, the most widespread tick species in Europe. It is an important vector of pathogens causing Lyme borreliosis and tick-borne encephalitis. The population dynamics depend on several biotic and abiotic factors. Such complexity makes it difficult to predict the future dynamics and density of I. ricinus and associated health risk for humans. The objective of this study is to force ecological models with high-resolution climate projection data to extrapolate I. ricinus tick density and activity patterns into the future. We used climate projection data of temperature, precipitation, and relative humidity for the period 1971-2099 from 15 different climate models. Tick activity was investigated using a climate-driven cohort-based population model. We simulated the seasonal population dynamics using climate data between 1971 and 2099 and observed weather data since 1949 at a specific location in southern Germany. We evaluated derived quantities of local tick ecology, e.g. the maximum questing activity of the nymphal stage. Furthermore, we predicted spatial density changes by extrapolating a German-wide tick density model. We compared the tick density of the reference period (1971-2000) with the counter-factual densities under the near-term scenario (2012-2041), mid-term scenario (2050-2079) and long-term scenario (2070-2099). We found that the nymphal questing peak would shift towards early seasons of the year. Also, we found high spatial heterogeneity across Germany, with predicted hotspots of up to 2,000 nymphs per 100 m2 and coldspots with constant density. As our results suggest extreme changes in tick behaviour and density, we discuss why caution is needed when extrapolating climate data-driven models into the distant future when data on future climate drive the model projection.