Modeling tiger population and territory dynamics using an agent-based approach

Collective signalling is shaped by feedbacks between signaller variation, receiver perception and acoustic environment in a simulated communication network

Communication takes place within a network of multiple signallers and receivers. Social network analysis provides tools to quantify how an individual's social positioning affects group dynamics and the subsequent biological consequences. However, network analysis is rarely applied to animal communication, likely due to the logistical difficulties of monitoring natural communication networks. We generated a simulated communication network to investigate how variation in individual communication behaviours generates network effects, and how this communication network's structure feeds back to affect future signalling interactions. We simulated competitive acoustic signalling interactions among chorusing individuals and varied several parameters related to communication and chorus size to examine their effects on calling output and social connections. Larger choruses had higher noise levels, and this reduced network density and altered the relationships between individual traits and communication network position. Hearing sensitivity interacted with chorus size to affect both individuals' positions in the network and the acoustic output of the chorus. Physical proximity to competitors influenced signalling, but a distinctive communication network structure emerged when signal active space was limited. Our model raises novel predictions about communication networks that could be tested experimentally and identifies aspects of information processing in complex environments that remain to be investigated. This article is part of the theme issue 'The power of sound: unravelling how acoustic communication shapes group dynamics'.

Predator-prey interactions across hunting mode, spatial domain size, and habitat complexities

Predator-prey interactions are a fundamental part of community ecology, yet the relative importance of consumptive and nonconsumptive effects (NCEs) (defined as a risk-induced response that alters prey fitness) has not been resolved. Theory suggests that the emergence and subsequent predominance of consumptive or NCEs depend on the given habitat's complexity as well as predator hunting mode and spatial domain sizes of both predator and prey, but their relative influence on the outcome of predator-prey interactions is unknown. We built agent-based models in NetLogo to simulate predator-prey interactions for three hunting modes-sit-and-wait, sit-and-pursue, and active-while concurrently simulating large versus small spatial domain sizes for both predators and prey. We studied (1) how hunting mode and spatial domain size interact to influence the emergence of consumptive or NCEs and (2) how, when NCEs do dominate, hunting mode and spatial domain separately or additively determine prey shifts in time, space, and habitat use. Our results indicate consumptive effects only dominate for active predators when prey habitat domains overlap completely with the predator's spatial domain and when sit-and-wait and sit-and-pursue predators and their prey both have large spatial domains. Prey are most likely to survive when they shift their time but most frequently shift their habitat. Our paper helps to better understand the underlying mechanisms that drive consumptive or NCEs to be most dominant.

Optimal foraging strategies for mutually avoiding competitors

Many animals are known to exhibit foraging patterns where the distances they travel in a given direction are drawn from a heavy-tailed Lévy distribution. Previous studies have shown that, under sparse and random resource conditions, solitary non-destructive (with regenerating resources) foragers perform a maximally efficient search with Lévy exponent μ equal to 2, while for destructive foragers, efficiency decreases with μ monotonically and there is no optimal μ. However, in nature, there also exist situations where multiple foragers, displaying avoidance behavior, interact with each other competitively. To understand the effects of such competition, we develop a stochastic agent-based simulation that models competitive foraging among mutually avoiding individuals by incorporating an avoidance zone, or territory, of a certain size around each forager which is not accessible for foraging by other competitors. For non-destructive foraging, our results show that with increasing size of the territory and number of agents the optimal Lévy exponent is still approximately 2 while the overall efficiency of the search decreases. At low values of the Lévy exponent, however, increasing territory size actually increases efficiency. For destructive foraging, we show that certain kinds of avoidance can lead to qualitatively different behavior from solitary foraging, such as the existence of an optimal search with 1<μ<2. Finally, we show that the variance among the efficiencies of the agents increases with increasing Lévy exponent for both solitary and competing foragers, suggesting that reducing variance might be a selective pressure for foragers adopting lower values of μ. Taken together, our results suggest that, for multiple foragers, mutual avoidance and efficiency variance among individuals can lead to optimal Lévy searches with exponents different from those for solitary foragers.

Do we all walk the walk? A comparison of walking behaviors across tetrapods

A walking gait has been identified in a range of vertebrate species with different body plans, habitats, and life histories. With increased application of this broad umbrella term, it has become necessary to assess the physical characteristics, analytical approaches, definitions, and diction used to describe walks. To do this, we reviewed studies of slow speed locomotion across a range of vertebrates to refine the parameters used to define walking, evaluate analytical techniques, and propose approaches to maximize consistency across subdisciplines. We summarize nine key parameters used to characterize walking behaviors in mammals, birds, reptiles, amphibians, and fishes. After identifying consistent patterns across groups, we propose a comprehensive definition for a walking gait. A walk is a form of locomotion where the majority of the forward propulsion of the animal comes from forces generated by the appendages interacting with the ground. During a walk, an appendage must be out of phase with the opposing limb in the same girdle and there is always at least one limb acting as ground-support (no suspension phase). Additionally, walking occurs at dimensionless speeds <1 v* and the duty factor of the limbs is always >0.5. Relative to other gaits used by the same species, the stance duration of a walk is long, the cycle frequency is low, and the cycle distance is small. Unfortunately, some of these biomechanical parameters, while effectively describing walks, may also characterize other, non-walking gaits. Inconsistent methodology likely contributes to difficulties in comparing data across many groups of animals; consistent application of data collection and analytical techniques in research methodology can improve these comparisons. Finally, we note that the kinetics of quadrupedal movements are still poorly understood and much work remains to be done to understand the movements of small, exothermic tetrapods.

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.

Anticipation of common buzzard population patterns in the changing UK landscape

Harmonious coexistence between humans, other animals and ecosystem services they support is a complex issue, typically impacted by landscape change, which affects animal distribution and abundance. In the last 30 years, afforestation on grasslands across Great Britain has been increasing, motivated by socio-economic reasons and climate change mitigation. Beyond expected benefits, an obvious question is what are the consequences for wider biodiversity of this scale of landscape change. Here, we explore the impact of such change on the expanding population of common buzzards Buteo buteo, a raptor with a history of human-induced setbacks. Using Resource-Area-Dependence Analysis (RADA), with which we estimated individuals' resource needs using 10-day radio-tracking sessions and the 1990s Land Cover Map of GB, and agent-based modelling, we predict that buzzards in our study area in lowland UK had fully recovered (to 2.2 ind km^-2) by 1995. We also anticipate that the conversion of 30%, 60% and 90% of economically viable meadow into woodland would reduce buzzard abundance nonlinearly by 15%, 38% and 74%, respectively. The same approach used here could allow for cost-effective anticipation of other animals' population patterns in changing landscapes, thus helping to harmonize economy, landscape change and biodiversity.

From theory to practice in pattern-oriented modelling: identifying and using empirical patterns in predictive models

To robustly predict the effects of disturbance and ecosystem changes on species, it is necessary to produce structurally realistic models with high predictive power and flexibility. To ensure that these models reflect the natural conditions necessary for reliable prediction, models must be informed and tested using relevant empirical observations. Pattern-oriented modelling (POM) offers a systematic framework for employing empirical patterns throughout the modelling process and has been coupled with complex systems modelling, such as in agent-based models (ABMs). However, while the production of ABMs has been rising rapidly, the explicit use of POM has not increased. Challenges with identifying patterns and an absence of specific guidelines on how to implement empirical observations may limit the accessibility of POM and lead to the production of models which lack a systematic consideration of reality. This review serves to provide guidance on how to identify and apply patterns following a POM approach in ABMs (POM-ABMs), specifically addressing: where in the ecological hierarchy can we find patterns; what kinds of patterns are useful; how should simulations and observations be compared; and when in the modelling cycle are patterns used? The guidance and examples provided herein are intended to encourage the application of POM and inspire efficient identification and implementation of patterns for both new and experienced modellers alike. Additionally, by generalising patterns found especially useful for POM-ABM development, these guidelines provide practical help for the identification of data gaps and guide the collection of observations useful for the development and verification of predictive models. Improving the accessibility and explicitness of POM could facilitate the production of robust and structurally realistic models in the ecological community, contributing to the advancement of predictive ecology at large.

Conserving an Endangered Canid: Assessing Distribution, Habitat Protection, and Connectivity for the Dhole (Cuon alpinus) in Bhutan

Most canids face population declines and range contractions worldwide. Although the dhole (Cuon alpinus) is widely distributed across 10 countries in South and Southeast Asia, limited studies exist on this species. Despite its globally “Endangered” status and ecological role as an apex predator, assessments on its distribution are limited to a few landscapes and countries. This explains the lack of a dhole-specific species conservation plan in most range countries, including Bhutan where no current population estimate exists. The species has also recovered from a country-wide poisoning campaign in the 1970s and 80s. In this study, we determine the dhole's distribution pattern and assess the protection and connectivity of dhole habitat in Bhutan. We anticipated dholes to be extant within their habitat well-represented in protected areas (PAs) and biological corridors (BCs). We used 721 georeferenced dhole occurrence records and eight environmental variables in MaxEnt software to model potential dhole distribution and habitat suitability. The model output was overlaid on the spatial layers of PAs and BCs to assess habitat protection and connectivity. As anticipated, we found the dhole widely distributed in all districts, PAs, and BCs in Bhutan. Dholes were recorded at the highest elevation range limit of 4,980 m above sea level, which overlapped with the “Vulnerable” snow leopard (Panthera uncia). Our model identified 72% (27,634 km2) of the country as suitable areas for dholes, of which, 31% (11,899 km2) was highly suitable and 41% (15,735 km2) was moderately suitable. Contrary to our expectation, PAs and BCs encompassed only 29% (8,046 km2) and 12% (3,185 km2) of suitable areas for dholes, respectively. A vast majority of the areas we deemed suitable for dholes currently remain unprotected, thus making dholes more vulnerable to human persecution and local extermination. We recommend adjusting PA boundaries to fully encompass suitable dhole habitat, and also advocate improved livestock husbandry to reduce dhole related livestock predation and minimize conflict, thereby ensuring its long-term survival in Bhutan.

Natural strongholds for red squirrel conservation in Scotland

The Eurasian Red Squirrel (Sciurus vulgaris) is under threat from the invasive North American eastern Grey Squirrel (Sciurus carolinensis) with 80% of the remaining red squirrel populations in the British Isles found in Scotland. In this study we develop a spatially explicit mathematical model of the red and grey squirrel system and use it to assess the population viability of red squirrels across Scotland. In particular, we aim to identify existing forests – natural strongholds for red squirrels – that can successfully support red squirrels under UK Forestry Standard management and protect them from potential disease-mediated competition from grey squirrels. Our model results indicate that if current levels of grey squirrel control, which restrict or reduce the distribution of grey squirrels, are continued then there will be large expanses of forests in northern Scotland that support viable red squirrel populations. Model results that represent (hypothetical) scenarios where grey squirrel control no longer occurred indicated that grey squirrel range expansion and the process of red squirrel replacement would be slow. Model results for an assumed worst-case scenario where grey squirrels have expanded to all regions in Scotland identified forest regions – denoted natural strongholds – that could currently support red squirrels under UK Forestry Standard management practice. The results will be used to inform forest management policy and support a strategic review of red squirrel management by land management agencies and other stakeholders.

Landscape-induced spatial oscillations in population dynamics

We study the effect that disturbances in the ecological landscape exert on the spatial distribution of a population that evolves according to the nonlocal FKPP equation. Using both numerical and analytical techniques, we characterize, as a function of the interaction kernel, the three types of stationary profiles that can develop near abrupt spatial variations in the environmental conditions vital for population growth: sustained oscillations, decaying oscillations and exponential relaxation towards a flat profile. Through the mapping between the features of the induced wrinkles and the shape of the interaction kernel, we discuss how heterogeneities can reveal information that would be hidden in a flat landscape.

Forging a Bayesian link between habitat selection and avoidance behavior in a grassland grouse

Habitat selection is a basic aspect of the ecology of many species, yet often the term is conflated or confused with both habitat preference and habitat use. We argue that each term fits within a conceptual framework that can be viewed in Bayesian terms and demonstrate, using long-term data on occupancy patterns of a grassland grouse, how prior probability profiles can be estimated. We obtained estimates by specifically focusing on whether and to what extent the Lesser Prairie-Chicken (Tympanuchus pallidicinctus) avoids anthropogenic features such as roads, powerlines, petroleum wells, fences, and buildings, in two study areas, one with denser and one with sparser incidence of features. Grouse strongly avoided large features such as outbuildings and tended to avoid tall features such as powerlines; by contrast, grouse did not or only slightly avoided low, unobtrusive features such as fences. We further examined co-location of pairs of anthropogenic features and found that certain features were avoided so strongly that avoidance distance may be shorter for other features; that is, birds were "pushed toward" some features because they are "pushed away" from others. In each case, our approach points toward a means to incorporate avoidance behavior directly into analytic studies of habitat selection, in that data on use (the posterior, as it were) could be used to infer the selection process provided data on preference (the prior, as it were) could be obtained.

Large deviations of a random walk model with emerging territories

We study an agent-based model of animals marking their territory and evading adversarial territory in one dimension with respect to the distribution of the size of the resulting territories. In particular, we use sophisticated sampling methods to determine it over a large part of territory sizes, including atypically small and large configurations, which occur with probability of less than 10^{-30}. We find hints for the validity of a large deviation principle, the shape of the rate function for the right tail of the distribution, and insight into the structure of atypical realizations.

An introduction to agent-based models as an accessible surrogate to field-based research and teaching

There are many barriers to fieldwork including cost, time, and physical ability. Unfortunately, these barriers disproportionately affect minority communities and create a disparity in access to fieldwork in the natural sciences. Travel restrictions, concerns about our carbon footprint, and the global lockdown have extended this barrier to fieldwork across the community and led to increased anxiety about gaps in productivity, especially among graduate students and early-career researchers. In this paper, we discuss agent-based modeling as an open-source, accessible, and inclusive resource to substitute for lost fieldwork during COVID-19 and for future scenarios of travel restrictions such as climate change and economic downturn. We describe the benefits of Agent-Based models as a teaching and training resource for students across education levels. We discuss how and why educators and research scientists can implement them with examples from the literature on how agent-based models can be applied broadly across life science research. We aim to amplify awareness and adoption of this technique to broaden the diversity and size of the agent-based modeling community in ecology and evolutionary research. Finally, we discuss the challenges facing agent-based modeling and discuss how quantitative ecology can work in tandem with traditional field ecology to improve both methods.

Mathematical modelling of cell migration

The complexity of biological systems creates challenges for fully understanding their behaviour. This is particularly true for cell migration which requires the co-ordinated activity of hundreds of individual components within cells. Mathematical modelling can help understand these complex systems by breaking the system into discrete steps which can then be interrogated in silico. In this review, we highlight scenarios in cell migration where mathematical modelling can be applied and discuss what types of modelling are most suited. Almost any aspect of cell migration is amenable to mathematical modelling from the modelling of intracellular processes such as chemokine receptor signalling and actin filament branching to larger scale processes such as the movement of individual cells or populations of cells through their environment. Two common ways of approaching this modelling are the use of models based on differential equations or agent-based modelling. The application of both these approaches to cell migration are discussed with specific examples along with common software tools to facilitate the process for non-mathematicians. We also highlight the challenges of modelling cell migration and the need for rigorous experimental work to effectively parameterise a model.

Effects of human-induced prey depletion on large carnivores in protected areas: Lessons from modeling tiger populations in stylized spatial scenarios

Prey depletion is a major threat to the conservation of large carnivore species globally. However, at the policy-relevant scale of protected areas, we know little about how the spatial distribution of prey depletion affects carnivore space use and population persistence. We developed a spatially explicit, agent-based model to investigate the effects of different human-induced prey depletion experiments on the globally endangered tiger (Panthera tigris) in isolated protected areas-a situation that prevails throughout the tiger's range. Specifically, we generated 120 experiments that varied the spatial extent and intensity of prey depletion across a stylized (circle) landscape (1,000 km2) and Nepal's Chitwan National Park (~1,239 km2). Experiments that created more spatially homogenous prey distributions (i.e., less prey removed per cell but over larger areas) resulted in larger tiger territories and smaller population sizes over time. Counterintuitively, we found that depleting prey along the edge of Chitwan National Park, while decreasing tiger numbers overall, also decreased female competition for those areas, leading to lower rates of female starvation. Overall our results suggest that subtle differences in the spatial distributions of prey densities created by various human activities, such as natural resource-use patterns, urban growth and infrastructure development, or conservation spatial zoning might have unintended, detrimental effects on carnivore populations. Our model is a useful planning tool as it incorporates information on animal behavioral ecology, resource spatial distribution, and the drivers of change to those resources, such as human activities.

A comparison of stable and fluctuating resources with respect to evolutionary adaptation and life-history traits using individual-based modeling and machine learning

There are three non-mutually-exclusive key strategies evolved by gene pools to cope with fluctuating food resource availability, including evolutionary adaptation, phenotypic plasticity, and migration. We focus primarily on evolutionary adaptation and behavioral plasticity, which is a type of phenotypic plasticity, resulting in life-history changes as ways of dealing with fluctuations in food resource availability. Using EcoSim, a predator-prey individual-based model, we compare individuals with stable food resources with those in environments where there are fluctuating food resources in terms of adaptation through behavioral plasticity and evolution. The purpose of our study is to determine whether evolution and behavioral plasticity truly play a role in adapting to an environment with fluctuating food resources, as well as to determine whether there are specific gene divergences between gene pools in fluctuating food resource environments versus gene pools where food resources are relatively stable. An important result of our study is that individuals in environments that are unstable with respect to food resource availability exhibited significant differences in behaviors versus those in environments with stable food resources. Although behavioral plasticity facilitates a rapid response to unstable food conditions, our study revealed the evolution of perceptual traits such as vision range in reaction to fluctuating food resources, indicating the importance of evolution in adapting to unstable resource environments in the long run. Moreover, using decision trees, we found that there were significant behavioral gene divergences between individuals in environments with fluctuating food resources as opposed to individuals in environments with stable food resources.

Mate choice strategies in a spatially-explicit model environment

Decisions about the choice of a mate can greatly impact both individual fitness and selection processes. We developed a novel agent-based model to investigate two common mate choice rules that may be used by female gray treefrogs (Hyla versicolor). In this model environment, female agents using the minimum-threshold strategy found higher quality mates and traveled shorter distances on average, compared with female agents using the best-of-n strategy. Females using the minimum-threshold strategy, however, incur significant lost opportunity costs, depending on the male population quality average. The best-of-n strategy leads to significant female:female competition that limits their ability to find high quality mates. Thus, when the sex ratio is 0.8, best-of-5 and best-of-2 strategies yield mates of nearly identical quality. Although the distance traveled by females in the mating task varied depending on male spatial distribution in the environment, this did not interact with female choice for the best-of-n or minimum-threshold strategies. By incorporating empirical data from the frogs in this temporally- and spatially-explicit model, we thus show the emergence of novel interactions of common decision-making rules with realistic environmental variables.

Spatial memory shapes density dependence in population dynamics

Most population dynamics studies assume that individuals use space uniformly, and thus mix well spatially. In numerous species, however, individuals do not move randomly, but use spatial memory to visit renewable resource patches repeatedly. To understand the extent to which memory-based foraging movement may affect density-dependent population dynamics through its impact on competition, we developed a spatially explicit, individual-based movement model where reproduction and death are functions of foraging efficiency. We compared the dynamics of populations of with- and without-memory individuals. We showed that memory-based movement leads to a higher population size at equilibrium, to a higher depletion of the environment, to a marked discrepancy between the global (i.e. measured at the population level) and local (i.e. measured at the individual level) intensities of competition, and to a nonlinear density dependence. These results call for a deeper investigation of the impact of individual movement strategies and cognitive abilities on population dynamics.

A Generic Individual-Based Spatially Explicit Model as a Novel Tool for Investigating Insect-Plant Interactions: A Case Study of the Behavioural Ecology of Frugivorous Tephritidae

Computational modelling of mechanisms underlying processes in the real world can be of great value in understanding complex biological behaviours. Uptake in general biology and ecology has been rapid. However, it often requires specific data sets that are overly costly in time and resources to collect. The aim of the current study was to test whether a generic behavioural ecology model constructed using published data could give realistic outputs for individual species. An individual-based model was developed using the Pattern-Oriented Modelling (POM) strategy and protocol, based on behavioural rules associated with insect movement choices. Frugivorous Tephritidae (fruit flies) were chosen because of economic significance in global agriculture and the multiple published data sets available for a range of species. The Queensland fruit fly (Qfly), Bactrocera tryoni, was identified as a suitable individual species for testing. Plant canopies with modified architecture were used to run predictive simulations. A field study was then conducted to validate our model predictions on how plant architecture affects fruit flies’ behaviours. Characteristics of plant architecture such as different shapes, e.g., closed-canopy and vase-shaped, affected fly movement patterns and time spent on host fruit. The number of visits to host fruit also differed between the edge and centre in closed-canopy plants. Compared to plant architecture, host fruit has less contribution to effects on flies’ movement patterns. The results from this model, combined with our field study and published empirical data suggest that placing fly traps in the upper canopy at the edge should work best. Such a modelling approach allows rapid testing of ideas about organismal interactions with environmental substrates in silico rather than in vivo, to generate new perspectives. Using published data provides a saving in time and resources. Adjustments for specific questions can be achieved by refinement of parameters based on targeted experiments.