The influence of landscape structure on epidemic invasion of agricultural crops is often underestimated in the construction and analysis of epidemiological models. Computer simulations of individual-based models (IBMs) are widely used to characterize disease spread under different management scenarios but can be slow in exploring large numbers of different landscape configurations. Here, we address the problem of finding an analytical measure of the impact of the spatial structure of a crop landscape on the invasion and spread of plant pathogens. We explore the potential of using an analytical approximation for the rate, r , at which susceptible crop fields become infected at the start of an epidemic to predict the effect that the spatial structure of a host landscape will have on an epidemic. We demonstrate the validity of this approach using two models: (i) a general IBM of the invasion and spread of a pathogen through an abstract host landscape; and (ii) an IBM of a real-life example for a virus disease spreading through a cassava landscape. Finally, we demonstrate that the analytical approach based on an estimate of the rate, r , can be used to identify spatial structures that effect deceleration of an invading pathogen.

In long‐lived monogamous species, the trigger of costly re‐pairing is not always clear. Limited research suggests that within‐pair behavioural compatibility may be an important driver of partnership success, as cooperation should be enhanced when pair members' decisions complement one another. Animals' decision‐making processes are influenced by personality traits – defined as individual differences in behaviour that are stable in time. Despite the potential for the personality trait ‘boldness’ to (a) directly impact individual willingness to re‐pair and (b) indirectly impact re‐pairing choices via reproductive success, there is currently little work exploring how re‐pairing decisions might be impacted by the pair members' personalities. Using a 13‐year dataset, we investigated whether within‐pair boldness and its relationship with breeding success explained re‐pairing patterns of black‐legged kittiwakes ( Rissa tridactyla ), breeding in two Arctic colonies. We found that pairs with dissimilar boldness levels were more likely to experience breeding failure and that failed pairs were more likely to re‐pair the following year. Despite this, only one colony displayed evidence of assortative mating by boldness, and there was no indication that re‐pairing impacted reproductive success the following season. Neither individual nor pair boldness directly influenced re‐pairing probability; however, in both colonies, re‐pairing birds chose partners that were slightly more similar to themselves in boldness than their previous mates. These results imply an indirect pathway by which poorer behavioural compatibility within pairs may lead to breeding failure and ultimately re‐pairing. Our findings highlight the importance of behavioural compatibility, and possibly personality, in mitigating sexual conflict and its population‐specific drivers.

Long-lived monogamous species gain long-term fitness benefits by equalizing effort during biparental care. For example, many seabird species coordinate care by matching foraging trip durations within pairs. Age affects coordination in some seabird species; however, the impact of other intrinsic traits, including personality, on potential intraspecific variation in coordination strength is less well understood. The impacts of pair members' intrinsic traits on trip duration and coordination strength were investigated using data from saltwater immersion loggers deployed on 71 pairs of wandering albatrosses Diomedea exulans. These were modeled against pair members' age, boldness, and their partner's previous trip duration. At the population level, the birds exhibited some coordination of parental care that was of equal strength during incubation and chick-brooding. However, there was low variation in coordination between pairs and coordination strength was unaffected by the birds' boldness or age in either breeding stage. Surprisingly, during incubation, foraging trip duration was mainly driven by partner traits, as birds which were paired to older and bolder partners took shorter trips. During chick-brooding, shorter foraging trips were associated with greater boldness in focal birds and their partners, but age had no effect. These results suggest that an individual's assessment of their partner's capacity or willingness to provide care may be a major driver of trip duration, thereby highlighting the importance of accounting for pair behavior when studying parental care strategies.

Computer simulations of individual-based models are frequently used to compare strategies for the control of epidemics spreading through spatially distributed populations. However, computer simulations can be slow to implement for newly emerging epidemics, delaying rapid exploration of different intervention scenarios, and do not immediately give general insights, for example, to identify the control strategy with a minimal socio-economic cost. Here, we resolve this problem by applying an analytical approximation to a general epidemiological, stochastic, spatially explicit SIR(S) model where the infection is dispersed according to a finite-ranged dispersal kernel. We derive analytical conditions for a pathogen to invade a spatially explicit host population and to become endemic. To derive general insights about the likely impact of optimal control strategies on invasion and persistence: first, we distinguish between ‘spatial' and ‘non-spatial' control measures, based on their impact on the dispersal kernel; second, we quantify the relative impact of control interventions on the epidemic; third, we consider the relative socio-economic cost of control interventions. Overall, our study shows a trade-off between the two types of control interventions and a vaccination strategy. We identify the optimal strategy to control invading and endemic diseases with minimal socio-economic cost across all possible parameter combinations. We also demonstrate the necessary characteristics of exit strategies from control interventions. The modelling framework presented here can be applied to a wide class of diseases in populations of humans, animals and plants.

Background Animals use diverse antipredator mechanisms, including visual signalling of aversive chemical defence (aposematism). However, the initial evolution of aposematism poses the problem that the first aposematic individuals are conspicuous to predators who have not learned the significance of the warning colouration. In one scenario, aposematism evolves in group-living species and originally persisted due to kin selection or positive frequency-dependent selection in groups. Alternatively, group-living might evolve after aposematism because grouping can amplify the warning signal. However, our current understanding of the evolutionary dynamics of these traits is limited, leaving the relative merit of these scenarios unresolved. Results We used a phylogenetic comparative approach to estimate phenotypic evolutionary models to enable inferences regarding ancestral states and trait dynamics of grouping and aposematic colouration in a classic model system (caterpillars). We find strong support for aposematism at the root of the clade, and some (but weaker) support for ancestral solitary habits. Transition rates between aposematism and crypsis are generally higher than those between group-living and solitary-living, suggesting that colouration is more evolutionarily labile than aggregation. We also find that the transition from group-living to solitary-living states can only happen in aposematic lineage, suggesting that aposematism facilitates the evolution of solitary caterpillars, perhaps due to the additional protection offered when the benefits of grouping are lost. We also find that the high frequency of solitary, cryptic caterpillars is because this state is particularly stable, in that the transition rates moving towards this state are substantially higher than those moving away from it, favouring its accumulation in the clade over evolutionary time. Conclusions Our results provide new insights into the coevolution of colour and aggregation in caterpillars. We find support for an aposematic caterpillar at the root of this major clade, and for the signal augmentation hypothesis as an explanation of the evolution of aposematic, group-living caterpillars. We find that colouration is more labile than aggregation behaviour, but that the combination of solitary and cryptic habits is particularly stable. Finally, our results reveal that the transitions from group-living to solitary-living could be facilitated by aposematism, providing a new link between these well-studied traits.

Dispersal polymorphism and mutation play significant roles during biological invasions, potentially leading to evolution and complex behaviour such as accelerating or decelerating invasion fronts. However, life-history theory predicts that reproductive fitness-another key determinant of invasion dynamics-may be lower for more dispersive strains. Here, we use a mathematical model to show that unexpected invasion dynamics emerge from the combination of heritable dispersal polymorphism, dispersal-fitness trade-offs, and mutation between strains. We show that the invasion dynamics are determined by the trade-off relationship between dispersal and population growth rates of the constituent strains. We find that invasion dynamics can be 'anomalous' (i.e. faster than any of the strains in isolation), but that the ultimate invasion speed is determined by the traits of, at most, two strains. The model is simple but generic, so we expect the predictions to apply to a wide range of ecological, evolutionary, or epidemiological invasions.

Allee effects occur when individual or population survival decreases due to populations being small or sparse. A key mechanism underlying Allee effects is difficulty in finding mates at low densities. Species may be particularly vulnerable to mate-finding Allee effects if females rely on an abundance of males to reproduce successfully. In sexually cannibalistic species, females may consume males before or after copulation, potentially reducing the supply of males to the point where a mate-finding Allee effect occurs. In this study, we investigate the extent to which sexual cannibalism can modulate mate-finding Allee effects, and the conditions under which sexual cannibalism is likely to be particularly detrimental to population viability. We created an individual-based model that tracked specific females throughout the breeding season and used extinction risk and per capita growth rate to measure the strength of the Allee effects. We varied both founder population size and mate encounter rate independently of each other to expose the mechanism driving the Allee effects. We also analysed how cannibalism-derived female fecundity benefits affected extinction risk. We found that sexual cannibalism could lead to high extinction risk, particularly when cannibalism occurred before copulation, founder population size was small and mate encounter rates were low. However, post-copulatory cannibalism reduced extinction risk, if cannibalism increased female fecundity enough. We found that there were strong threshold effects, in which small changes in encounter rate could strongly alter population extinction risk. We find that sexual cannibalism is likely to negatively impact population survival as population size and mate encounter rate decrease. This may be exacerbated if male quality declines and female hunger increases in declining populations. As many top invertebrate predators, such as spiders and mantises, are sexually cannibalistic, this may have ecosystem-wide impacts. We also suggest that other reproductive behaviours, such as rejecting all but high-quality mates or requiring multiple mates to ensure fertility, are also likely to cause mate-finding Allee effects when habitat quality degrades.

All organisms grow. Numerous growth functions have been applied to a wide taxonomic range of organisms, yet some of these models have poor fits to empirical data and lack of flexibility in capturing variation in growth rate. We propose a new VBGF framework that broadens the applicability and increases flexibility of fitting growth curves. This framework offers a curve-fitting procedure for five parameterisations of the VBGF: these allow for different body-size scaling exponents for anabolism (biosynthesis potential), besides the commonly assumed 2/3 power scaling, and allow for supra-exponential growth, which is at times observed. This procedure is applied to twelve species of diverse aquatic invertebrates, including both pelagic and benthic organisms. We reveal widespread variation in the body-size scaling of biosynthesis potential and consequently growth rate, ranging from isomorphic to supra-exponential growth. This curve-fitting methodology offers improved growth predictions and applies the VBGF to a wider range of taxa that exhibit variation in the scaling of biosynthesis potential. Applying this framework results in reliable growth predictions that are important for assessing individual growth, population production and ecosystem functioning, including in the assessment of sustainability of fisheries and aquaculture.

Microalgae contribute 50% to global primary production, most of which is consumed by protozoa. Determining the thermal-sensitivity of this trophic interaction is, therefore, fundamental to predicting impacts of climate change. Here, we question the application of current predictive approaches. Thermal responses are commonly described by the Arrhenius function: r=Ae-EakT, where r is a rate (e.g., growth), A is a scaling factor, E-a is the activation energy, k is the Boltzmann-constant, and T is absolute temperature. The influential metabolic theory of ecology (MTE) proposes that estimates of E-a for heterotrophs and autotrophs are 0.65 eV and 0.32 eV, respectively; when applied to specific growth rate of algae and protozoa, this difference has significant predictive consequences. Through literature review and statistical evaluation, we show that the MTE predictions do not apply to taxon-specific responses of protozoa (n = 103) or algae (n = 183), with mean E-a of 0.71 eV (95% confidence interval [CI]: 0.69-0.74) and 0.61 eV (95% CI: 0.58-0.63), respectively. To obtain these, we fitted a series of models where E-a was constant within a defined group (e.g., protozoa), and the amplitude A depended on the individual responses within the group. Then, by applying the MTE and our predictions to a generic protozoan-algal, predator-prey model we show that: (1) the "canonical" MTE values lead to misrepresenting productivity by several fold; (2) a general response encompassing both groups (0.69 eV) should suffice for such models; and (3) applying our new responses has substantial effects on algal-protozoan population dynamics over temperature shifts of 5 degrees C.

Individual-based models, 'IBMs', describe naturally the dynamics of interacting organisms or social or financial agents. They are considered too complex for mathematical analysis, but computer simulations of them cannot give the general insights required. Here, we resolve this problem with a general mathematical framework for IBMs containing interactions of an unlimited level of complexity, and derive equations that reliably approximate the effects of space and stochasticity. We provide software, specified in an accessible and intuitive graphical way, so any researcher can obtain analytical and simulation results for any particular IBM without algebraic manipulation. We illustrate the framework with examples from movement ecology, conservation biology, and evolutionary ecology. This framework will provide unprecedented insights into a hitherto intractable panoply of complex models across many scientific fields.

We introduce a general theoretical description of a combination of defences acting sequentially at different stages in the predatory sequence in order to make predictions about how animal prey should best allocate investment across different defensive stages. We predict that defensive investment will often be concentrated at stages early in the interaction between a predator individual and the prey (especially if investment is concentrated in only one defence, then it will be in the first defence). Key to making this prediction is the assumption that there is a cost to a prey when it has a defence tested by an enemy, for example because this incurs costs of deployment or tested costs as a defence is exposed to the enemies; and the assumption that the investment functions are the same among defences. But if investment functions are different across defences (e.g. the investment efficiency in making resources into defences is higher in later defences than in earlier defences), then the contrary could happen. The framework we propose can be applied to other victim-exploiter systems, such as insect herbivores feeding on plant tissues. This leads us to propose a novel explanation for the observation that herbivory damage is often not well explained by variation in concentrations of toxic plant secondary metabolites. We compare our general theoretical structure with related examples in the literature, and conclude that coevolutionary approaches will be profitable in future work.

House mice are a major ecosystem pest, particularly threatening island ecosystems as a non-native invasive species. Rapid advances in synthetic biology offer new avenues to control pest species for biodiversity conservation. Recently, a synthetic sperm-killing gene drive construct called t-Sry has been proposed as a means to eradicate target mouse populations owing to a lack of females. A factor that has received little attention in the discussion surrounding such drive applications is polyandry. Previous research has demonstrated that sperm-killing drivers are extremely damaging to a male’s sperm competitive ability. Here, we examine the importance of this effect on the t-Sry system using a theoretical model. We find that polyandry substantially hampers the spread of t-Sry such that release efforts have to be increased three- to sixfold for successful eradication. We discuss the implications of our finding for potential pest control programmes, the risk of drive spread beyond the target population, and the emergence of drive resistance. Our work highlights that a solid understanding of the forces that determine drive dynamics in a natural setting is key for successful drive application, and that exploring the natural diversity of gene drives may inform effective gene drive design.

Some behaviours that typically increase fitness at the individual level may reduce population persistence, particularly in the face of environmental changes. Sexual cannibalism is an extreme mating behaviour which typically involves a male being devoured by the female immediately before, during or after copulation, and is widespread amongst predatory invertebrates. Although the individual-level effects of sexual cannibalism are reasonably well understood, very little is known about the population-level effects. We constructed both a mathematical model and an individual-based model to predict how sexual cannibalism might affect population growth rate and extinction risk. We found that in the absence of any cannibalism-derived fecundity benefit, sexual cannibalism is always detrimental to population growth rate and leads to a higher population extinction risk. Increasing the fecundity benefits of sexual cannibalism leads to a consistently higher population growth rate and likely a lower extinction risk. However, even if cannibalism-derived fecundity benefits are large, very high rates of sexual cannibalism (>70%) can still drive the population to negative growth and potential extinction. Pre-copulatory cannibalism was particularly damaging for population growth rates and was the main predictor of growth declining below the replacement rate. Surprisingly, post-copulatory cannibalism had a largely positive effect on population growth rate when fecundity benefits were present. This study is the first to formally estimate the population-level effects of sexual cannibalism. We highlight the detrimental effect sexual cannibalism may have on population viability if (1) cannibalism rates become high, and/or (2) cannibalism-derived fecundity benefits become low. Decreased food availability could plausibly both increase the frequency of cannibalism, and reduce the fecundity benefit of cannibalism, suggesting that sexual cannibalism may increase the risk of population collapse in the face of environmental change.

The defences used by organisms against predators display a great degree of variability. Defence phenotypes can differ substantially among individuals of the same species, and a single individual can itself deploy a variety of defences. Here, we use a mathematical model that includes mutation and selection to understand the evolutionary origin of this variability in a population of a species that deploys defences sequentially ("first" and "second" defences). Typically, the first defence evolves to have lower variance, i.e. appears more closely accumulated around the ideal phenotype, than the second defence (even when the breaching the first defence incurs more fitness loss than breaching the second defence with the other parameters the same for both defences). However, if the first defence is much less effective in repelling predators, or is much less tolerant of deviation from the ideal phenotype, then the first defence can evolve to have higher variance than the second. Other factors like mutation strength and the losses in the fitness when each defence fails also influence the defence variance. Larger mutation rate incurs larger equilibrium variances, and when the comparative importance in fitness of one defence increases, then the ratio between the variances of this defence and the other defence decreases. Sequentially acting defences are found in many organisms, so we encourage empirical research to test our theoretical predictions.

One of the first successes of neutral ecology was to predict realistically-broad distributions of rare and abundant species. However, it has remained an outstanding theoretical challenge to describe how this distribution of abundances changes with spatial scale, and this gap has hampered attempts to use observed species abundances as a way to quantify what non-neutral processes are needed to fully explain observed patterns. To address this, we introduce a new formulation of spatial neutral biodiversity theory and derive analytical predictions for the way abundance distributions change with scale. For tropical forest data where neutrality has been extensively tested before now, we apply this approach and identify an incompatibility between neutral fits at regional and local scales. We use this approach derive a sharp quantification of what remains to be explained by non-neutral processes at the local scale, setting a quantitative target for more general models for the maintenance of biodiversity.

The competitive exclusion principle is one of the most influential concepts in ecology. The classical formulation suggests a correlation between competitor species similarity and competition severity, leading to rapid competitive exclusion where species are very similar; yet neutral models show that identical species can persist in competition for long periods. Here, we resolve the conflict by examining two components of similarity – niche overlap and competitive similarity – and modeling the effects of each on exclusion rate (defined as the inverse of time to exclusion). Studying exclusion rate, rather than the traditional focus on binary outcomes (coexistence versus exclusion), allows us to examine classical niche and neutral perspectives using the same currency. High niche overlap speeds exclusion, but high similarity in competitive ability slows it. These predictions are confirmed by a well‐known model of two species competing for two resources. Under ecologically plausible scenarios of correlation between these two factors, the strongest exclusion rates may be among moderately similar species, while very similar and highly dissimilar competitors have very low exclusion rates. Adding even small amounts of demographic stochasticity to the model blurs the line between deterministic and probabilistic coexistence still further. Thus, focusing on exclusion rate, instead of on the binary outcome of coexistence versus exclusion, allows a variety of outcomes to result from competitive interactions. This approach may help explain species coexistence in diverse competitive communities and raises novel issues for future work.

Since transgenic crops expressing Bacillus thuringiensis (Bt) toxins were first released, resistance evolution leading to failure in control of pests populations has been observed in a number of species. Field resistance of the moth Busseola fusca was acknowledged 8 years after Bt maize was introduced in South Africa. Since then, field resistance of this corn borer has been observed at several locations, raising questions about the nature, distribution and dynamics of the resistance trait. Using genetic markers, our study identified four outlier loci clearly associated with resistance. In addition, genetic structure at neutral loci reflected extensive gene flow among populations. A realistically parameterised model suggests that resistance could travel in space at speed of several kilometres a year. Markers at outlier loci delineated a geographic region associated with resistance spread. This was an area of approximately 100 km radius, including the location where resistance was first reported. Controlled crosses corroborated these findings and showed significant differences of progeny survival on Bt plants depending on the origin of the resistant parent. Last, our study suggests diverse resistance mutations, which would explain the widespread occurrence of resistant larvae in Bt fields across the main area of maize production in South Africa.

Summary Climate change is a global threat to species, and their capacity to adapt could be limited by habitat fragmentation. Many initiatives to restore habitats, increase connectivity and/or ensure ‘functioning ecological networks’ are explicitly or implicitly trying to address this threat. However, existing methods of analysing networks mainly treat the landscape as static, and it is difficult to use these to plan restoration. We use a recent method to approximate the speed of a species’ range expansion through a landscape by an analogy to an electrical circuit, which takes into account both the rates of colonisation between patches and the rates at which occupied habitat produces new emigrants. Based on this, we propose and test two methods that can help to optimise the spatial arrangement of habitat for range expansion. First, high current flowing through a habitat patch indicates that it should be a priority for conservation, and this can be the basis of an algorithm for iteratively dropping the least valuable patches. Secondly, high power in a link between two patches indicates that it is a bottleneck in the circuit, and this can be the basis of an algorithm for iteratively adding new patches in the most efficient places. We show that these methods perform well for a variety of realistic landscape patterns, assuming known and fixed dispersal ability and source/target locations. The calculations involved for each parameter set are fast enough to be used as building blocks in a larger optimisation for practical planning of landscapes for multiple species. Thus, we lay the foundation for a new genre of systematic conservation planning, which efficiently proposes restoration as well as minimising loss.

Summary A key challenge for both ecological researchers and biodiversity managers is the measurement and prediction of species richness across spatial scales. Typically, biodiversity is assessed at fine scales (e.g. in quadrats or transects) for practical reasons, but often we are interested in coarser‐scale (field, regional, global) diversity issues. Moreover, the pressures affecting biodiversity patterns are often scale specific, making multiscale assessment a crucial methodological priority. As species richness is not additive, it is difficult to translate from the scale of measurement to the scale(s) of interest. A number of methods have been proposed to tackle this problem, but most are too model specific or too rigid to allow general application. Here, we present a general framework (and a specific implementation of it) that allows such scale translations to be performed. Building on the intrinsic relationships among patterns of species richness, abundance and spatial turnover, we introduce a framework that links and predicts the profile of the species‐area relationship and the species‐abundance distributions across scales when a limited number of fine‐scale scattered samples are available. Using the correlation in species' abundances between pairs of samples as a function of the distance between them, we are able to link the effects of aggregation, similarity decay, species richness and species abundances across scales. Our approach allows one to draw inferences about biodiversity scaling under very general assumptions pertaining to the nature of interactions, the geographical distributions of individuals and ecological processes. We demonstrate the accuracy of our predictions using data from two well‐studied forest stands and also demonstrate the potential value of such methods by examining the effects of management on farmland insects across scales. The framework has important applications to biodiversity research and conservation practice.