Pathogen evolution following spillover from a resident to a migrant host population depends on interactions between host pace of life and tolerance to infection.

Changes to migration routes and phenology create novel contact patterns among hosts and pathogens. These novel contact patterns can lead to pathogens spilling over between resident and migrant populations. Predicting the consequences of such pathogen spillover events requires understanding how pathogen evolution depends on host movement behaviour. Following spillover, pathogens may evolve changes in their transmission rate and virulence phenotypes because different strategies are favoured by resident and migrant host populations. There is conflict in current theoretical predictions about what those differences might be. Some theory predicts lower pathogen virulence and transmission rates in migrant populations because migrants have lower tolerance to infection. Other theoretical work predicts higher pathogen virulence and transmission rates in migrants because migrants have more contacts with susceptible hosts. We aim to understand how differences in tolerance to infection and host pace of life act together to determine the direction of pathogen evolution following pathogen spillover from a resident to a migrant population. We constructed a spatially implicit model in which we investigate how pathogen strategy changes following the addition of a migrant population. We investigate how differences in tolerance to infection and pace of life between residents and migrants determine the effect of spillover on pathogen evolution and host population size. When the paces of life of the migrant and resident hosts are equal, larger costs of infection in the migrants lead to lower pathogen transmission rate and virulence following spillover. When the tolerance to infection in migrant and resident populations is equal, faster migrant paces of life lead to increased transmission rate and virulence following spillover. However, the opposite can also occur: when the migrant population has lower tolerance to infection, faster migrant paces of life can lead to decreases in transmission rate and virulence. Predicting the outcomes of pathogen spillover requires accounting for both differences in tolerance to infection and pace of life between populations. It is also important to consider how movement patterns of populations affect host contact opportunities for pathogens. These results have implications for wildlife conservation, agriculture and human health.

Mutualisms impact species' range expansion speeds and spatial distributions.

Species engage in mutually beneficial interspecific interactions (mutualisms) that shape their population dynamics in ecological communities. Species engaged in mutualisms vary greatly in their degree of dependence on their partner from complete dependence (e.g., yucca and yucca moth mutualism) to low dependence (e.g., generalist bee with multiple plant species). While current empirical studies show that, in mutualisms, partner dependence can alter the speed of a species' range expansion, there is no theory that provides conditions when expansion is sped up or slowed down. To address this, we built a spatially explicit model incorporating the population dynamics of two dispersing species interacting mutualistically. We explored how mutualisms impacted range expansion across a gradient of dependence (from complete independence to obligacy) between the two species. We then studied the conditions in which the magnitude of the mutualistic benefits could hinder versus enhance the speed of range expansion. We showed that either complete dependence, no dependence, or intermediate degree of dependence on a mutualist partner can lead to the greatest speeds of a focal species' range expansion based on the magnitude of benefits exchanged between partner species in the mutualism. We then showed how different degrees of dependence between species could alter the spatial distribution of the range expanding populations. Finally, we identified the conditions under which mutualistic interactions can turn exploitative across space, leading to the formation of a species' range limits. Our work highlights how couching mutualisms and mutualist dependence in a spatial context can provide insights about species range expansions, limits, and ultimately their distributions.

A unified evolutionary framework for understanding parasite infection and host migratory behaviour.

Animal migration impacts organismal health and parasite transmission: migrants are simultaneously exposed to parasites and able to reduce infection for both individuals and populations. However, these dynamics are difficult to study; empirical studies reveal disparate results while existing theory makes assumptions that simplify natural complexity. Here, we systematically review empirical studies of migration and infection across taxa, highlighting key gaps in our understanding. Next, we develop a unified evolutionary framework incorporating different selective pressures of parasite-migration interactions while accounting for ecological complexity that goes beyond previous theory. Our framework generates diverse migration-infection patterns paralleling those seen in empirical systems, including partial and differential migration. Finally, we generate predictions about which mechanisms dominate which empirical systems to guide future studies. Our framework provides an overarching understanding of selective pressures shaping migration patterns in the context of animal health and disease, which is critical for predicting how environmental change may threaten migration.

Take me for a ride: Herbivores can facilitate plant reinvasions.

Herbivores shape plant invasions through impacts on demography and dispersal, yet only demographic mechanisms are well understood. Although herbivores negatively impact demography by definition, they can affect dispersal either negatively (e.g., seed consumption), or positively (e.g., caching). Exploring the nuances of how herbivores influence spatial spread will improve the forecasting of plant movement on the landscape. Here, we aim to understand how herbivores impact how fast plant populations spread through varying impacts on plant demography and dispersal. We strive to determine whether, and under what conditions, we see net positive effects of herbivores, in order to find scenarios where herbivores can help to promote spread. We draw on classic invasion theory to develop a stage-structured integrodifference equation model that incorporates herbivore impacts on plant demography and dispersal. We simulate seven herbivore "syndromes" (combinations of demographic and/or dispersal effects) drawn from the literature to understand how increasing herbivore pressure alters plant spreading speed. We find that herbivores with solely negative effects on plant demography or dispersal always slow plant spreading speed, and that the speed slows monotonically as herbivore pressure increases. However, we also find that plant spreading speed can be hump shaped with respect to herbivore pressure: plants spread faster in the presence of herbivores (for low herbivore pressure) and then slower (for high herbivore pressure). This result is robust, occurring across all syndromes in which herbivores have a positive effect on plant dispersal, and is a sign that the positive effects of herbivores on dispersal can outweigh their negative effects on demography. For all syndromes we find that sufficiently high herbivore pressure results in population collapse. Thus, our findings show that herbivores can speed up or slow down plant spread. These insights allow for a greater understanding of how to slow invasions, facilitate native species recolonization, and shape range shifts with global change.

Pushed to the edge: Spatial sorting can slow down invasions.

Our ability to understand population spread dynamics is complicated by rapid evolution, which renders simple ecological models insufficient. If dispersal ability evolves, more highly dispersive individuals may arrive at the population edge than less dispersive individuals (spatial sorting), accelerating spread. If individuals at the low-density population edge benefit (escape competition), high dispersers have a selective advantage (spatial selection). These two processes are often described as forming a positive feedback loop; they reinforce each other, leading to faster spread. Although spatial sorting is close to universal, this form of spatial selection is not: low densities can be detrimental for organisms with Allee effects. Here, we present two conceptual models to explore the feedback loops that form between spatial sorting and spatial selection. We show that the presence of an Allee effect can reverse the positive feedback loop between spatial sorting and spatial selection, creating a negative feedback loop that slows population spread.

Gaps in modelling animal migration with evolutionary game theory: infection can favour the loss of migration.

Ongoing environmental changes alter how natural selection shapes animal migration. Understanding how these changes play out theoretically can be done using evolutionary game theoretic (EGT) approaches, such as looking for evolutionarily stable strategies. Here, we first describe historical patterns of how EGT models have explored different drivers of migration. We find that there are substantial gaps in both the taxa (mammals, amphibians, reptiles, insects) and mechanisms (mutualism, interspecific competition) included in past EGT models of migration. Although enemy interactions, including parasites, are increasingly considered in models of animal migration, they remain the least studied of factors for migration considered to date. Furthermore, few papers look at changes in migration in response to perturbations (e.g. climate change, new species interactions). To address this gap, we present a new EGT model to understand how infection with a novel parasite changes host migration. We find three possible outcomes when migrants encounter novel parasites: maintenance of migration (despite the added infection cost), loss of migration (evolutionary shift to residency) or population collapse, depending on the risk and cost of getting infected, and the cost currency. Our work demonstrates how emerging infection can alter animal behaviour such as migration. This article is part of the theme issue 'Half a century of evolutionary games: a synthesis of theory, application and future directions'.

How to study parasites and host migration: a roadmap for empiricists.

Animal migration (round-trip, predictable movements) takes individuals across space and time, bringing them into contact with new communities of organisms. In particular, migratory movements shape (and are shaped by) the costs and risk of parasite transmission. Unfortunately, our understanding of how migration and parasite infection interact has not proceeded evenly. Although numerous conceptual frameworks (e.g. mathematical models) have been developed, most empirical evidence of migration-parasite interactions are drawn from pre-existing empirical studies that were conducted using other conceptual frameworks, which limits our understanding. Here, we synthesise and analyse existing work, and then provide a roadmap for future (especially empirical) studies. First, we synthesise the conceptual frameworks that have been developed to understand interactions between migration and parasites (e.g. migratory exposure, escape, allopatry, recovery, culling, separation, stalling and relapse). Second, we highlight current challenges to studying migration and parasites empirically, and to integrating empirical and theoretical perspectives, particularly emphasizing the challenge of feedback loops. Finally, we provide a guide to overcoming these challenges in empirical studies, using comparative, observational and experimental approaches. Beyond guiding future empirical work, this review aims to inspire stronger collaboration between empiricists and theorists studying the intersection of migration and parasite infection. Such collaboration will help overcome current limits to our understanding of how migration and parasites interact, and allow us to predict how these critical ecological processes will change in the future.

Differential retention contributes to racial/ethnic disparity in U.S. academia.

Several racial and ethnic identities are widely understood to be under-represented within academia, however, actual quantification of this under-representation is surprisingly limited. Challenges include data availability, demographic inertia and identifying comparison points. We use de-aggregated data from the U.S. National Science Foundation to construct a null model of ethnic and racial representation in one of the world's largest academic communities. Making comparisons between our model and actual representation in academia allows us to measure the effects of retention (while controlling for recruitment) at different academic stages. We find that, regardless of recruitment, failed retention contributes to mis-representation across academia and that the stages responsible for the largest disparities differ by race and ethnicity: for Black and Hispanic scholars this occurs at the transition from graduate student to postdoctoral researcher whereas for Native American/Alaskan Native and Native Hawaiian/Pacific Islander scholars this occurs at transitions to and within faculty stages. Even for Asian and Asian-Americans, often perceived as well represented, circumstances are complex and depend on choice of baseline. Our findings demonstrate that while recruitment continues to be important, retention is also a pervasive barrier to proportional representation. Therefore, strategies to reduce mis-representation in academia must address retention. Although our model does not directly suggest specific strategies, our framework could be used to project how representation in academia might change in the long-term under different scenarios.

Let's move out together: a framework for the intersections between movement and mutualism.

Movement is a widespread behavior across organisms and is driven in part by interspecific interactions. Generally, negative interspecific interactions (such as competition and natural enemies) are more often studied in the context of movement than positive interactions (mutualism). Mutualistic relationships are incredibly common, yet only a subset are studied in the context of movement (transportation mutualisms). Overall, the costs and benefits that an individual experiences are shaped both by their movement behavior and their mutualistic relationships, as well as the intersection between these. Here we argue that the intersection between movement behavior and mutualistic relationships is understudied, and we present a conceptual framework to synthesize the links between movement and mutualisms and give examples of species that exhibit each. Our framework serves both to highlight the ways that mutualism can shape movement (and vice versa) and to draw parallels across different organisms (enabling a more abstract perspective of these biological systems, complementing the system-focused perspective). Finally, we show how considering movement in light of mutualisms (and vice versa) presents a number of new research questions to be answered by each empirical and theoretical approach going forward.

Migration and tolerance shape host behaviour and response to parasite infection.

Numerous theoretical models have demonstrated that migration, a seasonal animal movement behaviour, can minimize the risks and costs of parasite infection. Past work on migration-infection interactions assumes migration is the only strategy available to organisms for dealing with the parasite infection, that is they migrate to a different environment to recover or escape from infection. Thus, migration is similar to the non-spatial strategy of resistance, where hosts prevent infection or kill parasites once infected. However, an alternative defence strategy is to tolerate the infection and experience a lower cost to the infection. To our knowledge, no studies have examined how migration can change based on combining two host strategies (migration and tolerance) for dealing with parasites. In this paper, we aim to understand how both parasite transmission and infection tolerance can influence the host's migratory behaviour. We constructed a model that incorporates two host strategies (migration and tolerance) to understand whether allowing for tolerance affects the proportion of the population that migrates at equilibrium in response to infection. We show that the benefits of tolerance can either decrease or increase the host's migration. Also, if the benefit of migration is great, then individuals are more likely to migrate regardless of the presence of tolerance. Finally, we find that the transmission rate of parasite infection can either decrease or increase the tolerant host's migration, depending on the cost of migration. These findings highlight that adopting two defence strategies is not always beneficial to the hosts. Instead, a single strategy is often better, depending on the costs and benefits of the strategies and infection pressures. Our work further suggests that multiple host-defence strategies as a potential explanation for the evolution of migration to minimize the parasite infection. Moreover, migration can also affect the ecological and evolutionary dynamics of parasite-host interactions.

Pliant pathogens: Estimating viral spread when confronted with new vector, host, and environmental conditions.

Pathogen spread rates are determined, in part, by the performance of pathogens under altered environmental conditions and their ability to persist while switching among hosts and vectors.To determine the effects of new conditions (host, vector, and nutrient) on pathogen spread rate, we introduced a vector-borne viral plant pathogen, Barley Yellow Dwarf Virus PAV (BYDV-PAV) into hosts, vectors, and host nutrient supplies that it had not encountered for thousands of viral generations. We quantified pathogen prevalence over the course of two serial inoculations under the new conditions. Using individual-level transmission rates from this experiment, we parameterized a dynamical model of disease spread and projected spread across host populations through a growing season.A change in nutrient conditions (increased supply of phosphorus) reduced viral transmission whereas shifting to a new vector or host species had no effect on infection prevalence. However, the reduction in the new nutrient environment was only temporary; infection prevalence recovered after the second inoculation. Synthesis. These results highlight how robust the pathogen, BYDV-PAV, is to changes in its biotic and abiotic environment. Our study also highlights the need to quantify longitudinal infection information beyond snapshot assessments to project disease risk for pathogens in new environments.

Lessons from movement ecology for the return to work: Modeling contacts and the spread of COVID-19.

Human behavior (movement, social contacts) plays a central role in the spread of pathogens like SARS-CoV-2. The rapid spread of SARS-CoV-2 was driven by global human movement, and initial lockdown measures aimed to localize movement and contact in order to slow spread. Thus, movement and contact patterns need to be explicitly considered when making reopening decisions, especially regarding return to work. Here, as a case study, we consider the initial stages of resuming research at a large research university, using approaches from movement ecology and contact network epidemiology. First, we develop a dynamical pathogen model describing movement between home and work; we show that limiting social contact, via reduced people or reduced time in the workplace are fairly equivalent strategies to slow pathogen spread. Second, we develop a model based on spatial contact patterns within a specific office and lab building on campus; we show that restricting on-campus activities to labs (rather than labs and offices) could dramatically alter (modularize) contact network structure and thus, potentially reduce pathogen spread by providing a workplace mechanism to reduce contact. Here we argue that explicitly accounting for human movement and contact behavior in the workplace can provide additional strategies to slow pathogen spread that can be used in conjunction with ongoing public health efforts.

Consequences of ignoring dispersal variation in network models for landscape connectivity.

Habitat loss and fragmentation can negatively influence population persistence and biodiversity, but the effects can be mitigated if species successfully disperse between isolated habitat patches. Network models are the primary tool for quantifying landscape connectivity, yet in practice, an overly simplistic view of species dispersal is applied. These models often ignore individual variation in dispersal ability under the assumption that all individuals move the same fixed distance with equal probability. We developed a modeling approach to address this problem. We incorporated dispersal kernels into network models to determine how individual variation in dispersal alters understanding of landscape-level connectivity and implemented our approach on a fragmented grassland landscape in Minnesota. Ignoring dispersal variation consistently overestimated a population's robustness to local extinctions and underestimated its robustness to local habitat loss. Furthermore, a simplified view of dispersal underestimated the amount of habitat substructure for small populations but overestimated habitat substructure for large populations. Our results demonstrate that considering biologically realistic dispersal alters understanding of landscape connectivity in ecological theory and conservation practice.

Consecuencias de la Omisión de la Variación en la Dispersión en los Modelos de Redes para la Conectividad de Paisajes Resumen La pérdida y la fragmentación del hábitat pueden influir negativamente la persistencia de poblaciones y biodiversidad. Sin embargo, estos efectos pueden ser mitigados si las especies tienen una dispersión exitosa entre los fragmentos aislados de hábitat. Los modelos de redes son la herramienta principal para la cuantificación de la conectividad del paisaje, no obstante en la práctica, se tiende a usar una visión excesivamente simplista de la dispersión de especies. Es común que estos modelos ignoren la variación que existe entre individuos en sus habilidades de dispersión y que asuman que todos los individuos se pueden mover la misma distancia y con la misma probabilidad. En este estudio, desarrollamos una estrategia de modelaje para (minimizar o aminorar) estas limitaciones incorporando kernels de dispersión dentro de los modelos de redes para determinar cómo la variación individual de la dispersión altera el entendimiento de la conectividad a nivel de paisaje. Como un ejemplo, implementamos esta estrategia en un paisaje de pastizal fragmentado en Minnesota. Omitir la variación en la dispersión generó una sobreestimación sistemática de la robustez de la población ante las extinciones locales y una subestimación de la robustez ante la pérdida local del hábitat. Además, una visión simplificada de la dispersión subestimó la complejidad de hábitat para las poblaciones pequeñas, sin emgargo sobreestimó la complejidad para las poblaciones grandes. Nuestros resultados demuestran que incorporar parámetros que describan una dispersión biológica realista tiene implicaciones importantes en la teoría de conectividad de paisajes e implementación de practicas de conservación.

Parasite intensity and the evolution of migratory behavior.

Migration can allow individuals to escape parasite infection, which can lead to a lower infection probability (prevalence) in a population and/or fewer parasites per individual (intensity). Because individuals with more parasites often have lower survival and/or fecundity, infection intensity shapes the life-history trade-offs determining when migration is favored as a strategy to escape infection. Yet, most theory relies on susceptible-infected (SI) modeling frameworks, defining individuals as either healthy or infected, ignoring details of infection intensity. Here, we develop a novel modeling approach that captures infection intensity as a spectrum, and ask under what conditions migration evolves as function of how infection intensity changes over time. We show that relative timescales of migration and infection accumulation determine when migration is favored. We also find that population-level heterogeneity in infection intensity can lead to partial migration, where less-infected individuals migrate while more infected individuals remain resident. Our model is one of the first to consider how infection intensity can lead to migration. Our results frame migratory escape in light of infection intensity rather than prevalence, thus demonstrating that decreased infection intensity should be considered a benefit of migration, alongside other typical drivers of migration.

Orchard layout and plant traits influence fruit yield more strongly than pollinator behaviour and density in a dioecious crop.

Mutualistic plant-pollinator interactions are critical for the functioning of both non-managed and agricultural systems. Mathematical models of plant-pollinator interactions can help understand key determinants in pollination success. However, most previous models have not addressed pollinator behavior and plant biology combined. Information generated from such a model can inform optimal design of crop orchards and effective utilization of managed pollinators like western honey bees (Apis mellifera), and help generate hypotheses about the effects of management practices and cultivar selection. We expect that the number of honey bees per flower and male to female flower ratio will influence fruit yield. To test the relative importance of these effects, both singly and simultaneously, we utilized a delay differential equation model combined with Latin hypercube sampling for sensitivity analysis. Empirical data obtained from historical records and collected in kiwifruit (Actinidia chinensis) orchards in New Zealand were used to parameterize the model. We found that, at realistic bee densities, the optimal orchard had 65-75% female flowers, and the most benefit was gained from the first 6-8 bees/1000 flowers, with diminishing returns thereafter. While bee density significantly impacted fruit production, plant-based parameters-flower density and male:female flower ratio-were the most influential. The predictive model provides strategies for improving crop management, such as choosing cultivars which have their peak bloom on the same day, increasing the number of flowers with approximately 70% female flowers in the orchard, and placing enough hives to maintain more than 6 bees per 1000 flowers to optimize yield.

Eco-evolutionary dynamics of range expansion.

Understanding the movement of species' ranges is a classic ecological problem that takes on urgency in this era of global change. Historically treated as a purely ecological process, range expansion is now understood to involve eco-evolutionary feedbacks due to spatial genetic structure that emerges as populations spread. We synthesize empirical and theoretical work on the eco-evolutionary dynamics of range expansion, with emphasis on bridging directional, deterministic processes that favor evolved increases in dispersal and demographic traits with stochastic processes that lead to the random fixation of alleles and traits. We develop a framework for understanding the joint influence of these processes in changing the mean and variance of expansion speed and its underlying traits. Our synthesis of recent laboratory experiments supports the consistent role of evolution in accelerating expansion speed on average, and highlights unexpected diversity in how evolution can influence variability in speed: results not well predicted by current theory. We discuss and evaluate support for three classes of modifiers of eco-evolutionary range dynamics (landscape context, trait genetics, and biotic interactions), identify emerging themes, and suggest new directions for future work in a field that stands to increase in relevance as populations move in response to global change.

Recovery from infection is more likely to favour the evolution of migration than social escape from infection.

Pathogen and parasite infections are increasingly recognized as powerful drivers of animal movement, including migration. Yet, infection-related migration benefits can result from a combination of environmental and/or social conditions, which can be difficult to disentangle. Here, we focus on two infection-related mechanisms that can favour migration: moving to escape versus recover from infection. By directly comparing the evolution of migration in response to each mechanism, we can evaluate the likely importance of changing abiotic conditions (linked to migratory recovery) with changing social conditions (linked to migratory escape) in terms of infection-driven migration. We built a mathematical model and analysed it using numerically simulated adaptive dynamics to determine when migration should evolve for each migratory recovery and social migratory escape. We found that a higher fraction of the population migrated under migratory recovery than under social migratory escape. We also found that two distinct migratory strategies (e.g. some individuals always migrate and others only occasionally migrate) sometimes coexisted within populations with social migratory escape, but never with migratory recovery. Our results suggest that migratory recovery is more likely to promote the evolution of migratory behaviour, rather than escape from infected conspecifics (social migratory escape).

Causes and consequences of individual variation in animal movement.

Animal movement comes in a variety of 'types' including small foraging movements, larger one-way dispersive movements, seasonally-predictable round-trip migratory movements, and erratic nomadic movements. Although most individuals move at some point throughout their lives, movement patterns can vary widely across individuals within the same species: differing within an individual over time (intra-individual), among individuals in the same population (inter-individual), or among populations (inter-population). Yet, studies of movement (theoretical and empirical alike) more often focus on understanding 'typical' movement patterns than understanding variation in movement. Here, I synthesize current knowledge of movement variation (drawing parallels across species and movement types), describing the causes (what factors contribute to individual variation), patterns (what movement variation looks like), consequences (why variation matters), maintenance (why variation persists), implications (for management and conservation), and finally gaps (what pieces we are currently missing). By synthesizing across scales of variation, I span across work on plasticity, personality, and geographic variation. Individual movement can be driven by factors that act at the individual, population, community and ecosystem level and have ramifications at each of these levels. Generally the consequences of movement are less well understood than the causes, in part because the effects of movement variation are often nested, with variation manifesting at the population level, which in turn affects communities and ecosystems. Understanding both cause and consequence is particularly important for predicting when variation begets variation in a positive feedback loop, versus when a negative feedback causes variation to be dampened successively. Finally, maintaining standing variation in movement may be important for facilitating species' ability to respond to future environmental change.

Trait plasticity alters the range of possible coexistence conditions in a competition-colonisation trade-off.

Most of the classical theory on species coexistence has been based on species-level competitive trade-offs. However, it is becoming apparent that plant species display high levels of trait plasticity. The implications of this plasticity are almost completely unknown for most coexistence theory. Here, we model a competition-colonisation trade-off and incorporate trait plasticity to evaluate its effects on coexistence. Our simulations show that the classic competition-colonisation trade-off is highly sensitive to environmental circumstances, and coexistence only occurs in narrow ranges of conditions. The inclusion of plasticity, which allows shifts in competitive hierarchies across the landscape, leads to coexistence across a much broader range of competitive and environmental conditions including disturbance levels, the magnitude of competitive differences between species, and landscape spatial patterning. Plasticity also increases the number of species that persist in simulations of multispecies assemblages. Plasticity may generally increase the robustness of coexistence mechanisms and be an important component of scaling coexistence theory to higher diversity communities.

Increasing growth rate slows adaptation when genotypes compete for diffusing resources.

The rate at which a species responds to natural selection is a central predictor of the species' ability to adapt to environmental change. It is well-known that spatially-structured environments slow the rate of adaptation due to increased intra-genotype competition. Here, we show that this effect magnifies over time as a species becomes better adapted and grows faster. Using a reaction-diffusion model, we demonstrate that growth rates are inextricably coupled with effective spatial scales, such that higher growth rates cause more localized competition. This has two effects: selection requires more generations for beneficial mutations to fix, and spatially-caused genetic drift increases. Together, these effects diminish the value of additional growth rate mutations in structured environments.