Demographic rates reveal the benefits of protected areas in a long-lived migratory bird.

Recent studies have suggested that protected areas often fail to conserve target species. However, the efficacy of terrestrial protected areas is difficult to measure, especially for highly vagile species like migratory birds that may move between protected and unprotected areas throughout their lives. Here, we use a 30-y dataset of detailed demographic data from a migratory waterbird, the Whooper swan (Cygnus cygnus), to assess the value of nature reserves (NRs). We assess how demographic rates vary at sites with varying levels of protection and how they are influenced by movements between sites. Swans had a lower breeding probability when wintering inside NRs than outside but better survival for all age classes, generating a 30-fold higher annual growth rate within NRs. There was also a net movement of individuals from NRs to non-NRs. By combining these demographic rates and estimates of movement (into and out of NRs) into population projection models, we show that the NRs should help to double the population of swans wintering in the United Kingdom by 2030. These results highlight the major effect that spatial management can have on species conservation, even when the areas protected are relatively small and only used during short periods of the life cycle.

Fast-slow continuum and reproductive strategies structure plant life-history variation worldwide.

The identification of patterns in life-history strategies across the tree of life is essential to our prediction of population persistence, extinction, and diversification. Plants exhibit a wide range of patterns of longevity, growth, and reproduction, but the general determinants of this enormous variation in life history are poorly understood. We use demographic data from 418 plant species in the wild, from annual herbs to supercentennial trees, to examine how growth form, habitat, and phylogenetic relationships structure plant life histories and to develop a framework to predict population performance. We show that 55% of the variation in plant life-history strategies is adequately characterized using two independent axes: the fast-slow continuum, including fast-growing, short-lived plant species at one end and slow-growing, long-lived species at the other, and a reproductive strategy axis, with highly reproductive, iteroparous species at one extreme and poorly reproductive, semelparous plants with frequent shrinkage at the other. Our findings remain consistent across major habitats and are minimally affected by plant growth form and phylogenetic ancestry, suggesting that the relative independence of the fast-slow and reproduction strategy axes is general in the plant kingdom. Our findings have similarities with how life-history strategies are structured in mammals, birds, and reptiles. The position of plant species populations in the 2D space produced by both axes predicts their rate of recovery from disturbances and population growth rate. This life-history framework may complement trait-based frameworks on leaf and wood economics; together these frameworks may allow prediction of responses of plants to anthropogenic disturbances and changing environments.

Contact networks structured by sex underpin sex-specific epidemiology of infection.

Contact networks are fundamental to the transmission of infection and host sex often affects the acquisition and progression of infection. However, the epidemiological impacts of sex-related variation in animal contact networks have rarely been investigated. We test the hypothesis that sex-biases in infection are related to variation in multilayer contact networks structured by sex in a population of European badgers Meles meles naturally infected with Mycobacterium bovis. Our key results are that male-male and between-sex networks are structured at broader spatial scales than female-female networks and that in male-male and between-sex contact networks, but not female-female networks, there is a significant relationship between infection and contacts with individuals in other groups. These sex differences in social behaviour may underpin male-biased acquisition of infection and may result in males being responsible for more between-group transmission. This highlights the importance of sex-related variation in host behaviour when managing animal diseases.

Using Social Network Measures in Wildlife Disease Ecology, Epidemiology, and Management.

Contact networks, behavioral interactions, and shared use of space can all have important implications for the spread of disease in animals. Social networks enable the quantification of complex patterns of interactions; therefore, network analysis is becoming increasingly widespread in the study of infectious disease in animals, including wildlife. We present an introductory guide to using social-network-analytical approaches in wildlife disease ecology, epidemiology, and management. We focus on providing detailed practical guidance for the use of basic descriptive network measures by suggesting the research questions to which each technique is best suited and detailing the software available for each. We also discuss how using network approaches can be used beyond the study of social contacts and across a range of spatial and temporal scales. Finally, we integrate these approaches to examine how network analysis can be used to inform the implementation and monitoring of effective disease management strategies.

Integrated population modelling reveals a perceived source to be a cryptic sink.

Demographic links among fragmented populations are commonly studied as source-sink dynamics, whereby source populations exhibit net recruitment and net emigration, while sinks suffer net mortality but enjoy net immigration. It is commonly assumed that large, persistent aggregations of individuals must be sources, but this ignores the possibility that they are sinks instead, buoyed demographically by immigration. We tested this assumption using Bayesian integrated population modelling of Greenland white-fronted geese (Anser albifrons flavirostris) at their largest wintering site (Wexford, Ireland), combining capture-mark-recapture, census and recruitment data collected from 1982 to 2010. Management for this subspecies occurs largely on wintering areas; thus, study of source-sink dynamics of discrete regular wintering units provides unprecedented insights into population regulation and enables identification of likely processes influencing population dynamics at Wexford and among 70 other Greenland white-fronted goose wintering subpopulations. Using results from integrated population modelling, we parameterized an age-structured population projection matrix to determine the contribution of movement rates (emigration and immigration), recruitment and mortality to the dynamics of the Wexford subpopulation. Survival estimates for juvenile and adult birds at Wexford and adult birds elsewhere fluctuated over the 29-year study period, but were not identifiably different. However, per capita recruitment rates at Wexford in later years (post-1995) were identifiably lower than in earlier years (pre-1995). The observed persistence of the Wexford subpopulation was only possible with high rates of immigration, which exceeded emigration in each year. Thus, despite its apparent stability, Wexford has functioned as a sink over the entire study period. These results demonstrate that even large subpopulations can potentially be sinks, and that movement dynamics (e.g. immigration) among winters can dramatically obscure key processes driving subpopulation size. Further, novel population models which integrate capture-mark-recapture, census and recruitment data are essential to correctly ascribing source-sink status and accurately informing development of site-safeguard networks.

Should I stay or should I go? Fitness costs and benefits of prolonged parent-offspring and sibling-sibling associations in an Arctic-nesting goose population.

Theory predicts persistence of long-term family relationships in vertebrates will occur until perceived fitness costs exceed benefits to either parents or offspring. We examined whether increased breeding probability and survival were associated with prolonged parent-offspring and sibling-sibling relationships in a long-lived Arctic migrant herbivore, the Greenland white-fronted goose (Anser albifrons flavirostris). Although offspring associated with parents for 1-13 years, 79 % of these associations lasted two or less years. Only 65 (9.9 %) of the 656 marked offspring bred once in their lifetime, and just 16 (2.4 %) bred twice or more. The probability of birds with siblings breeding successfully in a subsequent year was credibly greater than that of independent birds at ages 5, 6, and 7. Survival of offspring with parents was credibly greater than that of independent/nonbreeder birds at all possible ages (i.e., ages 2-7+). A cost-benefit matrix model utilizing breeding and survival probabilities showed that staying with family groups was favored over leaving until age 3, after which there were no credible differences between staying and leaving strategies until the oldest ages, when leaving family groups was favored. Thus, most birds in this study either departed family groups early (e.g., at age 2, when the "stay" strategy was favored) or as predicted by our cost-benefit model (i.e., at age 3). Although extended family associations are a feature of this population, we contend that the survival benefits are not sufficient enough to yield clear fitness benefits, and associations only persist because parents and offspring mutually benefit from their persistence.

Seed bank dynamics govern persistence of Brassica hybrids in crop and natural habitats.

BACKGROUND AND AIMS: Gene flow from crops to their wild relatives has the potential to alter population growth rates and demography of hybrid populations, especially when a new crop has been genetically modified (GM). This study introduces a comprehensive approach to assess this potential for altered population fitness, and uses a combination of demographic data in two habitat types and mathematical (matrix) models that include crop rotations and outcrossing between parental species. METHODS: Full life-cycle demographic rates, including seed bank survival, of non-GM Brassica rapa × B. napus F1 hybrids and their parent species were estimated from experiments in both agricultural and semi-natural habitats. Altered fitness potential was modelled using periodic matrices including crop rotations and outcrossing between parent species. KEY RESULTS: The demographic vital rates (i.e. for major stage transitions) of the hybrid population were intermediate between or lower than both parental species. The population growth rate (λ) of hybrids indicated decreases in both habitat types, and in a semi-natural habitat hybrids became extinct at two sites. Elasticity analyses indicated that seed bank survival was the greatest contributor to λ. In agricultural habitats, hybrid populations were projected to decline, but with persistence times up to 20 years. The seed bank survival rate was the main driver determining persistence. It was found that λ of the hybrids was largely determined by parental seed bank survival and subsequent replenishment of the hybrid population through outcrossing of B. rapa with B. napus. CONCLUSIONS: Hybrid persistence was found to be highly dependent on the seed bank, suggesting that targeting hybrid seed survival could be an important management option in controlling hybrid persistence. For local risk mitigation, an increased focus on the wild parent is suggested. Management actions, such as control of B. rapa, could indirectly reduce hybrid populations by blocking hybrid replenishment.

Social evolution of toxic metal bioremediation in Pseudomonas aeruginosa.

Bacteria are often iron-limited, and hence produce extracellular iron-scavenging siderophores. A crucial feature of siderophore production is that it can be an altruistic behaviour (individually costly but benefitting neighbouring cells), thus siderophore producers can be invaded by non-producing social 'cheats'. Recent studies have shown that siderophores can also bind other heavy metals (such as Cu and Zn), but in this case siderophore chelation actually reduces metal uptake by bacteria. These complexes reduce heavy metal toxicity, hence siderophore production may contribute to toxic metal bioremediation. Here, we show that siderophore production in the context of bioremediation is also an altruistic trait and can be exploited by cheating phenotypes in the opportunistic pathogen Pseudomonas aeruginosa. Specifically, we show that in toxic copper concentrations (i) siderophore non-producers evolve de novo and reach high frequencies, and (ii) producing strains are fitter than isogenic non-producing strains in monoculture, and vice versa in co-culture. Moreover, we show that the evolutionary effect copper has on reducing siderophore production is greater than the reduction observed under iron-limited conditions. We discuss the relevance of these results to the evolution of siderophore production in natural communities and heavy metal bioremediation.

An unbiased method for clustering bacterial effectors using host cellular phenotypes.

We present a novel method implementing unbiased high-content morphometric cell analysis to classify bacterial effector phenotypes. This clustering methodology represents a significant advance over more qualitative visual approaches and can also be used to classify, and therefore predict the likely function of, unknown effector genes from any microbial genome. As a proof of concept, we use this approach to investigate 23 genetic regions predicted to encode antimacrophage effectors located across the genome of the insect and human pathogen Photorhabdus asymbiotica. Statistical cluster analysis using multiple cellular measures categorized treated macrophage phenotypes into three major groups relating to their putative functionality: (i) adhesins, (ii) cytolethal toxins, and (iii) cytomodulating toxins. Further investigation into their effects on phagocytosis revealed that several effectors also modulate this function and that the nature of this modulation (increased or decreased phagocytosis) is linked to the phenotype cluster group. Categorizing potential functionalities in this way allows rapid functional follow-up of key candidates for more-directed cell biological or biochemical investigation. Such an unbiased approach to the classification of candidate effectors will be useful for describing virulence-related regions in a wide range of genomes and will be useful in assigning putative functions to the growing number of microbial genes whose function remains unclear from homology searching.

Predictive systems ecology.

Human societies, and their well-being, depend to a significant extent on the state of the ecosystems that surround them. These ecosystems are changing rapidly usually in response to anthropogenic changes in the environment. To determine the likely impact of environmental change on ecosystems and the best ways to manage them, it would be desirable to be able to predict their future states. We present a proposal to develop the paradigm of predictive systems ecology, explicitly to understand and predict the properties and behaviour of ecological systems. We discuss the necessary and desirable features of predictive systems ecology models. There are places where predictive systems ecology is already being practised and we summarize a range of terrestrial and marine examples. Significant challenges remain but we suggest that ecology would benefit both as a scientific discipline and increase its impact in society if it were to embrace the need to become more predictive.

What has biotelemetry ever done for avian translocations?

Species translocation is a popular approach in contemporary ecological restoration and rewilding. Improving the efficacy of conservation translocation programmes requires a combination of robust data from comparable populations, population viability modelling and post-release monitoring. Biotelemetry is becoming an ever more accessible means to collect some of the high-resolution information on the ecology and behaviour of founding populations that such evaluations require. Here, we review 81 published case studies to consider how this capability could increase the success of avian translocations. We found that 67 translocations favoured traditional radio telemetry, with surveillance focussing mostly on immediate post-release dispersal, survival and breeding attempts. Just 28 projects tracked founder individuals for longer than 1 year and no studies referenced pre-release sampling or planning using biotelemetry. While our review shows that tracking devices have been deployed extensively in translocation projects, its application has been mostly limited to short-term spatial and demographic monitoring. We conclude that biotelemetry is a powerful tool for harnessing a multitude of lifetime eco-behavioural data which can be used to build valuable predictive models and surveillance programmes, but this capability has yet to be fully realised by researchers in avian translocations.

Differentiated Social Relationships and the Pace-of-Life-History.

When selection is imposed by both social and ecological environments, the costs and benefits of social relationships can depend on life-history strategy. We argue that the formation and maintenance of differentiated social relationships will prevail in species and individuals with slow life histories. Social behaviours that benefit survival can promote slower life histories. Meanwhile, longer lifespan promotes the development of strong and stable social bonds by allowing fitness payoffs to be postponed. Differentiated social behaviours should be favoured for fast life histories only when they promote the rate of reproduction. Finally, associations between life-history strategies and other traits (e.g., personality) provide a mechanism to drive inter-individual variation in social relationships, making life-history important for sociality across taxonomic scales.

Life history and population regulation shape demographic competence and influence the maintenance of endemic disease.

Host life history and demography play important roles in host-pathogen dynamics, by influencing the ability of hosts and their pathogens to coexist. We introduce the concept of demographic competence to describe the ability of host populations to sustain endemic infectious disease. Hosts with high demographic competence are more likely to act as keystone hosts and constitute reservoirs of infection that can spill over into other species. We propose that the pace of host life history will interact with pathogen life history to influence demographic competence. Our models demonstrate that slow-living hosts (with high survival and low recruitment rates) have greater demographic competence than fast-living hosts (with low survival and high recruitment rates) for susceptible-infected disease dynamics, although this difference is reduced when populations of slow hosts are age structured. Demographic competence is generally greater among hosts with populations regulated by survival compared to reproduction, but this difference is smallest among slow life histories and reversed for some pathogens with frequency-dependent transmission. An association between pathogen life history traits and the demographic competence of faster-living hosts also has implications for trade-offs between pathogen virulence and transmissibility. Overall, we demonstrate how host life history traits can help predict wildlife reservoirs of zoonoses and the vulnerability of populations to disease-induced extinction.

Group size and modularity interact to shape the spread of infection and information through animal societies.

Social interactions between animals can provide many benefits, including the ability to gain useful environmental information through social learning. However, these social contacts can also facilitate the transmission of infectious diseases through a population. Animals engaging in social interactions therefore face a trade-off between the potential informational benefits and the risk of acquiring disease. Theoretical models have suggested that modular social networks, associated with the formation of groups or sub-groups, can slow spread of infection by trapping it within particular groups. However, these social structures will not necessarily impact the spread of information in the same way if its transmission follows a "complex contagion", e.g. through individuals disproportionally copying the majority (conformist learning). Here we use simulation models to demonstrate that modular networks can promote the spread of information relative to the spread of infection, but only when the network is fragmented and group sizes are small. We show that the difference in transmission between information and disease is maximised for more well-connected social networks when the likelihood of transmission is intermediate. Our results have important implications for understanding the selective pressures operating on the social structure of animal societies, revealing that highly fragmented networks such as those formed in fission-fusion social groups and multilevel societies can be effective in modulating the infection-information trade-off for individuals within them. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s00265-021-03102-4.

Sexual selection on the genital lobes of male Drosophila simulans.

Sexual selection is thought to be responsible for the rapid divergent evolution of male genitalia with several studies detecting multivariate sexual selection on genital form. However, in most cases, selection is only estimated during a single episode of selection, which provides an incomplete view of net selection on genital traits. Here, we estimate the strength and form of multivariate selection on the genitalia arch of Drosophila simulans when mating occurs in the absence of a competitor and during sperm competition, in both sperm defence and offense roles (i.e., when mating first and last). We found that the strength of sexual selection on the genital arch was strongest during noncompetitive mating and weakest during sperm offense. However, the direction of selection was similar across selection episodes with no evidence for antagonistic selection. Overall, selection was not particularly strong despite genitals clearly evolving rapidly in this species.

Cultural inheritance drives site fidelity and migratory connectivity in a long-distance migrant.

Cultural transmission is thought to be a mechanism by which migratory animals settle into habitats, but little evidence exists in wild populations because of the difficulty of following individuals over successive generations and wide geographical distances. Cultural inheritance of migration routes represents a mechanism whereby geographical isolation can arise between separate groups and could constrain individuals to potentially suboptimal sites within their range. Conversely, adopting the parental migratory route in adult life, rather than dispersing randomly, may increase an individual's reproductive success because that strategy has already been proven to allow successful breeding. We combined a pedigree of related light-bellied Brent geese (Branta bernicla hrota) with 6 years of observations of marked birds to calculate the dispersal distances of adult offspring from their parents in both Ireland and Iceland. In both countries, the majority of offspring were found to recruit into or near their parental sites, indicating migratory connectivity in the flyway. Despite this kin structure, we found no evidence of genetic differentiation using genotype data from 1127 individuals across 15 microsatellite loci. We suggest that the existence of migratory connectivity of subpopulations is far more common than previous research indicates and that cultural information may play an important role in structuring reproductive isolation among them.

Human-mediated dispersal and disturbance shape the metapopulation dynamics of a long-lived herb.

As anthropogenic impacts on the natural world escalate, there is increasing interest in the role of humans in dispersing seeds. But the consequences of this Human-Mediated Dispersal (HMD) on plant spatial dynamics are little studied. In this paper, we ask how secondary dispersal by HMD affects the dynamics of a natural plant metapopulation. In addition to dispersal between patches, we suggest within-patch processes can be critical. To address this, we assess how variation in local population dynamics, caused by small-scale disturbances, affects metapopulation size. We created an empirically based model with stochastic population dynamics and dispersal among patches, which represented a real-world, cliff-top metapopulation of wild cabbage Brassica oleracea. We collected demographic data from multiple populations by tagging plants over eight years. We assessed seed survival, and establishment and survival of seedlings in intact vegetation vs. small disturbances. We modeled primary dispersal by wind using field data and used experimental data on secondary HMD by hikers. We monitored occupancy patterns over a 14-yr period in the real metapopulation. Disturbance had large effects on local population growth rates, by increasing seedling establishment and survival. This meant that the modeled metapopulation grew in size only when the area disturbed in each patch was above 35%. In these growing metapopulations, although only 0.2% of seeds underwent HMD, this greatly enhanced metapopulation growth rates. Similarly, HMD allowed more colonizations in declining metapopulations under low disturbance, and this slowed the rate of decline. The real metapopulation showed patterns of varying patch occupancy over the survey years, which were related to habitat quality, but also positively to human activity along the cliffs, hinting at beneficial effects of humans. These findings illustrate that realistic changes to dispersal or demography, specifically by humans, can have fundamental effects on the viability of a species at the landscape scale.

Patterns and rules for sensitivity and elasticity in population projection matrices.

Sensitivity and elasticity analysis of population projection matrices (PPMs) are established tools in the analysis of structured populations, allowing comparison of the contributions made by different demographic rates to population growth. In some commonly used structures of PPM, however, there are mathematically inevitable patterns in the relative sensitivity and elasticity of certain demographic rates. We take a simulation approach to investigate these mathematical constraints for a range of PPM models. Our results challenge some previously proposed constraints on sensitivity and elasticity. We also identify constraints beyond those that have already been proven mathematically and promote them as candidates for future mathematical proof. A general theme among these rules is that changes to the demographic rates of older or larger individuals have less impact on population growth than do equivalent changes among younger or smaller individuals. However, the validity of these rules in each case depends on the choice between sensitivity and elasticity, the growth rate of the population, and the PPM structure used. If the structured population conforms perfectly to the assumptions of the PPM used to model it, the rules we describe represent biological reality, allowing us to prioritize management strategies in the absence of detailed demographic data. Conversely, if the model is a poor fit to the population (specifically, if demographic rates within stages are heterogeneous), such analyses could lead to inappropriate management prescriptions. Our results emphasize the importance of choosing a structured population model that fits the demographics of the population.

Predicting the impact of stage-specific harvesting on population dynamics.

1. Perturbation analyses of population projection matrices predict the response of a population's growth rate to changes in lifestage-specific vital rates. Such predictions have been widely used in population management but their reliability remains hotly debated. 2. We grew replicate populations of the water flea Daphnia magna in controlled, density-independent conditions and subjected treatment populations to harvesting of the largest lifestage. We predicted the growth rate of treatment populations using sensitivity analysis (a linear approximation), and transfer function analysis (TFA; which captures nonlinear responses) applied to projection matrix models parameterized from the control populations. 3. When perturbation analyses considered only the direct effect of harvesting on adult survival, the growth rate of harvested populations (averaging 0.051) was significantly overestimated (average of 0.112) by TFA and non-significantly underestimated (average of 0.012) by sensitivity. 4. When the indirect effects of harvesting on other vital rates were accounted for in a structured perturbation, TFA gave accurate predictions (average growth rate of 0.068), while sensitivity gave significant underestimates (average of -0.043). 5. Our results demonstrate two crucial sources of error that may influence predictions of the impacts of demographic perturbations on population dynamics. First, impacts of stage-specific harvesting are inherently nonlinear, hence predictions based on sensitivity must be treated with caution. Second, stage-specific perturbations can change non-target demographic rates, even in the absence of adaptation. 6. Population managers should consider both nonlinear and indirect effects of perturbations when designing management interventions. We encourage the development of methods to assess the robustness of predictions to unforeseen perturbation structures and indirect harvesting impacts.

Integrating social behaviour, demography and disease dynamics in network models: applications to disease management in declining wildlife populations.

The emergence and spread of infections can contribute to the decline and extinction of populations, particularly in conjunction with anthropogenic environmental change. The importance of heterogeneity in processes of transmission, resistance and tolerance is increasingly well understood in theory, but empirical studies that consider both the demographic and behavioural implications of infection are scarce. Non-random mixing of host individuals can impact the demographic thresholds that determine the amplification or attenuation of disease prevalence. Risk assessment and management of disease in threatened wildlife populations must therefore consider not just host density, but also the social structure of host populations. Here we integrate the most recent developments in epidemiological research from a demographic and social network perspective, and synthesize the latest developments in social network modelling for wildlife disease, to explore their applications to disease management in populations in decline and at risk of extinction. We use simulated examples to support our key points and reveal how disease-management strategies can and should exploit both behavioural and demographic information to prevent or control the spread of disease. Our synthesis highlights the importance of considering the combined impacts of demographic and behavioural processes in epidemics to successful disease management in a conservation context. This article is part of the theme issue 'Linking behaviour to dynamics of populations and communities: application of novel approaches in behavioural ecology to conservation'.