Host Density Research Articles

Intraspecific interference between native parasitoids modified by a non‐native parasitoid and its consequence on population dynamics

1. The number of natural enemies that should be introduced to control a pest is a controversial subject in biocontrol. A previous semi‐mechanistic model parameterised using a laboratory system consisting of two parasitoid wasps, Anisopteromalus calandrae and Heterospilus prosopidis, parasitising a pest beetle, Callosobruchus chinensis, indicated that the introduction of the non‐native parasitoid H. prosopidis decreases the level of intraspecific interference between native A. calandrae females. The model also suggested that this decrease was the main factor destabilising the population dynamics of the host–parasitoid system, resulting in chaos.2. To test this population‐level decrease and host density independence in the interference of A. calandrae, we observed individual behaviours to quantify the level of intraspecific interference between two A. calandrae females in the presence or absence of H. prosopidis at two different host densities.3. When H. prosopidis was present, the number of direct antagonistic interference events between A. calandrae females, sting duration, host feeding events (but not stinging events), and patch residence time were reduced. However, the presence of H. prosopidis decreased the patch residence time and the proportion of hosts parasitised by A. calandrae only when the host density was low.4. The reduction in intraspecific interference between A. calandrae females by H. prosopidis and its host density independence support the population‐level prediction, whereas the observed reduction in host‐feeding behaviours in A. calandrae by H. prosopidis was not predicted. Overall pest control by the native parasitoid was unaffected by the non‐native parasitoid as host density increased.

Different environmental gradients associated to the spatiotemporal and genetic pattern of the H5N8 highly pathogenic avian influenza outbreaks in poultry in Italy.

Comprehensive understanding of the patterns and drivers of avian influenza outbreaks is pivotal to inform surveillance systems and heighten nations’ ability to quickly detect and respond to the emergence of novel viruses. Starting in early 2017, the Italian poultry sector has been involved in the massive H5N8 highly pathogenic avian influenza epidemic that spread in the majority of the European countries in 2016/2017. Eighty‐three outbreaks were recorded in north‐eastern Italy, where a densely populated poultry area stretches along the Lombardy, Emilia‐Romagna and Veneto regions. The confirmed cases, affecting both the rural and industrial sectors, depicted two distinct epidemic waves. We adopted a combination of multivariate statistics techniques and multi‐model regression selection and inference, to investigate how environmental factors relate to the pattern of outbreaks diversity with respect to their spatiotemporal and genetic diversity. Results showed that a combination of eco‐climatic and host density predictors were associated with the outbreaks pattern, and variation along gradients was noticeable among genetically and geographically distinct groups of avian influenza cases. These regional contrasts may be indicative of a different mechanism driving the introduction and spreading routes of the influenza virus in the domestic poultry population. This methodological approach may be extended to different spatiotemporal scale to foster site‐specific, ecologically informed risk mitigating strategies.

Effects of agrochemical pollution on schistosomiasis transmission: a systematic review and modelling analysis

BackgroundAgrochemical pollution of surface waters is a growing global environmental challenge, especially in areas where agriculture is rapidly expanding and intensifying. Agrochemicals might affect schistosomiasis transmission through direct and indirect effects on Schistosoma parasites, their intermediate snail hosts, snail predators, and snail algal resources. We aimed to review and summarise the effects of these agrochemicals on schistosomiasis transmission dynamics.MethodsWe did a systematic review of agrochemical effects on the lifecycle of Schistosoma spp and fitted dose-response models to data regarding the association between components of the lifecycle and agrochemical concentrations. We incorporated these dose-response functions and environmentally relevant concentrations of agrochemicals into a mathematical model to estimate agrochemical effects on schistosomiasis transmission. Dose-response functions were used to estimate individual agrochemical effects on estimates of the agrochemically influenced basic reproduction number, R0, for Schistosoma haematobium. We incorporated time series of environmentally relevant agrochemical concentrations into the model and simulated mass drug administration control efforts in the presence of agrochemicals.FindingsWe derived 120 dose-response functions describing the effects of agrochemicals on schistosome lifecycle components. The median estimate of the basic reproduction number under agrochemical-free conditions, was 1·65 (IQR 1·47–1·79). Agrochemical effects on estimates of R0 for S haematobium ranged from a median three-times increase (R0 5·05, IQR 4·06–5·97) to transmission elimination (R0 0). Simulations of transmission dynamics subject to interacting annual mass drug administration and agrochemical pollution yielded a median estimate of 64·82 disability-adjusted life-years (DALYs) lost per 100,000 people per year (IQR 62·52–67·68) attributable to atrazine use. In areas where aquatic arthropod predators of intermediate host snails suppress transmission, the insecticides chlorpyrifos (6·82 DALYs lost per 100,000 people per year, IQR 4·13–8·69) and profenofos (103·06 DALYs lost per 100,000 people per year, IQR 89·63–104·90) might also increase the disability burden through their toxic effects on arthropods.InterpretationExpected environmental concentrations of agrochemicals alter schistosomiasis transmission through direct and indirect effects on intermediate host and parasite densities. As industrial agricultural practices expand in areas where schistosomiasis is endemic, strategies to prevent increases in transmission due to agrochemical pollution should be developed and pursued.

Modelling how resource competition among snail hosts affects the mollusciciding frequency and intensity needed to control human schistosomes

Abstract Ecological interactions among intermediate hosts or vectors of human pathogens can enhance or hinder control efforts. However, we currently lack quantitative frameworks to predict how interactions among host physiology, ecology and control effort shape human disease risk. We explore this approach for human schistosomiasis, a major, historically neglected tropical disease. A recent re‐emphasis on snail host control using molluscicides highlights the need to re‐evaluate the ecological mechanisms driving emergence of schistosome cercariae, the life stage that directly infects humans. We integrate physiology, resource competition and control using individual‐based models based on general metabolic theory, Dynamic Energy Budget theory, to simulate human infectious schistosome density under molluscicide scenarios varying in frequency and intensity throughout a 150‐day transmission season. Without molluscicide control, our model predicts intense resource competition among hosts and large and early parasite peaks under algae and detritus resources. Consistent monthly control, as recommended by the WHO, can work if intense, that is, >90% host mortality. In contrast, one‐off, intense and early mollusciciding induces large delayed rebounds in parasites by releasing the few remaining snails from resource competition. Our simulations confirm the WHO recommendation that frequent mollusciciding can disrupt transmission, but contradict recent suggestions for infrequent mollusciciding, for example, annually, which can backfire because relaxed resource competition among hosts stimulates parasite production. Our results identify resource competition as a key ecological mechanism driving parasite population intensity for schistosome habitats across ecosystems. Our results show resource ecology models can identify peaks in parasite density. More generally, resource competition among hosts may complicate efforts to control infected snail host densities in the field and thus disease risk through culling or mortality‐based interventions. Connecting individuals to community and disease dynamics with resource ecology can inform better field control strategies and help managers avoid unintended consequences for human health. A free Plain Language Summary can be found within the Supporting Information of this article.

Parasitism potential of Diadegma argenteopilosa (Cameron) (Hymenoptera : Ichneumonidae), an internal larval parasitoid of Spodoptera litura (Fab.) (Noctuidae: Lepidoptera)

Diadegma argenteopilosa (Cameron) (Ichneumonidae: Hymenoptera) is an internal larval parasitoid of Spodoptera litura (Fab.) (Noctuidae: Lepidoptera), a notorious and polyphagus pest of pulses and vegetables in India. Attempt has been made to initiate their mass multiplication for successful biocontrol programme. Behavioral studies, food stuffs, host selection aspects plays a crucial role in mass multiplication of biocontrol agents. Therefore, present work was conducted to study the optimum host age, specificity and host density for maximum progeny production of the parasitoid under laboratory conditions and later their release in the field for the management of pest species. The parasitoid caused highest mortality in the pest larvae of second instars, 4 day old larvae were attacked most with high percent parasitism, 39.00%. Optimum density for maximum progeny production of D. argenteopilosa was 20, which generate maximum parasitism (43.00%). Host specificity by exposing the parasitoids towards different host species and analyse parasitoid preference by S. litura > Helicoverpa armigera (Hubner) > Mythimna separata Walker > Achaea janata (Linnaeus). Nutritional requirement of parasitoid was tested with different foodstuffs and found 50% honey best suited for maximum longevity 8.2 and 11.4 days for males and females respectively. The longevity ratio also female biased, 1: 1.39 (Male: Female). From the results it concludes that D. argenteopilosa fed with 50% honey solution, exposed to 3-5 day old caterpillars of S. litura at density of 20 gave maximum progeny production and effectively utilized in the biocontrol programme.

Global redistribution and local migration in semi-discrete host–parasitoid population dynamic models

Host–parasitoid population dynamics is often probed using a semi-discrete/hybrid modeling framework. Here, the update functions in the discrete-time model connecting year-to-year changes in the population densities are obtained by solving ordinary differential equations that mechanistically describe interactions when hosts become vulnerable to parasitoid attacks. We use this semi-discrete formalism to study two key spatial effects: local movement (migration) of parasitoids between patches during the vulnerable period; and yearly redistribution of populations across patches outside the vulnerable period. Our results show that in the absence of any redistribution, constant density-independent migration and parasitoid attack rates are unable to stabilize an otherwise unstable host–parasitoid population dynamics. Interestingly, inclusion of host redistribution (but not parasitoid redistribution) before the start of the vulnerable period can lead to stable coexistence of both species. Next, we consider a Type-III functional response (parasitoid attack rate increases with host density), where the absence of any spatial effects leads to a neutrally stable host–parasitoid equilibrium. As before, density-independent parasitoid migration by itself is again insufficient to stabilize the population dynamics and host redistribution provides a stabilizing influence. Finally, we show that a Type-III functional response combined with density-dependent parasitoid migration leads to stable coexistence, even in the absence of population redistributions. In summary, we have systematically characterized parameter regimes leading to stable/unstable population dynamics with different forms of spatial heterogeneity coupled to the parasitoid’s functional response using mechanistically formulated semi-discrete models.

Asexual Evolution and Forest Conditions Drive Genetic Parallelism in Phytophthora ramorum.

It is commonly assumed that asexual lineages are short-lived evolutionarily, yet many asexual organisms can generate genetic and phenotypic variation, providing an avenue for further evolution. Previous work on the asexual plant pathogen Phytophthora ramorum NA1 revealed considerable genetic variation in the form of Structural Variants (SVs). To better understand how SVs arise and their significance to the California NA1 population, we studied the evolutionary histories of SVs and the forest conditions associated with their emergence. Ancestral state reconstruction suggests that SVs arose by somatic mutations among multiple independent lineages, rather than by recombination. We asked if this unusual phenomenon of parallel evolution between isolated populations is transmitted to extant lineages and found that SVs persist longer in a population if their genetic background had a lower mutation load. Genetic parallelism was also found in geographically distant demes where forest conditions such as host density, solar radiation, and temperature, were similar. Parallel SVs overlap with genes involved in pathogenicity such as RXLRs and have the potential to change the course of an epidemic. By combining genomics and environmental data, we identified an unexpected pattern of repeated evolution in an asexual population and identified environmental factors potentially driving this phenomenon.

Divergent biotic and abiotic filtering of root endosphere and rhizosphere soil fungal communities along ecological gradients.

Plant roots assemble in two distinct microbial compartments: the rhizosphere (microbes in soil surrounding roots) and the endosphere (microbes within roots). Our knowledge of fungal community assembly in these compartments is limited, especially in wetlands. We tested the hypothesis that biotic factors would have direct effects on rhizosphere and endosphere assembly, while abiotic factors would have direct and indirect effects. Using a field study, we examined the influences of salinity, water level and biotic factors on baldcypress (Taxodium distichum) fungal communities. We found that endosphere fungi, unlike rhizosphere fungi, were correlated with host density and canopy cover, suggesting that hosts can impose selective filters on fungi colonizing their roots. Meanwhile, local abiotic conditions strongly influenced both rhizosphere and endosphere diversity in opposite patterns, e.g. highest endosphere diversity (hump-shaped) and lowest rhizosphere diversity (U-shaped) at intermediate salinity levels. These results indicate that the assembly and structure of the root endosphere and rhizosphere within a host can be shaped by different processes. Our results also highlight the importance of assessing how environmental changes affect plant and plant-associated fungal communities in wetland ecosystems where saltwater intrusion and sea level rise are major threats to both plant and fungal communities.

Evaluating moose Alces alces population response to infestation level of winter ticks Dermacentor albipictus

Many wildlife populations are experiencing a variety of environmental pressures due to the direct and indirect consequences of a changing climate. In the northeast, USA, moose Alces alces are declining in large part because of the increasing parasitism by winter tick Dermacentor albipictus, facilitated by high host density and optimal environmental conditions. To test this hypothesis, and better understand the influence of this interaction on the stability of the regional population, we constructed a population viability model using data collected through comprehensive survival and productivity studies in 2002–2005 and 2014–2018 in northern New Hampshire. Years of heavy tick infestation (epizootics) saw a marked reduction in calf survival (< 50%), adult calving (< 60%), twinning rate (< 5%) and complete loss of yearling productivity. We conducted population viability analysis using VORTEX ver. 10.2 to model this moose population for 40 years using mean demographics from both time periods, including environmental variation measured in the field during winter tick epizootic (2002, 2014, 2015, 2016) and non-epizootic (2003, 2004, 2005, 2017) years. This exercise highlights the influence of winter tick infestation on the trajectory of the population with the potential for rapid population growth or decline depending on the frequency of epizootics. We suggest a shift in moose management strategy focused on lowering moose density, assuming continued influence of climate change on the host–parasite relationship.

Response of egg parasitoids (Hymenoptera: Mymaridae and Trichogrammatidae) to the density of Dalbulus maidis (Hemiptera: Cicadellidae) eggs in maize habitats

Understanding the response of egg parasitoids to host density is essential for efficient biological control. However, this response has been little investigated in parasitoids that attack eggs of insect pests that transmit plant pathogens in a persistent-propagative mode. The objective of the present study was to investigate the response of two egg parasitoid communities to high and low densities of eggs of the corn leafhopper Dalbulus maidis, an efficient vector of maize plant pathogens. Five and ten two-week-old female D. maidis (for the low-density and high-density groups, respectively) were allowed to oviposit on landrace maize leaves. The maize plants with the eggs were then transported to a seasonal and a year-round maize habitat in central Mexico, where they were exposed to naturally occurring parasitoids. In total, four treatments were conducted: seasonal maize habitat/low egg density (SL), seasonal maize habitat/high egg density (SH), year-round maize habitat/low egg density (YL), and year-round maize habitat/high egg density (YH). The parasitoids emerging from the eggs included the Mymaridae Anagrus virlai and Anagrus incarnatus, and the Trichogrammatidae Paracentrobia sp., Pseudoligosita sp., and Oligosita sp., with A. virlai as the most abundant species. An inverse density-dependent relationship was found between the number of D. maidis eggs and the rate of parasitism in the SH group. In the SL, YL, and YH groups, an independent relationship was seen between the number of eggs and the parasitism rate. These results suggest that high vs. low egg density affects the density-dependence relationships between egg parasitoids and their hosts.

A mechanistic, stigmergy model of territory formation in solitary animals: Territorial behavior can dampen disease prevalencebut increase persistence.

Although movement ecology has leveraged models of home range formation to explore the effects of spatial heterogeneity and social cues on movement behavior, disease ecology has yet to integrate these potential drivers and mechanisms of contact behavior into a generalizable disease modeling framework. Here we ask how dynamic territory formation and maintenance might contribute to disease dynamics in a territorial, solitary predator for an indirectly transmitted pathogen. We developed a mechanistic individual-based model where stigmergy-the deposition of signals into the environment (e.g., scent marking, scraping)-dictates local movement choices and long-term territory formation, but also the risk of pathogen transmission. Based on a variable importance analysis, the length of the infectious period was the single most important variable in predicting outbreak success, maximum prevalence, and outbreak duration. Host density and rate of pathogen decay were also key predictors. We found that territoriality best reduced maximum prevalence in conditions where we would otherwise expect outbreaks to be most successful: slower recovery rates (i.e., longer infectious periods) and higher conspecific densities. However, for slower pathogen decay rates, stigmergy-driven movement increased outbreak durations relative to random movement simulations. Our findings therefore support a limited version of the "territoriality benefits" hypothesis-where reduced home range overlap leads to reduced opportunities for pathogen transmission, but with the caveat that reduction in outbreak severity may increase the likelihood of pathogen persistence. For longer infectious periods and higher host densities, key trade-offs emerged between the strength of pathogen load, the strength of the stigmergy cue, and the rate at which those two quantities decayed; this finding raises interesting questions about the evolutionary nature of these competing processes and the role of possible feedbacks between parasitism and territoriality. This work also highlights the importance of considering social cues as part of the movement landscape in order to better understand the consequences of individual behaviors on population level outcomes.

Spatio-temporal trends in richness and persistence of bacterial communities in decline-phase water vole populations

Understanding the driving forces that control vole population dynamics requires identifying bacterial parasites hosted by the voles and describing their dynamics at the community level. To this end, we used high-throughput DNA sequencing to identify bacterial parasites in cyclic populations of montane water voles that exhibited a population outbreak and decline in 2014–2018. An unexpectedly large number of 155 Operational Taxonomic Units (OTUs) representing at least 13 genera in 11 families was detected. Individual bacterial richness was higher during declines, and vole body condition was lower. Richness as estimated by Chao2 at the local population scale did not exhibit clear seasonal or cycle phase-related patterns, but at the vole meta-population scale, exhibited seasonal and phase-related patterns. Moreover, bacterial OTUs that were detected in the low density phase were geographically widespread and detected earlier in the outbreak; some were associated with each other. Our results demonstrate the complexity of bacterial community patterns with regard to host density variations, and indicate that investigations about how parasites interact with host populations must be conducted at several temporal and spatial scales: multiple times per year over multiple years, and at both local and long-distance dispersal scales for the host(s) under consideration.

A Holling Type II Discrete Switching Host-Parasitoid System with a Nonlinear Threshold Policy for Integrated Pest Management

A nonlinear discrete switching host-parasitoid model with Holling type II functional response function, in which the switch is guided by an economic threshold (ET), is proposed. Thus, if the weighted density of two generations of the host population increases and exceeds the ET, then integrated pest management (IPM) measures are enacted, i.e., biological and chemical measures are implemented together, assuming that the chemical immediately precedes the biological inputs to avoid pesticide-induced deaths of the natural enemies. First, the existence and local stability of the equilibria of two subsystems were studied, and the existence and coexistence of several types of equilibria of a nonlinear switching system were analysed. Next, the nonlinear switching system was investigated by numerical simulation, showing that the system exhibits quite complex dynamic behaviour. A two-dimensional bifurcation diagram revealed the existence and coexistence regions of different types of equilibria including regular and virtual equilibria. Moreover, period-adding bifurcations in two-dimensional parameter spaces were found. One-dimensional bifurcation diagrams revealed that the system has periodic, quasiperiodic, and chaotic solutions, Neimark–Sacker bifurcation, multiple coexisting attractors, period-doubling bifurcations, period-halving bifurcations, and so on. Finally, the initial densities of hosts and parasitoids associated with host outbreaks and their biological implications are discussed.

Long-Term Determinants of Tuberculosis in the Ungulate Host Community of Doñana National Park.

Animal tuberculosis (TB) is endemic in wild boar (Sus scrofa), red deer (Cervus elaphus), fallow deer (Dama dama) and cattle in south and central Spain. In order to clarify the processes that operate in the medium and long-term, we studied TB at the wildlife–livestock interface in Doñana National Park for 14 years (2006–2018) in relation to host density, stochastic factors (rainfall) and environmental features (e.g., aggregation points such as waterholes). Wild boar showed the highest prevalence of TB (76.7%), followed by red deer (42.5%), fallow deer (14.4%) and cattle (10.7%). We found evidence of relevant epidemiological processes which operate over the long-term and interact with host and community ecology. Interestingly, the effect of high wild boar population density on increased TB rates was mediated by sows, which could determine high incidence in young individuals already in maternal groups. Rainfall significantly determined a higher risk of TB in male red deer, probably mediated by sex-related differences in life history traits that determined more susceptibility and/or exposure in comparison to females. The positive association between the prevalence of TB in fallow deer and cattle may indicate significant interspecies transmission (in either direction) and/or similar exposure to risk factors mediated by ecological overlapping of grazing species. The identification of long-term drivers of TB provided evidence that its control in extensive pastoral systems can only be achieved by targeting all relevant hosts and integrating measures related to all the factors involved, such as: population abundance and the aggregation of wild and domestic ungulates, environmental exposure to mycobacteria, cattle testing and culling campaigns and adjustments of appropriate densities.

Big data–model integration and AI for vector‐borne disease prediction

AbstractPredicting the drivers of incursion and expansion of vector‐borne diseases as part of early‐warning strategies (EWS) is a major challenge for geographically extensive diseases where spread is mediated by spatial heterogeneity in climate and other environmental drivers. Geospatial data on these environmental drivers are increasingly available affording opportunities for application to a predictive disease ecology paradigm provided the data can be synthesized and harmonized with fine‐scale, highly resolved data on vector and host responses to their environment. Here, we apply a multi‐scale big data–model integration approach using human‐guided machine learning to objectively evaluate the importance of a large suite of spatially distributed environmental variables (&gt;400) to develop EWS for vesicular stomatitis (VS), a common viral vector‐borne vesicular disease affecting livestock throughout the Americas. Two temporally and phylogenetically distinct events were used to develop disease occurrence–environment relationships in incursion (2004) and expansion years (2005), and then to test those relationships (2014, 2015) at two scales: (1) local and (2) landscape to regional. Our results show that VS occurrence at a local scale of individual landowners was related to conditions that can be monitored (rainfall, temperatures, streamflow) or modified (vegetation). On‐site green vegetation during the month of occurrence and higher rainfall four months prior combined with either cool daytime (expansion) or nighttime (incursion) temperatures one month prior were indicators of VS occurrence. Distance to running water (incursion) and host density based on neighboring ranches (expansion) with infected animals were also important in individual years. At landscape‐to‐regional scales, conditions that favor specific VSV biological vectors were indicated, either black flies in incursion years or biting midges in expansion years. Changes in viral genetic lineage were less important to patterns in VS occurrence than factors affecting the host–vector–environment interactions. In combination with our onset map based on latitude, elevation, and long‐term annual precipitation, this year‐ and scale‐specific information can be used to develop strategies to minimize effects of future VS events. This big data approach coupled with expert knowledge and machine learning can be applied to other emerging diseases for improvement in understanding, prediction, and management of vector‐borne diseases.

Vaccination and monitoring strategies for epidemic prevention and detection in the Channel Island fox (Urocyon littoralis).

Disease transmission and epidemic prevention are top conservation concerns for wildlife managers, especially for small, isolated populations. Previous studies have shown that the course of an epidemic within a heterogeneous host population is strongly influenced by whether pathogens are introduced to regions of relatively high or low host densities. This raises the question of how disease monitoring and vaccination programs are influenced by spatial heterogeneity in host distributions. We addressed this question by modeling vaccination and monitoring strategies for the Channel Island fox (Urocyon littoralis), which has a history of substantial population decline due to introduced disease. We simulated various strategies to detect and prevent epidemics of rabies and canine distemper using a spatially explicit model, which was parameterized from field studies. Increasing sentinel monitoring frequency, and to a lesser degree, the number of monitored sentinels from 50 to 150 radio collared animals, reduced the time to epidemic detection and percentage of the fox population infected at the time of detection for both pathogens. Fox density at the location of pathogen introduction had little influence on the time to detection, but a large influence on how many foxes had become infected by the detection day, especially when sentinels were monitored relatively infrequently. The efficacy of different vaccination strategies was heavily influenced by local host density at the site of pathogen entry. Generally, creating a vaccine firewall far away from the site of pathogen entry was the least effective strategy. A firewall close to the site of pathogen entry was generally more effective than a random distribution of vaccinated animals when pathogens entered regions of high host density, but not when pathogens entered regions of low host density. These results highlight the importance of considering host densities at likely locations of pathogen invasion when designing disease management plans.

Influence of adult diet on fitness and reproductive traits of the egg parasitoid Anagrus virlai (Hymenoptera: Mymaridae), a potential biocontrol agent against the corn leafhopper

AbstractDalbulus maidis is the most important leafhopper pest of maize in the Americas. Anagrus virlai is an egg parasitoid commonly associated with the corn leafhopper. We evaluated whether the performance of A. virlai is dependent on different diets provided during 24 hr or throughout adult female lifetime. Additionally, functional response of A. virlai on D. maidis eggs using maize leaves containing honeydew plus honey was described. A. virlai is a mostly pro‐ovigenic autogenic species whose females are able to parasitize eggs immediately after emergence. We found that wasps oviposit the majority of their eggs in the first day of their adult life. Realized lifetime fecundity and lifetime potential fecundity did not differ significantly among treatments, but longevity and egg production increased when honey was added to diet. Data were consistent with an intermediate functional response between type II and III, but closer to type II, indicating a high parasitism rate at low host densities and a decrease in the oviposition rate at high host densities, due to a possible egg limitation. Our results suggest that carbohydrate food sources (honeydew and honey) might not be the factor limiting reproductive success during the first 24 hr. Food supply, however, might influence egg maturation and survivorship of wasps, thus potentially enhancing biological pest control when hosts are scarce in the course of the first few days of adulthood.

Role of Thrips palmi and Parthenium hysterophorus pollen in active spread of tobacco streak virus in the cotton ecosystem

Tobacco streak virus incidence in the cotton field, cv.CO14 at Department of Cotton, Tamil Nadu Agricultural University (TNAU), Coimbatore, India was nearly 36.50 %. Cotton plants infected with TSV exhibits different types of symptoms, including necrotic spots, lesions, mosaic, purplish necrotic rings, square drying, veinal necrosis and drying of terminal shoots. The highly prevalent thrips species in this cotton ecosystem was established as Thrips palmi (60.00 %) by morphological (ESEM) and molecular methods (RT-PCR using mtCOI primers). The density of the alternate weed host, Parthenium hysterophorus, was 15.05 plants per m2 in these fields. Association of Thrips palmi with Parthenium was confirmed, when observed under environmental scanning electron microscope (ESEM), Parthenium pollen grains (i.e., average size @ 15000X =12.94 μm) were found adhering to its body. Molecular studies through RT-PCR confirmed the presence of TSV in the leaves and pollen grains of symptomatic and symptom-free Parthenium plants collected from the cotton field (cv. CO14). Therefore, the combined role of Thrips palmi and the Parthenium pollen grains in the transmission of TSV was examined; acquiring of TSV and its presence in the body of Thrips palmi instars and adults after 72 h of AAP was convincingly demonstrated using RT-PCR, NASH and qPCR. However virus acquired thrips could not transmit the virus. Pollen from TSV infected Parthenium plants when dusted on cotton (ANKUR 2110) seedlings along with virus acquired or non-acquired thrips led to symptom development 22 days after sowing. From the study it is evident that thrips only facilitate the movement of TSV borne pollen grains, and thereby contributing to active spread of the virus.

Landscape epidemiology of ash dieback

Abstract Ash dieback is induced by Hymenoscyphus fraxineus, an invasive pathogenic fungus. It is causing severe damage to European ash populations. However, the local environment, such as climate or site conditions, is known to affect ash dieback. We studied the landscape epidemiology of the disease on a 22 km2 area in north‐eastern France at two stages of the invasion process using Bayesian spatio‐temporal models fitted with integrated nested Laplace approximation (INLA). Several features characterizing disease severity, crown dieback, frequency of collar canker and density of infected leaf debris in the litter were determined on a regular grid over a 3.5 × 6.5 km area. We first analysed the effect of landscape features on the disease establishment stage in 2012, 2 years after the first report of the disease in the area, and then on further disease development, in 2016–2018. Landscape features had little impact on the disease at the establishment stage, but strongly determined its further development. Local fragmentation of tree cover was the most important factor, with trees that are isolated or in hedges far less affected than trees in a forest environment. We showed that they were subjected to different microclimates, with higher crown temperatures unfavourable to pathogen development. Low host density strongly reduced disease development. The presence of large ash populations in the vicinity affected local disease severity up to several hundred metres. Synthesis. We showed that the landscape characteristics strongly affect the development and spread of ash dieback. The disease is far less severe in forest conditions when ash density is low or in open canopies such as hedges and isolated trees. Ash trees are often in these types of landscapes, which should strongly limit the overall impact of ash dieback.

Predicting disease risk areas through co-production of spatial models: The example of Kyasanur Forest Disease in India's forest landscapes.

Zoonotic diseases affect resource-poor tropical communities disproportionately, and are linked to human use and modification of ecosystems. Disentangling the socio-ecological mechanisms by which ecosystem change precipitates impacts of pathogens is critical for predicting disease risk and designing effective intervention strategies. Despite the global "One Health" initiative, predictive models for tropical zoonotic diseases often focus on narrow ranges of risk factors and are rarely scaled to intervention programs and ecosystem use. This study uses a participatory, co-production approach to address this disconnect between science, policy and implementation, by developing more informative disease models for a fatal tick-borne viral haemorrhagic disease, Kyasanur Forest Disease (KFD), that is spreading across degraded forest ecosystems in India. We integrated knowledge across disciplines to identify key risk factors and needs with actors and beneficiaries across the relevant policy sectors, to understand disease patterns and develop decision support tools. Human case locations (2014-2018) and spatial machine learning quantified the relative role of risk factors, including forest cover and loss, host densities and public health access, in driving landscape-scale disease patterns in a long-affected district (Shivamogga, Karnataka State). Models combining forest metrics, livestock densities and elevation accurately predicted spatial patterns in human KFD cases (2014-2018). Consistent with suggestions that KFD is an "ecotonal" disease, landscapes at higher risk for human KFD contained diverse forest-plantation mosaics with high coverage of moist evergreen forest and plantation, high indigenous cattle density, and low coverage of dry deciduous forest. Models predicted new hotspots of outbreaks in 2019, indicating their value for spatial targeting of intervention. Co-production was vital for: gathering outbreak data that reflected locations of exposure in the landscape; better understanding contextual socio-ecological risk factors; and tailoring the spatial grain and outputs to the scale of forest use, and public health interventions. We argue this inter-disciplinary approach to risk prediction is applicable across zoonotic diseases in tropical settings.