The Effect of Habitat on Insect Movements: Experimental Evidence from Wild-Caught Butterflies.

There is broad evidence that the main driver of the ongoing biodiversity crisis is land-use change, which reduces and fragments habitats. The consequence of habitat fragmentation on behavioural responses of fitness-related traits in insects have been so far understudied. In herbivorous insects, oviposition-related behaviours determine access to larval food, and the fate of the next generation. We present a pilot study to assess differences in behaviours related to movement and oviposition in Limenitis camilla butterflies from Wallonia (Belgium), one of the most fragmented regions in Europe. We first quantified variation in functional habitat connectivity across Wallonia and found that fragmented habitats had more abundant, but less evenly distributed host plants of L. camilla. Secondly, we quantified the behaviours of field-caught L. camilla females originating from habitats with contrasted landscape connectivity in an outdoor experimental setting. We found differences in behaviours related to flight investment: butterflies from fragmented woodlands spent more time in departing flight, which we associated with dispersal, than butterflies from homogenous woodlands. Although results from this study should be interpreted with caution given the limited sample size, they provide valuable insights for the advancement of behavioural research that aims to assess the effects of global changes on insects.

Evaluation of an open forecasting challenge to assess skill of West Nile virus neuroinvasive disease prediction.

BACKGROUND: West Nile virus (WNV) is the leading cause of mosquito-borne illness in the continental USA. WNV occurrence has high spatiotemporal variation, and current approaches to targeted control of the virus are limited, making forecasting a public health priority. However, little research has been done to compare strengths and weaknesses of WNV disease forecasting approaches on the national scale. We used forecasts submitted to the 2020 WNV Forecasting Challenge, an open challenge organized by the Centers for Disease Control and Prevention, to assess the status of WNV neuroinvasive disease (WNND) prediction and identify avenues for improvement. METHODS: We performed a multi-model comparative assessment of probabilistic forecasts submitted by 15 teams for annual WNND cases in US counties for 2020 and assessed forecast accuracy, calibration, and discriminatory power. In the evaluation, we included forecasts produced by comparison models of varying complexity as benchmarks of forecast performance. We also used regression analysis to identify modeling approaches and contextual factors that were associated with forecast skill. RESULTS: Simple models based on historical WNND cases generally scored better than more complex models and combined higher discriminatory power with better calibration of uncertainty. Forecast skill improved across updated forecast submissions submitted during the 2020 season. Among models using additional data, inclusion of climate or human demographic data was associated with higher skill, while inclusion of mosquito or land use data was associated with lower skill. We also identified population size, extreme minimum winter temperature, and interannual variation in WNND cases as county-level characteristics associated with variation in forecast skill. CONCLUSIONS: Historical WNND cases were strong predictors of future cases with minimal increase in skill achieved by models that included other factors. Although opportunities might exist to specifically improve predictions for areas with large populations and low or high winter temperatures, areas with high case-count variability are intrinsically more difficult to predict. Also, the prediction of outbreaks, which are outliers relative to typical case numbers, remains difficult. Further improvements to prediction could be obtained with improved calibration of forecast uncertainty and access to real-time data streams (e.g. current weather and preliminary human cases).

dynamAedes: a unified modelling framework for invasive Aedes mosquitoes.

Mosquito species belonging to the genus Aedes have attracted the interest of scientists and public health officers because of their capacity to transmit viruses that affect humans. Some of these species were brought outside their native range by means of trade and tourism and then colonised new regions thanks to a unique combination of eco-physiological traits. Considering mosquito physiological and behavioural traits to understand and predict their population dynamics is thus a crucial step in developing strategies to mitigate the local densities of invasive Aedes populations. Here, we synthesised the life cycle of four invasive Aedes species (Ae. aegypti, Ae. albopictus, Ae. japonicus and Ae. koreicus) in a single multi-scale stochastic modelling framework which we coded in the R package dynamAedes. We designed a stage-based and time-discrete stochastic model driven by temperature, photo-period and inter-specific larval competition that can be applied to three different spatial scales: punctual, local and regional. These spatial scales consider different degrees of spatial complexity and data availability by accounting for both active and passive dispersal of mosquito species as well as for the heterogeneity of the input temperature data. Our overarching aim was to provide a flexible, open-source and user-friendly tool rooted in the most updated knowledge on the species' biology which could be applied to the management of invasive Aedes populations as well as to more theoretical ecological inquiries.

Predicting the northward expansion of tropical lineage Rhipicephalus sanguineus sensu lato ticks in the United States and its implications for medical and veterinary health.

The tropical lineage within the Rhipicephalus sanguineus species complex is cause for growing concern in the U.S. based on its prominent role in creating and perpetuating multiple recently identified outbreaks of Rocky Mountain spotted fever in the southwestern United States and northern Mexico. This lineage is undergoing a northward range expansion in the United States, necessitating the need for enhanced surveillance for Rh. sanguineus. To inform more focused surveillance efforts we use species distribution models (SDMs) to predict current (2015-2019) and future (2021-2040) habitat for the tropical lineage. Models using the MaxEnt algorithm were informed using geolocations of ticks genetically confirmed to be of the tropical lineage, for which data on 23 climatic and ecological variables were extracted. Models predicted that suitability was optimal where temperatures are relatively warm and stable, and there is minimal precipitation. This translated into habitat being predicted along much of the coast of southern states including California, Texas, Louisiana, and Florida. Although the endophilic nature of tropical Rh. sanguineus somewhat violates the assumptions of SDMs, our models correctly predicted known locations of this tick and provide a starting point for increased surveillance efforts. Furthermore, we highlight the importance of using molecular methods to distinguish between ticks in the Rh. sanguineus species complex.

The Evolutionary Relevance of Social Learning and Transmission in Non-Social Arthropods with a Focus on Oviposition-Related Behaviors.

Research on social learning has centered around vertebrates, but evidence is accumulating that small-brained, non-social arthropods also learn from others. Social learning can lead to social inheritance when socially acquired behaviors are transmitted to subsequent generations. Using oviposition site selection, a critical behavior for most arthropods, as an example, we first highlight the complementarities between social and classical genetic inheritance. We then discuss the relevance of studying social learning and transmission in non-social arthropods and document known cases in the literature, including examples of social learning from con- and hetero-specifics. We further highlight under which conditions social learning can be adaptive or not. We conclude that non-social arthropods and the study of oviposition behavior offer unparalleled opportunities to unravel the importance of social learning and inheritance for animal evolution.

rasterdiv-An Information Theory tailored R package for measuring ecosystem heterogeneity from space: To the origin and back.

Ecosystem heterogeneity has been widely recognized as a key ecological indicator of several ecological functions, diversity patterns and change, metapopulation dynamics, population connectivity or gene flow.In this paper, we present a new R package-rasterdiv-to calculate heterogeneity indices based on remotely sensed data. We also provide an ecological application at the landscape scale and demonstrate its power in revealing potentially hidden heterogeneity patterns.The rasterdiv package allows calculating multiple indices, robustly rooted in Information Theory, and based on reproducible open-source algorithms.

Whole-genome assembly of Culex tarsalis.

The mosquito, Culex tarsalis, is a key vector in the western United States due to its role in transmission of zoonotic arboviruses that affect human health. Extensive research has been conducted on Cx. tarsalis ecology, feeding behavior, vector competence, autogeny, diapause, genetics, and insecticide resistance. Population genetic analyses in the western U.S. have identified at least three genetic clusters that are geographically distinct. However, in-depth genetic studies have been hindered by the lack of a reference genome. In this study, we present the first whole-genome assembly of this mosquito species (CtarK1) based on PacBio HiFi reads from high-molecular-weight DNA extracted from a single male. The CtarK1 assembly is 790 Mb with an N50 of 58 kb, which is 27% larger than Culex quinquefasciatus (578 Mb). This difference appears to be mostly composed of transposable elements. To annotate CtarK1, we used a previously assembled Cx. tarsalis transcriptome and approximately 17,456 protein genes from Cx. quinquefasciatus (N = 17,456). Genome completeness was assessed using the Benchmarking Universal Single-Copy Orthologs (BUSCO) tool, which identified 84.8% of the 2799 Dipteran BUSCO genes. Using a Bayesian phylogeny based on mitochondrial genomes, we place Cx. tarsalis in the context of other mosquito species and estimate the divergence between Cx. tarsalis and Cx. quinquefasciatus to be between 15.8 and 22.2 million years ago (MYA). Important next steps from this work include characterizing the genetic basis of diapause and sex determination in Culex mosquitoes.

Modeling Potential Habitat for Amblyomma Tick Species in California.

The Amblyomma genus of ticks comprises species that are aggressive human biters and vectors of pathogens. Numerous species in the genus are undergoing rapid range expansion. Amblyomma ticks have occasionally been introduced into California, but as yet, no established populations have been reported in the state. Because California has high ecological diversity and is a transport hub for potentially parasitized humans and animals, the risk of future Amblyomma establishment may be high. We used ecological niche modeling to predict areas in California suitable for four tick species that pose high risk to humans: Amblyomma americanum, Amblyomma maculatum, Amblyomma cajennense and Amblyomma mixtum. We collected presence data in the Americas for each species from the published literature and online databases. Twenty-three climatic and ecological variables were used in a MaxEnt algorithm to predict the distribution of each species. The minimum temperature of the coldest month was an important predictor for all four species due to high mortality of Amblyomma at low temperatures. Areas in California appear to be ecologically suitable for A. americanum, A. maculatum, and A. cajennense, but not A. mixtum. These findings could inform targeted surveillance prior to an invasion event, to allow mitigation actions to be quickly implemented.

Revisiting Alkali Metals As a Tool to Characterize Patterns of Mosquito Dispersal and Oviposition.

Mark-recapture methods constitute a set of classical ecological tools that are used to collect information on species dispersal and population size. These methods have advanced knowledge in disparate scientific fields, from conservation biology to pest control. Gathering information on the dispersal of mosquito species, such as Aedes aegypti, has become critical since the recognition of their role as vectors of pathogens. Here, we evaluate a method to mark mosquitoes that exploits the rare alkali metals rubidium (Rb) and caesium (Cs), which have been used previously to mark adult insects through feeding. We revised this method by adding Rb and Cs directly to water in which the immature stages of Ae. aegypti were allowed to develop. We then assessed the effect of Rb- and Cs-enriched water on fitness, survival and bioaccumulation in both adult females and their eggs. Results indicated that Cs had adverse effects on Ae. aegypti, even at low concentrations, whereas Rb at low concentrations had no measured effects on exposed individuals and accumulated at detectable levels in adult females. The method described here relies on passive uptake of Rb during immature stages, which has the benefit of avoiding handling or manipulation of the dispersive adults, which enables purer measurement of movement. Moreover, we demonstrated that Rb was transferred efficiently from the marked females to their eggs. To our knowledge, Rb is the only marker used for mosquitoes that has been shown to transfer vertically from females to eggs. The application of Rb rather than more traditional markers may therefore increase the quality (no impact on released individuals) and quantity (both adults and eggs are marked) of data collected during MR studies. The method we propose here can be used in combination with other markers, such as stable isotopes, in order to maximize the information collected during MR experiments.

Towards an eco-evolutionary understanding of endemism hotspots and refugia.

Background: Refugia are island-like habitats that are linked to long-term environmental stability and, as a result, high endemism. Conservation of refugia and endemism hotspots should be based on a deep ecological and evolutionary understanding of their functioning, which remains limited. Although functional traits can provide such insights, a corresponding, coherent framework is lacking. Proposed Framework: Plant communities in refugia and endemism hotspots should, due to long-term environmental stability, display unique functional characteristics linked to distinct phylogenetic patterns. Therefore, such communities should be characterized by a functional signature that exhibits: (1) distinct values and combinations of traits, (2) higher functional diversity and (3) a prevalence of similar traits belonging to more distantly related lineages inside, compared to outside, of endemism hotspots and refugia. While the limited functional trait data available from refugia and endemism hotspots do not allow these predictions to be tested rigorously, three potential applications of the functional signature in biogeography and conservation planning are highlighted. Firstly, it allows the functional characteristics of endemism hotspots and refugia to be identified. Secondly, the strength of the functional signature can be compared among these entities, and with the surrounding landscape, to provide an estimate of the capacity of endemism hotspots and refugia to buffer environmental changes. Finally, the pattern of the functional signature can reveal ecological and evolutionary processes driving community assembly and functioning, which can assist in predicting the effect of environmental changes (e.g. climate, land-use) on communities in endemism hotspots and refugia. Conclusion: The proposed functional signature concept allows the systematic integration of plant functional traits and phylogeny into the study of endemism hotspots and refugia, but more data on functional traits in these entities are urgently needed. Overcoming this limitation would facilitate rigorous testing of the proposed predictions for the functional signature, advancing the eco-evolutionary understanding of endemism hotspots and refugia.

The impact of forest roads on understory plant diversity in temperate hornbeam-beech forests of Northern Iran.

Forest roads alter the biotic and abiotic components of ecosystems, modifying temperature, humidity, wind speed, and light availability that, in turn, cause changes in plant community composition and diversity. We aim at investigating and comparing the diversity of herbaceous species along main and secondary forest roads in a temperate-managed hornbeam-beech forest, north of Iran. Sixteen transects along main and secondary forest roads were established (eight transects along main roads and eight along secondary roads). To eliminate the effect of forest type, all transects were located in Carpinetum-Fagetum forests, the dominant forest type in the study area. The total length of each transect was 200 m (100 m toward up slope and 100 m toward down slope), and plots were established along it at different distances from road edge. The diversity of herbaceous plant species was calculated in each plot using Shannon-Wiener index, species richness, and Pielou's index. The results showed that diversity index decreased when distance from road edge increases. This decreasing trend continued up to 60 m from forest road margin, and after this threshold, the index slightly increased. Depending on the type of road (main or secondary) as well as cut or fill slopes, the area showing a statistical different plant composition and diversity measured through Shannon-Wiener, species richness, and Pielou's index is up to 10 m. The length depth of the road edge effect found in main and secondary forest roads was small, but it could have cumulative effects on forest microclimate and forest-associated biota at the island scale. Forest managers should account for the effect of road buildings on plant communities.

Anticipating species distributions: Handling sampling effort bias under a Bayesian framework.

Anticipating species distributions in space and time is necessary for effective biodiversity conservation and for prioritising management interventions. This is especially true when considering invasive species. In such a case, anticipating their spread is important to effectively plan management actions. However, considering uncertainty in the output of species distribution models is critical for correctly interpreting results and avoiding inappropriate decision-making. In particular, when dealing with species inventories, the bias resulting from sampling effort may lead to an over- or under-estimation of the local density of occurrences of a species. In this paper we propose an innovative method to i) map sampling effort bias using cartogram models and ii) explicitly consider such uncertainty in the modeling procedure under a Bayesian framework, which allows the integration of multilevel input data with prior information to improve the anticipation species distributions.

Sometimes Scientists Get the Flu. Wrong !

In an international research environment, accurate communication is vital. However, the scientific literature does not always utilise consistent terminology and the misuse of some expressions in epidemiology is rife. We encourage the correct terms to be used appropriately to avoid confusion between scientists, policy makers, and members of the public.

An integrated pest control strategy against the Asian tiger mosquito in northern Italy: a case study.

BACKGROUND: In Europe, Aedes albopictus is an invasive mosquito species known to be a major nuisance as well as a vector of a range of arboviruses. A number of studies have indicated that community participation programmes are an effective pest control tool to reduce mosquito populations. However, few studies have evaluated the effectiveness of a community-based approach in Europe. In this study, we examined two Ae. albopictus control strategies that implemented a community-based approach in northern Italy: one was a partial intervention that included a public education campaign and the larviciding of public spaces, and the other was a full intervention that additionally included a door-to-door campaign. This latter consisted of going door to door actively to educate residents about control measures and deliver larvicide tablets for treating catch basins at home. A site where no intervention measures were carried out was used as a control. RESULTS: In the site where a full intervention was carried out, Ae. albopictus egg density was 1.6 times less than at the site that received partial intervention, and 1.9 times less than at the non-intervention site. No significant reduction in egg density was achieved in the partial intervention site. CONCLUSIONS: In our study, Ae. albopictus populations were most effectively reduced by larviciding both public and private catch basins. Door-to-door education was effective in convincing residents to apply control measures on their property; however, this method was labour intensive and costly. It may be possible to reduce personnel costs by involving volunteers or using a 'hot spot' approach. © 2016 Society of Chemical Industry.

First assessment of potential distribution and dispersal capacity of the emerging invasive mosquito Aedes koreicus in Northeast Italy.

BACKGROUND: Invasive alien species represent a growing threat for natural systems, economy and human health. Active surveillance and responses that readily suppress newly established colonies are effective actions to mitigate the noxious consequences of biological invasions. However, when an exotic species establishes a viable population in a new area, predicting its potential spread is the most effective way to implement adequate control actions. Emerging invasive species, despite monitoring efforts, are poorly known in terms of behaviour and capacity to adapt to the new invaded range. Therefore, tools that provide information on their spread by maximising the available data, are critical. METHODS: We apply three different approaches to model the potential distribution of an emerging invasive mosquito, Aedes koreicus, in Northeast Italy: 1) an automatic statistical approach based on information theory, 2) a statistical approach integrated with prior knowledge, and 3) a GIS physiology-based approach. Each approach possessed benefits and limitations, and the required ecological information increases on a scale from 1 to 3. We validated the model outputs using the only other known invaded area in Europe. Finally, we applied a road network analysis to the suitability surface with the highest prediction power to highlight those areas with the highest likelihood of invasion. RESULTS: The GIS physiological-based model had the highest prediction power. It showed that localities currently occupied by Aedes koreicus represent only a small fraction of the potentially suitable area. Furthermore, the modelled niche included areas as high as 1500 m a.s.l., only partially overlapping with Aedes albopictus distribution. CONCLUSIONS: The simulated spread indicated that all of the suitable portion of the study area is at risk of invasion in a relatively short period of time if no control policies are implemented. Stochastic events may further boost the invasion process, whereas competition with Aedes albopictus may limit it. According to our analysis, some of the major cities in the study area may have already been invaded. Further monitoring is needed to confirm this finding. The developed models and maps represent valuable tools to inform policies aimed at eradicating or mitigating Aedes koreicus invasion in Northeast Italy and Central Europe.

Identifying the environmental conditions favouring West Nile Virus outbreaks in Europe.

West Nile Virus (WNV) is a globally important mosquito borne virus, with significant implications for human and animal health. The emergence and spread of new lineages, and increased pathogenicity, is the cause of escalating public health concern. Pinpointing the environmental conditions that favour WNV circulation and transmission to humans is challenging, due both to the complexity of its biological cycle, and the under-diagnosis and reporting of epidemiological data. Here, we used remote sensing and GIS to enable collation of multiple types of environmental data over a continental spatial scale, in order to model annual West Nile Fever (WNF) incidence across Europe and neighbouring countries. Multi-model selection and inference were used to gain a consensus from multiple linear mixed models. Climate and landscape were key predictors of WNF outbreaks (specifically, high precipitation in late winter/early spring, high summer temperatures, summer drought, occurrence of irrigated croplands and highly fragmented forests). Identification of the environmental conditions associated with WNF outbreaks is key to enabling public health bodies to properly focus surveillance and mitigation of West Nile virus impact, but more work needs to be done to enable accurate predictions of WNF risk.