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Abstract Climatic, ecological, and socioeconomic factors are facilitating the spread of mosquito-borne diseases, heightening the importance of vector surveillance and control. Citizen science is proving to be an effective tool to track mosquito populations, but methods are needed to detect and account for small scale sampling biases in citizen science surveillance. In this article we combine two types of traditional mosquito surveillance records with data from the Mosquito Alert citizen science system to explore the ways in which the socioeconomic characteristics of urban neighborhoods result in sampling biases in citizen scientists’ mosquito reports, while also shaping the spatial distribution of mosquito populations themselves. We use Barcelona, Spain, as an example, and focus on Aedes albopictus, an invasive vector species of concern worldwide. Our results suggest citizen scientists’ sampling effort is focused more in Barcelona’s lower and middle income census tracts than in its higher income ones, whereas Ae. albopictus populations are concentrated in the city’s upper-middle income tracts. High resolution estimates of the spatial distribution of Ae. albopictus risk can be improved by controlling for citizen scientists’ sampling effort, making it possible to provide better insights for efficiently targeting control efforts. Our methodology can be replicated in other cities faced with vector mosquitoes to improve public health responses to mosquito-borne diseases, which impose massive burdens on communities worldwide.

Abstract Background Recently, Europe has seen an emergence of mosquito-borne viruses (MBVs). Understanding citizens’ perceptions of and behaviours towards mosquitoes and MBVs is crucial to reduce disease risk. We investigated and compared perceptions, knowledge, and determinants of citizens’ behavioural intentions related to mosquitoes and MBVs in the Netherlands and Spain, to help improve public health interventions. Methods Using the validated MosquitoWise survey, data was collected through participant panels in Spain (N = 475) and the Netherlands (N = 438). Health Belief Model scores measuring behavioural intent, knowledge, and information scores were calculated. Confidence Interval-Based Estimation of Relevance was used, together with potential for change indexes, to identify promising determinants for improving prevention measure use. Results Spanish participants’ responses showed slightly higher intent to use prevention measures compared to those of Dutch participants (29.1 and 28.2, respectively, p 0.03). Most participants in Spain (92.2%) and the Netherlands (91.8%) indicated they used at least one prevention measure, but differences were observed in which types they used. More Spanish participants indicated to have received information on mosquitoes and MBVs compared to Dutch participants. Spanish participants preferred health professional information sources, while Dutch participants favoured government websites. Determinants for intent to use prevention measures included “Knowledge”, “Reminders to Use Prevention Measures”, and “Information” in the Netherlands and Spain. Determinants for repellent use included “Perceived Benefits” and “Cues to Action”, with “Perceived Benefits” having a high potential for behavioural change in both countries. “Self-Efficacy” and “Knowledge” were determinants in both countries for breeding site removal. Conclusion This study found differences in knowledge between the Netherlands and Spain but similarities in determinants for intent to use prevention measures, intent to use repellents and intent to remove mosquito breeding sites. Identified determinants can be the focus for future public health interventions to reduce MBV risks.

Abstract We use complex systems science to explore the emergent behavioral patterns that typify eusocial species, using collective ant foraging as a paradigmatic example. Our particular aim is to provide a methodology to quantify how the collective orchestration of foraging provides functional advantages to ant colonies. For this, we combine (i) a purpose-built experimental arena replicating ant foraging across realistic spatial and temporal scales, and (ii) a set of analytical tools, grounded in information theory and spin-glass approaches, to explore the resulting data. This combined approach yields computational replicas of the colonies; these are high-dimensional models that store the experimental foraging patterns through a training process, and are then able to generate statistically similar patterns, in an analogous way to machine learning tools. These in silico models are then used to explore the colony performance under different resource availability scenarios. Our findings highlight how replicas of the colonies trained under constant and predictable experimental food conditions exhibit heightened foraging efficiencies, manifested in reduced times for food discovery and gathering, and accelerated transmission of information under similar conditions. However, these same replicas demonstrate a lack of resilience when faced with new foraging conditions. Conversely, replicas of colonies trained under fluctuating and uncertain food conditions reveal lower efficiencies at specific environments but increased resilience to shifts in food location.

Abstract Background Aedes albopictus (Skuse, 1894) is a vector for pathogens like dengue, chikungunya, and Zika viruses. Its adaptive capacity enables reproduction in temperate climates and development mainly in artificial containers with fresh water in urbanized areas. Nevertheless, breeding in coastal areas may also occur along with its aggressive invasiveness. Global warming and the consequent rise in sea levels will increase saline (> 30 ppt) or brackish (0.5–30 ppt salt) water in coastal regions. To address whether Ae. albopictus can breed in brackish water, we initiated the current study that analyses the survival of immature stages at different salinity concentrations and explores whether carryover effects occur in the resulting adults. This possible adaptation is important when considering the potential for development in new habitats and expansion of one of the world’s most invasive species. Methods We investigated the influence of salinity on the survival of Ae. albopictus larvae and adults under laboratory-controlled conditions. First instar larvae were exposed to different salinity concentrations (0 to 30 ppt) and their development time, pupation, adult emergence, and overall survival were monitored daily. We used Kaplan-Meier and Cox regression models to analyze the survival rates at different salinity levels. Furthermore, life tables were constructed under each salinity concentration. Results Increasing salt concentrations significantly increased the mortality risk during immature development, while no significant effect was observed on adult mortality risk. A comparison between distilled and bottled water revealed a notable increase in overall mortality risk for individuals developing in distilled water. However, no significant effects were found when analyzing survival from the first larval stage to adult emergence and adult lifespan. The life expectancy of immature stages decreased with increasing salt concentrations, although salinity concentration did not significantly impact adult life expectancy. Conclusions Our findings suggest that Ae. albopictus, previously considered freshwater species, can successfully develop and survive in brackish waters, even in the absence of characteristic structures found in euryhaline species. These adaptations may enable Ae. albopictus to establish new breeding sites and colonize unexplored territories. Knowledge of these physiological adaptations of Ae. albopictus to salinity should be pursued to increase the range of control of the species, and to make more accurate predictions of its dispersal and vectoring ability. Graphical Abstract

Abstract Due to climate change and the expanding geographical ranges of key mosquito species, several mosquito-borne viruses (MBVs) have recently emerged in Europe. Understanding people’s perceptions and behaviours towards these viruses and the mosquitoes capable of transmitting them is crucial for implementing effective prevention measures and targeted communication campaigns. However, there is currently no appropriate validated survey for European populations to assess this. This study developed and validated a standardized survey, based on the Health Belief Model (HBM), to assess perceptions of mosquitoes and MBVs among Europe’s residents. The survey was distributed online to United Kingdom (UK), Dutch and Spanish participants through panel providers. Survey validity and reliability were tested using confirmatory factor analysis (CFA) and Cronbach’s alpha. The optimised survey was completed by 336 UK, 438 Dutch and 475 Spanish residents, respectively, and the HBM items passed our validity and reliability testing in all three countries. The final survey has 57 questions, including 19 validated HBM items, and questions to assess demographic characteristics, knowledge, prevention measures and behavioural determinants. Our MosquitoWise survey bridges researchers' understandings of European residents’ perceptions and knowledge as a first step to improve preventive behaviour towards mosquitoes and MBVs and guide prevention and communication initiatives.

Invasive mosquito species, such as Aedes albopictus, pose significant threats to both ecosystems and public health due to their role in transmitting diseases, such as dengue, Zika, and chikungunya. The Sterile Insect Technique (SIT) is a promising vector control strategy aimed at reducing mosquito populations by releasing sterile males to mate with wild females and reduce their reproduction rates. In this study, we employed the captive cohort method, which assesses the remaining longevity of randomly caught released individuals, to assess the longevity and frailty dynamics of sterile and non-sterile Ae. albopictus males. Using a mark–release–recapture approach (MRR), we compared the residual lifespan of sterile and non-sterile released males with that of wild, non-sterile males, aiming to understand the frailty dynamics of released males and, therefore, their quality and field performance. Contrary to expectations, our results revealed that released sterile males showed increased longevity compared to non-sterile males. Further, the marking process did not impact the longevity between lab-kept and marked males, suggesting that the marking process does not adversely affect survival under controlled conditions. These findings underscore the importance of optimizing pre-release and mass-rearing practices to enhance the effectiveness of SIT programs. Our study also demonstrates for the first time the use of the captive cohort method for understanding the biological dynamics of sterile mosquito populations in SIT programs, providing valuable insights for improving vector control strategies.

BackgroundUnderstanding the patterns of disease importation through international travel is paramount for effective public health interventions and global disease surveillance. While global airline network data have been used to assist in outbreak prevention and effective preparedness, accurately estimating how these imported cases disseminate locally in receiving countries remains a challenge. ObjectiveThis study aimed to describe and understand the regional distribution of imported cases of dengue and malaria upon arrival in Spain via air travel. MethodsWe have proposed a method to describe the regional distribution of imported cases of dengue and malaria based on the computation of the “travelers’ index” from readily available socioeconomic data. We combined indicators representing the main drivers for international travel, including tourism, economy, and visits to friends and relatives, to measure the relative appeal of each region in the importing country for travelers. We validated the resulting estimates by comparing them with the reported cases of malaria and dengue in Spain from 2015 to 2019. We also assessed which motivation provided more accurate estimates for imported cases of both diseases. ResultsThe estimates provided by the best fitted model showed high correlation with notified cases of malaria (0.94) and dengue (0.87), with economic motivation being the most relevant for imported cases of malaria and visits to friends and relatives being the most relevant for imported cases of dengue. ConclusionsFactual descriptions of the local movement of international travelers may substantially enhance the design of cost-effective prevention policies and control strategies, and essentially contribute to decision-support systems. Our approach contributes in this direction by providing a reliable estimate of the number of imported cases of nonendemic diseases, which could be generalized to other applications. Realistic risk assessments will be obtained by combining this regional predictor with the observed local distribution of vectors.

Abstract Background Determination of the interactions between hematophagous mosquitoes and their human hosts is of great importance for better understanding the transmission dynamics of mosquito-borne arboviruses and developing effective strategies to mitigate risk. Genetic analysis of human and mosquito DNA can play a key role in this, but commercial kits for human short tandem repeat (STR) genotyping are expensive and do not allow for the simultaneous STR analysis of host and vector DNA. Here, we present an inexpensive and straightforward STR-loci multiplex system capable of simultaneously amplifying Aedes albopictus and human STRs from blood-fed mosquitoes. Additionally, we examine the effect of storage methods and post-feeding time on the integrity of host DNA. Methods Thirty-five STRs (16 human and 19 Ae. albopictus STRs) subdivided in three multiplexes were tested for amplification and scoring reliability. Under laboratory conditions we compared the efficacy of two preservation methods (absolute ethanol vs lysis buffer) on the integrity of host DNA in Ae. albopictus blood meals. We also evaluated the effect of post-feeding time by sacrificing blood-fed mosquitoes at different time intervals after feeding, and we assessed our ability to detect multiple feedings. To determine if the system can be employed successfully under field conditions, we carried out a preliminary study using field-collected Ae. albopictus. Results All 35 STRs amplified consistently in the laboratory. Lysis buffer performed better than absolute ethanol in terms of allele peak height and clarity of electropherograms. Complete human DNA profiles could be obtained up to 48 h following the blood meal. Analysis of multiple feedings confirmed that peak heights can be used as a proxy to determine post-feeding time and thus derive the number of different people bitten by a mosquito. In the field trial, amplification was successful for 32 STRs. We found human DNA signal in 38 of the 61 field-collected mosquitoes (62%), of which 34 (89%) had ingested a single blood meal, while four (11%) contained double meals. Conclusions Our new genotyping system allows fast and reliable screening of both host and vector species, and can be further adapted to other mosquito species living in close contact with humans. Graphical Abstract

Mosquito species, including the Asian tiger mosquito, can transmit disease-causing pathogens such as dengue, Zika, and chikungunya, with their population dynamics influenced by a variety of factors including climate shifts, human activity, and local environmental conditions. Understanding these dynamics is vital for effective control measures. Our study, conducted in Jardí Botanic Marimurtra from May to November 2021, monitored Ae. albopictus activity using BG-Traps and investigated larval control effects. We employed Generalized Linear Mixed Models to analyze variables like weather, human presence, and larvicidal control on adult mosquito abundance. Adults of Ae. albopictus exhibited a seasonal pattern influenced by temperature but with bimodal peaks linked to cumulative rainfall. Proximity to stagnant water and visitor influx directly affected mosquito captures. Additionally, the effectiveness of larvicide treatments depended on interactions between preceding rainfall levels and treatment timing. Our research emphasizes the significance of studying vector ecology at local scales to enhance the efficacy of control programs and address the escalating burden of vector-borne diseases. Considering the impacts of extreme weather events and climate shifts is essential for the development of robust vector control strategies. Furthermore, our distinct findings serve as a prime illustration of utilizing statistical modeling to gain mechanistic insights into ecological patterns and processes.

Abstract Background Age structure and longevity constitute fundamental determinants of mosquito populations’ capacity to transmit pathogens. However, investigations on mosquito-borne diseases primarily focus on aspects such as abundance or dispersal rather than survival and demography. Here, we examine the post-capture longevity of wild-caught populations of the Asian tiger mosquito Aedes albopictus to investigate the influence of environmental factors and individual frailty on longevity. Methods We captured females of Ae. albopictus from June to November 2021 in a vegetated and an urban area by two methods of capture (BG traps and Human Landing catch). They were kept in semi-controlled conditions in the field, and survival was monitored daily across the 859 individuals captured. We studied the differences in longevity per capture method and location and the influence on longevity of seasonal, climatic and individual factors. Results Photoperiod, GDD, minimum and maximum temperature and relative humidity showed an effect on the risk of death of females in the field. Females captured in urban area with Human Landing catch methods had greater longevity than females captured in non-urban areas with BG traps. Individual variance, reflecting individual frailties, had an important effect on the risk of death: the greater the frailty, the shorter the post-capture longevity. Overall, longevity is affected not only by climate and seasonal drivers like temperature and photoperiod but also by the individual frailty of mosquitoes. Conclusion This work unravels environmental drivers of key demographic parameters such as longevity, as modulated by individual frailty, in disease vectors with strong seasonal dynamics. Further demographic understanding of disease vectors in the wild is needed to adopt new surveillance and control strategies and improve our understanding of disease risk and spread.

Abstract Worldwide, citizen scientists help to map the distribution of native and introduced mosquito species in a variety of programs, contributing to environmental research and management decisions. Participant background, behavior, and engagement may vary depending on the project design, especially between those using digital apps and those using physical samples, which in turn may impact the quality and representativeness of the data collected. During the analysis of the responses to a survey directed at citizen scientists participating in a digital and an analog program, we found significant differences in the respondents’ demographic backgrounds. Diverse participant motivations and varying sentiments towards mosquitoes were observed, indicating differing susceptibility in response to the program messages. The results can be translated into recommendations to further strengthen the appeal of citizen science projects and to promote and sustain public engagement in environmental research.

Abstract A comprehensive view of disease epidemics demands a deep understanding of the complex interplay between human behaviour and infectious diseases. Here, we propose a flexible modelling framework that brings conclusions about the influence of human mobility and disease transmission on early epidemic growth, with applicability in outbreak preparedness. We use random matrix theory to compute an epidemic threshold, equivalent to the basic reproduction number $$R_{0}$$ R 0 , for a SIR metapopulation model. The model includes both systematic and random features of human mobility. Variations in disease transmission rates, mobility modes (i.e. commuting and migration), and connectivity strengths determine the threshold value and whether or not a disease may potentially establish in the population, as well as the local incidence distribution.

BackgroundWest Nile virus (WNV) outbreaks in birds, humans, and livestock have occurred in multiple areas in Europe and have had a significant impact on animal and human health. The patterns of emergence and spread of WNV in Europe are very different from those in the US and understanding these are important for guiding preparedness activities.MethodsWe mapped the evolution and spread history of WNV in Europe by incorporating viral genome sequences and epidemiological data into phylodynamic models. Spatially explicit phylogeographic models were developed to explore the possible contribution of different drivers to viral dispersal direction and velocity. A "skygrid-GLM" approach was used to identify how changes in environments would predict viral genetic diversity variations over time.FindingsAmong the six lineages found in Europe, WNV-2a (a sub-lineage of WNV-2) has been predominant (accounting for 73% of all sequences obtained in Europe that have been shared in the public domain) and has spread to at least 14 countries. In the past two decades, WNV-2a has evolved into two major co-circulating clusters, both originating from Central Europe, but with distinct dynamic history and transmission patterns. WNV-2a spreads at a high dispersal velocity (88km/yr-215 km/yr) which is correlated to bird movements. Notably, amongst multiple drivers that could affect the spread of WNV, factors related to land use were found to strongly influence the spread of WNV. Specifically, the intensity of agricultural activities (defined by factors related to crops and livestock production, such as coverage of cropland, pasture, cultivated and managed vegetation, livestock density) were positively associated with both spread direction and velocity. In addition, WNV spread direction was associated with high coverage of wetlands and migratory bird flyways.ConclusionOur results suggest that-in addition to ecological conditions favouring bird- and mosquito- presence-agricultural land use may be a significant driver of WNV emergence and spread. Our study also identified significant gaps in data and the need to strengthen virological surveillance in countries of Central Europe from where WNV outbreaks are likely seeded. Enhanced monitoring for early detection of further dispersal could be targeted to areas with high agricultural activities and habitats of migratory birds.

Abstract Robust and reliable estimates of demographic parameters are essential to understand population dynamics. Natal dispersal is a common process in monitored populations and can cause underestimations of survival and dispersal due to permanent emigration. Here, we present a multistate Bayesian capture-mark-recapture approach based on a joint estimation of natal dispersal kernel and detection probabilities to address biases in survival, dispersal, and related demographic parameters when dispersal information is limited. We implement this approach to long-term data of a threatened population: the Bonelli’s eagle in Catalonia (SW Europe). To assess the method’s performance, we compare demographic estimates structured by sex, age, and breeding status in cases of limited versus large data scales, with those of classical models where dispersal and detection probabilities are estimated separately. Results show substantial corrections of demographic estimates. Natal dispersal and permanent emigration probabilities were larger in females, and consequently, female non-breeder survival showed larger differences between separate and joint estimation models. Moreover, our results suggest that estimates are sensitive to the choice of the dispersal kernel, fat-tailed kernels providing larger values in cases of data limitation. This study provides a general multistate framework to model demographic parameters while correcting permanent emigration biases caused by natal dispersal.

Abstract Background Changes in human-induced resource availability can alter the behaviour of free-living species and affect their foraging strategies. The future European Landfill Waste Directive and Circular Economy Action Plan will reduce the number of predictable anthropogenic food subsidies (PAFS), above all, by closing landfills to preclude negative effects on human health. Obligate avian scavengers, the most threatened group of birds worldwide, are the most likely group of species that will be forced to change their behaviour and use of space in response to landfill site closures. Here, we examine the possible consequences of these management decisions on the foraging patterns of Egyptian vultures (Neophron percnopterus) in an expanding population in the Iberian Peninsula. Methods We tracked 16 individuals in 2018–2021, including breeders and non-breeders, and, using a combination of spatial-use and spatial-network modelling, assessed landscape connectivity between key resources based on movement patterns. We then carried out simulations of future scenarios based on the loss of PAFS to predict likely changes in the movement patterns of both non-breeders and breeders. Results Our results show that foraging strategies in non-breeders and breeders differ significantly: non-breeders performed more dispersal movements than breeding birds across a spatial-use network. Non-breeding and breeding networks were found to be vulnerable to the removal of central foraging areas containing landfill sites, a highly predictable resource, while perturbation analysis showed dissimilar foraging responses to the gradual reduction of other predictable resources. Under a context of the non-availability of landfills for breeders and non-breeders, vultures will increase their use of extensive livestock as a trophic resource. Conclusions Future environmental policies should thus extend the areas used by scavengers in which livestock carcasses are allowed to remain in the wild, a strategy that will also mitigate the lack of food caused by any reduction in available waste if landfills close. In general, our results emphasize the capabilities of a spatial network approaches to address questions on movement ecology. They can be used to infer the behavioural response of animal species and, also demonstrate the importance of applying such approaches to endangered species conservation within a context of changing humanized scenarios.

Physical distancing and contact tracing are two key components in controlling the COVID-19 epidemics. Understanding their interaction at local level is important for policymakers. We propose a flexible modeling framework to assess the effect of combining contact tracing with different physical distancing strategies. Using scenario tree analyses, we compute the probability of COVID-19 detection using passive surveillance, with and without contact tracing, in metropolitan Barcelona. The estimates of detection probability and the frequency of daily social contacts are fitted into an age-structured susceptible-exposed-infectious-recovered compartmental model to simulate the epidemics considering different physical distancing scenarios over a period of 26 weeks. With the original Wuhan strain, the probability of detecting an infected individual without implementing physical distancing would have been 0.465, 0.515, 0.617, and 0.665 in designated age groups (0–14, 15–49, 50–64, and >65), respectively. As the physical distancing measures were reinforced and the disease circulation decreased, the interaction between the two interventions resulted in a reduction of the detection probabilities; however, despite this reduction, active contact tracing and isolation remained an effective supplement to physical distancing. If we relied solely on passive surveillance for diagnosing COVID-19, the model required a minimal 50% (95% credible interval, 39–69%) reduction of daily social contacts to keep the infected population under 5%, as compared to the 36% (95% credible interval, 22–56%) reduction with contact tracing systems. The simulation with the B.1.1.7 and B.1.167.2 strains shows similar results. Our simulations showed that a functioning contact tracing program would reduce the need for physical distancing and mitigate the COVID-19 epidemics.

Abstract The Asian tiger mosquito, Aedes albopictus, is one of the most invasive species in the world. Native to the tropical forests of Southeast Asia, over the past 30 years it has rapidly spread throughout tropical and temperate regions of the world. Its dramatic expansion has resulted in public health concerns as a consequence of its vector competence for at least 16 viruses. Previous studies showed that Ae. albopictus spread has been facilitated by human-mediated transportation, but much remains unknown about how this has affected its genetic attributes. Here we examined the factors that contributed to shaping the current genetic constitution of Ae. albopictus in the Iberian Peninsula, where the species was first found in 2004, by combining population genetics and Bayesian modelling. We found that both mitochondrial and nuclear DNA markers showed a lack of genetic structure and the presence of worldwide dominant haplotypes, suggesting regular introductions from abroad. Mitochondrial DNA showed little genetic diversity compared to nuclear DNA, likely explained by infection with maternally transmitted bacteria of the genus Wolbachia. Multilevel models revealed that greater mosquito fluxes (estimated from commuting patterns and tiger mosquito population distribution) and spatial proximity between sampling sites were associated with lower nuclear genetic distance, suggesting that rapid short- and medium-distance dispersal is facilitated by humans through vehicular traffic. This study highlights the significant role of human transportation in shaping the genetic attributes of Ae. albopictus and promoting regional gene flow, and underscores the need for a territorially integrated surveillance across scales of this disease-carrying mosquito.

Summary: Climate change is one of several drivers of recurrent outbreaks and geographical range expansion of infectious diseases in Europe. We propose a framework for the co-production of policy-relevant indicators and decision-support tools that track past, present, and future climate-induced disease risks across hazard, exposure, and vulnerability domains at the animal, human, and environmental interface. This entails the co-development of early warning and response systems and tools to assess the costs and benefits of climate change adaptation and mitigation measures across sectors, to increase health system resilience at regional and local levels and reveal novel policy entry points and opportunities. Our approach involves multi-level engagement, innovative methodologies, and novel data streams. We take advantage of intelligence generated locally and empirically to quantify effects in areas experiencing rapid urban transformation and heterogeneous climate-induced disease threats. Our goal is to reduce the knowledge-to-action gap by developing an integrated One Health—Climate Risk framework.

Dimensionality reduction methods are fundamental to the exploration and visualisation of large data sets. Basic requirements for unsupervised data exploration are flexibility and scalability. However, current methods have computational limitations that restrict our ability to explore data structures to the lower range of scales. We focus on t-SNE and propose a chunk-and-mix protocol that enables the parallel implementation of this algorithm, as well as a self-adaptive parametric scheme that facilitates its parametric configuration. As a proof of concept, we present the pt-SNE algorithm, a parallel version of Barnes-Hat-SNE (an $O\left(n\,\mathrm{log}\,n\right)$ implementation of t-SNE). In pt-SNE, a single free parameter for the size of the neighbourhood, namely the perplexity, modulates the visualisation of the data structure at different scales, from local to global. Thanks to parallelisation, the runtime of the algorithm remains almost independent of the perplexity, which extends the range of scales to be analysed. The pt-SNE converges to a good global embedding comparable to current solutions, although it adds little noise at the local scale. This noise illustrates an unavoidable trade-off between computational speed and accuracy. We expect the same approach to be applicable to faster embedding algorithms than Barnes-Hat-SNE, such as Fast-Fourier Interpolation-based t-SNE or Uniform Manifold Approximation and Projection, thus extending the state of the art and allowing a more comprehensive visualisation and analysis of data structures.

Abstract Age drives differences in fitness components typically due to lower performances of younger and senescent individuals, and changes in breeding age structure influence population dynamics and persistence. However, determining age and age structure is challenging in most species, where distinctive age features are lacking and available methods require substantial efforts or invasive procedures. Here we explore the potential to assess the age of breeders, or at least to identify young and senescent individuals, by measuring some breeding parameters partially driven by age (e.g. egg volume in birds). Taking advantage of a long-term population monitored seabird, we first assessed whether age influenced egg volume, and identified other factors driving this trait by using general linear models. Secondly, we developed and evaluated a machine learning algorithm to assess the age of breeders using measurable variables. We confirmed that both younger and older individuals performed worse (less and smaller eggs) than middle-aged individuals. Our ensemble training algorithm was only able to distinguish young individuals, but not senescent breeders. We propose to test the combined use of field monitoring, classic regression analysis and machine learning methods in other wild populations were measurable breeding parameters are partially driven by age, as a possible tool for assessing age structure in the wild.

Dimension reduction methods on porcine sperm motility landscapes reveal heterogeneity and hierarchy in sperm movement behavior and show high-speed and straight-lined motion as predictive features of fertility.

Even as novel technologies emerge and medicines advance, pathogen-transmitting mosquitoes pose a deadly and accelerating public health threat. Detecting and mitigating the spread of Anopheles stephensi in Africa is now critical to the fight against malaria, as this invasive mosquito poses urgent and unprecedented risks to the continent. Unlike typical African vectors of malaria, An. stephensi breeds in both natural and artificial water reservoirs, and flourishes in urban environments. With An. stephensi beginning to take hold in heavily populated settings, citizen science surveillance supported by novel artificial intelligence (AI) technologies may offer impactful opportunities to guide public health decisions and community-based interventions. Coalitions like the Global Mosquito Alert Consortium (GMAC) and our freely available digital products can be incorporated into enhanced surveillance of An. stephensi and other vector-borne public health threats. By connecting local citizen science networks with global databases that are findable, accessible, interoperable, and reusable (FAIR), we are leveraging a powerful suite of tools and infrastructure for the early detection of, and rapid response to, (re)emerging vectors and diseases.

Abstract Background Classic ecological formulations of predator–prey interactions often assume that predators and prey interact randomly in an information-limited environment. In the field, however, most prey can accurately assess predation risk by sensing predator chemical cues, which typically trigger some form of escape response to reduce the probability of capture. Here, we explore under laboratory-controlled conditions the long-term (minutes to hours) escaping response of the sea urchin Paracentrotus lividus, a key species in Mediterranean subtidal macrophyte communities. Methods Behavioural experiments involved exposing a random sample of P. lividus to either one of two treatments: (i) control water (filtered seawater) or (ii) predator-conditioned water (with cues from the main P. lividus benthic predator—the gastropod Hexaplex trunculus). We analysed individual sea urchin trajectories, computed their heading angles, speed, path straightness, diffusive properties, and directional entropy (as a measure of path unpredictability). To account for the full picture of escaping strategies, we followed not only the first instants post-predator exposure, but also the entire escape trajectory. We then used linear models to compare the observed results from control and predators treatments. Results The trajectories from sea urchins subjected to predator cues were, on average, straighter and faster than those coming from controls, which translated into differences in the diffusive properties and unpredictability of their movement patterns. Sea urchins in control trials showed complex diffusive properties in an information-limited environment, with highly variable trajectories, ranging from Brownian motion to superdiffusion, and even marginal ballistic motion. In predator cue treatments, variability reduced, and trajectories became more homogeneous and predictable at the edge of ballistic motion. Conclusions Despite their old evolutionary origin, lack of cephalization, and homogenous external appearance, the trajectories that sea urchins displayed in information-limited environments were complex and ranged widely between individuals. Such variable behavioural repertoire appeared to be intrinsic to the species and emerged when the animals were left unconstrained. Our results highlight that fear from predators can be an important driver of sea urchin movement patterns. All in all, the observation of anomalous diffusion, highly variable trajectories and the behavioural shift induced by predator cues, further highlight that the functional forms currently used in classical predator–prey models are far from realistic.

Abstract Background Active surveillance aimed at the early detection of invasive mosquito species is usually focused on seaports and airports as points of entry, and along road networks as dispersion paths. In a number of cases, however, the first detections of colonizing populations are made by citizens, either because the species has already moved beyond the implemented active surveillance sites or because there is no surveillance in place. This was the case of the first detection in 2018 of the Asian bush mosquito, Aedes japonicus, in Asturias (northern Spain) by the citizen science platform Mosquito Alert. Methods The collaboration between Mosquito Alert, the Ministry of Health, local authorities and academic researchers resulted in a multi-source surveillance combining active field sampling with broader temporal and spatial citizen-sourced data, resulting in a more flexible and efficient surveillance strategy. Results Between 2018 and 2020, the joint efforts of administrative bodies, academic teams and citizen-sourced data led to the discovery of this species in northern regions of Spain such as Cantabria and the Basque Country. This raised the estimated area of occurrence of Ae. japonicus from < 900 km2 in 2018 to > 7000 km2 in 2020. Conclusions This population cluster is geographically isolated from any other population in Europe, which raises questions about its origin, path of introduction and dispersal means, while also highlighting the need to enhance surveillance systems by closely combining crowd-sourced surveillance with public health and mosquito control agencies’ efforts, from local to continental scales. This multi-actor approach for surveillance (either passive and active) shows high potential efficiency in the surveillance of other invasive mosquito species, and specifically the major vector Aedes aegypti which is already present in some parts of Europe. Graphical abstract

Abstract Global monitoring of disease vectors is undoubtedly becoming an urgent need as the human population rises and becomes increasingly mobile, international commercial exchanges increase, and climate change expands the habitats of many vector species. Traditional surveillance of mosquitoes, vectors of many diseases, relies on catches, which requires regular manual inspection and reporting, and dedicated personnel, making large-scale monitoring difficult and expensive. New approaches are solving the problem of scalability by relying on smartphones and the Internet to enable novel community-based and digital observatories, where people can upload pictures of mosquitoes whenever they encounter them. An example is the Mosquito Alert citizen science system, which includes a dedicated mobile phone app through which geotagged images are collected. This system provides a viable option for monitoring the spread of various mosquito species across the globe, although it is partly limited by the quality of the citizen scientists’ photos. To make the system useful for public health agencies, and to give feedback to the volunteering citizens, the submitted images are inspected and labeled by entomology experts. Although citizen-based data collection can greatly broaden disease-vector monitoring scales, manual inspection of each image is not an easily scalable option in the long run, and the system could be improved through automation. Based on Mosquito Alert’s curated database of expert-validated mosquito photos, we trained a deep learning model to find tiger mosquitoes (Aedes albopictus), a species that is responsible for spreading chikungunya, dengue, and Zika among other diseases. The highly accurate 0.96 area under the receiver operating characteristic curve score promises not only a helpful pre-selector for the expert validation process but also an automated classifier giving quick feedback to the app participants, which may help to keep them motivated. In the paper, we also explored the possibilities of using the model to improve future data collection quality as a feedback loop.

Abstract Background Plant dispersal is a critical factor driving ecological responses to global changes. Knowledge on the mechanisms of dispersal is rapidly advancing, but selective pressures responsible for the evolution of dispersal strategies remain elusive. Recent advances in animal movement ecology identified general strategies that may optimize efficiency in animal searches for food or habitat. Here we explore the potential for evolution of similar general movement strategies for plants. Methods We propose that seed dispersal in plants can be viewed as a strategic search for suitable habitat, where the probability of finding such locations has been optimized through evolution of appropriate dispersal kernels. Using model simulations, we demonstrate how dispersal strategies can optimize key dispersal trade-offs between finding habitat, avoiding kin competition, and colonizing new patches. These trade-offs depend strongly on the landscape, resulting in a tight link between optimal dispersal strategy and spatiotemporal habitat distribution. Results Our findings reveal that multi-scale seed dispersal strategies that combine a broad range of dispersal scales, including Lévy-like dispersal, are optimal across a wide range of dynamic and patchy landscapes. At the extremes, static and patchy landscapes select for dispersal strategies dominated by short distances, while uniform and highly unpredictable landscapes both select for dispersal strategies dominated by long distances. Conclusions By viewing plant seed dispersal as a strategic search for suitable habitat, we provide a reference framework for the analysis of plant dispersal data. Consideration of the entire dispersal kernel, including distances across the full range of scales, is key. This reference framework helps identify plant species’ dispersal strategies, the evolutionary forces determining these strategies and their ecological consequences, such as a potential mismatch between plant dispersal strategy and altered spatiotemporal habitat dynamics due to land use change. Our perspective opens up directions for future studies, including exploration of composite search behaviour and ‘informed searches’ in plant species with directed dispersal.

The Mosquito Alert dataset includes occurrence records of adult mosquitoes collected worldwide in 2014–2020 through Mosquito Alert, a citizen science system for investigating and managing disease-carrying mosquitoes. Records are linked to citizen science-submitted photographs and validated by entomologists to determine the presence of five targeted European mosquito vectors: Aedes albopictus, Ae. aegypti, Ae. japonicus, Ae. koreicus, and Culex pipiens. Most records are from Spain, reflecting Spanish national and regional funding, but since autumn 2020 substantial records from other European countries are included, thanks to volunteer entomologists coordinated by the AIM-COST Action, and to technological developments to increase scalability. Among other applications, the Mosquito Alert dataset will help develop citizen science-based early warning systems for mosquito-borne disease risk. It can also be reused for modelling vector exposure risk, or to train machine-learning detection and classification routines on the linked images, to assist with data validation and establishing automated alert systems.

Abstract Background Aedes japonicus is an invasive vector mosquito from Southeast Asia which has been spreading across central Europe since the year 2000. Unlike the Asian Tiger mosquito (Aedes albopictus) present in Spain since 2004, there has been no record of Ae. japonicus in the country until now. Results Here, we report the first detection of Ae. japonicus in Spain, at its southernmost location in Europe. This finding was triggered by the citizen science platform Mosquito Alert. In June 2018, a citizen sent a report via the Mosquito Alert app from the municipality of Siero in the Asturias region (NW Spain) containing pictures of a female mosquito compatible with Ae. japonicus. Further information was requested from the participant, who subsequently provided several larvae and adults that could be classified as Ae. japonicus. In July, a field mission confirmed its presence at the original site and in several locations up to 9 km away, suggesting a long-time establishment. The strong media impact in Asturias derived from the discovery raised local participation in the Mosquito Alert project, resulting in further evidence from surrounding areas. Conclusions Whilst in the laboratory Ae. japonicus is a competent vector for several mosquito-borne pathogens, to date only West Nile virus is a concern based on field evidence. Nonetheless, this virus has yet not been detected in Asturias so the vectorial risk is currently considered low. The opportunity and effectiveness of combining citizen-sourced data to traditional surveillance methods are discussed.

Mosquito-borne diseases continue to ravage humankind with >700 million infections and nearly one million deaths every year. Yet only a small percentage of the >3500 mosquito species transmit diseases, necessitating both extensive surveillance and precise identification. Unfortunately, such efforts are costly, time-consuming, and require entomological expertise. As envisioned by the Global Mosquito Alert Consortium, citizen science can provide a scalable solution. However, disparate data standards across existing platforms have thus far precluded truly global integration. Here, utilizing Open Geospatial Consortium standards, we harmonized four data streams from three established mobile apps—Mosquito Alert, iNaturalist, and GLOBE Observer’s Mosquito Habitat Mapper and Land Cover—to facilitate interoperability and utility for researchers, mosquito control personnel, and policymakers. We also launched coordinated media campaigns that generated unprecedented numbers and types of observations, including successfully capturing the first images of targeted invasive and vector species. Additionally, we leveraged pooled image data to develop a toolset of artificial intelligence algorithms for future deployment in taxonomic and anatomical identification. Ultimately, by harnessing the combined powers of citizen science and artificial intelligence, we establish a next-generation surveillance framework to serve as a united front to combat the ongoing threat of mosquito-borne diseases worldwide.

Emergence of collective, as well as superorganism-like, behaviour in biological populations requires the existence of rules of communication, either direct or indirect, between organisms. Because reaching an understanding of such rules at the individual level can be often difficult, approaches carried out at higher, or effective, levels of description can represent a useful alternative. In the present work, we show how a spin-glass approach characteristic of statistical physics can be used as a tool to characterize the properties of the spatial occupancy patterns of a biological population. We exploit the presence of pairwise interactions in spin-glass models for detecting correlations between occupancies at different sites in the media. Such correlations, we claim, represent a proxy to the existence of planned and/or social strategies in the spatial organization of the population. Our spin-glass approach does not only identify those correlations but produces a statistical replica of the system (at the level of occupancy patterns) that can be subsequently used for testing alternative conditions/hypothesis. Here, this methodology is presented and illustrated for a particular case of study: we analyse occupancy patterns of Aphaenogaster senilis ants during foraging through a simplified environment consisting of a discrete (tree-like) artificial lattice. Our spin-glass approach consistently reproduces the experimental occupancy patterns across time, and besides, an intuitive biological interpretation of the parameters is attainable. Likewise, we prove that pairwise correlations are important for reproducing these dynamics by showing how a null model, where such correlations are neglected, would perform much worse; this provides a solid evidence to the existence of superorganism-like strategies in the colony.

Monitoring of the spread of invasive mosquitos is important both for preventing and for understanding disease outbreaks. Here the author report that a scalable citizen science system can provide accurate early warning of the invasion process of the Asian tiger mosquito in Spain, with far more scalable coverage than that of traditional surveillance methods.

Abstract A characterization of the thermal ecology of fishes is needed to better understand changes in ecosystems and species distributions arising from global warming. The movement of wild animals during changing environmental conditions provides essential information to help predict the future thermal response of large marine predators. We used acoustic telemetry to monitor the vertical movement activity of the common dentex (Dentex dentex), a Mediterranean coastal predator, in relation to the oscillations of the seasonal thermocline during two summer periods in the Medes Islands marine reserve (NW Mediterranean Sea). During the summer stratification period, the common dentex presented a clear preference for the warm suprathermoclinal layer, and adjusted their vertical movements following the depth changes of the thermocline. The same preference was also observed during the night, when fish were less active. Due to this behaviour, we hypothesize that inter-annual thermal oscillations and the predicted lengthening of summer conditions will have a significant positive impact on the metabolic efficiency, activity levels, and population dynamics of this species, particularly in its northern limit of distribution. These changes in the dynamics of an ecosystem’s keystone predator might cascade down to lower trophic levels, potentially re-defining the coastal fish communities of the future.

Abstract The recent emergence in Europe of invasive mosquitoes and mosquito-borne disease associated with both invasive and native mosquito species has prompted intensified mosquito vector research in most European countries. Central to the efforts are mosquito monitoring and surveillance activities in order to assess the current species occurrence, distribution and, when possible, abundance, in order to permit the early detection of invasive species and the spread of competent vectors. As active mosquito collection, e.g. by trapping adults, dipping preimaginal developmental stages or ovitrapping, is usually cost-, time- and labour-intensive and can cover only small parts of a country, passive data collection approaches are gradually being integrated into monitoring programmes. Thus, scientists in several EU member states have recently initiated programmes for mosquito data collection and analysis that make use of sources other than targeted mosquito collection. While some of them extract mosquito distribution data from zoological databases established in other contexts, community-based approaches built upon the recognition, reporting, collection and submission of mosquito specimens by citizens are becoming more and more popular and increasingly support scientific research. Based on such reports and submissions, new populations, extended or new distribution areas and temporal activity patterns of invasive and native mosquito species were found. In all cases, extensive media work and communication with the participating individuals or groups was fundamental for success. The presented projects demonstrate that passive approaches are powerful tools to survey the mosquito fauna in order to supplement active mosquito surveillance strategies and render them more focused. Their ability to continuously produce biological data permits the early recognition of changes in the mosquito fauna that may have an impact on biting nuisance and the risk of pathogen transmission associated with mosquitoes. International coordination to explore synergies and increase efficiency of passive surveillance programmes across borders needs to be established.

The growing capacity to process and store animal tracks has spurred the development of new methods to segment animal trajectories into elementary units of movement. Key challenges for movement trajectory segmentation are to (i) minimize the need of supervision, (ii) reduce computational costs, (iii) minimize the need of prior assumptions (e.g. simple parametrizations), and (iv) capture biologically meaningful semantics, useful across a broad range of species. We introduce the Expectation-Maximization binary Clustering (EMbC), a general purpose, unsupervised approach to multivariate data clustering. The EMbC is a variant of the Expectation-Maximization Clustering (EMC), a clustering algorithm based on the maximum likelihood estimation of a Gaussian mixture model. This is an iterative algorithm with a closed form step solution and hence a reasonable computational cost. The method looks for a good compromise between statistical soundness and ease and generality of use (by minimizing prior assumptions and favouring the semantic interpretation of the final clustering). Here we focus on the suitability of the EMbC algorithm for behavioural annotation of movement data. We show and discuss the EMbC outputs in both simulated trajectories and empirical movement trajectories including different species and different tracking methodologies. We use synthetic trajectories to assess the performance of EMbC compared to classic EMC and Hidden Markov Models. Empirical trajectories allow us to explore the robustness of the EMbC to data loss and data inaccuracies, and assess the relationship between EMbC output and expert label assignments. Additionally, we suggest a smoothing procedure to account for temporal correlations among labels, and a proper visualization of the output for movement trajectories. Our algorithm is available as an R-package with a set of complementary functions to ease the analysis.

It is important to account for the movement behaviour of fishes when designing effective marine protected areas (MPAs). Fish movements occur across different spatial and temporal scales and understanding the variety of movements is essential to make correct management decisions. This study describes in detail the movement patterns of an economically and commercially important species, Diplodus sargus, within a well-enforced Mediterranean MPA. We monitored horizontal and vertical movements of 41 adult individuals using passive acoustic telemetry for up to one year. We applied novel analysis and visualization techniques to get a comprehensive view of a wide range of movements. D. sargus individuals were highly territorial, moving within small home ranges (< 1 km2), inside which they displayed repetitive diel activity patterns. Extraordinary movements beyond the ordinary home range were observed under two specific conditions. First, during stormy events D. sargus presented a sheltering behaviour, moving to more protected places to avoid the disturbance. Second, during the spawning season they made excursions to deep areas (> 50 m), where they aggregated to spawn. This study advances our understanding about the functioning of an established MPA and provides important insights into the biology and management of a small sedentary species, suggesting the relevance of rare but important fish behaviours.

Recent theoretical developments had laid down the proper mathematical means to understand how the structural complexity of search patterns may improve foraging efficiency. Under information-deprived scenarios and specific landscape configurations, Lévy walks and flights are known to lead to high search efficiencies. Based on a one-dimensional comparative analysis we show a mechanism by which, at random, a searcher can optimize the encounter with close and distant targets. The mechanism consists of combining an optimal diffusivity (optimally enhanced diffusion) with a minimal diffusion constant. In such a way the search dynamics adequately balances the tension between finding close and distant targets, while, at the same time, shifts the optimal balance towards relatively larger close-to-distant target encounter ratios. We find that introducing a multiscale set of reorientations ensures both a thorough local space exploration without oversampling and a fast spreading dynamics at the large scale. Lévy reorientation patterns account for these properties but other reorientation strategies providing similar statistical signatures can mimic or achieve comparable efficiencies. Hence, the present work unveils general mechanisms underlying efficient random search, beyond the Lévy model. Our results suggest that animals could tune key statistical movement properties (e.g. enhanced diffusivity, minimal diffusion constant) to cope with the very general problem of balancing out intensive and extensive random searching. We believe that theoretical developments to mechanistically understand stochastic search strategies, such as the one here proposed, are crucial to develop an empirically verifiable and comprehensive animal foraging theory.

Lake Redó, a dimictic oligotrophic mountain lake, was monitored for two complete years from July 1996 to July 1998. The main seasonal variations in the physical, chemical and biological parameters are described, with special emphasis on the comparison of external forcing (weather and atmospheric deposition) with internal lake dynamics. Annual mean air temperature was estimated to be 3.6 °C. The duration of ice cover on the lake was 4.5 months in 1996/97 and 5.8 months in 1997/98. The lake water was very ionpoor (mean annual conductivity 12 μS cm-1); however, ion concentrations in the lake were higher than in the precipitation, the differences being due mainly to Ca2+ and bicarbonates originating in the catchment. NH4 + was the main ion in the precipitation, with an average concentration of 17 μM, while in the lake it was always below 3 μM. However, the concentration of dissolved inorganic nitrogen always exceeded that of soluble reactive phosphorus by two or three orders of magnitude, so the latter is likely to be the limiting nutrient for phytoplankton growth. Four main production episodes were identified, occurring during spring and autumn overturn, in the upper hypolimnion during summer stratification, and under the ice at the beginning of the ice-covered period. The highest chlorophyll-a concentrations (1.2-2.2 μg l-1) were attained during spring overturn; concentrations of chlorophyll-c were high during both spring and autumn overturn, while chlorophyll-b was comparatively important in the upper hypolimnion during the stratification period. Daphnia pulicaria was the most abundant macrozooplankton species; its abundance was highest during the icecovered period, when its biomass was comparable to the measured sestonic particulate carbon concentration. The Daphnia maximum was associated with higher concentrations of NH4 + and dissolved organic carbon, suggesting that it may play an important role in the pelagic biogeochemical compartment of the lake under ice. Winter respiration rates for the lake were estimated to be 339 mg O2 m-2 d-1 for 1996/97 and 281 mg O2 m-2 d-1 for 1997/98.

Microbial plankton composition and biomass were monitored for two ice-free periods in a deep oligotrophic high-mountain lake (Redó, Pyrenees). Phytoplankton dominated microbial biomass, while the relationship between total water-column-integrated autotrophic and heterotrophic biomass ranged from 1.5 to 6.5 (an average of 4.4). Heterotrophic biomass was dominated by bacteria (an average of 47 %), but heterotrophic nanoflagellates and, to a lesser degree, ciliates occasionally constituted a sizeable proportion. In general, the microbial biomass ratios were 10:2:2:1 for PHY:BAC:HNF:CIL. About one hundred eukaryotic species were found, although most of them in low abundance and frequency. Phytoplankton biomass was dominated by flagellated chrysophytes and dinoflagellates (an average of 40 and 32% respectively); occasionally cryptophytes (in deep layers) and chlorococcal chlorophytes (during the autumn mixing period) were also significant. In the two years sampled, the maximum phytoplankton diversity was observed during the autumn mixing period. Heterotrophic flagellate biomass was dominated by chrysophytes (78% on average), but sporadically a non-identified species reached high abundances. Oligotrichs, (an average of 43% of total ciliate biomass) dominated the ciliate community, still other groups (gymnostomatida and prostomatida) were also significant. Bacteria biomass was largely homogeneous throughout the two periods, but size segregation was observed especially when the lake was stratified, with larger bacteria appearing in the upper layers. The highest planktonic microbial biomass occurred during the mixing periods, mainly during spring. But no clear relationships were found between the temporal distribution of bacteria, phytoplankton, heterotrophic flagellate and ciliate biomass.

The biological activity of the planktonic community of lake Redó, expressed in terms of carbon fluxes, was measured and compared to the changes in DIC, DOC and POC in the water column. Planktonic photosynthesis ranged between c. 0.01 - 0.3 μg C m-2 h-1. Release of EOC phytoplankton was highly variable, between 5 and 80% of total fixation. Bacterial uptake of EOC ranged between 1-20% of total fixation. Bacterial activities were, in absolute numbers, very low: 0.005±0.003 μg C m-2 h-1, in contrast with the higher grazing rates on bacteria of 0.036±0.021 μg C m-2 h-1. Respiration and diffusion of CO2 to the atmosphere seem to be the main processes controlling DIC concentration. DOC and POC concentrations were highly correlated, and their fluxes presented large fluctuations. These changes in DOC are larger than those due to the processes we have measured. Other processes that might affect DOC include diffusion from sediments, inputs from the catchment, uptake by mixotrophic algae and zooplankton, bacterial respiration, UV photoxidation, and flocculation. Lake Redó seems to act in general terms as an heterotrophic system: respiration is higher than photosynthesis, and the budget is balanced by the import of DOC and, to a lesser extent, POC. Most of the carbon seems to be ultimately released to atmosphere, since little is accumulated in sediments. The estimates of diffusive fluxes agreed with this hypothesis. At this stage, the comparison of biogeochemical budgets with biological activity measurements only serves as a rough approximation of the main pathways in the C cycling in the lake, and to point the issues that need further research in order to calculate the C budget in the lake with accuracy.

Animals can exhibit complex movement patterns that may be the result of interactions with their environment or may be directly the mechanism by which their behaviour is governed. In order to understand the drivers of these patterns we examine the movement behaviour of individual desert locusts in a homogenous experimental arena with minimal external cues. Locust motion is intermittent and we reveal that as pauses become longer, the probability that a locust changes direction from its previous direction of travel increases. Long pauses (of greater than 100 s) can be considered reorientation bouts, while shorter pauses (of less than 6 s) appear to act as periods of resting between displacements. We observe power-law behaviour in the distribution of move and pause lengths of over 1.5 orders of magnitude. While Lévy features do exist, locusts' movement patterns are more fully described by considering moves, pauses and turns in combination. Further analysis reveals that these combinations give rise to two behavioural modes that are organized in time: local search behaviour (long exploratory pauses with short moves) and relocation behaviour (long displacement moves with shorter resting pauses). These findings offer a new perspective on how complex animal movement patterns emerge in nature.

Many attempts to relate animal foraging patterns to landscape heterogeneity are focused on the analysis of foragers movements. Resource detection patterns in space and time are not commonly studied, yet they are tightly coupled to landscape properties and add relevant information on foraging behavior. By exploring simple foraging models in unpredictable environments we show that the distribution of intervals between detected prey (detection statistics) is mostly determined by the spatial structure of the prey field and essentially distinct from predator displacement statistics. Detections are expected to be Poissonian in uniform random environments for markedly different foraging movements (e.g. Lévy and ballistic). This prediction is supported by data on the time intervals between diving events on short-range foraging seabirds such as the thick-billed murre (Uria lomvia). However, Poissonian detection statistics is not observed in long-range seabirds such as the wandering albatross (Diomedea exulans) due to the fractal nature of the prey field, covering a wide range of spatial scales. For this scenario, models of fractal prey fields induce non-Poissonian patterns of detection in good agreement with two albatross data sets. We find that the specific shape of the distribution of time intervals between prey detection is mainly driven by meso and submeso-scale landscape structures and depends little on the forager strategy or behavioral responses.

Long-distance dispersal (LDD) events, although rare for most plant species, can strongly influence population and community dynamics. Animals function as a key biotic vector of seeds and thus, a mechanistic and quantitative understanding of how individual animal behaviors scale to dispersal patterns at different spatial scales is a question of critical importance from both basic and applied perspectives. Using a diffusion-theory based analytical approach for a wide range of animal movement and seed transportation patterns, we show that the scale (a measure of local dispersal) of the seed dispersal kernel increases with the organisms' rate of movement and mean seed retention time. We reveal that variations in seed retention time is a key determinant of various measures of LDD such as kurtosis (or shape) of the kernel, thinkness of tails and the absolute number of seeds falling beyond a threshold distance. Using empirical data sets of frugivores, we illustrate the importance of variability in retention times for predicting the key disperser species that influence LDD. Our study makes testable predictions linking animal movement behaviors and gut retention times to dispersal patterns and, more generally, highlights the potential importance of animal behavioral variability for the LDD of seeds.