The long-distance flight behavior of Drosophila supports an agent-based model for wind-assisted dispersal in insects

Despite the ecological importance of long-distance dispersal in insects, its mechanistic basis is poorly understood in genetic model species, in which advanced molecular tools are readily available. One critical question is how insects interact with the wind to detect attractive odor plumes and increase their travel distance as they disperse. To gain insight into dispersal, we conducted release-and-recapture experiments in the Mojave Desert using the fruit fly, Drosophila melanogaster. We deployed chemically baited traps in a 1 km radius ring around the release site, equipped with cameras that captured the arrival times of flies as they landed. In each experiment, we released between 30,000 and 200,000 flies. By repeating the experiments under a variety of conditions, we were able to quantify the influence of wind on flies’ dispersal behavior. Our results confirm that even tiny fruit flies could disperse ∼12 km in a single flight in still air and might travel many times that distance in a moderate wind. The dispersal behavior of the flies is well explained by an agent-based model in which animals maintain a fixed body orientation relative to celestial cues, actively regulate groundspeed along their body axis, and allow the wind to advect them sideways. The model accounts for the observation that flies actively fan out in all directions in still air but are increasingly advected downwind as winds intensify. Our results suggest that dispersing insects may strike a balance between the need to cover large distances while still maintaining the chance of intercepting odor plumes from upwind sources.

If asked to picture a migrating insect, the first image that comes to mind might be a large charismatic species such as the monarch butterfly, whose seasonal movements across North America have inspired naturalists for centuries. However, as pointed out by David and Elizabeth Lack (1), our impression of insect migration is strongly biased toward large animals; many species are so small that their geographic relocations escape our attention, especially if their population densities are not strongly concentrated by geological features such as narrow mountain passes. As research using high-altitude traps (2) and upward-looking radar (3, 4) indicates, long-distance migration may be more ubiquitous and ecologically important among both large and small insects than previously appreciated (5, 6). Long-distance dispersal (i.e., the noncyclic movement from one area to another) is even harder to observe and study in small insects, because the events are not generally predictable, and the animals are far too small to be captured on radar or outfitted with tracking devices. The dispersal of small insects across a landscape has often been modeled as stochastic processes governed by diffusion and advection (7), processes that may underestimate the ability of the animals to actively maintain constant trajectories over large spatial scales. Understanding long-distance migration and dispersal is quite important, because these phenomena are responsible for biomass relocation on both local and global scales (8, 9). Furthermore, as insect population densities decline due to environmental degradation and climate change (10–12), understanding the dispersal capacity of insects and the behavioral algorithms that underlie them will be crucial in predicting the ecological impact of population decline.Although not generally renowned for its capability to disperse over long distances, a series of release-and-recapture experiments over 40 y ago suggest that the fruit fly, Drosophila melanogaster, may be capable of movements on the order of 15 km in a single night, a distance equivalent to 6 million body lengths (13, 14). These experiments were conducted by releasing tens of thousands of fluorescently labeled flies in the evening and then censusing the contents of traps baited with yeast and banana placed at distant oases the next morning. Although these pioneering studies suggested that the dispersal capacity of Drosophila was much greater than previously estimated, they left open several critical questions. First, it was not clear whether individual flies dispersed in random directions or whether the population movement was biased by external conditions, such as the wind, geographical features, or celestial cues. Second, because the precise transit times of the flies were not known, it was impossible to estimate the actual groundspeeds used by the animals as they dispersed. To provide more clarity to these and other questions related to long-distance dispersal, we conducted a series of release-and-recapture experiments in the Mojave Desert. We equipped circular arrays of chemically baited traps with simple machine vision systems that captured the arrival times of flies as they landed and repeated the experiments under a variety of ambient wind conditions. The results provide key insight into the behavioral algorithms used by Drosophila while dispersing in the wild and serve as the basis for a general agent-based model of wind-assisted dispersal in insects.     

Effect of habitat fragmentation on the schistosome-transmitting snail Oncomelania hupensis in a mountainous area of China

The effect of habitat fragmentation on schistosome-transmitting snails was assessed in an intervention village and a control village in Sichuan Province, China. Snail habitats were fragmented by environmental management. After 2 years, the proportions of quadrats with snails in the fragmented habitats decreased from 9.35% to 2.41% in one patch (c3) and from 12.20% to 6.57% in another patch (c12), whilst the proportions in habitats without fragmentation did not alter significantly. Mean snail density decreased from 0.246 to 0.063 snails/0.11 m² in patch c3 and from 0.356 to 0.177 snails/0.11 m² in patch c12, whilst the mean snail density of other patches did not alter significantly. Most snails from the same patch and/or its remaining patches after fragmentation clustered together in the phylogenetic tree, except for c1, c3 and its remaining patches (c5, c6 and c11). Snail habitats in the study zone exhibited visible fragmentation. Habitat fragmentation could decrease the snail population size and limit migration and dispersal of snails between patches.     

The value of spatial information in MPA network design

The science of spatial fisheries management, which combines ecology, oceanography, and economics, has matured significantly. As a result, there have been recent advances in exploiting spatially explicit data to develop spatially explicit management policies, such as networks of marine protected areas (MPAs). However, when data are sparse, spatially explicit policies become less viable, and we must instead rely on blunt policies such as total allowable catches or imprecisely configured networks of MPAs. Therefore, spatial information has the potential to change management approaches and thus has value. We develop a general framework within which to analyze the value of information for spatial fisheries management and apply that framework to several US Pacific coast fisheries. We find that improved spatial information can increase fishery value significantly (>10% in our simulations), and that it changes dramatically the efficient management approach—switching from diffuse effort everywhere to a strategy where fishing is spatially targeted, with some areas under intensive harvest and others closed to fishing. Using all available information, even when incomplete, is essential to management success and may as much as double fishery value relative to using (admittedly incorrect) assumptions commonly invoked.     

Molecular epidemiology of Oropouche virus, Brazil

Oropouche virus (OROV) is the causative agent of Oropouche fever, an urban febrile arboviral disease widespread in South America, with >30 epidemics reported in Brazil and other Latin American countries during 1960-2009. To describe the molecular epidemiology of OROV, we analyzed the entire N gene sequences (small RNA) of 66 strains and 35 partial Gn (medium RNA) and large RNA gene sequences. Distinct patterns of OROV strain clustered according to N, Gn, and large gene sequences, which suggests that each RNA segment had a different evolutionary history and that the classification in genotypes must consider the genetic information for all genetic segments. Finally, time-scale analysis based on the N gene showed that OROV emerged in Brazil ≈223 years ago and that genotype I (based on N gene data) was responsible for the emergence of all other genotypes and for virus dispersal.     

The biocultural origins and dispersal of domestic chickens

Though chickens are the most numerous and ubiquitous domestic bird, their origins, the circumstances of their initial association with people, and the routes along which they dispersed across the world remain controversial. In order to establish a robust spatial and temporal framework for their origins and dispersal, we assessed archaeological occurrences and the domestic status of chickens from ∼600 sites in 89 countries by combining zoogeographic, morphological, osteometric, stratigraphic, contextual, iconographic, and textual data. Our results suggest that the first unambiguous domestic chicken bones are found at Neolithic Ban Non Wat in central Thailand dated to ∼1650 to 1250 BCE, and that chickens were not domesticated in the Indian Subcontinent. Chickens did not arrive in Central China, South Asia, or Mesopotamia until the late second millennium BCE, and in Ethiopia and Mediterranean Europe by ∼800 BCE. To investigate the circumstances of their initial domestication, we correlated the temporal spread of rice and millet cultivation with the first appearance of chickens within the range of red junglefowl species. Our results suggest that agricultural practices focused on the production and storage of cereal staples served to draw arboreal red junglefowl into the human niche. Thus, the arrival of rice agriculture may have first facilitated the initiation of the chicken domestication process, and then, following their integration within human communities, allowed for their dispersal across the globe.

Despite the global ubiquity and cultural importance of chickens (Gallus gallus domesticus L., 1758), the timing and circumstances of their domestication and subsequent dispersal remain both obscure and controversial (1). Although the spatiotemporal patterns of chicken dispersal following their domestication have been addressed by several studies (2–4), two key publications (5, 6) pertaining to the early history of chicken domestication are almost always cited but rarely challenged (SI Appendix, Table S1). In brief, the first argues for a Southeast Asian and possible South Indian origin for chickens (5), and the second claims that domestic chickens first appeared in northern China before following a northern trajectory toward Europe (6). Both of these oft-cited syntheses summarized, but did not critically assess either the original osteological and stratigraphic data or the cultural implications for the presence of chickens across the Old World.Inferring chicken origins and dispersal have primarily been hampered by a paucity of archaeological remains, and more specifically, issues related to excavation and recovery biases, faunal identification, and dating (7). Excavations that do not consistently employ fine sieving, for example, are unlikely to systematically retrieve chicken bones. When bird remains are recovered, confident identification can be problematic in the absence of reference collections, since chicken bones are difficult to distinguish from other related galliform species. Although early Holocene bird remains from northern China were initially claimed to be chickens (8), a reanalysis of those bones based upon discrete osteomorphological criteria demonstrated that the specimens were derived from pheasants (1, 9). More generally, ongoing hybridization between wild red junglefowl (G. gallus) populations and those birds living in human settlements (10) complicates the task of identifying early poultry husbandry in the archaeological record.The low density of excavated archaeological sites, specifically within the distribution of red junglefowl, means that the earliest shifts in the relationship between people and these birds remain opaque. Additionally, chicken bones are prone to taphonomic loss through scavenger activity (11) and stratigraphic displacement (12). The latter can lead to invalid claims regarding their dating and cultural context, and a recent program of radiocarbon dating demonstrated that numerous early claims for the first appearance of chickens in Europe were spurious (13).Regarding their geographic origin, genetic studies have demonstrated that of the four extant junglefowl species, chickens were primarily derived from the red junglefowl (14, 15). A more recent study analyzed 863 genomes from modern Gallus specimens, including all five subspecies of red junglefowl, and identified the subspecies Gallus gallus spadiceus as the most likely progenitor of domestic chickens (16). This result suggests that the chicken domestication process began within the distribution of this subspecies in Southeast Asia (Fig. 1 and SI Appendix, Fig S1). Genomic analyses further suggested that the divergence between the ancestral population of modern domestic chickens and G. gallus spadiceus occurred between 12,800 and 6,200 y ago. Importantly, this range cannot be equated with the initiation of a domestication process. Instead, this timeframe represents the divergence between G. gallus spadiceus and the lineage from which domestic chickens were derived (17), and thus represents an upper bound on the chicken domestication timeframe.Open in a separate windowFig. 1.A map depicting the distribution of both the gray and Ceylon junglefowl species and three subspecies of red junglefowl: G. gallus murghi, G. gallus spadiceus, and G. gallus jabouillei. The distribution of G. gallus gallus is depicted as the remainder of mainland southeast Asia and Sumatra following the general distribution in ref. 16. The G. gallus murghi distribution follows that of SI Appendix, Fig. S1, which draws on published maps in ornithological sources and the Global Biodiversity Information Facility (GBIF) records (119–121). For G. gallus spadiceus and G. gallus jabouillei, the GBIF records were augmented by specimens with genetic data reported by refs. 16 and 122.Here, in order to establish a robust spatial and temporal framework for the early occurrence of chickens both within and beyond the range of red junglefowl, including Africa and Oceania, we reevaluated reports of chicken remains from >600 archaeological sites in 89 countries. We did so by assessing the claims for chickens in their chrono-cultural and geographic contexts, and wherever possible, by reassessing the taxonomic determination of existing specimens by measuring either published photographs or the actual bones. We then combined zoogeographic, contextual, and osteometric data to confirm or question the domestic status of the birds. We also critically reviewed the stratigraphic position of each of the remains and assessed their intrusive potential. We complemented these efforts by investigating iconographic, written, and linguistic records pertaining to chickens. In addition, we interpreted these records within the context of the ecological characteristics and distributions of all the jungle fowl subspecies.These analyses allowed us to generate two datasets: a comprehensive table of archaeological remains consisting of chickens that were confidently assigned as domestic using conservative measures (SI Appendix, Table S2), and a list of remains whose identification or stratigraphic position was ambiguous (SI Appendix, Table S3). We then correlated the resulting spatiotemporal pattern of archaeological chickens with human societies and their subsistence strategies. This correlation allowed us to address the process, circumstances, and cultural context in which the initial shift in the human–chicken relationship that led to domestication took place, and the contexts of their subsequent translocations.     

Dendritic connectivity controls biodiversity patterns in experimental metacommunities

Biological communities often occur in spatially structured habitats where connectivity directly affects dispersal and metacommunity processes. Recent theoretical work suggests that dispersal constrained by the connectivity of specific habitat structures, such as dendrites like river networks, can explain observed features of biodiversity, but direct evidence is still lacking. We experimentally show that connectivity per se shapes diversity patterns in microcosm metacommunities at different levels. Local dispersal in isotropic lattice landscapes homogenizes local species richness and leads to pronounced spatial persistence. On the contrary, dispersal along dendritic landscapes leads to higher variability in local diversity and among-community composition. Although headwaters exhibit relatively lower species richness, they are crucial for the maintenance of regional biodiversity. Our results establish that spatially constrained dendritic connectivity is a key factor for community composition and population persistence.     

Demolishing the great wall of biofilms in Gram-negative bacteria: To disrupt or disperse?

Bacterial infections lead to high morbidity and mortality globally. While current therapies against bacteria often employ antibiotics, most bacterial pathogens can form biofilms and prevent effective treatment of infections. Biofilm cells can aggregate and encased themselves in a self-secreted protective exopolymeric matrix, to reduce the penetration by antibiotics. Biofilm formation is mediated by c-di-GMP signaling, the ubiquitous secondary messenger in bacteria. Synthesis of c-di-GMP by diguanylate cyclases leads to biofilm formation via the loss of motility, increased surface attachment, and production of biofilm matrix, whereas c-di-GMP degradation by phosphodiesterases causes biofilm dispersal to new sites via increased bacterial motility and matrix breakdown. The highly variable nature of biofilm development and antimicrobial tolerance imposes tremendous challenges in conventional antimicrobial therapies, indicating an imperative need to develop anti-biofilm drugs against biofilm infections. In this review, we focus on two main emergent approaches—active dispersal and disruption. While both approaches aim to demolish biofilms, we will discuss their fundamental differences and associated methods. Active dispersal of biofilms involves signaling the bacterial cells to leave the biofilm, where resident cells ditch their sessile lifestyle, gain motility and self-degrade their matrix. Biofilm disruption leads to direct matrix degradation that forcibly releases embedded biofilm cells. Without the protection of biofilm matrix, released bacterial cells are highly exposed to antimicrobials, leading to their eradication in biofilm infections. Understanding the advantages and disadvantages of both approaches will allow optimized utility with antimicrobials in clinical settings.     

Molecular epidemiology of circulating highly pathogenic avian influenza (H5N1) virus in chickens,in Bangladesh, 2007–2010

Bangladesh has been severely hit by highly pathogenic avian influenza H5N1 (HPAI-H5N1). However, little is known about the genetic diversity and the evolution of the circulating viruses in Bangladesh. In the present study, we analyzed the hemagglutinin gene of 30 Bangladeshi chicken isolates from 2007 through 2010. We analyzed the polybasic amino acid sequence motif of the cleavage site and amino acid substitution pattern. Phylogenetic history was reconstructed using neighbor-joining and Bayesian time-scaled methods. In addition, we used Mantel correlation tests to analyze the relation between genetic relatedness and spatial and temporal distances. Neighbor-joining phylogeography revealed that virus circulating in Bangladesh from 2007 through 2010 belonged to clade 2.2. The results suggest that clade 2.2 viruses are firmly entrenched and have probably become endemic in Bangladesh. We detected several amino acid substitutions, but they are not indicative of adaptation toward human infection. The Mantel correlation test confirmed significant correlation between genetic distances and temporal distances between the viruses. The Bayesian tree shows that isolates from waves 3 and 4 derived from a subgroup of isolates from the previous waves grouping with a high posterior probability (pp = 1.0). This indicates the possibility of formation of local subclades. One surprising finding of spatio-temporal analysis was that genetically identical virus caused independent outbreaks over a distance of more than 200 km and within 14 days of each other. This might indicate long distance dispersal through vectors such as migratory birds and vehicles, and challenges the effectiveness of movement restriction around 10 km radius of an outbreak. The study indicates possible endemicity of the clade 2.2 HPAI-H5N1 virus in Bangladesh. Furthermore, the formation of a subclade capable of transmission to humans cannot be ruled out. The findings of this study might provide valuable information for future surveillance, prevention and control programme.