The Role of Human Transportation Networks in Mediating the Genetic Structure of Seasonal Influenza in the United States

Recent studies have demonstrated the importance of accounting for human mobility networks when modeling epidemics in order to accurately predict spatial dynamics. However, little is known about the impact these movement networks have on the genetic structure of pathogen populations and whether these effects are scale-dependent. We investigated how human movement along the aviation and commuter networks contributed to intra-seasonal genetic structure of influenza A epidemics in the continental United States using spatially-referenced hemagglutinin nucleotide sequences collected from 2003–2013 for both the H3N2 and H1N1 subtypes. Comparative analysis of these transportation networks revealed that the commuter network is highly spatially-organized and more heavily traveled than the aviation network, which instead is characterized by high connectivity between all state pairs. We found that genetic distance between sequences often correlated with distance based on interstate commuter network connectivity for the H1N1 subtype, and that this correlation was not as prevalent when geographic distance or aviation network connectivity distance was assessed against genetic distance. However, these patterns were not as apparent for the H3N2 subtype at the scale of the continental United States. Finally, although sequences were spatially referenced at the level of the US state of collection, a community analysis based on county to county commuter connections revealed that commuting communities did not consistently align with state geographic boundaries, emphasizing the need for the greater availability of more specific sequence location data. Our results highlight the importance of utilizing host movement data in characterizing the underlying genetic structure of pathogen populations and demonstrate a need for a greater understanding of the differential effects of host movement networks on pathogen transmission at various spatial scales.     

The Effect of Geographical Proximity on Scientific Cooperation among Chinese Cities from 1990 to 2010

Background

The relations between geographical proximity and spatial distance constitute a popular topic of concern. Thus, how geographical proximity affects scientific cooperation, and whether geographically proximate scientific cooperation activities in fact exhibit geographic scale features should be investigated.

Methodology

Selected statistics from the ISI database on cooperatively authored papers, the authors of which resided in 60 typical cites in China, and which were published in the years 1990, 1995, 2000, 2005, and 2010, were used to establish matrices of geographic distance and cooperation levels between cities. By constructing a distance-cooperation model, the degree of scientific cooperation based on spatial distance was calculated. The relationship between geographical proximity and scientific cooperation, as well as changes in that relationship, was explored using the fitting function.

Result

(1) Instead of declining, the role of geographical proximity in inter-city scientific cooperation has increased gradually but significantly with the popularization of telecommunication technologies; (2) the relationship between geographical proximity and scientific cooperation has not followed a perfect declining curve, and at certain spatial scales, the distance-decay regularity does not work; (3) the Chinese scientific cooperation network gathers around different regional center cities, showing a trend towards a regional network; within this cooperation network the amount of inter-city cooperation occurring at close range increased greatly.

Conclusion

The relationship between inter-city geographical distance and scientific cooperation has been enhanced and strengthened over time.     

Population structure and landscape genetics in the endangered subterranean rodent Ctenomys porteousi

In order to devise adequate conservation and management strategies for endangered species, it is important to incorporate a reliable understanding of its spatial population structure, detecting the existence of demographic partitions throughout its geographical range and characterizing the distribution of its genetic diversity. Moreover, in species that occupy fragmented habitats it is essential to know how landscape characteristics may affect the genetic connectivity among populations. In this study we use eight microsatellite markers to analyze population structure and gene flow patterns in the complete geographic range of the endangered rodent Ctenomys porteousi. Also, we use landscape genetics approaches to evaluate the effects of landscape configuration on the genetic connectivity among populations. In spite of geographical proximity of the sampling sites (8–27 km between the nearest sites) and the absence of marked barriers to individual movement, strong population structure and low values of gene flow were observed. Genetic differentiation among sampling sites was consistent with a simple model of isolation by distance, where peripheral areas showed higher population differentiation than those sites located in the central area of the species’ distribution. Landscape genetics analysis suggested that habitat fragmentation at regional level has affected the distribution of genetic variation among populations. The distance of sampling sites to areas of the landscape having higher habitat connectivity was the environmental factor most strongly related to population genetic structure. In general, our results indicate strong genetic structure in C. porteousi, even at a small spatial scale, and suggest that habitat fragmentation could increase the population differentiation.     

Spatial Graphs: Principles and Applications for Habitat Connectivity

ABSTRACT Well-founded methods to assess habitat connectivity are essential to inform land management decisions that include conservation and restoration goals. Indeed, to be able to develop a conservation plan that maintains animal movement through a fragmented landscape, spatial locations of habitat and paths among them need to be represented. Graph-based approaches have been proposed to determine paths among habitats at various scales and dispersal movement distances, and balance data requirements with information content. Conventional graphs, however, do not explicitly maintain geographic reference, reducing communication capacity and utility of other geo-spatial information. We present spatial graphs as a unifying theory for applying graph-based methods in a geographic context. Spatial graphs integrate a geometric reference system that ties patches and paths to specific spatial locations and spatial dimensions. Arguably, the complete graph, with paths between every pair of patches, may be one of the most relevant graphs from an ecosystem perspective, but it poses challenges to compute, process and visualize. We developed Minimum Planar Graphs as a spatial generalization of Delaunay triangulations to provide a reasonable approximation of complete graphs that facilitates visualization and comprehension of the network of connections across landscapes. If, as some authors have suggested, the minimum spanning tree identifies the connectivity “backbone” of a landscape, then the Minimum Planar Graph identifies the connectivity “network”. We applied spatial graphs, and in particular the Minimum Planar Graph, to analyze woodland caribou habitat in Manitoba, Canada to support the establishment of a national park.     

Uncovering Patterns of Inter-Urban Trip and Spatial Interaction from Social Media Check-In Data

The article revisits spatial interaction and distance decay from the perspective of human mobility patterns and spatially-embedded networks based on an empirical data set. We extract nationwide inter-urban movements in China from a check-in data set that covers half a million individuals within 370 cities to analyze the underlying patterns of trips and spatial interactions. By fitting the gravity model, we find that the observed spatial interactions are governed by a power law distance decay effect. The obtained gravity model also closely reproduces the exponential trip displacement distribution. The movement of an individual, however, may not obey the same distance decay effect, leading to an ecological fallacy. We also construct a spatial network where the edge weights denote the interaction strengths. The communities detected from the network are spatially cohesive and roughly consistent with province boundaries. We attribute this pattern to different distance decay parameters between intra-province and inter-province trips.     

Disentangling the role of connectivity,environmental filtering,and spatial structure on metacommunity dynamics

Dispersal is a key process in metacommunity dynamics, allowing the maintenance of diversity in complex community networks. Geographic distance is usually used as a surrogate for connectivity implying that communities that are closely located are considered more prone to exchange individuals than distant communities. However, in some natural systems, organisms may be subjected to directional dispersal (air or water flows, particular landscape configuration), possibly leading close communities to be isolated from each other and distant communities to be connected. Using geographic distance as a proxy for realised connectivity may then yield misleading results regarding the role of dispersal in structuring communities in such systems. Here, we quantified the relative importance of flow connectivity, geographic distance, and environmental gradients to explain polychaete metacommunity structure along the coasts of the Gulf of Lions (northwest Mediterranean Sea). Flow connectivity was estimated by Lagrangian particle dispersal simulations. Our results revealed that this metacommunity is strongly structured by the environment at large spatial scales, and that both flow connectivity and geographic distance play an important role within homogeneous environments at smaller spatial scales. We thus strongly advocate for a wider use of connectivity measures, in addition to geographic distance, to study spatial patterns of biological diversity (e.g. distance decay) and to infer the processes behind these patterns at different spatial scales. Synthesis Everything is connected, but connections are seldom accurately quantified. Biological communities are often studied separately, using observations, experiments and models to unravel local dynamics of organisms interacting with each other. However, regional processes such as dispersal through ocean and air circulation, likely to connect distant communities and influence their local dynamics, are not always accounted for, or, at best, used as an homogeneous and distance‐related factor. Ocean models have being extensively developed and validated during the past decades with the increasing availability of accurate meteorological data. Using such model outputs, precise quantifi cation of exchange rates of organisms between communities was performed in a marine Mediterranean coastal area. Jointly with local environmental and biological data, these results were used to quantify the effects of realistic connectivity on local and regional polychaete community structure, and revealed that the environmental gradient, geographic distance, and connectivity were responsible for community structure at different spatial scales.     

The structural and functional connectivity of the grassland plant Lychnis flos-cuculi

Understanding the relationship between structural and functional connectivity is essential for successful restoration and conservation management, particularly in intensely managed agricultural landscapes. We evaluated the relationship between structural and functional connectivity of the wetland plant Lychnis flos-cuculi in a fragmented agricultural landscape using landscape genetic and network approaches. First, we studied the effect of structural connectivity, such as geographic distance and various landscape elements (forest, agricultural land, settlements and ditch verges), on gene flow among populations as a measurement of functional connectivity. Second, we examined the effect of structural graph-theoretic connectivity measures on gene flow among populations and on genetic diversity within populations of L. flos-cuculi. Among landscape elements, forests hindered gene flow in L. flos-cuculi, whereas gene flow was independent of geographic distance. Among the structural graph-theoretic connectivity variables, only intrapopulation connectivity, which was based on population size, had a significant positive effect on gene flow, that is, more gene flow took place among larger populations. Unexpectedly, interpopulation connectivity of populations, which takes into account the spatial location and distance among populations, did not influence gene flow in L. flos-cuculi. However, higher observed heterozygosity and lower inbreeding was observed in populations characterised by higher structural interpopulation connectivity. This finding shows that a spatially coherent network of populations is significant for maintaining the genetic diversity of populations. Nevertheless, lack of significant relationships between gene flow and most of the structural connectivity measures suggests that structural connectivity does not necessarily correspond to functional connectivity.     

A Bayesian Approach for Modeling Cattle Movements in the United States: Scaling up a Partially Observed Network

Networks are rarely completely observed and prediction of unobserved edges is an important problem, especially in disease spread modeling where networks are used to represent the pattern of contacts. We focus on a partially observed cattle movement network in the U.S. and present a method for scaling up to a full network based on Bayesian inference, with the aim of informing epidemic disease spread models in the United States. The observed network is a 10% state stratified sample of Interstate Certificates of Veterinary Inspection that are required for interstate movement; describing approximately 20,000 movements from 47 of the contiguous states, with origins and destinations aggregated at the county level. We address how to scale up the 10% sample and predict unobserved intrastate movements based on observed movement distances. Edge prediction based on a distance kernel is not straightforward because the probability of movement does not always decline monotonically with distance due to underlying industry infrastructure. Hence, we propose a spatially explicit model where the probability of movement depends on distance, number of premises per county and historical imports of animals. Our model performs well in recapturing overall metrics of the observed network at the node level (U.S. counties), including degree centrality and betweenness; and performs better compared to randomized networks. Kernel generated movement networks also recapture observed global network metrics, including network size, transitivity, reciprocity, and assortativity better than randomized networks. In addition, predicted movements are similar to observed when aggregated at the state level (a broader geographic level relevant for policy) and are concentrated around states where key infrastructures, such as feedlots, are common. We conclude that the method generally performs well in predicting both coarse geographical patterns and network structure and is a promising method to generate full networks that incorporate the uncertainty of sampled and unobserved contacts.     

Home range, activity and movements of a wolf pack in central Italy

Home range, habitat use, activity and movement patterns were studied in a pack of wolves in a mountainous region of Abruzzo, central Italy from June 1986 to March 1987. The home range, estimated by the minimum convex polygon from 421 radio locations, measured 197 km² and comprised several infrastructures and areas of human presence, including four garbage dumps and two offal sites. Core areas, calculated by the harmonic mean method, were located toward the centre of the home range where human disturbance and road density were lowest but forest cover was highest. During the time-span of the study, home-range use and movement patterns suggested a marked centrality in spatial behaviour and traditionality in retreat areas year-round, both during pup-rearing season and the following months. In addition, by being essentially nocturnal, resident wolves appeared to adopt tactics of temporal segregation from people to exploit food resources safely in the proximity of human settlements. Overall activity correlated with distance travelled (r = 0.90, P << 0.001), and corresponded to cyclic nocturnal movements from retreat to feeding areas. Wolf movement rate between 20:00 and 04:00 h averaged 2.5 km/h but varied up to about 8 km/h, and daily distance travelled (= 27 km/night; range 17–38 km/night) mostly depended on the location of traditional feeding sites. Home-range configuration, habitat use, activity and movements all appeared highly integrated so as to represent the most functional compromise between avoidance of human inteference and exploitation of the available food resources.     

Riverscape genetic structure of a threatened and dispersal limited freshwater species,the Rocky Mountain Sculpin (<Emphasis Type="Italic">Cottus</Emphasis> sp.)

Understanding the movement ability and the spatial scale(s) of population genetic structure of species can together better ‘tune’ management objectives to prevent potential range contraction and population declines. We studied the Rocky Mountain Sculpin (Cottus sp.), a threatened species in Canada, to demonstrate the utility of using two complementary approaches to assess connectivity of a species. To do so, we used Passive Integrated Transponder (PIT) tags with a stationary tracking array (n?=?223) to track movement and genetic data (n?=?1,015) from nine microsatellite loci to assess genetic population structure. The PIT tag results indicated that Rocky Mountain Sculpin are sedentary; approximately 50% of individuals only moved a maximum distance of 10 meters (upstream or downstream) over a 5-month period. Genetic analyses indicated that at the spatial scale of our study area (5500 km²), watershed structure (river basins) is the main geographic feature influencing population genetic structure. We used the Bayesian clustering tool STRUCTURE, which suggested four distinct sub-populations of Rocky Mountain Sculpin in Canada. Genetic structure at finer spatial scales (within basins and sub-basins) appears to be influenced by fluvial distance (i.e., geographic distance along a river) and elevation change between sample locations (i.e., isolation-by-distance and isolation-by-environment). Combining movement and genetic analyses provides complimentary evidence of limited dispersal in Rocky Mountain Sculpin and highlights that both approaches together can provide broader insight into connectivity between populations that may ultimately help to aid future management decisions.     

Connectivity,biodiversity conservation and the design of marine reserve networks for coral reefs

Networks of no-take reserves are important for protecting coral reef biodiversity from climate change and other human impacts. Ensuring that reserve populations are connected to each other and non-reserve populations by larval dispersal allows for recovery from disturbance and is a key aspect of resilience. In general, connectivity between reserves should increase as the distance between them decreases. However, enhancing connectivity may often tradeoff against a network’s ability to representatively sample the system’s natural variability. This “representation” objective is typically measured in terms of species richness or diversity of habitats, but has other important elements (e.g., minimizing the risk that multiple reserves will be impacted by catastrophic events). Such representation objectives tend to be better achieved as reserves become more widely spaced. Thus, optimizing the location, size and spacing of reserves requires both an understanding of larval dispersal and explicit consideration of how well the network represents the broader system; indeed the lack of an integrated theory for optimizing tradeoffs between connectivity and representation objectives has inhibited the incorporation of connectivity into reserve selection algorithms. This article addresses these issues by (1) updating general recommendations for the location, size and spacing of reserves based on emerging data on larval dispersal in corals and reef fishes, and on considerations for maintaining genetic diversity; (2) using a spatial analysis of the Great Barrier Reef Marine Park to examine potential tradeoffs between connectivity and representation of biodiversity and (3) describing a framework for incorporating environmental fluctuations into the conceptualization of the tradeoff between connectivity and representation, and that expresses both in a common, demographically meaningful currency, thus making optimization possible.     

Interactions of Cultures and Top People of Wikipedia from Ranking of 24 Language Editions

Wikipedia is a huge global repository of human knowledge that can be leveraged to investigate interwinements between cultures. With this aim, we apply methods of Markov chains and Google matrix for the analysis of the hyperlink networks of 24 Wikipedia language editions, and rank all their articles by PageRank, 2DRank and CheiRank algorithms. Using automatic extraction of people names, we obtain the top 100 historical figures, for each edition and for each algorithm. We investigate their spatial, temporal, and gender distributions in dependence of their cultural origins. Our study demonstrates not only the existence of skewness with local figures, mainly recognized only in their own cultures, but also the existence of global historical figures appearing in a large number of editions. By determining the birth time and place of these persons, we perform an analysis of the evolution of such figures through 35 centuries of human history for each language, thus recovering interactions and entanglement of cultures over time. We also obtain the distributions of historical figures over world countries, highlighting geographical aspects of cross-cultural links. Considering historical figures who appear in multiple editions as interactions between cultures, we construct a network of cultures and identify the most influential cultures according to this network.     

Contrasting demographic and genetic estimates of dispersal in the endangered Coahuilan box turtle: a contemporary approach to conservation

The evolutionary viability of an endangered species depends upon gene flow among subpopulations and the degree of habitat patch connectivity. Contrasting population connectivity over ecological and evolutionary timescales may provide novel insight into what maintains genetic diversity within threatened species. We employed this integrative approach to evaluating dispersal in the critically endangered Coahuilan box turtle (Terrapene coahuila) that inhabits isolated wetlands in the desert‐spring ecosystem of Cuatro Ciénegas, Mexico. Recent wetland habitat loss has altered the spatial distribution and connectivity of habitat patches; and we therefore predicted that T. coahuila would exhibit limited movement relative to estimates of historic gene flow. To evaluate contemporary dispersal patterns, we employed mark–recapture techniques at both local (wetland complex) and regional (intercomplex) spatial scales. Gene flow estimates were obtained by surveying genetic variation at nine microsatellite loci in seven subpopulations located across the species’ geographical range. The mark–recapture results at the local spatial scale reveal frequent movement among wetlands that was unaffected by interwetland distance. At the regional spatial scale, dispersal events were relatively less frequent between wetland complexes. The complementary analysis of population genetic substructure indicates strong historic gene flow (global F_ST = 0.01). However, a relationship of genetic isolation by distance across the geographical range suggests that dispersal limitation exists at the regional scale. Our approach of contrasting direct and indirect estimates of dispersal at multiple spatial scales in T. coahuila conveys a sustainable evolutionary trajectory of the species pending preservation of threatened wetland habitats and a range‐wide network of corridors.     

Arctic fox Vulpes lagopus population structure: circumpolar patterns and processes

Movement is a prominent process shaping genetic population structure. In many northern mammal species, population structure is formed by geographic distance, geographical barriers and various ecological factors that influence movement over the landscape. The Arctic fox Vulpes lagopus is a highly mobile, opportunistic carnivore of the Arctic that occurs in two main ecotypes with different ecological adaptations. We assembled microsatellite data in 7 loci for 1834 Arctic foxes sampled across their entire distribution to describe the circumpolar population structure and test the impact of (1) geographic distance, (2) geographical barriers and (3) ecotype designation on the population structure. Both Structure and Geneland demonstrated distinctiveness of Iceland and Scandinavia whereas low differentiation was observed between North America–northern Greenland, Svalbard and Siberia. Genetic differentiation was significantly correlated to presence of sea ice on a global scale, but not to geographical distance or ecotype designation. However, among areas connected by sea ice, we recorded a pattern of isolation by distance. The maximum likelihood approach in Migrate suggested that connectivity across North America–northern Greenland and Svalbard was particularly high. Our results demonstrate the importance of sea ice for maintaining connectivity between Arctic fox populations and we therefore predict that climate change will increase genetic divergence among populations in the future.     

Patterns and drivers of aquatic invertebrate diversity across an arid biome

Managing and restoring faunal diversity across large areas requires an understanding of the roles of connectivity and dispersal in driving community patterns. We sought to determine the influence of connectivity, water regime, water source, geographical location, and dispersal traits on patterns of aquatic invertebrate diversity across a continent‐wide arid biome. We compiled data on freshwater invertebrate assemblages from sites spanning the breadth of arid Australia. Univariate analyses (analysis of variance and rarefaction) revealed that alpha and gamma diversity across sites decreased as latitude increased. Multivariate analyses (ordination and analysis of similarity) revealed that community composition had considerable fidelity to geographic regions. Hydrological connectivity was strongly associated with riverine community composition although water rarely flowed (often less than annually). Hydrologically isolated sites (springs and rockholes) supported communities that were markedly dissimilar to hydrologically connected sites, and to each other. We investigated the influence of dispersal on diversity patterns by examining distance decay relationships for each of four dispersal trait groups (obligate aquatic and passive, weak, and strong aerial dispersers) on the basis of geodesic (shortest path) distances between pairs of sites and Mantel tests. We did not detect clear differences between dispersal traits and distance decay relationships at the continental scale, even for the two groups with the lowest dispersal ability (obligate aquatics and passive dispersers). Our results suggest that the loss of hydrological connectivity from water developments in arid lands (for example, the impoundment of intermittent rivers) is likely to affect macroinvertebrates. However, the exact flow mechanisms underlying such changes remain to be determined.     

Independently Outgrowing Neurons and Geometry-Based Synapse Formation Produce Networks with Realistic Synaptic Connectivity

Neuronal signal integration and information processing in cortical networks critically depend on the organization of synaptic connectivity. During development, neurons can form synaptic connections when their axonal and dendritic arborizations come within close proximity of each other. Although many signaling cues are thought to be involved in guiding neuronal extensions, the extent to which accidental appositions between axons and dendrites can already account for synaptic connectivity remains unclear. To investigate this, we generated a local network of cortical L2/3 neurons that grew out independently of each other and that were not guided by any extracellular cues. Synapses were formed when axonal and dendritic branches came by chance within a threshold distance of each other. Despite the absence of guidance cues, we found that the emerging synaptic connectivity showed a good agreement with available experimental data on spatial locations of synapses on dendrites and axons, number of synapses by which neurons are connected, connection probability between neurons, distance between connected neurons, and pattern of synaptic connectivity. The connectivity pattern had a small-world topology but was not scale free. Together, our results suggest that baseline synaptic connectivity in local cortical circuits may largely result from accidentally overlapping axonal and dendritic branches of independently outgrowing neurons.     

Evidence from genetic and Lagrangian drifter data for transatlantic transport of small juvenile green turtles

Aim A key life‐history component for many animals is the need for movement between different geographical locations at particular times. Green turtle (Chelonia mydas) hatchlings disperse from their natal location to spend an early pelagic stage in the ocean, followed by a neritic stage where small juveniles settle in coastal areas. In this study, we combined genetic and Lagrangian drifter data to investigate the connectivity between natal and foraging locations. In particular we focus on the evidence for transatlantic transport. Location Atlantic Ocean. Methods We used mitochondrial DNA (mtDNA) sequences (n = 1567) from foraging groups (n = 8) and nesting populations (n = 12) on both sides of the Atlantic. Genetic data were obtained for Cape Verde juvenile turtles, a foraging group not previously sampled for genetic study. Various statistical methods were used to explore spatial genetics and population genetic structure (e.g. exact tests of differentiation, Geneland and analysis of molecular variance). Many‐to‐many mixed stock analysis estimated the connectivity between nesting and foraging groups. Results Our key new finding is robust evidence for connectivity between a nesting population on the South American coast (25% of the Surinam nesting population are estimated to go to Cape Verde) and a foraging group off the coast of West Africa (38% of Cape Verde juveniles are estimated to originate from Surinam), thus extending the results of previous investigations by confirming that there is substantial transatlantic dispersal in both directions. Lagrangian drifter data demonstrated that transport by drift across the Atlantic within a few years is possible. Main conclusions Small juvenile green turtles seem capable of dispersing extensively, and can drop out of the pelagic phase on a transatlantic scale (the average distance between natal and foraging locations was 3048 km). Nevertheless, we also find support for the ‘closest‐to‐home’ hypothesis in that the degree of contribution from a nesting population to a foraging group is correlated with proximity. Larger‐sized turtles appear to feed closer to their natal breeding grounds (the average distance was 1133 km), indicating that those that have been initially transported to far‐flung foraging grounds may still be able to move nearer to home as they grow larger.     

Geographic constraints on social network groups

Social groups are fundamental building blocks of human societies. While our social interactions have always been constrained by geography, it has been impossible, due to practical difficulties, to evaluate the nature of this restriction on social group structure. We construct a social network of individuals whose most frequent geographical locations are also known. We also classify the individuals into groups according to a community detection algorithm. We study the variation of geographical span for social groups of varying sizes, and explore the relationship between topological positions and geographic positions of their members. We find that small social groups are geographically very tight, but become much more clumped when the group size exceeds about 30 members. Also, we find no correlation between the topological positions and geographic positions of individuals within network communities. These results suggest that spreading processes face distinct structural and spatial constraints.     

On geodetic distance computations in spatial modeling

Statisticians analyzing spatial data often need to detect and model associations based upon distances on the Earth's surface. Accurate computation of distances are sought for exploratory and interpretation purposes, as well as for developing numerically stable estimation algorithms. When the data come from locations on the spherical Earth, application of Euclidean or planar metrics for computing distances is not straightforward. Yet, planar metrics are desirable because of their easier interpretability, easy availability in software packages, and well-established theoretical properties. While distance computations are indispensable in spatial modeling, their importance and impact upon statistical estimation and prediction have gone largely unaddressed. This article explores the different options in using planar metrics and investigates their impact upon spatial modeling.     

Clines, clusters, and the effect of study design on the inference of human population structure

Previously, we observed that without using prior information about individual sampling locations, a clustering algorithm applied to multilocus genotypes from worldwide human populations produced genetic clusters largely coincident with major geographic regions. It has been argued, however, that the degree of clustering is diminished by use of samples with greater uniformity in geographic distribution, and that the clusters we identified were a consequence of uneven sampling along genetic clines. Expanding our earlier dataset from 377 to 993 markers, we systematically examine the influence of several study design variables—sample size, number of loci, number of clusters, assumptions about correlations in allele frequencies across populations, and the geographic dispersion of the sample—on the “clusteredness” of individuals. With all other variables held constant, geographic dispersion is seen to have comparatively little effect on the degree of clustering. Examination of the relationship between genetic and geographic distance supports a view in which the clusters arise not as an artifact of the sampling scheme, but from small discontinuous jumps in genetic distance for most population pairs on opposite sides of geographic barriers, in comparison with genetic distance for pairs on the same side. Thus, analysis of the 993-locus dataset corroborates our earlier results: if enough markers are used with a sufficiently large worldwide sample, individuals can be partitioned into genetic clusters that match major geographic subdivisions of the globe, with some individuals from intermediate geographic locations having mixed membership in the clusters that correspond to neighboring regions.