299 research outputs found
From Local Adaptation to Speciation: Specialization and Reinforcement
Local adaptation is the first step in the process of ecological speciation. It is, however, an unstable and dynamic situation. It can be strengthened by the occurrence of alleles more specialized to the different habitats or vanish if generalist alleles arise by mutations and increase in frequency. This process can have complicated dynamics as specialist alleles may be much more common and may maintain local adaptation for a long time. Thus, even in the absence of an absolute fitness tradeoff between habitats, local adaptation may persist a long time before vanishing. Furthermore, several feedback loops can help to maintain it (the reinforcement, demographic, and recombination loops). This reinforcement can occur by modifying one of the three fundamental steps in a sexual life cycle (dispersal, syngamy, meiosis), which promotes genetic clustering by causing specific genetic associations. Distinguishing these mechanisms complements the one- versus two-allele classification. Overall, the relative rates of the two processes (specialization and reinforcement) dictate whether ecological speciation will occur
Is spatial information in ICT data reliable?
An increasing number of human activities are studied using data produced by
individuals' ICT devices. In particular, when ICT data contain spatial
information, they represent an invaluable source for analyzing urban dynamics.
However, there have been relatively few contributions investigating the
robustness of this type of results against fluctuations of data
characteristics. Here, we present a stability analysis of higher-level
information extracted from mobile phone data passively produced during an
entire year by 9 million individuals in Senegal. We focus on two
information-retrieval tasks: (a) the identification of land use in the region
of Dakar from the temporal rhythms of the communication activity; (b) the
identification of home and work locations of anonymized individuals, which
enable to construct Origin-Destination (OD) matrices of commuting flows. Our
analysis reveal that the uncertainty of results highly depends on the sample
size, the scale and the period of the year at which the data were gathered.
Nevertheless, the spatial distributions of land use computed for different
samples are remarkably robust: on average, we observe more than 75% of shared
surface area between the different spatial partitions when considering activity
of at least 100,000 users whatever the scale. The OD matrix is less stable and
depends on the scale with a share of at least 75% of commuters in common when
considering all types of flows constructed from the home-work locations of
100,000 users. For both tasks, better results can be obtained at larger levels
of aggregation or by considering more users. These results confirm that ICT
data are very useful sources for the spatial analysis of urban systems, but
that their reliability should in general be tested more thoroughly.Comment: 11 pages, 9 figures + Appendix, Extended version of the conference
paper published in the proceedings of the 2016 Spatial Accuracy Conference, p
9-17, Montpellier, Franc
Crowdsourcing the Robin Hood effect in cities
Socioeconomic inequalities in cities are embedded in space and result in
neighborhood effects, whose harmful consequences have proved very hard to
counterbalance efficiently by planning policies alone. Considering
redistribution of money flows as a first step toward improved spatial equity,
we study a bottom-up approach that would rely on a slight evolution of shopping
mobility practices. Building on a database of anonymized credit card
transactions in Madrid and Barcelona, we quantify the mobility effort required
to reach a reference situation where commercial income is evenly shared among
neighborhoods. The redirections of shopping trips preserve key properties of
human mobility, including travel distances. Surprisingly, for both cities only
a small fraction () of trips need to be altered to reach equity
situations, improving even other sustainability indicators. The method could be
implemented in mobile applications that would assist individuals in reshaping
their shopping practices, to promote the spatial redistribution of
opportunities in the city.Comment: 9 pages, 4 figures + Appendi
From mobile phone data to the spatial structure of cities
Pervasive infrastructures, such as cell phone networks, enable to capture
large amounts of human behavioral data but also provide information about the
structure of cities and their dynamical properties. In this article, we focus
on these last aspects by studying phone data recorded during 55 days in 31
Spanish metropolitan areas. We first define an urban dilatation index which
measures how the average distance between individuals evolves during the day,
allowing us to highlight different types of city structure. We then focus on
hotspots, the most crowded places in the city. We propose a parameter free
method to detect them and to test the robustness of our results. The number of
these hotspots scales sublinearly with the population size, a result in
agreement with previous theoretical arguments and measures on employment
datasets. We study the lifetime of these hotspots and show in particular that
the hierarchy of permanent ones, which constitute the "heart" of the city, is
very stable whatever the size of the city. The spatial structure of these
hotspots is also of interest and allows us to distinguish different categories
of cities, from monocentric and "segregated" where the spatial distribution is
very dependent on land use, to polycentric where the spatial mixing between
land uses is much more important. These results point towards the possibility
of a new, quantitative classification of cities using high resolution
spatio-temporal data.Comment: 14 pages, 15 figure
Uncovering the spatial structure of mobility networks
The extraction of a clear and simple footprint of the structure of large,
weighted and directed networks is a general problem that has many applications.
An important example is given by origin-destination matrices which contain the
complete information on commuting flows, but are difficult to analyze and
compare. We propose here a versatile method which extracts a coarse-grained
signature of mobility networks, under the form of a matrix that
separates the flows into four categories. We apply this method to
origin-destination matrices extracted from mobile phone data recorded in
thirty-one Spanish cities. We show that these cities essentially differ by
their proportion of two types of flows: integrated (between residential and
employment hotspots) and random flows, whose importance increases with city
size. Finally the method allows to determine categories of networks, and in the
mobility case to classify cities according to their commuting structure.Comment: 10 pages, 5 figures +Supplementary informatio
The genetic architecture of local adaptation in a cline
Local adaptation is pervasive. It occurs whenever selection favors different phenotypes in different environments, provided that there is genetic variation for the corresponding traits and that the effect of selection is greater than the effect of drift and migration. In many cases, ecologically relevant traits are quantitative and controlled by many genes. It has been repeatedly proposed that the localization of these genes in the genome may not be random, but could be an evolved feature. In particular, the clustering of local adaptation genes may be theoretically expected and has been observed in several situations. Previous theory has focused on two-patch or continent-island models to investigate this phenomenon, reaching the conclusion that such clustering could evolve, but in relatively limited conditions. In particular, it required that migration rate was neither too low nor too large and that the full optimization of trait values could not be eventually achieved by a mutation at a single locus. Here, we investigate this question in a spatially-explicit model, considering two contiguous habitats with distinct trait optima on a circular stepping-stone. We find that clustering of local-adaptation genes is pervasive within clines during both the establishment phase of local adaptation and the subsequent “reconfiguration” phase where different genetic architectures compete with each other. We also show that changing the fitness function relating trait to fitness has a strong impact on the overall evolutionary dynamics and resulting architecture
Comparing and modeling land use organization in cities
The advent of geolocated ICT technologies opens the possibility of exploring
how people use space in cities, bringing an important new tool for urban
scientists and planners, especially for regions where data is scarce or not
available. Here we apply a functional network approach to determine land use
patterns from mobile phone records. The versatility of the method allows us to
run a systematic comparison between Spanish cities of various sizes. The method
detects four major land use types that correspond to different temporal
patterns. The proportion of these types, their spatial organization and scaling
show a strong similarity between all cities that breaks down at a very local
scale, where land use mixing is specific to each urban area. Finally, we
introduce a model inspired by Schelling's segregation, able to explain and
reproduce these results with simple interaction rules between different land
uses.Comment: 9 pages, 6 figures + Supplementary informatio
Nonparametric Estimation of Natural Selection on a Quantitative Trait using Mark-Recapture Data
Assessing natural selection on a phenotypic trait in wild populations is of primary importance for evolutionary ecologists. To cope with the imperfect detection of individuals inherent to monitoring in the wild, we develop a nonparametric method for evaluating the form of natural selection on a quantitative trait using mark-recapture data. Our approach uses penalized splines to achieve flexibility in exploring the form of natural selection by avoiding the need to specify an a priori parametric function. If needed, it can help in suggesting a new parametric model. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data for a wild population of sociable weavers (Philetairus socius) to investigate survival in relation to body mass. In agreement with previous parametric analyses, we found that lighter individuals showed a reduction in survival. However, the survival function was not symmetric, indicating that body mass might not be under stabilizing selection as suggested previously
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