Letteratura scientifica selezionata sul tema "Temporally variable migration"

Cultural evolution is partly driven by the strategies individuals use to learn behaviour from others. Previous experiments on strategic learning let groups of participants engage in repeated rounds of a learning task and analysed how choices are affected by individual payoffs and the choices of group members. While groups in such experiments are fixed, natural populations are dynamic, characterized by overlapping generations, frequent migrations and different levels of experience. We present a preregistered laboratory experiment with 237 mostly German participants including migration, differences in expertise and both spatial and temporal variation in optimal behaviour. We used simulation and multi-level computational learning models including time-varying parameters to investigate adaptive time dynamics in learning. Confirming theoretical predictions, individuals relied more on (conformist) social learning after spatial compared with temporal changes. After both types of change, they biased decisions towards more experienced group members. While rates of social learning rapidly declined in rounds following migration, individuals remained conformist to group-typical behaviour. These learning dynamics can be explained as adaptive responses to different informational environments. Summarizing, we provide empirical insights and introduce modelling tools that hopefully can be applied to dynamic social learning in other systems.

Humpback whale seasonal migrations, spanning greater than 6500 km of open ocean, demonstrate remarkable navigational precision despite following spatially and temporally distinct migration routes. Satellite-monitored radio tag-derived humpback whale migration tracks in both the South Atlantic and South Pacific include constant course segments of greater than 200 km, each spanning several days of continuous movement. The whales studied here maintain these directed movements, often with better than 1° precision, despite the effects of variable sea-surface currents. Such remarkable directional precision is difficult to explain by established models of directional orientation, suggesting that alternative compass mechanisms should be explored.

Abstract Running title: Monarch alternative migration: We collected 434 adult monarchs and surveyed milkweeds for immature monarchs in southwest Michigan, USA in order to test the hypothesis that monarchs are temporally variable, sequential partial migrants rather than partial migrants that may be spatially separated. Adult size, wing wear, female egg counts, fat content and sequestered chemical defenses were measured in monarchs across an entire season from spring migrant arrival, through breeding, until autumn migrant departure. We predicted that a population characterized by starting from all migrants and no residents, through breeding residents, to all migrants and no residents should show life history measures consistent with changes in these proportions. Results show that female monarch spring migrants arrive with chorionated eggs and high wing loads in both intact and fat-extracted adults. Wing loads of both males and females decrease during the summer and increase again immediately before autumn departure, when the fat content of all adults increases markedly. The high fat content of spring arrivals is also characteristic of migrants. Cardenolide content of adults showed a similar pattern of high content in spring arrivals, a decrease in the summer and then an accumulation of cardenolide defenses in adults in late summer just before migratory departure. We conclude that these results are consistent with temporally variable, sequential partial migration in a short-lived insect that contrasts with spatially variable partial migration in longer-lived vertebrates.

Migration is a valuable life history strategy for many species because it enables individuals to exploit spatially and temporally variable resources. Globally, the prevalence of species’ migratory behavior is decreasing as individuals forgo migration to remain resident year-round, an effect hypothesized to result from anthropogenic changes to landscape dynamics. Efforts to conserve and restore migrations require an understanding of the ecological characteristics driving the behavioral tradeoff between migration and residence. We identified migratory and resident behaviors of 42 mule deer (Odocoileus hemionus) based on GPS locations and correlated their locations to remotely sensed indicators of forage quality, land cover, snow cover, and human land use. The model classified mule deer seasonal migratory and resident niches with an overall accuracy of 97.8% and cross-validated accuracy of 81.2%. The distance to development was the most important variable in discriminating in which environments these behaviors occur, with resident niche space most often closer to developed areas than migratory niches. Additionally, snow cover in December was important for discriminating summer migratory niches. This approach demonstrates the utility of niche analysis based on remotely sensed environmental datasets and provides empirical evidence of human land use impacts on large-scale wildlife migrations.

Abstract Citizen science data have already been used to effectively address questions regarding migration, a fundamental stage in the life history of birds. In this study, we use data from eBird and from 3 additional regional citizen science databases to describe the migration routes and timing of the red-footed falcon Falco vespertinus in the Mediterranean region across 8 years (2010–2017). We further examine the seasonal and yearly variation in migration patterns and explore sites used during the species migration. Our results suggest that the autumn passage is spatially less variable and temporally more consistent among years than in spring and that birds migrate faster in spring than in autumn. The species seems to be more prevalent along the Central Mediterranean during spring migration, probably as a result of the clockwise loop migration that red-footed falcons perform. There was a high variation in annual median migration dates for both seasons as well as in migration routes across years and seasons. Higher variation was exhibited in the longitudinal component thus indicating flexibility in migration routes. In addition, our results showed the species’ preference for lowlands covered with cropland and mosaics of cropland and natural vegetation as stopover sites during migration. Stopover areas predicted from our distribution modeling highlight the importance of the Mediterranean islands as stopover sites for sea-crossing raptors, such as the red-footed falcon. This study is the first to provide a broad-scale spatiotemporal perspective on the species migration across seasons, years and flyways and demonstrates how citizen science data can inform future monitoring and conservation strategies.

Motile organisms actively detect environmental signals and migrate to a preferable environment. Especially, small animals convert subtle spatial difference in sensory input into orientation behavioral output for directly steering toward a destination, but the neural mechanisms underlying steering behavior remain elusive. Here, we analyze a C. elegans thermotactic behavior in which a small number of neurons are shown to mediate steering toward a destination temperature. We construct a neuroanatomical model and use an evolutionary algorithm to find configurations of the model that reproduce empirical thermotactic behavior. We find that, in all the evolved models, steering curvature are modulated by temporally persistent thermal signals sensed beyond the time scale of sinusoidal locomotion of C. elegans. Persistent rise in temperature decreases steering curvature resulting in straight movement of model worms, whereas fall in temperature increases curvature resulting in crooked movement. This relation between temperature change and steering curvature reproduces the empirical thermotactic migration up thermal gradients and steering bias toward higher temperature. Further, spectrum decomposition of neural activities in model worms show that thermal signals are transmitted from a sensory neuron to motor neurons on the longer time scale than sinusoidal locomotion of C. elegans. Our results suggest that employments of temporally persistent sensory signals enable small animals to steer toward a destination in natural environment with variable, noisy, and subtle cues.

Motile organisms actively detect environmental signals and migrate to a preferable environment. Especially, small animals convert subtle spatial difference in sensory input into orientation behavioral output for directly steering toward a destination, but the neural mechanisms underlying steering behavior remain elusive. Here, we analyze a C. elegans thermotactic behavior in which a small number of neurons are shown to mediate steering toward a destination temperature. We construct a neuroanatomical model and use an evolutionary algorithm to find configurations of the model that reproduce empirical thermotactic behavior. We find that, in all the evolved models, steering curvature are modulated by temporally persistent thermal signals sensed beyond the time scale of sinusoidal locomotion of C. elegans. Persistent rise in temperature decreases steering curvature resulting in straight movement of model worms, whereas fall in temperature increases curvature resulting in crooked movement. This relationship between temperature change and steering curvature reproduces the empirical thermotactic migration up thermal gradients and steering bias toward higher temperature. Further, spectrum decomposition of neural activities in model worms show that thermal signals are transmitted from a sensory neuron to motor neurons on the longer time scale than sinusoidal locomotion of C. elegans. Our results suggest that employments of temporally persistent sensory signals enable small animals to steer toward a destination in natural environment with variable, noisy, and subtle cues.

Abstract. Lateral migration of meandering rivers poses erosional risks to human settlements, roads, and infrastructure in alluvial floodplains. While there is a large body of scientific literature on the dominant mechanisms driving river migration, it is still not possible to accurately predict river meander evolution over multiple years. This is in part because we do not fully understand the relative contribution of each mechanism and because deterministic mathematical models are not equipped to account for stochasticity in the system. Besides, uncertainty due to model structure deficits and unknown parameter values remains. For a more reliable assessment of risks, we therefore need probabilistic forecasts. Here, we present a workflow to generate geomorphic risk maps for river migration using probabilistic modeling. We start with a simple geometric model for river migration, where nominal migration rates increase with local and upstream curvature. We then account for model structure deficits using smooth random functions. Probabilistic forecasts for river channel position over time are generated by Monte Carlo runs using a distribution of model parameter values inferred from satellite data. We provide a recipe for parameter inference within the Bayesian framework. We demonstrate that such risk maps are relatively more informative in avoiding false negatives, which can be both detrimental and costly, in the context of assessing erosional hazards due to river migration. Our results show that with longer prediction time horizons, the spatial uncertainty of erosional hazard within the entire channel belt increases – with more geographical area falling within 25 % < probability < 75 %. However, forecasts also become more confident about erosion for regions immediately in the vicinity of the river, especially on its cut-bank side. Probabilistic modeling thus allows us to quantify our degree of confidence – which is spatially and temporally variable – in river migration forecasts. We also note that to increase the reliability of these risk maps, we need to describe the first-order dynamics in our model to a reasonable degree of accuracy, and simple geometric models do not always possess such accuracy.

Abstract Inland-migrating shorebirds rely on wetlands as stopover sites to replenish nutrient reserves. Because wetlands are spatially and temporally dynamic, shorebirds may accumulate highly variable lipid reserves. We compared lipid reserves among four shorebird species (American Avocets [Recurvirostra americana], Long-billed Dowitchers [Limnodromus scolopaceus], Least Sandpipers [Calidris minutilla], and Western Sandpipers [C. mauri]) collected from playa wetlands in the southern Great Plains during spring 1993 and 1994. Because playas are ephemeral, we had the opportunity to examine the influence of a variable environment (a wet year and a dry year) on lipid reserves. Additionally, we examined the influence of different migration distances and strategies, and body sizes on lipid reserves. Western Sandpipers had the highest lipid reserves (41%–50%) and Dowitchers had the lowest reserves (18%). Least and Western Sandpipers had 7%–9% higher lipid reserves in the wet year than dry year. Thus, small-bodied shorebirds may be more affected by variable habitat conditions than large-bodied shorebirds because of their higher mass-specific metabolic rates. Reservas Lipídicas de Aves Playeras Migrantes Durante la Primavera en Humedales del Sur de la Gran Planicie Resumen. Las aves playeras que migran tierra adentro necesitan de humedales como lugares de escala migratoria para recuperar sus reservas de nutrientes. Debido a que los humedales son espacial y temporalmente dinámicos, las aves playeras pueden acumular lípidos como reserva de forma muy variable. En este estudio comparamos las resevas lipídicas entre cuatro especies de aves playeras (Recurvirostra americana, Limnodromus scolopaceus, Calidris minutilla y C. mauri) colectadas en los humedales “playa” de la parte sur de la gran planicie durante la primavera de 1993 y 1994. Debido a que estos humedales son ambientes efímeros, tuvimos la oportunidad de examinar la influencia de un ambiente variable (un año húmedo y un año seco) sobre las reservas lipídicas de las aves. Además, examinamos la influencia de distintas distancias y estrategias de migración y del tamaño corporal sobre las reservas. La especie con las mayores reservas lipídicas fue C. mauri (41%–50%) y la especie con las menores reservas fue L. scolopaceus (18%). Las dos especies de Calidris presentaron reservas lipídicas un 7%–9% mayores en el año húmedo que en el año seco. Por tanto, las aves playeras de tamaño pequeño podrían verse más afectadas por condiciones ambientales variables que las de tamaño grande como consecuencia de sus mayores tasas metabó licas con respecto al peso.

SummaryMigratory wader populations face global threats, mainly related to increasing rates of habitat loss and disturbance driven by human activities. To a large extent, the long-term survival of these populations requires the conservation of networks of sites along their migratory flyways. The Tagus estuary, Portugal, is among the most important wetlands for waders in the East Atlantic Flyway. Annual winter wader counts have been carried in this wetland since 1975 and a monthly roost-monitoring programme was implemented in 2007. Wintering populations of three out of the five most abundant species, DunlinCalidris alpina, Grey PloverPluvialis squatarolaand RedshankTringa totanus, showed significant population declines over the past three decades, which are most likely due to the loss and degradation of roost sites as a result of increasing human activity. The situation is unlikely to improve, as a high proportion of the wintering waders use roost sites that are situated in highly urbanised areas with no legal protection. The use of different roost sites by waders is highly variable both temporally and spatially, thus emphasizing the need for a network of good quality roost sites. Additionally, during migration, 60–80% of all the waders of the Tagus estuary concentrate at a single refuge, thus increasing the risk for wader populations during these periods.

Le monde change à un rythme sans précédent sous de nombreux aspects interconnectés les uns aux autres, et les écosystèmes sont parmi les premiers systèmes concernés. L'évolution actuelle des conditions environnementales – en partie induite par les activités anthropiques – s'accompagne d'une augmentation de la variabilité temporelle des processus environnementaux, qui vient s’ajouter à la variabilité naturelle existante. Ce travail de thèse fait partie des études qui cherchent à comprendre comment la variabilité de certains processus environnementaux clés va impacter la composition et les propriétés écologiques et évolutives des écosystèmes à différentes échelles. L'accent est mis en particulier sur l'interaction entre cette variabilité et le processus d'adaptation par évolution, qui est un aspect fondamental de la dynamique des écosystèmes. L'adaptation fait partie intégrante du fonctionnement des écosystèmes, mais elle est encore relativement peu considérée. Dans cette thèse, trois échelles biologiques sont considérées : l'échelle de la communauté, l'échelle de l'espèce et l'échelle des populations. Une approche de modélisation théorique est utilisée pour introduire certains aspects de la variabilité et étudier la façon dont les dynamiques écologiques et évolutives sont impactées.A l'échelle de la communauté, nous questionnons l'impact que des changements dans le niveau de co-adaptation des espèces peuvent avoir sur certaines relations biodiversité-fonctionnement des écosystèmes (BEF ; relations diversité-productivité, diversité-stabilité et diversité-réponse aux invasions). Des communautés aléatoires et co-adaptées sont comparées à l'aide de méthodes de dynamiques adaptatives. Les résultats montrent que la co-adaptation des espèces a un impact sur la plupart des relations BEF, inversant parfois la pente de la relation. À l'échelle de l'espèce, l'évolution de la tolérance au stress, dans le cadre d'un modèle de compromis entre la tolérance et la fécondité, est également explorée via des méthodes de dynamiques adaptatives. Les comportements évolutifs de ce modèle sont déterminés pour différentes intensités de trade-off et différentes distributions de stress. L'hétérogénéité du niveau de stress a un rôle plus important que le niveau de stress moyen dans la détermination de la stabilité de l’équilibre évolutif (contrôlant le branching). L’inverse est observé quant à la détermination de la valeur de la tolérance au stress à l’équilibre évolutif. Enfin, à l'échelle de la population, nous nous intéressons au flux génétique entre des sous-populations d'une même espèce, qui est un déterminant important de la dynamique évolutive. L'impact que des schémas de migrations variables dans le temps peuvent avoir sur le flux de gènes et sur l'adaptation locale est questionné en utilisant à la fois des analyses mathématiques et des simulations stochastiques d'un modèle île-continent. Dans ce modèle, la migration se produit sous forme de ``pulses'' récurrents. On constate que cette migratoire pulsée peut diminuer ou augmenter le taux de migration effectif selon le type de sélection appliquée. Globalement, la migration pulsée favorise la fixation d'allèles délétères et augmente la maladaptation. Les résultats suggèrent également que la migration pulsée peut laisser une signature détectable dans les génomes. Pour conclure, ces résultats sont mis en perspective, et des éléments sont proposés pour tester ces prédictions avec des données d’observations. Certaines conséquences pratiques que ces résultats peuvent avoir pour la gestion des écosystèmes et la conservation biologique sont également discutées
The world is changing at an unprecedented rate in many interconnected aspects, and ecosystems are primarily concerned. The current shift in environmental conditions is accompanied by an increase in the temporal variability of environmental processes, which is also driven by anthropogenic activities. This work is part of the effort to understand how variability in key environmental processes impacts ecosystem composition and ecological and evolutionary functioning at different scales. The focus is made in particular on the interplay between such variability and the process of adaptation, which is a key aspect of ecosystem dynamics. Adaptation is integral to the functioning of ecosystems, yet it is still relatively little considered. In this thesis, three biological scales are considered – the scale of the community, the scale of the species, and the scale of populations. A theoretical modeling approach is used to introduce some aspects of variability and investigate how ecological and evolutionary dynamics are impacted.At the community scale, the impact that changes in the species co-adaptation level may have on some biodiversity-ecosystem functioning (BEF) relationships (diversity-productivity, diversity-stability and diversity-response to invasion relationships) is questioned. Random and co-adapted communities are compared using adaptive dynamics methods. Results show that species co-adaptation impacts most BEF relationships, sometimes inverting the slope of the relationship. At the species scale, the evolution of stress tolerance under a tolerance-fecundity trade-off model is explored using adaptive dynamics as well. The evolutionary outcomes are determined under different trade-offs and different stress distributions. The most critical parameters in determining the evolutionary outcomes (ESS trait value, branching) are highlighted, and they evidence that stress level heterogeneity is more critical than average stress level. At the population scale, gene flow between sub-populations of the same species is an important determinant of evolutionary dynamics. The impact that temporally variable migration patterns have on gene flow and local adaptation is questioned using both mathematical analyses and stochastic simulations of a mainland-island model. In this model, migration occurs as recurrent “pulses”. This migration pulsedness is found to not only decrease, but also increase, the effective migration rate, depending on the type of selection. Overall, migration pulsedness favors the fixation of deleterious alleles and increases maladaptation. Results also suggest that pulsed migration may leave a detectable signature across genomes. To conclude, these results are put into perspective, and elements are proposed for possible tests of the predictions with observational data. Some practical consequences they may have for ecosystem management and biological conservation are also discussed

AbstractInternational movements by people from economically highly developed welfare states are a puzzle for the classic canon of migration theories, which generally focus on flows from less to more developed regions. Based on a simple theoretical framework linking largely disparate literatures on international and internal migration as well as the field of global work experience, this chapter provides an analysis of the emigration and remigration decisions of German citizens. Whereas the five theoretical dimensions-expected financial returns, job satisfaction, social capital, mobility capital, and employment in transnational professions-already explain much of the variance in the emigration decisions, the theoretical and empirical understanding of remigration decision-making processes remains a challenge. Contributing to recent debates about a brain drain from economically highly developed countries, this chapter provides evidence that the international migration of German citizens is best understood as brain circulation. Temporary migration dominates these international movements and emigrants are similar to remigrants along many theoretical dimensions. Although some indications for a potential loss of human capital caused by international migration do exist, they remain insignificant in light of Germany’s overall volume of international migration. Political debates about flows of people from highly developed countries should focus less on potential losses of human capital for national economies and more on the economic and non-economic returns international migration offers for individual life courses.

Abstract.—Upon entering marine waters, juvenile Pacific salmon <em>Oncorhynchus </em>spp. depend on feeding at high and sustained levels to achieve growth necessary for survival. In the last decade, several concurrent studies have been examining the food habits and feeding intensity of juvenile Pacific salmon in the shelf regions from California to the northern Gulf of Alaska. In this paper, we compared results from feeding studies for all five species of juvenile salmon (Chinook salmon <em>O. tshawytscha</em>, coho salmon <em>O. kisutch</em>, chum salmon <em>O. keta, </em>sockeye salmon <em>O. nerka</em>, and pink salmon <em>O. gorbuscha</em>) between 2000 and 2002, years when these regions were sampled extensively. Within these years, we temporally stratified our samples to include early (May–July) and late (August–October) periods of ocean migration. Coho and Chinook salmon diets were most similar due to a high consumption of fish prey, whereas pink, chum, and sockeye salmon diets were more variable with no consistently dominant prey taxa. Salmon diets varied more spatially (by oceanographic and regional factors) than temporally (by season or year) in terms of percentage weight or volume of major prey categories. We also examined regional variations in feeding intensity based on stomach fullness (expressed as percent body weight) and percent of empty or overly full stomachs. Stomach fullness tended to be greater off Alaska than off the west coast of the United States, but the data were highly variable. Results from these comparisons provide a large-scale picture of juvenile salmon feeding in coastal waters throughout much of their range, allowing for comparison with available prey resources, growth, and survival patterns associated with the different regions.

Abstract The migration of birds is a complex form of behavior, affected by many environmental factors, such as spatial and temporal variations in food availability, predators, temperature, winds, and breeding opportunities (Ens et al. 1994). Until recently, most optimization models of migration have dealt with isolated aspects like optimal migration speed (Alerstam 1979; Liechti 1995; Hedenstrom and Alerstam 1995) or optimal fuel loads (Weber et al. 1994). The dynamic state variable approach allows one to include many factors in a single model (Weber and Houston 1997; Weber et al. 1998; Farmer and Wiens 1998, 1999; Clark and Butler 1999).

Abstract A spatial and temporal framework is a prerequisite for analyzing migration and mobility behavior because these behaviors are defined by occupation of a set of locations in some temporal sequence and can only be recognized by keeping track of the locations of individuals over time. Investigations of migration and residential mobility have typically focused on one aspect of this spatial-temporal sequencing: the relocation events that move individuals from one place to an other. These are either migration events that involve the relocation of individuals between relatively distant communities or the relocation of a household to new housing within a community. Explanations of the two kinds of relocation events typically differ, with migration decisions often explained in terms of labor force participation and changes of housing treated as consumption decisions, but re search in both areas has usually centered on the events that move individuals or households from one location to another. Some recent developments in mobility research have shifted the emphasis toward explicitly longitudinal approaches in which migration and mobility behavior are analyzed in terms of sequences of be havior in space and time, which constitute locational histories for individuals. These histories provide continuous records of the whereabouts of individuals for some period of time, including the dates of relocation events, the lengths of the intervening sojourns, and information about the sequencing of relocation behavior; as well as information about the histories of other variables, such as individuals’ employment histories and marital histories.

One of the major problems challenging time series research based on stock and flow data is the inconsistency that occurs over time due to changes in variable definition, data classification and spatial boundary configuration. The census of population is a prime example of a source whose data are fraught with these problems, resulting in even the simplest comparison between the 2001 Census and its predecessor in 1991 being difficult. The first part of this chapter introduces the subject of inconsistencies between related data sets, with general reference to census interaction data. Various types of inconsistency are described. A number of approaches to dealing with inconsistency are then outlined, with examples of how these have been used in practice. The handling of journey to work data of persons who work from home is then used as an illustrative example of the problems posed by inconsistencies in base populations. Home-workers have been treated in different ways in successive UK censuses, a factor which can cause difficulties not only for researchers interested in such working practices, but also for those interested in other aspects of commuting. The latter set of problems are perhaps more pernicious, as users are less likely to be aware of the biases introduced into data sets that are being compared. In the second half of this chapter, we make use of a time series data set of migration interaction data that does have temporal consistency to explore how migration propensities and patterns in England and Wales have changed since 1999 and in particular since the year prior to the 2001 Census. The data used are those that are produced by the Office of National Statistics based on comparisons of NHS patient records from one year to the next and adjusted using data on NHS patients re-registering in different health authorities. The analysis of these data suggests that the massive exodus of individuals from major metropolitan across the country that has been identified in previous studies is continuing apace, particularly from London whose net losses doubled in absolute terms between 1999 and 2004 before reducing marginally in 2005 and 2006. Whilst this pattern of counterurbanisation is evident for all-age flows, it conceals significant variations for certain age groups, not least those aged between 16 and 24, whose migration propensities are high and whose net redistribution is closely connected with the location of universities. The time series analyses are preceded by a comparison of patient register data with corresponding data from the 2001 Census. This suggests strong correlation between the indicators selected and strengthens the argument that patient register data in more recent years provide reliable evidence for researchers and policy makers on how propensities and patterns change over time.

One of the major problems challenging time series research based on stock and flow data is the inconsistency that occurs over time due to changes in variable definition, data classification and spatial boundary configuration. The census of population is a prime example of a source whose data are fraught with these problems, resulting in even the simplest comparison between the 2001 Census and its predecessor in 1991 being difficult. The first part of this chapter introduces the subject of inconsistencies between related data sets, with general reference to census interaction data. Various types of inconsistency are described. A number of approaches to dealing with inconsistency are then outlined, with examples of how these have been used in practice. The handling of journey to work data of persons who work from home is then used as an illustrative example of the problems posed by inconsistencies in base populations. Home-workers have been treated in different ways in successive UK censuses, a factor which can cause difficulties not only for researchers interested in such working practices, but also for those interested in other aspects of commuting. The latter set of problems are perhaps more pernicious, as users are less likely to be aware of the biases introduced into data sets that are being compared. In the second half of this chapter, we make use of a time series data set of migration interaction data that does have temporal consistency to explore how migration propensities and patterns in England and Wales have changed since 1999 and in particular since the year prior to the 2001 Census. The data used are those that are produced by the Office of National Statistics based on comparisons of NHS patient records from one year to the next and adjusted using data on NHS patients re-registering in different health authorities. The analysis of these data suggests that the massive exodus of individuals from major metropolitan across the country that has been identified in previous studies is continuing apace, particularly from London whose net losses doubled in absolute terms between 1999 and 2004 before reducing marginally in 2005 and 2006. Whilst this pattern of counterurbanisation is evident for all-age flows, it conceals significant variations for certain age groups, not least those aged between 16 and 24, whose migration propensities are high and whose net redistribution is closely connected with the location of universities. The time series analyses are preceded by a comparison of patient register data with corresponding data from the 2001 Census. This suggests strong correlation between the indicators selected and strengthens the argument that patient register data in more recent years provide reliable evidence for researchers and policy makers on how propensities and patterns change over time.

Several visualisation methods have been recently proposed to aid a wide variety of users in the exploration of geographical trajectory, or trail, datasets. Such datasets consist of thousands up to millions of spatio-temporal trails that are also attributed by many additional data variables related to the identity of the tracked items, type of motion being recorded, data provenance, and more. As both data size and data dimensionality grow, finding efficient and effective ways to answer concrete questions, as well as discover unknown insights, from such data become increasingly important. We present an overview of recent information visualisation and visual analytics developments in this direction, with the aim of bridging the gap between Technical developments in this area and actual users and use-cases that can benefit from them. In this overview, we discuss strengths, limitations, assumptions, and other important characteristics of such visualisation methods, so as to help domain experts find optimal methods for their given application contexts. We illustrate our discussion with several examples of visualisation of large-scale, real-world, trajectory datasets related to migration data and use-cases.

Abstract Using the loanword ‘wanderlust’ as point of departure, the final chapter summarizes the many ways in which the mobility of speakers, words and languages are at the heart of how societies adjust their linguistic repertoires. As expounded in the previous chapters, trade, religion, nation-building, colonialism, migration, and technology impact the spatial and temporal dynamics of how people communicate, what languages they use, how they use them, and how they change them. Against this background, this chapter examines traditional patterns of language categorization and societal stratification and argues that a processual view of language and society in the spirit of Norbert Elias is the most promising approach for coming to grips with language and mobility in such a highly complex mix of variables and the momentous changes we are experiencing at present.

<em>Abstract</em>.—Allelic variation at 19 nuclear-encoded microsatellite loci and haplotype variation in a 590 bp protein-coding fragment of mitochondrial (mt)DNA were assayed among Gulf red snapper sampled from four cohorts at each of three offshore localities (12 samples total) in the northern Gulf of Mexico. Significant heterogeneity in allele and genotype distributions among samples was detected at four microsatellites; six of seven ‘significant’ pairwise comparisons between samples revealed the heterogeneity to be temporal rather than spatial. Nested-clade analysis of mtDNA variants indicated different temporal episodes of range expansion and isolation by distance. Estimates of variance effective population size (microsatellites) ranged between ∼1,000 and >75,000 and differed significantly among localities. The differences in variance effective size likely reflect differences in number of individuals successfully reproducing or differences in patterns and intensity of migration. Collectively, these findings are consistent with the hypothesis that red snapper in the northern Gulf occur as a network (or metapopulation) of semi-isolated assemblages that may be demographically independent over the short term, yet over the long term can influence each other’s demographics via gene flow. This type of population structure may be difficult to detect with commonly used, selectively neutral genetic markers.

<em>Abstract.</em>—The causes of spatial and temporal variation in Pacific salmon abundance are poorly understood. An additional challenge in the Arctic-Yukon-Kuskokwim (AYK) region is the expansive and remote nature of salmon habitat. In this paper, the authors discuss a hierarchical framework that may prove helpful in identifying key variables regulating Pacific salmon abundance. The hierarchical framework considers processes that act at multiple scales of space and time, identifies generalizations across scales, and considers interactions among variables operating at different scales. This framework is used to address three overarching questions for the AYK region: 1) What are the important units of focus for conservation and management? 2) What are the factors that control abundance and connectivity of these units? 3) How can these two questions be integrated to better understand and manage Pacific salmon? Genetic and ecotypic units are organized hierarchically in space and time. Genetic units of AYK salmon have been identified at a local level among tributaries in the Yukon and Kuskokwim drainages, the Norton Sound, and at a regional level where all species share similar genetic discontinuities. Ecotypic units are habitat-organismal trait associations characteristic of Pacific salmon, but are not well documented for AYK stocks. The processes controlling abundance and connectivity among these units also occur at multiple hierarchical levels with respect to life history, space, and time. Identifying the scale at which processes or interaction among processes have the largest relative impact on salmon recruitment will be critical to effectively managing Pacific salmon. Four feasible lines of study proposed for gathering informative data from the expansive and remote AYK region include: (1) a spatial comparison between habitat and spawning populations, (2) a comparison of mortality as related to life history diversity, (3) compilation of existing migration data to explain patterns in migration timing, and (4) coordination of genetic data to test hypotheses regarding population structure. Use of existing long-term data and coordination of ongoing research efforts should be of high importance for AYK biologists and managers.

Abstract Geologic carbon dioxide (CO2) sequestration has received significant attention from the scientific community as a response to global warming due to greenhouse gas emission. Effective monitoring of CO2 plume is critical to CO2 storage safety throughout the life-cycle of a geologic CO2 sequestration project. Although simulation-based techniques such as history matching can be used for predicting the evolution of underground CO2 saturation, the computational cost of the high-fidelity simulations can be prohibitive. Recent development in data-driven models can provide a viable alternative for rapid CO2 plume imaging. Here, we present a novel deep learning-based workflow that can efficiently visualize CO2 plume in near real-time. Our deep learning framework utilizes field measurements, such as downhole pressure, distributed pressure and temperature as input to visualize the subsurface CO2 plume images. However, the high output dimension of CO2 plume images makes the training inefficient. We address this challenge in two ways: first, we output a single CO2 onset time map rather than multiple saturation maps at different times; second, we apply an autoencoder-decoder network to identify lower dimensional latent variables that compress high dimensional output images. The ‘onset time’ is the calendar time when the CO2 saturation at a given location exceeds a specified threshold value. In our approach, a deep learning-based regression model is trained to predict latent variables of the autoencoder-decoder network. Subsequently the latent variables are used as inputs of the trained decoder network to generate the 3D onset time image, visualizing the evolving CO2 plume in near real-time. The power and efficacy of our approach are demonstrated using both synthetic and field-scale applications. We first validate the deep learning-based CO2 plume imaging workflow using a 2D synthetic example. Next, the visualization workflow is applied to a 3D field-scale reservoir to demonstrate the robustness and efficiency of the workflow. The monitoring data set consists of distributed temperature sensing (DTS) data acquired at a monitoring well, flowing bottom-hole pressure data at the injection well, and time-lapse pressure measurements at several locations along the monitoring well. Our approach is also extended to efficiently evaluate the uncertainty of predicted CO2 plume images. Additionally, an efficient workflow for optimizing data acquisition and measurement type is demonstrated using our deep learning-based framework. The novelty of this work is the development and applications of a unique and efficient deep learning-based subsurface visualization workflow for the spatial and temporal migration of the CO2 plume. The efficiency and flexibility of the data-driven workflow make our approach suitable for field-scale applications.