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450 results for “Spatio-temporal”
Data from: Rich do not rise early: spatio-temporal patterns in the mobility networks of different socio-economic classes
We analyse the urban mobility in the cities of Medellín and Manizales (Colombia). Each city is represented by six mobility networks, each one encoding the origin-destination trips performed by a subset of the population corresponding to a particular socio-economic status. The nodes of each network are the different urban locations whereas links account for the existence of a trip between two different areas of the city. We study the main structural properties of these mobility networks by focusing on their spatio-temporal patterns. Our goal is to relate these patterns with the partition into six socio-economic compartments of these two societies. Our results show that spatial and temporal patterns vary across these socio-economic groups. In particular, the two datasets show that as wealth increases the early-morning activity is delayed, the midday peak becomes smoother and the spatial distribution of trips becomes more localized.
Data from: Spatio-temporal variation of biotic and abiotic stress agents determines seedling survival in assisted oak regeneration
1. Mediterranean oak woodlands are currently undergoing considerable anthropogenic changes that globally threaten their long-term persistence. Restoration efforts via assisted regeneration depend on species traits and type of stress. However, how different sources of stress vary across space (microsites) and time (intra and inter-annual variation) for co-occurring oak species remains largely unknown. 2. We examined spatio-temporal variation of biotic (herbivory, seed predation) and abiotic (drought) stress agents to evaluate seedling survival across different regeneration microsites, and considering two climatically contrasting years. We used two co-occurring species of contrasting ecology and leaf traits in California oak woodlands: the deciduous Quercus lobata and the evergreen Q. agrifolia. 3. Most oak seedlings (98.8%) suffered from some type of stress. For both species, summer drought was the main cause of mortality, followed by rodent damage, ungulate browsing and insect damage. Rodents represented the predominant biotic stress, as all rodent-affected seedlings eventually died. Interactions among stress factors were nuanced: insect and ungulate-browsing stresses were greater during dry year, whereas rodent damage was similar in dry and average years. Intra-annually, rodent damage was the main stress agent in early spring, whereas water stress and ungulate-browsing were greater in late spring-early fall. Plant species traits were also determinant: overall, the evergreen species had greater survival probability than the deciduous one. 4. Across microsites, water stress showed higher occurrence in open grassland habitats, while rodent damage was prevalent under palatable shrubs and ungulate browsing under conspecific trees. Shrub and tree cover reduced damage attributed to water stress but increased rodent and ungulate damage, respectively. Interestingly, lower water stress but higher rodent damage was found further inside the shrub cover. 5. Synthesis and applications. Intra and inter-annual variation are critical determinants of stress type and intensity on oak recruitment. Spatial variation (microsite identity) is also informative to manipulate stress agent impact. We conclude that assisted regeneration should consider not only the predominance and lethality of each stress type and microsite, but also the interactions thereof and thus manipulate protective microsites accordingly.
Data from: Spatio-temporal modelling of auk abundance after the Erika oil spill and implications for conservation
Species distribution models are widely used in applied ecology and conservation. While accounting for spatial dependences is now the rule, temporal dependences have rarely been dealt with explicitly. In this study, we analyse wintering auk distribution in the Bay of Biscay and English Channel and estimate changes in abundance within and between years while accounting for space–time dependencies. We then propose a retrospective estimate of the impact of the Erika oil spill that occurred in December 1999. Two series of extensive aerial surveys, repeated at intervals of 1–2 months, were carried out at a 10-year interval off the French Atlantic coast (2001–2002 and 2011–2012). Spatially and temporally explicit Bayesian models were fitted to these data to provide spatio-temporal predictions of auk abundance. These were then used to compare abundances within the area affected by the Erika oil spill two and twelve years after the catastrophe. The results showed that 1·55 million auks wintered in the study area in 2011–2012. The main wintering area was the English Channel (more than one million auks) but the Bay of Biscay also became an important area in the middle of winter (470 000 auks) owing to a strong southward shift in auk distribution. Two years after the catastrophe (2001–2002), the area affected by the Erika oil spill hosted a small proportion of auks of the Bay of Biscay – about 80 000 individuals. This number increased by more than three times 10 years later and reached 270 000 individuals, whereas no significant change was detected elsewhere. We suggest that it could result from a recovery after the extra-mortality induced by the Erika oil spill. Policy implications. This study identified major auk wintering areas, with abundances much higher than previously realized. Oil spills have occurred regularly in these areas, with major delayed impacts on auk breeding populations. The worst case scenario would be if a major oil spill occurred in the English Channel in February, when abundance reaches one million auks. Although such a disaster has not so far occurred, stricter policies on the transport of hydrocarbons should be implemented to prevent such a possibility.
Data from: A genetic demographic analysis of Lake Malawi rock-dwelling cichlids using spatio-temporal sampling
We estimated the effective population sizes (Ne) and tested for short-term temporal demographic stability of populations of two Lake Malawi cichlids: Maylandia benetos, a micro-endemic, and Maylandia zebra, a widespread species found across the lake. We sampled a total of 351 individuals, genotyped them at 13 microsatellite loci and sequenced their mitochondrial D-loop to estimate genetic diversity, population structure, demographic history and effective population sizes. At the microsatellite loci, genetic diversity was high in all populations. Yet, genetic diversity was relatively low for the sequence data. Microsatellites yielded mean Ne estimates of 481 individuals (±99 SD) for M. benetos and between 597 (±106.3 SD) and 1524 (±483.9 SD) individuals for local populations of M. zebra. The microsatellite data indicated no deviations from mutation–drift equilibrium. Maylandia zebra was further found to be in migration–drift equilibrium. Temporal fluctuations in allele frequencies were limited across the sampling period for both species. Bayesian Skyline analyses suggested a recent expansion of M. zebra populations in line with lake-level fluctuations, whereas the demographic history of M. benetos could only be estimated for the very recent past. Divergence time estimates placed the origin of M. benetos within the last 100 ka after the refilling of the lake and suggested that it split off the sympatric M. zebra population. Overall, our data indicate that micro-endemics and populations in less favourable habitats have smaller Ne, indicating that drift may play an important role driving their divergence. Yet, despite small population sizes, high genetic variation can be maintained.
Data from: Spatio-temporal responses of predators to hyperabundant geese affect risk of predation for sympatric-nesting species
The Arctic is undergoing rapid changes, with anthropogenic shifts in climate having important and well-documented impacts on habitat. Populations of predators and their prey are affected by changing climate and other anthropogenic factors, and these changing trophic interactions could have profound effects on breeding populations of Arctic birds. Variable abundance of lemmings (a primary prey of generalist Arctic predators) and increasing abundance of light geese (Lesser Snow and Ross' Geese; a secondary prey) could have negative consequences for numerous sympatric shorebirds (an incidental prey). Using 16 years of predator-prey observations and 13-years of shorebird nest survival data at a site near a goose colony we identify relationships among geese, lemmings, and their shared predators and then relate predator indices to shorebird risk of nest predation. During two years, we also placed time-lapse cameras and artificial shorebird nests at increasing distances from a goose colony to document spatial trends in predators and their effect on risk of predation. In the long-term data, yearly indices of light geese positively influenced indices of gulls and jaegers, and shorebird nest predation rate was negatively correlated with jaeger and fox indices. All three predator indices were highest near the goose colony and artificial nest predation probability was negatively correlated with distance from goose colony, but these effects were less apparent during the second year. Combined, these results highlight the variation in predator-mediated interactions between geese and shorebirds and outline one mechanism by which hyperabundant geese may be contributing to local or regional declines in Arctic-nesting shorebird populations.
Data from: The impacts of climate change and disturbance on spatio-temporal trajectories of biodiversity in a temperate forest landscape
The ongoing changes to climate challenge the conservation of forest biodiversity. Yet, in thermally limited systems, such as temperate forests, not all species groups might be affected negatively. Furthermore, simultaneous changes in the disturbance regime have the potential to mitigate climate-related impacts on forest species. Here, we (i) investigated the potential long-term effect of climate change on biodiversity in a mountain forest landscape, (ii) assessed the effects of different disturbance frequencies, severities and sizes and (iii) identified biodiversity hotspots at the landscape scale to facilitate conservation management. We employed the model iLand to dynamically simulate the tree vegetation on 13 865 ha of the Kalkalpen National Park in Austria over 1000 years, and investigated 36 unique combinations of different disturbance and climate scenarios. We used simulated changes in tree cover and composition as well as projected temperature and precipitation to predict changes in the diversity of Araneae, Carabidae, ground vegetation, Hemiptera, Hymenoptera, Mollusca, saproxylic beetles, Symphyta and Syrphidae, using empirical response functions. Our findings revealed widely varying responses of biodiversity indicators to climate change. Five indicators showed overall negative effects, with Carabidae, saproxylic beetles and tree species diversity projected to decrease by more than 33%. Six indicators responded positively to climate change, with Hymenoptera, Mollusca and Syrphidae diversity projected to increase more than twofold. Disturbances were generally beneficial for the studied indicators of biodiversity. Our results indicated that increasing disturbance frequency and severity have a positive effect on biodiversity, while increasing disturbance size has a moderately negative effect. Spatial hotspots of biodiversity were currently found in low- to mid-elevation areas of the mountainous study landscape, but shifted to higher-elevation zones under changing climate conditions. Synthesis and applications. Our results highlight that intensifying disturbance regimes may alleviate some of the impacts of climate change on forest biodiversity. However, the projected shift in biodiversity hotspots is a challenge for static conservation areas. In this regard, overlapping hotspots under current and expected future conditions highlight priority areas for robust conservation management.
Data from: Spatio-temporal effects of logging and fire on tall, wet temperate eucalypt forest birds
Forests globally are subject to multiple disturbances such as logging and fire that create complex temporal variation in spatial patterns of forest cover and stand age. However, investigations that quantify temporal changes in biodiversity in response to multiple forms of disturbance in space and time are relatively uncommon. Over a 10-year period, we investigated the response of bird species to spatio-temporal changes in cover associated with logging and wildfire in the Mountain Ash (Eucalyptus regnans) forests of south-eastern Australia. Specifically, we examined how bird occurrence changed with shifts in the proportion of area burnt or logged in a 4.5km radius surrounding each of 87 field survey sites. Overall species richness was greatest in older forest patches. Bird species richness declined as the amount of fire around each site increased. At the individual species level, most species were more likely to be found in old growth than younger forest. Twenty-five of 36 bird species we modeled, exhibited a negative response to the amount of fire in the surrounding landscape (while two species responded positively to fire). Only nine species exhibited signs of post-fire recovery. Ten species were more likely to be recorded as the proportion of logged forest surrounding a site increased, suggesting a possible "concentration effect" with displaced birds moving into unlogged areas following harvesting of adjacent areas. In contrast to predictions from the disturbance-congruence hypothesis, no bird species exhibited similar responses to fire and logging in the landscape surrounding our sites. Similarly, no bird life history traits were associated with burned or logged forest, although insectivorous birds were more likely to be found in old growth forests and increased over time. Birds in Mountain Ash forests are strongly associated with old growth stands and exhibit complex, time-dependent and species-specific responses to landscape disturbance. Despite logging and fire both being high-severity perturbations, species responses to one kind of landscape-scale disturbance are not readily predictable based on an understanding of the responses to another kind of (albeit superficially similar) disturbance.
Data from: Spatio-temporal dynamics of density-dependent dispersal during a population colonisation
Predicting population colonisations requires understanding how spatio-temporal changes in density affect dispersal. Density can inform on fitness prospects, acting as a cue for either habitat quality, or competition over resources. However, when escaping competition, high local density should only increase emigration if lower-density patches are available elsewhere. Few empirical studies on dispersal have considered the effects of density at the local and landscape scale simultaneously. To explore this, we analyze 5 years of individual-based data from an experimental introduction of wild guppies Poecilia reticulata. Natal dispersal showed a decrease in local density dependence as density at the landscape level increased. Landscape density did not affect dispersal among adults, but local density-dependent dispersal switched from negative (conspecific attraction) to positive (conspecific avoidance), as the colonisation progressed. This study demonstrates that densities at various scales interact to determine dispersal, and suggests that dispersal trade-offs differ across life stages.
Data from: Population structure of a microparasite infecting Daphnia: spatio-temporal dynamics
Background: Detailed knowledge of spatial and temporal variation in the genetic population structure of hosts and parasites is required for understanding of hostparasite coevolution. As hot-spots of contemporary coevolution in natural systems are difficult to detect and long-term studies are restricted to few systems additional population genetic data from various hostparasite systems may provide important insights into the topic. This is particularly true for parasites as these players have been under-investigated so far due to the lower availability of suitable molecular markers. Here we traced genetic variation (based on sequence variants in the internal transcribed spacer region ITS) among seven geographically isolated populations of the ichthyosporean Caullerya mesnili a common microparasite of the cladoceran Daphnia (here the D. longispina hybrid complex). At some sites we also studied parasite genetic variation over time. Then we tested for associations between parasite genotypes and host species. Results: Parasite (and host) populations were significantly structured across space indicating limited dispersal. Moreover the frequency of parasite genotypes varied significantly over time suggesting rapid evolutionary change in Caullerya. Finally the distribution of parasite genotypes was similar across different host species which might in turn have important consequences for parasite epidemiology. Conclusions: The approach proposed here can be applied to track spatial and temporal changes in the population structure of other microparasite species for which sequence variation in the ITS or other highly variable genome regions has been documented but other types of polymorphic markers are lacking. Screening of parasite sequence variants allows for reliable detection of cross-species infections and using advanced sequencing techniques in the near future for detailed studies of parasite evolution in natural hostparasite systems.
Data from: Relationships between spatio-temporal environmental and genetic variation reveal an important influence of exogenous selection in a pupfish hybrid zone
The importance of exogenous selection in a natural hybrid zone between the pupfishes Cyprinodon atrorus and C. bifasciatus was tested via spatio-temporal analyses of environmental and genetic change over winter, spring, and summer for three consecutive years. A critical influence of exogenous selection on hybrid zone regulation was demonstrated by a significant relationship between environmental (salinity and temperature) and genetic (three diagnostic nuDNA loci) variation over space and time (seasons) in the Rio Churince system, Cuatro Ciénegas, Mexico. At sites environmentally more similar to parental habitats, the genetic composition of hybrids was stable and similar to the resident parental species, whereas complex admixtures of parental and hybrid genotypic classes characterized intermediate environments, as did the greatest change in allelic and genotypic frequencies across seasons. Within hybrids across the entire Rio Churince system, seasonal changes in allelic and genotypic frequencies were consistent with results from previous reciprocal transplant experiments, which showed C. bifasciatus to suffer high mortality (75%) when exposed to the habitat of C. atrorus in winter (extreme temperature lows and variability) and summer (abrupt salinity change and extreme temperature lows and variability). Though unconfirmed, the distributional limits of C. atrorus and C. atrorus-like hybrids appear to be governed by similar constraints (predation or competition). A crucial link was also established between contemporary exogenous selection in a hybrid zone between these species and previous demonstration of long-term evolutionary significance of environmental variation and introgression on the phenotypic diversification Cuatro Ciénegas Cyprinodon.
Data from: Spatio-temporal variation in fitness responses to contrasting environments in Arabidopsis thaliana
The evolutionary response of organisms to global climate change is expected to be strongly conditioned by pre-existing standing genetic variation. In addition, natural selection imposed by global climate change on fitness-related traits can be heterogeneous over time. We estimated selection of life-history traits of an entire genetic lineage of the plant A. thaliana occurring in north-western Iberian Peninsula that were transplanted over multiple years into two environmentally contrasting field sites in southern Spain, as southern environments are expected to move progressively northwards with climate change in the Iberian Peninsula. The results indicated that natural selection on flowering time prevailed over that on recruitment. Selection favored early flowering in six of eight experiments and late flowering in the other two. Such heterogeneity of selection for flowering time might be a powerful mechanism for maintaining genetic diversity in the long run. We also found that north-western A. thaliana accessions from warmer environments exhibited higher fitness and higher phenotypic plasticity for flowering time in southern experimental facilities. Overall, our transplant experiments suggested that north-western Iberian A. thaliana has the means to cope with increasingly warmer environments in the region as predicted by trends in global climate change models.
Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks: dataset
<p>This repository contains the data accompanying the paper "<em>Learning the intrinsic dynamics of spatio-temporal processes through Latent Dynamics Networks</em>", by Francesco Regazzoni, Stefano Pagani, Matteo Salvador, Luca Dedè and Alfio Quarteroni.</p> <p>The associated codes are available in the repository <a href="https://github.com/FrancescoRegazzoni/LDNets">https://github.com/FrancescoRegazzoni/LDNets</a></p>
Field and Lab_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Field and Lab observations_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Meteorological data_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Depressions and Boundary_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Depressions and Boundary_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Aerial Images_Part 3_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Aerial Images_Part 3_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Orthomosaic_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>Orthomosaic of the aerial images_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
DSM_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria
<p>DSM_Integrating Remote Sensing and Machine Learning for Developing Spatio-Temporal Model to Predict Aquatic Larval Habitats of Malaria</p>
Code and Data for "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Frontiers in Marine Science.
<p>This repository contains the code and data for the study of "Global Surface Eddy Mixing Ellipses: Spatio-temporal Variability and Machine Learning Prediction" By Jing et al. Submitted to Frontiers in Marine Science.</p> <p>Specifically, this repository contains the following items: </p> <p>(1) The codes needed for assessing the representation and prediction skills of Random Forest (RF), Convolutional Neural Network (CNN) and Spatial Transformer Networks (STN) models. </p> <p>(2) Original and normalized data to run these codes.</p> <p>(3) Code here is built on early work from our laboratory (Jaderberg et al., 2015; Guan et al., 2022; Zhang et al., 2023), though great modifications have been made tailored to our scientific question.</p> <p>[1] Jaderberg, M., Simonyan, K., Zisserman, A., et al. (2015). Spatial transformer networks. Advances in neural information processing systems, 28.</p> <p>[2] Guan, W., Chen, R., Zhang, H., Yang, Y., & Wei, H. (2022). Seasonal surface eddy mixing in the Kuroshio Extension: Estimation and machine learning prediction. Journal of Geophysical Research: Oceans, 127 (3), e2021JC017967.</p> <div>[3] Zhang, G., Chen, R., Li, X., Li, L., Wei, H., & Guan, W. (2023). Temporal variability of global surface eddy diffusivities: Estimates and machine learning prediction. Journal of Physical Oceanography, 53 (7), 1711–1730.</div>
Within-lake variation in fish predation risk shapes the spatio-temporal structure of the zooplankton community
<p>Scripts and datasets to reproduce figures and analyses of the article.</p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.