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147 results for “Spatial Network”
Legacy effects of seed dispersal mechanisms shape the spatial interaction network of plant species in Mediterranean forests
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Unraveling the cavity-nesting network at large spatial scales: The biogeographic role of woodpeckers as ecosystem engineers
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Data for: Thermal vulnerability in a mountain stream network: Temporal, spatial, and biological data
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Spatial variation in early-winter snow cover determines local dynamics in a network of alpine butterfly populations
<p>Snow cover is an extremely variable but critical component of alpine environments. We use long term population data on multiple small populations of the alpine butterfly <i>Parnassius smintheus</i>, combined with high-resolution satellite imagery of meadows, to show a strong link between fine-scale spatial and temporal variation in early-winter snow cover and annual change in butterfly population size, accounting for up to 80 percent of the variation in annual population change. Snow cover in early winter for each meadow is the best predictor of annual adult population change, despite being estimated for a relatively short time-window in late November. We identify a means by which subpopulation response to a local, short-term weather variable can be assessed over a large spatial extent, but also at a resolution relevant to the biology and local dynamics of this alpine species.</p>
Data from: Finding the best management policy to eradicate invasive species from spatial ecological networks with simultaneous actions
1. Spatial management of invasive species is more likely to be successful when multiple locations are treated simultaneously. However, selecting the best locations to act is difficult due to the many options available at any time. 2. We design a near-optimal policy for applying multiple actions simultaneously for faster invasive species control within a network. Our method uses a recent optimisation tool, the Graph-based Markov decision process (GMDP). Since the policy can be difficult to interpret, we extracted a simpler policy using classification trees. We applied our approach to the eradication of invasive mosquitofish (Gambusia holbrooki) from the habitat of the red-finned blue-eye (Scaturiginichthys vermeilipinnis), a critically endangered fish with a global population that is restricted to seven artesian springs in Queensland, Australia. 3. The policy returned by the GMDP was to manage springs occupied by mosquitofish and their connected neighbours, unless the neighbours were occupied by red-finned blue-eyes. 4. Simultaneous management resulted in rapid declines in simulated mosquitofish occupancy even if eradication effectiveness was low; however the cost of simultaneous eradication was high and sustained eradication effort was necessary to maintain low mosquitofish occupancy. 5. Synthesis and applications. Our paper finds a near-optimal, multi-action control policy to remove an invasive species from a multi-species spatial network. We introduce the Graph-based Markov decision process (GMDP) and apply it to a real case study – eradication of invasive mosquitofish from the habitat of the red-finned blue-eye. We find that the GMDP can generate policies for networks with extremely large state spaces, however it works best when nodes have fewer than five neighbours. We conclude that simultaneous eradications are effective for rapid control of invasive species; however, managers should consider the cost and time required for an effective eradication program.
Data from: Interaction networks of macrofungi and mycophagous beetles reflect diurnal variation and the size and spatial arrangement of resources
Ecological networks are useful for characterizing interspecific associations and predicting the resilience of ecological communities. We evaluated how such networks vary with the size, spatial distribution, and timing of availability of resources, with a focus on beetle-macrofungal associations. We used 2 y of field experiments to construct ecological networks based on manipulated sporocarp baits (resources; Pleurotus ostreatus) and natural communities of beetles (consumers) in a temperate forest. Centrality and interaction strength increased with resource size, but were associated weakly with resource density and isolation, and not at all with position within patches. Whole-network connectance was greater in mornings (when beetle richness and abundance were high) than evenings. Interannual differences in networks were consistent with differences in beetle communities between years. The capacity of networks to vary temporally, spatially, and as a function of resource traits is examined in light of understanding beetle-macrofungal associations, which are important components of fungal ecology.
Data from: Invariant antagonistic network structure despite high spatial and temporal turnover of interactions
Recent work has suggested that emergent ecological network structure exhibits very little spatial or temporal variance despite changes in community composition. However, the changes in network interactions associated with turnover in community composition have seldom been assessed. Here we examine whether changes in ecological networks are best detected by standard emergent network metrics or by assessing internal network changes (i.e. interaction and composition turnover). To eliminate possible spatial or phylogenetic effects, that in large-scale studies may obscure mechanisms structuring networks and interactions, we sampled multiple antagonistic (plant-herbivore) networks for a single diverse plant family (the Restionaceae) in the hyperdiverse Cape Floristic Region. These are the first plant-herbivore networks constructed for this global biodiversity hotspot. We found invariant emergent network structure despite considerable changes in insect and plant composition across communities over time and space. In contrast, there was high interaction turnover between networks. Seasonally, this was driven by turnover in insect species and insect host switching. Spatially, this was driven by simultaneous turnover in plant and insect species, suggesting that many insects are host specific or that both groups exhibit parallel responses to environmental gradients. Spatial interaction turnover was also driven by turnover in plants, showing that many insects can utilise multiple (possibly closely related) hosts and this may create divergent selection gradients that promote insect speciation. Thus we show highly variable interaction fidelity, despite invariant emergent network structure. We suggest that evaluating internal network changes may be more effective at elucidating the processes structuring networks, and many fine-scale changes may be obscured when only calculating emergent network metrics.
Data from: Ecological divergence among colour morphs mediated by changes in spatial network structure associated with disturbance
1. Differences in individual behaviour affect social interactions and contribute to the spatial structuring of animal populations. However, disturbance should also affect spatial networks by altering habitat heterogeneity and resource availability. Variation in resource availability should perturb the frequency and nature of social and ecological interactions within a population by affecting the spatial distribution of individuals. 2. In disturbed habitats where resources are limiting, spatial relationships should reflect behavioural differences among individuals, with higher-quality resources controlled by dominant individuals. In contrast, all individuals may exploit preferred resources in resource-rich habitats. Environmental variation and population reorganisation may also result in variation in morphological, behavioural, and ecological traits, which ultimately affect fitness. 3. We addressed these considerations for male tree lizards (Urosaurus ornatus) at three sites that differ in levels of disturbance. The habitats at these localities differed in the availability of live trees, the preferred microhabitat of U. ornatus. In addition, male U. ornatus exhibit a polymorphism in dewlap colour linked with differences in aggression, which should influence their position in a network and access to resources. We applied a network framework to characterise the spatial organisation of male morphs at each site and quantified male aggressive behaviour in the laboratory. We also compared body size, body condition, number of bite marks, parasite load, and the microhabitat use and diet, of males among the sites. 4. We detected no significant differences in spatial network structure between unburned and infrequently burned sites. However, at a frequently-burned site, the network shifted towards geographically closer, heteromorphic male neighbour associations. Males at this site were also larger, more aggressive, and had more bite marks but fewer parasites than males at the other sites. Moreover, we detected divergence in microhabitat use and diet among the morphs at the frequently-burned site that reflected the shift in spatial network structure and differences in morph behaviour. That is, only more-aggressive morphs usurped trees and consumed prey from higher trophic levels. 5. We conclude that environmental variation may influence animal spatial network structure. Jointly, behavioural and environmental variation may promote despotic social dynamics and ecological divergence in resource-limited habitats.
Data from: Network-scale effects of invasive species on spatially-structured amphibian populations
<p>Understanding the factors affecting the dynamics of spatially-structured populations (SSP) is a central topic of conservation and landscape ecology. Invasive alien species are increasingly important drivers of the dynamics of native species. However, the impacts of invasives are often assessed at the patch scale, while their effects on SSP dynamics are rarely considered. We used long-term abundance data to test whether the impact of invasive crayfish on subpopulations can also affect the whole SSP dynamics, through their influence on source populations. From 2010 to 2018, we surveyed a network of 58 ponds and recorded the abundance of Italian agile frog clutches, the occurrence of an invasive crayfish, and environmental features. Using Bayesian hierarchical models, we assessed relationships between frog abundance in ponds and a) environmental features; b) connectivity within the SSP; c) occurrence of invasive species at both the patch- and the SSP-levels. If spatial relationships between ponds were overlooked, we did not detect effects of crayfish presence on frog abundance or trends. When we jointly considered habitat, subpopulation, and SSP features, processes acting at all these levels affected frog abundance. At the subpopulation scale, frog abundance in a year was related to habitat features, but was unrelated to crayfish occurrence at that site during the previous year. However, when we considered the SSP level, we found a strong negative relationship between frog abundance in a given site and crayfish frequency in surrounding wetlands during the previous year. Hence, SSP-level analyses can identify effects that would remain unnoticed when focussing on single patches. Invasive species can affect population dynamics even in not invaded patches, through the degradation of subpopulation networks. Patch-scale assessments of the impact of invasive species can thus be insufficient: predicting the long-term interplay between invasive and native populations requires landscape-level approaches accounting for the complexity of spatial interactions.</p>
Data from: The contribution of land tenure diversity to the spatial resilience of protected area networks
1. The relationship between diversity and resilience is relatively well-established for ecological systems, but remains much less explored for socioeconomic systems. Institutional diversity may have particular relevance for protected areas, whose managerial responses to environmental change depend on their legal basis, ability to make and enforce rules, and socio-political acceptance and endorsement. 2. Protected area expansion strategies are increasingly turning to private land conservation to increase the configuration and connectivity of national protected area networks. Yet we know little about the relative role of privately-owned protected areas in protecting threatened and poorly protected (under-represented) habitats, and in the overall connectivity of the national protected area network. 3. We present an empirical assessment of protected area tenure diversity across South Africa. 4. Privately-owned protected areas comprise 25.58% (2878422.26 ha) of the area of the total protected area estate. 5. Private nature reserves emerged as the dominant protected area type in under-represented and threatened habitats, protecting, on average, 32%, 38%, and 41%, respectively, of poorly protected, threatened and endangered vegetation classes. 6. Private nature reserves had the largest overall effect, compared to other protected area types, on connectivity within the national network. A spatially randomised comparison showed that privately-owned protected areas are over-dispersed and more strategically positioned to connect other types of protected areas than would be expected by chance from their extent and abundance. 7. Our results suggest that privately-owned protected areas enhance the resilience of the national protected area network, making it more extensive and better-connected, with greater levels of habitat redundancy. More generally, our analysis highlights the potentially valuable role of institutional diversity in building resilient habitat networks for biodiversity conservation.
Pappulab/N130-Liquid-Structure: Biomolecular condensates form spatially inhomogeneous network fluids
<p>This repository contains the data for the Nature Communications manuscript, "Biomolecular condensates form spatially inhomogeneous network fluids" by F. Dar†, S. R. Cohen†, D. M. Mitrea, A. H. Phillips, G. Nagy, W. C. Leite, C. B. Stanley, J-M. Choi†,§, R. W. Kriwacki§, R. V. Pappu§. (†Equal contributors; §Co-corresponding authors). (2024). <a href="https://doi.org/10.1038/s41467-024-47602-z" target="_blank" rel="noopener">https://doi.org/10.1038/s41467-024-47602-z</a></p> <p>For accompanying analysis scripts, please consult: <a href="https://github.com/Pappulab/n130-liquid-structure" target="_blank" rel="noopener">https://github.com/Pappulab/n130-liquid-structure</a>.</p>
Imbalanced regressive neural network model for whistler-mode hiss waves: spatial and temporal evolution
<p>This dataset contains the whistler-mode hiss waves obtained from the Van Allen Probes. It is accompanied by the manuscript "<span>Imbalanced regressive neural network model for whistler-mode hiss waves: spatial and temporal evolution". </span></p>
The topology of spatial networks affects stability in experimental metacommunities
<p><span>Understanding the drivers of community stability has been a central goal in ecology. Traditionally the emphasis has been placed on studying the effects of biotic interactions on community variability, and less is understood about how the spatial configuration of habitats promotes or hinders metacommunity stability. To test the effects of contrasting spatial configurations on metacommunity stability, I designed metacommunities with patches connected as random or scale-free networks. In these microcosms, two prey and one protist predator dispersed, and I evaluated community persistence, tracked biomass variations, and measured synchrony between local communities and their neighbors. After 30 generations, scale-free metacommunities had lower global biomass variability and higher persistence, suggesting higher stability. At the local scale, patches in scale-free metacommunities showed a positive relationship between variability and patch connectivity, indicating higher stability in isolated communities. No clear relationship was observed in random networks. These results suggest the increased heterogeneity in connectivity of scale-free networks favors the prevalence of isolated patches in the metacommunity, which likely act as refugia against competition—the most dominant interaction in this system—resulting in higher global stability. These results highlight the importance of accounting for network topology in the study of spatial dynamics.</span></p>
Multiplexed protein profiling reveals spatial subcellular signaling networks
<ul> <li>Supplementary videos for "<strong>Multiplexed protein profiling reveals spatial subcellular signaling networks</strong>"</li> <li>The videos were made using Volocity 3D visualization software. </li> </ul>
Quantifying the spatial homogeneity of urban road networks via graph neural networks
<p>Publication: Quantifying the spatial homogeneity of urban road networks via graph neural networks, Nature Machine Intelligence, 2022.</p> <p>Publication DOI: 10.1038/s42256-022-00462-y</p> <p>Please refer to https://github.com/jiang719/road-network-predictability.</p>
Data from: Evaluating otter reintroduction outcomes using genetic spatial capture-recapture modified for dendritic networks
<p>River otters (Lontra canadensis) were extirpated from New Mexico by the 1950s. A limited reintroduction occurred during 2008–2010 in which 33 otters sourced from Washington (WA) were translocated to the Upper Rio Grande Basin (URG) of New Mexico. We conducted a noninvasive genetic capture-recapture survey during the winter of 2018 by collecting fecal DNA samples from river otter scats found at latrines in the URG dendritic network of perennial waterways. Our objectives were to: 1) estimate genetic diversity and effective population size; 2) genetic divergence from the WA source population and potential connectivity with regionally proximal populations; 3) spatially explicit population density and size; and 4) population growth rate since the founder event. Between February and April 2018, we collected 1,184 fecal DNA samples from 622 individual scats at 20 latrines; genotyping was attempted at 10 otter-specific microsatellite loci for a subsample of 543 samples. A bottlenecking founder effect was strongly supported, which, combined with genetic drift, reduced genetic diversity and effective population size by 20–26% and 106–170%, respectively, compared with the WA source population. Estimated population density from spatial capture-recapture models was 0.23–0.28 otter/km of waterway, or 1 otter/3.57–4.35 km of waterway, corresponding to a total population size of 83–100 otters across 359 km of the perennial dendritic network from La Mesilla, New Mexico to Alamosa National Wildlife Refuge, Colorado. Estimated average annual population growth rate since the founder event was 1.12–1.15/year. Despite successful population establishment, the URG river otter population remains small, is genetically degraded, and does not yet meet the criteria for long-term reintroduction success. Projections suggested that the population could reach the recommended minimum viable population size of ≥400 otters by the years 2030–2033, though sufficient habitat may not exist in the URG Basin to support that many otters. </p>
Knowledge Graph Neural Network with Spatial-Aware Capsule for Drug-Drug Interaction Prediction
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F I G U R E 6 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 6 Euclidean distances moved by Tetrahymena individuals depending on densities in our entire dataset. Across all replicates of all landscapes (patches from different landscapes types highlighted by different symbols; see legend) we find positively densitydependent movement. The solid lines represent fits of the averaged linear mixed model (red: dendritic landscapes; blue: linear landscapes) and the shaded area shows 95% confidence intervals (see Table 4 for model selection results). [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 4 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 4 Comparison of variation in population densities between linear and dendritic networks at day 15 of the experiment. The solid line represents the difference between inter-quartile range (IQR) over median population densities of linear and dendritic landscapes. The distribution (grey) represents the distribution of the differences between IQR over median population densities of 200,000 random re-samplings for our data. As we theoretically expect the dendritic landscapes to be more variable we can perform a one-sided test which gives a probability of p =.047 of our observed difference between IQR to median ratios to be larger than zero. [Colour figure can be viewed at wileyonlinelibrary.com]
F I G U R E 3 in Dispersal in dendritic networks: Ecological consequences on the spatial distribution of population densities
F I G U R E 3 Fit of theoretical expectations to the distribution of Tetrahymena population densities depending on network type (linear versus dendritic networks), network position (central versus inner versus outer nodes) for day 15. Violin plots show the overall distribution of the data, the white point gives the median, and the solid black line the 25% and 75% percentiles, respectively. Given the network structure (Figure 1) and the three replicates per landscape, distributions include N = 18 (9, 3) measurements for outer (inner, central) nodes of dendritic networks and N = 6 (6, 18) measurements for outer (inner, central) nodes of linear landscapes. Horizontal red and blue lines visualise fits of the theoretically expected distribution of population densities to data from the dendritic and linear networks assuming network specific dispersal rates (d) and carrying capacities (K). White squares show fits of the theoretically expected distribution of population densities assuming the same d and K values for both network types. Shaded areas, respectively, error bars, show 95% confidence intervals of the fits. [Colour figure can be viewed at wileyonlinelibrary.com]
ScienceDex guides
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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.