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364 results for “Network interaction”
Unveiling the genetic networks: Exploring the dynamic interaction of photosynthetic phenotypes in woody plants across varied light gradients
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Plant interaction networks reveal the limits of our understanding of diversity maintenance
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Non-trophic interactions amplify kelp harvest-induced biomass oscillations and biomass changes in a kelp forest ecological network model
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Data from: Abundant top predators increase species interaction network complexity in Northeastern Chinese forests
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Stable species and interactions in plant-pollinator networks deviate from core position in fragmented habitats
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Interactions outside local patches contribute to the compound topology of plant-pollinator networks in fragmented dune slacks
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Data from: A meta-analysis of plant interaction networks reveals competitive hierarchies as well as facilitation and intransitivity
The extent to which competitive interactions and niche differentiation structure communities has been highly controversial. To quantify evidence for key features of plant community structure, I recharacterized published data from interaction experiments as networks of competitive and facilitative interactions. I measured the network structure of 31 woody and herbaceous communities, including the intensity, distribution, and diversity of interactions at the species-pair and community level to determine the generality of competition, winner-loser relationships, and unequal interaction allocation. I developed novel methodology using meta-analysis to incorporate interaction uncertainty into estimates of structural metrics among independent networks. Plant communities were competitive, but intraspecific interactions were sometimes more intense than interspecific interactions. On the whole, interactions were imbalanced and communities were transitive. However, facilitation, balanced interactions, and intransitivity were common in individual communities. Synthesizing network metrics using meta-analysis is an original approach with which to generalize community structure in a systematic way.
Data from: Seed-dispersal networks in tropical forest fragments: area effects, remnant species, and interaction diversity
<p>Seed dispersal interactions involve key ecological processes in tropical forests that help to maintain ecosystem functioning. Yet this functionality may be threatened by increasing habitat loss, defaunation and fragmentation. However, generalist species, and their interactions, can benefit from the habitat change caused by human disturbance while more specialized interactions mostly disappear. Therefore changes in the structure of the local, within fragment, networks can be expected. Here we investigated how the structure of seed-dispersal networks changes along a gradient of increasing habitat fragmentation. We analysed 16 bird seed-dispersal assemblages from forest fragments of a biodiversity-rich ecosystem. We found significant species-, interaction- and network-area relationships, yet the later was determined by the number of species remaining in each community. The number of frugivorous bird and plant species, their interactions, and the number of links per species decreases as area is lost in the fragmented landscape. In contrast, network nestedness has a negative relationship with fragment area, suggesting an increasing generalization of the network structure in the gradient of fragmentation. Network specialization was not significantly affected by area, indicating that some network properties may be invariant to disturbance. Still, the local extinction of partner species, paralleled by a loss of interactions and specialist-specialist bird-plant seed dispersal associations suggests the functional homogenization of the system as area is lost. Our study provides empirical evidence for network-area relationships driven by the presence/absence of remnant species and the interactions they perform.</p>
Data from: Genetics-based interactions of foundation species affect community diversity, stability, and network structure
We examined the hypothesis that genetics-based interactions between strongly interacting foundation species, the tree Populus angustifolia and the aphid Pemphigus betae, affect arthropod community diversity, stability and species interaction networks of which little is known. In a 2-year experimental manipulation of the tree and its aphid herbivore four major findings emerged: (i) the interactions of these two species determined the composition of an arthropod community of 139 species; (ii) both tree genotype and aphid presence significantly predicted community diversity; (iii) the presence of aphids on genetically susceptible trees increased the stability of arthropod communities across years; and (iv) the experimental removal of aphids affected community network structure (network degree, modularity and tree genotype contribution to modularity). These findings demonstrate that the interactions of foundation species are genetically based, which in turn significantly contributes to community diversity, stability and species interaction networks. These experiments provide an important step in understanding the evolution of Darwin's 'entangled bank', a metaphor that characterizes the complexity and interconnectedness of communities in the wild.
Data from: Interaction rewiring and the rapid turnover of plant-pollinator networks
Whether species interactions are static or change over time has wide-reaching ecological and evolutionary consequences. However, species interaction networks are typically constructed from temporally aggregated interaction data, thereby implicitly assuming that interactions are fixed. This approach has advanced our understanding of communities, but it obscures the timescale at which interactions form (or dissolve) and the drivers and consequences of such dynamics. We address this knowledge gap by quantifying the within-season turnover of plant–pollinator interactions from weekly censuses across 3 years in a subalpine ecosystem. Week-to-week turnover of interactions (1) was high, (2) followed a consistent seasonal progression in all years of study and (3) was dominated by interaction rewiring (the reassembly of interactions among species). Simulation models revealed that species' phenologies and relative abundances constrained both total interaction turnover and rewiring. Our findings reveal the diversity of species interactions that may be missed when the temporal dynamics of networks are ignored.
Ecological mechanisms explaining interactions within plant-hummingbird networks: morphological matching increases towards lower latitudes
<p><a name="ab4">Interactions between species are influenced by different ecological mechanisms, such as morphological matching, phenological overlap, and species abundances</a>. <a name="Ab1"></a><a name="ab5">How</a> these mechanisms explain interaction frequencies across environmental gradients remains poorly understood. Consequently, we also know little about the mechanisms that drive the geographical patterns in network structure, such as complementary specialization and modularity. Here, we use data on morphologies, phenologies and abundances to explain interaction frequencies between hummingbirds and plants at a large geographic scale. <a name="ab2">For 24 quantitative networks sampled throughout the Americas, we found that</a> the tendency of species to interact with morphologically matching partners contributed to specialized and modular network structures. Morphological matching best explained interaction frequencies in networks found closer to the equator and in areas with low temperature seasonality. When comparing the three ecological mechanisms within networks, we found that both morphological matching and phenological overlap generally outperformed abundances in the explanation of interaction frequencies. Together, these findings provide insights into the ecological mechanisms that underlie geographical patterns in resource specialization. Notably, our results highlight morphological constraints on interactions as a potential explanation for increasing resource specialization towards lower latitudes.</p>
Bat-flower interaction networks in Caatinga reveal generalized associations and temporal stability
<p>Seasonal variation in precipitation regimes influences species composition and plant-animal interactions. Such temporal variation is especially relevant in the Brazilian Caatinga, the largest Seasonally Dry Tropical Forest in South America, where bat pollination is unusually frequent in comparison with other tropical plant communities. Here, we describe seasonal and annual variations of the interaction networks between nectarivorous bats and flower species in the Caatinga. Five species of nectar-feeding bats interacted with 30 plant species. Nectarivorous bats showed high levels of interaction overlap, which contributed to ecological generalization (low specialization and modularity) and lack of nestedness in the interaction networks. This pattern was consistent across seasons and years. Chiropterophilous and non-chiropterophilous plants were equally important components of the interaction network. The generalized interaction patterns found may be a necessary condition for the persistence of nectarivorous bats and their specialized plants in the environmentally harsh and variable Caatinga. The underappreciated generalized interactions of bats with plants calls for studies testing the effectiveness of bats in pollinating the plants they visit, including those not typically categorized as "bat-flowers".</p>
Interactive Tagging Networks (Following/Followers and Tags on 1 million Twitter Users)
<p><strong>Abstract</strong> (our paper)</p> <p>How do users behave if they can tag each other in social networks? In this paper, we answer this question by studying the interactive tagging network constructed by Twitter lists. Twitter lists can be regarded as the tagging process; a user (i.e., tagger) creates a list with a name (i.e., tag) and adds other users (i.e., tagged users) into the list. This tagging network is by nature different from the resource tagging networks (e.g., Flickr and Delicious) because users on this network can tag each other. We address the following research questions: (RQ1) What is the common patterns and the difference between the interactive tagging network and the resource tagging networks? (RQ2) Do users tag each other on the interactive tagging network? And if so, to what extent? (RQ3) What is the difference between the two types of relationships on Twitter: who-tags-whom and who-follows-whom? By quantitatively studying million-scale networks, we found the pervasive patterns across the different tagging networks, and the interactive patterns within the interactive tagging network. This study sheds light on the underlying characteristics of the interactive tagging network, which is relevant to the social scientists and the system designers of the tagging systems.</p> <p><strong>Data</strong></p> <p>twitter.seed.users:<br> The first column is the user id, and the second column is the json of the user objects on Twitter. This is the set of 1 million seed users to collect the following data.</p> <p>twitter.tagging.network:<br> The first column is the source user id (from user id), the second column is the destination user id (to user id), the third column is the tag (<em>i.e.</em> slug or list name), and the fourth column is the list id.</p> <p>twitter.tagging-out-going-from-seed-users.network:<br> The first column is the source user id (from user id), the second column is the destination user id (to user id), the third column is the tag (<em>i.e.</em> slug or list name), and the fourth column is the list id. This is only the out-going edges from the seed users, <em>i.e.</em>, this is a subset of twitter.tagging.network.</p> <p>twitter.following.network:<br> The first column is the source user id (from user id), and the second column is the destination user id (to user id).</p> <p>twitter.following-closed-seed-users.network:<br> The first column is the source user id (from user id), and the second column is the destination user id (to user id). This is not used in the following publication paper, but will be useful in other studies.</p> <p><strong>Publication</strong></p> <p>This data set was created for our study. If you make use of this data set, please cite:<br> Yuto Yamaguchi, Mitsuo Yoshida, Christos Faloutsos, Hiroyuki Kitagawa. Patterns in Interactive Tagging Networks. <em>Proceedings of the Ninth International AAAI Conference on Web and Social Media (ICWSM-15)</em>. pp.513-522, 2015.<br> http://www.aaai.org/ocs/index.php/ICWSM/ICWSM15/paper/view/10556</p> <p><strong>Code</strong></p> <p>Our code outputting experiment results made available at:<br> https://github.com/yamaguchiyuto/icwsm15</p>
Interactive Citation Networks for Texas Archaeology
<p>This dataset includes the JavaScript used to generate two interactive citation networks. IntNetFig1 includes the network filtered by the giant component and nodes sized by OutDegree, and IntNetFig2 is the same network filtered by a degree of two, nodes sized by Eigenvector Centrality and colored by modularity class.</p>
Optimal mechanical interactions direct multicellular network formation on elastic substrates
<p>Cells self-organize into functional, ordered structures during tissue morphogenesis, a process that is evocative of colloidal self-assembly into engineered soft materials. Understanding how intercellular mechanical interactions may drive the formation of ordered and functional multicellular structures is important in developmental biology and tissue engineering. Here, by combining an agent-based model for contractile cells on elastic substrates with endothelial cell culture experiments, we show that substrate deformation–mediated mechanical interactions between cells can cluster and align them into branched networks. Motivated by the structure and function of vasculogenic networks, we predict how measures of network connectivity like percolation probability and fractal dimension as well as local morphological features including junctions, branches, and rings depend on cell contractility and density and on substrate elastic properties including stiffness and compressibility. We predict and confirm with experiments that cell network formation is substrate stiffness dependent, being optimal at intermediate stiffness. We also show the agreement between experimental data and predicted cell cluster types by mapping a combined phase diagram in cell density substrate stiffness. Overall, we show that long-range, mechanical interactions provide an optimal and general strategy for multicellular self-organization, leading to more robust and efficient realizations of space-spanning networks than through just local intercellular interactions.</p>
HDAC6 protein-protein interaction network in CNS
<p>HDAC6 stands out as a distinctive member within the histone deacetylase family due to its predominant presence in the cytosol, facilitating its interaction with a wide array of non-histone proteins. Its dysregulation has been linked to various outcomes, encompassing diverse cancer types, immune-related disorders, and neurological conditions, including Alzheimer's, Parkinson's, ALS, Huntington's, Charcot-Marie-Tooth disease, and Rett syndrome.</p><p>The current network represents the known HDAC6 interactions in the central nervous system (CNS).</p><p>The latest version of the current network is available in WikiPathways under accession number WP5426.</p>
Patterns of liana diversity and host interaction networks in selectively-logged and unlogged forests of Uppangala, Western Ghats, India
<p>Lianas shape tropical forest species composition, structure, and dynamics. Increasing climate fluctuation and anthropogenic disturbances increase liana abundance. Despite the increasing number of liana studies in India, only a few have examined the distribution and association of hosts with lianas, or liana-host interaction networks to determine their functional significance and conservational value. Therefore, our objective was to fill the knowledge gap about the diversity, abundance, and network structure of liana-host interactions in response to logging disturbance in a wet evergreen forest of Uppangala in central Western Ghats, India. We sampled lianas ≥1 cm in diameter at 1.3 m from the base and their host trees in thirty 20m x 20m plots in selectively-logged and unlogged forest management regimes. We evaluated liana-host tree interactions in logged and unlogged forests and retrieved community-level measures (nestedness, connectance, modularity, and network specialization index) and species-level indicators (species specialization index). Diversity and abundance of liana species were considerably greater in the selectively logged forest site. The logged forest site had compartmentalization, anti-nestedness, and network specialization, while unlogged forests were not showing any significant network structure. Most species of lianas and hosts were peripherals, but others were structurally important (connectors, module hubs, and network hubs) in the two forest sites. Forest management regimes had distinct structurally significant species.</p>
Understanding trophic interactions in a warming world by bridging foraging ecology and biomechanics with network science
<p><strong><em><span>Background</span></em></strong></p> <p><span>Leaf-cutter ants (<em>Atta</em> spp. and <em>Acromyrmex </em>spp.) are the principal insect pest and a major ecosystem engineer throughout the Neotropics (Leal et al., 2014; Wirth et al., 2003). They harvest plant matter in the surroundings of their colonies to grow a fungus as crop, and in doing so they cut plant matter on an almost industrial scale: about 15 % of the foliar biomass in the Neotropics, or about every sixth leaf, is consumed by leaf-cutter ant colonies (Costa et al., 2008; Fowler et al., 1989; Herz et al., 2007; Wirth et al., 2003), and more than half of all woody species are attacked by them (Cherrett, 1968; Rockwood, 1976). Leaf-cutter ants are perhaps the most voracious and polyphagous herbivorous insects (Lugo et al., 1973; Wirth et al., 2003), and their foraging activity is affected by a variety of environmental conditions, including wind (Alma et al., 2016b), precipitation (Steadman et al., 2020) and barometric pressure (Sujimoto et al., 2020), all of which will be subject to variation due to climate change. </span></p> <p><span>Although leaf-cutter foraging is clearly a complex, multi-factorial behaviour, it has at its core a biomechanical interaction between ant consumer and plant food resource: the force the ants can apply must exceed the force required to drag the mandible through the tissue (Püffel, Roces, et al., 2023; Püffel, Walthaus, et al., 2023). The magnitude of the available bite force is determined by worker size, and the magnitude of the minimum required cutting force is determined by structural and mechanical properties of the plant leaf; consumer and resource properties interact. This mechanical competition has resulted in extraordinary adaptations in both the anatomy and physiology of the leaf-cutter ant bite apparatus: their disproportionately large heads are filled to the rim with optimally packed mandible closer muscles (Püffel et al., 2021). Both their muscle stress and size-specific bite forces are among the highest measured for any animal (Püffel, Johnston, et al., 2023; Püffel, Roces, et al., 2023), and their mandibles are close to “ideally sharp” (Püffel, Walthaus, et al., 2023). As a result, the vast majority of worker sizes can cut the majority of tropical leafs; without these adaptations, and a bite performance commensurate with their body size, only the largest workers would be able to perform this crucial mechanical task (Püffel, Roces, et al., 2023). How will a warming climate affect resource accessibility for the leaf-cutters?</span></p> <p><span>Temperature increases have various implications for the trophic interactions of ants, including altered search behaviour <span>(Frizzi, 2018),</span> and foraging site selection (Spicer et al., 2017; Traniello et al., 1984). An increase in average temperatures can also drive body size decreases in insects (Tseng et al., 2018), including ants (Molet et al., 2017)<a href="https://www.zotero.org/google-docs/?broken=QmLD4C"><span>,</span></a> concomitantly reducing their available bite force (Püffel, Roces, et al., 2023; Rühr et al., 2022). Since leaf-cutter mandibles are so sharp that they already cut with a force close to the minimum dictated by cutting mechanics, the force required to cut leaves will likely be unaffected (Püffel, Walthaus, et al., 2023), and any change in body size will therefore only significantly impact bite forces. Because the relationship between bite forces and body size in the leaf-cutter is well understood mechanistically (Püffel, Roces, et al., 2023), it is possible to predict how these changes will impact trophic networks. A very rough estimate of the change in network structure serves to illustrate how network science can integrate biomechanics and foraging ecology to study the effect of climate change on trophic interactions. </span></p> <p><span>To demonstrate the potential of network science to integrate biomechanical and foraging data within the context of climate change, we constructed and analysed hypothetical plant-ant networks across six hypothetical temperatures. </span></p> <p> </p> <p><strong><em><span>Datasets and methods</span></em></strong></p> <p><span>All analysis was performed in R version 4.3.1 (R Core Team, 2023), and data processed reproducibly via the ‘tidyverse’ package (Wickham et al., 2019). We compiled two datasets and some additional contextual information. Leaf-cutter ant biomass (a proxy for body size) and bite force data were taken from <span>Püffel et al. (2023)</span> for 248 individual ants across three colonies. Required cutting forces for 1197 individual plants representing 868 taxa available to leaf-cutter ants were taken from <span>Onoda et al. (2011)</span>. Insect temperature-body size relationships were taken from <span>Tseng et al. (2018)</span>; specifically, a body size decrease of 1.56 % per degree Celsius increase for museum specimens, to represent gradual long-term change. Based on these data, edgelists (i.e., pairwise lists of consumers and resources) were generated for ants and plants in which binary interaction weights were applied; where bite forces exceeded the force required to cut leaves, a weighting of 1 was given, and 0 otherwise. This edgelist was then replicated for incremental increases of 1 °C up to a 5 °C increase by adjusting bite forces based on incremental body size decreases of 1.56 %. In order to estimate the change of bite force with body mass, we used direct bite force measurements from Püffel et al. (2023), which suggest that maximum bite force in <em>Atta vollenweideri</em> varies with body mass <em>m</em> as <em>T ~ m^0.9</em>. Thus, if body size decreases by a factor of 0.9844 (i.e., 1.56 % decrease) with every degree Celsius temperature increase, then the maximum bite force decreases by a factor of 0.9844<em><sup>0.9</sup></em>. Consequently, adjusted bite forces were calculated, and new binary edgelist weightings generated based on whether the adjusted bite force was greater than the required cutting force.</span></p> <p><span>Bipartite networks were constructed with consumer nodes and resource nodes representing the three ant colonies and the 868 plant taxa, respectively. All six networks were visualised using ‘ggnetwork’ (Briatte, 2021) via ‘igraph’ (Csardi & Nepusz, 2006) in a single network diagram to highlight persistence of links across temperatures using scaled red colours. Network metrics, specifically consumer degree (the number of plants ants were deemed able to interact with) and generality (the total range of plants accessible across all ants), were generated via the ‘bipartite’ package (Dormann et al., 2008) and visually compared via ‘ggplot2’ (Wickham, 2016).</span></p>
Mechanistic interactions as the origin of modularity in biological networks
<p>Biological networks are often modular. Explanations for this peculiarity either assume an adaptive advantage of a modular design such as higher robustness, or attribute it to neutral factors such as constraints underlying network assembly. Interestingly, most insights on the origin of modularity stem from models in which interactions are either determined by highly simplistic mechanisms or have no mechanistic basis at all. Yet, empirical knowledge suggests that biological interactions are often mediated by complex structural or behavioural traits. Here, we investigate the origins of modularity using a model in which interactions are determined by potentially complex traits. Specifically, we model system elements - such as the species in an ecosystem - as finite-state machines (FSMs) and determine their interactions by means of communication between the corresponding FSMs. Using this model, we show that modularity likely emerges for free. We further find that the more modular an interaction network is, the less complex are the traits that mediate the interactions. Altogether, our results suggest that the conditions for modularity to evolve may be much broader than previously thought.</p>
Wildfire severity alters drivers of interaction beta-diversity in plant-bee networks
Spatial variation in species interactions (interaction β-diversity) and its ecological drivers are poorly understood, despite their relevance to community assembly, conservation, and ecosystem functioning. We investigated effects of wildfire severity on patterns and four proximate ecological drivers of interaction β-diversity in plant-bee communities across three localities in the Northern Rocky Mountains (Montana, USA). Wildfires decreased interaction β-diversity but increased interaction frequency (number of visits) and richness (number of links). After controlling for interaction frequency and richness, standardized effect sizes of interaction β-diversity were highest following mixed-severity wildfires, intermediate following high-severity wildfires, and lowest in unburned landscapes, suggesting that wildfire increases spatial aggregation of plant-bee interactions. Moreover, higher effect sizes in burned landscapes were largely determined by turnover in the species composition of both trophic levels rather than by interaction rewiring (spatial turnover in local species interactions not due to species turnover). The underrepresented level of rewiring indicated spatial consistency in post-disturbance patterns of interactions among co-occurring species. Together, our findings suggest that wildfire alters the β-diversity of mutualistic species interactions via linked assembly of plant-bee communities and provide insights into how environmental change alters complex networks of species interactions.
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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.