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88 results for “Community: disturbance”
Plant Community and Ecosystem Responses to Long-term Fertilization & Disturbance at the Kellogg Biological Station, Hickory Corners, MI (1989 to 2019)
Dataset AbstractThis work is part of the long-term sampling and monitoring of successional dynamics in abandoned fields – and responses to N-fertilization. Data from this research has been, and will continue to, contribute to LTER cross-site analysis of plant community dynamics, diversity-productivity, and responses to fertilization and disturbance.N-fertilized and tilled (disturbed) microplots are located in the NW corner of all treatment 7 (early successional communities) on the LTER main site. Experimental treatments are: 1) Nitrogen addition vs. no nitrogen addition and 2) Annual disturbance vs. undisturbedoriginal data source http://lter.kbs.msu.edu/datasets/60
Benthic community response to different disturbance type events across six islands between two timepoints in the Central Pacific
A coral reef's response to disturbance can be driven by various factors including community composition. This dataset highlights benthic cover and its changes between two timepoints at six islands across the central Pacific. The survey islands include Ant Atoll, Pakin Atoll, and Pohnpei located within the Federated States of Micronesia (FSM) as well as Upon and Savai'i in Samoa and Rarotonga in the Cook Islands. Survey years differed between sites but all sites had an estimated two-year time-difference between resampling. To extract benthic cover, photos were annotated using randomized points and labeled to their highest taxonomic resolution, down to genus-level for hard corals. Both abiotic and biotic substrate were identified and major functional groups included: hard corals, soft corals, invertebrates, turf algae, Halimeda spp., crustose coralline algae, and other (sand/debris/etc.). Disturbance type and community composition at the initial survey period drove changes in percent cover for major functional groups. Data was collected by annotating photos from transect surveys on a coral reef. This effort was completed by the 2020 SIO 'Pop-up' SURF REU that was formed in rapid response due to COVID-19 research limitations.
Disturbance and recovery of salt marsh arthropod communities in Louisiana and Mississippi following the 2010 BP Deepwater Horizon oil spill in the Gulf of Mexico
Oil spills represent a major environmental threat to coastal wetlands, which provide a variety of critical ecosystem services to humanity. The U.S. Gulf of Mexico is a hub of oil and gas exploration and production with recognized consequences on intertidal habitats, such as the salt marsh. Following the BP Deepwater Horizon oil spill, we sampled the marine invertebrate and the terrestrial arthropod community found in stands of Spartina alterniflora, the most abundant plant in coastal salt marshes, in 2010 as oil was washing ashore and a year later in 2011. In 2010, intertidal crabs and terrestrial arthropods (insects and spiders) were suppressed by oil exposure even in seemingly unaffected stands of plants; however, Littoraria snails appeared unaffected. One year later, crab and arthropods appeared to have largely recovered. Our work is the first attempt that we know of assessing vulnerability of the salt marsh arthropod community to oil exposure, and it suggests that arthropods are both quite vulnerable to oil exposure, and quite resilient, able to recover from exposure within a year if host plants remain healthy. BP's Deepwater Horizon spill in the Gulf Coast presented an opportunity to understand how stress from an oil spill might affect variables that we were measuring in the area. The study was conducted at sites in Louisiana and Mississippi. At each site, a 100m transect was sampled within 5m of the dead zone boundary. Sampling was conducted in August 2010 and August 2011. The number of sites and location of sites differed slightly among years.
Digital repository for: Large-scale forest disturbance and associated management shape bird communities in Central European spruce forests
<p>Repository containing R-script and data to reproduce analysis and main figures on the effect of large-scale forest disturbance and associated pre- and post-disturbance management on bird communities in the Harz Mountains, Germany.</p> <p>R-script includes:</p> <ul> <li>indicator species analysis (R package indicspecies; Cáceres & Legendre, 2009)</li> <li>non-metric multidimensional scaling (R package vegan; Oksanen et al., 2016)</li> <li>rarefaction- and extrapolation of Hill numbers (R package iNEXT; Hsieh et al., 2019)</li> <li>multi-species community distance sampling (R package sp Abundance; Doser et al., 2023)</li> </ul> <p>Attached files:</p> <ul> <li><strong>bird_data_Graser_et_al.csv </strong>(row data of bird species point counts per distance category)</li> <li><strong>bird_data_abundance_100_Graser_et_al.csv </strong>(abundance of species per sampling site, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>siteCovs_Graser_et_al.csv</strong> (environmental variables for each sampling point)</li> <li><strong>A_species_matrix_100_new_Graser_et_al.csv</strong> (species-site matrix of <strong>bark-beetle disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>B_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>windthrow disturbance, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>C_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle/windthrow disturbance, underplanted, unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>D_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, salvage-unlogged </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>E_species_matrix_100_new_Graser_et_al.csv </strong>(species-site matrix of <strong>bark-beetle /windthrow disturbance, underplanted, salvage-unlogged </strong>sites for rarefaction and extrapolation, summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong> F_species_matrix_100_new_Graser_et_al.cs</strong>v (species-site matrix of <strong>mature spruce plantation </strong>sites for rarefaction and extrapolation, species number summed up over all four sampling repeats only considering detected individuals up to 100 m around the sampling point)</li> <li><strong>msHDS_bird_data_management_model_Graser_et_al.rds</strong> (R-data set for multi-species community distance sampling of the effect of different pre- and post-disturbance management groups)</li> <li><strong>msHDS_bird_data_stand_age_model_Graser_et_al.rds </strong>(R-data set for multi-species community distance sampling of the effect of post-disturbance forest succession)</li> </ul> <p>A more detailed description of the data can be found in the README.txt document.</p> <p><span>References:</span></p> <p><span>Cáceres, M. D., & Legendre, P. (2009). </span><span>Associations between species and groups of sites: Indices and statistical inference. <em>Ecology</em>, <em>90</em>(12), 3566–3574. https://doi.org/10.1890/08-1823.1</span></p> <p><span>Doser, J. W., Finley, A. O., Kéry, M., & Zipkin, E. F. (2023). spAbundance: An R package for single‐species and multi‐species spatially explicit abundance models. <em>Methods in Ecology and Evolution</em>, <em>15</em>(6), 1024–1033. https://doi.org/10.1111/2041-210X.14332</span></p> <p><span>Hsieh, T. C., Ma, K. H., & Chao, A. (2019). <em>iNEXT-package: Interpolation and extrapolation for species diversity</em>. https://cran.r-project.org/web/packages/iNEXT/vignettes/Introduction.html</span></p> <p><span>Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., O’hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., Wagner, H., Minchin, P. R., Gavin, L., & Henry, H. (2016). Vegan: Community ecology package. R package version 1.17-4. <em>Http://CRAN. R-Project. </em></span><em><span>Org/Package=vegan</span></em><span>.</span></p> <p></p> <p></p>
Food web rewiring drives long-term compositional differences and late-disturbance interactions at the community level
<p><strong>Abstract</strong></p> <p>Ecological communities are constantly exposed to multiple natural and anthropogenic disturbances. Multivariate composition (if recovered) has been found to need significantly more time to be regained after pulsed disturbance compared to univariate diversity metrics and functional endpoints. However, the mechanisms driving the different recovery times of communities to single and multiple disturbances remain unexplored. Here, we apply for the first time quantitative ecological network analyses to try to elucidate the mechanisms driving long-term community composition dissimilarity and late-stage disturbance interactions at the community level. For this, we evaluate the effects of two pesticides, nutrients enrichment and their interactions in outdoor mesocosms containing a complex freshwater community. We found changes in interactions strength to be strongly related to compositional changes and identified post-disturbance interaction strength rewiring to be responsible for most of the observed compositional changes. Additionally, we found pesticides interactions to be significant in the long term only when both interactions strength and food web architecture are reshaped by the disturbances. We suggest that quantitative network analysis has the potential to unveil ecological processes that prevent long-term community recovery.</p> <p><strong>Significance Statement</strong></p> <p>Multiple anthropogenic disturbances affect the structure and functioning of communities. Recent evidence highlighted that, after pulse disturbance, the functioning a community performs may be recovered fast due to functional redundancy, whereas community multivariate composition needs longer time. Yet, the mechanisms that drive the different community recovery times have not been quantified empirically. We use quantitative food web analysis to assess the influence of species interactions on community recovery. We found species interactions strength to be the main mechanism driving differences between structural and functional recovery. Additionally, we show that interactions between multiple disturbances appear in the long term only when both species interaction strength and food web architecture change significantly.</p> <p>Please see the "readme" sheet in the datafile for a description of the file structure and treatments abreviations.</p>
Fig. 1 in Dynamics Of Mouse-Like Rodent Communities In Anthropogenically Disturbed Territories Of The Southeast Of Western Siberia (Kemerovo Region, Russia)
Fig. 1. The dynamics of similarity of small mammal populations in deforested zones compared to the initial population in taiga (using the Czekanowsky-SØrensen coefficient calculated for species' percentage in the community).
Disturbance-mediated invasions are dependent on community resource abundance
<p>Here is the data for the manuscript entitled "<em>Disturbance mediated invasions are dependent on community resource abundance</em>."</p> <p>The dataset columns are:</p> <ul> <li><strong>disturb</strong> - dusturbance frequency (1 = everyday, 2 = every two days etc)</li> <li><strong>kb</strong> - resource abundance. 0.01 = low, 0.1 medium and 1.0 high.</li> <li><strong>invader</strong> - nill = no invader added (not used in the manuscript), sm shows microcosms invaded by the Smooth invader and ws by the Wrinkly Spreader invader</li> <li><strong>smooth</strong> - the final number of resident smooths</li> <li><strong>wrinkly</strong> - the final number of resident wrinkly spreaders</li> <li><strong>fuzzy</strong> - the final number of resident fuzzy</li> <li><strong>iden</strong> - the final number of invader cfu</li> <li><strong>cfu/6ml</strong> - the number of resident cfu on day four</li> </ul> <p> </p> <p>Smooth, wrinkly, fuzzy and iden columns are cfu counts per 25uL</p>
Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits
<p>Dataset and R scripts used in the publication "Impact of forest disturbance on microarthropod communities depends on underlying ecological gradient and species traits", PeerJ</p>
Data from: The ghost of disturbance past: long-term effects of pulse disturbances on community biomass and composition
<p><span><span><span><span><span><span><span><span><span><span><span>Current global change is associated with an increase in disturbance frequency and intensity, with the potential to trigger population collapses and to cause permanent transitions to new ecosystem states. However, our understanding of ecosystem responses to disturbances is still incomplete. Specifically, there is a mismatch between the diversity of disturbance regimes experienced by ecosystems and the one-dimensional description of disturbances used in most studies on ecological stability. To fill this gap, we conducted a full factorial experiment on microbial communities, where we varied the frequency and intensity of disturbances affecting species mortality, resulting in twenty different disturbance regimes. We explored the <span><span>direct</span></span> and long-term effects of these disturbance regimes on community biomass. While most communities were able to recover biomass and composition states similar to undisturbed controls after a halt of the disturbances, we identified some disturbance thresholds that had long-lasting legacies on communities. <span><span>Using a model based on logistic growth, we identified qualitatively</span></span> the sets of disturbance frequency and intensity that had equivalent long-term <span><span>negative</span></span> impacts on experimental communities. Our results show that an increase in disturbance intensity is a bigger threat for biodiversity and biomass recovery than the occurrence of more frequent but less intense disturbances.</span></span></span></span></span></span></span></span></span></span></span></p>
Data from: Increased diversity and concordant shifts in community structure of coral-associated Symbiodiniaceae and bacteria subjected to chronic human disturbance
<p>Coral-associated bacteria and endosymbiotic algae (Symbiodiniaceae<i> </i>spp.) are both vitally important for the biological function of corals. Yet little is known about their co-occurrence within corals, how their diversity varies across coral species, or how they are impacted by anthropogenic disturbances. Here, we sampled coral colonies (n = 472) from seven species, encompassing a range of life history traits, across a gradient of chronic human disturbance (n = 11 sites on Kiritimati (Christmas) atoll) in the central equatorial Pacific, and quantified the sequence assemblages and community structure of their associated Symbiodiniaceae<i> </i>and bacterial communities. Although Symbiodiniaceae alpha diversity did not vary with chronic human disturbance, disturbance was consistently associated with higher bacterial Shannon diversity and richness, with bacterial richness by sample almost doubling from sites with low to very high disturbance. Chronic disturbance was also associated with altered microbial beta diversity for Symbiodiniaceae and bacteria, including changes in community structure for both and increased variation (dispersion) of the Symbiodiniaceae communities. We also found concordance between Symbiodiniaceae and bacterial<i> </i>community structure, when all corals were considered together, and individually for two massive species, <i>Hydnophora microconos</i> and <i>Porites lobata, </i>implying that symbionts<i> </i>and bacteria respond similarly to human disturbance in these species. Finally, we found that the dominant Symbiodiniaceae ancestral lineage in a coral colony was associated with differential abundances of several distinct bacterial taxa. These results suggest that increased beta diversity of Symbiodiniaceae<i> </i>and bacterial communities may be a reliable indicator of stress in the coral microbiome, and that there may be concordant responses to chronic disturbance between these communities at the whole-ecosystem scale.</p>
Data from: Plant selection initiates alternative successional trajectories in the soil microbial community after disturbance
Because interactions between plants and microbial organisms can influence species diversity and rates of nutrient cycling, how plants shape microbial communities is fundamental to understanding the structure of ecosystems. Despite this, the spatial and temporal scales over which plants influence microbial communities is poorly understood, particularly whether past abiotic or biotic legacies strongly constrain microbial community development. We examined biogeochemical cycling and microbial community structure in a coastal landscape where historical patterns of vegetation transition after a large fire in 1995 are well known, allowing us to account for past abiotic and biotic conditions. We found that alternative states in microbial community structure and ecosystem processes emerged under different plant species, regardless of past conditions. Greenhouse studies further demonstrated that these differences arise from direct plant selection of microbes, with selection stronger in roots compared with soils, especially for bacteria. Correlation of microbial community structure with seedling growth rates was also stronger for fungi compared to bacteria. Despite these effects, minimal overlap between seedling and field microbial communities indicates that the effects of initial plant selection are not stable, rather plant selection initiated alternative successional trajectories after the fire. Using data from a guild where we have abundant natural history information - ectomycorrhizal fungi - we show that greenhouse communities are dominated by ruderal taxa that are also common in the field after the fire, and that these ruderal fungi strongly alter spatial patterns in plant-soil feedback, enabling invasion and transformation of soils previously occupied by heterospecific plants, thus potentially acting as keystone mutualists.
Data from: Disturbance-mediated consumer assemblages determine fish community structure and moderate top-down influences through bottom-up constraints
<ol> <li>Disturbance is a strong structuring force that can influence the strength of species interactions at all trophic levels, but controls on the contributions to community structure of top-down and bottom-up processes across such gradients remain poorly understood. Changes in the composition of predator and consumer assemblages, and their associated traits, across gradients of environmental harshness (e.g., flooding) are likely to be a particularly important influence on the strength of top-down control and may drive bottom-up constraints.</li> <li>We examined how consumers with particular traits, and the predators that consumed them, varied across a gradient of stream flooding disturbance and used experiments to assess the predation impact on those contrasting consumer communities (ultimately quantifying how flood disturbance altered the strength of top-down control).</li> <li>Consumer community composition and mobility were strongly related to flood disturbance; the biomass and drift of protected primary consumers (i.e., those with morphological defences) decreased with increasing flood disturbance. Predatory fish species had different disturbance niches, and path analysis identified that both direct flood-disturbance effects and indirect bottom-up constraints of flood-disturbance on consumers influenced predatory fish composition and biomass. Fishes generally fed most effectively on consumer types associated with their particular niche, but all fishes were strongly size-selective when feeding on protected consumers. Although protected consumers did not grow large enough to escape predation, an <i>in situ </i>experiment showed protected consumers were at a reduced risk of predation as disturbance increased compared to unprotected consumers.</li> <li>Overall, top-down control declined with flood disturbance, but the effect depended on consumer traits. Predatory fishes were only capable of exerting top-down control on protected consumers in benign habitats but impacted unprotected consumers across a larger range of the disturbance gradient. Collectively our findings suggest that a shift towards a more disturbed state will probably result in reduced predator impacts and a weakening of top-down control. Moreover, predicted increases in the frequency and intensity of climatic events causing disturbance, such as flooding, are likely to result in a community shift that disproportionately impacts protected consumers and the predators that utilise them as prey through the subsequent bottom-up constraints.</li> </ol>
Data for: Effect of seaweed canopy disturbance on understory microbial communities on rocky shores
<p>The collapse of macroalgal habitats is altering the structure of benthic communities on rocky shores globally. Nonetheless, how the loss of canopy-forming macroalgae influences the structure of epilithic microbial communities is yet to be explored. Here, we used experimental field manipulations and 16S-rRNA-gene amplicon sequencing to determine the effects of macroalgal loss on the understorey bacterial communities and their relationship with epiphytic bacteria on macroalgae. Beds of the fucoid <em>Hormosira</em> <em>banksii</em> were exposed to different levels of disturbance resulting in five treatments: (i) 100% removal of <em>Hormosira</em> individuals, (ii) 50% removal, (iii) no removal, (iv) a procedural control that mimicked the removal process, but no <em>Hormosira</em> was removed and (v) adjacent bare rock. Canopy cover, bacterial communities (epilithic and epiphytic) and benthic macroorganisms were monitored for 16 months. Results showed that reductions in canopy cover rapidly altered understory bacterial diversity and composition. <em>Hormosira</em> canopies in 50% and 100% removal plots showed signs of recovery over time, but understory epilithic bacterial communities remained distinct throughout the experiment in plots that experienced full Hormosira removal. Changes in bacterial communities were not related to changes in other benthic macroorganisms. These results demonstrate that understory epilithic bacterial communities respond rapidly to environmental disturbances at small scales and these changes can be long-lasting. A deeper knowledge of the ecological role of understory epilithic microbial communities is needed to better understand potential cascading effects of disturbances on the functioning of macroalgal-dominated systems.</p>
Data from: Long-term climate and hydrologic regimes shape stream invertebrate community responses to a hurricane disturbance
<p>Disturbances can produce a spectrum of short- and long-term ecological consequences that depend on complex interactions of the characteristics of the event, antecedent environmental conditions, and the intrinsic properties of resistance and resilience of the affected biological system. We used Hurricane Harvey's impact on coastal rivers of Texas to examine the roles of storm-related changes in hydrology and long-term precipitation regime on the response of stream invertebrate communities to hurricane disturbance. We detected declines in richness, diversity, and total abundance following the storm, but responses were strongly tied to direct and indirect effects of long-term aridity and short-term changes in stream hydrology. The amount of rainfall a site received drove both flood duration and flood magnitude across sites, but lower annual rainfall amounts (i.e., aridity) increased flood magnitude and decreased flood duration. Across all sites, flood duration was positively related to the time it took for invertebrate communities to return to a long-term baseline and flood magnitude drove larger invertebrate community responses (i.e., changes in diversity and total abundance). However, invertebrate response per unit flood magnitude was lower in sub-humid sites, potentially because of differences in refuge availability or ecological-evolutionary interactions. Interestingly, sub-humid streams had temporary large peaks in invertebrate total abundance and diversity following recovery period that may be indicative of the larger organic matter pulses expected in these systems because of their comparatively well-developed riparian vegetation. Our findings show that hydrology and long-term precipitation regime predictably affected invertebrate community responses and, thus, our work underscores the important influence of local climate to ecosystem sensitivity to disturbances.</p>
Roadside disturbance promotes plant communities with arbuscular mycorrhizal associations in mountain regions worldwide
<p><em>Aim: </em>We aimed to assess the impact of road disturbances on the dominant mycorrhizal types in ecosystems at the global level and how this mechanism can potentially lead to lasting plant community changes.</p> <p><em>Location: </em>Globally distributed mountain regions</p> <p><em>Time Period:</em> 2007-2018 Taxa studied: Plants (linked to their associated mycorrhizal fungi)</p> <p><em>Methods:</em> We used a database of coordinated plant community surveys following mountain roads from 894 plots in 11 mountain regions across the globe in combination with an existing database of mycorrhizal-plant associations in order to approximate the relative abundance of mycorrhizal types in natural and disturbed environments.</p> <p><em>Results:</em> Our findings show that roadside disturbance promotes the cover of plants associated with arbuscular mycorrhizal (AM) fungi. This effect is especially strong in colder mountain environments and in mountain regions where plant communities are dominated by ectomycorrhizal (EcM) or ericoid-mycorrhizal (ErM) associations. Furthermore, non-native plant species, which we confirmed to be mostly AM plants, are more successful in environments dominated by AM associations.</p> <p><em>Main Conclusions:</em> These biogeographical patterns suggest that changes in mycorrhizal types could be a crucial factor in the worldwide impact of anthropogenic disturbances on mountain ecosystems. Indeed, roadsides foster AM-dominated systems, where AM-fungi might aid AM-associated plant species while potentially reducing the biotic resistance against invasive non-native species, often also associated with AM networks. Restoration efforts in mountain ecosystems will have to contend with changes in the fundamental make-up of EcM- and ErM plant communities induced by roadside disturbance.</p>
Data and code for 'Disturbances can facilitate prior invasions more than subsequent invasions in microbial communities'
<p>Data and R code for 'Disturbances can facilitate prior invasions more than subsequent invasions in microbial communities'.</p><p>Information about the files can be found in the README.txt file.</p>
The role of competition in structuring ant community composition across a tropical forest disturbance gradient
<b>Description: </b><p>Leaf litter ant community composition and competition</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/34"><b>The role of competition in structuring ant community composition across a tropical forest disturbance gradient.</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=1">here</a></p><p><b>Data worksheets: </b>There are 3 data worksheets in this dataset:</p><ol><li><p><b>Ant community composition</b> (Worksheet Composition)</p><p>Dimensions: 430 rows by 69 columns</p><p>Description: Site x species matrix of ant community composition</p><p>Fields: </p><ul><li><b>Forest Type</b>: Shows the two forest types used in the study (Field type: Categorical)</li><li><b>Site</b>: Represents the site/day sampled. 10 Sampling sites were used in each forest type (Field type: Location)</li><li><b>Time</b>: Represents the time in the day points were sampled (Field type: Time)</li><li><b>Point</b>: Represents the column of 3 sampling points for each time of day (Field type: Replicate)</li><li><b>ID</b>: Represents individual sampling point. Order is: Site(Day)/Time/Type/Sampling point no. Logged ID's also have LF at the start (Field type: ID)</li><li><b>Method</b>: Method used to record community (Field type: Categorical)</li><li><b>Diacamma</b>: Number of individuals (Field type: Abundance)</li><li><b>Odontoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Pheidole</b>: Number of individuals (Field type: Abundance)</li><li><b>Leptogenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Pheidologeton</b>: Number of individuals (Field type: Abundance)</li><li><b>Crematogaster</b>: Number of individuals (Field type: Abundance)</li><li><b>Odontomachus</b>: Number of individuals (Field type: Abundance)</li><li><b>Aphaenogaster</b>: Number of individuals (Field type: Abundance)</li><li><b>Acanthomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Nylanderia</b>: Number of individuals (Field type: Abundance)</li><li><b>Camponotus</b>: Number of individuals (Field type: Abundance)</li><li><b>Cardiocondyla</b>: Number of individuals (Field type: Abundance)</li><li><b>Anochetus</b>: Number of individuals (Field type: Abundance)</li><li><b>Technomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Monomorium</b>: Number of individuals (Field type: Abundance)</li><li><b>Recurvidris</b>: Number of individuals (Field type: Abundance)</li><li><b>Polyrhachis</b>: Number of individuals (Field type: Abundance)</li><li><b>Cladomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Lophomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Harpegnathos</b>: Number of individuals (Field type: Abundance)</li><li><b>Carebara</b>: Number of individuals (Field type: Abundance)</li><li><b>Cataulacus</b>: Number of individuals (Field type: Abundance)</li><li><b>Pachycondyla</b>: Number of individuals (Field type: Abundance)</li><li><b>Lordomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmecina</b>: Number of individuals (Field type: Abundance)</li><li><b>Proatta</b>: Number of individuals (Field type: Abundance)</li><li><b>Euprenolepis</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhytidoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Paratrechina</b>: Number of individuals (Field type: Abundance)</li><li><b>Paraparatrechina</b>: Number of individuals (Field type: Abundance)</li><li><b>Tetramorium</b>: Number of individuals (Field type: Abundance)</li><li><b>Paratopula</b>: Number of individuals (Field type: Abundance)</li><li><b>Strumigenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Pyramica</b>: Number of individuals (Field type: Abundance)</li><li><b>Ponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Hypoponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Tetraponera</b>: Number of individuals (Field type: Abundance)</li><li><b>Emeryopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Centromyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Tapinoma</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmicaria</b>: Number of individuals (Field type: Abundance)</li><li><b>Rotrastruma</b>: Number of individuals (Field type: Abundance)</li><li><b>Prionopelta</b>: Number of individuals (Field type: Abundance)</li><li><b>Gnamptogenys</b>: Number of individuals (Field type: Abundance)</li><li><b>Eurhopalothrix</b>: Number of individuals (Field type: Abundance)</li><li><b>Myrmoteras</b>: Number of individuals (Field type: Abundance)</li><li><b>Oecophylla</b>: Number of individuals (Field type: Abundance)</li><li><b>Myopias</b>: Number of individuals (Field type: Abundance)</li><li><b>Pseudolasius</b>: Number of individuals (Field type: Abundance)</li><li><b>Plagiolepis</b>: Number of individuals (Field type: Abundance)</li><li><b>Dacetinops</b>: Number of individuals (Field type: Abundance)</li><li><b>Mystrium</b>: Number of individuals (Field type: Abundance)</li><li><b>Echinopla</b>: Number of individuals (Field type: Abundance)</li><li><b>Philidris</b>: Number of individuals (Field type: Abundance)</li><li><b>Vollenhovia</b>: Number of individuals (Field type: Abundance)</li><li><b>Rhoptromyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Anillomyrma</b>: Number of individuals (Field type: Abundance)</li><li><b>Cryptopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Aenictus</b>: Number of individuals (Field type: Abundance)</li><li><b>Calyptomyrmex</b>: Number of individuals (Field type: Abundance)</li><li><b>Amblyopone</b>: Number of individuals (Field type: Abundance)</li><li><b>Prenolepis</b>: Number of individuals (Field type: Abundance)</li></ul><br></li><li><p><b>Morphometrics</b> (Worksheet Morpho)</p><p>Dimensions: 72 rows by 4 columns</p><p>Description: Size classes for the genera</p><p>Fields: </p><ul><li><b>Genera</b>: Genus ID (Field type: Taxa)</li><li><b>Size.Min</b>: Minimum body size (Field type: Categorical Trait)</li><li><b>Size.Max</b>: Maximum body size (Field type: Categorical Trait)</li></ul><br></li><li><p><b>Competition</b> (Worksheet Competition)</p><p>Dimensions: 866 rows by 15 columns</p><p>Description: Outcome of competitive interactions among individuals of different genera</p><p>Fields: </p><ul><li><b>Forest Type</b>: Shows the two forest types used in the study (Field type: Categorical)</li><li><b>Site</b>: Represents the site/day sampled. 10 Sampling sites were used in each forest type (Field type: Location)</li><li><b>Time</b>: Represents the time in the day points were sampled (Field type: Time)</li><li><b>ID</b>: Represents individual sampling point. Order is: Site(Day)/Time/Type/Sampling point no. Logged ID's also have LF at the start (Field type: ID)</li><li><b>Method</b>: Method used to record interaction (Field type: Categorical)</li><li><b>Genera1</b>: Genus ID of the first interacting individual (Field type: Taxa)</li><li><b>Genera2</b>: Genus ID of the second interacting individual (Field type: Taxa)</li><li><b>TimeG1</b>: The arrival time of the first genus in the interaction to the bait card in seconds (Field type: Numeric)</li><li><b>TimeG2</b>: The arrival time of the second genus in the interaction to the bait card in seconds (Field type: Numeric)</li><li><b>IntG1</b>: The competitive status of the first genus in the interaction (Field type: Categorical Interaction)</li><li><b>IntG2</b>: The competitive status of the second genus in the interaction (Field type: Categorical Interaction)</li><li><b>Interaction</b>: The type of interaction occuring between the two genera (Field type: Categorical Interaction)</li><li><b>GroupG1</b>: Whether or not the first genus was part of a group of individuals when interacting on the bait card (Field type: Categorical)</li><li><b>GroupG2</b>: Whether or not the second genus was part of a group of individuals when interacting on the bait card (Field type: Categorical)</li></ul><br></li></ol><p><b>Date range: </b>2016-02-02 to 2016-06-05</p><p><b>Latitudinal extent: </b>4.7273 to 4.7463</p><p><b>Longitudinal extent: </b>116.9669 to 117.5969</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Arthropoda<br> -  - Insecta<br> -  -  - Hymenoptera<br> -  -  -  - Formicidae<br> -  -  -  -  - <i>Acanthomyrmex</i><br> -  -  -  -  - <i>Aenictus</i><br> -  -  -  -  - <i>Amblyopone</i><br> -  -  -  -  - <i>Anillomyrma</i><br> -  -  -  -  - <i>Anochetus</i><br> -  -  -  -  - <i>Aphaenogaster</i><br> -  -  -  -  - <i>Calyptomyrmex</i><br> -  -  -  -  - <i>Camponotus</i><br> -  -  -  -  - <i>Cardiocondyla</i><br> -  -  -  -  - <i>Carebara</i><br> -  -  -  -  - <i>Cataulacus</i><br> -  -  -  -  - <i>Centromyrmex</i><br> -  -  -  -  - <i>Cladomyrma</i><br> -  -  -  -  - <i>Crematogaster</i><br> -  -  -  -  - <i>Cryptopone</i><br> -  -  -  -  - <i>Dacetinops</i><br> -  -  -  -  - <i>Diacamma</i><br> -  -  -  -  - <i>Echinopla</i><br> -  -  -  -  - <i>Emeryopone</i><br> -  -  -  -  - <i>Euprenolepis</i><br> -  -  -  -  - <i>Eurhopalothrix</i><br> -  -  -  -  - <i>Gnamptogenys</i><br> -  -  -  -  - <i>Harpegnathos</i><br> -  -  -  -  - <i>Hypoponera</i><br> -  -  -  -  - <i>Leptogenys</i><br> -  -  -  -  - <i>Lophomyrmex</i><br> -  -  -  -  - <i>Lordomyrma</i><br> -  -  -  -  - <i>Monomorium</i><br> -  -  -  -  - <i>Myopias</i><br> -  -  -  -  - <i>Myrmecina</i><br> -  -  -  -  - <i>Myrmicaria</i><br> -  -  -  -  - <i>Myrmoteras</i><br> -  -  -  -  - <i>Mystrium</i><br> -  -  -  -  - <i>Nylanderia</i><br> -  -  -  -  - <i>Odontomachus</i><br> -  -  -  -  - <i>Odontoponera</i><br> -  -  -  -  - <i>Oecophylla</i><br> -  -  -  -  - <i>Pachycondyla</i><br> -  -  -  -  - <i>Paraparatrechina</i><br> -  -  -  -  - <i>Paratopula</i><br> -  -  -  -  - <i>Paratrechina</i><br> -  -  -  -  - <i>Pheidole</i><br> -  -  -  -  - <i>Pheidologeton</i><br> -  -  -  -  - <i>Philidris</i><br> -  -  -  -  - <i>Plagiolepis</i><br> -  -  -  -  - <i>Polyrhachis</i><br> -  -  -  -  - <i>Ponera</i><br> -  -  -  -  - <i>Prenolepis</i><br> -  -  -  -  - <i>Prionopelta</i><br> -  -  -  -  - <i>Proatta</i><br> -  -  -  -  - <i>Pseudolasius</i><br> -  -  -  -  - <i>Pyramica</i><br> -  -  -  -  - <i>Recurvidris</i><br> -  -  -  -  - <i>Rhoptromyrmex</i><br> -  -  -  -  - <i>Rhytidoponera</i><br> -  -  -  -  - [<i>Rotrastruma</i>]<br> -  -  -  -  - <i>Strumigenys</i><br> -  -  -  -  - <i>Tapinoma</i><br> -  -  -  -  - <i>Technomyrmex</i><br> -  -  -  -  - <i>Tetramorium</i><br> -  -  -  -  - <i>Tetraponera</i><br> -  -  -  -  - <i>Vollenhovia</i><br></div><p></p>
Data from: Tropical understory herbaceous community responds more strongly to hurricane disturbance than to experimental warming
<p>The effects of climate change on tropical forests may have global consequences due to the forests' high biodiversity and major role in the global carbon cycle. In this study, we document the effects of experimental warming on the abundance and composition of a tropical forest floor herbaceous plant community in the Luquillo Experimental Forest, Puerto Rico. This study was conducted within Tropical Responses to Altered Climate Experiment (TRACE) plots, which use infrared heaters under free-air, open-field conditions, to warm understory vegetation and soils +4 °C above nearby control plots. Hurricanes Irma and María damaged the heating infrastructure in the second year of warming, therefore, the study included one pre-treatment year, one year of warming, and one year of hurricane response with no warming. We measured percent leaf cover of individual herbaceous species, fern population dynamics, and species richness and diversity within three warmed and three control plots.</p> <p>Results showed that one year of experimental warming did not significantly affect the cover of individual herbaceous species, fern population dynamics, species richness, or species diversity. In contrast, herbaceous cover increased from 20% to 70%, bare ground decreased from 70% to 6%, and species composition shifted pre- to post-hurricane. The negligible effects of warming may have been due to the short duration of the warming treatment or an understory that is somewhat resistant to higher temperatures. Our results suggest that climate extremes that are predicted to increase with climate change, such as hurricanes and droughts, may cause more abrupt changes in tropical forest understories than longer-term sustained warming.</p>
Long-term responses to large-scale disturbances: Spatiotemporal variation in gastropod populations and communities
<p>The Anthropocene is characterized by complex, primarily human-generated, disturbance regimes that include combinations of long-term press (e.g. climate change, pollution) and episodic pulse (e.g. cyclonic storms, floods, wildfires, land use change) disturbances. Within any regime, disturbances occur at multiple spatial and temporal scales, creating complex and varied interactions that influence spatiotemporal dynamics in the abundance, distribution, and biodiversity of organisms. Moreover, responses to disturbance are context-dependent, with the legacies of previous disturbances affecting responses to ensuing perturbations. We use three decades of annual data to evaluate the effects of repeated pulse disturbances and global warming on gastropod populations and communities in Puerto Rico at multiple spatial scales. More specifically, we quantify (1) the relative importance of large-scale and small-scale aspects of disturbance on variation in abundance, biodiversity, and species composition; and (2) the spatial scales at which populations and communities integrate information in the spatially heterogenous environments created by disturbances. Gastropods do not exhibit consistent decreases in abundance or biodiversity in association with global warming: abundance for many species has increased over time and species richness does not evince a temporal trend. Nonetheless, gastropods are sensitive to hurricane severity, spatial environmental variation, and successional trajectories of the flora. In addition, they exhibit context-dependent (i.e. legacy effects) responses that are scale-dependent. The Puerto Rican biota has evolved in a disturbance-mediated system. This historical exposure to repeated, severe hurricane-induced disturbances has imbued the biota with high resistance and resilience to the current disturbance regime, resulting in an ability to persist or thrive under current environmental conditions. Nonetheless, these ecosystems may yet be threatened by worsening direct and indirect effects of climate change. In particular, more frequent and severe hurricanes may prevent the establishment of closed-canopy forests, negatively impacting populations and communities that rely on these habitats.</p>
Data for: Local conditions matter: Minimal and variable effects of soil disturbance on microbial communities and functions in European vineyards
<p>Soil tillage or herbicide applications are commonly us<span>ed in agriculture for weed control. These measures may also represent a disturbance for soil microbial communities and their functions. However, the generality of response patterns of microbial communities and functions to disturbance have rarely been studied at large geographical scales. We investigated how a soil disturbance gradient (low, intermediate, high), realized by either tillage or herbicide application, affects diversity and composition of soil bacterial and fungal communities as well as soil functions in vineyards across five European countries. Microbial alpha-diversity metrics responded to soil disturbance sporadically, but inconsistently across countries. Increasing soil disturbance changed soil microbial community composition at the European level. However, the effects of soil disturbance on the variation of microbial communities were smaller compared to the effects of location and soil covariates. Microbial respiration was consistently impaired by soil disturbance, while effects on decomposition of organic substrates were inconsistent and showed positive and negative responses depending on the respective country. </span><span>Therefore, we conclude that it is difficult to extrapolate results from one locality to others because microbial communities and environmental conditions vary strongly over larger geographical scales.</span><span> </span></p>
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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.