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117 results for “multi-species”
Data from: Identifying priority areas for spatial management of mixed fisheries using ensemble of multi-species distribution models. Panzeri D. et al., 2023, Fish and Fisheries
<p>Panzeri D.<sup>1</sup>, Russo T., Arneri E., Carlucci R., Cossarini G., Isajlović I., Krstulović Šifner S., Manfredi C., Masnadi F., Reale M., Scarcella G., Solidoro C., Spedicato M.T., Vrgoč N., W. Zupa, Libralato S<sup>2</sup>.</p> <p><sup>1 </sup>dpanzeri@ogs.it<br> <sup>2 </sup>slibralato@ogs.it</p> <p>Spatial fisheries management is widely used to reduce overfishing, rebuild stocks, and protect biodiversity. However, the effectiveness and optimization of spatial measures depend on accurately identifying ecologically meaningful areas, which can be difficult in mixed fisheries. To apply a method generally to a range of target species, we developed an ensemble of species distribution models (e-SDM) that combines general additive models, generalized linear mixed models, random forest, and gradient-boosting machine methods in a training and testing protocol. The e-SDM was used to integrate density indices from two scientific bottom trawl surveys with the geopositional data, relevant oceanographic variables from the three-dimensional physical-biogeochemical operational model, and fishing effort from the vessel monitoring system. The determined best distributions for juveniles and adults are used to determine hot spots of aggregation based on single or multiple target species. We applied e-SDM to juvenile and adult stages of 10 marine demersal species representing 60% of the total demersal landings in the central areas of the Mediterranean Sea. Using the e-SDM results, hot spots of aggregation and grounds potentially more selective were identified for each species and for the target species group of otter trawl and beam trawl fisheries. The results confirm the ecological appropriateness of existing fishery restriction areas and support the identification of locations for new spatial management measures.</p> <p>Data (csv) for Panzeri et al. 2023</p> <p>1. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Ensemble_density_F&F_D.Panzeri_et_al_2023.csv: CSV file with density values (column pred) in terms of number of individuals (log N/km2) for each species (column sp) and life stage (column age) for each grid cell (X = longitude and Y = latitude).</a> </p> <p>2. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Getis_hotspot_F&F_D.Panzeri_et_al_2023.csv: CSV file with Getis ord Gi* values (column Gi) derived from the previous file 1, developed for each species and life stage for each grid cell (X = longitude and Y = latitude).</a></p> <p>3. <a href="https://zenodo.org/api/files/0b1b7af4-6a3b-481d-8d5f-57cf02d20eaa/Ensemble_density_F%26F_D.Panzeri_et_al_2023.csv">Multispecies_HotSpot_F&F_D.Panzeri_et_al_2023.csv: Frequency map expressed as the number of species for each grid cell (column freq) that has the hotspot (previous file 2) above the third quartile.</a></p> <p> </p> <p> </p>
Data from: Complementary strengths of spatially-explicit and multi-species distribution models
<p><span><span><span><span><span><span><span><span><span><span><span> Species distribution models (SDMs) project the outcome of community assembly processes - dispersal, the abiotic environment, and biotic interactions - onto geographic space. Recent advances in SDMs account for these processes by simultaneously modeling the species that comprise a community in a multivariate statistical framework or by incorporating residual spatial autocorrelation in SDMs. However, the effects of combining both multivariate and spatially-explicit model structures on the ecological inferences and the predictive abilities of a model are largely unknown. We used data on eastern hemlock (<i>Tsuga canadensis</i>L.) and five additional co-occurring overstory tree species in 35,569 forest stands across Michigan, USA to evaluate how the choice of model structure, including spatial and non-spatial forms of univariate and multivariate models, affects ecological inference about the processes that shape community composition as well as model predictive ability.</span></span></span></span></span></span></span></span></span></span></span></p> <p><span><span><span><span><span><span><span><span><span><span> Incorporating residual spatial autocorrelation via spatial random effects did not improve out-of-sample prediction for the six tree species, although in-sample model fit was higher in the spatial models. Spatial models attributed less variation in occurrence probability to environmental covariates than the non-spatial models for all six tree species, and estimated higher (more positive) residual co-occurrence values for most species pairs. The non-spatial multivariate model was better suited for evaluating habitat suitability and hypotheses about the processes that shape community composition. Environmental correlations and residual correlations among species pairs were positively related, perhaps indicating that residual correlations were due to shared responses to unmeasured environmental covariates. This work highlights the importance of choosing a non-spatial model formulation to address research questions about the species-environment relationship or residual co-occurrence patterns, and a spatial model formulation when within-sample prediction accuracy is the main goal.</span></span></span></span></span></span></span></span></span></span></p>
Supporting data for "Mammalian species abundance across a gradient of tropical land-use intensity: A hierarchical multi-species modelling approach"
<p>Combined camera trap and live trap dataset underlying the analyses in a Biological Conservation paper (https://doi.org/10.1016/j.biocon.2017.05.007), provided in .csv format. This spatially- and temporally-replicated dataset is suitable for occupancy modelling.</p> <p>The first 3 columns in the dataset are:</p> <p>1) Trap location name – old-growth forest, logged forest and oil palm plantation locations have the prefixes "Old", "Log" and "Palm", respectively</p> <p>2) Sampling occasion number – camera trap and live trap occasions have the prefixes “Lvtrap” and “Ctrap”, respectively, and are defined in the paper</p> <p>3) Calendar year in which sampling took place (most locations were sampled in > 1 calendar years)</p> <p>Following these 3 columns, there are 66 columns for each of the mammal species detected during the study (species common names are used). The values for each species represent the number of independent captures, as defined in the paper. This can be reduced to detection/non-detection data (zeroes and ones), if needed, for occupancy modelling.</p>
Figures 1–3. 1 in Nocturnal multi-species roosts of Cicindelidae (Coleoptera) in a Neotropical lowland rainforest
Figures 1–3. 1) Forest path #1 at the study site in lowland terra firme Venezuelan rainforest, February 1999. 2) Communal roost of Odontocheila Laporte de Castelnau spp. (O. confusa (Dejean) and O. angulipenis W. Horn/O. margineguttata (Dejean)) at the study site in lowland terra firme Venezuelan rainforest, June 1998. 3) Communal roost of Odontocheila Laporte de Castelnau spp. (O. confusa (Dejean) and O. angulipenis W. Horn/O. margineguttata (Dejean)) at the study site in lowland terra firme Venezuelan rainforest, May 1998.
Dataset from: Tolerance to aerial exposure influences distributional patterns in multi-species intertidal seagrass meadows
<p>This is the dataset for an article published in Marine Environmental Research titled, 'Tolerance to aerial exposure influences distributional patterns in multi-species intertidal seagrass meadows', in October 2023. Following is the abstract for the paper for which this was the primary data:</p><p>Multi-specific seagrass meadow assemblages dominate most tropical intertidal regions but the relative role of environmental stress in determining distribution patterns is still uncertain. Here we combine observational and experimental approaches to examine aerial exposure as a factor driving species occurrence patterns in intertidal meadows of the Andaman archipelago, where up to 6 seagrass species co-occur. In the studied meadow, patterns of exposure did not map onto distance from the coast, instead creating a patchy matrix of exposure, based on fine-scale bathymetric differences. Distributional surveys showed that seagrass species were similarly patchy, often tracking the degree of aerial exposure during low tide. While some species (<i>Halophila ovalis, Halophila minor,</i> and <i>Thalassia hemprichii</i>) frequently occurred in submerged or subtidal areas and were rarely found in completely exposed areas, other species (<i>Cymodocea rotundata</i>, <i>Halophila beccarii,</i> and <i>Halodule uninervis</i>) also occupied areas that were subject to partial or complete aerial exposure during low tide. To confirm this pattern, we used field-based transplant experiments, employing a natural gradient of tidal exposure to subject six seagrass species to different desiccation exposure times. After a month, <i>H. beccarii</i> and <i>H. uninervis</i> transplants survived in areas that sustained more than 3 h of aerial tidal exposure without significant mortality, compared with other species (<i>H. ovalis, H. minor, T. hemprichii, C. rotundata</i>) that showed dramatic shoot mortality at the same exposure regimes. For all species, 4 h represented the upper limit of exposure, in both experimental and distributional studies. However, despite their wider tolerance of exposure to air, <i>H. beccarii</i> and <i>H. uninervis</i> did not dominate the entire meadow. This could be a result either of their poor tolerance to other environmental factors or their lower competitive abilities among other mechanisms. This suggests that in tropical multi-specific meadows, strong environmental filters could override clear intertidal zonation to create patchy matrices based on species tolerances.</p>
Bacterial pathogens dynamic during multi-species infections
<p>Illumina gapA sequences of synthetic communities of plant bacterial pathogens: Pectobacterium and Dickeya genus. Sequencing was performed after growth on TSB synthetic medium (2 days post inoculation) or growth on potato tubers (5 days post infection).</p> <p> </p> <p>The following files are available:</p> <p>PT_table.txt: description of the potato tubers samples</p> <p>TSB_table.txt: description of samples in synthetic medium (TSB)</p> <p>gapA_PT.fasta.gz: Illumina fasta sequences after potato tubers infection (35,000 reads)</p> <p>gapA_TSB.fasta.gz: Illumina fasta sequences after synthetic medium inoculation (35,000 reads)</p> <p>gapA_without_primers.fasta: gapA sequences (without primers) of Pectobacterium and Dickeya strains used in this study (27 strains)</p> <p>species.txt: list of bacterial species used in this study (9 species)</p> <p>strains.txt: list of bacterial strains used in this study (27 strains)</p> <p>count.py: python3 script used to analyse the output of blastn</p> <p>R_script_FigureS1.R: R script for statistical analysis</p> <p>R_script_Figure2b.R: R script for statistical analysis</p> <p>R_script_Figure2a.R: R script for statistical analysis</p> <p> </p> <p>Method (examplified with the gapA_TSB sequences at the species level):</p> <p>• gapA sequences were blasted (blastn) against gapA sequences of Pectobacterium and Dickeya strains used in this study:</p> <p>makeblastdb -in gapA_without_primers.fasta -dbtype nucl -out dbblastn</p> <p>blastn -db dbblastn -query gapA_TSB.fasta -outfmt 6 -out blast.blastn -num_threads 12 -evalue 0.00001 -num_alignments 1</p> <p>• Reads count. Reads matching (100% identity) with gapA sequences of Pectobacterium and Dickeya strains used in this study were counted using the count.py python script. The output is a tab-separated values (.tsv) file:</p> <p>python3 count.py species.txt blast.blastn</p>
Linked collectors and determiners for: A revision of Gerrhopilus inornatus (Squamata: Gerrhopilidae) reveals a multi-species complex.
Natural history specimen data linked to collectors and determiners held within, "A revision of Gerrhopilus inornatus (Squamata: Gerrhopilidae) reveals a multi-species complex". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="https://bionomia.net/dataset/28ad10b7-ef05-4349-a058-05d7f75104de">https://bionomia.net/dataset/28ad10b7-ef05-4349-a058-05d7f75104de</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/28ad10b7-ef05-4349-a058-05d7f75104de">https://gbif.org/dataset/28ad10b7-ef05-4349-a058-05d7f75104de</a>. Formatted as a Frictionless Data package.
Acoustic video cameras multi-species multi-cameras Training Dataset (TD) for Deep Learning applications
<p>This images dataset, called also TD (Training Dataset), is designed to train/test/validate deep learning models to identify fish species in sonar camers video flux. It includes data from two different type of cameras (ARIS and DIDSON), two sites (Touques and Selune rivers in Normandy, France), 6 different fishes classes (Atlantic Salmon, European Eel, Sea Lamprey, Allis Shad, European Catfish and generic unidentified fish). This dataset, formatted in the yolo-darknet format as explained in <a href="https://github.com/AlexeyAB/darknet">https://github.com/AlexeyAB/darknet</a>, includes also a large number of images without any fish passage, in order to test the effect of negative data on the trainings.</p>
Data from Lamb et al.: "Hanging out at the club: breeding status and territoriality affect individual space use, multi-species overlap, and pathogen transmission risk at a seabird colony"
<p>This dataset consists of two files:</p> <p><strong>ams_sku_all provides</strong> GPS locations from tracked skuas.</p> <p><strong>Skua_GPS_Metadata</strong> provides information on tracked skuas. The file consists of two workseets, the data table ("skua_gps_metadata", and a key providing descriptions of the column names and values ("Key")</p>
Modelling heterogeneity in the classification process in multi-species distribution models can improve predictive performance
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Assessing patterns and risk to Chilean freshwater fish distributions using multi-species occupancy models
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Data from: Complementary strengths of spatially-explicit and multi-species distribution models
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Estimating waiting distances between genealogy changes under a multi-species extension of the sequentially Markov coalescent
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Data from: Multi-species sensory networks and social foraging strategies: Implications for population decline in procellariiform seabirds
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Data from: Local soil legacy effects in a multi-species grassland community are underlain by root foraging and soil nutrient availability
<p>1. Plant soil legacies consisting of species-specific microbial communities are hypothesized to play a critical, structuring role in plant species co-existence processes. Plant species are thought to perform worse on soil conditioned by the same species compared to soil of other species, which serves as a self-limitation mechanism and averts mono-dominance of strong competitors. Here we test in a multi-species community setting, whether root colonisation and resource utilisation of soil patches with distinct soil legacies, are consistent with this hypothesis. 2. We grew eight grassland species together in an outdoor mesocosm setup in unconditioned soil and created soil patches in these communities conditioned by one of four plant species, or a soil mixture of all four. During two subsequent growing seasons, we tested the effect of these conditioned soil patches on belowground root colonisation into the patches of each surrounding plant species using a novel sequencing based approach. In addition, we tested the effect of soil conditioning on local root functioning by injecting tracers into the soil patches and measuring the recovery in aboveground biomass. 3. Against expectations, plant species did not place less roots in own soil patches compared to foreign soil patches, nor did species take up less tracer from own compared to foreign soil patches. Using structural equation modelling, we found that tracer uptake of the plant species was to a varying degree explained by root densities in the various soil patches and by differing soil nutrient availability of the soil patches. We conclude that soil legacy effects are inextricably connected to soil nutrient availability, which needs to be taken into account in plant-soil feedback research to understand the processes that shape plant communities. 4. Synthesis. We found that soil legacy effects in complex, multi-species semi-field conditions did not match expectations based on theory and experiments in controlled conditions. Among the many complicating factors that may modify or even overrule soil legacy effects in semi-field settings, we identified soil nutrient availability as a critical force that may, together with soil biota, shape plant species co-existence processes.</p>
Data: Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning
<p>This data file consists of state-space model-derived locations and individual data used to analyze transmitter effects for sea ducks in Eastern North America and is associated with the manuscript "Assessing year-round habitat use by migratory sea ducks in a multi-species context reveals seasonal variation in habitat selection and partitioning" published in Ecography. Columns are organized as follows:</p> <p>id - unique identifier</p> <p>species - species from which the centroid was obtained (BLSC = black scoter, COEI = common eider, LTDU = long-tailed duck, SUSC = surf scoter, WWSC = white-winged scoter)</p> <p>date - date of location (mm/dd/yy)</p> <p>jday - Julian date of location</p> <p>year - calendar year of location</p> <p>lon - longitude of location</p> <p>lat - latitude of location</p> <p>b - average assignment of location to either migrant (1) or resident (2) across all runs of the state-space model</p> <p>b.5 - most probable behavioral category based on average state assignment (1 = b ≤ 1.5 ; 2 = b > 1.5)</p> <p>sex - sex of individual (M = male, F = female)</p> <p>age - age of individual (HY = hatch year, SY = second year, TY = third year, ASY = after second year, ATY = after third year, AHY = after hatch year</p> <p>capture_reg - general area where individual was captured</p> <p>capture_subreg - specific region within capture region where individual was captured</p> <p>stage - period of the annual cycle to which the centroid belongs (W = winter, B = breeding, S = spring staging, M = fall staging and molt, WM = winter migration, BM = breeding migration, MM = molt migration, SM = spring migration)</p> <p>site - position of centroid within season (i.e., W1 = first site occupied during winter, W2 = second site occupied, etc.)</p> <p>cycle - number of annual cycles following transmitter attachment (1 = first cycle after attachment, 2 = second cycle after attachment, etc.)</p> <p>season - season of annual cycle in which centroid occurred (W = winter, F = fall, B = breeding, S = spring)</p>
Multi-species occupancy modeling provides novel insights into amphibian metacommunity structure and wetland restoration
<p>A fundamental goal of community ecology is to understand species-habitat relationships and how they shape metacommunity structure. Recent advances in occupancy modeling enable habitat relationships to be assessed for both common and rare species within metacommunities using multi-species occupancy models (MSOM). These models account for imperfect species detection and offer considerable advantages over other analytical tools commonly used for community analyses under the elements of metacommunity structure (EMS) framework. Here, we demonstrate that MSOM can be used to infer habitat relationships and test metacommunity theory, using amphibians. Repeated frog surveys were undertaken at 55 wetland sites in eastern Australia. We detected 11 frog species from three families (Limnodynastidae, Myobatrachidae and Pelodryadidae). The rarest species was detected at only one site whereas the most common species was detected at 42 sites (naïve occupancy rate: 0.02 – 0.76). Two models were assessed representing two competing hypotheses; the best-supported model included the covariates distance to the nearest site (connectivity), wetland area, presence of the non-native eastern mosquitofish (<i>Gambusia holbrooki</i>), proportion cover of emergent vegetation, an interaction term between Gambusia and emergent vegetation cover, and the proportion canopy cover over a site. Hydroperiod played no detectable role in metacommunity structure. We found species-habitat relationships that fit with current metacommunity theory – occupancy increased with wetland area and connectivity. There was a strong negative relationship between occupancy and the presence of predatory Gambusia, and a positive interaction between Gambusia and emergent vegetation. The presence of canopy cover strongly increased occupancy for several tree frog species, highlighting the importance of terrestrial habitat for amphibian community structure. We demonstrated how responses by amphibians to environmental covariates at the species level can be linked to occupancy patterns at the metacommunity scale. Our results have clear management implications – wetland restoration projects for amphibians and likely other taxa should maximize wetland area and connectivity, establish partial canopy cover, and eradicate Gambusia or provide aquatic vegetation to mitigate the impact of this non-native fish. We strongly advocate the use of MSOM to elucidate the habitat drivers behind animal occupancy patterns and to derive unbiased occupancy estimates for monitoring programmes.</p>
Data from: Trait-based formal definition of plant functional types and functional communities in the multi-species and multi-traits context
<p>The concepts of traits, plant functional types (PFT), and functional communities are effective tools for the study of complex phenomena such as plant community assembly. Here, we (1) suggest a procedure formalising the classification of response traits to construct a PFT system; (2) integrate the PFT, and species compositional data to formally define functional communities; and, (3) identify environmental drivers that underpin the functional-community patterns.A species–trait data set featuring species pooled from two study sites (Eneabba and Cooljarloo, Western Australia), both supporting kwongan vegetation (sclerophyllous scrub and woodland communities), was subjected to classification to define PFTs. Species of both study sites were replaced with the newly derived PFTs and projected cover abundance-weighted means calculated for every plot. Functional communities were defined by classifications of the abundance-weighted PFT data in the respective sites. Distance-based redundancy analysis (using the abundance-weighted community and environmental data) was used to infer drivers of the functional community patterns for each site.A classification based on trait data assisted in reducing trait-space complexity in the studied vegetation and revealed 26 PFTs shared across the study sites. In total, seven functional communities were identified. We demonstrate a putative functional-community pattern-driving effect of soil-texture (clay—sand) gradients at Eneabba (42% of the total inertia explained) and that of water repellence at Cooljarloo (36%). Synthesis. This paper presents a procedure formalising the classification of multiple response traits leading to the delineation of PFTs and functional communities. This step captures plant responses to stresses and disturbance characteristic of kwongan vegetation, including low nutrient status, water stress, and fire (a landscape-level disturbance factor). Our study is the first to introduce a formal procedure assisting their formal recognition. Our results support the role of short-term abiotic drivers structuring the formation of fine-scale functional community patterns in a complex, species-rich vegetation of Western Australia.</p>
Crop diversity and within field multi-species interactions mediate herbivore abundances in cotton fields
<p>Insect herbivore abundances in agricultural fields partly depend on surrounding landscape compositional heterogeneity (e.g., landscape complexity). Landscape complexity can directly (e.g., dilution of host crops) and indirectly (promoting herbivore biocontrol) regulate herbivores in agricultural fields. While much is known about direct (e.g., resource concentration) and indirect effects (i.e., promoting biocontrol) of landscape complexity on herbivore populations, more work is needed to study whether landscape complexity can regulate herbivore populations by mediating within field multi-species interactions among herbivores and their shared natural enemies. During 2019 and 2020, we estimated <em>Bemisia tabaci </em>and<em> Aphis gossypii</em> abundances, their dominant predators (coccinellids, spiders, <em>Orius </em>spp., and <em>Geocoris </em>spp.), and their interaction (using molecular analysis) in 38 cotton fields along a gradient of landscape diversity across Georgia, USA. Within cotton fields, we assessed the effect of predator abundances, their frequency of feeding on herbivores, and the correlation between herbivore abundances (<em>B. tabaci </em>and <em>A. gossypii</em>) on the <em>B. tabaci</em> and <em>A. gossypii</em> abundance. At the landscape scale, crop diversity and different cover types influenced the abundance of <em>B. tabaci</em> and <em>A. gossypii</em> within cotton fields. We found a complex interaction among pests at the field scale, with higher aphid abundance correlated with decreased whitefly abundance. Our results support crop diversification for improving suppression of generalist pests in cotton landscapes through promoting biocontrol and diluting host crop area. Our result further suggests that the landscape complexity effect on whiteflies can indirectly mediate aphid abundance in cotton fields, indicating the importance of within field species interactions.</p>
A multi-species approach to manage effects of land cover and weather on upland game birds
<p class="Text">Loss and degradation of grasslands in the Great Plains region has resulted in major declines in abundance of grassland bird species. To ensure future viability of grassland bird populations, it is crucial to evaluate specific effects of environmental factors among species to determine drivers of population decline and develop effective conservation strategies. We used threshold models to quantify effects of land cover and weather changes on lesser and greater prairie-chickens (<i>Tympanuchus pallidicinctus </i>and <i>T. cupido</i>, respectively), northern bobwhites (<i>Colinus virginianus</i>), and ring-necked pheasants (<i>Phasianus colchicus</i>). We demonstrated a novel approach for estimating landscape conditions needed to optimize abundance across multiple species at a variety of spatial scales. Abundance of all four species was highest following wet summers and dry winters. Prairie-chicken and ring-necked pheasant abundance was highest following cool winters, while northern bobwhite abundance was highest following warm winters. Greater prairie-chicken and northern bobwhite abundance was also highest following cooler summers. Optimal abundance of each species occurred in landscapes that represented a grassland and cropland mosaic, though prairie-chicken abundance was optimized in landscapes with more grassland and less edge habitat than northern bobwhites and ring-necked pheasants. Because these effects differed among species, managing for an optimal landscape for multiple species may not be the optimal scenario for any one species.</p>
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.