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538 results for “Local Effects”
Tree seedling abundance mediated by local neighborhood effects and microsite conditions
Tree recruitment across elevational gradients is shaped by myriad factors, including abundance of nearby conspecific adults and abiotic establishment conditions. We measured seedling abundance and overstory basal area for six tree species that dominate northern temperate and montane boreal forests on mountains in the northeastern United States. Data were collected on elevational transects spaced at 100m-intervals of elevation on ten mountains. Associated environmental variables, including vegetation cover, substrate, microclimate, and light environment, were also collected.
Accounting for local temperature effect substantially alters afforestation patterns - data
<p>Output data produced in "Accounting for local temperature effect substantially alters afforestation patterns"</p> <p>Contact: michael.gregory.windisch@alumni.ethz.ch</p> <p>Content: Output of the partial equilibrium model MAgPIE (https://github.com/magpiemodel/magpie) version v4.3.1-BGP (https://github.com/magpiemodel/magpie/tree/v4.3.1-BGP) documentation (<a href="https://rse.pik-potsdam.de/doc/magpie/4.3.1/">https://rse.pik-potsdam.de/doc/magpie/4.3.1/</a>). Archived are all runs performed to obtain data and figures for the main assessment (main_output.zip) and the two sensitivity experiments (sensitivity_output_globalTCRE.zip; sensitivity_output_plantation.zip).</p> <p> </p> <p>Naming key:</p> <p>main_output control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS</p> <p>main_output experiment runs: BPHfillexp_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS</p> <p>sensitivity analysis for global TCRE control runs: BPHfillexp_ann_nobgp_{SSP}_noBECCS</p> <p>sensitivity analysis for global TCRE experiment runs: BPHfillexp_ann_bph_{SSP}_global_{TCRE uncertainty}_noBECCS</p> <p>sensitivity analysis for plantation A/R control runs: BPH_plant_nobgp_{SSP}_noBECCS</p> <p>sensitivity analysis for plantation A/R experiment runs: BPH_plant_ann_bph_{SSP}_local_{TCRE uncertainty}_noBECCS</p>
A New Method for Accurate and Efficient Modeling of the Local Ocean Induction Effects. Application to Long-Period Responses from Island Geomagnetic Observatories
<p>Dataset presented in Figures 3-7, S1 and S3 in the recently submitted AGU paper "A New Method for Accurate and Efficient Modeling of the Local Ocean Induction Effects. Application to Long-Period Responses from Island Geomagnetic Observatories".</p>
Contrasting effects of host or local specialization: widespread haemosporidians are host generalist whereas local specialists are locally abundant
<p><strong>Aim: </strong>Despite the wide distribution of many parasites around the globe, the range of individual species varies significantly even among phylogenetically related taxa. Since parasites need suitable hosts to complete their development, parasite geographical and environmental ranges should be limited to communities where their hosts are found. <span><span>Parasites may also suffer from a trade-off between being locally abundant or widely dispersed</span></span>. We hypothesize that the geographical and environmental ranges of parasites are negatively associated to their host specificity and their local abundance.</p> <p><strong>Location: </strong>Worldwide</p> <p><strong>Time period: </strong>2009 to 2021</p> <p><strong>Major taxa studied: </strong>Avian haemosporidian parasites</p> <p><strong>Methods:</strong> We tested these hypotheses using a global database which comprises data on avian haemosporidian parasites from across the world. For each parasite lineage, we computed five metrics: phylogenetic host-range, environmental range, geographical range, and their mean local and total number of observations in the database. Phylogenetic generalized least squares models were ran to evaluate the influence of phylogenetic host-range and total and local abundances on geographical and environmental range. In addition, we analysed separately the two regions with the largest amount of available data: Europe and South America.</p> <p><strong>Results: </strong>We evaluated 401 lineages from 757 localities and observed that generalism (i.e. phylogenetic host range) associates positively to both the parasites' geographical and environmental ranges at global and Europe scales. For South America, generalism only associates with geographical range. Finally, mean local abundance (mean local number of parasite occurrences) was negatively related to geographical and environmental range. This pattern was detected worldwide and in South America, but not in Europe.</p> <p><strong>Main Conclusions:</strong> We demonstrate that parasite specificity is linked to both their geographical and environmental ranges. The fact that locally abundant parasites present restricted ranges, indicates a trade-off between these two traits.<span><span> This trade-off, however, only becomes evident when sufficient heterogeneous host communities are considered.</span></span></p>
Figure 5 in Effect of season and housing systems on various physiobehavioral attributes of local breed of rabbits (Oryctolagus cuniculus) in Southern Punjab, Pakistan
Figure 5. Effect of seasons on TSL of male rabbits under cage system. Data is mean (± SE) and different letters on the bars depict statistical difference at (p ≤ 0.05) for seasons.
Figure 4 in Effect of season and housing systems on various physiobehavioral attributes of local breed of rabbits (Oryctolagus cuniculus) in Southern Punjab, Pakistan
Figure 4. Effect of housing system on various physiological attributes of rabbits. Data is mean (± SE). Similar letters on the bars indicate non-significant (p ≥ 0.05) difference within caged and colony reared rabbits for rectal temperature. Different letters on the bars indicate significant (p ≤ 0.05) difference within caged and colony reared rabbits for respiration rate.
Short-term effects of sound localization training in virtual reality
<p>This repository contains the dataset and software used in the submission to Scientific Reports entitled "Short-term effects of sound localization training in virtual reality".</p> <p>A README.txt file is included, which describes the contents of the repository.</p> <p>Please note that the authors were not granted permission to redistribute the LIMSI Spatialization Engine, which was used to spatialize the sounds described in the manuscript. Please contact the author(s) for details.</p>
Figure 1. Map showing the localities where F in Effects of genetic relatedness, spatial distance, and context on intraspecific aggression in the red wood ant Formica pratensis (Hymenoptera: Formicidae)
Figure 1. Map showing the localities where F. pratensis colonies were sampled for the analysis of genetic relatedness and tested for their aggressive behavior towards each other. The numbers denote the localities. 1: Balaban village (N 41°49ʹ18ʺ, E 27°40ʹ44ʺ) containing three nests; B1, B2, and B3, 2: Asilbeyli village (N 41°39ʹ32ʺ, E 27°13ʹ50ʺ), one nest (As), 3: Ulukonak village (N 41°39ʹ35ʺ, E 27°01ʹ52ʺ) one nest (U), 4: Doğanköy village (N 41°56ʹ12ʺ, E 26°41ʹ20ʺ) one nest (D), and 5: Ahmetler village (N 42°00ʹ37ʺ, E 27°11ʹ12ʺ), three nests; Ah1, Ah2, and Ah3.
Fig. 1 in Bird diversity in an urban ecosystem: the role of local habitats in understanding the effects of urbanization
Fig. 1. Bird species richness and overall abundance recorded in point counts (surveyed on September 2013) in the municipality of Canoas, Rio Grande do Sul, Brazil.
Fig. 2 in Bird diversity in an urban ecosystem: the role of local habitats in understanding the effects of urbanization
Fig. 2. Ordination diagram presenting the first two axes of the Canonical Correspondence Analysis (CCA) (percent of explained variability: axis I = 7.1%, axis II = 1.9%) based on the distribution of species abundance in 118 sample units (dots) in the urban area of Canoas, Rio Grande do Sul, Brazil, and its correlation with seven explanatory variables (arrows). The first axis shows the urbanization gradient (negatives values on left = more urbanized regions; positive values on right = less urbanized regions). All axes were significant (Monte Carlo test with 9,999 permutations: P <0.001). Species names are given in full in Appendix 1. Variables are described in Tab. I.
FIGURE 6 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 6 | Relationship between forest cover and the functional richness index observed in streams located in the Tanguro Farm, municipality of Querência, state of Mato Grosso. Forest cover is represented by the Axis I of the PCA performed with land use variables obtained from a 60 m buffer. Sites 1, 2 and 3 overlapped and were rearranged for better visualization.
FIGURE 5 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 5 | Relationship between species composition and the first PCA axis, ordinated by a Principal Coordinate Analysis. Lighter colors represent sample points with less forest cover. The species corresponding to the codes are in Tab. 2.
FIGURE 4 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 4 | Relationship between forest cover and the physical integrity index of streams located in the Tanguro Farm, Municipality of Querência, state of Mato Grosso. Forest cover is represented by the Axis I of the PCA performed with land use variables obtained from a 60 m buffer. Sites 1, 2 and 3 overlapped, and were rearranged for better visualization. Sgrid: Site.
FIGURE 2 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 2 | Principal component analysis performed with the percentages of land use in 60 m riparian buffers in the catchment of nine streams located in the Tanguro Farm, Municipality of Querência, state of Mato GrossoT. Sites 1, 2, and 3 overlapped, and were rearranged for better visualization. Sgrid: Site.
FIGURE 7 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 7 | Distribution of functional groups related to forest cover loss in Amazonian streams, state of Mato Grosso. OS: Opportunistic strategy; ES: Equilibrium strategy. Forest cover values vary from green (more forest cover) to yellow (less forest cover).
FIGURE 1 in Local effects of deforestation on stream fish assemblages in the Amazon-Savannah transitional area
FIGURE 1 | Location of the nine streams sampled in the dry season of 2017, Tanguro Farm, state of Mato Grosso, Brazil.
Geometry models of specimens: Micro-CT, Mechanical, and Histological Examination of the Effect of Local Adjuvants on Porcine Cortical Bone Following Intralesional Curettage of Bone Tumors.
<p>Bone samples for micro CT measurements and reconstructed bone geometry from micro CT data.</p>
Local vs. site-level effects of algae on coral microbial communities
<p>Microbes influence ecological processes, including the dynamics and health of macro-organisms and their interactions with other species. In coral reefs, microbes mediate negative effects of algae on corals when corals are in contact with algae. However, it is unknown whether these effects extend to larger spatial scales, such as at sites with high algal densities. We investigated how local algal contact and site-level macroalgal cover influenced coral microbial communities in a field study at two islands in French Polynesia, Mo'orea and Mangareva. At 5 sites at each island, we sampled prokaryotic microbial communities (microbiomes) associated with corals, macroalgae, turf algae, and water, with coral samples taken from individuals that were isolated from or in contact with turf or macroalgae. Algal contact and macroalgal cover had antagonistic effects on coral microbiome alpha and beta diversity. Additionally, coral microbiomes shifted and became more similar to macroalgal microbiomes at sites with high macroalgal cover and with algal contact, although the microbial taxa that changed varied by island<i>.</i> Our results indicate that coral microbiomes can be affected by algae outside of the coral's immediate vicinity, and local- and site-level effects of algae can obscure each other's effects when both scales are not considered. </p>
The effect of shear strain and shear localization on fault healing
<p>This is the ReadMe file corresponding to the study entitled:<br> "The effect of shear strain and shear localization on fault healing"<br> By Noël C., Giorgetti C., Collettini C. and Marone C.</p> <p>This Read-Me file has been last edited in August 2023</p> <p>This readme file describes the data repository and supplementary files accompanying the above publication. <br> For any further queries please contact corentin.noel@geoazur.unice.fr</p>
Effects of local density dependence and temperature on the spatial synchrony of marine fish populations
<ol> <li><span>Disentangling empirically the many processes affecting spatial population synchrony is a challenge in population ecology. Two processes that could have major effects on the spatial synchrony of wild population dynamics are density dependence and variation in environmental conditions like temperature. Understanding these effects is crucial for predicting the effects of climate change on local and regional population dynamics.</span></li> <li><span>We quantified the direct contribution of local temperature and density dependence to spatial synchrony in the population dynamics of nine fish species inhabiting the Barents Sea. First, we estimated the degree to which the annual spatial autocorrelations in density are influenced by temperature. Second, we estimated and mapped the local effects of temperature and strength of density dependence on annual changes in density. Finally, we measured the relative effects of temperature and density dependence on the spatial synchrony in changes in density. </span></li> <li><span>Temperature influenced the annual spatial autocorrelation in density more in species with greater affinities to the benthos and to warmer waters. Temperature correlated positively with changes in density in the eastern Barents Sea for most species. Temperature had a weak synchronising effect on density dynamics, while increasing strength of density dependence consistently desynchronised the dynamics. </span></li> <li><span>Quantifying the relative effects of different processes affecting population synchrony is important to better predict how population dynamics might change when environmental conditions change. Here, high degrees of spatial synchrony in the population dynamics remained unexplained by local temperature and density dependence, confirming the presence of additional synchronizing drivers, such as trophic interactions or harvesting. </span></li> </ol>
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.