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Figure 4 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 4. Means comparison of shannon-wiener index of oribatid mites in four systems (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman-Keuls test).
Figure 3 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 3. Means comparison of diversity of oribatid mites in sampling times (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman-Keuls test).
Figure 2 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 2. Means comparison of species richness of oribatid mites in four systems (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman.
Figure 1 in Relative abundance of oribatid mites (Sarcoptiformes: Oribatida) in two tillage systems of irrigated and rain-fed wheat farms of Khodabandeh County, Iran
Figure 1. Means comparison of species richness of oribatid mites in sampling times (Different letters on the top of the bars indicate significant difference at P <0.05 by Student Newman–Keuls test).
Fig. 5 in Barn Swallows Hirundo rustica in Peninsular Malaysia: urban winter roost counts after 50 years, and dietary segregation from house-farmed swiftlets Aerodramus sp.
Fig. 5. Diet distribution of swallows and house-farmed swiftlets at Bentong identified by NGS molecular analysis.
Fig. 1 in Barn Swallows Hirundo rustica in Peninsular Malaysia: urban winter roost counts after 50 years, and dietary segregation from house-farmed swiftlets Aerodramus sp.
Fig. 1. (Left) Map of Peninsular Malaysia, with an enlarged plan of Pahang State; the circle indicates the study area, Bentong District. (Right) Google view of Bentong municipality, showing old town centre (red) and suburbs where house-farmed swiftlet colonies (blue) were counted.
Fig. 2 in Barn Swallows Hirundo rustica in Peninsular Malaysia: urban winter roost counts after 50 years, and dietary segregation from house-farmed swiftlets Aerodramus sp.
Fig. 2. Swallows roosting on utility wires along streets of the Bentong town centre. Pacific Swallows, recognisable from below by the grey belly, were present in very low numbers during the passage and wintering period.
Fig. 4 in Barn Swallows Hirundo rustica in Peninsular Malaysia: urban winter roost counts after 50 years, and dietary segregation from house-farmed swiftlets Aerodramus sp.
Fig. 4. Comparative diets of swallows and house-farmed swiftlets in Bentong, identified by morphological analysis.
Fig. 3 in Barn Swallows Hirundo rustica in Peninsular Malaysia: urban winter roost counts after 50 years, and dietary segregation from house-farmed swiftlets Aerodramus sp.
Fig. 3. Number of Barn Swallows in the urban roost in Bentong town, Pahang, in 2015–16 and averaged for 1966–68.
Fig. 2 in Genetic diversity among white-nest swiftlets of the genus Aerodramus (Aves: Apodidae: Collocaliini) of house-farms in Malaysia
Fig. 2. Schematic diagram of the mitochondrial cyt-b region sequenced in the previous and present studies. Dark bands on the grey strip indicate the location of the five clade-specific sites.
Fig. 1 in Genetic diversity among white-nest swiftlets of the genus Aerodramus (Aves: Apodidae: Collocaliini) of house-farms in Malaysia
Fig. 1. One of the six equally parsimonious trees rooted with Collocalia esculenta. Bootstrap values shown above the nodes. Posterior probabilities from Bayesian Inference shown below the nodes.
Figure 5 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 5. Vigtorniella spp. Haplotype network of cytochrome c oxidase subunit I (COI). Each large circle represents a sequence from an individual of Vigtorniella ardabilia that has been collected in Sweden (white) or Norway (grey). Black circles represent V. flokati, collected in the Pacific Ocean, three specimens sampled sharing the same haplotype. Letters in circles, A-G, represent haplotypes of V. ardabilia sampled in this study (Table 1). Each line represents a mutation and small empty circles are inferred haplotypes not present in the current study.
Figure 4 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 4. Vigtorniella ardabilia sp. nov., specimen from whale-fall in Sweden, light micrographs: (A) parapodia from mid-body region, (B) detail of neuropodial falcigers, (C) detail of notopodial spine. Scale bar in (A) is 100 Mm, in (B) and (C) 10 Mm.
Figure 3 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 3. Vigtorniella ardabilia sp. nov., specimen from whale-fall in Sweden. SEM micrographs of (A) head region dorsal view, (B) head region ventral view, (C) fine neuropodial falcigers from segment 2, (D) neuropodial falcigers from mid-body region, and (E) notopodial spine. Scale bars in (A) and (B) are 150 Mm, in (C) 7.5 Mm, in (D) 15 Mm and in (E) 6 Mm.
Figure 2 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 2. Vigtorniella ardabilia sp. nov., live photo of specimen from whale-fall in Sweden. The worm is 6 mm long.
Figure 3 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 3. Relationship between the number of chaetigers and total bodylength in 15 specimens of Vigtorniella ardabilia and 33 specimens of V. flokati.
Figure 6. Diagram showing Kimura 2 in Cryptic speciation at organic-rich marine habitats: a new bacteriovore annelid from whale-fall and fish farms in the North-East Atlantic
Figure 6. Diagram showing Kimura 2 Parameter (K2P)-distances between congeneric species in four chrysopetalid genera, for two nuclear genes (18S, 28S) and two mitochondrial genes (16S, cytochrome c oxidase subunit I (COI)).
Farm and regional levels' database used to test the effectiveness of slope and distance from buildings in approximating the pastoral site-use intensity of alpine pastures
<p>The excel file contains the two databases used in the paper “Slope and distance from buildings are easy-to-retrieve proxies for estimating livestock site-use intensity in alpine summer pastures” to test the effectiveness of slope and distance from buildings in approximating the pastoral site-use intensity of alpine pastures.</p> <p>The database in the ‘farm level’ sheet has been used to assess if slope and distance from buildings were good predictors of site-use intensity at farm level, i.e. the number of GPS locations counted within sample units was modelled as a function of the two proxies. Moreover, this database has been used to evaluate if the expected transition of Vegetation Ecological Groups (VEGs) from the shrub-encroached to the nitrophilous ones corresponded to a real site-use intensity gradient as represented by the stocking rates measured through GPS locations, i.e. by modelling the total number of GPS locations within sample units in function VEGs.</p> <p>The database in the ‘Regional level’ sheet has been used to evaluate if the five VEGs were effectively discriminated by distance from buildings and slope. Two models were performed by specifying either slope and distance from buildings as response variables and VEG as fixed factor.</p>
Scottish hill farming score by agricultural parishes
<p>Dataset to accompany work on the impact of hill farming in Scotland commissioned by RESAS (Scottish Government). Data resolution is agricultural parishes, spatial data defining these can be downloaded from <https://data.gov.uk/dataset/939fdd5e-7322-4ab7-9dc9-bbfc538c4477/agricultural-parishes>.</p> <p>Data used to define the hill farming score is derived from the following datasets: Ordnance Survey Terrain 50; Scottish Natural Heritage, landscape character assessment, carbon and peatland map; James Hutton Institute land capability for agriculture; RESAS agricultural census common and rough grazing areas.</p> <p>Licence statements for input data are:</p> <p>Derived from or contains: Scottish Government and SNH information licensed under the Open Government Licence v3.0; James Hutton Institute materials licensed under the Open Government Licence v.2.0; and Ordnance Survey data Crown copyright and database right 2018.</p> <p>Generation code can be found here: https://doi.org/10.5281/zenodo.1887477</p>
Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm - Manuscript data
<p>Time averaged power and farm inflow velocity for the manuscript "Comparison of Large Eddy Simulations against measurements from the Lillgrund offshore wind farm" for publication in the wind energy science journal. Data is uploaded for the 5 simulation cases covered.</p> <p>'Power' files contain average power production for 48 turbines. First row corresponds to LES data, second row corresponds to SCADA data from the Lillgrund wind farm.</p> <p>'Velocity' files contain inflow mean velocity measurements at the 72 range gate locations. First row corresponds to LES inflow data, second row corresponds to LIDAR inflow data from the Lillgrund wind farm.</p>
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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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.