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Fig. 4 in Interpreting the condition of the forest environment with use of the SCP/MIB model of carabid communities (Coleoptera: Carabidae)
Fig. 4. The effect of unevenaged forest stands fires on their Carabidae communities in Ostrow Mazowiecka
Fig. 5 in Interpreting the condition of the forest environment with use of the SCP/MIB model of carabid communities (Coleoptera: Carabidae)
Fig. 5. The effect of unevenaged forest stands fires on their Carabidae communities in Solec Kujawski
Fig. 3 in Interpreting the condition of the forest environment with use of the SCP/MIB model of carabid communities (Coleoptera: Carabidae)
Fig. 3. The SCP/MIB model presenting the development of the Carabidae communities as taking part in the course of the Scots pine forest stands production cycle, in the post arable ground (dotted line) and in the forest soil (solid line). Denotations I. Post arable grounds: A – arable ground, A1 - 2-6- year old forest cultures, A2 - 8-14 year old coppices, Pdc3 - 18-year old coppices, A4 - 25-year-old forest stands, A5 - 33-62-year old forest stands, A6 – old growth (98-year old) forest stands. II. Forest grounds: F1 - 2-3- year old forest cultures, F2 - 6-11- year old coppices, F3 - 18 22-year old forest stands, F4 - 25-42- year old forest stands, F5 - 62-98 year old forest stands.
Figure 3 in Spatiotemporal distribution, abundance, and species-environment relationships of Scyphozoa (Cnidaria) species in Hisarönü, Marmaris, and Fethiye bays (Muğla, Turkey
Figure 3. RDA ordination plot for Scyphozoa species, environmental parameters, sampling months, and stations. Sampling stations in RDA plot indicated with □: Hisarönü 1; ■: Hisarönü 2; O: Marmaris 1; ●: Marmaris 2; ◇: Marmaris 3; ◆: Marmaris 4; ×: Marmaris 5; ∆: Fethiye 1; △: Fethiye 2; ▲: Fethiye 3. Scyphozoa species indicated by the following abbreviations: Aa: Aurelia aurita; Ct: Cotylorhiza tuberculata; Ca: Cassiopea andromeda. Sampling months in RDA plot indicated with: 1: September 2011; 2: October 2011; 3: November 2011; 4: December 2011; 5: January 2012; 6: February 2012; 7: March 2012; 8: April 2012; 9: May 2012; 10: June 2012; 11: July 2012; 12: August 2012; 13: September 2012; 14: October 2012. See Table 4 for abbreviations of environmental variables.
Figure 1Sampling site and stations.1A in Living in the sunlight: micro-environments with higher exposure of sunlight have more abundance and diversity of Hymenoptera in a Brazilian Atlantic Forest fragment
Figure 1Sampling site and stations.1A) Study area including the RAPELD modules.Each black point represents a permanent plot.1B) Trap-nest stations and selected micro-environments: treefall gap (A), placed in wooden post at 1.5m height; understory (B), placed in a tree branch at approximately 1.5 meters height; canopy (C), suspended with thread in a tree (height between 19.0 and 9.1 meters).
Figure 2 in Living in the sunlight: micro-environments with higher exposure of sunlight have more abundance and diversity of Hymenoptera in a Brazilian Atlantic Forest fragment
Figure 2 Interpolation curves of the richness and diversity of trap-nesting Hymenoptera (Atlantic forest, Brazil) in relation to the lowest observed abundance brood cells sampled and assessed for three Hill numbers (0, 1 e 2). CAN= canopy; GAP= treefall gap; UND= Understory.
Figure 5 in Do disturbed environments affect density of the tunnel-web spider Acanthogonatus centralis (Mygalomorphae: Nemesiidae) from native grasslands in Argentina?
Figure 5. Spatial distribution of A. centralis plotted from the four 10 × 10 quadrants during autumn at Cerro Ceferino, Sierra de la Ventana, Argentina. Circles: males; triangles: females; squares: juveniles.
Figure 4 in Do disturbed environments affect density of the tunnel-web spider Acanthogonatus centralis (Mygalomorphae: Nemesiidae) from native grasslands in Argentina?
Figure 4. Seasonal density of A. centralis (spiders/m2). Nonsignificant differences were found among seasons (F: 1.03; P = 0.43).
Figure 1 in Do disturbed environments affect density of the tunnel-web spider Acanthogonatus centralis (Mygalomorphae: Nemesiidae) from native grasslands in Argentina?
Figure 1. Details of the 3 sampling sites in Sierra de la Ventana, Buenos Aires, Argentina. A: Ernesto Tornquist Provincial Park, considered to be at low disturbance level (LD); B: Funke Ranch, considered to be at medium disturbance level (MD); C: Cerro Ceferino, considered to be at high disturbance level (HD).
Fig. 7 in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 7. Non-metric multidimensional scaling based on the Nymphalidae species composition captured in 4 climatic periods—wet (dark blue), dry (red), transition from wet to dry (T.wd, light blue), and transition from dry to wet (T.dw, black)—in 2 habitats, savanna (S) and gallery forest (F) in the Fazenda Água Limpa and the Reserva Ecológica do Roncador, Brasília, DF. A.dem, Archeoprepona demophon; M.hel, Morpho helenor; and P.pol, Pariphthimoides poltys best characterize the T.dw, whereas C.aco, Catonephele acontius; P.oci, Pareupthichia ocirrhoe; and T.lao, Temenis laothoe best characterize the T.wd. Stress: 0.15.
Fig. 6 in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 6. Pielou's evenness values of the Nymphalidae species in the dry and wet seasons and in the transitional periods between these 2 seasons,from wet to dry (T.wd) and from dry to wet (T.dw), in savanna (Cerrado sensu stricto, ss) and forest (gallery forest) habitats in the Fazenda Água Limpa and the Reserva Ecológica do Roncador, Brasília, DF. Different lowercase letters represent significant differences (P <0.05).
Fig. 4. A in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 4. A) Temporal variation in Nymphalidae abundance captured in the dry and wet seasons and in the 2 transitional periods between those seasons, from wet to dry (T.wd) and from dry to wet (T.dw), in savanna (Cerrado sensu stricto, ss) and forest (gallery forest) habitats of the Fazenda Água Limpa and the Reserva Ecológica do Roncador, Brasília, DF. The box plots show the differences between the 4 climatic periods, considering B) the total butterfly abundance (gallery forest + savanna), and that C) in the gallery forest and D) in the savanna separately. Different lowercase letters represent significant differences (P <0.05).
Fig. 3 in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 3. Circular analysis of the number of individuals reflecting the abundance of the different Nymphalidae subfamilies and tribes captured from Jul 2012 to Jun 2013 in the Fazenda Água Limpa and Reserva Ecológica do Roncador. In this analysis, each column's length represents the observed abundance and the arrow the tendency of the highest abundance.
Fig. 2 in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 2. Circular analysis of the number of individuals reflecting the abundance of Nymphalidae captured from Jul 2012 to Jun 2013 in the Fazenda Água Limpa and Reserva Ecológica do Roncador. In this analysis, each column's length represents the observed abundance and the arrow the tendency of the highest abundance.
Fig. 1. Rarefaction curves, generated with 1,000 in Temporal dynamics of fruit-feeding butterflies (Lepidoptera: Nymphalidae) in two habitats in a seasonal Brazilian environment
Fig. 1. Rarefaction curves, generated with 1,000 randomizations without replacement, based on the MauTau (Sobs, black circles) and "total" estimated (Jackknife 1, gray circles) values. The data of Nymphalidae species richness was acquired from Jul 2012 to Jun 2013 in the Fazenda Água Limpa and the Reserva Ecológica do Roncador, Brasilia, DF.
Figure 1 in Life in the extreme environment: Structure and species richness of bird assemblages on Yuzhny Island of Novaya Zemlya, Russia
Figure 1. Study region on Yuzhny Island of Novaya Zemlya. (A) Map of Novaya Zemlya. The yellow circle indicates the study region of Yuzhny Island. (B) Detailed map of the study region with the location of counting routes. The shaded area represents the study area (1). The dashed red lines indicate the counting routes (2). The dashed black line indicates the helicopter route (3).
Figure 4 in Life in the extreme environment: Structure and species richness of bird assemblages on Yuzhny Island of Novaya Zemlya, Russia
Figure 4. Relative bird species abundance (log10 scale) over habitat patches on Yuzhny Island of Novaya Zemlya. Numbers of (01) – (10) are the codes of the habitat types. Differences between assemblages were all significant (Kruskal-Wallis test: p = 0.003). Images show habitat types; numbers indicate their codes (see Table 2 for detail). (Photos: V. M. Spitsyn).
Figure 3 in Life in the extreme environment: Structure and species richness of bird assemblages on Yuzhny Island of Novaya Zemlya, Russia
Figure 3. Species diversity of bird assemblages on Yuzhny Island of Novaya Zemlya. (A) Bi-plot of detrended correspondence analysis (DCA) with supplementary variables, showing the ordination of species and environmental variables. Circles indicate bird species abundance (categorical estimations by using a logarithmic scale, see Table 3), abundances decrease with increasing distance from each point in a unimodal fashion (ter Braak and Smilauer, 2002). Data represent independent samples from various habitats (n = 10). Total variation is 2.44, supplementary variables account for 66.1% (adjusted explained variation is 23.8%). Eigenvalues (lambda) are 0.675, 0.162, 0.069, and 0.025 for first (horizontal), second (vertical), third and fourth axes, respectively. The first two axes explain 34.4% of the variation. The pseudo-canonical correlations of bird abundance and environmental variables for axes 1 and 2 are 0.77 and 0.91, respectively. For an explanation of environmental variables, see Table 4. For abbreviations of species names see Fig. 4. (B) Bi-plot of the same analysis revealing the ordination of species richness over a range of habitats and environmental variables. Circles indicate bird assemblages in primary types of habitats (size of each circle corresponds to the number of bird species). The red numbers near the circles indicate species richness. The black numbers near the circles (01–10) indicate the codes of habitat types (see Fig. 4 and Table 2 for detail).
Figure 9 in The impact of wildfires on the Lake Skadar/Shkodra environment
Figure 9. Flooded burnt areas near the island of Vranjina in the northern part of Lake Skadar/Shkodra (photographed on October 3, 2020). Photo by V. Pešić.
Figure 8 in The impact of wildfires on the Lake Skadar/Shkodra environment
Figure 8. Burnt areas (brown patches) resulted from wildfires southeastward of Lake Šas are shown for (a) 11 September, (b) 13 September and (c) 21 September 2020 (MSI Sentinel-2). Yellow arrow shows zoom on the selected area marked by yellow square.
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.