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7,883 results for “tropics.”
Fig. 2 in Ikedosoma (Annelida: Echiura: Thalassematidae) from the Tropical Pacific, with Description of a New Species
Fig. 2. Comparison of morphology around the basal proboscis among three species of Ikedosoma (ventral view). Arrowheads indicate mouth position to show lower lip absence (B) or presence (C, D). A, B, Ikedosoma abemama sp. nov., preserved specimen (holotype, NSMT- Ec 187); C, I. elegans, live specimen (non-type, NSMT-Ec 113); D, I. gogoshimense, live specimen (non-type, NSMT-Ec 116). Scales: A, C, D, 1 cm; B, 2 mm.
Fig. 1 in Ikedosoma (Annelida: Echiura: Thalassematidae) from the Tropical Pacific, with Description of a New Species
Fig. 1. Ikedosoma abemama sp. nov. (holotype, NSMT-Ec 187). A, lateral view of the entire body, before dissection; B, dorsal view of the dissected trunk showing musculature (with aid of light box); C, magnified trunk wall showing two longitudinal muscle bands (marked by asterisks) and the continuous oblique muscle layer between them. Scales: A, B, 1 cm; C, 1 mm.
Fig. 5 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 5. (left column) Distribution-based Redundancy Analysis (db-RDA) ordination diagram of Lake Chapala with environmental variables (thick arrows), atherinopsids species (italic letters), sampling sites (numbers), and principal coordinates axes (thin arrows) at dry season (a: May of 1999) and rainy season (b: August of 1999; c: 2000). The fish are: jordani = Chirostoma jordani; consocium = Chirostoma consocium; labarcae = Chirostoma labarcae. The environmental variables are: Temp = temperature, DO = dissolved oxygen, Sal = salinity. In figure 5c shallow sites are in italic and deep sites in regular.
Fig. 3 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 3. GAM results for May and August of site influence on fish density to show differential distribution of species in Lake Chapala. a: Chirostoma jordani; b: Chirostoma consocium; c: Chirostoma labarcae. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).
Fig. 2 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 2. GAM results for May of environmental characteristics influence on fish density. a: effect of depth (m) on Chirostoma jordani; b: effect of temperature (°C) on C. jordani; c: effect of salinity on C. consocium. Circles represent the residuals. Spline fit (solid line) is bound by 95% confidence intervals (dotted lines).
Fig. 1 in Spatial patterns of zooplanktivore Chirostoma species (Atherinopsidae) during water-level fluctuation in the shallow tropical Lake Chapala, Mexico: seasonal and interannual analysis
Fig. 1. Map of Lake Chapala, Mexico. Numbers in bold represent sample sites and numbers in italic lake depths.
Fig. 1 in Dynamics of fish assemblages on a continuous rocky reef and adjacent unconsolidated habitats at Fernando de Noronha Archipelago, tropical western Atlantic
Fig. 1. Map of the Fernando de Noronha Archipelago showing the study area (Porto Beach) and permanent sampling stations.
Fig. 3 in Dynamics of fish assemblages on a continuous rocky reef and adjacent unconsolidated habitats at Fernando de Noronha Archipelago, tropical western Atlantic
Fig. 3. Canonical plotting of microhabitat characteristics (arrows) and fish species (points). Rug.: rugosity; Crev.: number of crevices; S. height: substratum height; C. algae: percent cover of encrusting coralline algae; Macr.: percent cover of Macroalgae; Turf: percent cover of turf algae; L. coral: percent cover of live coral; Other: percent cover of other organisms; B. rock: percent cover of bare rock; Sand: percent cover of sand and limestone; IHC: index of habitat complexity; Species names are abbreviated as the first three letters of genus and first three letters of specific epithet (see Table 4 for full scientific names).
Fig. 3 in The "Southern form" of short-finned pilot whale (Globicephala macrorhynchus) in tropical west Pacific Ocean off Taiwan
Fig. 3. Genealogical relationship reconstructed by the medianjoining algorithms via the mtDNA haplotype data for short-finned pilot whales from: A, Taiwanese and Philippines waters (593-bp sequence); B, Worldwide (345-bp sequence). Each circle represents a haplotype and the number in the circle indicates the sample size (when sample size> 1). The number at the bar between each haplotype indicates the position of variable site (Table 3). Haplotypes, sample size, and origin for worldwide data in B from Oremus et al., 2009. Haplotype N is the haplotype most closelyrelated to those long-finned pilot whales (six mutation steps; see Oremus et al., 2009).
Fig. 2 in The "Southern form" of short-finned pilot whale (Globicephala macrorhynchus) in tropical west Pacific Ocean off Taiwan
Fig. 2. Short-finned pilot whales sighted around Taiwan—offshore and beached on the coasts of Taiwan—showing two external morphological characteristics that define the Southern form (Kasuya et al., 1988). A, the post-fin dorsum was uniformly black in all whales observed, four shown here from group of about 30 whales (O8, Table 1), a lighter coloured saddle patch was not seen; B, a male with flattened forehead ("square-head", arrow) from another group of about 90 whales (O19, Table 1), and indistinct lighter coloured mottling over post-fin dorsum (the saddle patch area) on two other whales; C, carcass of a fresh adult male stranded on the west coast of Taiwan (S7) showing a flattened forehead and the lack of a clear post-fin saddle patch, characteristic of the Southern form.
Fig. 1 in The "Southern form" of short-finned pilot whale (Globicephala macrorhynchus) in tropical west Pacific Ocean off Taiwan
Fig. 1. Sighting observation (open triangles) and stranding (solid circles) locations of short-finned pilot whales around the coasts of Taiwan (1998–2012). See Tables 1 and 2 for event codes; sighting or stranding events without a detail location record (i.e., GPS position) were not indicated in the map. The star locates a group sighting near the Dongsha plateau recorded on video-clip (see text; Supplement A).
Data for "Do electric vehicles mitigate urban heat? The case of a tropical city"
<p>This dataset contains the underlying data used in the publication "Do electric vehicles mitigate urban heat? The case of a tropical city", which is under review in <em>Front. Environ. Sci. .</em></p> <p>The dataset includes two folders:</p> <p>1. <strong>data</strong> <br> Include COSMO-DCEP-BEP model inputs and output needed to reproduce the results in the manuscript (NetCDF). </p> <p>2. <strong>script</strong><br> Include post-processing scripts used to generate the figures in the manuscript (Jupiter Python 3 Notebook).</p> <p><em> </em></p>
Contributions of Anomalous Large-Scale Circulations to the Absence of Tropical Cyclones over the Western North Pacific in July 2020
<p>The datasets are for the article 'Contributions of Anomalous Large-Scale Circulations to the Absence of Tropical Cyclones over the Western North Pacific in July 2020', including the WRF Initial conditions (horizontal wind at 850 hPa, geopotential height at 850 and 200 hPa) of sensitivity experiments (CTRL, W_WNPSH, W_SAH, W_TUTT, and S_SASM) in July 2020, and the formation records of the simulated TC formation in all experiments.</p>
Stronger negative species interactions in the tropics supported by a global analysis of nest predation in songbirds
<p>Original data, phylogeny and list of studies from: "Stronger negative species interactions in the tropics supported by a global analysis of nest predation in songbirds"</p>
Data set: Land use and land cover change in a tropical mountain landscape of northern Ecuador: altitudinal patterns and driving forces
<p>Tropical mountain ecosystems are threatened by land use pressures, compromising their capacity to provide multiple ecosystem services. The analysis of landscape changes and their proximate driving forces is often qualitative and sectorial oriented, although local patterns and numerous interactions among socio-economic, demographic, and biophysical factors shape these socio-ecological systems. We characterized land use land cover (LULC) dynamics using Markov-chain probabilities by elevation and geographic settings and then, implementing the DPSIR holistic approach, we integrated them with a variety of freely available geospatial and temporal data into a Generalized Additive Model (GAM) to uncover the factors driving such landscape dynamics in a sensitive region of the northern Ecuadorian Andes. Our results demonstrated a dynamic and clear geographical pattern of distinct LULC transitions through time, explained by different combination of socio-economic factors, demographic and infrastructure variables and environmental parameters, from which topographic variables were the main drivers of change in this landscape. We found that deforestation of remnant native forest and agricultural expansion still occur in higher elevations, while land conversion toward anthropic environments, particularly significant expansion of floriculture and urban areas were observed in lower elevations to the east of the studied territory. Our findings also revealed an unexpected stability trend of paramo and a successional recovery of previous agricultural land to the west and center of the territory, which could be explained by agricultural land abandonment. However, the very low probability of persistence of montane forests found overall, highlights the greater threat to permanently lose the already vulnerable mountain native biodiversity. The methodological approach and our findings, demonstrating dynamic patterns through space and time and their explanatory drivers, could help local authorities and stakeholder to improve sustainably resource land management in vulnerable landscapes such as the tropical Andes in northern Ecuador.</p>
Data for: Trap type affects dung beetle taxonomic and functional diversity in Bornean tropical forests
<p>Dung beetle community composition data. Data was collected using either dung-baited pitfall traps or flight interception traps. Each row represents one trap, with the author/study information, name of study site, sampling period, trap type and habitat type. Dung beetle species and their abundances are listed. See "metadata" tab for more details.</p> <p>Paper abstract: Baited pitfall traps (BPTs) and flight intercept traps (FITs) are the most common methods employed for sampling dung beetle communities. These methods vary in their efficacy and are affected by factors such as the bait types used and the dispersal abilities of different dung beetle species. We present the first quantitative comparison of the taxonomic and functional diversity, and community composition of dung beetles caught in BPTs and FITs in Bornean tropical forests. We show that BPTs and FITs captured complementary communities with different functional traits, and that BPTs captured more functionally diverse communities. We therefore recommend using a combination of both baited BPTs and FITs for studies assessing the composition of dung beetles across habitat types. Our results also highlight that it is important to consider how trap type affects the trait composition of communities when relating dung beetle communities and functional traits to ecological functioning. We suggest modifications to FITs based on the design of harp traps to increase their effectiveness in capturing larger-bodied beetles.</p>
Fig. 5 in Four new species of Sabicea (Rubiaceae) from tropical Africa, with additional notes on the genus
Fig. 5. – Sabicea ezangae Zemagho, O. Lachenaud & Sonké. A. Flowering stem; B. Detail of lower leaf surface; C. Node and stipules; D. Inflorescence; E. Flower; F. Flower, longitudinal section. [Lachenaud et al. 1544, BR & BRLU] [Drawing: A. Fernandez]
Fig. 7 in Four new species of Sabicea (Rubiaceae) from tropical Africa, with additional notes on the genus
Fig. 7. – Sabicea uniflora Zemagho, O. Lachenaud & Sonké. A. Flowering stem; B. Node and stipules. C. Inflorescence; D. Longitudinal section of flower; E. Inflorescence (corolla removed). [Wieringa et al. 4567, BR] [Drawing: A. Fernandez]
Acoustic lures increase tropical forest understorey bat captures
<p>Data used in the publication "Effectiveness of acoustic lures for increasing tropical forest understorey bat captures".</p>
Sowing storms: how model timestep can control tropical cyclone frequency in a GCM
<p>Supplementary dataset to JAMES article "Sowing storms: how model timestep can control tropical cyclone frequency in a GCM" DOI:10.1029/2021MS002791</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.