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7,883 results for “tropics.”
Functional genomics and co-occurrence in a diverse tropical tree genus: The roles of drought and defense related genes
<p>Tropical tree communities are among the most diverse in the world. A small number of genera often disproportionately contribute to this diversity. How so many species from a single genus can co-occur represents a major outstanding question in biology. Niche differences are likely to play a major role in promoting congeneric diversity, but the mechanisms of interest are often not well-characterized by the set of functional traits generally measured by ecologists. To address this knowledge gap, we used a functional genomic approach to investigate the mechanisms of co-occurrence in the hyper-diverse genus <em>Ficus</em>. Our study focused on over 800 genes related to drought and defense, providing detailed information on how these genes may contribute to the diversity of <em>Ficus</em> species. We find widespread and consistent evidence of the importance of defense gene dissimilarity in co-occurring species, providing genetic support for what would be expected under the Janzen-Connell mechanism. We also find that drought-related gene sequence similarity is related to <em>Ficus</em> co-occurrence, indicating that similar responses to drought promote co-occurrence. We provide the first detailed functional genomic evidence of how drought- and defense-related genes simultaneously contribute to the local co-occurrence in a hyper-diverse genus. Our results demonstrate the potential of community transcriptomics to identify the drivers of species co-occurrence in hyper-diverse tropical tree genera.</p>
Figure 2. – A in First record of Carolines parrotfish (Calotomus carolinus) and king angelfish (Holacanthus passer) around the Clipperton Atoll-La Passion Island (North-Eastern Tropical Pacific)
Figure 2. – A: Photograph of the female adult individual of Calotomus carolinus with a close up showing the details of the separated teeth (B), that are specific to this species (Photos E. Clua). C: Photograph of the juvenile individual of Holacanthus passer (Photo S. Planes) along with an adult individual (D) (Photo H. Debelius) in its natural environment, showing the specific vertical white stripe, which is present both in adult and juvenile individuals.
Figure 1. – A in First record of Carolines parrotfish (Calotomus carolinus) and king angelfish (Holacanthus passer) around the Clipperton Atoll-La Passion Island (North-Eastern Tropical Pacific)
Figure 1. – A: Clipperton-La Passion Island (France), Tropical Eastern Pacific Ocean. B: Approximative location of the sighting and capture of the adult female individual of Calotomus carolinus (X) and the sighting of the male individual (X') on the 11 and 13 August 2018, respectively. Approximative location of the sighting and capture of the juvenile individual of Holacanthus passer (Y) (maps modified from "Cartes de l'île de la Passion" by C. Jost, 2015).
Alignment and Tree file from: Two novel species of tropical Morchella (Ascomycota, Pezizales, Morchellaceae) discovered in the UNESCO Rinjani Lombok Biosphere Reserve, Indonesia
<p>Alignment and Tree file from: Two novel species of tropical Morchella (Ascomycota, Pezizales, Morchellaceae) discovered in the UNESCO Rinjani Lombok Biosphere Reserve, Indonesia</p>
What do we know about the missing millions of Earth's insect species: evidence from Australian tropical rainforest bark beetles?
<p><span>Only 20% of the estimated five million species of insects on Earth are named despite over 240 years of taxonomy. Yet insects are poorly represented in protected area assessments, and insect declines are of concern globally. Here we explore how to increase the discovery of new species and understanding of this group through analysis of 10,097 tropical rainforest bark beetles (Scolytinae) from eight different ecological studies using beetles between 2000 and 2018 in the Australian Wet Tropics. Of the 107 species identified, 58 are undescribed: an increase of 35% on the 166 species known from Australia. As hypothesised, new species are significantly smaller, less abundant and less widespread than described species making them more extinction prone than named species. Rarefaction indicates doubling sampling would increase the number of species by 17. Flight Interception Traps (FIT) collected 84% of individuals and 98% of species confirming the effectiveness of a single sampling method for some beetles. Increased locations and collection from the canopy may sample further species rather than additional collecting methods.<span> </span>Scolytines are relatively well studied with a cadre of taxonomists at the forefront of using modern methods to resolve formerly intractable groups. These new species are more likely to be named than others in many other beetle groups where taxonomy has largely stalled. To increase species description rates and to avoid most species becoming extinct before being named, we call on taxonomists to use new character systems provided by DNA methods and to look at working with Artificial Intelligence tools.<span> </span></span></p>
F I G U R E 5 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 5 Log–log plot of the relative condition factor (Krel) vs. standard length (cm) calculated from length–weight relationships (LWRs) of the species (a) Argyropelecus affinis, (b) Argyropelecus sladeni, (c) Ceratoscopelus warmingii, (d) Diaphus dumerilii, (e) Electrona risso, (f) Lampanyctus nobilis, (g) Lepidophanes guentheri, (h) Notoscopelus resplendens and (i) Scopelogadus mizolepis (Table 3). Geographic regions are indicated by linetype, symbol and colour (EQ–C, dotted line, dark-blue square; EQ–N, two-dashed line, turquoise triangle; LO–E, solid line, red circle; LO–W, dashed line, violet diamond). If present, vertical dashed grey line indicates breakpoint in the LWR estimated by segmented regression analysis (cf. Table 2)
F I G U R E 1 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 1 Stations in the eastern low-oxygen (LO–E), western low-oxygen (LO–W), northern equatorial (EQ–N) and central equatorial (EQ–C) regions of the eastern tropical North Atlantic sampled in this study
F I G U R E 4 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 4 Distribution of form factor a3.0 for 55 mesopelagic species related to (a) body shape, (b) taxonomic family and (c) species. Form factor calculated from Equation 2 using across-species slope of S = 1.358 based on 1223 fish species presented in equation 17 in Froese (2006)
F I G U R E 3 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 3 Scatter plot of mean log a (SL) over mean b for 55 mesopelagic species with information on body shape. Body shape:, elongated;, fusiform;, short-deep
F I G U R E 2 in Length-weight relationships of 55 mesopelagic fishes from the eastern tropical North Atlantic: Across- and within-species variation (body shape, growth stanza, condition factor)
F I G U R E 2 Frequency distribution of (a) mean log a (binwidth 0.2) and (b) mean exponent b (binwidth 0.1) based on 55 records (measured in centimetres and grams) of mesopelagic species of the eastern tropical North Atlantic during cruise WH383
Fire promotes functional plant diversity and modifies soil carbon dynamics in tropical savanna
<p>The dataset associated with the manuscript "Fire promotes functional plant diversity and modifies soil carbon dynamics in tropical savanna" (Teixeira et al.) includes 6 different datasets, for which we provided one metadata.<br> </p> <p><strong>Version 2</strong> includes an update of the biomass data set, including the correct transformation to g/m2 on fine roots biomass data.<br><br><strong>Version 3 </strong>includes an update of the belowground traits data set based on correcting formatting errors in the belowground traits data. <br><br><strong>Version 4 </strong>Sorry for the inconvenience. This version includes the correct updated belowground traits data file based on the correct formatting errors in the belowground trait data. <br><br>fluxes: it includes data related to net ecosystem C and water exchange. NEE and ET from each plot were measured using the LiCOR 7500 infrared gas analyzer (Li-Cor Inc.). See the method section in the manuscript for full details.</p> <p>soil_carbon: it includes carbon soil data.<br><br>biomass_v2: it includes data related to aboveground and belowground biomass. Aboveground data were collected in 0.5m2 subplot and belowground at 0.25m2 at 20cm depth both within 1m2 sampling plot. See the method section in the manuscript for full details.</p> <p>aboveground_traits: all aboveground functional traits from plant species. See the method section in the manuscript for full details.</p> <p>belowground_traitsv3: all roots functional traits from plant species. See the method section in the manuscript for full details.</p> <p>species_composition: plant community composition. See the method section in the manuscript for full details.</p> <p><br><strong>Abstract</strong><br>Fire is an evolutionary environmental filter in tropical savanna ecosystems altering functional diversity and associated C pools in the biosphere and fluxes between the atmosphere and biosphere. Therefore, alterations in fire regimes (e.g. fire exclusion) will strongly influence ecosystem processes and associated dynamics. In those ecosystems, C dynamics and functions are underestimated by the fire-induced offset between C output and input. To determine how fire shapes ecosystem C pools and fluxes in an open savanna across recently burned and fire excluded areas, we measured the following metrics: (I) plant diversity including taxonomic (i.e. richness, evenness) and plant functional diversity (i.e. functional diversity, functional richness, functional dispersion and community weighted means); (II) structure (i.e. above- and below-ground biomass, litter accumulation); and (III) functions related to C balance (i.e. net ecosystem carbon dioxide (CO<sub>2</sub>)<sub> </sub>exchange (NEE), ecosystem transpiration (ET), soil respiration (soil CO<sub>2</sub> efflux), ecosystem water use efficiency (eWUE) and total soil organic C (SOC). We found that fire promoted aboveground live and belowground biomass, including belowground organs, and coarse and fine root biomass, and contributed to higher biomass allocation belowground. Fire also increased both functional diversity and dispersion. NEE and total SOC were higher in burned plots compared to fire-excluded plots whereas soil respiration recorded lower values in burned areas. Both ET and eWUE were not affected by fire. Fire strongly favored functional diversity, fine root, and belowground organ biomass in piecewise SEM models but the role of both functional diversity and ecosystem structure to mediate the effect of fire on ecosystem functions remain unclear. Fire regime will impact C balance, and fire exclusion may lead to lower C input in open savanna ecosystems.</p>
Evaluation of Upper Tropospheric Geopotential Height Anomalies over the Tropical and Subtropical Oceans in CMIP6 Models Using GNSS Radio Occultation Observations
<p>The set-up of CESM2-CAM6 sensitivity experiments for winter season (Dec-Jan-Feb: DJF), with prognostic falling ice radiative effects on (SON) and off (NOS), is an updated two-moment stratiform cloud scheme (MG2, Gettelman & Morrison, 2015) in the CESM2 atmospheric component of CAM6. CESM2-CAM6 participated in CMIP6. Both the NOS and SON simulations were configured following the same approach as the CMIP6 "historical" run spanning from 1980 to 2014.</p> <p> </p> <p>The data are:</p> <p> </p> <p>TS: skin temperature (K)</p> <p>TAUX: zonal surface wind stress</p> <p>TAUY: meridinal surface wind stress</p> <p>DTCOND: moist condensation heating rate</p> <p>QRL: long wave heating rate</p> <p>OMEGA: vertical motion</p> <p>Z3: geopotential height</p> <p> </p>
Figures 44–52 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 44–52: Alexandrium tamarense, LM and SEM. (44) Cell in ventral view, LM. (45) Empty cell in ventral view with plate tabulation, LM. (46) Detail of the epitheca with some plates and ventral pore (arrow), LM. (47) Apical view, with plate tabulation, LM. (48, 49) Hypotheca with plate tabulation, including the posterior sulcal plate (Sp) and its pore (arrow), LM. (50) Epitheca with plate tabulation and the ventral pore (arrow), SEM. (51) Epitheca with plate tabulation, SEM. (52) Po with some plates surrounding it, and the ventral pore (arrow), SEM.
Figures 28–37 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 28–37: Alexandrium monilatum, LM and SEM.(28, 29) A long chain (8 cells) and detail of that chain, respectively, LM. (30) Pair of cells in ventral view, SEM. (31) General outline of a cell, LM. (32) Cell in ventral view showing Po and 1′, SEM. (33) Detail of the cingulum and sulcus, showing the first apical plate (1′), SEM. (34) Apical view with plate tabulation, SEM. (35) Hypotheca showing the posterior sulcal plate (Sp) and its connecting pore (arrow), SEM. (36) Po plate with the conjunction pore and foramen, SEM. (37) Posterior sulcal plate showing the connection pore, LM.
Figures 20–21 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 20–21: Alexandrium leei, LM. (20) Recently fixed cell in ventral view. (21) An empty cell in ventral view showing plate tabulation, arrow indicates the ventral pore in the first apical plate (1′).
Figures 9–11 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 9–11: Alexandrium gaarderae, LM. (9, 10) Two different focal planes of a solitary cell in ventral view, showing the cell outline, cingulum and sulcus. (11) A cell in dorsal view.
Figures 2–8 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 2–8: Alexandrium affine, LM. (2, 3) Chains of 8 and 3 cells, respectively. (4) An empty cell showing only the theca in ventral view. (5) Epitheca in ventral view showing the ventral pore (arrow) in the first apical plate (1′). (6) Epitheca with Po and 1′ showing the ventral pore (arrow). (7, 8) Po and posterior sulcal plate (Sp) (with a connecting pore), respectively.
Figures 67–69 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 67–69: Alexandrium tropicale, LM. (67) Pair of cells. (68, 69) Epitheca and hypotheca with plate tabulation.
Figure 1 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figure 1: Map with the sampling points where species of Alexandrium were found and the sites from which the established strains were isolated.
Figures 38–43 in Diversity and distribution of species of the planktonic dinoflagellate genus Alexandrium (Dinophyta) from the tropical and subtropical Mexican Pacific Ocean
Figures 38–43: Alexandrium pseudogonyaulax, LM. (38) Cell in ventral view. (39) Empty cell in ventral view, showing 1′, 4′, 6″ and the large ventral pore (arrow). (40) Detail of Po with the foramen. (41–43) Epitheca in ventral view showing 1′, 4′, 6″, and ventral pore (arrow).
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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.