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2,441 results for “extinct”
Data from: Niche width predicts extinction from climate change and vulnerability of tropical species
<p>Climate change may be a major threat to global biodiversity, especially to tropical species. Yet, why tropical species are more vulnerable to climate change remains unclear. Tropical species are thought to have narrower physiological tolerances to temperature, and they have already experienced a higher estimated frequency of climate-related local extinctions. These two patterns suggest that tropical species are more vulnerable to climate change because they have narrower thermal niche widths. However, no studies have tested whether species with narrower climatic niche widths for temperature have experienced more local extinctions, and if these narrower niche widths can explain the higher frequency of tropical local extinctions. Here, we test these ideas using resurvey data from 538 plant and animal species from 10 studies. We found that mean niche widths among species and the extent of climate change (increase in maximum annual temperatures) together explained most variation (>75%) in the frequency of local extinction among studies. Surprisingly, neither latitude nor occurrence in the tropics alone significantly predicted local extinction among studies, but latitude and niche widths were strongly inversely related. Niche width also significantly predicted local extinction among species, as well as among and (sometimes) within studies. Overall, niche width may offer a relatively simple and accessible predictor of the vulnerability of populations to climate change. Intriguingly, niche width has the best predictive power to explain extinction from global warming when it incorporates coldest yearly temperatures.</p>
FIGURE 4 in Palleptoceridae fam. nov., an extinct leptoceroid family in mid-Cretaceous Burmese amber (Insecta, Trichoptera)
FIGURE 4. Palleptocerus grimaldii sp. nov., paratypes. A, Female paratype 2, ZFMK-TRI000832, adult in ventral view; scale bar = 1 mm. A Inset, Female genitalia with a pair of dorsal setose lobes (dolo); scale bar = 0.3 mm. B, Male paratype, ZFMKTRI000833, adult in ventral view; scale bar = 1 mm. B Inset, Male genitalia with five-segmented maxillary palps (mx); scale bar = 0.3 mm.
FIGURE 3 in Palleptoceridae fam. nov., an extinct leptoceroid family in mid-Cretaceous Burmese amber (Insecta, Trichoptera)
FIGURE 3. Palleptocerus grimaldii sp. nov., genitalia. A, Male holotype, ZFMK-TRI000831, adult in dorsal view; scale bar = 1 mm. A Inset, Male genitalia with a pair of inferior appendages (inf ap); scale bar = 0.3 mm. B, Female paratype 1, ZFMKTRI000831, adult in dorsal view; scale bar = 1 mm. B Inset, Female genitalia with a pair of lobes (dolo); scale bar = 0.2 mm. C, Mesoscutum sclerotized, running longitudinally, with dark marginal ridges on both sides; scale bar = 0.1 mm. C Inset, a row of setae, inside along of the marginal ridge of mesoscutum, scale bar = 0.05 mm
FIGURE 2 in Palleptoceridae fam. nov., an extinct leptoceroid family in mid-Cretaceous Burmese amber (Insecta, Trichoptera)
FIGURE 2. Palleptocerus grimaldii sp. nov., characters. A, Maxillary palp of female paratype 1, ZFMK-TRI000831; scale bar = 0.1 mm. B, Wing venations, venations of male forewing, female forewing and hind wing; scale bar = 1 mm.
FIGURE 1 in Palleptoceridae fam. nov., an extinct leptoceroid family in mid-Cretaceous Burmese amber (Insecta, Trichoptera)
FIGURE 1. Palleptocerus grimaldii sp. nov., mating. A, A mating pair, male holotype (right), female paratype 1 (left), ZFMKTRI000831, in ventral view; scale bar = 2 mm. B, Male paratype, ZFMK-TRI000833, metatibia, each with a pair of apical and preapical spurs (arrows), circle = branching spurs; scale bar = 0.5 mm.
A three-dimensional Galactic extinction model
<p><strong>Overview</strong></p> <p>A large-scale three-dimensional model of Galactic extinction is presented based on the Galactic dust distribution model of Drimmel & Spergel (2001). The extinction A<sub>V</sub> to any point within the Galactic disk can be quickly deduced using a set of three-dimensional Cartesian grids. Extinctions from the model are compared to empirical extinction measures, including lines-of-sight in and near the Galactic plane using optical and NIR extinction measures; in particular we show how extinction can be derived from NIR color-magnitude diagrams in the Galactic plane to a distance of 8 kiloparsec.</p> <p>Please cite <a href="https://ui.adsabs.harvard.edu/abs/2003A%26A...409..205D/abstract">Drimmel, Cabrera-Lavers, and López-Corredoira (2003)</a> when using this model.</p> <p>The provided tarball includes the contribution to the extinction from different Galactic components in binary format. Code to read and use this data is included in the <a href="https://github.com/jobovy/mwdust">mwdust</a> package.</p> <p><strong>Instructions for use of the extinction grids (from the original README)</strong></p> <pre>The data-for.tar.gz file contains a suite of three-dimensional cartesian grids of the extinction in V band. Each grid corresponds to one of three structural components of the dust model (disk, spiral arms, local Orion arm). Local and "global" grids provide different levels of detail, or resolution. The local grids are centered on the Sun, the large scale grids cover the entire Galaxy, excepting that of the local Orion arm. For all grids the z=0 plane corresponds to the Galactic Plane. For the local grids the x-axis points toward the Galactic center. The conversion from Galactic coordinates (l,b,d) to cartesian heliocentric coordinates are: x = d cosb cosl y = d cosb sinl z = d sinb + Z_sun with Z_sun = 0.015 kpc. Using the convention that array indices start at 0 (as in IDL), the grid coordinates (i,j,k) are given by i = x / \Delta x + (n_x - 1)/2 j = y / \Delta y + (n_y - 1)/2 k = z / \Delta z + (n_z - 1)/2 where the dimensions of the grid are (n_x, n_y, n_z) and the grid spacing is (\Delta x, \Delta y, \Delta z), where \Delta x = \Delta y for all the grids. The table below lists these parameters for each of the grids. The above formulas will be convenient for any 3-D interpolation routine that requires grid coordinates for the points to be interpolated. Note that for FORTRAN +1 should be added to the above grid coordinates to conform with the convention that array indices start with the number 1. For the large scale grids galactocentric coordinates are more convenient. Using the same axis directions the same conversions from (l,b,d) to cartesian coordinates above will still apply with the exception of the x-coordinate, which is now x = d cosb cosl + X_sun with X_sun = -8 kpc. For the grids avdisk and avspir the same conversions to (i,j,k) can be used, however the grid avori only covers part of the Galactic disk, so that i = x/ \Delta x + 2.5(n_x - 1) Care should be taken not to extrapolate beyond the boundaries of the large-scale grids, but a working approximation for points beyond the grid boundaries is to use a point farthest from the Sun *along the line-of-sight* that is on the boundary of the large-scale grid. In most directions this is equivalent to the total Galactic extinction. Grid parameters: grid component \Delta x \Delta z n_x n_y n_z ---------------------------------------------------------------------------- large-scale: avgrid all 0.2 0.02 151 151 51 avdisk disk 0.2 0.02 151 151 51 avspir spiral arms 0.2 0.02 151 151 51 avori Orion arm 0.05 0.02 76 151 51 local: avloc all 0.02 0.02 101 201 51 avdloc disk 0.05 0.02 31 31 51 avori2 Orion arm 0.02 0.02 101 201 51 ---------------------------------------------------------------------------- Rescaling factors: The rescaling factors are based on the residuals between the COBE FIR observations and the predictions of the dust distribution model. For this reason the rescaling factors are rooted to the COBE data structure; for each COBE pixel there is an associated rescaling factor. This introduces some complication in the retrieval of the rescaling factors for any arbitrary direction as the COBE sky maps use a nonstandard projection and pixel ordering scheme. (See http://space.gsfc.nasa.gov/astro/cobe/skymap_info.html for a brief introduction and Appendix G of the COBE Guest Investigator Software (CGIS) Software User's Guide (version 2.2), retrievable at ftp://rosette.gsfc.nasa.gov/pub/cobe-gi/doc/, for further details.) The rescaling factors for each COBE pixel are contained in a binary file in unformatted FORTRAN format, rf_allsky.dat. This file contains arrays that specify: the COBE pixel number, the structural component to be rescaled (i.e. the component with a rescaling factor not equal to 1), the Galactic longitude and latitude of each pixel, and the rescaling factor to be applied. (See the example FORTRAN code below.) The second integer array specifies the component to be rescaled is an integer array with a value of 1, 2 or 3, corresponding to the disk, spiral and local arm components respectively. There are a total of 393216 pixels. To access these rescaling factors the user must find the pixel that coincides with the direction of interest. For this task there are at least three options: 1) Write a routine that searches through the list of longitudes and latitudes for the nearest pixel. 2) Work within the UIDL environment which provides an efficient means, via CGIS IDL code, to retrieve the pixel number nearest a given direction. The UIDL package with instructions for installation can be found at http://space.gsfc.nasa.gov/astro/cobe/cgis.html. The code findext.pro in this directory is an example of such a routine. 3) Use stand alone CGIS code (standard FORTRAN) to retrieve the pixel number for a given direction. This code can be down loaded via anonymous ftp from ftp://rosette.gsfc.nasa.gov/pub/cobe-gi/. The relevant files are aacgis_for.txt and cgis-for.tar, the latter containing the FORTRAN library with makefiles. The code ll2pix.for queries for longitude, latitude, coordinate system and resolution level to return a pixel number. The resolution level corresponding to the FIR data, and hence the rescaling factors, is level 9. See the FORTRAN code Av3_FEB03.f as an example. Once the correct COBE pixel index is found for the desired direction, use the first array to discern to which component the rescaling factor should be applied to. For example, using the array nomenclature in the example FORTRAN code below, if for pixel J the the NCOMP(J) value is 2, then the extinction should be AV = AVDISK + RF(J)*AVSPIR + AVORI, where AVDISK, AVSPIR and AVORI correspond to the interpolated values from these three-dimensional arrays. The user is also cautioned that in directions where extragalactic sources contribute significantly to the FIR flux the derived rescaling factors will be erroneous. This includes the Andromeda Galaxy, M33, the LMC and SMC. There are also nearby regions within the Galaxy that have anomalous emission due to warm dust that are not described by the model, especially the rho Ophiucus and Orion regions. Finally, the nuclear disk in the Galactic center (|l| < 3 deg) is not described by the model. The rescaling factors in these directions also should not be used. Algorithm: Using the three-dimensional extinction grids a value for the extinction A_i due to each of the components i of the dust distribution can be found for any point in the Galactic disk via interpolation. Together with the appropriate rescaling factor a final estimate of the extinction is arrived at: A(l,b,r) = \sum f_i(l,b) A_i(l,b,r) To summarize, an algorithm for arriving at an extinction A_v for a point in the Galaxy (l,b,r) is outlined below: 1) Find the COBE pixel coinciding to (l,b). 2) Recover the rescaling factor f_i and component i to be rescaled from the rf_allsky.dat file. (Set f=1 for the other components.) 3) Determine the grid coordinates: (l,b,r) ----> (x,y,z) -----> (i,j,k) 4) Interpolate from appropriate grids to find A_i(l,b,r) for each component. 5) Sum over the components (above equation) to arrive at A(l,b,r). </pre>
Data from: Evolutionary constraints mediate extinction risk under climate change
<p>Mounting evidence suggests that rapid evolutionary adaptation may rescue some organisms from the impacts of climate change. However, evolutionary constraints might hinder this process, especially when different aspects of environmental change generate antagonistic selection on genetically correlated traits. Here, we use individual-based simulations to explore how genetic correlations underlying the thermal physiology of ectotherms might influence their responses to the two major components of climate change—increases in mean temperature and thermal variability. We found that genetic correlations can influence population dynamics under climate change, with declines in population size varying three-fold depending on the type of correlation present. Surprisingly, populations whose thermal performance curves were constrained by genetic correlations often declined less rapidly than unconstrained populations. Our results suggest that accurate forecasts of the impact of climate change on ectotherms will require an understanding of the genetic architecture of the traits under selection.</p>
Data used to generate results for Meireles et al. 2023. The future of suitable habitats of an endangered Neotropical grassland bird: a path to extinction? Ecology and Evolution.
<p>Here we include all occurrence records (264) found for Campo Miner, in addition to the 47 records of current distribution of the species (*) used for ecological niche modeling analyses. </p>
Data from: Can body mass and skull morphology predict seed and fruit ingestion potential for mammal species? A test using extant species and its application to extinct species
<p>Larger animals are assumed to ingest larger seeds and consume larger fruits, but empirical studies reveal inconsistent trends between body mass and the average size of fruits and seeds ingested. Further, no studies have explored seed size relationships with morphological traits, such as skull dimensions. Such characteristics might provide more reliable estimates of ingestion ability and allow for accurate predictions of seed dispersal capacity in species for which we lack empirical data, especially extinct species. To determine whether (i) mammalian skull dimensions are better predictors of the maximum size of ingested seeds and fruits, compared to body mass and (ii) body mass are the better predictors of mean fruit and seed sizes, we studied these relationships across three mammalian orders: Chiroptera, Primates, and Carnivora.</p> <p>We collected novel data on skull dimensions and collated available data on body mass and maximum and mean sizes of ingested fruits and seeds for mammals (N=100) across the Neotropics, Asia, Africa, and Madagascar. We explored the relationships between anatomical traits and fruit and seed sizes of extant species and made predictions for five extinct species.</p> <p>Our results revealed that body mass and skull dimensions are essential determinants of ingested fruit and seed size in mammals. The latter traits can generate predictions for extinct species, especially coronoid height and maximum jaw gape. Nevertheless, body mass predicted larger ingested fruits and seeds than skull dimensions and explained a greater part of the variance for both maximum and mean sizes in our dataset.</p> <p>Our results show how body mass and cranial anatomy constrain seed size and reinforce the importance of maintaining functional diversity in seed dispersers to maintain tropical forest structure. We also show that scientists can use morphological characteristics to predict the seed dispersal potential of extinct mammals allowing better inferences on past and future consequences of frugivore extinctions within tropical forests.</p>
Multiple co-occurring bioeconomic drivers of overexploitation can accelerate rare species extinction risk
<p>1. The unsustainable harvest of species for the global wildlife trade is a major cause of vertebrate extinction. Through the Anthropogenic Allee Effect, overexploitation to extinction can occur when a species' rarity drives up its market price, enabling profitable harvest of all remaining individuals. Even in the absence of rarity value, however, the harvest of other species can subsidize the overexploitation of a rare species to the point of extinction, a phenomenon termed opportunistic exploitation. These two pathways to extinction have only been considered independently, but many traded species experience them simultaneously.</p> <p>2. In this study, we develop a simple model that incorporates these mechanisms simultaneously and demonstrate that including multiple harvest strategies with market-based feedbacks fundamentally alters rare species extinction risk and the rate at which overexploitation occurs. As a pertinent case study, we consider the harvest of ground pangolins (<em>Smutsia</em> <em>temminckii</em>).</p> <p>3. Our results show that pangolin extinction was generally associated with high rarity value, the use of multiple harvest strategies, and the simultaneous harvest of a common species that has a fast life-history. Pangolin population depletion and short-term extinction risk were greatest when harvesters used a combination of pursuit and opportunistic (i.e. multi-species) harvest strategies.</p> <p>4. Policy implications. Our results suggest that feedbacks between multiple financial incentives to overharvest can exacerbate the risk of extinction of rare species. As a result, continuing to address AAE and opportunistic exploitation as separate extinction pathways may insufficiently capture extinction risk for many exploited species. Criteria for assessing extinction risk or harvest sustainability of exploited species should incorporate multiple drivers of harvest pressure, with an expanded focus on including species with high rarity value that are exploited in multi-species harvest regimes.</p>
FIGURE 1 in Rediscovery of the presumably extinct fairy lantern Thismia kobensis (Thismiaceae) in Hyogo Prefecture, Japan, with discussions on its taxonomy, evolutionary history, and conservation
FIGURE 1. Thismia kobensis at the new locality. (A–C) Flower, lateral view. (D–F) Flower, upper view. (G) Flower without perianth lobes. (H) Flower with broken perianth tube and exposed stigma. Scale bars: 5 mm. Photographed by Kenji Suetsugu.
FIGURE 3 in Rediscovery of the presumably extinct fairy lantern Thismia kobensis (Thismiaceae) in Hyogo Prefecture, Japan, with discussions on its taxonomy, evolutionary history, and conservation
FIGURE 3. Thismia kobensis (Kenji Suetsugu & Kohei Yamana T1-3, HYO). (A) Habit. (B) Longitudinal section of perianth tube with stamens, style, and stigma. (C) Flower, upper view. (D) Flower with perianth lobes removed. (E) Stamens, inner view. (F) Stamens, upper view. (G) Inner perianth lobe. (H) Outer perianth lobe. (I) Style and stigma. Scale bars: 5 mm (A–B), 3 mm (C–H), and 1 mm (I). Photographed by Kenji Suetsugu.
FIGURE 2 in Rediscovery of the presumably extinct fairy lantern Thismia kobensis (Thismiaceae) in Hyogo Prefecture, Japan, with discussions on its taxonomy, evolutionary history, and conservation
FIGURE 2. Thismia huangii at the type locality. (A) Habit. (B) Flower, upper view. (C) Flower, lateral view. (D) Longitudinal section of perianth tube with stamens, style, and stigma. (E) Style and stigma. Arrows indicate a long hair on each lobe. Scale bars: 20 mm (A), 5 mm (B–D), and 1 mm (E). Photographed by Tsung-Hsin Hsieh (A, D–E) and Tian-Chuan Hsu (B–C).
FIGURE 4 in Rediscovery of the presumably extinct fairy lantern Thismia kobensis (Thismiaceae) in Hyogo Prefecture, Japan, with discussions on its taxonomy, evolutionary history, and conservation
FIGURE 4. Thismia kobensis (holotype). (A) Habit. (B–C) Flower, upper view. (D) Flattened perianth tube. (E) Stamens, inner view. (F) Stamens, outer view. (G) Stigma. Scale bars: 5 mm (A–B), 3 mm (C–D), and 1 mm (E–G). Photographed by Kumi Hamasaki.
Mercury isotope evidence for marine photic zone euxinia across the end-Permian mass extinction
<p>The compiled geochemical data used for plots in the main manuscipt </p>
Data from: Widespread extinctions of co-diversified gut bacterial symbionts from humans
<p><span>Humans and other primates harbour complex gut bacterial communities that influence health and disease, but the evolutionary histories of these symbioses remain unclear due to a lack of information about the state of the microbiota in ancestral primates. Here we show that hundreds of gut bacterial lineages co-diversified with primate species over millions of years, but that nearly half of these ancestral symbionts have been lost from humans. Analyses of thousands of metagenome-assembled genomes from humans, chimpanzees, bonobos, and other non-human primates revealed significant co-diversification within ten gut bacterial phyla. Remarkably, 44% of the co-diversifying clades detected in African apes were absent from available human metagenomic data. In contrast, only ~3% of the clades displaying the weakest evidence for co-diversification and detected in African apes were absent from humans. This study identifies bacterial symbioses that predate hominid diversification, revealing accelerated extinctions of ancestral, co-diversifying symbionts from human populations. </span></p>
First demographic insights reveal high extinction risk of an endemic raptor species: the Reunion harrier
<p><span>Gathering demographic information on rare species is critical to understanding their population dynamics and implementing efficient conservation measures. Using integrated models, w</span><span>e jointly analyzed multiple data sets, including capture-recapture, GPS tracking, and nest monitoring data collected over the last 10 years, to provide the first demographic insights for </span><span>one of the world's rarest raptors,</span><span> the </span><span>endemic </span><span>Reunion harrier </span><em><span>Circus maillardi</span></em><span>. We estimated key demographic rates including annual survival and breeding parameters (clutch size, hatching and fledging success), and used population projection models to assess population growth rate and quasi-extinction risk. In order to guide future conservation actions for the population, we evaluated the effects of different management scenarios that improve survival, fecundity, or both, on population growth and quasi-extinction risk. Comparison of the estimated annual survival (juvenile and subadult survival: 0.66; adult survival: 0.71) and breeding parameters (clutch size: 2.3; hatching success: 0.47; fledging success: 0.74) with those of other harrier species suggests that adult survival and breeding parameters of Reunion harriers are low. A small data set collected 40 years ago suggests that the probability of an egg producing a fledgling was higher and has declined to the current low level. The population models project that the Reunion harrier population is declining and faces a high risk of quasi-extinction in the next 40 years. Only management measures that simultaneously improve adult survival and fecundity could lead to a recovery of the population. These alarming results call for immediate conservation action aimed at rapidly improving the demographic rates. </span></p>
Análisis de la cobertura mediática de Extinction Rebelion
<p>Datos tratados por el programa SPSS del análisis informativo de la cobertura mediática de Extinction Rebelion.</p>
FIGURES 5–7 in News from Baltic amber: a new tribe of extinct Paleogene ironclad beetles (Coleoptera: Zopheridae: Zopherinae)
FIGURES 5–7. Representatives of the tribe Zopheromimini trib. nov. (microphotographs): 5—head of Zopheromimus auriborussiensis; 6—abdomen of Z. auriborussiensis; 7—abdomen of Yantaroxenos colydioides. Abbreviations: mem— membranes between non-connate ventrites; pag—preapical groove on abdominal ventrite 5.
FIGURES 3–4 in News from Baltic amber: a new tribe of extinct Paleogene ironclad beetles (Coleoptera: Zopheridae: Zopherinae)
FIGURES 3–4. Zopheromimus auriborussiensis sp. nov., holotype, No KAM 8325/2, forebody, ventro-lateral view: 3— microphotograph; 4—schematic drawing. Abbreviations: A2—antennomere 2 (as long as antennomere 3); E—eye (lateral, hemispherical); PH—prothoracic hypomeron (not grooved); PC—procoxal cavity (externally closed); AP—abdominal procoxal process (triangular).
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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)
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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.