Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
22,455
datasets available to search
ShareScore release 0.9.0
Dataset results
22,455 results for “Diversion”
Fig. 31 in Diversity and taxonomy of the Late Triassic sauropodomorphs (Saurischia, Sauropodomorpha) stored in the Palaeontological Collection of Tübingen, Germany, historically referred to Plateosaurus
Fig. 31 (see next page). Uncatalogued material separated as "Weishampel 1983" in the collection, presumably from the expedition led by von Huene between 1922–1923 to Obere Mühle. A. GPITPV-60210, fragment of a right mandible in medial view. B. GPIT-PV-60225, left maxilla in lateral view. C. GPIT-PV-60224, right maxilla in lateral view. D. GPIT-PV-60214, dorsal vertebra in right lateral view. E. GPIT-PV-60215, dorsal vertebra in right lateral view. F–G. GPIT-PV-60220, anterior caudal vertebra in right lateral view (F) and in dorsal view (G). H. GPIT-PV-60221, anterior caudal vertebra in anterior view and associated fragment. I. GPIT-PV-60222, anterior caudal vertebra in left lateral view and associated fragments. J. GPIT-PV-60219, middle caudal vertebra in right lateral view. K. GPIT-PV-60228, middle caudal vertebra in right ventrolateral view. L. GPIT-PV-60229, middle caudal vertebra in right lateral view. M. GPIT-PV-60233, posterior caudal vertebra in right lateral view. N. GPIT-PV-60232, posterior caudal vertebra in right lateral view. O. GPIT-PV-60231, distal caudal vertebra in left lateral view. P. GPIT-PV-60226, left metacarpals I to IV in anterior view. Q. GPIT-PV-60227, right metacarpal II. R. GPIT-PV-60212, left metatarsal IV. S. GPIT-PV-60213, left metatarsal IV. T. GPIT-PV-60217, left metatarsal I. U. GPIT-PV-60265, chevron in lateral view. V. GPIT-PV-60264, chevron in lateral view. W. GPIT-PV-60261, chevron in anterior view. X. GPIT-PV-60262, chevron in anterior view. Y. GPITPV-60261, chevron in lateral view. Z. GPIT-PV-60211, right pubis in anterior view. AA. GPIT-PV-60216, right ilium in lateral view.
Maps of the diversity and distribution of Raunkiær's life forms in European vegetation
<p>This repository contains raster files (TIF format) with a 50 km × 50 km resolution (over UTM grid EPSG:32633), showcasing the diversity and distribution of Raunkiær’s life forms in European vegetation. The maps are based on two key metrics: (i) the proportion (%) of species within each life form and (ii) the diversity of life forms, including richness and evenness.</p> <p>To generate these maps, we averaged plot-level metric values across a comprehensive dataset comprising 546,501 vegetation plots sourced from the European Vegetation Archive (EVA; Project 163; <a href="https://euroveg.org" target="_new">https://euroveg.org</a>). These plots cover diverse habitats, including 173,190 forests, 260,884 grasslands, 52,517 scrubs, and 59,910 wetlands.</p> <p>The maps encompass the entire dataset, offering a visualization of the geographical distribution patterns of life forms across Europe. Additionally, we created habitat-specific maps by subsetting the dataset to explore unique patterns within each habitat type (forest, grassland, scrub, and wetland).</p> <p>Furthermore, we generated additional maps based on standardised effect sizes (SES) of diversity metrics. Through 500 species identity shuffles without replacement, specific to each habitat type, we examined the deviations from random expectations. SES values outside the range of -1.96 to 1.96 indicate significantly lower or higher metric values than expected at random, respectively. </p> <p> </p> <table> <tbody> <tr> <td><strong>Folder name</strong></td> <td><strong>Description of TIF raster values</strong></td> </tr> <tr> <td>full.div</td> <td>Mean richness and evenness of life forms across all habitat types</td> </tr> <tr> <td>full.mean.rel.prop</td> <td>Mean proportion of each life form across all habitat types</td> </tr> <tr> <td>habitat.div</td> <td>Mean richness and evenness of life forms across separate habitat types (forest, grassland, scrub, and wetland)</td> </tr> <tr> <td>habitat.mean.rel.prop</td> <td>Mean proportion of each life form across separate habitat types (forest, grassland, scrub, and wetland)</td> </tr> <tr> <td>SES.full.div</td> <td>Mean richness and evenness of life forms across all habitat types measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.full.mean.rel.prop</td> <td>Mean proportion of each life form across all habitat types measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.habitat.div</td> <td>Mean richness and evenness of life forms across separate habitat types (forest, grassland, scrub, and wetland) measured with standardized effect sizes (SES)</td> </tr> <tr> <td>SES.habitat.mean.rel.prop</td> <td>Mean proportion of each life form across separate habitat types (forest, grassland, scrub, and wetland) measured with standardized effect sizes (SES)</td> </tr> </tbody> </table> <p><br>Additional information is available in our publication:<br><br>Midolo, G., Axmanová, I., Divíšek, J., Dřevojan, P., Lososová, Z., Večeřa, M., Karger, D. N., Thuiller, W., Bruelheide, H., Aćić, S., Attorre, F., Biurrun, I., Boch, S., Bonari, G., Čarni, A., Chiarucci, A., Ćušterevska, R., Dengler, J., Dziuba, T., Garbolino, E., Jandt, U., Lenoir, J., Marcenò, C., Rūsiņa, S., Šibík, J., Škvorc, Ž., Stančić, Z., Stanišić-Vujačić, M., Svenning, J. C., Swacha, G., Vassilev, K., & Chytrý, M. (2024) Diversity and distribution of Raunkiær’s life forms in European vegetation.<em> Journal of Vegetation Science. </em>Accepted on the 10th of December 2023</p>
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>
Drivers of plant diversity, community composition, functional traits and soil processes along an alpine gradient in the central Chilean Andes
<p>The datasets in this repository include plant community surveys, hyperspectral reflectance data at the leaf and canopy level, leaf trait data, and soil chemistry data collected at five sites along an elevation gradient of 2400m-3500m in the Chilean Andes (33°S, 70°W). The purpose of this study was to evaluate the environmental drivers of community assembly processes along the elevation gradient.</p>
A lack of genetic diversity and minimal adaptive evolutionary divergence in introduced Mysis shrimp after 50 years
<p>The successes of introduced populations in novel habitats often provide powerful examples of evolution and adaptation. In the 1950's, opossum shrimp (<em>Mysis diluviana</em>) individuals from Clearwater Lake in Minnesota, USA were transported and introduced to Twin Lakes in Colorado, USA by fisheries managers to supplement food sources for trout. Shrimp were subsequently introduced from Twin Lakes into numerous lakes throughout Colorado. Because managers kept detailed records of the timing of the introductions, we had the opportunity to test for evolutionary divergence within a known time interval. Here, we used reduced representation genomic data to investigate patterns of genetic diversity and test for genetic divergence between populations and for evidence of adaptive evolution within the introduced populations in Colorado. We found overall very low levels of genetic diversity across all populations, with evidence for some genetic divergence between the Minnesota source population and the introduced populations in Colorado. There was also little differentiation among the Colorado populations, consistent with the known provenance of a single founding population, with the exception of the population from Gross Reservoir, Colorado. Demographic modeling suggests that the population in Gross Reservoir is of hybrid origin, with an earlier founding population from an unknown source being later supplemented from another population. Despite the overall low genetic diversity we observed, F<sub>ST</sub> outlier and environmental association analyses identified multiple loci exhibiting signatures of selection and adaptive variation related to elevation and lake depth. The success of introduced species is thought to be limited by genetic variation, but our results imply that populations with limited genetic variation can become established in a wide range of novel environments.</p>
Rapid in situ diversification rates in Rhamnaceae explain the parallel evolution of high diversity in temperate biomes from global to local scales
<p>The macroevolutionary processes that have shaped biodiversity across the temperate realm remain poorly understood and may have resulted from evolutionary dynamics related to diversification rates, dispersal rates, and colonization times, closely coupled with Cenozoic climate change.</p> <p>We integrated phylogenomic, environmental ordination, and macroevolutionary analyses for the cosmopolitan angiosperm family Rhamnaceae to disentangle the evolutionary processes that have contributed to high species diversity within and across temperate biomes.</p> <p>Our results show independent colonization of environmentally similar but geographically separated temperate regions mainly during the Oligocene, consistent with the global expansion of temperate biomes. High global, regional, and local temperate diversity was the result of high <em>in</em> <em>situ</em> diversification rates, rather than high immigration rates or accumulation time, except for Southern China, which was colonized much earlier than other regions. The relatively common lineage dispersals out of temperate hotspots highlights strong source-sink dynamics across the cosmopolitan distribution of Rhamnaceae.</p> <p>The proliferation of temperate environments since the Oligocene may have provided the ecological opportunity for rapid <em>in</em> <em>situ</em> diversification of Rhamnaceae across the temperate realm. Our study illustrates the importance of high <em>in</em> <em>situ</em><strong> </strong>diversification rates for the establishment of modern temperate biomes and biodiversity hotspots across spatial scales.</p>
Insights into intraspecific diversity of central carbon metabolites in Saccharomyces cerevisiae during wine fermentation
<p>Supplementary data including the data set used for the " Insights into intraspecific diversity of central carbon metabolites in <em>Saccharomyces cerevisiae</em> during wine fermentation" publication.</p> <p>Abstract:</p> <p><em>Saccharomyces cerevisiae</em>, as the workhorse of alcoholic fermentation, is a major actor in winemaking. In this context, this yeast species performs alcoholic fermentation to convert sugars from the grape must into ethanol and CO2 with outstanding efficiency as it reaches on average 92% of the maximum theoretical yield of conversion. Primary metabolites produced during fermentation have a great importance in wine where they significantly impact wine characteristics. While ethanol content contributes to the overall profile, others metabolites also have significant impacts, even when present in lower concentrations: glycerol, succinate, acetate, ⍺-ketoglutarate, lactate… <em>S. cerevisiae</em> is known for its great genetic diversity and plasticity that is directly related to its living environment, natural or technological and therefore to domestication. This leads to a wide phenotypic diversity of metabolites production. However, the range of metabolic diversity is variable and depends on the pathway considered. With the aim to improve wine quality, the selection, development and use of strains with dedicated metabolites production without genetic modifications can rely on the already existing natural diversity. Here we detail a screening experiment that aims to assess the diversity of primary metabolites production in a set of 51 <em>S. cerevisiae</em> strains from various genetic backgrounds (wine, flor, rum, West African, sake…). To approximate winemaking conditions, we used a synthetic grape must as fermentation medium and measured seven metabolites by HPLC. Results pointed out great yield differences between strains depending on the metabolite considered. Ethanol appeared as the one with the smallest variation among our set of strains, although it was by far the most produced. A clear negative correlation between ethanol and glycerol was observed, confirming glycerol synthesis as a suitable lever to reduce ethanol yield. Genetic groups were linked to specific metabolic yields such as high α-ketoglutarate and low acetate yields for wine strains. This study thus helps to characterise the phenotypic diversity of <em>S. cerevisiae</em> in a wine-like context and comforts the use of natural diversity in the development of new strains. Finally, it provides a detailed data set usable to study diversity of well known (ethanol, glycerol, acetate) or little-known (lactate) primary metabolites production, including in common commercial wine strains.</p> <p> </p> <p> </p>
Ant handling changes myrmecochore seed coat microbiomes and alters diversity of seed-borne plant pathogenic fungi
<p>The putative benefits to seeds in myrmecochory (ant-mediated seed dispersal) are often cast in a reward context. However, microbes have been mostly overlooked as seed mortality agents in myrmecochory, as have potential treatments provided by ant-handling. We investigated the effects of ant handling on the diversity of seed coat fungal communities of three myrmecochorous plant species. Ant-handling altered measures of both alpha and beta diversity of fungal communities. Ant-handled seeds harbored different overall fungal communities and plant pathogen communities than non-ant-handled seeds. The myrmecochore pathogenic fungal community showed high dissimilarity (high pairwise community turnover) between ant-handled and control seeds, while beta diversity measures for ant-handled seeds and seeds with manually-removed elaiosomes were less dissimilar. Ant handling may offer an additional benefit to myrmecochorous seeds via the reduction of the seed coat pathogenic community, which may be driven by elaiosome removal or as a byproduct of ant cleaning behaviors and chemical secretions. </p>
Data from: Exponential history integration with diverse temporal scales in retrosplenial cortex supports hyperbolic behavior
<p>Animals rely on their experience to guide their next choice. In foraging-type tasks guided by history-dependent value, these experiences are typically integrated such that the weights of past events initially decay quickly over time but show a longer tail than expected by exponential decay. Rather, such integration is better described by a hyperbolic function. Hyperbolic integration affords sensitivity to both recent environmental dynamics and long-term trends, however the mechanism by which the brain implements this hyperbolic integration is unknown. We trained mice on a history-dependent, value-based decision task and found that the mice indeed showed hyperbolic decay on their weighting of past experience. However, the activity of history-encoding cortical neurons showed weighting with exponential decay. In resolving this apparent mismatch, we observed that cortical neurons encode history information heterogeneously across a wide variety of exponential time-constants, with the retrosplenial cortex (RSC) overrepresenting longer time-constants compared to other areas. A model that combines these diverse timescales of exponential history integration can recreate the heavy-tailed, hyperbolic history integration observed in behavior. In particular, time-constants of RSC neurons best matched the behavior, and optogenetic inactivation of RSC uniquely reduced the use of history information. These results indicate that behavior-relevant history information is maintained in neurons across multiple timescales in parallel, and suggest that the neural population in RSC is a critical reservoir of this information guiding decision-making.</p>
Restored off-channel pond habitats create thermal regime diversity and refuges within a Mediterranean-climate watershed
<p>Cool-water habitats provide increasingly vital refuges for cold-water fish living on the margins of their historical ranges; consequently, efforts to enhance or create cool-water habitat are becoming a major focus of river restoration practices. However, the effectiveness of restoration projects for providing thermal refuge and creating diverse temperature regimes at the watershed scale remains unclear. In the Klamath River in Northern California, the Karuk Tribe Fisheries Program, the Mid-Klamath Watershed Council, and the U.S. Forest Service constructed a series of off-channel ponds that recreate floodplain habitat and support juvenile coho salmon (<em>Oncorhynchus kisutch</em>) and steelhead (<em>Oncorhynchus mykiss</em>) along the Klamath River and its tributaries. We instrumented these ponds and applied multivariate auto-regressive time series models of fine-scale temperature data from ponds, tributaries, and the mainstem Klamath River to assess how off-channel ponds contributed to thermal regime diversity and thermal refuge habitat in the Klamath riverscape. Our analysis demonstrated that ponds provide diverse thermal habitats that are significantly cooler than creek or mainstem river habitats, even during severe drought. Wavelet analysis of long-term (10 years) temperature data indicated that thermal buffering (i.e. dampening of diel variation) increased over time but was disrupted by drought conditions in 2021. Our analysis demonstrates that in certain situations, human-made off-channel ponds can increase thermal diversity in modified riverscapes even during drought conditions, potentially benefiting floodplain-dependent cold-water species. Restoration actions that create and maintain thermal regime diversity and thermal refuges will become an essential tool to conserve biodiversity in climate-sensitive watersheds. </p>
Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability
<p>Datasets used for the analysis done for the paper "Elevation differently shapes functional diversity patterns in understory forest communities when considering intraspecific and interspecific trait variability".</p> <p>Files present are:</p> <p>-Species x Plot (vegetation releveés).</p> <p>-Plot x Environment.</p> <p>-Plot x CWM_inter for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover.</p> <p>-Plot x CWM_intra for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation.</p> <p>-Plot x SES-FD_inter (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) using the traits fixed for species, i.e., holding traits constant as the species mean, thus incorporating only turnover.</p> <p>-Plot x SES-FD_intra (Standard Effect Size Functional Diversity) for Plant height, Leaf area, Specific Leaf Area (SLA), Leaf Dry Matter Content (LDMC) based on an individual by trait matrix, therefore incorporating both turnover and intraspecific trait variation.</p> <p>All analysis were carried out using the software R version 4.1.2 (R Foundation for Statistical Computing, Vienna, Austria, <a href="http://www.R-project.org">http://www.R-project.org</a>) and can be consulted on GitHub https://github.com/AriannaFerrara/Elevation-and-Intraspecific-trait-variability.git</p>
Fig. 5 in Late Silurian palynomorphs from the Precordillera of San Juan, Argentina: Diversity, palaeoenvironmental and palaeogeographic significance
Fig. 5. Palynomorphs from the studied sections of the Los Espejos Formation of Argentina, Quebrada Ancha, Gorstian?–Ludfordian? (A, T), Quebrada Ancha, Ludfordian (B–F, H–K, N, O, Q, R), Cerro La Chilca, Ludfordian (G, L, M, P, S). A. Ammonidium cornuatum Loeblich and Wicander, 1976; MPLP 8-60677 (H27/3). B. Ammonidium ludloviense (Dorning, 1981) Mullins, 2001; MPLP 2-60704 (T22/2). C. Ammonidium maravillosum (Cramer, 1969) Thusu, 1973a; MPLP 7-60736 (S29/1). D. Ammonidium waldronense (Tappan and Loeblich, 1971) Dorning, 1981; MPLP 8-60677 (T50/2). E. Ammonidium sp. A in Mullins 2001; MPLP 7-60736 (N27/1). F. Indeterminated miospore, MPLP 8-60677 (O44/2). G. Baculatireticulatus baculatus Al-Ameri, 1984; MPLP 4-61059 (J45/4). H. Baculatireticulatus sp.; MPLP 7-60736 (N43/2). I. Breconisporites sp.; MPLP 8-60677 (U33). J. Buedingiisphaeridium lunatum Le Hérissé, 1989; MPLP 4-61059 (D47). K. Carminella maplewoodensis Cramer, 1968; slide MPLP 7-60736 (R26/2). L. Chelinospora cf. cantabrica Richardson, Rodríguez, and Sutherland 2001; MPLP 5-61060 (U38). M. Chelinospora sanpetrensis (Rodríguez, 1978) Richardson, Rodríguez, and Sotherland 2001; MPLP 7-61062 (C35). N. Chelinospora verrucata var. verrucata Morphon in García Muro et al., 2014b; slide MPLP 8-60677 (K43/1). O. Clypeolus tortugaides (Cramer, 1966a) Miller, Playford, and Le Hérissé, 1997; MPLP 4-62521 (V42/2). P. cf. Concentricosisporites agradabilis (Rodríguez, 1978) Rodríguez, 1983; MPLP 6-61061 (H45/1). Q. Confossuspora sp.; MPLP 2-60704 (O42/1). R. Cordobesia uruguayensis (MartinezMacchiavello, 1968) Pöthé de Baldis, 1977; MPLP 3-60659 (E46/4). S. Coronaspora cromatica (Rodríguez, 1978) Richardson, Rodríguez, and Sutherland, 2001; MPLP 4-61059 (Q28). T. Cymatiosphaera acuminata Mullins, 2001; MPLP 8-60677 (G48/3). Scale bars 20 μm.
Fig. 4 in Late Silurian palynomorphs from the Precordillera of San Juan, Argentina: Diversity, palaeoenvironmental and palaeogeographic significance
Fig. 4. Ludlow–Přídolí (424 My) phytoplankton and miospore assemblages plotted on a palaoegeographic reconstruction using BugPlate software (Torsvik 2009). 1, UK (Richardson and Lister 1969; Lister 1970; Richardson et al. 1981; Burgess and Richardson 1995; Wellman and Richardson 1996; Richards and Mullins 2003; Mullins 2001, 2004); 2, Gotland, Sweeden (Stricanne et al. 2004; Stricanne et al. 2006); 3, Allenport, USA (Beck and Strother 2008); 4, Nova Scotia, Canada (Beck and Strother 2001); 5, Ontario, Canada (McGregor and Camfield 1976); 6, Sweden (Mehlqvist et al. 2012; Mehlqvist et al. 2014); 7, Libya (Richardson and Ioannides 1973; Rubinstein and Steemans 2002; Le Hérissé 2002); 8, Saudia Arabia (Le Hérissé et al. 1995; Wellman et al. 2000; Breuer et al. 2017); 9, Poland (Porębska et al. 2004); 10, Turkey (Steemans et al. 1996; Lakova and Göncüoğlu 2005); 11, Iraq (Al-Almeri 1984; 2010); 12, Maranhão Basin, Brazil (Brito 1967); 13, Bolivia (Cramer et al. 1974; Kimyai 1983; Racheboeuf et al. 2012); 14, Spain and West France (Rodríguez González 1978; 1983; Steemans 1989; Cramer 1964a; Richardson et al. 2001); 15, Amazon Basin, Brazil (Cardoso 2005; Steemans et al. 2008); 16, Santiago del Estero, Argentina (Pöthe de Baldis 1974a); 17, Precordillera Argentina (Rubinstein 1992a, b, 1995; García Muro et al. 2014b; this contribution). References discussed in the papers are also included.
Fig. 11 in Late Silurian palynomorphs from the Precordillera of San Juan, Argentina: Diversity, palaeoenvironmental and palaeogeographic significance
Fig. 11. Palynomorphs from the studied sections of the Los Espejos Formation of Argentina, Quebrada Ancha, Přídolí (A, F, K, M, N), Cerro La Chilca, Gorstian?–Ludfordian? (B, L), Quebrada Ancha, Ludfordian (C, E, H), Cerro La Chilca, Ludfordian (D, G, I, J). A. Tylotopalla caelamenicutis Loeblich, 1970; MPLP 14-60982 (E32/3). B. Tylotopalla deerlijkianum (Martin, 1973) Martin, 1978; MPLP 2-61057 (K42/2). C. Tylotopalla robustispinosa (Downie, 1959) Mullins, 2001; MPLP 2-60704 (L42/2). D. Veryhachium trispinosum Group Servais, Vecoli, Li, Molyneux, Raevskaya, and Rubinstein, 2007; MPLP 4-61059 (E33). E. Vestitusdyadus sp.; MPLP 8-60677 (G31/1). F. Villosacapsula setosapellicula (Loeblich, 1970) Loeblich and Tappan, 1976; MPLP 9-60664 (Q30). G. Villosacapsula sp.; MPLP 5-61060 (U32/2). H. Visbysphaera cf. pirifera (Eisenack, 1954) Kiryanov, 1978; MPLP 8-60677 (T33). I. Indeterminate palynomorphs; MPLP 4-61059 (G35/4) (I1, I2 are different focus). J. cf. Veryhachium sp., with abnormal processes, distally expanded; MPLP 4-61059 (P25/3). K–N. Emphanisporites? tenuis sp. nov. K. MPLP 13-60984 (N30/2). L. MPLP 2-61057 (Q42). M. MPLP 10- 60673 (J23). N. MPLP 12-60986 (R34). Scale bars 20 μm.
Fig. 9 in Late Silurian palynomorphs from the Precordillera of San Juan, Argentina: Diversity, palaeoenvironmental and palaeogeographic significance
Fig. 9. Palynomorphs from the studied sections of the Los Espejos Formation of Argentina, Cerro La Chilca, Homerian? (A, L), Cerro La Chilca, Gorstian?–Ludfordian? (B, I), Cerro La Chilca, Ludfordian (C, H, O, Q, T), Quebrada Ancha, Ludfordian (D–G, J, N, P, R, S), Quebrada Ancha, Přídolí (K, U), Quebrada Ancha, Gorstian?–Ludfordian? (M). A–F. cf. Melikeriopalla sp. A. MPLP 1-61065 (W30/3). B. MPLP 3-61058 (L33). C. MPLP 7-61062 (P43/3). D. MPLP 2-60704 (L26). E. MPLP 3-60659 (F38). F. MPLP 4-62521 (T40/4). G. Multiplicisphaeridium arbusculum forma A of Mullins (2001); MPLP 7-60736 (D30/1). H. Multiplicisphaeridium cladum (Downie, 1963) Eisenack, 1969; MPLP 4-61059 (E50/1). I. Multiplicisphaeridium mingusi Le Hérissé, 1989; MPLP 2-61057 (M31/1). J. Multiplicisphaeridium monki Le Hérissé, 1989; MPLP 3-60659 (O45/2). K. Multiplicisphaeridium rochesterensis Cramer and Diez, 1972; MPLP 9-60664 (U27). L. Nanocyclopia sp.; MPLP 1-61065 (U38/1). M. Neoveryhachium carminae (Cramer, 1964a) Cramer, 1970; MPLP 1-60667 (P45/2). N. Onondagella asymmetrica (Deunff, 1961) Playford, 1977; MPLP 7-60736 (X44). O. cf. Oppilatala frondis (Cramer and Díez, 1972) Dorning, 1981; MPLP 4-61059 (F45). P. Oppilatala grahni Le Hérissé, 1989; MPLP 7-60736 (E38/1). Q. Oppilatala insolita (Cramer and Díez, 1972) Dorning, 1981; MPLP 4-61059 (Q50). R. Oppilatala ramusculosa (Deflandre, 1945) Dorning, 1981; MPLP 7-60736 (N37/4). S. Ozotobrachion palidodigitatus (Cramer, 1966b) Playford, 1977; MPLP 7-60736 (P48/4). T. Percultisphaera incompta Richards and Mullins, 2003; MPLP 4-61059 (W47/4). U. Polyedrixium? cf. embudum Cramer, 1964a; MPLP 9-60664 (D39/1). Scale bars 20 μm.
Energy input, habitat heterogeneity, and host specificity on avian haemosporidian diversity at continental scales
<p>The correct identification of biotic and abiotic drivers affecting parasite diversity and assemblage composition at different spatial scales is crucial for understanding how pathogen distribution responds to anthropogenic disturbance and climate change. Here, we used a database of avian haemosporidian parasites to identify such drivers and their effect on the taxonomic and phylogenetic diversity of genera Plasmodium, Haemoproteus, and Leucocytozoon from three zoogeographic regions. We explored how parasite diversity is related to energy input (i.e., temperature, precipitation, and potential evapotranspiration [PET]), to habitat heterogeneity (i.e., climatic seasonality, vegetation density, ecosystem heterogeneity, human disturbance, and host richness), and to a novel assemblage-level metric related to parasite niche overlap (degree of generalism). We found that the relative importance of the predictors differed between the three studied parasite genera and across diversity metrics. Among the most consistent predictors, host richness was positively related to the taxonomic diversity of the three genera. Energy input and human footprint explained the phylogenetic diversity of Haemoproteus. Finally, the degree of generalism explained the diversity of Plasmodium and Leucocytozoon. Our results suggest that different dimensions of haemosporidian diversity are shaped by energy input, host heterogeneity, and assembly processes related to parasite resource use within local parasite assemblages.</p>
Fig. 5 in Detection and characterization of diverse coccidian protozoa shed by California sea lions
Fig. 5. Indirect fluorescence antibody test of California sea lion sporulated oocyst cultures. Zoites derived from cultivated oocysts from animal CSL10089 (A), CSL10092 (B), and CSL10100 (C) were tested using serum from a Sarcocystis neurona-infected horse. Image D shows reactivity of serum from the S. neurona-infected horse to S. neurona culture isolate snUCD-1. Image E shows a lack of seroreactivity of negative control serum from a S. neurona-negative horse to zoite culture from CSL10089. Scale bars are 15 Mm.
Fig. 3 in Detection and characterization of diverse coccidian protozoa shed by California sea lions
Fig. 3. Three California sea lion haul-out sites (red circles) on the central California coast where fecal samples were collected from free-ranging animals. Field sample identifiers for test-positive samples are given (Ãno-, PL- and WR-) at each location. Coccidian parasite genotypes and species amplified in sample DNA are indicated in parentheses: A, Coccidia A; B, Coccidia B; Sn, Sarcocystis neurona-like; unchar, uncharacterized species. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.).
Major changes in fish thermal habitat diversity in Canada's Arctic lakes due to climate change
<p>Climate warming is a major disruptor of fish community structure globally. We use large-scale geospatial analyses of 447,077 Canadian Arctic lakes to predict how climate change would impact lake thermal habitat diversity across the Arctic landscape. Increases in maximum surface temperature (+2.4–6.7 °C), ice-free period (+14–38 days), and thermal stratification presence (+4.2–18.9%) occur under all climate scenarios. Lakes, currently fishless due to deep winter ice, open up; many thermally uniform lakes become thermally diverse. Resilient coldwater habitat supply is predicted; however, thermally diverse lakes shift from providing almost exclusively coldwater habitat to providing substantial coolwater habitat and previously absent warmwater habitat. Across terrestrial ecozones, most lakes exhibit major shifts in thermal habitat. The prevalence of thermally diverse lakes more than doubles, providing refuge for coldwater taxa. Ecozone-specific differences in the distribution of thermally diverse and thermally uniform lakes require different management strategies for adapting fish resource use to climate change.</p>
Data and code from: SIDERITE: Unveiling Hidden Siderophore Diversity in the Chemical Space Through Digital Exploration
<h1>TMAP of COCONUT database</h1> <p>The script and data used in SIDERITE paper to generate TMAP picture (Figure S3 in supplementart material).</p> <p>Requirement: tmap</p> <p>You can install tmap by conda.</p> <blockquote> <p>conda create -n tmap python=3.7</p> <p>conda activate tmap</p> <p>conda install -c tmap tmap</p> <p>pip install faerun</p> <p>pip install matplotlib</p> <p>conda install scipy</p> <p>conda install -c rdkit rdkit</p> <p>conda install -c conda-forge mhfp</p> </blockquote> <p> </p> <p>Usage: python plot_COCONUT.py</p> <p>Then it will use COCONUT.csv to generate index.html and index.js. Open index.html to see result.</p> <h1>Other large input files</h1> <p>Tanimoto_COCONUT_SIDERITE.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/Clustering_coconut.m">SIDERITE/predicted_new/Clustering_coconut.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>Sid_structure_output3.xlsx is used in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/statistics/Figure1.m" target="_blank" rel="noopener">SIDERITE/statistics/Figure1.m at main · RuolinHe/SIDERITE</a>, <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a> and <a href="https://github.com/RuolinHe/SIDERITE/blob/main/siderophore_process/Sid_process_code.m" target="_blank" rel="noopener">SIDERITE/siderophore_process/Sid_process_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT4MetFrag_Canonical.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>.</p> <p> </p> <p>COCONUT_r.txt is the output file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/tmap_code.m" target="_blank" rel="noopener">SIDERITE/TAMP/tmap_code.m at main · RuolinHe/SIDERITE</a>. and the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/predicted_new/isSiderophore1.py" target="_blank" rel="noopener">SIDERITE/predicted_new/isSiderophore1.py at main · RuolinHe/SIDERITE.</a></p> <p> </p> <p>COCONUT4MetFrag.xlsx is the input file in <a href="https://github.com/RuolinHe/SIDERITE/blob/main/TAMP/CheckSMILES2.py" target="_blank" rel="noopener">SIDERITE/TAMP/CheckSMILES2.py at main · RuolinHe/SIDERITE</a>.</p> <p> </p>
ScienceDex guides
Understand access before you commit
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.