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955 results for “Subtropical”
FIG. 1 in Revision of the genus Actinostella (Cnidaria: Actiniaria: Actinioidea) from tropical and subtropical western Atlantic and eastern Pacific: redescriptions and synonymies
FIG. 1. Geographic distribution of species of Actinostella.
Sühs_et_al_2024-subtropical_plant_interactions
<p>Dataset</p>
Figure 4 in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams
Figure 4. Length frequency distribution of the fibers.
Figure 2 in Far from urban areas: plastic uptake in fish populations of subtropical headwater streams
Figure 2. Plastic fibres from fish intestines.
Figure 2 in Spatio-temporal variability in the Cladocera assemblage of a subtropical hypersaline lagoon
Figure 2. TS-diagram. At the 12 collection stations.
Self-Healing Concrete using Encapsulated Bacterial Spores in a Simulated Hot Subtropical Climate
<p>Corresponding data set for Tran-SET Project No. 18CLSU02. Abstract of the final report is stated below for reference:</p> <p>"Bacterial concrete has become one of the most promising self-healing alternatives due to its capability to seal crack widths through microbial induced calcite precipitation (MICP). In this study, two bacterial strains were embedded at varying dosages (by weight of cement) in concrete. Beam specimens were used to identify the maximum crack-sealing efficiency, while cylinder samples were used to determine their effects on the intrinsic mechanical properties, as well as its stiffness recovery over time after inducing damage. The concrete specimens were cured in wet-dry cycles to determine their feasibility in Region 6. The results showed that the specimen groups with the highest calcium alginate concentrations (including the control specimens with embedded alginate beads but no bacteria) resulted in higher increases in stiffness recovery. Similarly, the beam samples containing alginate beads (also including the Control 3%C specimen group) had superior crack-healing efficiencies than the control samples without alginate beads (Control NC). This was attributed to the fact that the alginate beads act as a reservoir that can further enhance the autogenous healing capability of concrete. Overall, further research is recommended to verify whether the promising results reported in the literature (relating to self-healing mortar) correlate with concrete proportionally. In addition, there is a need to explore the factors that can maximize the self-healing mechanism of bio concrete through MICP, whether an alternative encapsulation mechanism, nutrient selection, curing regime, or bacterial strain is desired."</p>
Fig. 4 in Rare Spiders Of The Genus Cyclocosmia (Arachnida: Araneae: Ctenizidae) From Tropical And Subtropical China
Fig. 4. Abdomen of Cyclocosmia latusicosta, new species, paratype, caudal view.
Fig. 1 in Rare Spiders Of The Genus Cyclocosmia (Arachnida: Araneae: Ctenizidae) From Tropical And Subtropical China
Fig. 1. Abdomen of Cyclocosmia ricketti (Pocock, 1901), caudal view.
Fig. 3 in Rare Spiders Of The Genus Cyclocosmia (Arachnida: Araneae: Ctenizidae) From Tropical And Subtropical China
Fig. 3. Burrow entrance and trapdoor of Cyclocosmia latusicosta, new species.
Synthetic Pelagic Biomass Size Spectra of the Tropical and Subtropical Atlantic - biovolume and carbon biomass data
<p>Synthetic Pelagic Biomass Size Spectra of the Tropical and Subtropical Atlantic</p> <p>Normalized size spectra data are presented for (a) biovolume and (b) for carbon contents for the following ecosystem components: Phytoplankton, zooplankton and micronekton</p> <p>Dataset Biovolume_NBSS contains the following variables, three heading lines</p> <table> <tbody> <tr> <td> <p>COLUMN</p> </td> <td> <p>HEADER</p> </td> <td> <p>DESCRIPTION</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>ConsecutiveNumber</p> </td> <td> <p>Control number</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>Cruise</p> </td> <td> <p>Cruise name</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>Reference</p> </td> <td> <p>Cruise/data record reference</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>CruiseID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>StationID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>Net_index</p> </td> <td> <p>ID, opt.</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>Date</p> </td> <td> <p>YYYY-MM-DD</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>Longitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>Latitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>Target organisms</p> </td> <td> <p>Phytoplankton</p> <p>Zooplankton</p> <p>Detritus + zooplankton (only for UVP)</p> <p>Mesopelagic fishes</p> <p>invMicronekton – invertebrate micronekton only</p> <p>totMicronekton – mesopelagic fishes + invertebrate Micronekton</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>Gear</p> </td> <td> <p>Gear applied</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>Operation mode</p> </td> <td> <p>Gear operation mode</p> </td> </tr> <tr> <td> <p>13</p> </td> <td> <p>Catching Depth max [m]</p> </td> <td> <p>Catching depth maximum</p> </td> </tr> <tr> <td> <p>14</p> </td> <td> <p>Catching Depth min [m]</p> </td> <td> <p>Catching depth minimum</p> </td> </tr> <tr> <td> <p>15</p> </td> <td> <p>Biomass determination</p> </td> <td> <p>Biomass Determination method</p> </td> </tr> <tr> <td> <p>16</p> </td> <td> <p>Contact Person</p> </td> <td> <p>Contact person</p> </td> </tr> <tr> <td> <p>17</p> </td> <td> <p>Day/night</p> </td> <td> <p>Sampling time</p> </td> </tr> <tr> <td> <p>18</p> </td> <td> <p>Region</p> </td> <td> <p>Region affiliation</p> </td> </tr> <tr> <td> <p>19-74</p> </td> <td>mm3 m-3 mm-3</td> <td> <p>Biovolume data normalized, additionally with reference to "Size class interval (mm-mm]" and "log mm3/individual"</p> </td> </tr> </tbody> </table> <p> </p> <p> </p> <p>Dataset Carbon_NBSS contains the following variables, three heading lines</p> <table> <tbody> <tr> <td> <p>COLUMN</p> </td> <td> <p>HEADER</p> </td> <td> <p>DESCRIPTION</p> </td> </tr> <tr> <td> <p>1</p> </td> <td> <p>ConsecutiveNumber</p> </td> <td> <p>Control number</p> </td> </tr> <tr> <td> <p>2</p> </td> <td> <p>Cruise</p> </td> <td> <p>Cruise name</p> </td> </tr> <tr> <td> <p>3</p> </td> <td> <p>Reference</p> </td> <td> <p>Cruise/data record reference</p> </td> </tr> <tr> <td> <p>4</p> </td> <td> <p>CruiseID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>5</p> </td> <td> <p>StationID</p> </td> <td> <p>ID</p> </td> </tr> <tr> <td> <p>6</p> </td> <td> <p>Net_index</p> </td> <td> <p>ID, opt.</p> </td> </tr> <tr> <td> <p>7</p> </td> <td> <p>Date</p> </td> <td> <p>YYYY-MM-DD</p> </td> </tr> <tr> <td> <p>8</p> </td> <td> <p>Longitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>9</p> </td> <td> <p>Latitude</p> </td> <td> <p>Position, decimal degrees</p> </td> </tr> <tr> <td> <p>10</p> </td> <td> <p>target organisms</p> </td> <td> <p>Phytoplankton</p> <p>Zooplankton</p> <p>Mesopelagic fishes</p> <p>invMicronekton – invertebrate micronekton only</p> <p>totMicronekton – mesopelagic fishes + invertebrate Micronekton</p> </td> </tr> <tr> <td> <p>11</p> </td> <td> <p>Gear</p> </td> <td> <p>Gear applied</p> </td> </tr> <tr> <td> <p>12</p> </td> <td> <p>Operation mode</p> </td> <td> <p>Gear operation mode</p> </td> </tr> <tr> <td> <p>13</p> </td> <td> <p>Catching Depth max [m]</p> </td> <td> <p>Catching depth maximum</p> </td> </tr> <tr> <td> <p>14</p> </td> <td> <p>Catching Depth min [m]</p> </td> <td> <p>Catching depth minimum</p> </td> </tr> <tr> <td> <p>15</p> </td> <td> <p>Biomass determination</p> </td> <td> <p>Biomass Determination method</p> </td> </tr> <tr> <td> <p>16</p> </td> <td> <p>Contact Person</p> </td> <td> <p>Contact person</p> </td> </tr> <tr> <td> <p>17</p> </td> <td> <p>filtered volume [m3]</p> </td> <td> <p> </p> </td> </tr> <tr> <td> <p>18</p> </td> <td> <p>Day/night</p> </td> <td> <p>Sampling time</p> </td> </tr> <tr> <td> <p>19</p> </td> <td> <p>SST (C)</p> </td> <td> <p>In situ SST</p> </td> </tr> <tr> <td> <p>20</p> </td> <td> <p>Temperature (C)</p> </td> <td> <p>In situ temperature</p> </td> </tr> <tr> <td> <p>21</p> </td> <td> <p>Salinity</p> </td> <td> <p>In situ salinity (PSU)</p> </td> </tr> <tr> <td> <p>22</p> </td> <td> <p>Oxygen (umol/kg)</p> </td> <td> <p>In situ oxygen (µmol/kg)</p> </td> </tr> <tr> <td> <p>23</p> </td> <td> <p>Region</p> </td> <td> <p>Region affiliation</p> </td> </tr> <tr> <td> <p>24-79</p> </td> <td>gC m-3 g-1C</td> <td> <p>Carbon biomass data normalized, additionally with reference to " Size class number" and "</p> <p>Exponent"</p> </td> </tr> </tbody> </table> <p> </p>
Table 1 in Colossoma macropomum (Characiformes: Serrasalmidae) adapted to new climate regime: differential gene expression from farmed tambaqui juveniles raised in subtropical and tropical regions
<p><b>Table 1:</b> Details of target genes (<i>hif-1α</i>, <i>hsp70</i>, <i>ras</i>, <i>mstn</i>, <i>acly</i>, <i>per-1</i>, <i>cry-1</i>, <i>ube3a</i> and <i>ogt</i>) and reference genes (<i>β- tubulin</i> and <i>β- actin</i>) primers.</p><table><tbody><tr><th><b>Gene</b></th><th><b>Length (bp)</b></th><th><b>R</b> <b>2</b></th><th><b>Efficiency (%)</b></th><th><b>Primers sequence (5ʹ-3ʹ) forward/reverse</b></th></tr></tbody><tbody><tr><th><i>tubulin</i> -F</th><td>20</td><td>0.99</td><td>109.5</td><td>GACGTGGTGCCCAAAGATGT</td></tr><tr><th><i>tubulin</i> -R</th><td>18</td><td>TGGATGGTGCGCTTGGT</td></tr><tr><th><i>β- actin</i> -F</th><td>21</td><td>0.99</td><td>100.5</td><td>GCTGTTTTCCCCTCCATTGTT</td></tr><tr><th><i>β- actin</i> -R</th><td>19</td><td>TCCCATGCCAACCATCACT</td></tr><tr><th><i>hif-1α</i> -F</th><td>20</td><td>0.99</td><td>105.2</td><td>CTTCTGAGCTCTGATGAGGC</td></tr><tr><th><i>hif-1α</i> -R</th><td>20</td><td>GAAAGCACCATCAGGAAGCC</td></tr><tr><th><i>hsp-70</i> -F</th><td>20</td><td>0.99</td><td>100.9</td><td>GCAAGGAGAACAAGATCACC</td></tr><tr><th><i>hsp-70</i> -R</th><td>19</td><td>CACTCCGTTGCACTTGTCC</td></tr><tr><th><i>mstn</i> -F</th><td>20</td><td>0.98</td><td>100.5</td><td>AATCCAAGCGAGGGAAAAGC</td></tr><tr><th><i>mstn</i> -R</th><td>22</td><td>CCTCCATCACCTGAAAGGTCTT</td></tr><tr><th><i>ras</i> -F</th><td>20</td><td>0.97</td><td>99.31</td><td>CCAGTACATGAGGACAGGAG</td></tr><tr><th><i>ras</i> -R</th><td>20</td><td>CAAGCACCATTGGCACATCG</td></tr><tr><th><i>acly</i> -F</th><td>19</td><td>0.99</td><td>100.7</td><td>ATCATCTCCCGCACTACAG</td></tr><tr><th><i>acly</i> -R</th><td>19</td><td>TACCTCCAATCTCTCCCAG</td></tr><tr><th><i>ube3a</i> -F</th><td>21</td><td>0.98</td><td>103.3</td><td>GCCATAAGCAAGCAGCACAAC</td></tr><tr><th><i>ube3a</i> -R</th><td>19</td><td>CCAGTCAGTCCGCACATCG</td></tr><tr><th><i>per-1</i> -F</th><td>20</td><td>0.98</td><td>104.1</td><td>TGTTGAAGTTTGTGCCCCAG</td></tr><tr><th><i>per-1</i> -R</th><td>18</td><td>CAGTCCAGATGCTCCTCC</td></tr><tr><th><i>cry-1</i> -F</th><td>19</td><td>0.99</td><td>103.6</td><td>GTCCAACAGCCCTCAAACT</td></tr><tr><th><i>cry-1</i> -R</th><td>18</td><td>TACGCCAAGCACTCCAGA</td></tr><tr><th><i>ogt</i> -F</th><td>19</td><td>0.99</td><td>104.1</td><td>CCTCCCTTTGCTGTGTTCC</td></tr><tr><th><i>ogt</i> -R</th><td>20</td><td>TGTCTGCTTTCCGCTTTCGC</td></tr></tbody></table>
Data from: Odonate species occupancy frequency distribution and abundance – occupancy relationship patterns in temporal and permanent water bodies in a subtropical area
<p>This paper investigates species richness and species occupancy frequency distributions (SOFD) as well as patterns of abundance-occupancy relationship (SAOR) in Odonata (dragonflies and damselflies) in a subtropical area. A total of 82 species and 1983 individuals were noted from 73 permanent and temporal water bodies (lakes and ponds) in the Pampa biome in southern Brazil. Odonate species occupancy ranged from 1 to 54. There were few widely distributed generalist species and several specialist species with a restricted distribution. About 70% of the species occurred in less than 10% of the water bodies, yielding a surprisingly high number of rare species, often making up the majority of the communities. No difference in species richness was found between temporal and permanent water bodies. Both temporal and permanent water bodies had odonate assemblages that fitted best with the unimodal satellite SOFD pattern. It seems that unimodal satellite SOFD pattern frequently occurred in the aquatic habitats. The SAOR pattern was positive and did not differ between permanent and temporal water bodies. Our results are consistent with a niche-based model rather than a metapopulation dynamics model.</p>
Combined genotype and phenotype analyses reveal patterns of genomic adaptation to local environments in the subtropical oak Quercus acutissima
Understanding the effects of the demographic dynamics and environmental heterogeneity on the genomic variation of forest species is important not only for uncovering the evolutionary history of the species but also for predicting their ability to adapt to climate change. In this study, we combined a common garden experiment with range-wide population genomics analyses to infer the demographic history and characterize patterns of local adaptation in a subtropical oak species, Quercus acutissima. We scanned about 8% of the oak genome using a balanced representation of both genic and non-genic regions and identified a total of 55,361 SNPs in 167 trees. Genomic diversity analyses revealed an east-west split in the species distribution range. Coalescent-based model simulations inferred a late Pleistocene divergence in Q. acutissima between the east and west groups as well as subsequent pre-glaciation population expansion events. Consistent with observed genetic differentiation, morphological traits also showed east-west differentiation and the biomass allocation in seedlings was significantly associated with precipitation. Environment was found to have a significant and stronger impact on the non-neutral than the neutral SNPs, and also significantly associated with the phenotypic differentiation, suggesting that apart from the geography, environment had played a role in determining non-neutral and phenotypic variation. Our approach, which combined a common garden experiment with landscape genomics data, validated the hypothesis of local adaptation of this long-lived oak tree of subtropical China. Our study joins the small number of studies that have combined genotypic and phenotypic data to detect patterns of local adaptation.
Figure 4 in Comparative population biology of Uca rapax (Smith, 1870) (Brachyura, Ocypodidae) from two subtropical mangrove habitats on the Brazilian coast
Figure 4. Uca rapax. Monthly size–frequency distributions for the Ubatumirim population.
Figure 3 in Comparative population biology of Uca rapax (Smith, 1870) (Brachyura, Ocypodidae) from two subtropical mangrove habitats on the Brazilian coast
Figure 3. Uca rapax. Monthly size–frequency distributions for the Itamambuca population.
Tree species richness differentially affects the chemical composition of leaves, roots and root exudates in four subtropical tree species - Sampling Raw Data
<p>Sampling Raw Data for the manuscript "<strong>Tree species richness differentially affects the chemical composition of leaves, roots and root exudates in four subtropical tree species </strong>" </p> <p>R Code for producing the sunburst plots from the data obtained by classyFire</p> <p> </p>
FIGURE 7 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 7: Distribution of the fossil E. glaesi and of the four extant species of the genus Eunicolina, shown on paleogeographic map of Europe (c. 40 Mya) (adapted from maps given by Charbit et al. 2007, Swedo, Sontag 2013, Scotese 1997).
FIGURE 6 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 6: Genito-anal area: A – Disposition of genital and anal shields (drawn from the extant species E. travei) Aa, Ab: ventral view, female (a), male (b); Ac: male lateral view. Eunicolina glaesi n. sp.: B-C – extremity of the opisthosoma, lateral view (B) and interpretation (Ca, Cb, Cc).
FIGURE 5 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 5: Eunicolina glaesi n. sp.: A – Oculo-pustular zone. bo.p: trichobthria, la?: supposed insertion of the la seta; lb: seta lb; ly: post-ocular lyriform organ; B – Detail of the PI tarsus showing the bidactylus claw, one of the two tarsal solnidia (ω). F?: possible famulus of the tarsus. Some insertions of setae are marked by circles.
FIGURE 3 in Before the summer turns to winter: the third labidostommatid genus from Baltic amber has subtropical kin
FIGURE 3:. Eunicolina glaesi n. sp.: A – Dorsal shield, anterior part; B – Detail of the posterior trichobothrium; C – Ventral view of epimeral plates and detail of ornamentation. Abbreviations: AS: additional posterior seate of the infracapitulum; bo.a, bo.p: anterior and posterior bothridia; CH: Chelicera; cha, chb cheliceral setae; gr, la: ocular and lateral setae of the dorsal shield; PI, PII: legs I and II; Pp: palp. ω1: tarsal solenidion of the palp.
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Allen Brain Atlas
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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
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