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FIGURE 6 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 6. Known geographic distribution of Ololygon skuki. The white star indicates the type locality in Mata do Catolé, municipality of Maceió, state of Alagoas. The white dot indicates the new record for the state of Bahia in the municipality of São Sebastião do Passé. We only consider records with voucher specimens in collections.
FIGURE 3 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 3. Male topotypes of Ololygon skuki in life. Body in (A) dorsolateral, (C) dorsal, (D) ventral, and (E) lateral views of CFBH 47968 (male, SVL 14.7 mm). Body in (B) in dorsolateral view of MHNUFAL 12390 (male, SVL 15.3 mm). (F) Body in posterodorsal view showing the hidden posterior surfaces of thighs and shanks of CFBH 47968. Photo (B): João Almeida.
FIGURE 2 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 2. Nuptial pad on fingers II and III of the left hand of the topotype specimen of Ololygon skuki (CFBH 47968, male). Hand in (A) ventral and (B) dorsal (digitally reversed) views. The arrow indicates the glandular acini of the nuptial pad on Finger III. Scales = 0.2 mm.
FIGURE 8 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 8. Gular region of males of Ololygon argyreornata showing different degrees of external distension of the vocal sac. (A) CFBH 5346, (B) CFBH 127, and (C) CFBH 5347. Scales = 2.5 mm.
FIGURE 1 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 1. Ololygon skuki (CFBH 47968, male topotype, SVL 14.7 mm). (A) Dorsal and (B) ventral views of the body. (C) Right hand and (D) right foot in ventral view. (E) Head in lateral view. Scales = 1 mm.
FIGURE 5 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 5. Phylogenetic relationships of the Ololygon argyreornata group as recovered in one of the 2,450 most parsimonious trees obtained from the analysis of molecular dataset with gaps as a fifth state under equal weights for all transformations. All nodes shown are retained in the strict consensus. Values around nodes are parsimony jackknife supports. An asterisk (*) indicates lineages with 100% jackknife frequencies. Nodes lacking values have <50% jackknife support. See Araujo-Vieira et al. (2023: appendix S1) for the list of GenBank accession numbers and localities.
FIGURE 4 in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
FIGURE 4. Vocalization of Ololygon skuki (MHNUFAL-SOM 001; unvouchered specimen). (A) Oscillogram (above) and spectrogram (below) of one call. (B) Oscillogram (above) and spectrogram (below) of two notes in the red brackets of (A). (C) Expanded oscillogram of the first note of (B).
Anonymised Phone Call Dataset for Anomaly Detection
<p>The dataset provides anonymized information related to phone calls, including the following details:</p> <p>1. Origin Numbers (A-Numbers)<br>2. Destination Numbers (B-Numbers)<br>3. Timestamp of the call<br>4. Call Result, indicating whether the call was blacklisted (coded as 001) or not (coded as 000)</p> <p>The dataset is divided into two subsets with the following characteristics:</p> <p>Dataset 1<br>- Collection Period: 24th July 2018 to 21st October 2018<br>- Duration: 89 days<br>- Total Records: 83,366,367 examples<br>- Unique A-Numbers: 9,006,011<br>- Unique B-Numbers: 2,387,932</p> <p>Dataset 2<br>- Collection Period: 1st June 2019 to 30th June 2019<br>- Duration: 29 days<br>- Total Records: 32,879,670 examples<br>- Unique A-Numbers: 3,217,069<br>- Unique B-Numbers: 1,380,235</p>
Figure 2 in What do frog calls tell us about males? The advertisement call of Physalaemus albifrons (Amphibia: Leptodactylidae) in the Brazilian semiarid region does not reflect either gonadal investment or energy storage
Figure 2. On the left, testis (solid arrow) and fat bodies (dashed arrow) of Physalaemus albifrons (CHSA. A 140). On the right, spectrogram (top) and oscillogram (bottom) of the typical harmonic note of the advertisement call of Physalaemus albifrons (CASA 241).
Figure 1 in What do frog calls tell us about males? The advertisement call of Physalaemus albifrons (Amphibia: Leptodactylidae) in the Brazilian semiarid region does not reflect either gonadal investment or energy storage
Figure 1. Male of Physalaemus albifrons calling in a temporary pond in the Brazilian semiarid region. Photograph: Milena Wachlevski.
Voice data in Dioula language relating to the words Yes, No, Call, Next, Previous, Dial, Stop, True, False, Enter and Exit
<p><span>For this project entitled “Development of a speech recognition model for under-resourced languages”, the collected dataset includes audio recordings of native speakers of the Dioula language pronouncing a series of specific keywords such as “Yes”, “No”, “Call”, “Next”, “Previous”, “Dial”, “Stop”, “True”, “False”, “Enter” and “Exit”. These recordings were obtained in diverse environments, with a wide variety of speakers to ensure that the different tones, accents, and phonetic variations specific to Dioula are taken into account. Each audio file was assigned to a category corresponding to the spoken word, creating a class-structured dataset. This corpus will be used to train a speech recognition model using deep learning techniques, with the objective of improving recognition accuracy in real contexts. This database is essential for the design and evaluation of a model capable of facilitating access and voice interaction for the Dioula community.</span></p>
Fractiformers: A New Paradigm in AI Architecture – Whitepapers, Prototypes, and Industry Call-to-Action
<p>This record introduces Fractiformers, a pioneering architecture that redefines traditional transformer models by incorporating fractal-based attention mechanisms, recursive processing, quantum-inspired superposition, and adaptive context management. Developed to address the limitations of transformer-based models in handling long-range dependencies, context adaptation, and computational efficiency, Fractiformers represent a leap forward in AI’s ability to manage complex, dynamic data at scale.</p> <p> </p> <p>Included in this record are detailed whitepapers that outline the theoretical framework, potential applications, and comparative advantages of Fractiformers over traditional transformers. These whitepapers also serve as a call-to-action for GPU manufacturers and AI developers, encouraging collaboration to build hardware and applications optimized for Fractiformers. A prototype implementation is also provided to demonstrate the architecture’s practical benefits, showcasing how Fractiformers outperform conventional models in resource efficiency, contextual coherence, and adaptability.</p> <p> </p> <p>Key Features:</p> <p> </p> <p>• Whitepapers: Comprehensive analysis of Fractiformer architecture, including comparisons with transformers and a breakdown of its unique recursive, fractal, and adaptive components.</p> <p>• Prototype Code: A demonstration prototype to showcase Fractiformers’ performance advantages in handling complex, long-range contexts.</p> <p>• Industry Call-to-Action: An open letter urging GPU manufacturers and AI developers to collaborate on Fractiformer-compatible hardware, with an invitation to participate in joint research and development initiatives.</p> <p> </p> <p>Applications: This record is valuable for AI researchers, GPU manufacturers, and developers aiming to push the boundaries of AI architecture, particularly in fields that demand high-performance, contextually adaptive models such as conversational AI, autonomous systems, and advanced NLP applications.</p>
TABLE 2. Uncorrected p in Phylogenetic position, morphological data, call, and geographic distribution of the elusive treefrog Ololygon skuki (Hylidae: Hylinae: Scinaxini)
<p><b>TABLE 2.</b> Uncorrected p-distances (%) between the 16SrDNA gene fragment sequences for the <i>Ololygon argyreornata</i> group. See Araujo-Vieira <i>et al.</i> (2023: appendix S1) for the list of GenBank accession numbers and localities.</p><table><tbody><tr><th></th><th>Voucher</th><th>1</th><th>2</th><th>3</th><th>4</th><th>5</th><th>6</th><th>7</th><th>8</th><th>9</th><th>10</th><th>11</th><th>12</th><th>13</th><th>14</th><th>15</th><th>16</th><th>17</th><th>18</th><th>19</th><th>20</th><th>21</th><th>22</th><th>23</th><th>24</th><th>25</th><th>26</th></tr></tbody><tbody><tr><th>1</th><td><i>O. argyreornata</i> A CFBH 14991</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>2</th><td><i>O. argyreornata</i> B CFBH 32028</td><td>2.4</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>3</th><td><i>O. argyreornata</i> A CFBHt2199</td><td>0.2</td><td>2.6</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>4</th><td><i>O. argyreornata</i> A CFBHt2209</td><td>0.0</td><td>2.4</td><td>0.2</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>5</th><td><i>O. argyreornata</i> A CFBHt2212</td><td>0.0</td><td>3.2</td><td>0.3</td><td>0.0</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>6</th><td><i>O. argyreornata</i> A MNRJ 34915</td><td>0.2</td><td>2.6</td><td>0.4</td><td>0.2</td><td>0.3</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>7</th><td><i>O. argyreornata</i> A MNRJ 38399</td><td>0.0</td><td>2.4</td><td>0.2</td><td>0.0</td><td>0.0</td><td>0.2</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>8</th><td><b><i>O. skuki</i> CFBH 47968</b></td><td><b>12.9</b></td><td><b>11.7</b></td><td><b>13.1</b></td><td><b>12.9</b></td><td><b>14.8</b></td><td><b>12.9</b></td><td><b>12.9</b></td><td><b>-</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>9</th><td><b><i>O. skuki</i> MHNUFAL 12390</b></td><td><b>12.9</b></td><td><b>11.7</b></td><td><b>13.1</b></td><td><b>12.9</b></td><td><b>14.8</b></td><td><b>12.9</b></td><td><b>12.9</b></td><td><b>0.0</b></td><td><b>-</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>10</th><td><b><i>O. skuki</i> UFBA 10246</b></td><td><b>12.5</b></td><td><b>11.3</b></td><td><b>12.7</b></td><td><b>12.5</b></td><td><b>15.1</b></td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>0.4</b></td><td><b>0.4</b></td><td><b>-</b></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>11</th><td><i>O.</i> sp. 2 CFBH19504</td><td>3.0</td><td>2.4</td><td>3.2</td><td>3.0</td><td>3.9</td><td>3.2</td><td>3.0</td><td><b>11.5</b></td><td><b>11.5</b></td><td><b>11.1</b></td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>12</th><td><i>O.</i> sp. 2 CFBH10902</td><td>3.2</td><td>2.4</td><td>3.4</td><td>3.2</td><td>4.0</td><td>3.4</td><td>3.2</td><td><b>11.6</b></td><td><b>11.6</b></td><td><b>11.1</b></td><td>1.5</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>13</th><td><i>O.</i> sp. 2 CFBH31021</td><td>3.2</td><td>2.6</td><td>3.4</td><td>3.2</td><td>4.1</td><td>3.4</td><td>3.2</td><td><b>11.9</b></td><td><b>11.9</b></td><td><b>11.4</b></td><td>1.5</td><td>1.1</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>14</th><td><i>O.</i> sp. 4 CFBH38367</td><td>4.3</td><td>4.1</td><td>4.5</td><td>4.3</td><td>5.6</td><td>4.5</td><td>4.3</td><td><b>13.2</b></td><td><b>13.2</b></td><td><b>12.8</b></td><td>3.0</td><td>3.3</td><td>3.5</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>15</th><td><i>O.</i> sp. 4 CFBH38892</td><td>4.3</td><td>4.1</td><td>4.5</td><td>4.3</td><td>5.6</td><td>4.5</td><td>4.3</td><td><b>13.2</b></td><td><b>13.2</b></td><td><b>12.8</b></td><td>3.0</td><td>3.3</td><td>3.5</td><td>0.0</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>16</th><td><i>O.</i> sp. 5 495</td><td>7.4</td><td>6.5</td><td>7.6</td><td>7.4</td><td>9.6</td><td>7.6</td><td>7.4</td><td><b>11.4</b></td><td><b>11.4</b></td><td><b>10.9</b></td><td>6.3</td><td>6.0</td><td>6.7</td><td>7.6</td><td>7.6</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>17</th><td><i>O.</i> sp. 5 CFBH32489</td><td>7.3</td><td>6.3</td><td>7.4</td><td>7.3</td><td>9.3</td><td>7.4</td><td>7.3</td><td><b>11.2</b></td><td><b>11.2</b></td><td><b>10.8</b></td><td>6.1</td><td>5.8</td><td>6.5</td><td>7.4</td><td>7.4</td><td>0.2</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>18</th><td><i>O.</i> sp. 5 MTR00285</td><td>6.5</td><td>6.1</td><td>6.7</td><td>6.5</td><td>8.6</td><td>6.7</td><td>6.5</td><td><b>11.0</b></td><td><b>11.0</b></td><td><b>10.2</b></td><td>5.6</td><td>5.6</td><td>6.0</td><td>6.9</td><td>6.9</td><td>2.8</td><td>2.6</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>19</th><td><i>O.</i> sp. 6 CFBH32106</td><td>9.1</td><td>7.4</td><td>9.3</td><td>9.1</td><td>11.2</td><td>9.3</td><td>9.1</td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>11.6</b></td><td>7.6</td><td>7.6</td><td>7.4</td><td>8.7</td><td>8.7</td><td>8.4</td><td>8.5</td><td>8.5</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>20</th><td><i>O.</i> sp. 6 CFBH32110</td><td>9.1</td><td>7.4</td><td>9.3</td><td>9.1</td><td>11.2</td><td>9.3</td><td>9.1</td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>11.6</b></td><td>7.6</td><td>7.6</td><td>7.4</td><td>8.7</td><td>8.7</td><td>8.4</td><td>8.5</td><td>8.5</td><td>0.0</td><td>-</td><td></td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>21</th><td><i>O.</i> sp. 6 CFBH36772</td><td>9.1</td><td>7.4</td><td>9.3</td><td>9.1</td><td>11.2</td><td>9.3</td><td>9.1</td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>11.6</b></td><td>7.6</td><td>7.6</td><td>7.4</td><td>8.7</td><td>8.7</td><td>8.4</td><td>8.5</td><td>8.5</td><td>0.0</td><td>0.0</td><td>-</td><td></td><td></td><td></td><td></td><td></td></tr><tr><th>22</th><td><i>O.</i> sp. 6 CFBH36774</td><td>8.8</td><td>7.1</td><td>9.0</td><td>8.8</td><td>10.6</td><td>9.0</td><td>8.8</td><td><b>12.1</b></td><td><b>12.1</b></td><td><b>11.3</b></td><td>7.4</td><td>7.2</td><td>7.1</td><td>8.5</td><td>8.5</td><td>8.2</td><td>8.4</td><td>8.2</td><td>0.6</td><td>0.6</td><td>0.6</td><td>-</td><td></td><td></td><td></td><td></td></tr><tr><th>23</th><td><i>O.</i> sp. 6 CFBH36776</td><td>8.6</td><td>6.9</td><td>8.8</td><td>8.6</td><td>10.6</td><td>8.8</td><td>8.6</td><td><b>12.1</b></td><td><b>12.1</b></td><td><b>11.3</b></td><td>7.2</td><td>7.1</td><td>6.9</td><td>8.3</td><td>8.3</td><td>8.2</td><td>8.4</td><td>8.0</td><td>0.9</td><td>0.9</td><td>0.9</td><td>0.6</td><td>-</td><td></td><td></td><td></td></tr><tr><th>24</th><td>O. sp. 6 CFBH36792</td><td>9.1</td><td>7.4</td><td>9.3</td><td>9.1</td><td>11.2</td><td>9.3</td><td>9.1</td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>11.6</b></td><td>7.6</td><td>7.6</td><td>7.4</td><td>8.7</td><td>8.7</td><td>8.4</td><td>8.5</td><td>8.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.6</td><td>0.9</td><td>-</td><td></td><td></td></tr><tr><th>25</th><td><i>O.</i> sp. 6 MZUESC9812</td><td>9.1</td><td>7.4</td><td>9.3</td><td>9.1</td><td>11.2</td><td>9.3</td><td>9.1</td><td><b>12.5</b></td><td><b>12.5</b></td><td><b>11.6</b></td><td>7.6</td><td>7.6</td><td>7.4</td><td>8.7</td><td>8.7</td><td>8.4</td><td>8.5</td><td>8.5</td><td>0.0</td><td>0.0</td><td>0.0</td><td>0.6</td><td>0.9</td><td>0.0</td><td>-</td><td></td></tr><tr><th>26</th><td><i>O.</i> sp. 6 UFMG4938</td><td>8.9</td><td>7.2</td><td>9.1</td><td>8.9</td><td>10.9</td><td>9.1</td><td>8.9</td><td><b>12.3</b></td><td><b>12.3</b></td><td><b>11.4</b></td><td>7.4</td><td>7.4</td><td>7.2</td><td>8.5</td><td>8.5</td><td>8.2</td><td>8.4</td><td>8.4</td><td>0.2</td><td>0.2</td><td>0.2</td><td>0.7</td><td>1.1</td><td>0.2</td><td>0.2</td><td>-</td></tr></tbody></table>
Replication Package for "A Call for Critically Rethinking and Reforming Data Analysis in Empirical Software Engineer"
<p><strong>Content Overview</strong></p> <p>This replication package contains the following materials:</p> <p>- Data: RAW Focus Group Datasets and Aggregated Results</p> <p>For any issues, questions, or further assistance, please do not hesitate to contact the paper's authors. We are here to help!</p>
Data from: On the advertisement call of Dermatonotus muelleri (Boettger, 1885) (Anura, Microhylidae)
As presently recognized, Dermatonotus muelleri (Boettger, 1885) occurs throughout Argentina, Bolivia, Brazil and Paraguay (Brusquetti & Lavilla 2006); Paraguay referred as the type-locality (Frost 2013). Its advertisement call was briefly described by Nelson (1973) based on a sample from Brazil. In the present work, we redescribe its advertisement call based on a large sample from the Cerrado biome of Triângulo Mineiro region, state of Minas Gerais.
Data from: Meerkat close calling patterns are linked to sex, social category, season and wind, but not fecal glucocorticoid metabolite concentrations
It is well established that animal vocalizations can encode information regarding a sender's identity, sex, age, body size, social rank and group membership. However, the association between physiological parameters, particularly stress hormone levels, and vocal behavior is still not well understood. The cooperatively breeding African meerkats (Suricata suricatta) live in family groups with despotic social hierarchies. During foraging, individuals emit close calls that help maintain group cohesion. These contact calls are acoustically distinctive and variable in rate across individuals, yet, information on which factors influence close calling behavior is missing. The aim of this study was to identify proximate factors that influence variation in call rate and acoustic structure of meerkat close calls. Specifically, we investigated whether close calling behavior is associated with sex, age and rank, or stress hormone output (i.e., measured as fecal glucocorticoid metabolite (fGCM) concentrations) as individual traits of the caller, as well as with environmental conditions (weather) and reproductive seasonality. To disentangle the effects of these factors on vocal behavior, we analyzed sound recordings and assessed fGCM concentrations in 64 wild but habituated meerkats from 9 groups during the reproductive and non-reproductive seasons. Dominant females and one-year old males called at significantly higher rates compared to other social categories during the reproductive season. Additionally, dominant females produced close calls with the lowest mean fundamental frequencies (F0) and the longest mean pulse durations. Windy conditions were associated with significantly higher call rates during the non-reproductive season. FGCM concentrations were unrelated to close calling behavior. Our findings suggest that meerkat close calling behavior conveys information regarding the sex and social category of the caller, but shows no association with fGCM concentrations. The change in call rate in response to variation in the social and ecological environments individuals experience indicates some degree of flexibility in vocal production.
Figure 2 in Climatic dependence in the daily and seasonal calling activity of anurans from coastal wetlands of southernmost Brazil
Figure 2. Rose-diagram of the circular analysis and mean vector length (r), indicated by the arrow vector, of the number of anuran species exhibiting calling activity (a; r = 0.36) and frequency of the calling activity records throughout the day (b; r = 0.46). The arrow vector indicates the concentration of species exhibiting calling activities throughout the months (a) and the recording frequency of these species throughout the hours of the day (b).
Figure 1 in Climatic dependence in the daily and seasonal calling activity of anurans from coastal wetlands of southernmost Brazil
Figure 1. Map of the study area. (a) The North and South America continent. (b) The Rio Grande do Sul state, Brazil. (c) The area of the TAIM Ecological Station.
Figure 3 in Climatic dependence in the daily and seasonal calling activity of anurans from coastal wetlands of southernmost Brazil
Figure 3. (a) Monthly variation of the maximum (continuous line) and minimum (dashed line) water temperature (°C), minimum absolute air relative humidity (dotted line; %), and hours of rainfall from December 2012 to April 2014. (b) Monthly calling activity of the anuran amphibians community in a wetland area from southernmost Brazil from December 2012 to April 2014. The number of species that exhibited calling activities in each month is shown at the top of the graph and the following categories were used: white – no records; dotted area – between 0.1 and 3.99 hours of daily activity; horizontal bar – between 4 and 7.99 hours of daily activity; dark grey – between 8 and 11.99 hours of daily activity; black – between 12 and 17 hours of daily activity; and plus symbol – activity peak indicated by the mean vector (µ) of the circular analysis.
Figure 4 in Climatic dependence in the daily and seasonal calling activity of anurans from coastal wetlands of southernmost Brazil
Figure 4. Calling activity frequency of the species of anuran amphibians found in wetlands from southernmost Brazil, highlighting the seasons with greatest activity: spring 2013 (September– November 2013); summer 2013 (December 2012–February 2013) and summer 2014 (December 2013–February 2014). The number of records per hour is represented by: white – no records; dotted area – 1-7 records; horizontal bar – 8-14 records; dark grey – 15-21 records; black – 22- 36 records; and plus symbol – activity peak indicated by the mean vector (µ) of the circular analysis.
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Allen Brain Atlas
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Annotated Behaviour and Observability Dataset (ABODe)
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