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126 results for “Malaysian Borneo”
Fig. 3 in Diversity and host associations of Myrsidea chewing lice (Phthiraptera: Menoponidae) in the tropical rainforest of Malaysian Borneo
Fig. 3. Myrsidea franciscae sp.n. A, dorso-ventral view of female thorax and abdomen; B, head shape; C, male metasternal plate and sternites I–II; D, male genital sac sclerite.
Fig. 2 in Diversity and host associations of Myrsidea chewing lice (Phthiraptera: Menoponidae) in the tropical rainforest of Malaysian Borneo
Fig. 2. Myrsidea carmenae sp.n. A, dorso-ventral view of female thorax and abdomen; B, head shape; C, male metasternal plate and sternites I–II; D, male genital sac sclerites.
Fig. 5 in Diversity and host associations of Myrsidea chewing lice (Phthiraptera: Menoponidae) in the tropical rainforest of Malaysian Borneo
Fig. 5. Myrsidea victoriae sp.n. A–D, dorso-ventral view of female thorax and abdomen (A), head shape (B), male metasternal plate and sternites I–II (C), male genital sac sclerite (D); Myrsidea macronoi E, male genital sac sclerite.
Fig. 1 in Diversity and host associations of Myrsidea chewing lice (Phthiraptera: Menoponidae) in the tropical rainforest of Malaysian Borneo
Fig. 1. Map of sampling localities (black dots) in the Yayasan Sabah Forest Management Area, Malaysian Borneo.
Fig. 2 in Camera-Trapping Survey Of Mammals In And Around Imbak Canyon Conservation Area In Sabah, Malaysian Borneo
Fig. 2. The observed species accumulation curve (-o-) and 95% CIs (---) for mammalian species in and around Imbak Canyon Conservation Area. The curve was constructed using abundancebased rarefaction approach (i.e., by using the number of independent photographs captured) with 100 randomisation runs in EstimateS (Colwell, 2009).
Fig. 3. Activity patterns for 14 in Camera-Trapping Survey Of Mammals In And Around Imbak Canyon Conservation Area In Sabah, Malaysian Borneo
Fig. 3. Activity patterns for 14 mammal species (with n ≥ 8) photocaptured in and around Imbak Canyon Conservation Area in central Sabah, Malaysian Borneo. Dotted bar indicates percent frequency of independent photographs taken during the day time (0600–1800 hours); Black bar indicates percent frequency of independent photographs taken during night time (1800–0600 hours). Species are listed in order of decreasing frequency of diurnal activity. Numbers in parentheses indicate sample size.
Fig. 1 in Camera-Trapping Survey Of Mammals In And Around Imbak Canyon Conservation Area In Sabah, Malaysian Borneo
Fig. 1. Imbak Canyon Conservation Area (ICCA) in central Sabah, northern part of Malaysian Borneo. Circles show the localities of 13 plots (P1–P13) where camera traps were placed (+). Each plot is approximately 3.5 km in radius.
Fig. 2. A in An assessment of avifauna in a recovering lowland forest at Kinabalu National Park, Malaysian Borneo
Fig. 2. A species accumulation curve (from the 2014 Cornell expedition, lowland species only). This curve demonstrates that we continued to accumulate new species throughout the entire time spent in the field.
Fig. 6 in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 6. Live colours of Arachnothelphusa rhadamanthysi from Gomantong limestone cave in Sabah, specimen not collected. A, male, from outside of the cave; B, inside of cave. Photographs: Keith Christenson.
Fig. 3 in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 3. Arachnothelphusa sarang, new species, holotype male (20.4 × 14.7 mm) (ZRC 2020.0098), limestone cave, Bukit Sarang, Bintulu, Sarawak, Malaysia. A, dorsal view of left G1; B, dorsal view of distal part of left G1; C, ventral view of left G1; D, ventral view of distal part of left G1; E, dorsal view of left G2. Scales = 0.5 mm.
Fig. 1. Arachnothelphusa sarang, new species. A in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 1. Arachnothelphusa sarang, new species. A, male (12.1 × 9.9 mm) (ZRC 2020.0351), Batu Rusa cave, Bukit Sarang, Bintulu, Sarawak, Malaysia; B, female (12.9 × 10.4 mm) (ZRC 2020.0351), Batu Kelelut, Bukit Sarang, Bintulu, Sarawak, Malaysia, specimen; C–E, paratype male (18.7 × 15.3 mm) (ZRC 2020.0099), Bukit Sarang, Bintulu, Sarawak, Malaysia; F, paratype female (15.8 × 11.8 mm) (ZRC 2020.0099), Bukit Sarang, Bintulu, Sarawak, Malaysia. A, B, photographed in situ; C, F, overall dorsal habitus; D, ventral view of cephalothorax; E, frontal view of cephalothorax and chelae. Photographs: Tan Heok Hui.
Fig. 5 in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 5. Gonopod morphology of Arachnothelphusa species. A–E, A. merarapensis Grinang, Pui & Ng, 2015, holotype, male (22.5 × 16.8 mm) (ZRC 2016.0297), Merarap Hot Spring, Lawas, Sarawak; F–J, A. terrapes Ng, 1991, holotype, male (17.6 × 13.3 mm) (ZRC 1992.7918), Danum Valley, Lahad Datu, Sabah; K–N, A. kadamaiana (Borradaile, 1900), male (20.1 × 14.9 mm) (SMF 4282), Kadamian River, Sabah; O–S, A. melanippe (De Man, 1899), lectotype, male (18.9 × 14.4 mm) (RMNH D1303a), Mt. Liang Koebeng, Kalimantan, Borneo. C, F, K, O, ventral view of left G1; D, G, L, P, ventral view of distal part of left G1; A, H, Q, dorsal view of left G1; B, I, M, R, ventral view of distal part of left G1; E, J, N, S, left G2. A–E, K–N after Grinang et al. (2015); F–J, O–S after Ng (1991).
Fig. 4 in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 4. Carapace morphology of Arachnothelphusa species. A, A. sarang, new species, holotype male (20.4 × 14.7 mm) (ZRC 2020.0098), limestone cave, Bukit Sarang, Bintulu, Sarawak; B, A. merarapensis Grinang, Pui & Ng, 2015, holotype male (22.5 × 16.8 mm) (ZRC 2016.0297), Merarap Hot Spring, Lawas, Sarawak; C, A. terrapes Ng, 1991, male (30.8 × 20.5 mm) (ZRC 2017.1205), Danum Valley, Lahad Datu, Sabah; D, A. kadamaiana (Borradaile, 1900), male (20.1 × 14.9 mm) (SMF 4282), Kadamian River, Sabah; E, A. melanippe (De Man, 1899), paratype female (21.4 × 16.7 mm) (RMNH D1303b), Mt. Liang Koebeng, Kalimantan, Indonesia. E after Ng (1991).
Fig. 2. Arachnothelphusa sarang, new species. A–E in A new species of the genus Arachnothelphusa Ng, 1991 (Crustacea: Decapoda: Gecarcinucidae) from a limestone cave in Sarawak (Malaysian Borneo)
Fig. 2. Arachnothelphusa sarang, new species. A–E, holotype male (20.4 × 14.7 mm) (ZRC 2020.0098), Bukit Sarang, Bintulu, Sarawak, Malaysia; F, G, paratype female (19.8 × 15.8 mm) (ZRC 2020.0100), Bukit Sarang, Bintulu, Sarawak, Malaysia. A, F, dorsal view of habitus; B, G, ventral view of carapace showing pleon; C, frontal view of cephalothorax; D, outer view of left chela; E, outer view of right fourth ambulatory leg. Scales: A, B, C, F, G = 10 mm; D, E = 5 mm.
FIG. 4 in Tentaculariids (Cestoda, Trypanorhyncha) of elasmobranchs from Malaysian Borneo
FIG. 4. — Nybelinia aequidentata: A, scolex with lobate velum; B, basal (left illustration) towards metabasal armature of a tentacle cut in two parts, bothrial surface. Scale bars: A, 500 µm; B, 100 µm.
FIG. 1. — Homeokotorella anterioporus n. gen., n in Tentaculariids (Cestoda, Trypanorhyncha) of elasmobranchs from Malaysian Borneo
FIG. 1. — Homeokotorella anterioporus n. gen., n. sp. ex Taeniura lymma 1: A, B, scolex; C, metabasal armature, bothrial surface; D, basal towards metabasal armature, bothrial surface (BH and MH indicate basal and metabasal hooks, respectively); E, F, mature proglottid, in F, open circles are vitelline follicles. Scale bars: A, B, E, F, 125 µm; C, D, 20 µm.
FIG. 2. — Nybelinia pseudafricana n in Tentaculariids (Cestoda, Trypanorhyncha) of elasmobranchs from Malaysian Borneo
FIG. 2. — Nybelinia pseudafricana n. sp. holotype, ex Lamiopsis tephrodes: A, scolex; B, basal towards metabasal armature, bothrial surface; C, metabasal armature, bothrial surface; D, mature proglottid. Scale bars: A, D, 125 µm; B, C, 50 µm.
A labelled dataset of the loud calls of four vertebrates collected using passive acoustic monitoring in Malaysian Borneo
<p><em>Passive acoustic monitoring data collection</em></p> <p>We collected data using first generation Swift autonomous recording units (ARUs) (Koch et al. 2016) with a microphone sensitivity of −44 (+/−3) dB re 1 V/Pa. The microphone frequency response was not measured but is assumed to be flat (+/− 2 dB) in the frequency range 100 Hz to 7.5 kHz. The analog signal was amplified by 40 dB and digitized (16-bit resolution) using an analog-to-digital converter (ADC) with a clipping level of −/+ 0.9 V. We collected acoustic data from one primary conservation area in Sabah, Malaysia: Danum Valley Conservation Area (with 11 recording units from March to July 2018). Danum Valley covers an area of roughly 440 km², and is characterized by lowland dipterocarp forest. Unlike many tropical forest regions, this area is considered 'aseasonal' due to its lack of clearly differentiated wet and dry seasons (Walsh and Newbery 1999). In Danum Valley, the ARUs recorded at a sampling rate of 16 kHz. All recordings were saved in waveform audio (.wav) format, with files of 2-hr duration. We affixed each recording unit to trees approximately 2-m above the ground and recorded continuously over 24 hours. We set the units on a 750 m grid structure, and preliminary field tests indicate that with these recording settings the detection range of gibbon vocalizations is ~ 400 m.</p> <p> </p> <p><em>Acoustic data processing </em></p> <p>We randomly chose approximately 500 h of recordings from Danum Valley Conservation Area to use to create a training dataset. We used a band-limited energy detector (BLED) to identify potential sounds of interest in the gibbon frequency range. For the BLED detector, we convert the 2-hr recordings into a spectrogram using a 1,600-point (100 ms) Hamming window (3 dB bandwidth = 13 Hz) with 0% overlap and a 2,048-point DFT, with the "seewave" package (Sueur et al. 2008). We then filtered the spectrogram to focus on the desired frequency range, specifically 0.5–1.6 kHz for Northern grey gibbons. For each unique time window in the recording, we determined the total energy across frequency bins which gave a single value for every 100 ms interval. Utilizing the "quantile" function in base R, we established the threshold to delineate signal from noise. Preliminary tests with varied quantile values revealed that the 15th quantile led to optimized recall for our target signal. This approach resulted in 1,439 unique sound events. The sound events were then annotated by a single observer (DJC) using a custom-written function in R to visualize the spectrograms into the following categories: great argus pheasant (<em>Argusianus argus</em>) long and short calls (Clink et al. 2021), helmeted hornbills (<em>Rhinoplax vigil</em>), rhinoceros hornbills (<em>Buceros rhinoceros</em>), female gibbons (<em>Hylobates funereus</em>) and a catch-all “noise” category. </p> <p><em>Update Version 5 and later</em></p> <p>Includes labeled test clips from a second conservation area, Maliau Basin Conservation Area, Sabah, Malaysia recorded during August 2019. The ARUs recorded at a sampling rate of 16 kHz. All recordings were saved in waveform audio (.wav) format, with files of 2-hr duration. We affixed each recording unit to trees approximately 2-m above the ground and recorded continuously over 24 hours.</p> <p> </p> <p><strong>References</strong></p> <p>Clink, D. J., Groves, T., Ahmad, A. H., & Klinck, H. (2021). Not by the light of the moon: Investigating circadian rhythms and environmental predictors of calling in Bornean great argus. <em>PloS one</em>, <em>16</em>(2), e0246564.</p> <p>Koch, R., Raymond, M., Wrege, P., & Klinck, H. (2016). SWIFT: A small, low-cost acoustic recorder for terrestrial wildlife monitoring applications. In <em>North American Ornithological Conference</em> (p. 619). Washington, D.C.</p> <p>Sueur, J., Aubin, T., & Simonis, C. (2008). Seewave: a free modular tool for sound analysis and synthesis. <em>Bioacoustics</em>, <em>18</em>, 213–226.</p> <p>Walsh, R. P., & Newbery, D. M. (1999). The ecoclimatology of Danum, Sabah, in the context of the world’s rainforest regions, with particular reference to dry periods and their impact. <em>Philosophical transactions of the Royal Society of London. Series B, Biological sciences</em>, <em>354</em>(1391), 1869–83. https://doi.org/10.1098/rstb.1999.0528</p> <p>Webb, C. O., & Ali, S. (2002). Plants and vegetation of the Maliau Basin Conservation Area, Sabah, East Malaysia. <em>Final Report to Maliau Basin Management Committee</em>.</p> <p> </p>
Above-ground carbon density derived from LiDAR data over oil palm plantations in Malaysian Borneo, 2014
<b>Description: </b><p>The work was carried out in the oil palm plantations within the Stability of Altered Forest Ecosystem (SAFE) Project, located within lowland dipterocarp forest regions of East Sabah in Malaysian Borneo. Airborne LiDAR data were acquired on 5 November 2014 using a Leica LiDAR50-II flown at 1850 m altitude on a Dornier 228-201 travelling at 135 knots. The LiDAR sensor emitted pulses at 83.1 Hz with a field of view of 12.0°, and a footprint of about 40 cm diameter. The average pulse density was 7.3/m2. The Leica LiDAR50-II sensor records full waveform LiDAR, but for the purposes of this study the data were discretised, with up to four returns recorded per pulse. The LiDAR data were pre-processed by NERC's Data Analysis Node and delivered in standard LAS format. All further processing was undertaken using LAStools (Rapidlasso GmbH, LAStools). Points were classified as ground and non-ground, and a digital elevation model (DEM) was fitted to the ground returns, producing a raster of 1 m resolution. The DEM elevations were subtracted from elevations of all non-ground returns to produce a normalised point cloud, and a canopy height model (CHM) was constructed from this on a 0.5 m raster by averaging the first returns. Finally, holes in the raster were filled by averaging neighbouring cells. </p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/25"><b>Influences of disturbance and environmental variation on biomass change in Malaysian Borneo</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant, JKM/MBS.1000-2/2 JLD.3 (128))</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence JKM/MBS.1000-2/2 JLD.3 (128))</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3247699">here</a></p><p><b>Files: </b>This consists of 1 file: LiDAR_Aboveground_Carbon.xlsx</p><p><b>LiDAR_Aboveground_Carbon.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>LiDAR aboveground carbon in Oil palm plantations</b> (described in worksheet LiDAR_ Aboveground_Carbon)</p><p>Description: The output of a LiDAR50-II sensor records full waveform LiDAR, but for the purposes of this study the data were discretised, with up to four returns recorded per pulse. The LiDAR data was pre-processed by NERC's Data Analysis Node and delivered in standard LAS format. All further processing was undertaken using LAStools (Rapidlasso GmbH, LAStools). Points were classified as ground and non-ground, and a digital elevation model (DEM) was fitted to the ground returns, producing a raster of 1 m resolution. The DEM elevations were subtracted from elevations of all non-ground returns to produce a normalised point cloud, and a canopy height model (CHM) was constructed from this on a 0.5 m raster by averaging the first returns. Finally, holes in the raster were filled by averaging neighbouring cells. </p><p>Number of fields: 35</p><p>Number of data rows: 27</p><p>Fields: </p><ul><li><b>Year</b>: Year the oil palm trees were planted (Field type: Numeric)</li><li><b>Plot</b>: Plot number based on the SAFE project framework. Each plot is 25 metres x 25 metres size or 0.0625 hectares (Field type: Location)</li><li><b>meanH</b>: Average tree height per plot (Field type: Numeric)</li><li><b>TreeN_plot</b>: Number of trees per plot (Field type: Numeric)</li><li><b>TreeN_ha</b>: Number of trees per hectare obtained by upscaling the number of trees within each 25m x 25m (0.0625 ha) plot to 1 ha (Field type: Numeric)</li><li><b>ACD_plot</b>: Sum of the aboveground carbon density per plot (Field type: Numeric)</li><li><b>ACD_ha</b>: Sum of the aboveground carbon density per hectare obtained by upscaling the number of aboveground carbon density within each 25m x 25m (0.0625 ha) plot to 1 ha (Field type: Numeric)</li><li><b>CC1</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 1 metre height (Field type: Numeric)</li><li><b>CC2</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 2 metres height (Field type: Numeric)</li><li><b>CC3</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 3 metres height (Field type: Numeric)</li><li><b>CC4</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 4 metres height (Field type: Numeric)</li><li><b>CC5</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 5 metres height (Field type: Numeric)</li><li><b>CC6</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 6 metres height (Field type: Numeric)</li><li><b>CC7</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 7 metres height (Field type: Numeric)</li><li><b>CC8</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 8 metres height (Field type: Numeric)</li><li><b>CC9</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 9 metres height (Field type: Numeric)</li><li><b>CC10</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 10 metres height (Field type: Numeric)</li><li><b>CC11</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 11 metres height (Field type: Numeric)</li><li><b>CC12</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 12 metres height (Field type: Numeric)</li><li><b>CC13</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 13 metres height (Field type: Numeric)</li><li><b>CC14</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 14 metres height (Field type: Numeric)</li><li><b>CC15</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 15 metres height (Field type: Numeric)</li><li><b>CC16</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 16 metres height (Field type: Numeric)</li><li><b>CC17</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 17 metres height (Field type: Numeric)</li><li><b>CC18</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 18 metres height (Field type: Numeric)</li><li><b>CC19</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 19 metres height (Field type: Numeric)</li><li><b>CC20</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 20 metres height (Field type: Numeric)</li><li><b>CC21</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 21 metres height (Field type: Numeric)</li><li><b>CC22</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 22 metres height (Field type: Numeric)</li><li><b>CC23</b>: Average canopy cover per hectare: the proportion of area occupied by crowns at 23 metres height (Field type: Numeric)</li><li><b>TCH</b>: Top of canopy height: mean height of Canopy Height Model (CHM) pixels per hectare. (Field type: Numeric)</li><li><b>TreeN_itc</b>: Number of segmented trees per hectare obtained by using the itcSegment function implemented in R (Field type: Numeric)</li><li><b>meanH_itc</b>: Average tree height per hectare obtained by using the itcSegment function inmplement in R (Field type: Numeric)</li><li><b>meanHc_itc</b>: Corrected average tree height per hectare obtained by using the itcSegment function inmplement in R (Field type: Numeric)</li><li><b>ACDc_itc</b>: Sum of the aboveground carbon density per hectare obtained by using the itcSegment function inmplement in R (Field type: Numeric)</li></ul></li></ol><p><b>Date range: </b>2014-11-05 to 2014-11-05</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p>
Invertebrate activity data from an experiment in Malaysian Borneo, 2014-16 [HMTF]
<b>Description: </b><p>This resource comprises a time series dataset of ant and other invertebrate abundance measured fortnightly at bait monitoring cards on an experimental plot in the Maliau Basin Conservation Area, Malaysian Borneo. The resource includes data regarding the amount of food resource removed from experimental plots when either ants or vertebrates were excluded from the resource. The data were collected to assess the roles that the different groups (ants, invertebrates, vertebrates) play in ecosystem function, and the capacity for functional redundancy within and between these groups. Data were collected between 2014 and 2016 during a project run by the University of Liverpool, which was part of the NERC Human-modified tropical forest (HMTF) Programme.</p><p><b>Project: </b>This dataset was collected as part of the following SAFE research project: <a href="https://www.safeproject.net/projects/project_view/54"><b>Biodiversity and land-use impacts on tropical ecosystem function (BALI): Experimental manipulations of biodiversity at SAFE</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>UK NERC-funded Biodiversity And Land-use Impacts on Tropical Ecosystem Function (BALI) consortium (Standard grant, NERC grant NE/L000016/1)</li></ul><p>This dataset is released under the CC-BY 4.0 licence, requiring that you cite the dataset in any outputs, but has the additional condition that you acknowledge the contribution of these funders in any outputs.</p><p></p><p><b>Permits: </b>These data were collected under permit from the following authorities:</p><ul><li>Sabah Biodiversity Centre (Research licence na)</li></ul><p></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3265748">here</a></p><p><b>Files: </b>This consists of 1 file: Ant_Monitoring.xlsx</p><p><b>Ant_Monitoring.xlsx</b></p><p>This file contains dataset metadata and 3 data tables:</p><ol><li><p><b>Ant monitoring data</b> (described in worksheet Ant_Monitoring_Data)</p><p>Description: ant count taken on bait cards at an experimental plot</p><p>Number of fields: 4</p><p>Number of data rows: 18296</p><p>Fields: </p><ul><li><b>Date</b>: Date cards were collected? (Field type: Date)</li><li><b>Plot</b>: Plot in the Maliau basin (Field type: Location)</li><li><b>Treatment</b>: Refers to ant or termite exclusion, or control (Field type: Categorical)</li><li><b>Score</b>: Number of ants (Field type: Numeric trait)</li></ul></li><li><p><b>Non ant invertebrate data </b> (described in worksheet Non_Ant_Invertebrate_Data)</p><p>Description: non ant count taken on bait monitoring cards</p><p>Number of fields: 12</p><p>Number of data rows: 463</p><p>Fields: </p><ul><li><b>Date</b>: Date cards were collected? (Field type: Date)</li><li><b>Plot</b>: Plot in the Maliau basin (Field type: location)</li><li><b>Treatment</b>: Refers to ant or termite exclusion, or control (Field type: categorical)</li><li><b>Wasp</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Cricket</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Fly</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Springtail</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Beetle</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Cockroach</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Spider</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Harvestman</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric trait)</li><li><b>Sum</b>: The score used to estimate the numbers of inverts observed on the bait cards (Field type: Numeric)</li></ul></li><li><p><b>Percentage of bait removed </b> (described in worksheet Percentage_Bait_Removed_Data)</p><p>Description: percentage of bait removed</p><p>Number of fields: 10</p><p>Number of data rows: 377</p><p>Fields: </p><ul><li><b>Date_put_out</b>: Date the bait was placed (Field type: Date)</li><li><b>Date_collected</b>: Date the bait was collected (Field type: Date)</li><li><b>rep</b>: Replicate (Field type: Replicate)</li><li><b>plot</b>: Plot used in the Maliau basin (Field type: Location)</li><li><b>plot_treat</b>: Plot treatment (Field type: Categorical)</li><li><b>bait</b>: Bait used (Field type: Categorical)</li><li><b>cage_treat</b>: Cage structure (Field type: Categorical)</li><li><b>start_weight</b>: Weight of the bait before being placed in the field (Field type: Numeric)</li><li><b>end_weight</b>: Weight of the bait after being placed in the field (Field type: Numeric)</li><li><b>perc_gone</b>: Percentage of the bait consumed (Field type: Numeric)</li></ul></li></ol><p><b>Date range: </b>2014-12-04 to 2017-03-15</p><p><b>Latitudinal extent: </b>4.5000 to 5.0700</p><p><b>Longitudinal extent: </b>116.7500 to 117.8200</p><p><b>Taxonomic coverage: </b><br> All taxon names are validated against the GBIF backbone taxonomy. If a dataset uses a synonym, the accepted usage is shown followed by the dataset usage in brackets. Taxa that cannot be validated, including new species and other unknown taxa, morphospecies, functional groups and taxonomic levels not used in the GBIF backbone are shown in square brackets.</p><div>Animalia<br> - Arthropoda<br> -  - Arachnida<br> -  -  - Araneae<br> -  -  - Opiliones<br> -  - Entognatha<br> -  -  - Collembola<br> -  - Insecta<br> -  -  - Blattodea<br> -  -  - Coleoptera<br> -  -  - Diptera<br> -  -  - Hymenoptera<br> -  -  - Orthoptera<br></div><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.