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4,059 results for “mammal”
Life history consequences of climate change in hibernating mammals: A review
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Both selection and drift drive the spatial pattern of adaptive genetic variation in a wild mammal
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Dung counts large mammals Volcanoes NP, Rwanda, 2008 and 2021
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Digital biodiversity datasets reveal breeding phenology and its drivers in a widespread North American mammal
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Age and location influence the costs of compensatory and accelerated growth in a hibernating mammal
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Advances in thermal physiology of diving marine mammals: The dual role of peripheral perfusion
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At-sea seabird censuses. Data on the species encountered (including marine mammals), their abundance, distribution and behavior. Data collected aboard cruises off the coast of the Western Antarctic Penninsula, 1993 - 2018.
The objectives of the LTER seabird component during the 92-93 season cruises were similar. These objectives included 1) determining the pelagic abundance and distribution of Adelie Penguins, 2) examining how the physical and biological characteristics of the marine environment influence these parameters and, 3) using these data to identify foraging areas that may be important to Adelie populations being studied as part of land-based work at Palmer Station. Secondary objectives included documenting the abundance and distribution of other seabirds and marine mammals within the LTER study area. The focus of the January cruise was the nearshore foraging habitat,which required sampling at smaller scales. All seabird censuses were thus conducted within approximately 100 kms of Palmer Station while traversing a sampling grid with stations at 10km intervals. The first two days (18-20 January) of this cruise were spent covering the selected grid as rapidly as possible resulting in 45 transects spaced at 45-60 minute intervals. There were no stops at the 10km stations during this Fast Grid phase. Upon completion of the Fast Grid, a force 12 gale suspended data collection for 24 hours. From January 22-25 the grid direction was reversed and the grid repeated. During this Slow Grid phase, 2-M net tows were done at 10km intervals and BOPS and 1-M and 2-M net tows every 20 km. All seabird censuses during the cruise were done using the procedures outlined in the previous paragraph.
At-sea seabird censuses. Data on the species encountered (including marine mammals), their abundance, distribution and behavior. Data collected aboard cruises off the coast of the Western Antarctic Penninsula, 1993, 1999 and 2001.
The objectives of the LTER seabird component during the 92-93 season cruises were similar. These objectives included 1) determining the pelagic abundance and distribution of Adelie Penguins, 2) examining how the physical and biological characteristics of the marine environment influence these parameters and, 3) using these data to identify foraging areas that may be important to Adelie populations being studied as part of land-based work at Palmer Station. Secondary objectives included documenting the abundance and distribution of other seabirds and marine mammals within the LTER study area. The focus of the January cruise was the nearshore foraging habitat,which required sampling at smaller scales. All seabird censuses were thus conducted within approximately 100 kms of Palmer Station while traversing a sampling grid with stations at 10km intervals. The first two days (18-20 January) of this cruise were spent covering the selected grid as rapidly as possible resulting in 45 transects spaced at 45-60 minute intervals. There were no stops at the 10km stations during this Fast Grid phase. Upon completion of the Fast Grid, a force 12 gale suspended data collection for 24 hours. From January 22-25 the grid direction was reversed and the grid repeated. During this Slow Grid phase, 2-M net tows were done at 10km intervals and BOPS and 1-M and 2-M net tows every 20 km. All seabird censusesduring the cruise were done using the procedures outlined in theprevious paragraph.
At-sea seabird censuses. Data on the species encountered (including marine mammals), their abundance, distribution and behavior. Data collected aboard cruises off the coast of the Western Antarctic Penninsula, 1993 - 2018.
The objectives of the LTER seabird component during the 92-93 season cruises were similar. These objectives included 1) determining the pelagic abundance and distribution of Adelie Penguins, 2) examining how the physical and biological characteristics of the marine environment influence these parameters and, 3) using these data to identify foraging areas that may be important to Adelie populations being studied as part of land-based work at Palmer Station. Secondary objectives included documenting the abundance and distribution of other seabirds and marine mammals within the LTER study area. The focus of the January cruise was the nearshore foraging habitat, which required sampling at smaller scales. All seabird censuses were thus conducted within approximately 100 kms of Palmer Station while traversing a sampling grid with stations at 10km intervals. The first two days (18-20 January) of this cruise were spent covering the selected grid as rapidly as possible resulting in 45 transects spaced at 45-60 minute intervals. There were no stops at the 10km stations during this Fast Grid phase. Upon completion of the Fast Grid, a force 12 gale suspended data collection for 24 hours. From January 22-25 the grid direction was reversed and the grid repeated. During this Slow Grid phase, 2-M net tows were done at 10km intervals and BOPS and 1-M and 2-M net tows every 20 km. All seabird censuses during the cruise were done using the procedures outlined in the previous paragraph. Seventy-two 30-minute transects and 15 station censuses were completed during the January cruise. Athough seabirds were widely distributed throughout the study area, the highest densities and greatest biomass occurred consistently within 2-5 km of Anvers Island and several major island groups to the south and west near the Antarctic Peninsula. Adelie Penguins were the dominant component of this seabird assemblage in terms of both abundance and biomass. South Polar Skuas ranked second and Black-browed Al
At-sea seabird censuses. Data on the species encountered (including marine mammals), their abundance, distribution and behavior. Data collected aboard cruises off the coast of the Western Antarctic Penninsula, 1993, 1999 and 2001.
The objectives of the LTER seabird component during the 92-93 season cruises were similar. These objectives included 1) determining the pelagic abundance and distribution of Adelie Penguins, 2) examining how the physical and biological characteristics of the marine environment influence these parameters and, 3) using these data to identify foraging areas that may be important to Adelie populations being studied as part of land-based work at Palmer Station. Secondary objectives included documenting the abundance and distribution of other seabirds and marine mammals within the LTER study area. The focus of the January cruise was the nearshore foraging habitat,which required sampling at smaller scales. All seabird censuses were thus conducted within approximately 100 kms of Palmer Station while traversing a sampling grid with stations at 10km intervals. The first two days (18-20 January) of this cruise were spent covering the selected grid as rapidly as possible resulting in 45 transects spaced at 45-60 minute intervals. There were no stops at the 10km stations during this Fast Grid phase. Upon completion of the Fast Grid, a force 12 gale suspended data collection for 24 hours. From January 22-25 the grid direction was reversed and the grid repeated. During this Slow Grid phase, 2-M net tows were done at 10km intervals and BOPS and 1-M and 2-M net tows every 20 km. All seabird censusesduring the cruise were done using the procedures outlined in theprevious paragraph.
Mammal Species Commonly Present at Barro Colorado Island
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at Barro Colorado Island, Panama, was retrieved from http://biogeodb.stri.si.edu/biodiversity/bci/ on 10/30/2013 as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Mammal Species Commonly Present at Coweeta LTER
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at Coweeta LTER, North Carolina, was retrieved from http://coweeta.uga.edu/species/speciesII.php on 10/30/2013 as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Mammal Species Commonly Present at Harvard Forest LTER
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at Harvard Forest LTER, Massachusetts, were compiled by Jeanine McGann, Information Resource Manager, on 10/30/2013 as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Mammal Species Commonly Present at HJ Andrews LTER
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at HJ Andrews LTER, Oregon, was retrieved from http://andrewsforest.oregonstate.edu/lter/about/site/species/list.cfm?sa... on October 29, 2013, as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Mammal Species Commonly Present at Luquillo LTER
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at Luquillo LTER, Puerto Rico, was derived from the text of "The Food Web of a Tropical Rain Forest," edited by Douglas P. Reagan and Robert B. Waide, University of Chicago Press, Chicago, (c) 1996, Chapter 12, "Mammals," by Michael R. Willig and Michael R. Gannon, pp. 399-431, as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Mammal Species Commonly Present at Niwot Ridge LTER
Patterns of biodiversity, such as the increase toward the tropics and the peaked curve during ecological succession, are fundamental phenomena for ecology. Such patterns have multiple, interacting causes, but temperature emerges as a dominant factor across organisms from microbes to trees and mammals, and across terrestrial, marine, and freshwater environments. However, there is little consensus on the underlying mechanisms, even as global temperatures increase and the need to predict their effects becomes more pressing. The purpose of this project is to generate and test theory for how temperature impacts biodiversity through its effect on biochemical processes and metabolic rate. A combination of standardized surveys in the field and controlled experiments in the field and laboratory measure diversity of three taxa -- trees, invertebrates, and microbes -- and key biogeochemical processes of decomposition in seven forests distributed along a geographic gradient of increasing temperature from cold temperate to warm tropical. This list of mammal species at Niwot Ridge LTER, Colorado, was retrieved from: http://culter.colorado.edu/NWT/site_info/flora_and_fauna.html (10/30/2013) and http://www.colorado.edu/mrs/mammal (3/25/2014), as part of a macrosystems biodiversity and latitude project supported by the National Science Foundation under Cooperative Agreement DEB#1065836.
Geographical Distribution of Mammal Images (Flickr-Mammal dataset)
<p>This dataset is created based on the geographical distribution of common mammal images on Flickr.</p> <p>In this dataset, we provide the metadata of all images in this dataset, including their geotags, license status, URL to the images, and their corresponding countries and geographical regions (based on <a href="https://unstats.un.org/unsd/methodology/m49/">UN M49 Standard</a>).</p> <p>We also provide easy-to-use scripts for the user to download the images from their URLs.</p> <p>If you use this dataset in your research, we would appreciate a reference to the following paper:</p> <p>Kevin Hsieh, Amar Phanishayee, Onur Mutlu, and Phillip B Gibbons. "<a href="https://proceedings.icml.cc/static/paper_files/icml/2020/3152-Paper.pdf">The Non-IID Data Quagmire of Decentralized Machine Learning</a>." <em>Proceedings of the 37th International Conference on Machine Learning (ICML 2020)</em>.</p> <p>Bibtex entry</p> <pre><code>@incollection{icml2020_3152, author = {Hsieh, Kevin and Phanishayee, Amar and Mutlu, Onur and Gibbons, Phillip}, booktitle = {International Conference on Machine Learning ({ICML})}, pages = {5819--5830}, title = {The Non-{IID} Data Quagmire of Decentralized Machine Learning}, year = {2020} }</code></pre> <p> </p>
Fig. 2 in Skeleton of a Cretaceous mammal from Madagascar reflects long-term insularity
Fig. 2 | Cranium, lower jaw and dentition of A. hui holotype (UA 9030).
Importance of riparian reserves and other forest fragments for small mammal diversity in disturbed and converted forest landscapes
<b>Description: </b><p>The primary objective of this study was to document the species richness, community composition of the small mammals in riparian remnants within oil palm plantation and in degraded forests. The purpose is to assess the value of retaining riparian remnants within oil palm plantation and logged forest habitats for small mammals conservation. <br>Main questions <br>1. Is there a difference in species richness and community composition of small mammals in riparian remnants within oil palm and logged forests? <br>2. What effects do maintaining riparian remnants in oil palm and logged forests have on small mammal diversity? <br>3. Does the structure and width of riparian remnants in oil palm and logged forests affect small mammal species diversity? <br>4. How does the structure of riparian reserves could be managed to improve the extent to which they retain small mammals communities in oil palm and logged forests?<br>Methods<br>Sampling will be conducted at several sites representing four habitat treatments: (1) riparian reserves in old growth forests as control treatment (at Maliau Basin Conservation Area); (2) riparian reserves of different widths in logged forests (SAFE project area); (3) riparian remnants of different widths in oil palm (south of SAFE project area); and (4) oil palm without any riparian remnants (south of SAFE project area). In addition, sampling was conducted in other forest remnants within oil palm habitats. Each habitat treatment will be represented by three sites serving as replicates. <br>Used a grid trapping of 4 x 12 grid points (23m spacing) for sampling the small mammals. We shall establish one grid at each site with 48 trap stations. Two wire-mesh cage traps (28 x 15 x 12.5 cm), baited with oil palm fruits, will be placed at each station. Trapping of small mammals and searchers for amphibians will be conducted in four sampling sessions. In each session we will visit randomly four sites representing the four habitat treatments. Each sampling session at each site will last for four months. Overall, each habitat treatment will be sampled three times over a 12 months period. The following variables will be collected for each sampling site to characterize the habitat structure: canopy cover, number of large and small logs, number of large and small trees, percentage leaf litter cover and other variables that may influence the distribution and abundance of small mammals.</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/3"><b>Importance of riparian reserves and other forest fragments for mammal and amphibian diversity in disturbed and converted forest landscapes</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>Universiti Malaysia Sabah (Grant)</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 council (Research licence Local)</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=3908128">here</a></p><p><b>Files: </b>This consists of 1 file: UMS_Small_mammal_data.xlsx</p><p><b>UMS_Small_mammal_data.xlsx</b></p><p>This file contains dataset metadata and 1 data tables:</p><ol><li><p><b>Data</b> (described in worksheet Data)</p><p>Description: small mammal presence and absense</p><p>Number of fields: 29</p><p>Number of data rows: 140</p><p>Fields: </p><ul><li><b>landuse</b>: Habitat type (Field type: categorical)</li><li><b>site</b>: Location of sampling (Field type: location)</li><li><b>plot</b>: Plot name (Field type: categorical)</li><li><b>day</b>: Day of sampling (Field type: categorical)</li><li><b>Callosciurus notatus</b>: Number of species caught (Field type: abundance)</li><li><b>Echinosorex gymnurus</b>: Number of species caught (Field type: abundance)</li><li><b>Haeromys margarettae</b>: Number of species caught (Field type: abundance)</li><li><b>Lariscus hosei</b>: Number of species caught (Field type: abundance)</li><li><b>Leopoldamys sabanus</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys alticola</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys baeodon</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys ochraceiventer</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys rajah</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys surifer</b>: Number of species caught (Field type: abundance)</li><li><b>Maxomys whiteheadi</b>: Number of species caught (Field type: abundance)</li><li><b>Niniventer cremoriventer</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus exulans</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus rattus</b>: Number of species caught (Field type: abundance)</li><li><b>Rattus tiomanicus</b>: Number of species caught (Field type: abundance)</li><li><b>Sundamys muelleri</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus hippurus</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus lowii</b>: Number of species caught (Field type: abundance)</li><li><b>Sundasciurus tenuis</b>: Number of species caught (Field type: abundance)</li><li><b>Trichys fasciculata</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia glis</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia gracilis</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia minor</b>: Number of species caught (Field type: abundance)</li><li><b>Tupaia tana</b>: Number of species caught (Field type: abundance)</li><li><b>Grand Total</b>: Total (Field type: numeric)</li></ul></li></ol><p><b>Date range: </b>2015-03-01 to 2019-04-30</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> -  -  Chordata <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Trichys</i> <br> -  -  -  -  -  -  -  <i>Trichys fasciculata</i> <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys alticola</i> <br> -  -  -  -  -  -  -  <i>Maxomys baeodon</i> <br> -  -  -  -  -  -  -  <i>Maxomys ochraceiventer</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  -  <i>Rattus rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus tiomanicus</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Haeromys</i> <br> -  -  -  -  -  -  -  <i>Haeromys margarettae</i> <br> -  -  -  -  -  -  <i>Niviventer</i> <br> -  -  -  -  -  -  -  <i>Niviventer cremoriventer</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia glis</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br></div><p></p>
Core SAFE project small mammal trapping data
<b>Description: </b><p>This is the combined dataset for the SAFE project's core small mammal trapping programme, which was run from 2011-2014 by O.R. Wearn, from 2015-2017 by P. M. Chapman, and from 2018-2019 by S. Heon. In total, trapping grids have been run at 30 sites across the SAFE landscape and control areas, covering blocks D, E, F, OG1, OG2, OG3 and OP2. However, since 2014 trapping has been limited to 12 standard permanent grids which are resampled annually: two in D (the 100ha fragment site), six in E (two each in the 1, 10 and 100ha sites), two in OG2 at the Maliau Basin Conservation area and two in OP2 at the Selangan Batu Oil Palm estate. In 2018, 2 new mammal grids were added : Dmatrix-1 and Ematrix-1 grid. The following grids were dropped E1-1, E10-1, E100-1 and D100-1, while D1-2 and D10-2 were sampled. In 2019, OG2-N, trap lines 1-8 were not accessible due to a massive landslide. In replacement, lines 47-56 were added to the trap grid for OG2-N. trapping grids Dmatrix-2 and Ematrix-2 were also added. All the new grids are reflected on the locations sheet. One standard annual sampling session comprises 96 traps run for seven nights, and the first sheet in the dataset ("Deployment") records this as 672 rows detailing the basic outcome of each trap night in the sampling session. There are several grids which form exceptions to this trapping pattern; details of these are recorded in the metadata. The subsequent two sheets (Corrected_Trapping_Data and Raw_Trapping_Data) form a more detailed record of captured animals. These sheets have the non-capture rows removed, along with most of the basic trap location and state data; however they can easily be linked back to the relevant rows in "Deployment" by the date and the unique trap identifier. At first capture, all possible details of captured animals are recorded, including age, sex, biometric measurements, crude estimates of parasite load, and the ID of any associated samples. All animals captured in good health were fitted with a Passive Integrated Transponder (PIT) Tag so the unique 10-digit alphanumeric number associated with each PIT tag is also recorded. Upon recapture, the animals are merely weighed and the PIT tag number and trap location recorded; this is partly to save time and partly to avoid unneccessary repeat anaesthesia. In 2018, Prevost's squirrel with the species code PVSQ was added into the species list. <br>The entire dataset from 2011-2017 was extensively error-checked by PMC in 2018, then from 2018-2019 by SH with many errors identified, recorded, and where possible, rectified. These errors are most frequently duplications or typos in the PIT tag string. Where these errors are unresolvable, the true unique ID of the individual is no longer certain, and its independence from other individuals cannot be guaranteed. These records will require omitting from most analyses. The detailed dataset with capture data is therefore presented in both its raw and corrected forms. ("Raw_Trapping_Data" and "Corrected_Trapping_Data", respectively). In the corrected datasheet, all the resolvable errors have been corrected, with a brief note made of what was done and why. Notes have also been added to irresolvable errors briefly explaining the problem, and recommending omission from analyses where appropriate. We strongly recommend that all users rely on the corrected version; however we also include the raw data for completeness. In 2018, an additional sheet - general site information details was added</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/140"><b>The impacts of tropical forest fragmentation on dispersal behaviour of mammal communities</b></a></p><p><b>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3955050">here</a></p><p><b>Files: </b>This consists of 1 file: SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</p><p><b>SAFE_Core_Small_Mammal_Data_V3_2019_ROB_SUI.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>Basic trap outcome data</b> (described in worksheet Deployment)</p><p>Description: This is the basic trapping data covering the outcome of every trap night since the start of the study in 2011. It comprises merely the location and date information for the trap, the person who was responsible for baiting it, the state of the trap and bait on checking, any invertebrates captured, the number of small mammal captures (generally 0 or 1, but occasionally 2) and any notes pertaining to the trap itself.</p><p>Number of fields: 15</p><p>Number of data rows: 71123</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps etween days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Block</b>: The SAFE sampling block (Field type: categorical)</li><li><b>Fragment</b>: The fragment (SAFE landscape; 1, 10, or 100ha) or sub-block (control sites; e.g. OP2, OG1, etc) of the sampling session. (Field type: id)</li><li><b>Grid</b>: The grid of the sampling session. There are two grids (1 and 2, numered outwards from the centre of the lock) in each fragment in the SAFE design, and three in each su-block in the control sites (North, East and West). (Field type: id)</li><li><b>Point</b>: The camera trap/small mammal sampling point where the trap was located. (Field type: id)</li><li><b>Trap</b>: The trap identifier (two traps, A and B, are located within a 5m radius of each sampling point) (Field type: id)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>State</b>: The state of the trap when checked. (Field type: categorical)</li><li><b>Bait</b>: The state of the bait when checked. (Field type: categorical)</li><li><b>Invertebrates</b>: Comments on any invertebrates found; in particular the presence of ants is frequently recorded, as these can be a severe danger to small mammals. (Field type: comments)</li><li><b>Capture_N</b>: Number of small mammals caught. This is almost invarialy zero or one, however very occasionally two are caught together. Models such as Spatially Explicit Capture Recapture treat small mammal traps as "single-catch" traps, and the model is violated y these occasions - so they are worth flagging up. (Field type: numeric)</li><li><b>Who_baited</b>: Person who baited the trap (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. On the "Deployment" sheet this column has Been trimmed to only include notes covering the placement and condition of the traps - with notes pertaining to captured animals removed. (Field type: comments)</li></ul></li><li><p><b>Corrected trapping data</b> (described in worksheet Corrected_Trapping_Data)</p><p>Description: This is the modified, corrected version of the detailed trapping data covering all the small mammal captures from 2011 (i.e. blank rows are removed). It is directly based on the raw trapping data, however it has been fully verified, with all rectifiable errors corrected. Extra columns are included to: 1.) display any corrections to species ID and PIT tag ID of an individual record, 2.) explain the reason for corrections applied, or any unresolvable errors, and 3.) recommend a record for omission from analyses, where appropriate.</p><p>Number of fields: 36</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique_Trap_ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional caputures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species_Validated</b>: Corrected, verified species ID for the captured animal. This should be used in preference to "Species" as any misidentifications have been amended. Codes follow those in the "Raw Taxon" column (Field type: taxa)</li><li><b>Species_Uncertainty</b>: Indicates uncertainty around the species identification (after correction). Species IDs are not alwaysCERtain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw verson. (Field type: id)</li><li><b>PIT_Tag/ID_Validated</b>: Corrected, validated individual ID for the captured small mammal. This should be used in preference to "PIT_Tag/ID" as resolvable errors have been amended. In some occasional cases this ID does not correspond to the (corrected) PIT tag string. In these cases a standardised generic ID was applied, generally under two possible conditions: 1.) The individual was released alive without tagging but there is effectively no chance of recapture (such as an animal on the last day of trapping in an isolated block which was not trapped subsequently). 2.) The animal was a new, untagged individual found dead in the trap. Case 1: individuals recieve an identifier comprised of the species code and a unique three-digit number e.g. "WH001". Case 2: Individuals recieve a unique two-digit number preceded by "NewDead". (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing_Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T_%_of_HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag_W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross_W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net_W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite_Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body_Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue_Sample_ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite_Sample_ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur_sample_ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal_Sample_1_ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal_Sample_2_ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Omit</b>: Identifies individuals which should be omitted from all analyses ("Y") or some analyses ("SA") due to data errors (Field type: categorical)</li><li><b>Correction_Notes</b>: Comments on any corrections made or reasoning for suggesting omissions in "Omit". Omissions are usually due to the individual ID or species ID of a capture being uncertain. Several common omission reasons are recorded with standard prhases in capitals for clarity: these include escapes, animals released untagged for various reasons (including non-target captures), and dead individuals where species identification was impossible or where it was uncertain if the individual was new or a recapture. More complex cases are discussed individually. (Field type: comments)</li><li><b>Other_Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Raw trapping data</b> (described in worksheet Raw_Trapping_Data)</p><p>Description: This is the unmodified, raw version of the detailed trapping data, covering all the small mammal sampling from 2011 (i.e. blank rows are removed). It is included for information only and we do not recommend that it is used.</p><p>Number of fields: 32</p><p>Number of data rows: 8101</p><p>Fields: </p><ul><li><b>Grid-Session-Occasion</b>: An identifier for the individual trapping day ("occasion") within a sampling year ("session"). This nomenclature originates from applying Spatially Explicit Capture-Recapture models to this data, however experience suggests this is the most concise, intuitive way of referring to a particular day of trapping (rather than using the actual date). This is applied to all grids which were trapped in the standard pattern of 96 traps run for seven consecutive days. There are five exceptions: OG2-E in 2011, D100-2 in 2011, D100-1 in 2012, F100-1 in 2012, and F100-2 in 2012. These were all trapped in a non-standard pattern (either total trapping effort ≠ 96 traps and 7 days, or there were gaps between days such that the total trapped duration > 7 days). These exceptions are given NA (Field type: id)</li><li><b>Date</b>: The calendar date of trapping (Field type: date)</li><li><b>Unique_Point_ID</b>: Unique identifier for the sampling point (corresponds to the Locations sheet, and the locations in the Gazeteer) (Field type: location)</li><li><b>Unique Trap ID</b>: Unique identifier for the individual trap. (Field type: id)</li><li><b>Species</b>: Raw species ID for the captured animal. All "target" small mammals receive an identifying code for brevity (see the Taxa sheet) while occasional captures of "non-target" taxa (larger mammals, other vertebrates) are referred to in full. Fully unknown small mammal species are referred to as "Unknown". (Field type: taxa)</li><li><b>Species Uncertainty</b>: Indicates uncertainty around the species identification. Species IDs are not always certain, especially in the case of aberrant individuals, cryptic species or complexes such as Rattus, or heavily scavenged dead indivuduals. (Field type: categorical)</li><li><b>New/Recapture</b>: Indicates whether the individual is a new record or a recapture. NB: Biometric data (apart from weight) is not collected for recaptures for reasons of time and ethics (unnecessary anaesthesia). (Field type: categorical)</li><li><b>PIT_Tag/ID</b>: Raw individual ID for the captured animal. This is usually a 10-digit numeric or alphanumeric string, the number of the fitted Passive Integrated Transponder (PIT) tag. All zeros in PIT strings are replaced with capital Os due to persistent problems with Excel irreversibly modifying particular string formats (these errors are included in this raw data). Various other "generic" individual IDs have been applied to occasional animals which were untagged but somehow deemed to be otherwise identifiable. The format and use of these varies between fieldworkers and has not been standardised here in this raw dataset. (Field type: id)</li><li><b>Age</b>: Age of the individual captured. Uncertain ages are given with question marks. Completely unknown or unrecorded age are given as NA. (Field type: categorical trait)</li><li><b>Sex</b>: Sex of the individual captured. Uncertain sexes are given with question marks. Completely unknown or unrecorded sexes are given as NA. (Field type: categorical trait)</li><li><b>Sexing Notes</b>: Notes on criteria used for sexing. (Field type: comments)</li><li><b>HF</b>: (Left) Hind foot measurement (Field type: numeric trait)</li><li><b>E</b>: (Left) Ear length measurement (only rats) (Field type: numeric trait)</li><li><b>AGD</b>: Ano-genital distance measurement (only rats) (Field type: numeric trait)</li><li><b>HB</b>: Head-body length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T</b>: Tail length measurement (only treeshrews, squirrels and some rat species where ID is uncertain) (Field type: numeric trait)</li><li><b>T % of HB</b>: Tail length as a percentage of body head-body length (Field type: numeric trait)</li><li><b>MZ</b>: Muzzle length measurement (only treeshrews) (Field type: numeric trait)</li><li><b>Bag W</b>: Mass of the polythene weighing bag (Field type: numeric)</li><li><b>Gross W</b>: Mass of the polythene weighing bag including animal (Field type: numeric)</li><li><b>Net W</b>: Mass of the animal (Field type: numeric)</li><li><b>Parasite Count</b>: Approximate ectoparasite load: rough visual count of the number of fur mites and other ectoparasites shed within the anaesthesia pot during anaesthesia (Field type: numeric trait)</li><li><b>Body Fat</b>: Body fat score: a nine-level categorical score. Only applied from 2017 onwards. (Field type: categorical trait)</li><li><b>Injuries</b>: Description of any injuries or visible signs of diease to the captured small mammal. (Field type: comments)</li><li><b>Dead</b>: Was the individual found dead, or euthanised in the course of processing? (Field type: categorical trait)</li><li><b>Tissue Sample ID</b>: Identifier for any tissue samples taken (rats only, from the right ear) (Field type: id)</li><li><b>Parasite Sample ID</b>: Identifier for any parasite samples taken (Field type: id)</li><li><b>Fur sample ID</b>: Identifier for any fur samples taken (Field type: id)</li><li><b>Faecal Sample 1 ID</b>: Identifier for any faecal samples taken (for first investigator) (Field type: id)</li><li><b>Faecal Sample 2 ID</b>: Identifier for any faecal samples taken (for second investigator) (Field type: id)</li><li><b>Processor</b>: Person who processed the animal (Field type: comments)</li><li><b>Other Notes</b>: Original supplementary field notes on the trap outcome or the animal captured. This column includes supporting notes for ID, descriptions of the circumstances of a death, admissions of missing data, etc etc. These have not been error-checked or modified. (Field type: comments)</li></ul></li><li><p><b>Site deployment information</b> (described in worksheet Site_Deployment_Info)</p><p>Description: This sheet contains information about the weather condition, animal occurrences or human disturbances which may influence the live mammal trapping outcome during the course of the live trapping. It contains the grid information, trapping day, data, observers and the weather condition and if any general observations made about the grid on the trapping days. </p><p>Number of fields: 6</p><p>Number of data rows: 154</p><p>Fields: </p><ul><li><b>Location</b>: Grid-Session-Occasion (Field type: id)</li><li><b>Day</b>: Trapping day number (Field type: id)</li><li><b>Date</b>: Date of trap collection (Field type: date)</li><li><b>Observer</b>: Observer (Field type: comments)</li><li><b>Weather condition</b>: Weather notes (Field type: comments)</li><li><b>General Notes</b>: Other notes (Field type: comments)</li></ul></li></ol><p><b>Date range: </b>2011-05-12 to 2019-11-22</p><p><b>Latitudinal extent: </b>4.6429 to 4.7539</p><p><b>Longitudinal extent: </b>116.9471 to 117.5938</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> -  -  Chordata <br> -  -  -  Aves <br> -  -  -  -  Cuculiformes <br> -  -  -  -  -  Cuculidae <br> -  -  -  -  -  -  <i>Centropus</i> <br> -  -  -  -  Passeriformes <br> -  -  -  -  -  Timaliidae <br> -  -  -  -  -  -  <i>Macronus</i> <br> -  -  -  -  -  -  -  <i>Macronus bornensis</i> <br> -  -  -  -  -  Pellorneidae <br> -  -  -  -  -  -  <i>Malacocincla</i> <br> -  -  -  -  -  -  -  <i>Malacocincla malaccensis</i> <br> -  -  -  -  -  Pittidae <br> -  -  -  -  -  -  <i>Pitta</i> <br> -  -  -  -  -  -  -  <i>Pitta arquata</i> <br> -  -  -  Mammalia <br> -  -  -  -  Rodentia <br> -  -  -  -  -  Sciuridae <br> -  -  -  -  -  -  <i>Callosciurus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus adamsi</i> <br> -  -  -  -  -  -  -  <i>Callosciurus notatus</i> <br> -  -  -  -  -  -  -  <i>Callosciurus prevostii</i> <br> -  -  -  -  -  -  <i>Lariscus</i> <br> -  -  -  -  -  -  -  <i>Lariscus hosei</i> <br> -  -  -  -  -  -  <i>Sundasciurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus brookei</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus hippurus</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus lowii</i> <br> -  -  -  -  -  -  -  <i>Sundasciurus tenuis</i> <br> -  -  -  -  -  Muridae <br> -  -  -  -  -  -  <i>Maxomys</i> <br> -  -  -  -  -  -  -  <i>Maxomys rajah</i> <br> -  -  -  -  -  -  -  <i>Maxomys ochraceiventer</i> <br> -  -  -  -  -  -  -  <i>Maxomys surifer</i> <br> -  -  -  -  -  -  -  <i>Maxomys baeodon</i> <br> -  -  -  -  -  -  <i>Rattus</i> <br> -  -  -  -  -  -  -  <i>Rattus tiomanicus</i> <br> -  -  -  -  -  -  -  <i>Rattus exulans</i> <br> -  -  -  -  -  -  -  <i>Rattus rattus</i> <br> -  -  -  -  -  -  <i>Sundamys</i> <br> -  -  -  -  -  -  -  <i>Sundamys muelleri</i> <br> -  -  -  -  -  -  <i>Niviventer</i> <br> -  -  -  -  -  -  -  <i>Niviventer cremoriventer</i> <br> -  -  -  -  -  -  <i>Chrotomys</i> <br> -  -  -  -  -  -  -  <i>Chrotomys whiteheadi</i> (as homotypic_synonym: <i>Maxomys whiteheadi</i>)<br> -  -  -  -  -  -  <i>Leopoldamys</i> <br> -  -  -  -  -  -  -  <i>Leopoldamys sabanus</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  Mustelidae <br> -  -  -  -  -  -  <i>Martes</i> <br> -  -  -  -  -  -  -  <i>Martes flavigula</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Scandentia <br> -  -  -  -  -  Tupaiidae <br> -  -  -  -  -  -  <i>Tupaia</i> <br> -  -  -  -  -  -  -  <i>Tupaia longipes</i> <br> -  -  -  -  -  -  -  <i>Tupaia minor</i> <br> -  -  -  -  -  -  -  <i>Tupaia tana</i> <br> -  -  -  -  -  -  -  <i>Tupaia gracilis</i> <br> -  -  -  -  -  -  -  <i>Tupaia dorsalis</i> <br> -  -  -  Reptilia <br> -  -  -  -  Squamata <br> -  -  -  -  -  Gekkonidae <br> -  -  -  -  -  Scincidae <br> -  -  -  -  -  Varanidae <br> -  -  -  -  -  -  <i>Varanus</i> <br></div><p></p>
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Allen Brain Atlas
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