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3,136 results for “Terrestrialization”
Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes
<p>The data supports the manuscript entitled “Low Frequency Radio Pulses Produced by Terrestrial Gamma-ray Flashes<br> ” that is under review in GRL. These files can be opened by MATLAB. The data can be used freely for scientific purposes with appropriate citation.</p>
Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats
<b>Description: </b><p>A study on the small mammals communities was carried out in disturbed habitats aroundsabah, namely university malaysia sabah (ums), klias peat swamp forest reserve(klias), kawang forest reserve (kawang), kalabakan forest reserve (safe) and maliaubasin conservation area (maliau). the objectives were (1) to determine the speciesrichness and composition of non-volant small mammal communities in disturbedhabitats; (2) to characterize the microhabitat-use patterns of the non-volant smallmammal communities in disturbed habitats; and (3) to determine the microhabitatpreferences of the non-volant small mammal communities in disturbed habitats. the aimof this study was to investigate how the habitat disturbance affects the species richness,community compositions and microhabitat-use pattern of the small mammals. this studywas conducted from october 2014 to march 2015 with a total sampling effort of 540trap-nights. overall, 71 individuals representing 14 species were successfully caughtduring this study. the species richness peaked at safe, and then declined at the rest ofthe study sites. habitat variables analysis showed that all study sites were divided intothree distinctive groups in terms of habitat types. canonical discriminant functionanalysis were used to analyze the microhabitat preferences and use-pattern of smallmammals and results showed the preferences of small mammals towards shrub cover(rattus rattus and callosciurus notatus), litter cover (callosciurus prevostii and echinorexgymnurus) and herbs limber (tupaia gracilis). The locations of the traps have not been given longitute and latitute as there were set on animal trails approximately 20metres from one another. </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/150"><b>Species richness, composition and microhabitat characteristics of non-volant terrestrial mammals in disturbed habitats</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 Biodiverstiy Council (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=3265704">here</a></p><p><b>Files: </b>This consists of 1 file: Veg_Volent_mammals.xlsx</p><p><b>Veg_Volent_mammals.xlsx</b></p><p>This file contains dataset metadata and 2 data tables:</p><ol><li><p><b>Vegetation cover</b> (described in worksheet Vegetation_cover)</p><p>Description: The estimated canopy cover and percentage of ground cover of traps across disturbed habitats</p><p>Number of fields: 19</p><p>Number of data rows: 180</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Habitat_type</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Canopy_cover</b>: Percentage of canopy cover (Field type: Numeric)</li><li><b>Canopy_height</b>: Canopy height (Field type: Numeric)</li><li><b>Herbs_Climber</b>: Any climbers seen on trees for example vines and lianas (Field type: Numeric)</li><li><b>Tree_GBH_>10CM</b>: Tree girth at breast height of 10 cm (Field type: Numeric)</li><li><b>Tree_GBH_>30CM</b>: Tree girth at breast height of 30 cm (Field type: Numeric)</li><li><b>Tree_GBH_>60CM</b>: Tree girth at breast height of 60 cm (Field type: Numeric)</li><li><b>Tree_GBH_>90CM</b>: Tree girth at breast height of 90 cm (Field type: Numeric)</li><li><b>Fallen_trees_bran</b>: Percentage cover (Field type: Numeric)</li><li><b>Bareground</b>: Percentage cover (Field type: Numeric)</li><li><b>Shrub</b>: Percentage cover (Field type: Numeric)</li><li><b>grass</b>: Percentage cover (Field type: Numeric)</li><li><b>Rock</b>: Percentage cover (Field type: Numeric)</li><li><b>Litter</b>: Percentage cover (Field type: Numeric)</li><li><b>Water</b>: Percentage cover (Field type: Numeric)</li><li><b>Twig</b>: Percentage cover (Field type: Numeric)</li></ul></li><li><p><b>Non volent mammal abundance</b> (described in worksheet Non_volent_mammals)</p><p>Description: The abundance of non-volant terrestrails mammals caught across disturbed habitats. Growth and sex measurements takens</p><p>Number of fields: 17</p><p>Number of data rows: 490</p><p>Fields: </p><ul><li><b>Date</b>: Date the vegetation cover was collected (Field type: Date)</li><li><b>Location</b>: Where data was collected (Field type: Location)</li><li><b>Transect</b>: Transect number (Field type: ID)</li><li><b>Habitat</b>: Habitat type (Field type: Categorical)</li><li><b>Trap_station</b>: Transect and trap number (Field type: ID)</li><li><b>Species</b>: Species of non volent mammals caught in trap (Field type: Taxa)</li><li><b>Weight</b>: Weight of caught non volent mammal (Field type: Numeric)</li><li><b>Ear</b>: Ear measurment of caught non volent mammal (Field type: Numeric)</li><li><b>Hind_leg</b>: Hind leg measurement of caught non-volent mammal (Field type: Numeric)</li><li><b>Head_body</b>: Head to body measurement of caught non volent mammal (Field type: Numeric)</li><li><b>Tail</b>: Tail length of caught non volent mammal (Field type: Numeric)</li><li><b>Sex</b>: Sex of caught non volent mammal (Field type: Categorical)</li><li><b>Sexual_activity</b>: Sexual maturity of caught non volent mammal (Field type: Categorical)</li><li><b>Age</b>: Age class of caught non volent mammal (Field type: Categorical)</li><li><b>Trap_condition</b>: Trap condition (Field type: Categorical)</li><li><b>Trap_open_closed</b>: Trap open or closed (Field type: Categorical)</li><li><b>Bait</b>: Bait taken or intact (Field type: Categorical)</li></ul></li></ol><p><b>Date range: </b>2014-10-22 to 2015-03-30</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> -  -  - Erinaceomorpha<br> -  -  -  - Erinaceidae<br> -  -  -  -  - <i>Echinosorex</i><br> -  -  -  -  -  - <i>Echinosorex gymnura</i><br> -  -  - Rodentia<br> -  -  -  - Muridae<br> -  -  -  -  - <i>Lenothrix</i><br> -  -  -  -  -  - <i>Lenothrix canus</i><br> -  -  -  -  - <i>Leopoldamys</i><br> -  -  -  -  -  - <i>Leopoldamys sabanus</i><br> -  -  -  -  - <i>Maxomys</i><br> -  -  -  -  -  - <i>Maxomys rajah</i><br> -  -  -  -  -  - <i>Maxomys surifer</i><br> -  -  -  -  - <i>Niviventer</i><br> -  -  -  -  -  - <i>Niviventer cremoriventer</i><br> -  -  -  -  - <i>Rattus</i><br> -  -  -  -  -  - <i>Rattus rattus</i><br> -  -  -  - Sciuridae<br> -  -  -  -  - <i>Callosciurus</i><br> -  -  -  -  -  - <i>Callosciurus adamsi</i><br> -  -  -  -  -  - <i>Callosciurus notatus</i><br> -  -  -  -  -  - <i>Callosciurus prevostii</i><br> -  -  -  -  - <i>Sundasciurus</i><br> -  -  -  -  -  - <i>Sundasciurus lowii</i><br> -  -  - Scandentia<br> -  -  -  - Tupaiidae<br> -  -  -  -  - <i>Tupaia</i><br> -  -  -  -  -  - <i>Tupaia dorsalis</i><br> -  -  -  -  -  - <i>Tupaia glis</i><br> -  -  -  -  -  - <i>Tupaia gracilis</i><br></div><p></p>
Global heat map of probable importance of terrestrial ecosystems on meeting local demand of freshwater services
<p>This map (raster dataset, single layer) uses existing datasets to map globally “How important point x is likely to be for meeting the demand of a reliable & useable source of water on a scale of 0 to 1?” This relatively simple approach uses estimated water demand in a given basin as weight to identify pressure for flow regulation and water provisioning services. Precipitation and land cover estimates are then combined with it to give some insight into the hydrologic attributes of “location” and “timing” of flow that the ecosystems may influence. The underlying assumption here is that undisturbed ecosystems everywhere are performing the ecohydrological functions leading to freshwater services. The question is more (at the global scale): how dependent are the populations in the basin on the continued functioning of these services.</p> <p><strong>Input datasets:</strong></p> <ol> <li>Annual surface & groundwater (“blue”) water consumption estimates. URL: <a href="http://waterfootprint.org/en/resources/water-footprint-statistics/">http://waterfootprint.org/en/resources/water-footprint-statistics/</a></li> <li>HydroBasins watershed outline.</li> <li>European Space Agency (ESA) global land cover 2015.</li> <li>WorldClim annual average precipitation (Version 2.0).</li> </ol> <p><strong>Process:</strong></p> <p>Step 1: Calculate average annual water consumption estimates over HydroBasin outlines. This step spreads the demand laterally (in case of small basins) and upstream to the headwaters from (typically) downstream consumer concentration.</p> <p>Step 2: Normalize the demand globally and map the normalized values on to “natural” land cover classes from the land cover dataset [forests, grasslands, etc].</p> <p>Step 3: Normalize annual precipitation layer within basins on the scale 0-1 where 1 is the maximum annual precipitation in that basin. This is also mapped on the “natural” land cover. Precipitation is thus acting as ‘weight’ for importance within the basin. Example, upland headwaters will typically receive more rainfall and can be argued to be important for the flow regulation in the basin.</p> <p>Step 4: Combine the layers from 2 and 3.</p> <p><strong>Caveats:</strong></p> <ol> <li>Identification of what constitutes a “natural” land cover is not trivial, especially from global land cover maps. Example: Forests and plantations are hard to distinguish from these products.</li> <li>Improvement of quality of water is assumed to be implicit for functioning ecosystems.</li> </ol>
Data repository of the paper "The First Terrestrial Electron Beam Observed by The Atmosphere-Space Interactions Monitor" by D. Sarria et al.
<p>Data repository / Supporting information of the paper "The First Terrestrial Electron Beam Observed by The Atmosphere-Space Interactions Monitor" (2019) by D. Sarria et al.</p> <p>Access to the article: <a href="https://doi.org/10.1029/2019JA027071">https://doi.org/10.1029/2019JA027071</a></p>
Occurrence of blood feeding terrestrial leeches in a degraded forest ecosystem
<b>Description: </b><p>This dataset includes the abundance of two species of terrestrial leech collected at multiple sites at the SAFE project in Sabah, Malaysia. Leech collections took place over two seasons, one in the dry season of 2015 and one in the wet season of 2016. For each of the sites, four repeated visits took place and 20 minute searches were conducted within the boundaries of 25 m2 vegetation plots. As these sites have been subjected to differennt degrees of current and historic degradation, the vegetation structure data is also included for each site. For a subset of the leech sites there is corresponding mammal detection data from camera traps across the landscape, which is also included in this dataset.</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/10"><b>The effects of rainforest fragmentation on mammal community assemblages using leech blood-meal analysis</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>NERC (Standard grant , NE/K016148/1)</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>XML metadata: </b>GEMINI compliant metadata for this dataset is available <a href="https://www.safeproject.net/datasets/xml_metadata?id=3476542">here</a></p><p><b>Files: </b>This consists of 1 file: Drinkwater2019_leech_occurrence.v2.xlsx</p><p><b>Drinkwater2019_leech_occurrence.v2.xlsx</b></p><p>This file contains dataset metadata and 4 data tables:</p><ol><li><p><b>Leech abundance and survey-covariates 2015</b> (described in worksheet abundance2015)</p><p>Description: This dataset has the abundance of all the leech individuals of both species collected during surveys in 2015 between February and June. The number of leech collected is split by species of leech and each of the four visits per site. For each survey at a site the associated survey-specific covariates are included. These are the associated effort (number of people collecting the leeches) and the date the visits happened (julian day since the beginning of the year). </p><p>Number of fields: 17</p><p>Number of data rows: 169</p><p>Fields: </p><ul><li><b>site</b>: SAFE second order point (Field type: location)</li><li><b>visit_B1</b>: Number of brown leeches collected during first visit to each site (Field type: abundance)</li><li><b>visit_B2</b>: Number of brown leeches collected during second visit to each site (Field type: abundance)</li><li><b>visit_B3</b>: Number of brown leeches collected during third visit to each site (Field type: abundance)</li><li><b>visit_B4</b>: Number of brown leeches collected during fourth visit to each site (Field type: abundance)</li><li><b>visit_T1</b>: Number of tiger leeches collected during first visit to each site (Field type: abundance)</li><li><b>visit_T2</b>: Number of tiger leeches collected during second visit to each site (Field type: abundance)</li><li><b>visit_T3</b>: Number of tiger leeches collected during third visit to each site (Field type: abundance)</li><li><b>visit_T4</b>: Number of tiger leeches collected during fourth visit to each site (Field type: abundance)</li><li><b>eff_1</b>: Number of people collecting leeches per survey as a measure of survey effort for the first visit to each site (Field type: abundance)</li><li><b>eff_2</b>: Number of people collecting leeches per survey as a measure of survey effort for the second visit to each site (Field type: abundance)</li><li><b>eff_3</b>: Number of people collecting leeches per survey as a measure of survey effort for the third visit to each site (Field type: abundance)</li><li><b>eff_4</b>: Number of people collecting leeches per survey as a measure of survey effort for the fourth visit to each site (Field type: abundance)</li><li><b>date.1</b>: Julian date of visit 1 (Field type: numeric)</li><li><b>date.2</b>: Julian date of visit 2 (Field type: numeric)</li><li><b>date.3</b>: Julian date of visit 3 (Field type: numeric)</li><li><b>date.4</b>: Julian date of visit 4 (Field type: numeric)</li></ul></li><li><p><b>Leech abundance and survey-covariates 2016</b> (described in worksheet abundance2016)</p><p>Description: This dataset has the abundance of all the leech individuals of both species collected during surveys in 2016 between September and December. The number of leech collected is split by species of leech and each of the four visits per site. For each survey at a site the associated survey-specific covariates are included. These are the associated effort (number of people collecting the leeches) and the date the visits happened (julian day since the beginning of the year). </p><p>Number of fields: 17</p><p>Number of data rows: 169</p><p>Fields: </p><ul><li><b>site</b>: SAFE second order point (Field type: location)</li><li><b>visit_B1</b>: Number of brown leeches collected during first visit to each site (Field type: abundance)</li><li><b>visit_B2</b>: Number of brown leeches collected during second visit to each site (Field type: abundance)</li><li><b>visit_B3</b>: Number of brown leeches collected during third visit to each site (Field type: abundance)</li><li><b>visit_B4</b>: Number of brown leeches collected during fourth visit to each site (Field type: abundance)</li><li><b>visit_T1</b>: Number of tiger leeches collected during first visit to each site (Field type: abundance)</li><li><b>visit_T2</b>: Number of tiger leeches collected during second visit to each site (Field type: abundance)</li><li><b>visit_T3</b>: Number of tiger leeches collected during third visit to each site (Field type: abundance)</li><li><b>visit_T4</b>: Number of tiger leeches collected during fourth visit to each site (Field type: abundance)</li><li><b>eff_1</b>: Number of people collecting leeches per survey as a measure of survey effort for the first visit to each site (Field type: abundance)</li><li><b>eff_2</b>: Number of people collecting leeches per survey as a measure of survey effort for the second visit to each site (Field type: abundance)</li><li><b>eff_3</b>: Number of people collecting leeches per survey as a measure of survey effort for the third visit to each site (Field type: abundance)</li><li><b>eff_4</b>: Number of people collecting leeches per survey as a measure of survey effort for the fourth visit to each site (Field type: abundance)</li><li><b>date.1</b>: Julian date of visit 1 (Field type: numeric)</li><li><b>date.2</b>: Julian date of visit 2 (Field type: numeric)</li><li><b>date.3</b>: Julian date of visit 3 (Field type: numeric)</li><li><b>date.4</b>: Julian date of visit 4 (Field type: numeric)</li></ul></li><li><p><b>Site specific covariates</b> (described in worksheet covariates)</p><p>Description: Vegetation structure data associated with each site for which leech surveys were conducted. The metrics include canopy height, moran's I and plant-area-index. These data were extracted from LiDAR data with a 50 m2 buffer around the centroid for each site.</p><p>Number of fields: 6</p><p>Number of data rows: 169</p><p>Fields: </p><ul><li><b>site</b>: SAFE second order point code (Field type: location)</li><li><b>tch</b>: Top of canopy height per site (Field type: numeric)</li><li><b>canopy_height_moran</b>: Habitat heterogeneity - Morans I - per site (Field type: numeric)</li><li><b>canopy_height_sd</b>: Standard deviation of canopy height (Field type: numeric)</li><li><b>pai_mean</b>: Mean plant area index at site (Field type: numeric)</li><li><b>pai_sd</b>: Plant area index standard deviation (Field type: numeric)</li></ul></li><li><p><b>Mammal detections </b> (described in worksheet mammals)</p><p>Description: This dataset contains the mammal detections recorded from camera traps at a subset of the leech survey locations. Sampling effort is also included as a measure of survey effort. </p><p>Number of fields: 27</p><p>Number of data rows: 83</p><p>Fields: </p><ul><li><b>Camera</b>: Name of camera (Field type: location)</li><li><b>CTNs</b>: Measure of trapping effort - number of nights the cameras were operational (Field type: numeric)</li><li><b>Asian Elephant</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Banded Civet</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Banteng</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Bearded Pig</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Bornean Yellow Muntjac</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Common Palm Civet</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Greater Mouse-deer</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Leopard Cat</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Lesser Mouse-deer</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Long-tailed Macaque</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Long-tailed Porcupine</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Malay Civet</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Malay Porcupine</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Marbled Cat</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Masked Palm Civet</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Moonrat</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Mousedeer sp.</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Muntjac sp.</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Orangutan</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Pig-tailed Macaque</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Red Muntjac</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Sambar Deer</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Sun Bear</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Sunda Pangolin</b>: Count of detections for this taxon (Field type: abundance)</li><li><b>Thick-spined Porcupine</b>: Count of detections for this taxon (Field type: abundance)</li></ul></li></ol><p><b>Date range: </b>2015-02-01 to 2016-12-31</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> -  -  -  -  -  Hystricidae <br> -  -  -  -  -  -  <i>Hystrix</i> <br> -  -  -  -  -  -  -  <i>Hystrix brachyura</i> <br> -  -  -  -  -  -  -  <i>Hystrix crassispinis</i> <br> -  -  -  -  -  -  <i>Trichys</i> <br> -  -  -  -  -  -  -  <i>Trichys fasciculata</i> <br> -  -  -  -  Proboscidea <br> -  -  -  -  -  Elephantidae <br> -  -  -  -  -  -  <i>Elephas</i> <br> -  -  -  -  -  -  -  <i>Elephas maximus</i> <br> -  -  -  -  Carnivora <br> -  -  -  -  -  Viverridae <br> -  -  -  -  -  -  <i>Viverra</i> <br> -  -  -  -  -  -  -  <i>Viverra tangalunga</i> <br> -  -  -  -  -  -  <i>Paguma</i> <br> -  -  -  -  -  -  -  <i>Paguma larvata</i> <br> -  -  -  -  -  -  <i>Paradoxurus</i> <br> -  -  -  -  -  -  -  <i>Paradoxurus hermaphroditus</i> <br> -  -  -  -  -  -  <i>Hemigalus</i> <br> -  -  -  -  -  -  -  <i>Hemigalus derbyanus</i> <br> -  -  -  -  -  Felidae <br> -  -  -  -  -  -  <i>Pardofelis</i> <br> -  -  -  -  -  -  -  <i>Pardofelis marmorata</i> <br> -  -  -  -  -  -  <i>Prionailurus</i> <br> -  -  -  -  -  -  -  <i>Prionailurus bengalensis</i> <br> -  -  -  -  -  Ursidae <br> -  -  -  -  -  -  <i>Helarctos</i> <br> -  -  -  -  -  -  -  <i>Helarctos malayanus</i> <br> -  -  -  -  Primates <br> -  -  -  -  -  Cercopithecidae <br> -  -  -  -  -  -  <i>Macaca</i> <br> -  -  -  -  -  -  -  <i>Macaca fascicularis</i> <br> -  -  -  -  -  -  -  <i>Macaca nemestrina</i> <br> -  -  -  -  -  Hominidae <br> -  -  -  -  -  -  <i>Pongo</i> <br> -  -  -  -  -  -  -  <i>Pongo pygmaeus</i> <br> -  -  -  -  -  -  <i>Homo</i> <br> -  -  -  -  -  -  -  <i>Homo sapiens</i> <br> -  -  -  -  Pholidota <br> -  -  -  -  -  Manidae <br> -  -  -  -  -  -  <i>Manis</i> <br> -  -  -  -  -  -  -  <i>Manis javanica</i> <br> -  -  -  -  Erinaceomorpha <br> -  -  -  -  -  Erinaceidae <br> -  -  -  -  -  -  <i>Echinosorex</i> <br> -  -  -  -  -  -  -  <i>Echinosorex gymnura</i> <br> -  -  -  -  Artiodactyla <br> -  -  -  -  -  Suidae <br> -  -  -  -  -  -  <i>Sus</i> <br> -  -  -  -  -  -  -  <i>Sus barbatus</i> <br> -  -  -  -  -  Bovidae <br> -  -  -  -  -  -  <i>Bos</i> <br> -  -  -  -  -  -  -  <i>Bos javanicus</i> <br> -  -  -  -  -  Tragulidae <br> -  -  -  -  -  -  <i>Tragulus</i> <br> -  -  -  -  -  -  -  <i>Tragulus napu</i> <br> -  -  -  -  -  -  -  <i>Tragulus kanchil</i> <br> -  -  -  -  -  Cervidae <br> -  -  -  -  -  -  <i>Muntiacus</i> <br> -  -  -  -  -  -  -  <i>Muntiacus atherodes</i> <br> -  -  -  -  -  -  -  <i>Muntiacus muntjak</i> <br> -  -  -  -  -  -  <i>Rusa</i> <br> -  -  -  -  -  -  -  <i>Rusa unicolor</i> <br> -  -  Annelida <br> -  -  -  Clitellata <br> -  -  -  -  Arhynchobdellida <br> -  -  -  -  -  Haemadipsidae <br> -  -  -  -  -  -  <i>Haemadipsa</i> <br> -  -  -  -  -  -  <i>Haemadipsa</i> <br> -  -  -  -  -  -  -  <i>Haemadipsa picta</i> <br></div><p></p>
Fig. 5 in First Records from Japan of European Vermi-composter Dendrobaena veneta (Rosa, 1886) and of "Classical" Lumbricus terrestris Linnaeus, 1758 (Annelida, Oligochaeta, Megadrilacea, Lumbricidae)
Fig. 5. Setal ratios provide simple differentiation.
Figure 6 in Assessment of terrestrial snails' diversity and composition in six forests of west central - Morocco along an altitudinal gradient
Figure 6. Diversity of stations along altitudinal gradient using Shannon index.
Figure 5 in Assessment of terrestrial snails' diversity and composition in six forests of west central - Morocco along an altitudinal gradient
Figure 5. Species composition per forest site (For site abbreviations, see Table 1).
Figure 4 in Assessment of terrestrial snails' diversity and composition in six forests of west central - Morocco along an altitudinal gradient
Figure 4. Families composition per forest site (For site abbreviations, see Table 1).
Figures 1–3 in Some terrestrial Parasitengona with new records of the genera Iberochyzeria, Leptus and Charletonia (Trombidiformes: Chyzeriidae, Erythraeidae) from Türkiye
Figures 1–3. Iberochyzeria fornielesi (Turkish specimen): 1. Ta I; 2. Ta II; 3. Ta III.
Fig. 9 in Diversity and conservation of terrestrial, freshwater, and marine reptiles and amphibians in Saudi Arabia
Fig. 9. The Zarudnyi Worm Lizard, Diplometopon zarudnyi. Photos by A. Aloufi.
Fig. 2 in Diversity and conservation of terrestrial, freshwater, and marine reptiles and amphibians in Saudi Arabia
Fig. 2. Ad Disah mountains, southwest Tabuk. Photo by S. Al Jathli.
Fig. 1 in Diversity and conservation of terrestrial, freshwater, and marine reptiles and amphibians in Saudi Arabia
Fig. 1. Map of Saudi Arabia showing main geographic landmarks (after Al-Nafie 2018).
Fig. 4 in Diversity and conservation of terrestrial, freshwater, and marine reptiles and amphibians in Saudi Arabia
Fig. 4. Phytogeographical regions of Saudi Arabia (after Al-Nafie 2008).
Fig. 5 in A new species of terrestrial-breeding frog of the genus Psychrophrynella (Anura: Strabomantidae) from the Cordillera de Vilcabamba, southeastern Peru
Fig. 5. View of the type locality of Psychrophrynella vilcabambensis sp. nov.
Map 36 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Map 36. Distribution map for Trachelipus rathkii.
Fig. 39 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Fig. 39. Corrected number of observations per two-month period for Porcellium conspersum (N = 63).
Map 35 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Map 35. Distribution map for Porcellium conspersum.
Fig. 40 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Fig. 40. Corrected number of observations per two-month period for Trachelipus rathkii (N = 189).
Map 34 in Habitat and seasonal activity patterns of the terrestrial isopods (Isopoda: Oniscidea) of Belgium
Map 34. Distribution map for Porcellionides pruinosus.
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Allen Brain Atlas
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