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53 results for “paleotropical”
Fig. 5 in Seed morphology of the paleotropical tribe Paropsieae (Passifloraceae, Malpighiales), and paleobotanical implications
Fig. 5. Seeds of the genus Paropsia Noronha ex Thouars. A–D. Paropsia humblotii H.Perrier (Ragauaparany 8040; P04766828). E–H. Paropsia madagascariensis H.Perrier (R. Bernard 120; P04766852). I–L. Paropsia obscura O.Hoffm (Madiomanana et al. 108; P05470672). M–P. Paropsia vareciformis (Griff.) Mast. (H. Schaller & L.E. Teo 3826; P05538484). A, E, I, M. Face view. B, F, J, N. Side view. C, G, K, O. Second face view. D, H, L, P. Basal view. Scale bar = 5 mm.
Fig. 2 in Seed morphology of the paleotropical tribe Paropsieae (Passifloraceae, Malpighiales), and paleobotanical implications
Fig. 2. Seeds of Androsiphonia adenostegia Stapf. A–D. From specimen A.J.B. Chevalier 17461 (P04772166). E–H. From specimen A.J.B. Chevalier 21194 (P04772168). A, E. Face view. B, F. Side view. C, G. Second face view. D, H. Basal view. Scale bar = 5 mm.
Fig. 4 in Seed morphology of the paleotropical tribe Paropsieae (Passifloraceae, Malpighiales), and paleobotanical implications
Fig. 4. Seeds of the genus Paropsia Noronha ex Thouars. A–D. Paropsia brazzaeana Braill. (E. Dekindt 564; P04772425). E–H. Paropsia edulis Thouars (G. Cours 3424; P04767996). I–L. Paropsia grewioides Welw. ex Mast. (R. Letouzey 5589; P04772193). M–P. Paropsia grandiflora Sleumer (H. Humbert 32553; P04767592). A, E, I, M. Face view. B, F, J, N. Side view. C, G, K, O. Second face view. D, H, L, P. Basal view. Scale bar = 5 mm.
Fig. 6 in Seed morphology of the paleotropical tribe Paropsieae (Passifloraceae, Malpighiales), and paleobotanical implications
Fig. 6. Seeds of the genera Paropsiopsis Engl. and Smeathmannia R.Br. A–D. Paropsiopsis decandra (Baill.) Sleumer (T.J. Klaine 194; P04772112). E–H. Smeathmannia laevigata Sol. ex R.Br. (Heudelot 655; P04772782). I–L. Smeathmannia pubescens Sol. ex R.Br. (A.J.B. Chevalier 17306; P04772722). A, E, I. Face view. B, F, J. Side view. C, G, K. Second face view. D, H, L. Basal view. Scale bar = 5 mm. Arrow: mucro.
Fig. 3 in Review Of The Paleotropical Neogastrini Earthworms (Oligochaeta, Acanthodrilidae: Benhamiinae) With Description Of Two New Genera
Fig. 3. Wegeneriella birangi sp. n. A: ventral side of the clitellum, fp = female pore, pp = prostatic pores; B: spermatheca
Fig. 2 in Review Of The Paleotropical Neogastrini Earthworms (Oligochaeta, Acanthodrilidae: Benhamiinae) With Description Of Two New Genera
Fig. 2. Pickfordiella eudrilina gen et sp. n. A: ventral side of the clitellum. fp = female pore, pp = prostatic pore., B: prostate. p = glandular part of the prostate, cs = copulatory chamber., C: Spermatheca. d = diverticulum, s = septum
Linked collectors and determiners for: Systematics of Mendoncia (Acanthaceae: Thunbergioideae) in the Paleotropics.
Natural history specimen data linked to collectors and determiners held within, "Systematics of Mendoncia (Acanthaceae: Thunbergioideae) in the Paleotropics". Claims or attributions were made on Bionomia by volunteer Scribes, <a href="http://bionomia.net/dataset/cd311325-4188-40bf-b36c-fedbfc64d9ff">https://bionomia.net/dataset/cd311325-4188-40bf-b36c-fedbfc64d9ff</a> using specimen data from the dataset aggregated by the Global Biodiversity Information Facility, <a href="https://gbif.org/dataset/cd311325-4188-40bf-b36c-fedbfc64d9ff">https://gbif.org/dataset/cd311325-4188-40bf-b36c-fedbfc64d9ff</a>. Formatted as a Frictionless Data package.
Resilience and virus ecology of paleotropical bats
<b>Description: </b><p>Emerging infectious diseases (EIDs) are a threat to human and animal health. Bats are known reservoir hosts for various highly fatal viruses associated with EIDs. Previously, outbreaks of some EIDs were directly associated with environmental conditions, namely an increased contact zone between reservoir hosts and humans resulting from bush-meat consumption and increasing anthropogenic land-use. <br>However, anthropogenic land-use, especially habitat logging and fragmentation, may also take effect via consequences upon wildlife communities, including population declines. Before effects manifest in decreased population sizes, individuals may show changes in physiological parameters. In this project, I investigated if habitat logging and fragmentation are associated with changes in body mass, levels of chronic stress, immunity and occurrence of viruses in bats. I sampled individuals of eight bat species of the genus Rhinolophus, Hipposideros and Kerivoula at the SASFE project in Sabah, Malaysia. I found that individuals of foliage-roosting bat species weighed less in currently logged and recently fragmented habitats and had lower white blood cell counts than their conspecifics from undisturbed forests. In a cave-roosting species (Rhinolophus borneensis) individuals from fragmented forests showed higher levels of chronic stress (indicated by the neutrophil to lymphocyte ratio) than conspecifics from actively logged forests. Overall, I conclude that foliage-roosting bat species may be particularly vulnerable to habitat fragmentation, affecting their overall health including cell-mediated immunity.<br>Further, I investigated if the detrimental effects of habitat logging and<br>fragmentation on the overall health of bats are reflected in increased detection rates of corona- and astroviruses in fecal samples of bats in the same study site. An increase in detection rates may increase the risk for pathogen spill-overs from bats to humans. Unexpectedly, the detection rates were not associated with habitat logging and fragmentation in any species. However, I identified the rainy season as a risk factor for increased astrovirus shedding. Further, individuals in poor body condition tended to have a higher risk for astrovirus shedding.<br>In conclusion, foliage-roosting bat species may turn into a source for future viral spillover events if they are sufficiently resistant to remain in logged and fragmented habitats. Ongoing landscape fragmentation in Southeast Asia and worldwide will reduce the connectivity of remaining habitats, resulting in lower mobility and genetic diversity of bats within a species in future generations. These bat populations may have a higher susceptibility to contract and shed viruses especially during the rainy season. If <br>humans or their livestock live nearby, these viruses or other pathogens may spill over in new hosts.</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/73"><b>Resilience and virus ecology of paleotropical bats</b></a></p><p><b>Funding: </b>These data were collected as part of research funded by: </p><ul><li>German Research Council (Research grant, DFG Priority Programm 1596; Vo890/23, DR772/10-1 and 2)</li><li>UK NERC Natural Environment Research Council (Research grant, HTMF Human-Modified Tropical Forests program under the LOMBoK Land-Use Options for Maintaining Biodiversity and Ecosystem Function consortium)</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 JKM/MBS.1000-2/2 JLD.3 (153))</li><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/2 JLD.3 (317))</li><li>Sabah Biodiversity Council (Research licence JKM/MBS.1000-2/3 JLD.2 (16))</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=3948443">here</a></p><p><b>Files: </b>This dataset consists of 2 files: Seltmann_bat_data_V2.xlsx, Traps2014.2015.gpx</p><p><b>Seltmann_bat_data_V2.xlsx</b></p><p>This file contains dataset metadata and 9 data tables:</p><ol><li><p><b>ACTH_challenge</b> (described in worksheet ACTH_challenge)</p><p>Description: ACTH challenge</p><p>Number of fields: 17</p><p>Number of data rows: 15</p><p>Fields: </p><ul><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Capture</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Cortisol</b>: Blood cortisol levels (Field type: numeric trait)</li><li><b>Recapture</b>: Is the bat a recapture (Field type: categorical trait)</li><li><b>Date</b>: Date of capture (Field type: date)</li><li><b>Trap</b>: Trap number (Field type: id)</li><li><b>Species</b>: Species of bat (Field type: taxa)</li><li><b>Sex</b>: Sex of bat (Field type: categorical trait)</li><li><b>Age</b>: Age of bat (A - adult) (Field type: categorical trait)</li><li><b>Rep</b>: Reproductive status (PL - postlactating) (Field type: categorical trait)</li><li><b>Forearm_length</b>: Forearm length (Field type: numeric trait)</li><li><b>Weight</b>: Weight (Field type: numeric trait)</li><li><b>Fed</b>: Feeding status (Field type: categorical trait)</li><li><b>T1</b>: Temperature before ACTH injection (Field type: numeric trait)</li><li><b>T2</b>: Temperature after ACTH injection (Field type: numeric trait)</li><li><b>Parasites</b>: Parasites observed on sampled bat (Field type: categorical trait)</li><li><b>W</b>: Wing punch (Field type: categorical trait)</li></ul></li><li><p><b>Viral_fecal_samples</b> (described in worksheet Viral_fecal_samples)</p><p>Description: Viral prevalences 03-04 2015</p><p>Number of fields: 31</p><p>Number of data rows: 790</p><p>Fields: </p><ul><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Capture</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Pool_comments</b>: Pool ID (Field type: comments)</li><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Time</b>: Time of sampling (Field type: time)</li><li><b>Astro</b>: Astrovirus prevalence (Field type: categorical trait)</li><li><b>COV</b>: Coronavirus prevalence (Field type: categorical trait)</li><li><b>Band_no</b>: Ring-Number (Field type: id)</li><li><b>R</b>: Recapture (uk - unknown) (Field type: categorical trait)</li><li><b>Trap</b>: Trap ID (Field type: id)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>Sex</b>: Sex of bat sampled (Field type: categorical trait)</li><li><b>Age</b>: Age of bat sampled (A - adult, S - subadult, J - juvenile) (Field type: categorical trait)</li><li><b>Rep</b>: Reproductive status (L - lactating, PL - postlacting, RPL - recently postlactating, Pr - Pregnant, NR - non reproductive) (Field type: categorical trait)</li><li><b>Forearm_length</b>: Forearm length (Field type: numeric trait)</li><li><b>Weight</b>: Biomass of bat (Field type: numeric trait)</li><li><b>Fed</b>: Feeding status (Field type: categorical trait)</li><li><b>O</b>: Oral swab (Field type: numeric trait)</li><li><b>U</b>: Urine swab (Field type: numeric trait)</li><li><b>F</b>: fecal sample (Field type: numeric trait)</li><li><b>FS</b>: fecal swab (Field type: numeric trait)</li><li><b>BS</b>: blood smear (Field type: numeric trait)</li><li><b>B1</b>: blood sample before ACTH injection (Field type: numeric trait)</li><li><b>T1</b>: temperature before ACTH injection (Field type: numeric trait)</li><li><b>B2</b>: blood sample after ACTH injection (Field type: numeric trait)</li><li><b>T2</b>: temperature after ACTH injection (Field type: numeric trait)</li><li><b>Parasites</b>: Parasites on sampled bats (Field type: comments)</li><li><b>W</b>: Wing punch taken (Field type: numeric trait)</li><li><b>Comments</b>: Comments (Field type: comments)</li><li><b>Dave</b>: Daves comments (Field type: comments)</li><li><b>File</b>: Orignal file name (Field type: comments)</li></ul></li><li><p><b>Overview_3</b> (described in worksheet Overview_3)</p><p>Description: Viral prevalences 03-04 2015</p><p>Number of fields: 4</p><p>Number of data rows: 7</p><p>Fields: </p><ul><li><b>Species</b>: Species of bat (Field type: taxa)</li><li><b>Scientific_name</b>: Scientific name of bat (Field type: comments)</li><li><b>Total_urine_samples</b>: Total number of urine samples (Field type: numeric trait)</li><li><b>Total_fecal_samples</b>: Total number of fecal samples (Field type: numeric trait)</li></ul></li><li><p><b>Sequences</b> (described in worksheet Sequences)</p><p>Description: Coronavirsu sequences</p><p>Number of fields: 3</p><p>Number of data rows: 5</p><p>Fields: </p><ul><li><b>ID</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>Gene_seq</b>: Gene sequence code (Field type: comments)</li></ul></li><li><p><b>IgG_BKA</b> (described in worksheet IgG_BKA)</p><p>Description: IgGs and BKA</p><p>Number of fields: 28</p><p>Number of data rows: 44</p><p>Fields: </p><ul><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Capture</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Band</b>: Ring-Number (Field type: id)</li><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Trap</b>: Trap ID (Field type: id)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>R</b>: Recapture (Field type: categorical trait)</li><li><b>Sex</b>: Sex of bat (Field type: categorical trait)</li><li><b>Age</b>: Age of bat (A - adult) (Field type: categorical trait)</li><li><b>Rep</b>: Reproductive status (L - lactating, PL - postlacting, RPL - recently postlactating, Pr - Pregnant, NR - non reproductive) (Field type: categorical trait)</li><li><b>Forearm length</b>: Forearm length (Field type: numeric trait)</li><li><b>Weight</b>: Biomass of bat (Field type: numeric trait)</li><li><b>BC</b>: Body condition (mass divided by forearm) (Field type: numeric trait)</li><li><b>Fed</b>: Feeding status (Field type: categorical trait)</li><li><b>O</b>: Oral swab (Field type: numeric trait)</li><li><b>U</b>: Urine swab (Field type: numeric trait)</li><li><b>F</b>: fecal sample (Field type: numeric trait)</li><li><b>FS</b>: fecal swab (Field type: numeric trait)</li><li><b>BS</b>: blood smear (Field type: numeric trait)</li><li><b>B1</b>: blood sample before ACTH injection (Field type: numeric trait)</li><li><b>T1</b>: temperature before ACTH injection (Field type: numeric trait)</li><li><b>B2</b>: blood sample after ACTH injection (Field type: numeric trait)</li><li><b>T2</b>: temperature after ACTH injection (Field type: numeric trait)</li><li><b>W</b>: Wing punch (Field type: numeric trait)</li><li><b>Iggs1</b>: IgGs (optical density) measured before blood injected with hormone ACTH intraperitoneal (Field type: numeric trait)</li><li><b>Iggs2</b>: IgGs (optical density) measured 2.5 hours after blood injected with hormone ACTH intraperitoneal (Field type: numeric trait)</li><li><b>BKA1</b>: "The BKA is a constitutive innate marker of the immune system and measures humoral and cellular components in function of the sample used. While using whole blood is possible to quantify the overall constitutive innate immunity of an individual44, with serum or plasma samples only the humoral part is measured45,46. We assessed the bacterial killing activity (BKA) of the plasma against E. coli in vitro following the method of Schneeberger et al.47. The BKA of plasma is a functional marker of the humoral part of the constitutive innate immunity45,46. Plasma samples were diluted 1:50 in sterile PBS and we added 10 µl of a suspension of living E. coli (ATCC #8739) to each diluted sample (140 µl). The bacterial suspension was adjusted to a concentration of ~200 colonies per 50 µl plasma-bacteria mixture. The mixtures were then incubated for 30 min at 37°C. After incubation, 50 µl aliquot of the vortexed mixture was spread onto Tryptic Soy Agar plates in duplicate, followed by overnight incubation at 37°C. To obtain the initial number of bacteria that we had before starting to interact with the plasma, we diluted 140 µl PBS with bacterial suspension and plated in similar ways. On the following day, the colony-forming units were counted and the bacterial killing activity was defined as percent of the killed bacteria, which was calculated as 1-(average of viable bacteria after incubation / the initial number of bacteria47). 45 Heinrich, S. K. et al. Feliform carnivores have a distinguished constitutive innate immune response. Biol. Open 5, 550-555 (2016). 46 Heinrich, S. K. et al. Cheetahs have a stronger constitutive innate immunity than leopards. Sci. Rep. 7, 44837 (2017). 47 Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Measures of the constitutive immune system are linked to diet and roosting habits of Neotropical bats. PLoS One 8, e54023 (2013). (Field type: numeric trait)</li><li><b>BKA2</b>: "The BKA is a constitutive innate marker of the immune system and measures humoral and cellular components in function of the sample used. While using whole blood is possible to quantify the overall constitutive innate immunity of an individual44, with serum or plasma samples only the humoral part is measured45,46. We assessed the bacterial killing activity (BKA) of the plasma against E. coli in vitro following the method of Schneeberger et al.47. The BKA of plasma is a functional marker of the humoral part of the constitutive innate immunity45,46. Plasma samples were diluted 1:50 in sterile PBS and we added 10 µl of a suspension of living E. coli (ATCC #8739) to each diluted sample (140 µl). The bacterial suspension was adjusted to a concentration of ~200 colonies per 50 µl plasma-bacteria mixture. The mixtures were then incubated for 30 min at 37°C. After incubation, 50 µl aliquot of the vortexed mixture was spread onto Tryptic Soy Agar plates in duplicate, followed by overnight incubation at 37°C. To obtain the initial number of bacteria that we had before starting to interact with the plasma, we diluted 140 µl PBS with bacterial suspension and plated in similar ways. On the following day, the colony-forming units were counted and the bacterial killing activity was defined as percent of the killed bacteria, which was calculated as 1-(average of viable bacteria after incubation / the initial number of bacteria47). 45 Heinrich, S. K. et al. Feliform carnivores have a distinguished constitutive innate immune response. Biol. Open 5, 550-555 (2016). 46 Heinrich, S. K. et al. Cheetahs have a stronger constitutive innate immunity than leopards. Sci. Rep. 7, 44837 (2017). 47 Schneeberger, K., Czirják, G. Á. & Voigt, C. C. Measures of the constitutive immune system are linked to diet and roosting habits of Neotropical bats. PLoS One 8, e54023 (2013). (Field type: numeric trait)</li></ul></li><li><p><b>Leukocytes</b> (described in worksheet Leukocytes)</p><p>Description: Leukocyte counts</p><p>Number of fields: 37</p><p>Number of data rows: 57</p><p>Fields: </p><ul><li><b>Site</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Transect</b>: Transect within SAFE block (Field type: replicate)</li><li><b>Trap</b>: Trap ID (Field type: id)</li><li><b>Capture</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Band</b>: Ring-Number (Field type: id)</li><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Time</b>: Time of sampling (Field type: time)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>Recapture</b>: Recapture (uk - unknown) (Field type: categorical trait)</li><li><b>Age</b>: Age of bat sampled (Field type: categorical trait)</li><li><b>Rep</b>: Reproductive status (L - lactating, PL - postlacting, RPL - recently postlactating, Pr - Pregnant, NR - non reproductive) (Field type: categorical trait)</li><li><b>Sex</b>: Sex of bat sampled (Field type: categorical trait)</li><li><b>Forearm</b>: Forearm length (Field type: numeric trait)</li><li><b>Body mass</b>: Biomass of bat (Field type: numeric trait)</li><li><b>Fed</b>: Feeding status (Field type: categorical trait)</li><li><b>O</b>: Oral swab (Field type: numeric trait)</li><li><b>U</b>: Urine swab (Field type: numeric trait)</li><li><b>F</b>: fecal sample (Field type: numeric trait)</li><li><b>FS</b>: fecal swab (Field type: numeric trait)</li><li><b>BS</b>: blood smear (Field type: numeric trait)</li><li><b>B1</b>: blood sample before ACTH injection (Field type: numeric trait)</li><li><b>T1</b>: temperature before ACTH injection (Field type: numeric trait)</li><li><b>B2</b>: blood sample after ACTH injection (Field type: numeric trait)</li><li><b>T2</b>: temperature after ACTH injection (Field type: numeric trait)</li><li><b>Parasites</b>: Parasites on bat (Field type: comments)</li><li><b>W</b>: Wing punch (Field type: numeric trait)</li><li><b>CommentsEnglish</b>: Blood sample comments (Field type: comments)</li><li><b>Eosinophiles</b>: Eosinophiles (Field type: numeric trait)</li><li><b>Basophiles</b>: Basophiles (Field type: numeric trait)</li><li><b>Neutrophiles</b>: Neutrophiles (Field type: numeric trait)</li><li><b>Monocytes</b>: Monocytes (Field type: numeric trait)</li><li><b>Lymphocytes</b>: Lymphocytes (Field type: numeric trait)</li><li><b>CommentsGerman</b>: Comments in german (Field type: comments)</li><li><b>NL-ratio</b>: NL-ratio (Field type: numeric trait)</li><li><b>Monolayers</b>: Monolayers (Field type: numeric trait)</li><li><b>Leukocytes</b>: Leukocytes (Field type: numeric trait)</li><li><b>Mean_leukocytes_monolayer</b>: Proportion of monolayers with leukocytes (Field type: numeric trait)</li></ul></li><li><p><b>PCR</b> (described in worksheet PCR)</p><p>Description: PCR analysis</p><p>Number of fields: 10</p><p>Number of data rows: 78</p><p>Fields: </p><ul><li><b>ID</b>: Bat ID (Field type: id)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>Location</b>: Location within the SAFE landscape (Field type: location)</li><li><b>Ct_bIL-6</b>: ? (Field type: numeric trait)</li><li><b>Ct_bSTAT1</b>: ? (Field type: numeric trait)</li><li><b>Ct_bMAPK</b>: ? (Field type: numeric trait)</li><li><b>Ct_bActin_B</b>: ? (Field type: numeric trait)</li><li><b>Ct_bIL-6-2</b>: ? (Field type: numeric trait)</li><li><b>Ct_bSTAT1-2</b>: ? (Field type: numeric trait)</li><li><b>Ct_bMAPK-2</b>: ? (Field type: numeric trait)</li></ul></li><li><p><b>Bat data</b> (described in worksheet Bat_data)</p><p>Description: Collection of bat data</p><p>Number of fields: 26</p><p>Number of data rows: 891</p><p>Fields: </p><ul><li><b>Locations</b>: Location of trap (Field type: location)</li><li><b>Capture</b>: Bat ID. Start with year, e.g. 140001 is the first bat caught in 2014. Numbers starting with Q follow Dave Bennett's and Victoria Kemp's consecutive capture numbers, numbers starting without a lettter or with "L" only appear in my dataset. (Field type: id)</li><li><b>Band_number</b>: Ring-Number (Field type: id)</li><li><b>R</b>: Recapture (Field type: categorical)</li><li><b>Date</b>: Date of sampling (Field type: date)</li><li><b>Time</b>: Time of sampling (Field type: time)</li><li><b>Trap</b>: Trap ID (Field type: id)</li><li><b>Species</b>: Species of bat sampled (Field type: taxa)</li><li><b>Sex</b>: Sex of bat (Field type: categorical trait)</li><li><b>Age</b>: Age of bat (A - adult, J - juvenile) (Field type: categorical)</li><li><b>Rep</b>: Reproductive status (L - lactating, PL - postlacting, RPL - recently postlactating, Pr - Pregnant, NR - non reproductive) (Field type: categorical)</li><li><b>Forearm lenght</b>: Forearm length (Field type: numeric trait)</li><li><b>Weight</b>: Biomass of bat (Field type: numeric trait)</li><li><b>Fed</b>: Feeding status (Field type: categorical trait)</li><li><b>O</b>: Oral swab (Field type: numeric trait)</li><li><b>U</b>: Urine swab (Field type: numeric trait)</li><li><b>F</b>: fecal sample (Field type: numeric trait)</li><li><b>FS</b>: fecal swab (Field type: numeric trait)</li><li><b>BS</b>: blood smear (Field type: numeric trait)</li><li><b>B1</b>: blood sample before ACTH injection (Field type: numeric trait)</li><li><b>T1</b>: temperature before ACTH injection (Field type: numeric trait)</li><li><b>B2</b>: blood sample after ACTH injection (Field type: numeric trait)</li><li><b>T2</b>: temperature after ACTH injection (Field type: numeric trait)</li><li><b>Parasites</b>: Parasites present on bat (Field type: comments)</li><li><b>W</b>: Wing punch (Field type: numeric trait)</li><li><b>Comments</b>: Additional comments (Field type: comments)</li></ul></li><li><p><b>Harp_trap</b> (described in worksheet Harp_trap)</p><p>Description: Harp trap data </p><p>Number of fields: 13</p><p>Number of data rows: 322</p><p>Fields: </p><ul><li><b>Date_harp_open</b>: Date that harp trap was open (Field type: date)</li><li><b>Date_harp_closed</b>: Date the harp was closed (Field type: date)</li><li><b>Location</b>: Location of harp trap transect (Field type: location)</li><li><b>Night_number</b>: night number (Field type: id)</li><li><b>Trap_opened</b>: Time trap as opened (Field type: time)</li><li><b>Trap_closed</b>: Time trap was closed (Field type: time)</li><li><b>Trap_hrs</b>: Numbers of hours the trap was open (Field type: numeric)</li><li><b>Trap_nights</b>: Number of nights traps was open (Field type: numeric)</li><li><b>Rain</b>: Rain conditions (Field type: categorical)</li><li><b>Wind</b>: Wind conditions (Field type: categorical)</li><li><b>Moon</b>: Moon conditions (Field type: categorical)</li><li><b>Other</b>: Other notes about the weather conditions (Field type: comments)</li><li><b>Comments</b>: Other comments (Field type: comments)</li></ul></li></ol><p><b>Traps2014.2015.gpx</b></p><p>Description: Trap locations gps locations</p><p><b>Date range: </b>2014-01-31 to 2015-09-04</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> -  -  -  -  Chiroptera <br> -  -  -  -  -  Rhinolophidae <br> -  -  -  -  -  -  <i>Rhinolophus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus acuminatus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus borneensis</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus sedulus</i> <br> -  -  -  -  -  -  -  <i>Rhinolophus trifoliatus</i> <br> -  -  -  -  -  Nycteridae <br> -  -  -  -  -  -  <i>Nycteris</i> <br> -  -  -  -  -  -  -  <i>Nycteris tragata</i> <br> -  -  -  -  -  Hipposideridae <br> -  -  -  -  -  -  <i>Hipposideros</i> <br> -  -  -  -  -  -  -  <i>Hipposideros cervinus</i> <br> -  -  -  -  -  -  -  <i>Hipposideros diadema</i> <br> -  -  -  -  -  -  -  <i>Hipposideros doriae</i> <br> -  -  -  -  -  -  -  <i>Hipposideros dyacorum</i> <br> -  -  -  -  -  -  -  <i>Hipposideros ridleyi</i> <br> -  -  -  -  -  -  -  <i>Hipposideros doriae</i> <br> -  -  -  -  -  Vespertilionidae <br> -  -  -  -  -  -  <i>Hesperoptenus</i> <br> -  -  -  -  -  -  -  <i>Hesperoptenus blanfordi</i> <br> -  -  -  -  -  -  <i>Kerivoula</i> <br> -  -  -  -  -  -  -  <i>Kerivoula hardwickii</i> <br> -  -  -  -  -  -  -  <i>Kerivoula intermedia</i> <br> -  -  -  -  -  -  -  <i>Kerivoula papillosa</i> <br> -  -  -  -  -  -  -  <i>Kerivoula pellucida</i> <br> -  -  -  -  -  -  <i>Myotis</i> <br> -  -  -  -  -  -  -  <i>Myotis muricola</i> <br> -  -  -  -  -  -  <i>Pipistrellus</i> <br> -  -  -  -  -  -  -  <i>Pipistrellus tenuis</i> <br> -  -  -  -  -  -  <i>Phoniscus</i> <br> -  -  -  -  -  -  -  <i>Phoniscus atrox</i> <br> -  -  -  -  -  -  <i>Murina</i> <br> -  -  -  -  -  -  -  <i>Murina aenea</i> <br> -  -  -  -  -  -  -  <i>Murina cyclotis</i> <br> -  -  -  -  -  -  -  <i>Murina suilla</i> <br> -  -  -  -  -  Pteropodidae <br> -  -  -  -  -  -  <i>Cynopterus</i> <br> -  -  -  -  -  -  -  <i>Cynopterus brachyotis</i> <br> -  -  -  -  -  -  <i>Rousettus</i> <br> -  -  -  -  -  -  -  <i>Rousettus spinalatus</i> <br> -  -  -  -  -  -  <i>Balionycteris</i> <br> -  -  -  -  -  -  -  <i>Balionycteris maculata</i> <br> -  -  -  -  -  Emballonuridae <br> -  -  -  -  -  -  <i>Emballonura</i> <br> -  -  -  -  -  -  -  <i>Emballonura alecto</i> <br> -  -  -  -  -  -  -  <i>Emballonura monticola</i> <br></div><p></p>
Data from: A Cretaceous aged Paleotropical dispersal established an endemic lineage of Caribbean praying mantises
Recent phylogenetic advances have uncovered remarkable biogeographic histories that have challenged traditional concepts of dispersal, vicariance and diversification in the Greater Antilles. Much of this focus has centred on vertebrate lineages despite the high diversity and endemism of terrestrial arthropods, which account for 2.5 times the generic endemism of all Antillean plants and non-marine vertebrates combined. In this study, we focus on three Antillean endemic praying mantis genera, Callimantis, Epaphrodita and Gonatista, to determine their phylogenetic placement and geographical origins. Each genus is enigmatic in their relation to other praying mantises due to their morphological affinities with both Neotropical and Old World groups. We recovered the three genera as a monophyletic lineage among Old World groups, which was supported by molecular and morphological evidence. With a divergence at approximately 107 Ma, the lineage originated during the break-up of Gondwana. Ancestral range reconstruction indicates the lineage dispersed from an African + Indomalayan range to the Greater Antilles, with a subsequent extinction in the Old World. The profound ecomorphic convergence with non-Caribbean groups obscured recognition of natural relationships within the same geographical distribution. To the best of our knowledge, the lineage is one of the oldest endemic animal groups in the Greater Antilles and their morphological diversity and restricted distribution mark them as a critical taxon to conserve.
FIGURE 7 in Systematics of Mendoncia (Acanthaceae: Thunbergioideae) in the Paleotropics
FIGURE 7. Map of central Africa showing distributions of Mendoncia combretoides and M. lindaviana.
FIGURE 18 in Systematics of Mendoncia (Acanthaceae: Thunbergioideae) in the Paleotropics
FIGURE 18. Map of central Africa showing distribution of Mendoncia phytocrenoides.
FIGURE 16 in Systematics of Mendoncia (Acanthaceae: Thunbergioideae) in the Paleotropics
FIGURE 16. Map of Madagascar showing distribution of Mendoncia kely.
Fig. 1 in Review Of The Paleotropical Neogastrini Earthworms (Oligochaeta, Acanthodrilidae: Benhamiinae) With Description Of Two New Genera
Fig. 1. Distribution of the Neogastrini genera
Testing the causes of richness patterns in the paleotropics: time and diversification in cycads (Cycadaceae)
<p>The paleotropics harbor many biodiversity hotspots and show many different species richness patterns. However, it remains unclear which factors are the most important in directly shaping richness patterns among regions in the paleotropics (i.e. diversification rates, colonization times, dispersal frequency). Here we used Cycadaceae as a model system to test the causes of regional richness patterns in the paleotropics. Specifically we tested the roles of dispersal frequency, colonization time, diversification rates, and their combined role in explaining richness patterns among regions. We generated a well-sampled, time-calibrated phylogeny and then used this to estimate dispersal events, colonization times, and diversification rates. Richness patterns were significantly associated with the timing of the first colonization of each region, and were best explained by the combined effects of colonization time and diversification rates. The number of dispersal events into each region and the diversification rates of species in each region were not significantly related to richness. Ancestral-area reconstructions showed frequent migrations across Wallace's Line, with a higher diversification rate east of Wallace's Line than west of it. Overall, our study shows that colonization time can be an important factor for explaining regional richness patterns in the paleotropics.</p>
Data from: A Cretaceous aged Paleotropical dispersal established an endemic lineage of Caribbean praying mantises
Open the record for dataset details and reuse information.
Testing the causes of richness patterns in the paleotropics: time and diversification in cycads (Cycadaceae)
Open the record for dataset details and reuse information.
FIGURE 2 in Zalmoxidae (Arachnida: Opiliones: Laniatores) of the Paleotropics: a catalogue of Southeast Asian and Indo-Pacific species
FIGURE 2. Male paratype of Bunofagea gracilipes Lawrence, 1959 (MNHN). Left, lateral view of penis; right, dorsal view of penis. Scale bar = 100 m.
FIGURE 4 in Zalmoxidae (Arachnida: Opiliones: Laniatores) of the Paleotropics: a catalogue of Southeast Asian and Indo-Pacific species
FIGURE 4. Map of the Southwest Pacific showing known localities for Zalmoxidae species. Island groups embellished for clarity.
FIGURE 1 in Zalmoxidae (Arachnida: Opiliones: Laniatores) of the Paleotropics: a catalogue of Southeast Asian and Indo-Pacific species
FIGURE 1. Zalmoxis Sørensen, 1886, (a) Zalmoxis cardwellensis Forster, 1955, male paratype (AMNH); (b) Zalmoxis cf. cuspanalis (MCZ); (c) Zalmoxis darwinensis Goodnight & Goodnight, 1948, male holotype (AMNH); (d) Zalmoxis jewetti (Goodnight & Goodnight, 1947), male holotype (AMNH); (e) Zalmoxis marchei Roewer, 1912, male holotype (MCZ); (f) Zalmoxis mitobatipes (Roewer, 1926), male paratype (MCZ); (g) Zalmoxis neocaledonicus Roewer, 1912, male holotype (MCZ); (h) Zalmoxis remingtoni (Goodnight & Goodnight, 1948), male holotype (AMNH); (i) Zalmoxis tuberculatus Goodnight & Goodnight, 1948, male paratype (AMNH).
FIGURE 3 in Zalmoxidae (Arachnida: Opiliones: Laniatores) of the Paleotropics: a catalogue of Southeast Asian and Indo-Pacific species
FIGURE 3. Map of Southeast Asia showing known localities for Zalmoxidae species. Inset, map of Mascarene Islands showing known localities for Indian Ocean species.
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