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124 results for “terrestrial mammals”
FIGURE 4 in Quantifying vertebrate zoogeographical regions of Australia using geospatial turnover in the species composition of mammals, birds, reptiles and terrestrial amphibians
FIGURE 4. The zoogeographical regions proposed by Cracraft (1991, thick black lines) and superimposed over the three clusters found in this study.
Data from: Environmental factors explain the spatial mismatches between species richness and phylogenetic diversity of terrestrial mammals
Aim: Explore the spatial variation of the relationships between species richness (SR), phylogenetic diversity (PD) and environmental factors to infer the possible mechanisms underlying patterns of diversity in different regions of the globe. Location: Global. Time period: Present day. Major taxa studied: Terrestrial mammals. Methods: We used a hexagonal grid to map SR and PD of mammals and four environmental factors (temperature, productivity, elevation and climate-change velocity since the Last Glacial Maximum). We related those variables through direct and indirect pathways using a novel combination of Path Analysis and Geographically Weighted Regression to account for spatial non-stationarity of path coefficients. Results: SR, PD and environmental factors relate differently across the geographic space, with most relationships varying in both, magnitude and direction. Species richness is associated with lower phylogenetic diversity in much of the tropics and in the Americas, which reflects the tropical origin and the recent diversification of some mammalian clades in these regions. Environmental effects on PD are predominantly mediated by their effects on SR. But once richness is controlled for, the relationships between environmental factors and PD (i.e. PDSR) highlight environmentally driven changes in species composition. Environmental-PDSR relationships suggest that the relative importance of different mechanisms driving biodiversity shifts spatially. Across most of the globe, temperature and productivity are the strongest predictors of richness, while PDSR is best predicted by temperature. Main conclusions: Richness explains most spatial variation in PD, but both dimensions of biodiversity respond differently to environmental conditions across the globe, as indicated by the spatial mismatches in the relationships between environmental factors and these two types of diversity. We show that accounting for spatial non-stationarity and environmental effects on PD while controlling for richness uncovers a more complex scenario of drivers of biodiversity than previously observed.
Data from: Evolution of the MHC-DQB exon 2 in marine and terrestrial mammals
On the basis of a general low polymorphism, several studies suggest that balancing selection in the class II major histocompatibility complex (MHC) is weaker in marine mammals as compared with terrestrial mammals. We investigated such differential selection among Cetacea, Artiodactyla, and Primates at exon 2 of MHC-DQB gene by contrasting indicators of molecular evolution such as occurrence of transpecific polymorphisms, patterns of phylogenetic branch lengths by codon position, rates of nonsynonymous and synonymous substitutions as well as accumulation of variable sites on the sampling of alleles. These indicators were compared between the DQB and the mitochondrial cytochrome b gene (cytb) as a reference of neutral expectations and differences between molecular clocks resulting from life history and historical demography. All indicators showed that the influence of balancing selection on the DQB is more variable and overall weaker for cetaceans. In our sampling, ziphiids, the sperm whale, monodontids and the finless porpoise formed a group with lower DQB polymorphism, while mysticetes exhibited a higher DQB variation similar to that of terrestrial mammals as well as higher occurrence of transpecific polymorphisms. Different dolphins appeared in the two groups. Larger variation of selection on the cetacean DQB could be related to greater stochasticity in their historical demography and thus, to a greater complexity of the general ecology and disease processes of these animals.
Data from: An updated global dataset for diet preferences in terrestrial mammals: testing the validity of extrapolation
1. Diet is a key trait of an organism's life history that influences a broad spectrum of ecological and evolutionary processes. Kissling et al. (2014) compiled a species-specific dataset of diet preferences of mammals for 38% of a total of 5364 terrestrial mammalian species assessed for the International Union for Conservation of Nature's Red List, to facilitate future studies. The authors imputed dietary data for the remaining 62% by using extrapolation from phylogenetic relatives. 2. We collected dietary information for 1261 mammalian species for which data were extrapolated by Kissling et al. (2014), in order to evaluate the success with which such extrapolation can predict true diets. 3. The extrapolation method devised by Kissling et al. (2014) performed well for broad dietary categories (consumers of plants and animals). However, the method performed inconsistently, and sometimes poorly, for finer dietary categories, varying in accuracy in both dietary categories and mammalian orders. 4. The results of the extrapolation performance serve as a cautionary tale. Given the large variation in extrapolation performance, we recommend a more conservative approach for inferring mammalian diets, whereby dietary extrapolation is implemented only when there is a high degree of phylogenetic conservatism for dietary traits. Phylogenetic comparative methods can be used to detect and measure phylogenetic signal in diet. If data for species are needed, then only the broadest feeding categories should be used. This would ensure a greater level of accuracy and provide a more robust dataset for further ecological and evolutionary analysis.
Data from: Random versus game trail-based camera trap placement strategy for monitoring terrestrial mammal communities
Camera trap surveys exclusively targeting features of the landscape that increase the probability of photographing one or several focal species are commonly used to draw inferences on the richness, composition and structure of entire mammal communities. However, these studies ignore expected biases in species detection arising from sampling only a limited set of potential habitat features. In this study, we test the influence of camera trap placement strategy on community-level inferences by carrying out two spatially and temporally concurrent surveys of medium to large terrestrial mammal species within Tanzania's Ruaha National Park, employing either strictly game trail-based or strictly random camera placements. We compared the richness, composition and structure of the two observed communities, and evaluated what makes a species significantly more likely to be caught at trail placements. Observed communities differed marginally in their richness and composition, although differences were more noticeable during the wet season and for low levels of sampling effort. Lognormal models provided the best fit to rank abundance distributions describing the structure of all observed communities, regardless of survey type or season. Despite this, carnivore species were more likely to be detected at trail placements relative to random ones during the dry season, as were larger bodied species during the wet season. Our findings suggest that, given adequate sampling effort (> 1400 camera trap nights), placement strategy is unlikely to affect inferences made at the community level. However, surveys should consider more carefully their choice of placement strategy when targeting specific taxonomic or trophic groups.
Data from: Establishing macroecological trait datasets: digitalization, extrapolation, and validation of diet preferences in terrestrial mammals worldwide
Ecological trait data are essential for understanding the broad-scale distribution of biodiversity and its response to global change. For animals, diet represents a fundamental aspect of species' evolutionary adaptations, ecological and functional roles, and trophic interactions. However, the importance of diet for macroevolutionary and macroecological dynamics remains little explored, partly because of the lack of comprehensive trait datasets. We compiled and evaluated a comprehensive global dataset of diet preferences of mammals ("MammalDIET"). Diet information was digitized from two global and cladewide data sources and errors of data entry by multiple data recorders were assessed. We then developed a hierarchical extrapolation procedure to fill-in diet information for species with missing information. Missing data were extrapolated with information from other taxonomic levels (genus, other species within the same genus, or family) and this extrapolation was subsequently validated both internally (with a jack-knife approach applied to the compiled species-level diet data) and externally (using independent species-level diet information from a comprehensive continentwide data source). Finally, we grouped mammal species into trophic levels and dietary guilds, and their species richness as well as their proportion of total richness were mapped at a global scale for those diet categories with good validation results. The success rate of correctly digitizing data was 94%, indicating that the consistency in data entry among multiple recorders was high. Data sources provided species-level diet information for a total of 2033 species (38% of all 5364 terrestrial mammal species, based on the IUCN taxonomy). For the remaining 3331 species, diet information was mostly extrapolated from genus-level diet information (48% of all terrestrial mammal species), and only rarely from other species within the same genus (6%) or from family level (8%). Internal and external validation showed that: (1) extrapolations were most reliable for primary food items; (2) several diet categories ("Animal," "Mammal," "Invertebrate," "Plant," "Seed," "Fruit," and "Leaf") had high proportions of correctly predicted diet ranks; and (3) the potential of correctly extrapolating specific diet categories varied both within and among clades. Global maps of species richness and proportion showed congruence among trophic levels, but also substantial discrepancies between dietary guilds. MammalDIET provides a comprehensive, unique and freely available dataset on diet preferences for all terrestrial mammals worldwide. It enables broad-scale analyses for specific trophic levels and dietary guilds, and a first assessment of trait conservatism in mammalian diet preferences at a global scale. The digitalization, extrapolation and validation procedures could be transferable to other trait data and taxa.
On the study of fauna (macroinvertebrates, fish, amphibians, reptiles, birds and mammals) of the lower course of Shokhdara river valley in Pamir, Mountain Bodakhshan, Tajikistan.Appendices. Lists of terrestrial vertebrates recorded in the field survey at the Shokhdara and Panj Rivers
<p><strong><span>Appendix</span><span> 1. A list of records of batracho- and herpetofauna in the field survey.<br><span>Appendix 2.</span> List of avifauna of the surveyed region.<br><span>Appendix 3<span> A</span><span> list of mammals recorded in the field survey.</span></span></span></strong></p>
FIGURE 4. Bayesian trees constructed using 16S in Species diversity and phylogeny of fleas of small terrestrial mammals in the forests of the Central Highlands of Madagascar
FIGURE 4. Bayesian trees constructed using 16S (A) and 12S (B) sequences. Values at nodes correspond to the posterior probability values (P) obtained after 100 replicates. P values under 0.7 are not shown. Trees were rooted using sequences of the species Tunga trimamillata, T. penetrans, Hectopsylla cypha and H. pulex. The number of sequences we obtained for each species was given in brackets. Sequences of exotic species (available in our data) such as Xenopsylla brasiliensis and X. cheopis were added.
FIGURE 2 in Species diversity and phylogeny of fleas of small terrestrial mammals in the forests of the Central Highlands of Madagascar
FIGURE 2. Flea species isolated in this study. (a) Centetipsylla madagascariensis, male. (b) C. madagascariensis, female. (c) Synopsyllus fonquerniei, male. (d) S. fonquerniei, female. (e) S. estradei, male. (f) S. estradei, female. (g) S. robici, male. (h) Paractenopsyllus vauceli, male. (i) P. vauceli, female. (j) P. petiti, male. (k) P. petiti, female. (l) P. viettei, male.
FIGURE 3 in Species diversity and phylogeny of fleas of small terrestrial mammals in the forests of the Central Highlands of Madagascar
FIGURE 3. Bayesian trees constructed using COII (A) and ITS2 (B) sequences. Values at nodes correspond to the posterior probability values (P) obtained after 100 replicates. P values under 0.7 are not shown. Trees were rooted using sequences of the species Tunga penetrans, T. trimamillata and Hectopsylla cypha. The number of sequences we obtained for each species was given in brackets. Sequences of exotic species (available in our data) such as Xenopsylla cheopis, X. brasiliensis, Pulex irritans, Peromyscopsylla fallax and one endemic species isolated in other site Synopsyllus girardi were added.
FIGURE 2 in Species diversity and phylogeny of fleas of small terrestrial mammals in the forests of the Central Highlands of Madagascar
FIGURE 2 (continued). Flea species isolated in this study. (m) Paractenopsyllus grandidieri, male. (n) P. grandidieri, female. (o) P. goodmani, male. (p) P. goodmani, female. (q) P. rouxi, male. (r) P. raxworthyi, male. (s) Tsaractenus rodhaini, male. (t) Dinopsyllus brachypecten, male. (u) D. brachypecten, female.
FIGURE 5 in Species diversity and phylogeny of fleas of small terrestrial mammals in the forests of the Central Highlands of Madagascar
FIGURE 5. Maximum parsimonious trees using COII (A), ITS2 (B), 16S (C) and 12S (D) sequences. Values at nodes correspond to the bootstrap values (B) obtained after 100 replicates. B values under 50 are not shown. Trees were rooted using sequences of the species Tunga penetrans, T. trimamillata and Hectopsylla pulex.
Supplementary material 2 from: Bego F, Saçdanaku E, Pacifici M, Rondinini C (2018) Small terrestrial mammals of Albania: distribution and diversity (Mammalia, Eulipotyphla, Rodentia). ZooKeys 742: 127-163. https://doi.org/10.3897/zookeys.742.22364
Table S2. List of species with numbers of records by year of publication and/or year of data collection :
Supplementary material 3 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 3 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 1 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 1 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 2 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 2 from: Taylor PJ, Neef G, Keith M, Weier S, Monadjem A, Parker DM (2018) Tapping into technology and the biodiversity informatics revolution: updated terrestrial mammal list of Angola, with new records from the Okavango Basin. ZooKeys 779: 51-88. https://doi.org/10.3897/zookeys.779.25964
Supplementary material 1 from: Miu IV, Chisamera GB, Popescu VD, Iosif R, Nita A, Manolache S, Gavril VD, Cobzaru I, Rozylowicz L (2018) Conservation priorities for terrestrial mammals in Dobrogea Region, Romania. ZooKeys 792: 133-158. https://doi.org/10.3897/zookeys.792.25314
Publications used to compile distribution of terrestrial mammal species from Dobrogea Region, Romania (field reports and data from museum collections) :
Supplementary material 2 from: Miu IV, Chisamera GB, Popescu VD, Iosif R, Nita A, Manolache S, Gavril VD, Cobzaru I, Rozylowicz L (2018) Conservation priorities for terrestrial mammals in Dobrogea Region, Romania. ZooKeys 792: 133-158. https://doi.org/10.3897/zookeys.792.25314
Occurrences maps for 59 mammal species : Explanation note: The mammal species old (before 1990) and new (after 1990) occurrence records at a 5 × 5 km grid resolution within Dobrogea, Romania.
FIGURE 7 in A review of the biological diversity and distribution of small mammal taxa in the terrestrial ecoregions and protected areas of Nepal 3072
FIGURE 7. Dorsal (a) and ventral (b) views of the skull and lateral views of the skull (c) and mandible (d) of FMNH 114259.
FIGURE 6 in A review of the biological diversity and distribution of small mammal taxa in the terrestrial ecoregions and protected areas of Nepal 3072
FIGURE 6. Lateral outlines of the skulls (from top to bottom) of Myotis sp. (MCZ 32977) from Nepal; M. mystacinus (HZM 25.35972) from Shan State, Myanmar; M. siligorensis (HZM 11.36227) from Meghalaya, India; M. csorbai (HNHM 97.2.4) from 4 km. E. of Syangja, Nepal; and M. muricola (HZM 18.31749) from Pu Mat Reserve, Vietnam.
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.