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19,493 results for “Populism”
Figure 7 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 7. Monthly distribution of individuals of Macrobrachium iheringi (Ortmann, 1897) by size classes, captured from July 1991 to June 1992.
Figure 5 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 5. Estimation of the size at onset of morphological sexual maturity of Macrobrachium iheringi (Ortmann, 1897) females. The estimated size is the carapace length (CL) of the smallest adult individual, obtained after the distinction of juvenile (open circles) and adult (black circles) equations. PW = pleura width, AL = abdomen length, IL = ischium length, ML = merus length, CrL = carpus length, PpL = propodus length, DcL = dactyl length and PpH = propodus height.
Figure 4 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 4. Estimation of the size at onset of morphological sexual maturity of Macrobrachium iheringi (Ortmann, 1897) males. The estimated size is the carapace length (CL) of the smallest adult individual, obtained after the distinction of juvenile (open circles) and adult (black circles) equations. PW = pleura width, AL = abdomen length, IL = ischium length, ML = merus length, CrL = carpus length, PpL = propodus length, DcL = dactyl length and PpH = propodus height.
Figure 3 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 3. Monthly variation of water temperature and pluviosity during the two sampling periods, July 1991 to June 1992 and July 1993 to June 1994, in Botucatu, state of São Paulo, Brazil.
Figure 2 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 2. Measurements taken from each specimen of Macrobrachium iheringi (Ortmann, 1897) (CL = carapace length, PW = pleura width, AL = abdomen length. IL = ischium length, ML = merus length, CrL = carpus length, PpL = propodus length, DcL = dactyl length and PpH = propodus height).
Figure 1 in Relative growth and population dynamics of Macrobrachium iheringi (Decapoda, Palaemonidae)
Figure 1. Map showing the sampling site, Ribeirão da Hortelã (22°57'S and 48°26'W), in Botucatu, São Paulo.
APOE4 is associated with elevated blood lipids and lower levels of innate immune biomarkers in a tropical Amerindian subsistence population
<p>In post-industrial settings, <i>APOE4</i> is associated with increased cardiovascular and neurological disease risk. However, the majority of human evolutionary history occurred in environments with higher pathogenic diversity and low cardiovascular risk. We hypothesize that in high-pathogen and energy-limited contexts, the <i>APOE4</i> allele confers benefits by reducing innate inflammation when uninfected, while maintaining higher lipid levels that buffer costs of immune activation during infection. Among Tsimane forager-farmers of Bolivia (N=1266), <i>APOE4</i> is associated with 30% lower C-reactive protein, and higher total cholesterol and oxidized-LDL. Blood lipids were either not associated, or negatively associated with inflammatory biomarkers, except for associations of oxidized-LDL and inflammation which were limited to high BMI adults. Further, <i>APOE4</i> carriers maintain higher levels of total and LDL cholesterol at low BMIs. These results suggest the relationship between <i>APOE4</i> and lipids may be beneficial for pathogen-driven immune responses, and unlikely to increase cardiovascular risk in an active subsistence population.</p>
Tables and Appendix indicate population density and distribution of Cheer Pheasant (Catreus wallichii) in different localities of AJ&K
<p><strong>Table 5 </strong>Population density (per sq. km.) of Cheer Pheasant <em>(Catreus wallichii) </em>in different localities of AJ&K.</p> <p><strong>Table 6 </strong>Population density (per sq. km.) of Cheer Pheasant <em>(Catreus wallichii) </em>in different sub-localities of AJ&K.</p> <p><strong>Table 7 </strong>Population density (per sq. km.) of Cheer Pheasant <em>(Catreus wallichii) </em>across the months in AJ&K.</p> <p><strong>Appendix-I </strong>Distribution and Population density of Cheer Pheasant (<em>Catreus wallichi</em>) in Jhelum Velley, AJ&K.</p> <p><strong>Appendix-II </strong>Distribution and Population density of Cheer Pheasant (<em>Catreus wallichii</em>) at Machiara National Park, Muzaffarabad AJ&K.</p> <p><strong>Appendix-III </strong>Distribution and Population density of Cheer Pheasant (<em>Catreus wallichii</em>) at Phalla Game Reserve, Haveli, AJ&K.</p> <p><strong>Appendix-IV </strong>Distribution and Population density of Cheer Pheasant (<em>Catreus wallichii</em>) at Nar Sher Ali Khan, Bagh, Azad Jammu & Kashmir.</p> <p> </p> <p> </p>
Identifying priority giant anteater (Myrmecophaga tridactyla) populations for conservation in São Paulo State, Brazil
<p>Habitat loss is the main threat to biodiversity conservation worldwide. Some species may be particularly susceptible to the effects of fragmentation and the isolation of populations. The impacts of human activity on wild animal populations may be understood through relationships between individual genetic data and spatial landscape variables, particularly when considering local population dynamics influenced by fragmented habitats. Thus, the objective of this study was to analyze the population structure and genetic diversity of the giant anteater (<i>Myrmecophaga tridactyla</i>) using an individual sampling scheme (ISS) on a regional geographic scale. Data were collected from 41 specimens from twenty different locations in São Paulo State, Brazil, and six polymorphic microsatellite loci were genotyped. Our results indicate that barriers to gene flow exist and have segregated individuals of the farther away areas into two spatially structured clusters. The populations were also found to have high genetic diversity. The experimental sampling approach used herein enabled an analysis of the population dynamics of the giant anteater on a regional scale, as well as the identification of priority populations for genetic resource conservation for this species. The results reflect the need for adequate management plans. The efficacy of the sampling scheme may vary based on the study model used, but we argue that the use of an ISS combined with suitable molecular markers and statistical methods may serve as an important tool for initial analyses of threatened or vulnerable species, particularly in anthropized regions where species populations are small or hard to characterize.</p>
Fig. 1 in Population size, distribution and daylight behaviour of Irrawaddy dolphins (Orcaella brevirostris) in Penang Island, Malaysia
Fig. 1. Penang Island. Shown are the survey trackline west of island and fishing villages.
Fig. 2 in Estimating Population Size And Distribution Of Hume'S Pheasant In Northern Thailand
Fig. 2. Predicted habitat of Hume's Pheasant in northern Thailand.
Fig. 1 in Assessing the distribution, roosting site characteristics, and population of Pteropus lylei in Thailand
Fig. 1. Study area and location of Pteropus lylei roosts in Thailand.
Fig. 4 in A Mark-Recapture Study Of A Dog-Faced Water Snake Cerberus Schneiderii (Colubridae: Homalopsidae) Population In Sungei Buloh Wetland Reserve, Singapore
Fig. 4. Percentage frequency distribution of snout-vent length (SVL) of Cerberus schneiderii.
Fig. 1 in Low Genetic Variability In The Recovering Urban Banded Leaf Monkey Population Of Singapore
Fig. 1. Distribution of Presbytis femoralis.
Fig. 35 in Hybridization Among Western Whiptail Lizards (Cnemidophorus Tigris) In Southwestern New Mexico: Population Genetics, Morphology, And Ecology In Three Contact Zones
Fig. 35. Ventral views of the same lizards arranged in the same sequence as in figure 34.
Fig. 3. The contact region. Numbers designate collecting sites. Compare with figure 49 in Hybridization Among Western Whiptail Lizards (Cnemidophorus Tigris) In Southwestern New Mexico: Population Genetics, Morphology, And Ecology In Three Contact Zones
Fig. 3. The contact region. Numbers designate collecting sites. Compare with figure 49.
Figure 4 in Population genetic structure and demographic history of the Chinese endemic Mongoloniscus sinensis (Dollfus, 1901) (Isopoda: Oniscidea)
Figure 4. Pairwise mismatch distributions for six derived clades.
Figure 1 in Genetic diversity, population structure and demographic history of Dugesia japonica in Taihang Mountains
Figure 1. Geographical distribution of Dugesia japonica populations sampled in Taihang Mountains.
Fig. 3 in Population size, demography and diet of the Siamese crocodile, Crocodylus siamensis (Schneider, 1801) in the Mesangat Swamp in Kalimantan, Indonesia
Fig. 3. Correlation between total Crocodylus siamensis sightings and moon index.
Fig. 8 in Developmental Abnormalities in Wild Populations of Birds: Examples from Lesser Snow Geese (Chen caerulescens caerulescens)
Fig. 8. Asymmetrically reduced lower mandible of specimen LPB006.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.