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26 results for “Peromyscus maniculatus”
Figure 2. A in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 2. A) Phylogenetic tree generated using Bayesian (MrBayes; Huelsenbeck and Ronquist 2001), maximum likelihood (RAxML; Version 8.1.17, Stamatakis 2006), and parsimony methods (PAUP* v. 4.0a165, Swofford 2002) and DNA sequence data from the mitochondrial cytochrome-b gene. The topology depicted is from the Bayesian analysis. Clade probability values (≥ 0.95) for the Bayesian analysis are indicated by an asterisk (*) and are to the left of the first slash, bootstrap values for the maximum likelihood analysis are shown between the two slashes, and bootstrap values obtained from the parsimony analysis are to the right of the last slash. Line at bottom of figure depicts the nucleotide substitution rate per site per million years. B) Same phylogenetic tree as depicted in Figure 2A except unsupported nodes (C, G, and H) were collapsed.
Figure 4. Approximate distributions and associated divergence times for A in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 4. Approximate distributions and associated divergence times for A) Peromyscus maniculatus-like ancestor; B) P. melanotis-like ancestor; C) P. gambelii/keeni/sejugis/sp.-like ancestor; D) P. polionotus-like ancestor; E) P. sonoriensis-like ancestor; F) P. labecula and P. maniculatus - like ancestor; G) P. keeni/sp.-like ancestor; and H) P. keeni-like, P. gambelii-like, P. sejugis-like, and P. sp.-like ancestors. Divergence times were estimated from the BEAST analysis (Version 2.4, Bouckaert et al. 2014) of the mitochondrial cytochrome-b gene dataset (see Fig. 3). Shading schemes that correspond to species distributions are shown in the inset.
Figure 1 in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 1. Distribution of selected populations and species of the Peromyscus maniculatus species group from Canada, Mexico, and the United States. Shaded areas represent distributions of taxa (defined in figure insert) as originally defined by Hall (1981) and modified based on the results of this study. Closed circles represent collecting localities listed in the Appendix; note that multiple individuals may be represented by a single closed circle. White boxes with black stars indicate type localities for each taxon and triangles indicate localities where haplotypes representing P. sonoriensis were found to be in sympatry with samples of P. gambelii and P. labecula, respectively.
Figure 3 in Mitochondrial Dna Sequence Data Indicate Evidence For Multiple Species Within Peromyscus Maniculatus
Figure 3. Time-calibrated ultrametric tree obtained from the BEAST analysis (Version 2.4, Bouckaert et al. 2014) of the mitochondrial cytochrome-b gene dataset. Scale bars at nodes represent the 95% highest posterior densities and numbers associated to each node are the estimated divergence times in million years ago.
Figure 2 in Taxonomy And Phylogenetics Of The Peromyscus Maniculatus Species Group
Figure 2. Maximum parsimony tree derived from sequence variation (ND3/ND4/ND4L) for the northeastern, central and western samples of Peromyscus maniculatus and reference sequences for P. sejugis, P. gambelii, P. keeni, P. polionotus, P. melanotis, and P. leucopus. Numbers associated with the branches are maximum parsimony bootstrap values and Bayesian posterior probabilities. Locality and GenBank references are given in the Materials and Methods.
Effects of X-ray irradiation and housing conditions on mitochondria in Peromyscus maniculatus
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Microscopy images from: A physiological and histological atlas of reproduction in the North American deer mouse (Peromyscus maniculatus)
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Konza Prairie site, station Konza Prairie LTER watershed 001d, study of animal abundance of Peromyscus maniculatus in units of numberPerTransectLinePer4DayTrapSeason on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Konza Prairie (KNZ) contains animal abundance of Peromyscus maniculatus measurements in numberPerTransectLinePer4DayTrapSeason units and were aggregated to a yearly timescale.
Konza Prairie site, station Konza Prairie LTER watershed 004b, study of animal abundance of Peromyscus maniculatus in units of numberPerTransectLinePer4DayTrapSeason on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Konza Prairie (KNZ) contains animal abundance of Peromyscus maniculatus measurements in numberPerTransectLinePer4DayTrapSeason units and were aggregated to a yearly timescale.
Sevilleta site, station Rio Salado Grass Study Site, study of animal abundance of Peromyscus maniculatus in units of numberPerTrappingWeb on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Sevilleta (SEV) contains animal abundance of Peromyscus maniculatus measurements in numberPerTrappingWeb units and were aggregated to a yearly timescale.
Sevilleta site, station Rio Salado Larrea Study Site, study of animal abundance of Peromyscus maniculatus in units of numberPerTrappingWeb on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Sevilleta (SEV) contains animal abundance of Peromyscus maniculatus measurements in numberPerTrappingWeb units and were aggregated to a yearly timescale.
Sevilleta site, station Two-22 Study Site, study of animal abundance of Peromyscus maniculatus in units of numberPerTrappingWeb on a yearly timescale
The EcoTrends project was established in 2004 by Dr. Debra Peters (Jornada Basin LTER, USDA-ARS Jornada Experimental Range) and Dr. Ariel Lugo (Luquillo LTER, USDA-FS Luquillo Experimental Forest) to support the collection and analysis of long-term ecological datasets. The project is a large synthesis effort focused on improving the accessibility and use of long-term data. At present, there are ~50 state and federally funded research sites that are participating and contributing to the EcoTrends project, including all 26 Long-Term Ecological Research (LTER) sites and sites funded by the USDA Agriculture Research Service (ARS), USDA Forest Service, US Department of Energy, US Geological Survey (USGS) and numerous universities. Data from the EcoTrends project are available through an exploratory web portal (http://www.ecotrends.info). This web portal enables the continuation of data compilation and accessibility by users through an interactive web application. Ongoing data compilation is updated through both manual and automatic processing as part of the LTER Provenance Aware Synthesis Tracking Architecture (PASTA). The web portal is a collaboration between the Jornada LTER and the LTER Network Office. The following dataset from Sevilleta (SEV) contains animal abundance of Peromyscus maniculatus measurements in numberPerTrappingWeb units and were aggregated to a yearly timescale.
Data from: Botfly infections impair the aerobic performance and survival of montane populations of deer mice, Peromyscus maniculatus rufinus
1. Elevations >2000 m represent consistently harsh environments for small endotherms because of abiotic stressors such as cold temperatures and hypoxia. 2. These environmental stressors may limit the ability of populations living at these elevations to respond to biotic selection pressures — such as parasites or pathogens — that in other environmental contexts would impose only minimal energetic- and fitness-related costs. 3. We studied deer mice (Peromyscus maniculatus rufinus) living along two elevational transects (2300 – 4400 m) in the Colorado Rockies and found that infection prevalence by botfly larvae (Cuterebridae) declined at higher elevations. We found no evidence of infections at elevations > 2400 m, but that 33.6% of all deer mice, and 52.2% of adults, were infected at elevations < 2400 m. 4. Botfly infections were associated with reductions in hematocrit levels of 23%, hemoglobin concentrations of 27%, and cold-induced VO2max measures of 19% compared to uninfected individuals. In turn, these reductions in aerobic performance appeared to influence fitness, as infected individuals suffered 19-34% higher overwinter mortality. 5. In contrast to studies at lower elevations, we found evidence indicating that botfly infections influence the aerobic capabilities and fitness of deer mice living at elevations between 2000 – 2400 m. Our results therefore suggest that the interaction between botflies and small rodents is likely highly context-dependent and that, more generally, high-elevation populations may be susceptible to additional biotic selection pressures.
Data from: Microsatellite genetic structure and cytonuclear discordance in naturally fragmented populations of deer mice (Peromyscus maniculatus)
The Great Lakes impose high levels of natural fragmentation on local populations of terrestrial animals in a way rarely found within continental ecosystems. Although separated by major water barriers, woodland deer mouse (Peromyscus maniculatus gracilis) populations on the islands and on the Upper Peninsula (UP) and Lower Peninsula (LP) of Michigan have previously been shown to have a mitochondrial DNA contact zone that is incongruent with the regional landscape. We analyzed 11 microsatellite loci for 16 populations of P. m. gracilis distributed across 2 peninsulas and 6 islands in northern Michigan to address the relative importance of geographical structure and inferred postglacial colonization patterns in determining the nuclear genetic structure of this species. Results showed relatively high levels of genetic structure for this species and a significant correlation between interpopulation differentiation and separation by water but little genetic structure and no isolation-by-distance within each of the 2 peninsulas. Genetic diversity was generally high on both peninsulas but lower and correlated to island size in the Beaver Island Archipelago. These results are consistent with the genetic and demographic isolation of Lower Peninsula populations, which is a matter of concern given the dramatic decline in P. m. gracilis abundance on the Lower Peninsula in recent years.
On following pages: 248. Merriam''s Deermouse (Peromyscus merriami); 249. Cactus Deermouse (Peromyscus eremicus); 250. San Lorenzo Deermouse (Peromyscus interparietalis); 251. Southern Baja Deermouse (Peromyscus eva); 252. Northern Baja Deermouse (Peromyscus fraterculus); 253. Monserrat Island Deermouse (Peromyscus caniceps); 254. Dickey's Deermouse (Peromyscus dickeyi); 255. La Guarda Deermouse (Peromyscus guardia); 256. Coronados Deermouse (Peromyscus pseudocrinitus); 257. Cotton Deermouse (Peromyscus gossypinus); 258. White-footed Deermouse (Peromyscus leucopus); 259. Santa Cruz Deermouse (Peromyscus sejugis); 260. North-western Deermouse (Peromyscus keeni): 261. Oldfield Deermouse (Peromyscus polionotus); 262. North American Deermouse (Peromyscus maniculatus); 263. Black-eared Deermouse (Peromyscus melanotis); 264. Black-tailed Deermouse (Peromyscus melanurus); 265. Broad-faced Deermouse (Peromyscus megalops); 266. Black-wristed Deermouse (Peromyscus melanocarpus); 267. Catalina Deermouse (Peromyscus slevini); 268. Tawny Deermouse (Peromyscus perfulvus); 269. Plateau Deermouse (Peromyscus melanophrys); 270. Puebla Deermouse (Peromyscus mekisturus); 271. Mayan Deermouse (Peromyscus mayensis); 272. Stirton's Deermouse (Peromyscus stirtoni); 273. Yucatan Deermouse (Peromyscus yucatanicus); 274. Chimoxan Deermouse (Peromyscus tropicalis); 275. Talamancan Deermouse (Peromyscus nudipes); 276. Mexican Deermouse (Peromyscus mexicanus); 277. Naked-eared Deermouse (Peromyscus gymnotis); 278. Chiapan Deermouse (Peromyscus zarhynchus); 279. Gardner's Deermouse (Peromyscus gardneri); 280. Nicaraguan Deermouse (Peromyscus nicaraguae); 281. Salvadorean Deermouse (Peromyscus salvadorensis); 282. Guatemalan Deermouse (Peromyscus guatemalensis); 283. Large Deermouse (Peromyscus grandis). in Cricetidae
On following pages: 248. Merriam''s Deermouse (Peromyscus merriami); 249. Cactus Deermouse (Peromyscus eremicus); 250. San Lorenzo Deermouse (Peromyscus interparietalis); 251. Southern Baja Deermouse (Peromyscus eva); 252. Northern Baja Deermouse (Peromyscus fraterculus); 253. Monserrat Island Deermouse (Peromyscus caniceps); 254. Dickey's Deermouse (Peromyscus dickeyi); 255. La Guarda Deermouse (Peromyscus guardia); 256. Coronados Deermouse (Peromyscus pseudocrinitus); 257. Cotton Deermouse (Peromyscus gossypinus); 258. White-footed Deermouse (Peromyscus leucopus); 259. Santa Cruz Deermouse (Peromyscus sejugis); 260. North-western Deermouse (Peromyscus keeni): 261. Oldfield Deermouse (Peromyscus polionotus); 262. North American Deermouse (Peromyscus maniculatus); 263. Black-eared Deermouse (Peromyscus melanotis); 264. Black-tailed Deermouse (Peromyscus melanurus); 265. Broad-faced Deermouse (Peromyscus megalops); 266. Black-wristed Deermouse (Peromyscus melanocarpus); 267. Catalina Deermouse (Peromyscus slevini); 268. Tawny Deermouse (Peromyscus perfulvus); 269. Plateau Deermouse (Peromyscus melanophrys); 270. Puebla Deermouse (Peromyscus mekisturus); 271. Mayan Deermouse (Peromyscus mayensis); 272. Stirton's Deermouse (Peromyscus stirtoni); 273. Yucatan Deermouse (Peromyscus yucatanicus); 274. Chimoxan Deermouse (Peromyscus tropicalis); 275. Talamancan Deermouse (Peromyscus nudipes); 276. Mexican Deermouse (Peromyscus mexicanus); 277. Naked-eared Deermouse (Peromyscus gymnotis); 278. Chiapan Deermouse (Peromyscus zarhynchus); 279. Gardner's Deermouse (Peromyscus gardneri); 280. Nicaraguan Deermouse (Peromyscus nicaraguae); 281. Salvadorean Deermouse (Peromyscus salvadorensis); 282. Guatemalan Deermouse (Peromyscus guatemalensis); 283. Large Deermouse (Peromyscus grandis).
Data from: Botfly infections impair the aerobic performance and survival of montane populations of deer mice, Peromyscus maniculatus rufinus
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Body size trends in response to climate and urbanization in the widespread North American deer mouse, Peromyscus maniculatus
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Data from: Microsatellite genetic structure and cytonuclear discordance in naturally fragmented populations of deer mice (Peromyscus maniculatus)
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Data from: Development of homeothermic endothermy is delayed in high altitude native deer mice (Peromyscus maniculatus)
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Figure 1 in Taxonomy And Phylogenetics Of The Peromyscus Maniculatus Species Group
Figure 1. Map of the general distributions of species in the P. maniculatus group as discussed and recognized herein. Peomyscus sejugis is restricted to Isla Santa Cruz and Isla San Diego in the Gulf of California and is not figured. Numbers in parentheses refer to the DNA clades as designated by Dragoo et al. (2006), and cross hatching indicates distributional overlap of P. melanotis and P. labecula. The general distributions of species were determined by plotting the geographically marginal specimens reported in the following papers: Bowers et al. (1973), Allard and Greenbaum (1988), Hogan et al. (1993), Wike (1998), Zheng et al. (2003), Lucid and Cook (2004), Dragoo et al. (2006), Walker et al. (2006), Lucid and Cook (2007), Gering et al. (2009), Yang and Kenagy (2011), Domingues et al. (2012), Kalkvik et al. (2012), Natarajan et al. (2015), Greenbaum et al. (2017), Kingsley et al. (2017), Sawyer et al. (2017), and Kalkvik et al. (2018).
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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.