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502 results for “small mammals”
CSM09 Small mammal host-parasite sampling data associated with the Consume herbivore exclusion plots across two burned and native-grazed watersheds at Konza Prairie
Data set contains summaries of the number of individuals of each species of small mammal captured (relative abundance) on each trapping grid. Each record contains date, treatment, grid, trap station, species, specimen number, recapture status, specimen disposition, external body measurements (where applicable), reproductive information, and miscellaneous associated comments. These sampling records are based on nightly captures during one 4-night trapping period in fall (October concurrent with annual bison roundup activites) for each of 4 permanent trapping grids established on two fire/grazing treatments (two grids per treatment). These treatments are both grazed by native grazers (bison) and include one treatment burned annually (N1A) and one treatment burned every 4 years (N4B). In each treatment, sampling grids are arranged as 5 x 10 permanent stakes spaced 10m apart and labeled numerically between 1-50 for grid A and 51-100 for grid B. One grid per treatment (grid A) is sampled using capture-mark-release methods and the other grid in each treatment (grid B) is sampled using specimen removal and subsequent whole body processing and curation.
Small mammal disturbance data for Martinelli slope, 1989 - 1992.
Permanent plots were established on the Martinelli slope in 1987. The 25 plots are organized in a Latin square design consisting of 5 rows and 5 columns. Plots are numbered according to row and column, beginning with 11 at the northwest corner of the grid. Plot 55 is located at the southeast corner of the grid. Each plot has dimensions of 1.5 m x 2.0 m. The corners of each plot are marked with rebar stakes. Each plot is divided into an evenly spaced grid consisting of 15 x 20 points on each side, for a total of 300 points, with each point situated 10 cm from its nearest neighbors. Small mammal disturbances were classified each year at each point where such disturbances occurred. The point-quadrat method used was similar to that described by Auerbach (1992): The point-quadrat method was used for estimating canopy stratification and plant cover. Aluminum point-quadrat frames were 3m^2 in size, with double-layer filament spaced 10 cm apart to make a 145 x 195 cm grid for a total of 300 sample points per plot. If small mammal disturbances were present at a point, those disturbances were classified as indicated in the comments section.
Figures 9–10 in Studies on palearctic Onthophagus associated with burrows of small mammals. IV. A new Iranian species belonging to the furciceps group (Coleoptera, Scarabaeidae, Onthophagini)
Figures 9–10. Onthophagus (Paleonthophagus) psychopompus sp. n. Male, paratype (Iran, Sirdan, Qazvin prov.) and female, paratype (Iran, Saqqez, Kordestan prov.). 9 Dorsum of male 10 Dorsum of female. Photos by A. Ballerio, scanned by G. Fiumi.
Figures 1–7 in Studies on palearctic Onthophagus associated with burrows of small mammals. IV. A new Iranian species belonging to the furciceps group (Coleoptera, Scarabaeidae, Onthophagini)
Figures 1–7. Onthophagus (Paleonthophagus) psychopompus sp. n. Male, holotype, and female, allotype (Iran, Hashtgerd, Tehran prov.). 1 Male: head and pronotum, dorsal view 2 Male: head, frontal view 3 Female: head and pronotum, dorsal view 4 Female: head, frontal view 5 Parameres, lateral view 6 Parameres, dorsal view 7 Lamella copulatrix, ventral side. Drawings by I. Gudenzi.
Application of LiDAR to assess the habitat selection of an endangered small mammal in an estuarine wetland environment
<p>Light detection and ranging (lidar) has emerged as a valuable tool for examining the fine-scale characteristics of vegetation. However, lidar is rarely used to examine coastal wetland vegetation or the habitat selection of small mammals. Extensive anthropogenic modification has threatened the endemic species in the estuarine wetlands of the California coast, such as the endangered salt marsh harvest mouse (<em>Reithrodontomys raviventris</em>; SMHM). A better understanding of SMHM habitat selection could help managers better protect this species. We assessed the ability of airborne topographic lidar imagery in measuring the vegetation structure of SMHM habitats in a coastal wetland with a narrow range of vegetation heights. We also aimed to better understand the role of vegetation structure in habitat selection at different spatial scales. Habitat selection was modeled from data compiled from 15 small mammal trapping grids collected in the highly urbanized San Francisco Estuary in California, USA. Analyses were conducted at three spatial scales: microhabitat (25 m<sup>2</sup>), mesohabitat (2,025 m<sup>2</sup>), and macrohabitat (10,000 m<sup>2</sup>). A suite of structural covariates was derived from raw lidar data to examine vegetation complexity. We found that adding structural covariates to conventional habitat selection variables significantly improved our models. At the microhabitat scale in managed wetlands, SMHM preferred areas with denser and shorter vegetation, and selected for proximity to levees and taller vegetation in tidal wetlands. At the mesohabitat scale, SMHM were associated with a lower percentage of bare ground and with pickleweed (<em>Salicornia pacifica</em>) presence. All covariates were insignificant at the macrohabitat scale.<em> </em>Our results suggest that SMHM preferentially selected microhabitats with access to tidal refugia and mesohabitats with consistent food sources. Our findings showed that lidar can contribute to improving our understanding of habitat selection of wildlife in coastal wetlands and help to guide future conservation of an endangered species.</p>
High-precision body mass estimators for small mammals: A case study in the Mesozoic
<p>Body mass is a pivotal quantity in palaeobiology but must be estimated from an imperfect fossil record. We analyse the precision of skeletal predictors of mammalian body mass as a mean to inform the Mesozoic mammal record, including a new eutriconodont from North America. We focus on the critical small end of the size spectrum – critical because the earliest mammals were small, because small size persisted onto the stems of the major extant radiations, and because small mammals compose a large proportion of crown diversity. Linear regressions based on extant small mammals indicate a universal correlation of body mass with observed measurements, but with clear differences in precision. Postcranial predictors outperform jaw and dental metrics, with certain femoral joint dimensions providing surprisingly precise estimations. Overall, our data indicate small-mammal evolution during the Mesozoic unfolded in patterns of underappreciated complexity. Studying these dynamics is only possible when estimating body mass within a strict, highly focused phylogenetic context. The heuristic value of the estimators we provide here are not limited to the Mesozoic but are phylogenetically justified for any small-bodied mammal regardless of age.</p>
MicromAsia: small mammal surveys in Western China and Kyrgyzstan (1994-2014)
<p>This dataset corresponds to surveys carried out in Asia (western China and Kyrgyzstan) between May 1994 and August 2014 as part of the research expeditions of Patrick Giraudoux and his team. It includes:</p> <ul> <li>Traplines set up and small mammal captured. The corresponding collection of skulls, specimens and tissues has been donated to the <em>Museum National d'Histoire Naturelle</em>, Paris since the 22nd of November 2022.</li> <li>Activity index transect walked to provide abundance estimates over a larger range than possible using trapping methods</li> <li>Miscellaneous supplementary files and trapline photos.</li> </ul> <p><strong>Main files</strong></p> <p><a href="https://zenodo.org/record/7614879/files/Traplines.txt?download=1">Traplines.txt </a> <a href="https://zenodo.org/api/files/17e03137-dc8a-4b79-bd1c-4a9752fe0a9d/Traplines.txt"> </a><br>This file is a table that describes the 787 traplines or trap clusters or circumstances by which small mammal specimens have been captured. Some traplines can have no capture. This is a point to consider when trapping success is computed joining the trapline table to the capture table. Those two tables can be joined using the field 'idLine'. For more details about sampling design, trap types, distance between two traps, etc. please refer to the articles published using those data (see references on this web page).</p> <ul> <li>nameStudysite, name of the survey site</li> <li>country, country ISO code</li> <li>countryName, country name</li> <li>province, province name</li> <li>idLine, trapline ID code: digits #1-2 location ID, digits #3-4 year, digits #5-6 month, digits #7-8 line number. The two latter digits can be coded on numbers 01, 02, 03... or on letters AA, AB, AC,...</li> <li>sLongitude, longitude of the trapline beginning (for surveys carried out before 1998 included, GPS receivers were not available: geographical coordinates are those of the nearest village, whose name is given in the field 'nameStudysite', and the position of trapline is given relative to this village (see field 'emplacementMethod' = CoordCloserVillage and 'distVillage' and 'azimuthVillage')</li> <li>sLatitude, latitude of the trapline beginning (for surveys carried out before 1998 included, GPS receivers were not available: geographical coordinates are those of the nearest village, whose name is given in the field 'nameStudysite', and the position of trapline is given relative to this village (see field 'emplacementMethod' = CoordCloserVillage and 'distVillage' and 'azimuthVillage')</li> <li>eLongitude, longitude of the trapline end</li> <li>eLatitude, latitude of the trapline beginning</li> <li>cLongitude, longitude of the trapline centroid (for surveys carried out before 1998 included, GPS receivers were not available: geographical coordinates are those of the nearest village, whose name is given in the field 'nameStudysite', and the position of trapline is given relative to this village (see field 'emplacementMethod' = CoordCloserVillage and 'distVillage' and 'azimuthVillage')</li> <li>cLatitude, latitude of the trapline beginning (for surveys carried out before 1998 included, GPS receivers were not available: geographical coordinates are those of the nearest village, whose name is given in the field 'nameStudysite', and the position of trapline is given relative to this village (see field 'emplacementMethod' = CoordCloserVillage and 'distVillage' and 'azimuthVillage')</li> <li>altitude, altitude</li> <li>emplacementMethod, way location is recorded: CoordCloserVillage, distance and direction of the nearest village (used on a time when GPS receivers were nor available); GPS, geographical coordinates; unknown</li> <li>distVillage, distance to the nearest village (in m)</li> <li>azimuthVillage, bearing direction to the nearest village</li> <li>habitat, habitat description</li> <li>campagneObs, month and year of the survey</li> <li>campagneObsBegin, date of the beginning of the survey</li> <li>campagneObsEnd, date of the end of the survey</li> <li>traptype, trap type (see e.g. <a href="https://zenodo.org/record/7614879/files/Traptypes.pdf?download=1">Traptypes.pdf</a> for some illustrations): <ul> <li>INRA, INRA trap</li> <li>sbbt, small break back trap</li> <li>apporté, brought by people</li> <li>apporté (?), possibly brought by people</li> <li>BBBT, big break back trap</li> <li>sSherman, small Sherman trap</li> <li>BSHERMAN, big Sherman trap</li> <li>CAGE, cage trape</li> <li>tong, tong trap</li> <li>attrapé à la main, caught by hand</li> <li>road, found dead along a road</li> <li>trouvés, found</li> <li>assommoir, deadfall trap</li> <li>tong trap, tong trap</li> <li>bbbt, small break back trap</li> <li>child, brought by a child</li> <li>collet, snare</li> <li>BBBT ou jaw, big break back trap or jaw trap</li> <li>jaw, jaw trap</li> </ul> </li> <li>remarks, remarks</li> <li>nbControlNights, number of control nights (traps were set up during the day and controlled every morning)</li> <li>nbTrapsInstal1, number of traps set up</li> <li>nbTrapsRecov1, number of traps recovered on first control</li> <li>nbTrapsRecov2, number of traps recovered on control #2</li> <li>nbTrapsRecov3, number of traps recovered on control #3</li> <li>nbTrapsRecov4, number of traps recovered on control #4</li> <li>nbTrapsRecov5, number of traps recovered on control #5</li> </ul> <p><a href="https://zenodo.org/records/14246016/files/capturesV2.txt?download=1">CapturesV2.txt</a></p> <p>This file is a table that describes the 2178 animals captured. As a table, it can be joined to the trapline table using the field 'idLine'. Animals with an idMNHN have had their skulls and sometimes other body parts deposited at the <em>Museum National d'Histoire Naturelle</em> in Paris.</p> <ul> <li>country, country ISO code</li> <li>idCapture, Capture ID code: digits #1-8 trapline ID, see field 'idLine' of <a href="https://zenodo.org/record/7614879/files/Traplines.txt?download=1">Traplines.txt</a> for details, digits #9-10 capture ID in the trapline</li> <li>numControlNight, number of the control night</li> <li>dateControlNight, date of the control night</li> <li>labCode, code for the laboratory</li> <li>speciesField, species as identified in the field; for abbreviations see <a href="https://zenodo.org/record/7614879/files/SpeciesNames.txt?download=1">SpeciesNames.txt </a></li> <li>species, species as confirmed in the lab</li> <li>sex, M male; F female.</li> <li>reproducing T true; F False</li> <li>remarks</li> <li>HeadBodyLength, head-body length</li> <li>UterusDiameter (mm)</li> <li>WholeBodyWetmass, body mass (g)</li> <li>EarLength (mm)</li> <li>ToesForelegNb, number of toes (foreleg)</li> <li>ToesHindlegNb, number of toes (hintleg)</li> <li>ClawLength (mm)</li> <li>TailLength (mm)</li> <li>TailQuiffLength (mm)</li> <li>HindFootLength (mm)</li> <li>CristallineLensNb, number of crystalline lens weighed (sometimes only one could be taken)</li> <li>CristallineLensDrymass, dry mass of the crystalline lens weighed (one or two together according to 'CristallineLensNb'</li> <li>TesticleLength (mm)</li> <li>TesticleWidth (mm)</li> <li>SeminalVesicleLength (mm)</li> <li>SeminalVesicleWidth (mm)</li> <li>PlacentaScarsNb, number of placental scares</li> <li>EmbryosNb, number of embryos</li> <li>idLine, ID of the trapline where the animal was caught</li> <li>idMNHN, MNHN ID</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/Parasites.txt?download=1">Parasites.txt </a></p> <p>Livers and general cavity were generally examined visually to identify macroparasites such as cestode kysts or nematodes with a particular attention for <em>Echinococcus multilocularis</em> metacestodes. Additionnal informations on parasites might have been reported in the field 'remarks' of <a href="https://zenodo.org/record/7614879/files/Captures.txt?download=1">Captures.txt</a>. As a table, it can be joined to the capture table using the field 'idCapture'</p> <ul> <li>country, country ISO code</li> <li>idCapture, Capture ID code see field idCapture of <a href="https://zenodo.org/record/7614879/files/Captures.txt?download=1">Captures.txt</a><a href="https://zenodo.org/api/files/17e03137-dc8a-4b79-bd1c-4a9752fe0a9d/Captures.txt"> </a></li> <li>species, parasite species name: "?" or "99" = unknown (generally a small unidentifiable white dot); "CH" = Capillaria hepatica (sometimes in full "Capillaria hepatica"); "Em" = Echinococcus multilocularis (sometimes in full "Echinococcus multilocularis"); "Taenia" ; "Taenia crassiceps"; "Taenia taeniformis"</li> <li>number</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/Transects.zip?download=1">Transects.zip </a></p> <p>Transects were used to sample open habitats such as grassland, arable fields etc., for species that leave conspicuous activity indices on the ground surface, in order to provide abundance estimates over a larger range than possible using trapping methods. For each transect, 10 paces intervals were surveyed with activity indicators identifiable to species or genus level (including foraging corridors, ground holes, earth tumuli and small mammal faeces) recorded. Except for Sary Mogol, Kyrgyzstan, where transect were walked on twenty 10-paces intervals centred on the nodes of a grid, transect routes were selected opportunistically under accessibility constraints in order to cross the largest portion of each habitat patch. They were recorded via Global Positioning System receivers with an approximate 15 m accuracy. The zip file includes the followings:</p> <ul> <li>Transect file descriptions.rtf, the description of the fields of each transect table</li> <li>Transects_Honlong_2007_09.txt, transects walked near HongLong, China, in September 2007</li> <li>Transects_Narati_2006_09.txt, transects walked near Narati, China, in September 2006</li> <li>Transects_Ningxia_2003_09.txt, transects walked in Ningxia, China, in September 2003</li> <li>Transects_SaryMoghul_2012_2014.txt, transects walked near Sary Moghul, Kyrgyzstan, in May 2012 and August 2014</li> <li>Transects_Serxu_2002_07.txt, transects walked near Serxu, China, in July 2002</li> <li>Transects_Tuotuohe_2006_07.txt, transects walked on the way from Xining to Tuotuo He, China, in July 2006</li> </ul> <p><strong>Supplementary files</strong></p> <p><a href="https://zenodo.org/record/7614879/files/1MapStudyAreas.jpg?download=1">1MapStudyAreas.jpg</a> Map of the main areas surveyed</p> <p><a href="https://zenodo.org/record/7614879/files/DNA_sequencing.txt?download=1">DNA_sequencing.txt </a>table of the specimens whose DNA has been sequenced</p> <ul> <li>ind_number, Capture ID code: see field 'idCapture' in <a href="https://zenodo.org/record/7614879/files/Captures.txt?download=1">Captures.txt </a></li> <li>ID_lab, lab identification label</li> <li>Species_DNA, species as identified by DNA sequencing</li> <li>laboratory, people and/or lab who performed the analysis</li> <li>ID morphometry/karyotype, species as identified by morphology + karyotype</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/Photos_traplines.zip?download=1">Photos_traplines.zip</a> Photos of traplines and habitats for the following surveys</p> <ul> <li>Honglong, CN, September 2007</li> <li>Maerkang, CN, September 2005</li> <li>Narati, CN, September 2006</li> <li>Ningxia, CN, September 2003, July 2012</li> <li>Rantang, CN, June 2004</li> <li>Sary Mogol, KG, April 2008</li> <li>Serxu, CN, July 2002</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/SpeciesNames.txt?download=1">SpeciesNames.txt</a> Abbreviations, latin, English, French names of species</p> <ul> <li>Code, code on 4 digits</li> <li>Nom latin, latin name</li> <li>Nom commun (Anglais), common name (English)</li> <li>Nom commun (Français), common name (French)</li> <li>Remark</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/Small_mammal_measurements.pdf?download=1">Small_mammal_measurements.pdf</a> Method for small mammal sampling and measurements.</p> <p><a href="https://zenodo.org/record/7614879/files/TrapLocationCodes.txt?download=1">TrapLocationCodes.txt</a> Codes for the location of traplines</p> <ul> <li>Location, location name</li> <li>Symbol, symbol (first two digits of idLine in <a href="https://zenodo.org/record/7614879/files/Traplines.txt?download=1">Traplines.txt </a></li> <li>Province, province name</li> <li>Trapping, remarks about sampling design</li> </ul> <p><a href="https://zenodo.org/record/7614879/files/Traptypes.pdf?download=1">Traptypes.pdf</a> Samples of small and big break back traps, tong trap and INRA trap.<br> </p>
Small mammal ARTS: Orion receiver data for site radiomapping and vole tracking, and scripts and results for localization and activity estimates
<p class="FirstParagraph">This data set accompanies "An Automated Radio-Telemetry System (ARTS) for Monitoring Small Mammals". </p> <p class="FirstParagraph">The behavior of small fossorial mammals, such as voles, is extremely difficult to observe in natural environments. Small mammals were traditionally studied with labor intensive methods such as trapping and recapture or radio telemetry via homing, which require week/months of work and produce static home range estimates.</p> <p class="FirstParagraph">In pursuit of better understanding natural history and behavioral ecology we implemented an automated radio telemetry system (ARTS) to continuously monitor small mammals. We used an isotropic antenna array coupled with broadband receivers to estimate animal positions with nonlinear least squares, nonparameteric, and Bayesian trilateration methods. We then used Lomb-Scargle periodograms to estimate activity patterns of freely-behaving Prairie voles.</p>
Fig. 2 in Accumulation Of Heavy Metals By Small Mammals The Background And Polluted Territories Of The Urals
Fig. 2. The dendrogram is obtained for element analysis (Cu+Zn+Cd) in small mammals from natural populations in the background zone (Bcg) and polluted territories (Imp). The results of cluster analysis confirmed the statistically significant differences in heavy metals total accumulation in three species of small mammals.
Small mammals reduce distance-dependence and increase seed predation risk in tropical rainforest fragments
Seed predation and reduced predation risk with distance from conspecific trees are important influences on tree regeneration in tropical forests. Shifts in animal communities, such as an increase in rodents and other small mammals due to forest fragmentation, could alter patterns of seed predation and affect tree regeneration and community dynamics in forest fragments. We performed a field experiment on four native rainforest tree species in the Western Ghats, India, to test whether fragmentation increases seed predation by mammals and alters the distance-dependence of seed predation. We monitored seed predation within open and mammal-exclosure plots, near and far from the canopies of conspecific trees, in contiguous and fragmented forests. Seed predation of Cullenia exarillata, Ormosia travancorica, and Syzygium rubicundum was markedly higher in forest fragments, and more so within open plots than exclosures, while the predominantly insect-predated Acronychia pedunculata experienced similar predation in contiguous forests and fragments. Seed predation of C. exarillata and S. rubicundum was unrelated to distance from conspecific trees in open plots in both contiguous forests and fragments, in contrast to exclosures that showed marked near versus far differences in seed predation. Our findings suggest that by increasing overall seed predation risk and imposing similar seed predation risk near and far from adults variably across the tree species, small mammals could alter processes that shape tree diversity and species composition in fragmented tropical rainforests.
Decomposing niche components reveals simultaneous effects of opposite deterministic processes structuring alpine small mammal assembly
<p><span>Our knowledge of community assembly dynamics under multiple stressors is limited because of opposite niche-based processes, i.e., limiting similarity and habitat filtering could simultaneously occur, masking the overall patterns. Alpine biomes provide the ideal systems to explore the influences of co-occurrence processes as these communities usually face multiple stresses such as resources limitation and habitat constraints. However, the assembly processes of mammals in alpine areas have hardly been exclusively studied. Here, we</span> <span>aimed to address how different processes structured small mammal communities at the tree line transition zone, which represents one of the most distinct vegetation boundaries separating alpine from montane habitats. We compiled a regional dataset including species list, phylogeny, and functional traits from field collections across 18 mountains of southwest China and complemented them with published data sources. The traits were decomposed into different niche components to determine the respective effects of specific stressors. Phylogenetic and functional diversity indices representing evolutionary history, trait space, and pairwise species distance were calculated and compared with null expectations. Linear mixed-effect models were constructed to assess the increasing or decreasing tendencies of diversity values against increasing elevation. The results showed that phylogenetic and functional richness were strongly correlated with species richness, unlike the distance-based indices which were uncorrelated with species richness. There was no evidence found to support non-random phylogenetic or overall trait patterns. However, the resource acquisition niche tended to be more overdispersed (positive slopes), while the habitat affinity niche tended to be more clustered (negative slopes) as habitats became less productive and less vegetated. We conclude that limiting similarity and habitat filtering simultaneously structure small mammal communities in alpine areas. Altogether, the present study provides vital insights into the complexity of co-occurring assembly processes by niche decomposition, and highlights the importance of considering different diversity dimensions when assessing community structure.</span></p>
Fig. 2 in Difference In Small Mammal Assemblages In The Diet Of The Common Barn-Owl Tyto Alba Between Two Landscapes
Fig. 2. Difference of estimated species richness of the Common Barn-owl's food composition between two landscape categories, based on individual rarefaction analysis
Fig. 1 in Difference In Small Mammal Assemblages In The Diet Of The Common Barn-Owl Tyto Alba Between Two Landscapes
Fig. 1. Study area in the South-Transdanubian region, Hungary, showing the location of sampled nesting sites (settlements) and the two separated landscape types, indicated by different symbols
Fig. 3 in Difference In Small Mammal Assemblages In The Diet Of The Common Barn-Owl Tyto Alba Between Two Landscapes
Fig. 3. Variables factor maps at land-use level (A), species level (B) and guild level (C) in case of the agricultural lands (D-AL) and the semi-natural habitats (D-SNH)
Resource availability alters breeding strategies in a small mammal community
<p>Following a resource pulse, animals may finance reproduction by consuming concurrently available resources (income breeding) or by storing resources for future reproduction (capital breeding). Understanding how these reproductive strategies are used is important for determining the ecological mechanisms that structure the timing of reproduction and that drive interannual population fluctuations in animals. We gathered a reproductive dataset for five small mammal species over a 12-year period in Northeastern USA during which six masting events of American beech (<em>Fagus grandifolia</em>) and eastern hemlock (<em>Tsuga canadensis</em>) occurred. Masting created alternate years where seeds were either available late (masting year) or early (cached from the previous year) in the breeding season. The small mammal species differed in reliance on seeds and overwintering strategies. We quantified the diet using stable isotopes and recorded reproduction timing, proportion breeding, and litter size in females and testes size in males. Timing of seed availability minimally affected litter size but strongly affected proportion breeding and timing of reproduction. During masting years (late seed availability), a higher proportion of females reproduced, with breeding taking place later in the season (lactation timed with peak seed availability), although the delay was restricted in <em>Napaeozapus insignis</em>, an obligate hibernator. After a fall mast, cached seeds were used as capital in the following spring (early seed availability) to support a litter that, depending on the species, occurred 24 to 79 days sooner than a mast year. No late-season reproduction occurred in years with early seed availability except for <em>Myodes gapperi</em> which produced a second litter, likely financed by fungal consumption. Males also showed strong responses to seed availability, mirroring female reproduction with testes size staying constant in years with late seed availability and sharply decreasing over the breeding season in years with early seed availability. Our results highlight that although photoperiod and temperature broadly set the bounds of the breeding season in temperate environments, resource availability influences the reproductive strategies that species use, which in turn alters reproductive timing and can drive large inter-annual population fluctuations. Differences in overwintering strategies and diet may further modulate reproductive timing and output relative to resource pulses.</p>
Рис. 2. НасеΛение меΛких мΛекопитающих Хингано-Архаринского заказника по Δанным учета Λовчими стаканами (описание местообитаний см. в тексте) Fig. 2. Small mammals abundance in flood medow (стХА1, see ХА1 description, fig. 1) and larch- birch forest (стХА2, see ХА2 description, fig. 1), counts with pitfalls (0,5 l glasses) in (Eulipotyphla) Of The Khingano-Arkharinskyi Zakaznik
Рис. 2. НасеΛение меΛких мΛекопитающих Хингано-Архаринского заказника по Δанным учета Λовчими стаканами (описание местообитаний см. в тексте) Fig. 2. Small mammals abundance in flood medow (стХА1, see ХА1 description, fig. 1) and larch- birch forest (стХА2, see ХА2 description, fig. 1), counts with pitfalls (0,5 l glasses)
Рис. 1. Вероятность обнаружения меченых животных (среΑнее ± ошибка) при пяти- и Αесятиметровых интерваΛах межΑу прикормочными станциями в Αвух экспериментах. По второму эксперименту расчеты сΑеΛаны ΑΛя резуΛьтатов отΛова в течение первых трех и поΛных Αесяти Αней. Значение «p» отражает уровень статистической значимости разΛичий межΑу ΑоΛями животных с меткой при Αвух интерваΛах Fig. 1. Probability of finding marked animals (average±standard error) between feeding stations placed at intervals of five and ten meters in the two experiments. In the second experiment, calculations were made for the results of trapping during the first three days and during the whole period of ten days. The p value reflects the statistical significance of differences between the fractions of animals with a mark for two types of intervals in Verification of the bottle-based method for estimating abundance of small mammals using biomarkers
Рис. 1. Вероятность обнаружения меченых животных (среΑнее ± ошибка) при пяти- и Αесятиметровых интерваΛах межΑу прикормочными станциями в Αвух экспериментах. По второму эксперименту расчеты сΑеΛаны ΑΛя резуΛьтатов отΛова в течение первых трех и поΛных Αесяти Αней. Значение «p» отражает уровень статистической значимости разΛичий межΑу ΑоΛями животных с меткой при Αвух интерваΛах Fig. 1. Probability of finding marked animals (average±standard error) between feeding stations placed at intervals of five and ten meters in the two experiments. In the second experiment, calculations were made for the results of trapping during the first three days and during the whole period of ten days. The p value reflects the statistical significance of differences between the fractions of animals with a mark for two types of intervals
Figure 4 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)
Figure 4. Labial views of the second lower molars of the didelphid marsupials (A) Cryptonanus sp. (this study, Campos dos Goytacazes, Rio de Janeiro state), (B) Gracilinanus microtarsus (NPM 1682, Macaé, Rio de Janeiro state), and (C) Monodelphis iheringi (NPM 1010, Macaé, Rio de Janeiro state), showing the variation in the entoconid size.
Figure 3 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)
Figure 3. Manipulation and identification of the pellets collected below the artificial nest of the Tyto furcata pair. (A) Separation of bone material; (B) Selection of craniums and mandibles for morphological identification.
Figure 1 in Small mammals in the diet of Barn Owls (Tyto furcata) in an urban area in Rio de Janeiro state, Brazil, with a new record of the dwarf mouse opossum (Cryptonanus)
Figure 1. Satellite image showing nesting site of the T. furcata couple and the surrounding area in Campos dos Goytacazes, Rio de Janeiro. Adapted from Google Earth®.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.