Find research datasets worth reusing
Search datasets from major research repositories and use ShareScore to quickly assess how well each record supports discovery, access, and reuse.
235
datasets available to search
ShareScore release 0.7.1
Dataset results
235 results for “Canis”
Distribution of large carnivores in Europe 2012 - 2016: Distribution map for Golden Jackal (Canis aureus)
<p><strong>Abstract</strong></p> <p>Regular assessments of species’ status are an essential component of conservation planning and adaptive management. They allow the progress of past or ongoing conservation actions to be evaluated and can be used to redirect and prioritize future conservation actions. Most countries perform periodic assessments for their own national adaptive management procedures or national red lists. Furthermore, the countries of the European Union have to report on the status of all species listed on the directives of the Habitats Directive every 6 years as part of their obligations under Article 17. However, these national level assessments are often made using non-standardized procedures and do not always adequately reflect the biological units (i.e., the populations) which are needed for ecologically meaningful assessments.</p> <p>Since the early 2000’s the Large Carnivore Initiative for Europe (a Specialist Group of the IUCN’s Species Survival Commission) has been coordinating periodic surveys of the status of large carnivores across Europe (e.g., von Arx et al. 2004; Salvatori & Linnell 2005, Kaczensky et al. 2013). These have covered the Eurasian lynx (<em>Lynx lynx</em>), the wolf (<em>Canis lupus</em>), the brown bear (<em>Ursus arctos</em>) and the wolverine (<em>Gulo gulo</em>). The golden jackal (<em>Canis aureus</em>) has been added to the LCIE prerogatives in 2014. The species is rapidly expanding in Europe (Trouwborst <em>et al.</em> 2015; Männil & Ranc 2022), a large-scale phenomenon that resembles that of the other large carnivores. Golden jackals are thriving in human-dominated landscapes (Ćirović <em>et al.</em> 2016; Lanszki <em>et al.</em> 2018; Fenton <em>et al.</em> 2021), where they are often functioning as the top predators, despite having smaller body size that is typical for large carnivores. The expansion of the species triggers many questions among scientists, stakeholders, and policy makers (Trouwborst <em>et al.</em> 2015; Hatlauf <em>et al.</em> 2021), that are closely connected to those raised by the other large carnivores (e.g., potential conflicts with livestock or hunting). In this context, monitoring the species’ expansion, delineating populations, assessing the species' legal and protection status, and addressing the concerns raised by this rapidly expanding carnivore requires a high level of coordination among regional experts.</p> <p>These surveys involve the contributions of the best available experts and sources of information. While the underlying data quality and field methodology varies widely across Europe, these coordinated assessments do their best to integrate the diverse data in a comparable manner and make the differences transparent. They also endeavor to conduct the assessments on the most important scales. This includes the continental scale (all countries except for Russia, Belarus, Moldova and the parts of Ukraine outside the Carpathian Mountain range), the scale of the EU 28 (where the Habitats Directive operates) and of the biological populations which reflect the scale at which ecological processes occur (Linnell et al. 2008). In this way, the independent LCIE assessments provide a valuable complement to the ongoing national processes.</p> <p>Our last assessments covered the period 2006-2011 (Kaczensky et al. 2013; Chapron et al. 2014) but, at the time, did not include golden jackals. The current assessment is based on the period 2012-2016 and broadly follows the same methodology. Explicit distinctions are made between classification based on empirical data and expert opinion. The population definitions used in this report follow those proposed in (Ranc <em>et al.</em> 2018); areas whose presence category was defined by expert opinion were not assigned to a specific population, though. </p> <p> </p> <p><strong>Methods</strong></p> <p>The mapping approach follows the methods described in Chapron et al. (2014) and Kaczensky et al. (2013). It updates the published Species Online Layers (SPOIS) to the period 2012-2016.</p> <p>In short, large carnivore presence was mapped at a 10x10 km ETRS89-LAEA Europe grid scale. This grid is widely used for the Flora-Fauna-Habitat reporting by the European Union (EU) and can be downloaded at: http://www.eea.europa.eu/data-and-maps/data/eea-reference-grids-2</p> <p>The map encompasses the EU countries plus the non-EU Balkan states, Switzerland, Norway, and the Carpathian region of Ukraine. Presence in a grid cell was ideally mapped based on carnivore presence and frequency in a cell resulting in:</p> <p>1 = Permanent (presence confirmed in >= 3 years in the last 5 years OR in >50% of the time OR reproduction confirmed within the last 3 years)</p> <p>3 = Sporadic (highly fluctuating presence) (presence confirmed in <3 years in the last 5 years OR in <50% of the time)</p> <p>5 = Expert-based presence (high confidence) (expert-based opinion; very suitable habitat near permanent presence areas)</p> <p>6 = Expert-based presence (low confidence or unconfirmed records) (expert-based opinion; suitable habitat near presence areas or unconfirmed C3 records of jackal presence)</p> <p>7 = Expert-based absence (high confidence) (jackal presence according to coarse-resolution hunting bag data but experts think, with high confidence, the species is not present)</p> <p>8 = Expert-based absence (low confidence) (jackal presence according to coarse-resolution hunting bag data but experts think the species is not present)</p> <p>Where grid cells were assigned different values between neighboring countries; the “disputed” cells were given the “higher” presence values e.g., a cell categorized as “sporadic” by one country and “permanent” by another was categorized as “permanent”. Data-based categories (1,3) were given priority over expert-based categories (5 through 8).</p> <p>To assess the quality of carnivore signs we used the SCALP criteria developed for the standardized monitoring of Eurasian lynx (<em>Lynx lynx</em>) in the Alps (Molinari-Jobin et al. 2012):</p> <p>Category 1 (C1): “Hard facts”, verified and unchallenged large carnivore presence signs (e.g., dead animals, DNA, verified camera trap images);</p> <p>Category 2 (C2): Large carnivore presence signs controlled and confirmed by a large carnivore expert (e.g., trained member of the network), which requires documentation of large carnivore signs; and</p> <p>Category 3 (C3): Unconfirmed category 2 large carnivore presence signs and all presence signs such as sightings and calls which, if not additionally documented, cannot be verified.</p> <p>See Hatlauf and Böcker (2022) for best practices regarding golden jackal records.</p> <p> </p> <p><strong>Usage Notes</strong></p> <p>The data available consists of a shapefile at a 10 x 10 km resolution compiled for the period 2012-2016 for the Large Carnivore Initiative of Europe IUCN Specialist Group and for the IUCN Red List Assessment.</p> <p> </p> <p><strong>References</strong></p> <p>Boitani, L., F. Alvarez, O. Anders, H. Andren, E. Avanzinelli, V. Balys, J. C. Blanco, U. Breitenmoser, G. Chapron, P. Ciucci, A. Dutsov, C. Groff, D. Huber, O. Ionescu, F. Knauer, I. Kojola, J. Kubala, M. Kutal, J. Linnell, A. Majic, P. Mannil, R. Manz, F. Marucco, D. Melovski, A. Molinari, H. Norberg, S. Nowak, J. Ozolins, S. Palazon, H. Potocnik, P.-Y. Quenette, I. Reinhardt, R. Rigg, N. Selva, A. Sergiel, M. Shkvyria, J. Swenson, A. Trajce, M. Von Arx, M. Wolfl, U. Wotschikowsky and D. Zlatanova. 2015. Key actions for Large Carnivore populations in Europe. Institute of Applied Ecology (Rome, Italy). Report to DG Environment, European Commission, Bruxelles. Contract no. 07.0307/2013/654446/SER/B3</p> <p>Ćirović, D., A. Penezić and M. Krofel. 2016. Jackals as cleaners: Ecosystem services provided by a mesocarnivore in human-dominated landscapes. <em>Biological Conservation</em>, 199: 51–55.</p> <p>Chapron, G., Kaczensky, P., Linnell, J.D.C., von Arx, M., Huber, D., Andrén, H., López-Bao, J.V., Adamec, M., Álvares, F., Anders, O., Balčiauskas, L., Balys, V., Bedő, P., Bego, F., Blanco, J.C., Breitenmoser, U., Brøseth, H., Bufka, L., Bunikyte, R., Ciucci, P., Dutsov, A., Engleder, T., Fuxjäger, C., Groff, C., Holmala, K., Hoxha, B., Iliopoulos, Y., Ionescu, O., Jeremić, J., Jerina, K., Kluth, G., Knauer, F., Kojola, I., Kos, I., Krofel, M., Kubala, J., Kunovac, S., Kusak, J., Kutal, M., Liberg, O., Majić, A., Männil, P., Manz, R., Marboutin, E., Marucco, F., Melovski, D., Mersini, K., Mertzanis, Y., Mysłajek, R.W., Nowak, S., Odden, J., Ozolins, J., Palomero, G., Paunović, M., Persson, J., Potočnik, H., Quenette, P.-Y., Rauer, G., Reinhardt, I., Rigg, R., Ryser, A., Salvatori, V., Skrbinšek, T., Stojanov, A., Swenson, J.E., Szemethy, L., Trajçe, A., Tsingarska[1]Sedefcheva, E., Váňa, M., Veeroja, R., Wabakken, P., Wölfl, M., Wölfl, S., Zimmermann, F., Zlatanova, D. and Boitani, L. 2014. Recovery of large carnivores in Europe’s modern human-dominated landscapes. <em>Science</em> 346: 1517-1519.</p> <p>Fenton, S., Moorcroft, P.R., Ćirović, D., Lanszki, J., Heltai, M., Cagnacci, F., Breck, S., Bogdanović, N., Pantelić, I., Ács, K. and Ranc, N. 2021. Movement, space-use and resource preferences of European golden jackals in human-dominated landscapes: insights from a telemetry study. <em>Mammalian Biology</em>, 101: 619–630.</p> <p>Hatlauf, J. and Böcker, F. 2022. Recommendations for the documentation and assessment of golden jackal (<em>Canis aureus</em>) records in Europe. BOKU reports on wildlife research and willdife management 27. Ed: Institute of Wildlife Biology and Game Management (IWJ), University of Natural Resources and Life Sciences, Vienna. ISBN: 978-3-900932-94-7</p> <p>Hatlauf, J., Bayer, K., Trouwborst, A. and Hackländer, K. 2021. New rules or old concepts? The golden jackal (<em>Canis aureus</em>) and its legal status in Central Europe. <em>European Journal of Wildlife Research</em>, 67, 25.</p> <p>Kaczensky, P., Chapron, G., Von Arx, M., Huber, D., Andrén, H. and Linnell, J. 2013. Status, management and distribution of large carnivores - bear, lynx, wolf and wolverine - in Europe. Istituto di Ecologia Applicata, Rome, Italy.</p> <p>Lanszki, J., Schally, G., Heltai, M. and Ranc, N. 2018. Golden jackal expansion in Europe: first telemetry evidence of a natal dispersal. <em>Mammalian Biology</em>, 88: 81–84.</p> <p>Linnell, J.D.C., Salvatori, V. and Boitani, L. 2008. Guidelines for population level management plans for large carnivores in Europe. A Large Carnivore Initiative for Europe report prepared for the European Commission (contract 070501/2005/424162/MAR/B2).</p> <p>Männil, P. and Ranc, N. 2022. Golden jackal (<em>Canis aureus</em>) in Estonia: development of a thriving population in the boreal ecoregion. <em>Mammalian Research,</em> 67: 245-250.</p> <p>Molinari-Jobin, A., Kéry, M., Marboutin, E., Molinari, P., Koren, I., Fuxjäger, C., Breitenmoser-Würsten, C., Wölfl, S., Fasel, M., Kos, I., Wölfl, M. and Breitenmoser, U. 2012. Monitoring in the presence of species misidentification: the case of the Eurasian lynx in the Alps. <em>Animal Conservation </em>15: 266-273.</p> <p>Ranc, N., Krofel, M. and Cirovic, D. 2018. IUCN Red List Mapping for the regional assessment of the Golden Jackal (<em>Canis aureus</em>) in Europe. IUCN Red List Threatened Species, 13.</p> <p>Salvatori, V. and Linnell, J.D.C. 2005. Report on the conservation status and threats for wolf (Canis lupus) in Europe. Council of Europe Report T-PVS/Inf (2005) 16.</p> <p>Trouwborst, A., Krofel, M. and Linnell, J.D.C. 2015. Legal implications of range expansions in a terrestrial carnivore: the case of the golden jackal (<em>Canis aureus</em>) in Europe. <em>Biodiversity Conservation</em>, 24: 2593–2610.</p> <p>von Arx, M., Breitenmoser-Würsten, C., Zimmermann, F. and Breitenmoser, U. 2004. Status and conservation of the Eurasian lynx (<em>Lynx lynx</em>) in Europe in 2001. KORA Report 19e: 1-330.</p> <p> </p> <p><strong>Contact information</strong></p> <p>Nathan Ranc, nathan.ranc@inrae.fr</p>
Dataset for the Diet of the grey wolf Canis lupus in Roztocze and Solska Forest, south-east Poland
<p>The dataset for the article: Mysłajek R.W., Stachyra P., Figura M., Nędzyńska-Stygar M., Stefański R., Korga M., Kwiatkowska I., Stępniak K.M., Tołkacz K., Nowak S. 2022. Diet of the grey wolf <em>Canis lupus</em> in Roztocze and Solska Forest, south-east Poland. Journal of Vertebrate Biology 71: 22040. DOI: <a href="https://doi.org/10.25225/jvb.22040">10.25225/jvb.22040</a></p>
Fig. 1 in Winter Diet Of The Common Genet, Genetta Genetta (Carnivora, Viverridae), And The African Golden Wolf, Canis Anthus (Carnivora, Canidae), In Altitudinal Locality Of The Edough Forest (Northeastern Algeria)
Fig. 1. Geographical situation of the study locality. (with indication of the three transects: 1, 2 and 3). Source: https://journals.openedition.org/physio-geo/docannexe/image/4217/img-1.jpg. Modified by Boukheroufa (present work).
Figure 1 in A 19th Century New Ireland Dog, Canis familiaris novaehiberniae Lesson, 1827 and the Status of Canis hallstromi Troughton, 1957
Figure 1. Map of New Guinea region showing colonial territories in the late 1800s and type localities of: (1) Canis familiaris novaehiberniae Lesson, 1827a, New Ireland; (2) C. f. papuensis Ramsay, 1879, unspecified, southeastern New Guinea; and (3) C. hallstromi Troughton, 1957, Lavani Valley, Southern Highlands District.
Fig. 6 in Toxocara canis-induced changes in host intestinal microbial communities
Fig. 6 Correlation networks of the microbiome. a Heatmap of correlation coefficients in the CI, II and Tc groups. b Network map between species. Each node in the graph represents a species, with the color of the dot representing the highest relative abundance observed within these subgroups.The size of the dot corresponds to the average relative abundance of the species, with larger dots indicating higher abundance.The species are connected to each other through straight lines, with the color pink indicating a positive correlation and blue indicating a negative correlation. The thickness of the lines reflects the magnitude of the correlation, with only correlation coefficients> 0.2 between species being displayed
Fig. 3 in Toxocara canis-induced changes in host intestinal microbial communities
Fig. 3 Comparison of beta diversity indicator of flora among CI, II and Tc groups. a Unweighted uniFrac analysis, b Weighted uniFrac analysis, c Partial least-squares discriminant analysis. CI, Intestine samples of dogs in control group; II, intestine samples of dogs in infected group; plsda, partial least-squares discriminant analysis; Tc, Toxocara canis samples
Fig. 5 in Toxocara canis-induced changes in host intestinal microbial communities
Fig. 5 Differences in species composition of flora in the CI, II and Tc group at the genus level. The horizontal coordinate is the sample name and the vertical coordinate is the relative abundance of the species annotated. Species not annotated at this taxonomic level and whose abundance was <0.5% of the sample were combined as "Others" (a). b The top 10 species at the genus level in the CI, II and TI group. Note that the significance of the test of difference was marked with an asterisk at the top of the bar graph if available. CI, Intestine samples of dogs in control group; II, intestine samples of dogs in infected group; Tc, Toxocara canis samples
Fig. 2 in Toxocara canis-induced changes in host intestinal microbial communities
Fig. 2 Boxplots showing comparisons of the alpha diversity indicators of flora among the three experimental groups. a Coverage index, b Chao index, c Shannon index, d Ace index. CI, Intestine samples of dogs in control group; II, intestine samples of dogs in infected group; Tc, Toxocara canis samples
Fig. 1 in Toxocara canis-induced changes in host intestinal microbial communities
Fig. 1 OTU cluster analysis. OTUs were generated according to 97% sequence similarity clustering. a Venn diagram of the unique and common OTUs among the three groups. b Rank-abundance curves. c Rarefaction curve. d Species accumulation curve. CI, Intestine samples of dogs in control group; II, intestine samples of dogs in infected group; OTU, operational taxonomic unit; Tc, Toxocara canis samples
Fig. 5 in Remarks on the skull morphology of Canis lupaster Hemprich and Herenberg, 1832 from the collection of the Natural History Museum "G. Doria" of Genoa, Italy
Fig. 5 - Box plots of selected absolute measurements and ratios; a) comparison of total length (TL) of C. lupaster and C. lupus male and female; b) ratio between length of premolars an length of molars (LPR/LMR); c) ratio between the great palatal breadth and the breadth measured at canine alveoli (GPB/BCA; d) ratio between total length and condilobasal length (TL/CL).
Fig. 2 in Remarks on the skull morphology of Canis lupaster Hemprich and Herenberg, 1832 from the collection of the Natural History Museum "G. Doria" of Genoa, Italy
Fig. 2 - Teeth comparison; a1: upper teeth of C. lupus; a2) lower teeth of C lupus; b1) upper teeth of C. lupaster; b2) lower teeth of C lupaster; c1) upper teeth of C. anthus; c2) lower teeth of C. anthus.
Fig. 3 - Specimen MSNG 26228 in Remarks on the skull morphology of Canis lupaster Hemprich and Herenberg, 1832 from the collection of the Natural History Museum "G. Doria" of Genoa, Italy
Fig. 3 - Specimen MSNG 26228; a) skull in dorsal view; b) skull in ventral view, oronasal fistula indicated from white arrow; c) skull in right lateral view; d) detail of the right upper carnassial; e) mandible in occlusal view.
Fig. 1 - Specimen MSNG 26232. a in Remarks on the skull morphology of Canis lupaster Hemprich and Herenberg, 1832 from the collection of the Natural History Museum "G. Doria" of Genoa, Italy
Fig. 1 - Specimen MSNG 26232. a) skull in left lateral view; b) skull in ventral view; c) skull in dorsal view; d) left hemimandible in lingual view; e) left hemimandible in labial view; f) occlusal view of P4-M3.
Fig. 4 in Remarks on the skull morphology of Canis lupaster Hemprich and Herenberg, 1832 from the collection of the Natural History Museum "G. Doria" of Genoa, Italy
Fig. 4 - Multivariate analysis; triangle) C. lupus; square) C. lupaster; circle) C. anthus; a) PCA on skull and mandible; b) MANOVA on upper and lower teeth.
Fig. 1 in Golden jackal (Canis aureus Linnaeus, 1758) and Red fox (Vulpes vulpes Linnaeus, 1758) population dynamics in Sarnena Sredna Gora Mts., Bulgaria based on hunting statistics
Fig. 1. Golden jackal (Canis aureus L.) and Red fox (Vulpes vulpes L.) population dynamics trends in Sarnena Sredna Gora Mts., Bulgaria, for a period of 11 years based on the analysis of the hunting data base (number of shot individuals)
Figure 1 in Cyclosporine A increases the intensity of Toxocara canis infection in swiss mice
Figure 1. Relative mRNA transcription of interleukins IL-4, IL-10, IL-12 in splenocytes of Swiss mice treated with CsA (50 mg/Kg), infected with Toxocara canis eggs and euthanized 30 days postinoculation.
Fig. 1 in Short Communication The golden jackal Canis aureus L. 1758 (Carnivora: Canidae) on the Tuscan Apennines
Fig. 1 - Map showing the area where the two golden jackals have been observed in Tuscany. The precise coordinates are omitted for species conservation reasons (Lunghi et al., 2019). / Mappa che mostra l'area in cui sono stati osservati i due sciacalli dorati in Toscana. Le coordinate precise sono omesse per motivi relativi alla conservazione della specie (Lunghi et al., 2019).
Fig. 2 in Short Communication The golden jackal Canis aureus L. 1758 (Carnivora: Canidae) on the Tuscan Apennines
Fig. 2 - The first (A-B) and the second (C-D) of the two golden jackals observed in Tuscany. Individual recognition was carried out by the pattern of the muzzle fur (in the area indicated by the red circle). Photo taken with Victure HC300 trail camera. The full video of the observation can be seen at https://www.youtube.com/watch?v=B0wO4i4SNXA. / Il primo (A-B) e il secondo (C-D) dei due sciacalli dorati osservati in Toscana. Il riconoscimento individuale è stato effettuato attraverso il disegno del pelo del muso (nell'area indicata dal cerchio rosso). Foto scattata con la trail camera Victure HC300. Il video completo dell'osservazione può essere visto su https:// www.youtube.com/watch?v=B0wO4i4SNXA.
Fig. 2 in On the activity of two medium-sized canids: the Golden Jackal (Canis aureus) and the Red Fox (Vulpes vulpes) in the Natural Bark "Sinite Kamani" (Bulgaria) revealed by camera traps
Fig. 2. Number of all pictures of Red Fox (Vulpes vulpes) taken during 24h (expressed for one hour time interval) during seasons.
Fig. 4 in On the activity of two medium-sized canids: the Golden Jackal (Canis aureus) and the Red Fox (Vulpes vulpes) in the Natural Bark "Sinite Kamani" (Bulgaria) revealed by camera traps
Fig. 4. Daytime activity (feeding on dog food) of the Red Fox and the Golden Jackal registered by camera traps at the Sinite Kamani Natural Park.
ScienceDex guides
Understand access before you commit
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.