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Supplemental Information to Climate-driven habitat shifts of high-ranked prey species structure Late Upper Paleolithic hunting
<p>The data provided here are the supplemental information accompanying Yaworsky et al, 2023 in the journal <em>Scientific Reports</em>. These data represent the following, which are referenced in the published work at DOI: 10.1038/s41598-023-31085-x.</p> <p><strong>Below is the legend for the Supplementary Information</strong>, including how it is referenced within the text of the publication, the file name, and a brief description. More thorough descriptions of the data can be found within the publication in <em>Scientific Reports</em>.</p> <p><strong>Supplementary 1</strong> – <em>UpperPaleoDietV4.html</em> – HTML document of the analyses performed and presented in the paper. This is a Markdown document compiled in R with R code chunks and descriptions.</p> <p><strong>Supplementary 2</strong> – <em>Support Information 2.docx</em> – Word document containing supplementary tables 2 and 3.</p> <p><strong>Supplementary 3</strong> – <em>ArchaeoloigcalDataset_v8.csv</em> – Archaeological data referenced in the Material and Methods. These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 4</strong> – <em>EuroUpperPaleoFaunas_v6.csv</em> – Zooarchaeological data referenced in the Material and Methods. These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 5 </strong>– <em>Lupo2016.csv</em> – Data of Arficant fauna weight derived from table in Lupo and Schmitt 2016 (Table 2). These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 6</strong> – <em>PushkinaRaia_FaunaWeights.csv</em> – Data of Pleistocene fauna weights derived from table in Pushkina and Raia 2008 (Table 1). These data are necessary for running the code presented in SI 1.</p> <p><strong>Supplementary 7</strong> – <em>environmental_BG.csv</em> – Data representing background environmental conditions derived from the CHELSA TRaCE21k data. These data are necessary for running the code in SI 1.</p> <p>For more information on the data, methods, and results, please see the main paper. </p> <p> </p> <p> </p>
Hunting for vampires and other unlikely forms of parity violation at the Large Hadron Collider: lhe files
<p>Parton-level simulations in the PV-mSME model with various values of lambdaPV and for the standard model (lambdaPV=0).</p> <p>This dataset includes one example lhe file generated by MadGraph for each sample used in the <a href="https://arxiv.org/abs/2205.09876">paper</a>.<br> <br> The MadGraph version and the modifications we make to its generated code are included in the code sharing dataset on <a href="https://github.com/Rupt/paper-hunting-vampires">git</a> and <a href="https://doi.org/10.5281/zenodo.6827723">Zenodo</a>.<br> <br> Main files are named `liv_3j_4j_${lambdaPV}_0.lhe.gz`, where lambdaPV is a floating point number with "." replaced with "p".<br> <br> Other files named `liv_rot_${hour}_0.lhe.gz ` are from the rotated PV-mSME from the appendix that studies the effect of a rotating planet. Each rotation in radians is <em>hour * 2 pi / 24 </em>(for discrete rotations in a 24 hour day).<br> <br> The suffix "_0" encodes that each was generated with the first in our sequence of random seeds.</p> <p>`sm_3j_4j_0.lhe.gz` is simulated from the Standard Model, which is physically equivalent to lambdaPV = 0.</p>
Waterbirds counts in the Drugeon bassin, France (game reserves and hunting areas) in 2020
<p>This dataset describes waterbird observations performed in game reserves and in hunting areas of the Drugeon river basin, France, in 2020.</p> <p>For each game reserve, a similar hunting area was selected in the same or an adjacent commune. If the hunting reserve was a stretch of river, as in Bonnevaux or Houtaud, another stretch of river was surveyed for comparison. In Frasne, the hunting reserve covers the Lothaud pond. Therefore, the adjacent Lucien pond was surveyed as a huntable area. The other nine wetland reserves are located in marshes and therefore nine other marshes were surveyed. Once this work was done, 10 other wetlands were also surveyed to complete the study. In total, 12 hunting reserves and 22 huntable areas, all in wetlands, were surveyed twice during the autumn of 2020. One of the 13 reserves was not surveyed (just forgotten in the sampling plan). The first survey was carried out between 24 August and 5 September, i.e. just before the opening of the waterfowl hunting season on 6 September. The second pass was carried out between 19 and 29 October, i.e. 44 to 54 days after the opening of the hunting season.</p> <p>Each sector was surveyed on foot, with round trips spaced at approximately 20 m intervals. The use of the Caynax application on Android allowed to control the location of the route, the regular spacing of the passages and the length of the route taken on each wetland. For both ponds, the water bodies were circled and birds were counted along the banks and on the water table. All characteristic wetland birds were noted, specifying whether they had been seen landing or in transit flight. Only birds landing are taken into account in this study. The observations were then recorded in an Excel table with the name of the area, its hunting status, the surface area, the number of kilometres covered during the survey and the date of the survey (see table <a href="https://zenodo.org/api/files/1546581e-0a8a-4966-9250-cc37eeafb414/db0.txt">db0.txt</a> and article cited below for more details).</p> <p><strong>FILE DESCRIPTION:</strong></p> <p><a href="https://zenodo.org/record/7539822/files/CartePAIGN_BB.jpg?download=1">CartePAIGN_BB.jpg </a>map of the areas studied. Green, game reserves sampled; red , hunting areas sampled: blue, one game reserve not sampled.</p> <p><a href="https://zenodo.org/record/7539822/files/db0.txt?download=1">db0.txt</a> counts for each area sampled</p> <ul> <li>com, commune</li> <li>lieu, place name</li> <li>pair, pair ID</li> <li>res, game reserve (OUI = yes, NON = no)</li> <li>ha, area sampled</li> <li>km, number of kilometers walked</li> <li>mois, month</li> <li>The next 28 colums are species ID, for full names see table <a href="https://zenodo.org/record/7539822/files/Statuts.txt?download=1">Statuts.txt</a>.</li> </ul> <p><a href="https://zenodo.org/record/7539822/files/Game reserves and hunting areas sampled.kml?download=1">Game reserves and hunting areas sampled.kml </a> kml file of the areas sampled (game reserves in green, hunting areas sampled in red; in blue, one reserve not sampled)</p> <p><a href="https://zenodo.org/record/7539822/files/Statuts.txt?download=1">Statuts.txt</a> list of species recorded</p> <ul> <li>espece, specie name (in French)</li> <li>nom latin, latin name</li> <li>nom anglais, species name (in English)</li> <li>sp, species ID</li> <li>protection, protection status: Protégée, protected; Chassable, huntable</li> <li>migrateur, migratory status: Migrateur tardif, late migratory; Migrateur précoce, early migratory</li> </ul> <p><strong>SUPPLEMENTARY FILES</strong></p> <p><a href="http://zenodo.org/record/7539822/files/R_code_for_Analysis.zip?download=1">R_code_for_analysis.zip</a> Workflow (in French) and R code for the analyses carried out in the article Michelat & Giraudoux (2023).</p> <p> </p>
Data for Hunting of sika deer over six decades does not restore forest regeneration, Journal of Applied Ecology
<p>Data used for Hunting of sika deer over six decades does not restore forest regeneration.</p>
Fig. 7 in Coordinated hunting behaviors of mixed-species groups of piscivores and associated species at Isla del Coco National Park (Eastern Tropical Pacific)
Fig. 7. Cluster analysis of species co-occurrences in groups based on the Ward linkage method and Pearson distance. Abbreviations for each species are defined in Tab. 1. Note two dominant clusters (cluster 1 at left and cluster 2 at right). An asterisk below species codes indicate membership in top 10 species based on mixed-species links.
Fig. 5 in Coordinated hunting behaviors of mixed-species groups of piscivores and associated species at Isla del Coco National Park (Eastern Tropical Pacific)
Fig. 5. Network visualization of the web of associations between species (33 species with 288 pair-wise links). The size of each species node is weighted relative to the frequency of each species in any group (abbreviations for each species are defined in Tab. 1). The lines between species nodes are weighted by the relative frequency of associations between each species pair.
Fig. 3 in Coordinated hunting behaviors of mixed-species groups of piscivores and associated species at Isla del Coco National Park (Eastern Tropical Pacific)
Fig. 3. Examples of mixed-species hunting groups observed to ca. 35 m depth. (A) Caranx melampygus, Dermatolepis dermatolepis and Bodianus diplotenia at a crevice. Note D. dermatolepis and B. diplotaenia are able to maneuver deep into the crevice while C. melampygus follow from above and search for escaping prey. (B) Group composed of C. melampygus, Trianodon obesus, Cephalopholis panamensis and unidentified muraenid eel (hidden within crevices) hunt for prey within crevices amongst coral and coral rubble along reef edge. (C) Lutjanus argentiventris, D. dermatolepis, C. melampygus and B. diplotaenia hunt for prey as group traverses low relief volcanic pavement along a pinnacle. (D) Group composed of D. dermatolepis, C. melampygus and Aulostomus chinensis. Note position of A. chinensis in lead over C. melampygus. (E) C. melampygus follows above a muraenid eel hunting within narrow crevices. (F) As in previous image, D. dermatolepis follows above muraenid eel hunting within narrow crevice. (G) C. melampygus follow B. diplotaenia hunting over sand and volcanic rubble habitat. (H) B. diplotaenia and A. chinensis hunt in tandem along edge of pinnacle.
Model outputs for occurrence and hunting data‐based models of wild boar distribution and abundance, July 2019 update
<p>These maps are wild boar habitat suitability outputs based on newly available data of wild boar, and models for predicting wild boar relative abundance using hunting yields.</p> <p><strong>Objectives</strong>:</p> <p>- Validation of previously produced hunting yield maps and new ones<br> - Downscaling to 10x10 km grid<br> - Downscaling to 2x2 km grid</p> <p><strong>Model settings and predictors: </strong> <br> - Model from ENETWILD report August 2019<br> - Assuming cells as municipality in 10x10 km grid downscaling<br> - Assuming cells as hunting grounds in 2x2 km grid downscaling </p> <p><strong>Conclusions guiding future methodological steps</strong><br> - To update wild boar hunting yield data for some specific regions;<br> - To increase hunting yield data resolution;<br> - To explore model independent parametrization for each bioregion.</p> <p><strong>Files:</strong></p> <p>August_2019_HY_nut00_10x10 >> Model outputs based on hunting yield GLM analyses<br> August_2019_occurrences_bioclim >> Model outputs based on Bioclim analyses<br> August_2019_occurrences_glm >> Model outputs based on Generalised linear model<br> August_2019_occurrences_ksvm >> Model outputs based on Support vector Machine analyses<br> August_2019_occurrences_maxent >> Model outputs based on Maxent analyses<br> August_2019_occurrences_randomForest>> Model outputs based on Random Forest analyses</p> <p>---------------------------------------------------------------------------------------------------------------------------------------------------------</p> <p>These maps are models obtained in intermediate phases of the ENETWILD project based on available information. <br> There are frequent updates in order to improve the results. For methodological approach and details check the paper: </p> <p>ENETWILD‐consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, G. Body, A. Cohen, R. Soriguer, J. Vicente (2019). ENETwild modelling of wild boar distribution and abundance: update of occurrence and hunting data‐based models. EFSA Supporting Publications, 16(8), 1674E.<br> <a href="https://eur03.safelinks.protection.outlook.com/?url=https%3A%2F%2Fefsa.onlinelibrary.wiley.com%2Fdoi%2Fabs%2F10.2903%2Fsp.efsa.2019.EN-1674&data=02%7C01%7C%7Ca8ad922eefde42f5cb5208d7c5054851%7C406a174be31548bdaa0acdaddc44250b%7C1%7C0%7C637194498792136402&sdata=fqdiYEOqYIlHaDbp5a7kVdGQ6FWuFEydJNhSWOghH%2FQ%3D&reserved=0">https://efsa.onlinelibrary.wiley.com/doi/abs/10.2903/sp.efsa.2019.EN-1674</a></p> <p>.</p> <p>Permission for reuse occurrence outputs records is granted under the terms of a CC-BY-NC license.<br> Permission for reuse hunting yield outputs is granted under the terms indicated by EFSA.</p>
FIG. 12 in Hunting, husbandry, exchange and ritual: animal use and meaning at Moxviquil, Chiapas Mexico
FIG. 12. — Mollusca: A, B, Lysinoe ghiesbreghti Nyst, 1841; C, D, Pachychilus sp.; E, Dosinia sp. or Mercenaria mercenaria Linnaeus, 1758; F, Ostreidae shell fragment. Photographs: Elizabeth Paris. Scale bar: 4 cm.
FIG. 4. — A-I in Hunting, husbandry, exchange and ritual: animal use and meaning at Moxviquil, Chiapas Mexico
FIG. 4. — A-I, Canis lupus familiaris Linnaeus, 1758; J-L, Urocyon cinereoargenteus Schreber, 1775; M-X, Canis lupus familiaris Linnaeus, 1758; A, adult left mandible with PM2, PM3, PM4, M1; B, juvenile left mandible fragment with DPM2, with adult cusp visible below; C, D, two adult left mandibular PM3; E, juvenile right maxillary I3; F, G, two juvenile left mandibular M1; H, adult right maxilla with PM4, M1, M2; I, adult right maxillary PM4; J, adult right maxillary PM4; K, L, two adult left maxillary PM4; M, adult maxillary left canine with perforated root; N, O, standard juvenile right maxillary M1 with cusp mutation; P-R, standard juvenile left maxillary M1 with cusp mutation; S, miniature adult left maxillary M1 with cusp mutation; T, miniature adult right maxillary M1 with cusp mutation; U, miniature adult left maxillary M1 with cusp mutation; V, adult left maxillary PM2 and maxilla fragment; W, atlas; X, juvenile ribs, including a broken and healed rib (two left and four right fragments). Photographs: Elizabeth Paris. Scale bar: 4 cm.
FIG. 1 in Hunting, husbandry, exchange and ritual: animal use and meaning at Moxviquil, Chiapas Mexico
FIG. 1. — Map of the Maya culture area with, archaeological sites and, modern towns mentioned in the text. Drafted by Elizabeth Paris, from base map by Wikimedia Commons (commons.wikimedia.org). Abbreviations: CD, Central Depression; CP, Comitán Plateau; EH, Eastern Highlands; SL, Sierra Lacandona; SMC, Sierra Madre de Chiapas; WH, Western Highlands.
FIG. 3 in Hunting, husbandry, exchange and ritual: animal use and meaning at Moxviquil, Chiapas Mexico
FIG. 3. — Odocoileus virginianus Zimmermann, 1780 antler fragments from the monumental zone. Photographs: Elizabeth Paris. Scale bar: 4 cm.
FIG. 2 in Hunting, husbandry, exchange and ritual: animal use and meaning at Moxviquil, Chiapas Mexico
FIG. 2. — Map of Moxviquil, including the locations of the monumental zone, Operation 4, an outlying residential zone, and Operation 7, a funerary cave located on the hillslope below Operation 4. Drafted by Roberto López Bravo & Stephanie Reyes Ibelles, from topographic base map by INEGI (Mexico) and Moxviquil monumental zone map by Frans Blom digitally redrafted by Elizabeth Paris from the unpublished original on file at the Museo Na Bolom. Abbreviations: Op., operation; Str., structure.
Model outputs for update of occurrence and hunting yield-based data models for wild boar at European scale: new approach to handle the bioregion effect, May 2020 update
<p>These maps are models obtained in intermediate phases of the ENETWILD project based on available information. There are frequent updates in order to improve the results.<br> <br> Objectives:<br> <br> - Incorporate additional data to provide new maps of wild boar suitability with a resolution of 2x2 km >>> file 3_June_2020_suitability_2x2.tif<br> - New model based on hunting yield with different approaches to handle the biorregion effect >>> files 1_June_2020_HY_nut01_10x10_twostep.tif & 2_June_2020_HY_nut01_10x10_pca.tif<br> <br> Model settings and predictors: <br> - Hunting yield modeling including biorregion effect as bioclimatic PCA scores<br> - Hunting yield addressing biorregion effect in a two-step procedure with independent parametrization for each bioregion<br> <br> Conclusions guiding future methodological steps:<br> - For wild boar suitability maps at 2x2 km, additional data on survey effort is critical in the southern bioregion<br> - Hunting yield model predictions at 10x10 km grids overestimated the hunting bag numbers obtained from the external datasets<br> - HY model with independent parametrization for each bioregion performed better that previous and new strategies<br> <br> For further details and methodological approach see the paper:<br> ENETWILD-consortium, P. Acevedo, S .Croft, G C Smith, J. A. Blanco-Aguiar, J. Fernandez-Lopez, M. Scandura, M. Apollonio, E.Ferroglio, Oliver Keuling, M. Sange, S. Zanet, F. Brivio, T. Podgórski, K.Petrović, Soriguer, J. Vicente (2020) update of occurrence and hunting yield-based data models for wild boar at European scale: new approach to handle the bioregion effect. EFSA supporting publication 2020 TO BE COMPLETED<br> <br> Permission for reuse hunting yield outputs is granted under the terms indicated by EFSA.</p>
Data for: Hunting mode and habitat selection mediate the success of human hunters
<p class="MsoNormal"><span>As a globally widespread apex predator, humans have unprecedented lethal and non-lethal effects on prey populations and ecosystems<span>. </span>Yet compared to non-human predators<span>, little is known about the </span>drivers and consequences of<span> </span>human<span> hunt</span>ing behavior<span>.<strong> </strong>Here, we characterized the hunting modes, habi</span>tat selection,<span> and harvest success of 483 rifle hunters in California</span> using<span> high-resolu</span>tion <span>GPS </span>data<span>. We used Hidden Markov Models to characterize fine-scale behavior, and k-means clustering to group hunters by hunting mode, on the basis of their time spent in each behavioral state. Hunters exhibited three distinct and successful hunting modes ("coursing", "stalking", and "sit-and-wait"), with stalking as the most successful strategy. Across hunting modes, there was variation in patterns of selection for roads, topography, and habitat cover, with </span>important<span> differences in habitat use of successful and unsuccessful hunters across modes. Our study indicates that hunters can successfully employ a diversity of harvest strategies, and </span>that<span> hunting success </span>is <span>mediated by the </span>interacting effects of<span> hunting mod</span>e and <span>landscape features. Such results high</span>light the breadth of human hunting modes, even within a single hunting technique, and lend insight into the varied ways that humans exert predation pressure on wildlife.</span></p>
Public perceptions of trophy hunting are pragmatic, not dogmatic
<div> <div> <div> <div> <p>Fierce international debates rage over whether trophy hunting is socially acceptable, especially when people from the Global North hunt well-known animals in sub-Saharan Africa. We used an online vignette experiment to investigate public perceptions of the acceptability of trophy hunting in sub-Saharan Africa among people who live in urban areas of the USA, UK and South Africa. Acceptability depended on specific attributes of different hunts as well as participants' characteristics. Zebra hunts were more acceptable than elephant hunts, hunts that would provide meat to local people were more acceptable than hunts in which meat would be left for wildlife, and hunts in which revenues would support wildlife conservation were more acceptable than hunts in which revenues would support either economic development or hunting enterprises. Acceptability was generally lower among participants from the UK and those who more strongly identified as an animal protectionist, but higher among participants with more formal education, who more strongly identified as a hunter, or who would more strongly prioritize people over wild animals. Overall, acceptability was higher when hunts would produce tangible benefits for local people, suggesting that members of three urban publics adopt more pragmatic positions than are typically evident in polarized international debates.</p> </div> </div> </div> </div>
Individual behaviour, growth, survival and vulnerability to hunting in a large mammal
<p>Humans have exploited wild animals for thousands of years. Recent studies indicate that harvest-induced selection on life-history and morphological traits may lead to ecological and evolutionary changes. Less attention has been given to harvest-induced selection on behavioural traits, especially in terrestrial systems. We assessed in a wild population of large terrestrial mammals whether decades of hunting led to harvest-induced selection on trappability, a proxy of risk-taking behaviour. We investigated links between trappability, horn growth and survival across individuals in early life and quantified the correlations between early life trappability and horn growth with availability to hunters and probability of being shot. We found positive among-individual correlations between early life trappability and horn growth, early life trappability and survival, and early life horn growth and survival. Faster growing individuals were more likely to be available to hunters and shot at a young age. We found no correlations between early life trappability and availability to hunters or probability of being shot. Our results show that correlations between behaviour and growth can occur in wild terrestrial population but may be context dependent. This result highlights the difficulty in formulating general predictions about harvest-induced selection on behaviour, which can be affected by species ecology, harvesting regulations, and harvesting methods used. Future studies should investigate mechanisms linking physiological, behavioural, and morphological traits and how this effects harvest vulnerability to evaluate the potential for harvest to drive selection on behaviour in wild animal populations.</p>
Fig. 1 in Use of filter papers to determine seroprevalence of Toxoplasma gondii among hunted ungulates in remote Peruvian Amazon
Fig. 1. Animals were hunted in the area surrounding the community of Nueva Esperanza, the only permanent settlement located along the Yavarí-Mirín River. The study site's geographic remoteness reflects extremely limited contact with domestic animals and humans, which eliminates the effect of spillover from domestic animals as a potential source of infection for wildlife. The data from this study are likely to shed light on the maintenance of T. gondii in its natural environment.
Datasets for "Recreational hunting as an ecosystem service of restoration in the Bay-Delta watershed"
<p>These are the raw data from two surveys of recreational hunters in northern California conducted from 2019-2021 in association with the Delta Stewardship Council funded project "Recreational hunting as an ecosystem service of restoration in the Bay-Delta watershed" (Agreement #18211). Intercept data were collected in-person at hunt sites during deer, upland gamebird, and waterfowl hunt seasons in 2019-20. Followup survey data were collected online from a subset of the original interceptees as well as No. Cal hunters solicited for participation via social media, snowball sampling, and hunter chatrooms. Headers refer to questionnaires archived in Zenodo at https://doi.org/10.5281/zenodo.5809668.</p>
Figures 7–8. Aporus hirsutus prey transport. 7 in Nesting behavior, ecology, and functional morphology of the trapdoor spider-hunting spider wasp Aporus (Plectraporus) hirsutus (Banks) (Hymenoptera: Pompilidae)
Figures 7–8. Aporus hirsutus prey transport. 7) Aporus hirsutus female dragging Aptostichus simus juvenile backwards across sand, grasping end of its right foreleg with her mandibles. Sandy coastal back dunes, Santa Barbara County, CA; 17 June 2015; A. Abela. Photograph © Alice Abela. 8) Aporus hirsutus female dragging Aptostichus simus juvenile backwards across sand, grasping tibia of its 2nd left leg with her mandibles. The wasp's wings are folded on her dorsum, sandy coastal back dunes, Santa Barbara County, CA; 17 June 2015; A. Abela. Photograph © Alice Abela.
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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)
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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.