Skip to main content
Powered by ShareScore

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.

662

datasets available to search

ShareScore release 0.9.0

Reset

Dataset results

662 results for “Savanna”

Learn how ShareScore rates datasets ↗
zenodo40/100

Figure 8 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 8. Oribatida and Gamasina abundance (tsd. ind./m2) in plots (mb: maize bare, mmdom: maize with DOM). Abundances being significantly different from each other are marked by different letters for each microarthropod group (Wilcoxon signed rank test [p ˂ 0.05]). Error bars = standard error.

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 7 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 7. Collembola, Oribatida and Gamasina abundance (tsd. ind./m2) in plots (mb: maize bare, mbnpk: maize with chemical NPK). Abundances being significantly different from each other are marked by different letters (Wilcoxon signed rank test [p ˂ 0.05]). Error bars = standard error.

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 6 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 6. Effect of Maize cultivation on Collembola, Oribatida and Gamasina in control plots (sav ctrl: savanna, mb: maize bare). Abundances being significantly different from each other are marked by different letters for each microarthropod group (Wilcoxon signedrank test [p ˂ 0.05]). Error bars = standard error.

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 5 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 5. Temporal variation of Collembola, Oribatida and Gamasina abundance (tsd. ind./m2) in savanna and experimental field in (A) 2017 and (B) 2018. Abundance being significantly different from each other in time per treatment are marked by different letters for each microarthropod group (Wilcoxon signed-rank test [p ˂ 0.05]). Months not sampled are marked by asterisks. Error bars = standard error. sav ctrl: savanna, mb: maize bare, mbnpk: maize with chemical NPK fertilizer, mmdom: maize with dry organic matter (DOM).

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 2 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 2. Completely randomized block design of the experimental field; experimental field before sowing (A: 08/05/17) and with maize crop (B: 28/06/17); sav ctrl: savanna untreated (outside). mb(1): maize bare = maize plot without mulch or NPK fertilizer; mbnpk(2): maize bare with NPK = Maize plot treated with NPK fertilizer only and mmdom(3): maize mulch = maize plot treated with mulch only.

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 1 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 1. Weather data for the Ngaoundéré area, Jan. to Dec. 2017 and 2018, provided by Ngaoundéré airport meteorological station; t: temperature, p: precipitation, h: relative humidity; h: averages per month; p: sum per month.

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 3 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 3. Abundances (mean ± S.E.) of Acari and Collembola for the rainy seasons of 2017 (n = 4) and 2018 (n = 4) as well as for the dry season of 2017/18 (n = 2). n sampling campaigns with 9 samples per plot [sav ctrl: savanna; mb: maize bare; mbnpk: maize with chemical NPK fertilizer; mmdom: maize with dead organic matter (DOM)].

opencc-by-4.0Mar 2023View details →
zenodo40/100

Figure 4 in Effect of three different land use types on the temporal dynamics of microarthropod abundance in the high Guinean savanna of Ngaoundéré (Adamawa, Cameroon)

Figure 4. Abundances (mean ± S.E.) of Oribatida and Gamasina for the rainy seasons of 2017 (n = 4) and 2018 (n = 4) as well as for the dry season of 2017/18 (n = 2). n sampling campaigns with 9 samples per plot [sav ctrl: savanna; mb: maize bare; mbnpk: maize with chemical NPK fertilizer; mmdom: maize with dead organic matter (DOM)].

opencc-by-4.0Mar 2023View details →
zenodo40/100

Fire promotes functional plant diversity and modifies soil carbon dynamics in tropical savanna

<p>The dataset associated with the manuscript "Fire promotes functional plant diversity and modifies soil carbon dynamics in tropical savanna" (Teixeira et al.) includes 6 different datasets, for which we provided one metadata.<br>&nbsp;</p> <p><strong>Version 2</strong> includes an update of the biomass data set, including the correct transformation to g/m2 on fine roots biomass data.<br><br><strong>Version 3 </strong>includes an update of the belowground traits data set based on correcting formatting errors in the belowground traits data.&nbsp;<br><br><strong>Version 4 </strong>Sorry for the inconvenience. This version includes the correct updated belowground traits data file based on the correct formatting errors in the belowground trait data.&nbsp;<br><br>fluxes: it includes data related to net ecosystem C&nbsp; and water exchange. NEE and ET from each plot were measured using the LiCOR 7500 infrared gas analyzer (Li-Cor Inc.). See the method section in the manuscript for full details.</p> <p>soil_carbon: it includes carbon soil data.<br><br>biomass_v2: it includes data related to aboveground and belowground biomass. Aboveground data were collected in 0.5m2 subplot and belowground at 0.25m2 at 20cm depth both within 1m2 sampling plot. See the method section in the manuscript for full details.</p> <p>aboveground_traits: all aboveground functional traits from plant species. See the method section in the manuscript for full details.</p> <p>belowground_traitsv3: all roots functional traits from plant species. See the method section in the manuscript for full details.</p> <p>species_composition: plant community composition. See the method section in the manuscript for full details.</p> <p><br><strong>Abstract</strong><br>Fire is an evolutionary environmental filter in tropical savanna ecosystems altering functional diversity and associated C pools in the biosphere and fluxes between the atmosphere and biosphere. Therefore, alterations in fire regimes (e.g. fire exclusion) will strongly influence ecosystem processes and associated dynamics. In those ecosystems, C dynamics and functions are underestimated by the fire-induced offset between C output and input. To determine how fire shapes ecosystem C pools and fluxes in an open savanna across recently burned and fire excluded areas, we measured the following metrics: (I) plant diversity including taxonomic (i.e. richness, evenness) and plant functional diversity (i.e. functional diversity, functional richness, functional dispersion and community weighted means); (II) structure (i.e. above- and below-ground biomass, litter accumulation); and (III) functions related to C balance (i.e. net ecosystem carbon dioxide (CO<sub>2</sub>)<sub> </sub>exchange (NEE), ecosystem transpiration (ET), soil respiration (soil CO<sub>2</sub> efflux), ecosystem water use efficiency (eWUE) and total soil organic C (SOC). We found that fire promoted aboveground live and belowground biomass, including belowground organs, and coarse and fine root biomass, and contributed to higher biomass allocation belowground. Fire also increased both functional diversity and dispersion. NEE and total SOC were higher in burned plots compared to fire-excluded plots whereas soil respiration recorded lower values in burned areas. Both ET and eWUE were not affected by fire. Fire strongly favored functional diversity, fine root, and belowground organ biomass in piecewise SEM models but the role of both functional diversity and ecosystem structure to mediate the effect of fire on ecosystem functions remain unclear. Fire regime will impact C balance, and fire exclusion may lead to lower C input in open savanna ecosystems.</p>

opencc-by-4.0Mar 2021View details →
zenodo40/100

UV radiation accelerates litter decomposition in a valley-type savanna by enhancing microbial community diversity and function

<p><span>We present the data of the study by Gao et al. (202</span><span>4</span><span>): <a name="_Hlk179470571"></a><a name="OLE_LINK42"></a><strong><span>UV radiation accelerates litter decomposition in a valley-type savanna by enhancing microbial community diversity and function</span></strong></span><span>.</span><span> The excel file (Raw Data) includes the following sheets: 1- Radiation (w&middot;m<sup>-2</sup>) variation of UV-A and UV-B during the experimental period. 2- Decay constants (<em>K</em>, yr<sup>&minus;1</sup>) and changes in the mass loss rate of litter under different UV conditions during the experimental period<span>. 3- </span>The content of lignin, cellulose, C, N and P of litter under different UV conditions during the experimental period<span>. 4-</span></span><span> </span><span>16S ASVs under different UV conditions<span>. 5-</span></span><span> </span><span>ITS ASVs under different UV conditions.</span></p>

opencc-by-4.0Nov 2024View details →
zenodo40/100

Data from: A burning issue: Savanna fire management can generate enough carbon revenue to help restore Africa's rangelands and fill Protected Area funding gaps

<p>Many savanna-dependent species in Africa including large herbivores and apex predators are at increasing risk of extinction.&nbsp; Achieving effective management of protected areas (PAs) in Africa where lions live will cost an estimated USD &gt;$1-2 B/year in new funding. We explored the potential for fire management-based carbon-financing programs to fill this funding gap and benefit degrading savanna ecosystems. We demonstrated how introducing early dry season fire management programs could produce potential carbon revenues (PCR) from either a single carbon-financing method (avoided emissions) or from multiple sequestration methods ranging from USD $59.6-$655.9 M/year (at USD $5/ton) or USD $155.0 M&ndash;$1.7 B/year (at USD $13/ton).&nbsp; We highlighted variable but significant PCR for savanna PAs from USD $1.5&ndash;$44.4 M/year per PA. We suggest investing in fire management programs to jump-start the United Nations Decade of Ecological Restoration to help restore degraded African savannas and conserve imperiled keystone herbivores and apex predators.&nbsp;<br> <br> Open Access article:&nbsp;<a href="https://doi.org/10.1016/j.oneear.2021.11.013">https://doi.org/10.1016/j.oneear.2021.11.013</a></p>

opencc-by-4.0Nov 2021View details →
zenodo40/100

Fig. 1 in The impact of land use on species composition and habitat structure in Sudanian savannas - A modelling study in protected areas and agricultural lands of southeastern Burkina Faso

Fig. 1. − Study area including the Pama reserve and neighbouring PAs of the western WAPO complex. The Pama, Tindangou and Madjoari areas are enclaves where agriculture is allowed. The small country map in the lower right shows the position of the study area within Burkina Faso.

opencc-by-4.0Aug 2016View details →
zenodo40/100

Fig. 3 in The impact of land use on species composition and habitat structure in Sudanian savannas - A modelling study in protected areas and agricultural lands of southeastern Burkina Faso

Fig. 3. − Maps of mean maximum plant size (calculated as average of maximum plant size of all species predicted as present within a grid cell). A. Grasses (Poaceae) (30-360 cm); B. Woody species (3-25 m). The color coding stretches from light yellow for the lowest values via orange and red to violet for the highest values.

opencc-by-4.0Aug 2016View details →
zenodo40/100

Fig. 2 in The impact of land use on species composition and habitat structure in Sudanian savannas - A modelling study in protected areas and agricultural lands of southeastern Burkina Faso

Fig. 2. − Maps of species richness. A. All plant species (2-211 spp.); B. Graminoids (0-50 spp.); C. Forbs (0-86 spp.); D. Woody species (0-52 spp.); E. Weedy species (0-48 spp.); F. Non-weedy species (0-140 spp.). The color coding stretches from light yellow for the lowest values via orange and red to violet for the highest values.

opencc-by-4.0Aug 2016View details →
dryad40/100

Data for Diniz et al. (2022) Changing the main course: strong bat visitation to the ornithophilous mistletoe Psittacanthus robustus (Loranthaceae) in a Neotropical savanna (Biotropica)

<p>The Neotropical genus <i>Psittacanthus</i> comprises mostly specialized ornithophilous mistletoes, with rare exceptions. <i>Psittacanthus robustus </i>is a common ornithophilous species from the South American savannas whose bright-yellow flowers secrete copious diluted nectar. Due to a three-day-long anthesis and a short, non-restrictive floral tube, we suggest that the species also serves as a resource for flower-visiting bats. In a Cerrado area in central Brazil, we investigated the usage of the species by bats through systematic bat captures for pollen sampling, its nocturnal nectar secretion dynamics, mating system, and the relative dependence on diurnal and nocturnal pollinators for reproduction. Nine phyllostomid bat species visited <i>P. robustus</i>. Up to 50% of pollen samples from bats contained the species<i> </i>during peak flowering, equating or surpassing the prevalence of chiropterophilous species and representing roughly a third of the floral resources consumed by specialized nectarivores <i>Glossophaga soricina </i>and <i>Anoura caudifer</i>. Flowers actively produced nectar at night with volume and concentration values in the ideal ranges for bat consumption. Nectar is continuously secreted after sunset and accumulates in the absence of visitors. <i>Psittacanthus robustus </i>is self-compatible but seeds are set mostly by diurnal visitors. Nocturnal animals had a low and secondary contribution to plant fitness. This is the second report of bat pollination for the genus <i>Psittacanthus</i>, and the largest assemblage of bat visitors for the family Loranthaceae. Although ornithophilous, <i>P. robustus </i>is an important resource for bats in the Brazilian savanna, potentially representing a mixed or early transitional state towards bat pollination.</p>

opencc-zeroJan 2022View details →
dryad40/100

Environmental drivers of biseasonal anthrax outbreak dynamics in two multi-host savanna systems

<p>Environmental factors are common forces driving infectious disease dynamics. We compared inter-annual and seasonal patterns of anthrax infections in two multi-host systems in southern Africa: Etosha National Park, Namibia, and Kruger National Park, South Africa. Using several decades of mortality data from each system, we assessed possible transmission mechanisms behind anthrax dynamics, examining 1) within- and between-species case correlations, and 2) associations between anthrax mortalities and environmental factors, specifically rainfall and the Normalized Difference Vegetation Index (NDVI). Anthrax cases in Kruger had wide inter-annual variation in case numbers, and large outbreaks seemed to follow roughly a decadal cycle. In contrast, outbreaks in Etosha were smaller in magnitude and occurred annually. In Etosha, the host species commonly affected remained consistent over several decades, although plains zebra (<em>Equus quagga</em>) became relatively more dominant. In Kruger, turnover of the main host species occurred after the 1990s, where the previously dominant host species, greater kudu (<em>Tragelaphus strepsiceros</em>), was replaced by impala (<em>Aepyceros melampus</em>). In both parks, anthrax infections showed two seasonal peaks, with each species having only one peak in a year. Zebra, springbok (<em>Antidorcas marsupialis</em>), wildebeest (<em>Connochaetes taurinus</em>) and impala cases peaked in wet seasons, while elephant (<em>Loxodonta africana</em>), kudu and buffalo (<em>Syncerus caffer</em>) cases peaked in dry seasons. For common host species shared between the two parks, anthrax mortalities peaked in the same season in both systems. Among host species with cases peaking in the same season, anthrax mortalities were mostly synchronized, which may imply similar transmission mechanisms or shared sources of exposure. Between seasons, outbreaks in one species may contribute to more cases in another species in the following season. Higher vegetation greenness was associated with more zebra and springbok anthrax mortalities in Etosha, but fewer elephant cases in Kruger. These results suggest that host behavioral responses to changing environmental conditions may affect anthrax transmission risk, with differences in transmission mechanisms leading to multi-host biseasonal outbreaks. This study reveals the dynamics and potential environmental drivers of anthrax in two savanna systems, providing a better understanding of factors driving biseasonal dynamics and outbreak variation among locations.</p>

opencc-zeroMar 2022View details →
zenodo40/100

Fig. 1 in Avian Communities Of A Mixed Mopane-Acacia Savanna In The Cuvelai Drainage System, North-Central Namibia, During The Dry And Wet Season

Fig. 1. Seasonal changes in percentage contribution of main feeding guilds in avian assemblage in mixed Mopane-Acacia savanna (F — frugivores, G — granivores, I — insectivores, O — other guilds).

opencc-by-4.0Jul 2014View details →
dryad40/100

Data from: Pyrophilic plants respond to post-fire soil conditions in a frequently burned longleaf pine savanna

<p class="RealLife">Fire-plant feedbacks engineer recurrent fires in pyrophilic ecosystems like savannas. The mechanisms sustaining these feedbacks may be related to plant adaptations that trigger rapid responses to fire's effects on soil. Plants adapted for high fire frequencies should quickly regrow, flower, and produce seeds that mature rapidly and disperse post-fire. We hypothesized that offspring of such plants would germinate and grow rapidly, responding to fire-generated changes in soil nutrients and biota. We conducted an experiment using longleaf pine savanna plants that were paired based on differences in reproduction and survival under annual ("more" pyrophilic) vs. less frequent ("less" pyrophilic) fire regimes. Seeds were planted in different soil inoculations from experimental fires of varying severity. The "more" pyrophilic species displayed high germination rates followed by species specific, rapid growth responses to soil location and fire severity effects on soils. In contrast, the "less" pyrophilic species had lower germination rates that were not responsive to soil treatments. This suggests that rapid germination and growth constitute adaptations to frequent fires, and that plants respond differently to fire severity effects on soil abiotic factors and microbes. Further, variable plant responses to post-fire soils may influence plant community diversity and fire-fuel feedbacks in pyrophilic ecosystems.</p>

opencc-zeroJun 2022View details →
zenodo40/100

Interactions between land use, taxonomic group and aspects and levels of diversity in a Brazilian savanna: implications for the use of bioindicators

<p>The study was carried out&nbsp;in&nbsp;the&nbsp;Tri&acirc;ngulo&nbsp;Mineiro region of Minas Gerais state, covering the municipalities of&nbsp;Uberl&acirc;ndia, Monte&nbsp;Alegre,&nbsp;and Nova Ponte,&nbsp;in&nbsp;south-eastern&nbsp;Brazil.&nbsp;We&nbsp;conducted the study&nbsp;in&nbsp;five habitat types,&nbsp;comprising&nbsp;two&nbsp;natural&nbsp;habitats&nbsp;(savanna&nbsp;and&nbsp;semideciduous forest),&nbsp;and three anthropogenic land-uses:&nbsp;cattle pastures (planted with&nbsp;introduced&nbsp;Urochloa&nbsp;grasses),&nbsp;soy fields (where sampling took place when plants were at the vegetative phase)&nbsp;and&nbsp;&nbsp;plantations&nbsp;of&nbsp;Eucalyptus&nbsp;trees&nbsp;(&ge;&nbsp;6&nbsp;yrs&nbsp;old).&nbsp;Ants&nbsp;and beetles&nbsp;were sampled&nbsp;at&nbsp;the same&nbsp;40 sites (8&nbsp;replicates&nbsp;per&nbsp;land use), and birds&nbsp;at&nbsp;30 sites (6&nbsp;replicates&nbsp;per land use), only some of which were the same as for ants and beetles.&nbsp;</p> <p>Ants&nbsp;that forage on ground&nbsp;and&nbsp;dung beetles&nbsp;were sampled&nbsp;using&nbsp;pitfall traps. Sampling took&nbsp;place in&nbsp;November&nbsp;and December&nbsp;(early wet season)&nbsp;2017.&nbsp;In each site, eight traps were&nbsp;installed with traps located at the corners of a 100&times;100&nbsp;m square, and at the mid-points of&nbsp;the sides of the square,&nbsp;keeping a&nbsp;minimum distance of 50&nbsp;m between&nbsp;any two&nbsp;traps.&nbsp;All traps were at least 75 m distant from the edge of the respective land&nbsp;use.&nbsp;Traps were plastic containers (19 cm&nbsp;diam, 11 cm height) filled with 150 ml of a saline solution and detergent. Each trap had a wire hoop suspended over it to accommodate a small (4 cm&nbsp;diam, 4 cm height) plastic container for holding a dung bait. We used a 20 cm&nbsp;diameter plastic cover supported by three sticks to protect traps from rain. Traps were baited with&nbsp;~40 g of a mixture of pig dung and human&nbsp;faeces&nbsp;(4:1 proportion)&nbsp;and left in the field for 48-hrs.</p> <p>Birds were surveyed&nbsp;using&nbsp;20-min point counts in the rainy season (November 2017 to March 2018). At each site,&nbsp;five sampling points were established, 200 m distant from each other. All surveys started at sunrise (about 6 a.m.), and all species seen or heard from each point were recorded. Each sampling site was&nbsp;re-surveyed&nbsp;in the&nbsp;following&nbsp;dry season (April to&nbsp;October to 2018); however, for logistic reasons we were unable to re-survey the plantation sites.&nbsp;</p> <p>Ant&nbsp;and dung beetle&nbsp;species were identified to&nbsp;species or morphospecies&nbsp;by comparison with named species in the Zoological Collection at the Federal University of&nbsp;Uberl&acirc;ndia&nbsp;(UFU)&nbsp;or&nbsp;with&nbsp;specialist assistance from Fernando Vaz de Mello, respectively.&nbsp;Vouchers of&nbsp;all&nbsp;species have been deposited&nbsp;at&nbsp;UFU&acute;s Zoological Collection.&nbsp;Birds were identified directly in the field and species&nbsp;names follow the checklist produced by the Brazilian Ornithological Records Committee.</p> <p>We classified species&nbsp;functionally&nbsp;based on&nbsp;primary diet, foraging&nbsp;location&nbsp;and/or&nbsp;behaviour, and body size,&nbsp;as&nbsp;these&nbsp;traits&nbsp;are known to be sensitive&nbsp;to habitat modifications&nbsp;and of importance for the ecosystem services provided by ants, birds, and dung beetles.</p> <p>Ant species were classified according to their diet as&nbsp;predators,&nbsp;fungivores,&nbsp;nectarivores&nbsp;or omnivores,&nbsp;and according to their main foraging location&nbsp;as arboreal, epigeal&nbsp;(aboveground)&nbsp;or hypogeal&nbsp;(in soil and litter), based on&nbsp;information provided by Brown (2000) and Silvestre&nbsp;et al.&nbsp;(2003). Species were&nbsp;further&nbsp;classified&nbsp;into four body size categories based on&nbsp;our&nbsp;measurements of body length&nbsp;(Weber&acute;s length;&nbsp;Brown,&nbsp;1953)&nbsp;of&nbsp;1-5&nbsp;ant workers&nbsp;per species:&nbsp;1 (&lt; 0.75&nbsp;mm),&nbsp;2 (0.75-1.74&nbsp;mm),&nbsp;3 (1.75-3&nbsp;mm),&nbsp;and 4 (&gt; 3 mm).</p> <p>Dung beetles were classified as coprophagous, necrophagous, frugivore, generalist or predator, according to the type of food resource each species is most&nbsp;often&nbsp;attracted to. This classification was based on over 30 years of field experience&nbsp;throughout Brazil&nbsp;by one of the authors&nbsp;of this study&nbsp;(FVM),&nbsp;who used multiple types of baits&nbsp;(e.g., carcasses, fruits, faeces)&nbsp;to attract and collect dung beetles, and/or on literature information.&nbsp;Although information about the &ldquo;attractiveness&rdquo; of different types of baits&nbsp;to&nbsp;dung beetles (used here as a proxy for primary diet)&nbsp;was&nbsp;not obtained&nbsp;directly&nbsp;in the sites of the present study, it is importat to note that we are not aware of&nbsp;any evidence&nbsp;of geographic or habitat&nbsp;variation in bait preference&nbsp;among tropical species of dung beetles.&nbsp;Dung beetles&nbsp;were also&nbsp;classified&nbsp;according&nbsp;to&nbsp;their&nbsp;foraging&nbsp;behaviour as:&nbsp;telecoprid&nbsp;(species that make a dung ball and roll it away for burial),&nbsp;paracoprid&nbsp;(species that store dung in tunnels dug immediately below the dung&nbsp;source),&nbsp;or&nbsp;endocoprid&nbsp;(species living within or immediately below the dung, without moving it).&nbsp;For this,&nbsp;we used&nbsp;the database of the&nbsp;Zoological Collection&nbsp;of&nbsp;the Federal University&nbsp;of&nbsp;Mato Grosso (UFMT).&nbsp;Whenever sample sizes&nbsp;allowed, 30&nbsp;individuals from each species&nbsp;were weighed for determination of body mass&nbsp;(following Almeida et al.,&nbsp;2011), and species were&nbsp;classified&nbsp;according to the following ordinal scale: 1&nbsp;(&lt;&nbsp;10&nbsp;mg);&nbsp;2&nbsp;(10-99&nbsp;mg);&nbsp;3&nbsp;(100-300&nbsp;mg);&nbsp;and&nbsp;4&nbsp;(&gt;300&nbsp;mg).</p> <p>Each bird&nbsp;species&nbsp;was&nbsp;classified according to&nbsp;its&nbsp;primary diet as&nbsp;frugivores granivore, insectivore, nectarivore,&nbsp;carnivore,&nbsp;detritivore,&nbsp;or omnivore,&nbsp;and according to the main&nbsp;foraging&nbsp;location&nbsp;as&nbsp;ground, understory/shrubby vegetation, or tree canopy, based on&nbsp;the&nbsp;Wilman&nbsp;et al.&nbsp;(2014) database and&nbsp;our&nbsp;own&nbsp;field experience.&nbsp;Using these&nbsp;same sources,&nbsp;we obtained information&nbsp;on&nbsp;mean body weights of each&nbsp;species and&nbsp;assigned&nbsp;them&nbsp;to one of&nbsp;five&nbsp;size categories: 1-&nbsp;(&lt;15 g);&nbsp;2&nbsp;(15-39 g);&nbsp;3&nbsp;(40-199&nbsp;g);&nbsp;4&nbsp;(200-599 g);&nbsp;and 5&nbsp;(&gt;&nbsp;600 g).</p>

opencc-by-4.0Aug 2022View details →
dryad40/100

Savanna monkey (Chlorocebus spp.) population genetics/genomics pipeline

<p>In the last 300 thousand years, the genus <em>Chlorocebus</em> expanded from equatorial Africa into the southernmost latitudes of the continent, where colder climate was a likely driver of natural selection. We investigated population-level genetic variation in the mitochondrial uncoupling protein 1 (<em>UCP1</em>) gene region—implicated in non-shivering thermogenesis (NST)— in 73 wild savanna monkeys from three taxa representing this southern expansion (<em>Chlorocebus</em> <em>pygerythrus</em> <em>hilgerti</em>, <em>Chlorocebus</em> <em>cynosuros</em> and <em>Chlorocebus</em> <em>pygerythrus</em> <em>pygerythrus</em>) ranging from Kenya to South Africa. We found 17 SNPs with extended haplotype homozygosity consistent with positive selective sweeps, 10 of which show no significant linkage disequilibrium with each other. Phylogenetic generalized least-squares modelling with ecological covariates suggests that most derived allele frequencies are significantly associated with solar irradiance and winter precipitation, rather than overall low temperatures. This selection and association with irradiance are demonstrated by a relatively isolated population in the southern coastal belt of South Africa. We suggest that sunbathing behaviours common to savanna monkeys, in combination with the strength of solar irradiance, may mediate adaptations to thermal stress via NST among savanna monkeys. The variants we discovered all lie in non-coding regions, some with previously documented regulatory functions, calling for further validation and research.</p>

opencc-zeroSep 2022View details →

ScienceDex guides

Understand access before you commit

These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.

Compare curated 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.

allen-brain-atlas
neuroscienceopenDocumentation, web resources, and API references are available online.
Last verified 2026-04-30Open record

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.

abode-home-cage
behavioral-neuroscienceopenThe DataShare record exposes download links for annotations, documentation, license text, and the zipped per-snippet data directory.
Last verified 2026-04-30Open record

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.

dandi-nwb
electrophysiologyopenPublished Dandiset metadata and archive endpoints are available through the production DANDI API.
Last verified 2026-04-30Open record

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.

ibl
behavioral-neuroscienceopenPublic sessions can be searched and loaded from the IBL public data server through ONE.
Last verified 2026-04-29Open record

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.

openneuro
neuroscienceopenPublished datasets are available on demand over the internet.
Last verified 2026-04-29Open record