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.
518
datasets available to search
ShareScore release 0.7.1
Dataset results
518 results for “life history traits”
Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India
<p>This dataset contains compiled Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India. The list of species included are mainly from the following two related publications:<br>- Muthuramkumar, S., Ayyappan, N., Parthasarathy, N., Mudappa, D., Raman, T.R.S., Selwyn, M.A. and Pragasan, L.A. (2006), <a href="https://doi.org/10.1111/j.1744-7429.2006.00118.x">Plant Community Structure in Tropical Rain Forest Fragments of the Western Ghats, India</a>. <em>Biotropica</em>, 38: 143-160. https://doi.org/10.1111/j.1744-7429.2006.00118.x<br>- Osuri, A., Chakravarthy, D., Mudappa, D., Raman, T., Ayyappan, N., Muthuramkumar, S., & Parthasarathy, N. (2017). <a href="http://httpd//doi.org/10.1017/S0266467417000219">Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India</a>. <em>Journal of Tropical Ecology</em>, 33(4), 270-284. doi:10.1017/S0266467417000219<br>The present dataset is an expanded and updated version of the related dataset available at <a href="https://doi.org/10.5061/dryad.vd0nn">https://doi.org/10.5061/dryad.vd0nn</a><br> <br>Species traits information was collated from <a href="http://www.biotik.org/">BIOTIK (http://www.biotik.org/</a>), <a href="http://www.flowersofindia.net/">Flowers of India (http://www.flowersofindia.net/)</a>, India Biodiversity Portal (http://indiabiodiversity.org/), <a href="https://doi.org/10.5061/dryad.234/1">Global wood density database (https://doi.org/10.5061/dryad.234/1)</a> and <a href="https://doi.org/10.1017/S0266467417000219">Osuri et al. (2014): https://doi.org/10.1017/S0266467417000219</a>. We also referred to the following previous studies that provided information on the successional status of rain-forest species in the Western Ghats (Chetana 2013, Pascal 1988, Raman et al. 2009, Sreejith 2005).</p> <p><strong>References:</strong><br>CHETANA, H. C. 2013. Assessing the ecological processes in abandoned tea plantations and its implication for ecological restoration in the Western Ghats, India. PhD thesis, Manipal University.<br>OSURI, A. M., KUMAR, V. S. & SANKARAN, M. 2014. Altered stand structure and tree allometry reduce carbon storage in evergreen forest fragments in India’s Western Ghats. <em>Forest Ecology and Management </em>329: 375–383.<br>PASCAL, J. P. 1988. <em>Wet evergreen forests of the Western Ghats of India: Ecology, structure, floristic composition and succession</em>. Institut Français de Pondichéry, Pondicherry.<br>RAMAN, T. R. S., MUDAPPA, D. & KAPOOR, V. 2009. Restoring rainforest fragments: survival of mixed-native species seedlings under contrasting site conditions in the Western Ghats, India. <em>Restoration Ecology</em> 17:137–147.<br>SREEJITH, K. A. 2005. Ecological and ecophysiological studies on the successional status of tree seedlings in tropical wet evergreen and semi-evergreen forests of Kerala. PhD thesis, Forest Research Institute, Dehradun.</p> <p><strong>Geographic Coverage:</strong><br>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India<br>2. GPS coordinates: Valparai Plateau (10°15'- 10°22'N, 76°52' - 76°59'E); Anamalai Tiger Reserve (10°12' - 10°35'N, 76°49' - 77°24'E)</p> <p><strong>Temporal Coverage:</strong><br>1. Begins: 2003-03-01 (Year, Month, Day)<br>2. Ends: 2024-02-10 (Year, Month, Day)</p> <p>Besides the <strong>README.txt</strong> file, the dataset includes the following comma-delimited text (csv) file with the data in columns as explained below:</p> <p><strong>Anamalai_tree_traits_2024.csv</strong></p> <p><strong>spec_name_ORIG:</strong> Scientific name of the species used during the data collection<br><strong>genus:</strong> Genus of the taxon<br><strong>specificEpithet:</strong> Specific epithet of the taxon in the Latin binomial name<br><strong>Accept_name_WFO:</strong> Updated scientific name of the species as in Plants of the World Online (POWO, https://powo.science.kew.org/)<br><strong>Habit:</strong> life form of the species(tree/shrub/cane/palm)<br><strong>Distribution:</strong> Distribution of the species in the study area (Native/Endemic/Introduced)<br><strong>IUCN_status:</strong> IUCN status of the species (CR-Critically Endangered,DD-Data deficient,EN-Endangered,LC-Least Concern,NT-Near Threatened,VU-Vulnerable,NA-Unknown)<br><strong>Wden_final:</strong> Wood density value assigned for the species (g cm^-3); NA - not available; sourced from Global wood density database (https://doi.org/10.5061/dryad.234/1)<br><strong>wd_level:</strong> Level in which the wood density value belongs (Species - wood density value is from species level; genus - wood density value assigned is the genus level average value)<br><strong>fruit_type:</strong> Morphological type of fruit<br><strong>fleshy_dry:</strong> Whether fruit is a dry fruit or fleshy, with aril or other parts <br><strong>seed_size:</strong> Species seed size: L = Large (>3 cm); M = Medium (1-3 cm); S = Small (<1 cm)<br><strong>disperser:</strong> Categories indicating seed dispersal mode: Bird, mammal, bird and mammal (Mammal_bird), gravity, wind, or unknown<br><strong>habitat:</strong> Habitat affinity category: EG_edg - evergreen forest edge; EG_for - evergreen forest; Dec_for - deciduous forest; Int – Introduced species; Unknown – Unknown<br><strong>habt_new:</strong> Habitat affinity new category: Mature – mature forest; Secondary – secondary forest, NA - unknown/Introduced species<br><strong>ad_ht:</strong> Species maximum adult height (m)</p>
Life History Traits of Resprouting Puerto Rican Tropical Dry Forest Trees, Guánica Forest, 1981-2018
This dataset provides trait and demographic data for 44 tropical dry forest tree species from the Guánica State Forest in southwest Puerto Rico. The study area spans 4,500 ha of semi-deciduous TDF, where the sampled species represent over 90% of all individuals with a diameter at breast height (dbh) ≥2.5 cm. The dataset integrates ten functional traits, combining newly collected measurements (2017–2018) with previously published data (Vargas et al. 2021b). Previously published data includes xylem-specific hydraulic conductivity (ks), Huber value (hv), and hydraulic safety margin (HSM), with species-level data availability ranging from 19 to 44 species, except for HSM, which was measured for six species. Trait measurements were primarily collected during the wet season (August–November), except stomatal behaviour traits (psimax, psidv, and gsmax), which were assessed during the winter dry season before leaf fall. Demographic data encompass species-specific growth rates and annual survival rates for adult trees, derived from four permanent census plots (625 m² to 10,000 m²) distributed across the forest. These plots, established in mature upland TDF on limestone substrates with mollisol soils, were monitored between 1992 and 2019. Growth rate estimates are based on diameter increments recorded at regular censuses over 20.4–26.4 years. Survival rates were calculated over a 21-year period (1998–2019), mitigating the influence of extreme drought events. Standardised measurement protocols ensured data consistency, including repeated diameter assessments at multiple stem locations and the exclusion of wet-season measurements to prevent water-related swelling artifacts. Growth rates were derived from the regression slope of dbh against time, incorporating a minimum of two dbh measurements per individual (following Poorter et al. 2010). Annual survival rate was calculated over a 21-year timespan (1998–2019) to avoid bias introduced by an intense drought in 1997. The followin
Potential effects of invasive plants on mosquito life-history traits.
<p>Invasive plants offer suitable oviposition sites for some vector species (a); invasive plant litter increases proliferation of immature vectors (b); dense canopy cover or thickets of invasive plants provide suitable micro-habitats for adult mosquitoes (c); nectariferous flowers (d) and extra-floral glands (e) of invasive plants are important sugar sources for adult vectors; invasive plants can influence the pathogen transmission ability of the vector (f).</p> <p>A grey-scaled version was published as Figure 1 in <a href="https://doi.org/10.3390/v13010032">Agha et al. (2020)</a>.</p> <p>Required software: <a href="https://krita.org/">Krita</a> and <a href="https://www.gimp.org/">Gimp</a>.</p>
Sharkipedia: A Curated Open Access Database of Shark and Ray Life History Traits and Abundance Time-series
<p>This dataset represent the intial launch of Sharkipedia: a curated open access database of shark and ray life history traits and abundance time-series. A curated database of shark and ray biological data is increasingly necessary both to support fisheries management and conservation efforts, and to test the generality of hypotheses of vertebrate macroecology and macroevolution. Sharks and rays are one of the most charismatic, evolutionary distinct, and threatened lineages of vertebrates, comprising around 1,250 species. To accelerate shark and ray conservation and science, we developed Sharkipedia as a curated open-source database and research initiative to make all published biological traits and population trends accessible to everyone. Sharkipedia hosts information on 58 life history traits from 264 sources, for 170 species, from 39 families, and 12 orders related to length (n=9 traits), age (8), growth (12), reproduction (19), demography (5), and allometric relationships (5), as well as 871 population time-series from 202 species. Sharkipedia relies on the backbone taxonomy of the IUCN Red List and the bibliography of Shark-References. Sharkipedia has profound potential to support the rapidly growing data demands of fisheries management, international trade regulation as well as anchoring vertebrate macroecology and macroevolution.</p>
Figure 7 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 7. Mean number of (a) above-ground nesting bee individuals, (b) floral specialist bee individuals, (c) oligolectic bee individuals and (d) oil-collecting bee individuals in cropped area (n = 28 points) and semi-natural area (n = 11 points). ns indicates a non-significant result. Asterisks indicate that means are significantly different (Wilcoxon rank sum test, ** = P <0.01). Bars show SEs.
Figure 2 in Diversity and life-history traits of wild bees (Insecta: Hymenoptera) in intensive agricultural landscapes in the Rolling Pampa, Argentina
Figure 2. Semi-natural area of the study site: (a) semi-natural grassland; (b) the stream 'Arroyo Dulce' and its banks (Photos: Violette Le Féon).
Figure 10. Spheniopsis brasiliensis. A in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 10. Spheniopsis brasiliensis. A transverse section through the heart. AM, Amoebocyte; AU, auricle; PE, pericardium; PEG, pericardial gland; R, rectum; SM, suspensory membrane; V, ventricle.
Figure 3. Spheniopsis brasiliensis. A in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 3. Spheniopsis brasiliensis. A ventral view of the septum, foot and mouth. BG, Byssal groove; F, foot; F(T), 'toe' of foot; M, mouth; SE, septum; SEM, margin of septal membrane; SEP(1),(2),(3),(4), septal pores.
Figure 1 in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 1. Spheniopsis brasiliensis. SEM views of the siphonal apparatus. (A) Posterior view of the exhalant and inhalant siphons, with three and four siphonal papillae, respectively. (B) Higher magnification view of a single siphonal papilla with a terminal array of sensory cilia. CI, Cilia; ES, exhalant siphon; IS, Inhalant siphon; SP, sensory papilla; SPB, base of sensory papillae.
Figure 9. Spheniopsis brasiliensis. A in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 9. Spheniopsis brasiliensis. A transverse section through the pedal ganglia and the statocysts. PEGA, Pedal ganglia; STAT, statocyst; STL, statolith.
Figure 5 in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 5. Spheniopsis brasiliensis. Transverse sections through the (A) oesophagous; (B) crystalline style sac; (C) mid gut; (D) hind gut; and (E) rectum, all drawn to the same scale. CC, Collagen coat; CS, crystalline style.
Figure 8. Spheniopsis brasiliensis. A transverse section through a in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 8. Spheniopsis brasiliensis. A transverse section through a single digestive tubule. AM, Amoebocyte; CRC, crypt cell; DC, digestive cell.
Figure 4. Spheniopsis brasiliensis. A in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 4. Spheniopsis brasiliensis. A transverse section through the stomach in the region of the conjoined style sac and mid gut. CS, Crystalline style; CSMG, conjoined style sac and mid gut; CSS, crystalline style sac; FIPI, fragments of ingested prey; GS, gastric shield; MG, mid gut; SC, secretory cells.
Figure 7 in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 7. Spheniopsis brasiliensis. Histological sections through the visceral mass and ingested prey items. (A) A transverse section through the stomach with ingested prey items inside it. (B, C) The remains of captured and ingested ostracods. (D) The skeletal remains of an unknown prey item. CSS, Crystalline style sac; GS, gastric shield; IPI, ingested prey item; ST, stomach.
Figure 12. Spheniopsis brasiliensis. A section through a in The organs of prey capture and digestion in the miniature predatory bivalve Spheniopsis brasiliensis (Anomalodesmata: Cuspidarioidea: Spheniopsidae) expose a novel life-history trait
Figure 12. Spheniopsis brasiliensis. A section through a portion of a gonadial follicle. C, Cuticle; DN, dividing nucleus; DO, developing oocyte; EO, encapsulated oocyte; GE, germinal epithelium; N, nucleus; RT, regressing testes; STA, stalk; SPZ, spermatozoan; Y, yolk.
Efficient assays to quantify the life history traits of algal viruses
<p>Data and analysis files accompanying the paper 'Efficient assays to quantify the life history traits of algal viruses' (Lievens et al. 2023, Applied & Environmental Microbiology). Includes data and code for the modified one-step growth (mOSG) assay, modified survival (mS) assay, and comparison of the two assays.</p> <p>The only difference with the previous version of this package (doi 10.5281/zenodo.6573770) is that two typos were corrected in the file "mOSG & mS comparison.rmd" (lines 172 & 182; corrections noted in the script).</p>
Thermal performance of Aedes sierrensis life history traits for populations collected across the species range
<p>How mosquitoes may respond to rapid climate warming remains unknown for most species, but will have major consequences for their future distributions, with cascading impacts on human well-being, biodiversity, and ecosystem function. We investigated the adaptive potential of a wide-ranging mosquito species, <em>Aedes sierrensis</em>, across a large climatic gradient by conducting a common garden experiment measuring the thermal limits of mosquito life history traits. Although field-collected populations originated from vastly different thermal environments that spanned over 1,200 km, we found limited variation in upper thermal tolerance between populations. In particular, the upper thermal limits of all life history traits varied by <3°C across the species range and, for most traits, did not differ significantly between populations. For one life history trait—pupal development rate—we did detect significant variation in upper thermal limits between populations, and this variation was strongly correlated with source temperatures, providing evidence of local thermal adaptation for pupal development. However, we found that maximum environmental temperatures across most of the species' range already regularly exceed the highest upper thermal limits estimated under constant temperatures. This result suggests that strategies for coping with and/or avoiding thermal extremes are likely key components of current and future mosquito thermal tolerance.</p>
Figure 8 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 8. Hypothesized life cycle of Plesionika edwardsii in the Azorean region. After the incubation period of shrimp eggs, (1) larvae are released into the water column and (2) juveniles develop in shallow waters. Mature females and males are distributed up to 600 m with a sexual segregation by depth: (3) non-ovigerous females are mainly found up to 200 m, (4) ovigerous females between 200 and 300 m, and (5) males from 400 to 500 m deep. Females are bigger than males, and ovigerous females are bigger than nonovigerous females. A bigger-deeper trend is observed up to 400 m. (6) Long larval stages of P. edwardsii increases its potential for dispersal (Landeira et al., 2009), favoring connectivity and stock homogeneity between adjacent areas.
Figure 5 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 5. Sex ratio of Plesionika edwardsii by depth stratum in the Azorean region during the period 1999–2000.
Figure 2 in Unraveling distributional patterns and life-history traits of a deep-water shrimp Plesionika edwardsii (Decapoda, Pandalidae) under unexploited virgin conditions: a benchmark for fisheries management
Figure 2. Seasonal predicted mean catch per unit effort (CPUE, g trap-1) by depth stratum for males, non-ovigerous and ovigerous females of Plesionika edwardsii in the Azorean region for the period 1999–2000. Light-colored symbols represent raw data. Detailed parameter estimates are in Tab. S4.
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.