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2,291 results for “life history”
Life History of a Climax Forest in Pisgah State Forest in Winchester NH 1929-1930
Old-growth forest is uncommon across the northeastern United States, as most areas have been historically cleared for agriculture or harvested for timber. This study provides rare direct insight into the overstory and midstory dynamics across a semi-contiguous old-growth landscape in New England. Pisgah State Park in southwestern New Hampshire comprises 5300 ha of Hardwoods-Hemlock-White Pine forest, all but 300 ha of which was cutover by the 1880s. To protect a high-quality, old-growth stand from harvest, Harvard Forest purchased a 10 ha tract (the Harvard Tract) in 1927. In 1929 and 1930, Branch, Daley, and Lotti located and sampled all of the known remaining old-growth stands in the Pisgah area. This included 74 0.04 ha old-growth stands, 14 of which were located the Harvard Tract. They also surveyed 27 0.04 ha stands that had been cut just prior to the study (stump plots), where stumps as well as the remaining overstory trees were recorded. Note that only 61 old-growth plots and 23 stump plots have valid measurements. Species, diameter class, and position (overstory or midstory) were recorded for each tree; cover type, elevation, and location was described for each plot. Dead and downed trees were also recorded.
Life histories of the perennial geophyte Erythronium grandiflorum (Liliaceae) in Colorado subalpine transplant garden from annual measurements, 1991 onward
In an outdoor garden at Irwin, Colorado, we established glacier lily plants in open-bottomed PVC pots that protected them from gopher attack. The initial cohorts were excavated from field sites as mature corms of unknown age. Later cohorts were grown from seed, so their ages are known. Each spring since 1991, we have noted fruit and flower production. In August, after the aboveground parts have died back, we exhume the plants, wash off the soil, weigh the corms, characterize their morphology, photograph them, and replant them. If a corm splits, we replant the pieces in separate pots. The study is ongoing, with 264 plants in 2019. Main findings through 2020: plants produce 0-4 flowers per year, depending on size; most plants flower each year; death is rare, with many plants having survived the entire study; setting a fruit reduces corm substantially (cost of reproduction); plants appear to regulate weight by adjusting flower production, and by splitting; genotypes vary in splitting propensity. Oddly, mortality is higher in very large corms than in mid-sized ones. Evidence for senescence is scant.
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
Density independent prey choice, taxonomy, life history and web characteristics determine the diet and biocontrol potential of spiders (Linyphiidae and Lycosidae) in cereal crops - Dataset
<p>Materials and Methods</p> <p>Fieldwork</p> <p>Money spiders (Araneae: Linyphiidae) and wolf spiders (Araneae: Lycosidae) were the two most common families present in these field surveys, so were prioritised for collection. Spiders were visually located along transects in two adjacent barley fields at Burdons Farm, Wenvoe in South Wales (51°26'24.8"N, 3°16'17.9"W) and collected from occupied webs and the ground, between April and September 2018. Surveys and sampling were conducted five days per week across this period. Each transect was adjacent to a randomly selected tramline and they were distributed across the entire field. The areas searched were 4 m<sup>2</sup> quadrats at least 10 m apart and all observed linyphiids and lycosids were collected in approximately 15-minute searches. The spiders included in this study were taken from 64 locations across 24 days (Supplementary Table 3) along the aforementioned transects. Spiders were individually placed into 1.5 ml microcentrifuge tubes containing 100 % ethanol using an aspirator, regularly changing meshing, at least every five spiders, to limit potential cross-contamination between spiders (spiders were also subsequently washed during transferral to fresh ethanol at the identification and, separately, dissection stages). Linyphiids occupying webs were prioritised for collection, but ground-active linyphiid spiders were also collected. For each spider taken from a web, the height of the web from the ground and its approximate dimensions were recorded, the latter calculated as approximate web area. Spiders were taken to Cardiff University, transferred to fresh ethanol, adults identified to species-level and juveniles to genus, and stored at -80 °C in 100 % ethanol until subsequent DNA extraction. To obtain data on local prey density, 4 m<sup>2</sup> of ground and crop stems were suction sampled using a ‘G-vac’ for 30 seconds at each quadrat from which spiders were collected, with the collected material emptied into a bag, any organisms immediately killed with ethyl-acetate and material frozen for storage before sorting into 70 % ethanol in the lab.</p> <p>All invertebrates were identified to family level due to the restriction of many of the metabarcoding-derived dietary data to this level, and the difficulty associated with finer taxonomic resolution of many taxa. Exceptions included springtails of the superfamily Sminthuroidea (Sminthuridae and Bourletiellidae, which were often indistinguishable following suction sampling and preservation due to the fine features necessary to distinguish them) which were left at super-family, mites (many of which were immature or in poor condition) which were identified to order level and wasps of the superfamily Ichneumonoidea (which were identified no further due to obscurity of wing venation due to damage).</p> <p> </p> <p>Extraction and high-throughput sequencing of spider gut DNA</p> <p>Given their prevalence in field collections, dietary analysis was carried out for the linyphiid genera <em>Erigone</em>, <em>Tenuiphantes</em>, <em>Bathyphantes</em> and <em>Microlinyphia </em>(Araneae: Linyphiidae), and the Lycosidae genus <em>Pardosa</em>. Spiders were transferred to and washed in fresh 100 % ethanol to reduce external contaminants prior to identification via morphological key <sup>1</sup>. Abdomens were removed from spiders and again washed in and transferred to fresh 100 % ethanol. DNA was extracted from the abdomens via Qiagen TissueLyser II and DNeasy Blood & Tissue Kit (Qiagen) as per the manufacturer protocol, but with an extended lysis time of 12 hours to account for the complex and branched gut system in spider abdomens <sup>2</sup>. At least one extraction negative (blank tubes treated identically to samples) was included per 12 spiders (each extraction typically contained 24 spiders, thus two extraction negatives), which was included in subsequent PCR and high-throughput sequencing to detect instances of lab/reagent contamination.</p> <p>For amplification of DNA, two primer pairs were used. BerenF-LuthienR <sup>3</sup> amplified a broad range of invertebrates including spiders, and TelperionF-LaureR, amplified a range of invertebrates but fewer spiders (modified from TelperionF-LaurelinR <sup>3</sup> via one base-pair change from Laurelin; 5’-ggrtawacwgttcawccagt-3’). Primers were labelled with unique 10 bp molecular identifier tags (MID-tags) so that each individual had a unique pairing of forward and reverse tags for identification of each spider post-sequencing. PCR reactions of 25 µl contained 12.5 µl Qiagen PCR Multiplex kit, 0.2 µmol (2.5 µl of 2 µM) of each primer and 5 µl template DNA. Reactions were carried out in the same thermocycler, optimised via temperature gradient, with an initial 15 minutes at 95 °C, 35 cycles of 95 °C for 30 seconds, the primer-specific annealing temperature for 90 seconds and 72 °C for 90 seconds, respectively, followed by a final extension at 72 °C for 10 minutes. BerenF-LuthienR and TelperionF-LaureR used annealing temperatures of 52 °C and 42 °C, respectively.</p> <p>Within each PCR 96-well plate, 12 negative controls (extraction and PCR), 2 blank controls and 2 positive controls were included (i.e. 80 samples per plate), based on Taberlet <em>et al. </em>(2018). Positive controls were mixtures of invertebrate DNA comprised of non-native Asiatic species in four different proportions (Supplementary Table 1) and blanks were empty wells within each plate to identify tag-jumping into unused MID-tag combinations. PCR negative controls were DNase-free water treated identically to DNA samples. A negative control was present for each MID-tag to identify any contamination of primers. All PCR products were visualised in a 2 % agarose gel with SYBRSafe (Thermo Fisher Scientific, Paisley, UK) and placed in categories based on their relative brightness. The concentration of these brightness categories was quantified via Qubit dsDNA High-sensitivity Assay Kits (Thermo Fisher Scientific, Waltham, MA, USA) with at least three representatives of each category per plate. The PCR products were then proportionally pooled according to these concentrations. Each pool was cleaned via SPRIselect beads (Beckman Coulter, Brea, USA), with a left-side size selection using a 1:1 ratio (retaining ~300-1000 bp fragments). The concentration of the pooled DNA was then determined via Qubit dsDNA High-sensitivity Assay Kits and pooled together into one library per primer pair. Library preparation for Illumina sequencing was carried out on the cleaned libraries via NEXTflex Rapid DNA-Seq Kit (Bioo Scientific, Austin, USA) and samples were sequenced on an Illumina MiSeq via a V3 chip with 300-bp paired-end reads (expected capacity ≤25,000,000 reads). Bioinformatic analysis followed (Drake et al., 2021; Supplementary Information 1).</p> <p> </p> <p>Statistical analysis</p> <p>All analyses were conducted in R v4.0.0 <sup>6</sup>. Initial multivariate analyses used binary data (i.e., presence/absence) given the various problems inherent to quantifying metabarcoding data <sup>7,8</sup>. Prey species that occurred only once across all of the dietary samples were removed before further analyses to prevent outliers skewing the results, which is particularly problematic for non-metric multidimensional scaling. Spider diets were compared between variables using multivariate generalized linear models (MGLMs) via ‘manyglm’ in the ‘mvabund’ package <sup>9</sup> with a binomial error family and Monte Carlo resampling. Model independent variables included spider genus, spider life stage (juvenile or adult, the latter defined by fully developed genitalia), spider sex and all two-way interactions between these variables. Pairwise two-way interactions were also included between the aforementioned variables and Julian day to account for how seasonality may affect these relationships.</p> <p>Coarse dietary differences were visualised by non-metric multidimensional scaling (NMDS) via metaMDS in the ‘vegan’ package <sup>10</sup> with Jaccard distance in two dimensions and 999 tries. For NMDS, outliers (usually samples containing rare taxa) were identified by plotting and subsequently removed to facilitate separation of samples and achieve minimum stress. For visualisation of the effect of categorical variables against the dietary NMDS, spider plots were created using ‘ordispider’ with ‘ggplot’ and the ‘RColorBrewer’ ‘Accent’ colour palette <sup>11</sup>. Spider diet was compared against web characteristics for spiders for which both data were available using the MGLM process outlined above, but with starting models containing web height, web area, an interaction between the two, and pairwise interactions between genus, life stage and sex with the two web variables. This model used the same binomial error family as above, but with a ‘cloglog’ link function. For visualisation of the effect of continuous variables against the NMDS, surf plots were created with scaled coloured contours using the function “ordisurf” of the “ggplot” package in R.</p> <p>All prey taxa were classified as agricultural pests, natural enemies or excluded from subsequent analyses of intraguild predation and biocontrol (Supplementary Table 2). Intraguild predation and biocontrol variables were created by counting the number of natural enemy taxa, and, separately, of agriculturally relevant “pest” taxa (taxa containing species that commonly adversely affect agricultural productivity; Supplementary Table 2) in each spider’s diet. These resultant count data (effectively the diversity of pests and natural enemies predated by each individual spider) were separately analysed against spider genus, life stage and sex via GLM. “Site” (denoting the 4 m<sup>2</sup> area from which spiders were collected within fields) was initially included as a random effect in generalized linear mixed-models, but no significant effect was observed when comparing this model against a standard GLM via a likelihood ratio test of nested models using the ‘lrtest’ command in the ‘lmtest’ package <sup>12</sup>. Standard GLMs were thus used to avoid issues relating to singularity in the mixed models. The assumptions for the resultant Poisson error family GLMs were tested using the “testResiduals” function of the ‘DHARMa’ package <sup>13</sup>. Intraguild predation and biocontrol differences between significant terms were visualised using violin plots with the quartiles, median and 95 % upper limit annotated using the ‘geom_violin’ function in ‘ggplot2’.</p> <p><em>In situ</em> spider prey choice was analysed using network-based null models in the ‘econullnetr’ package <sup>14</sup> with the ‘generate_null_net’ command, visually represented with the ‘plot_preferences’ command. Binary dietary data were used alongside suction sample count data to represent prey availability. These suction sample data, as described above, were collected at the same sites as the spiders three days after spider collection. Prior to the taxonomic prey choice analysis, an hemipteran identified no further than order level through dietary analysis was removed due to the inability to pair it to any present prey taxa with certainty. Standardised effect sizes (SES) were extracted for all comparisons for each individual spider and compared between genera, life stages and sexes using permutational multivariate analysis of variance (PerMANOVA) using the ‘adonis’ function of the ’vegan’ package with 9999 permutations and a Euclidean distance matrix to determine overall differences in prey choice.</p> <p> </p> <p>References</p> <p>1. Roberts, M. J. <em>The Spiders of Great Britain and Ireland (Compact Edition)</em>. (Harley Books, 1993).</p> <p>2. Krehenwinkel, H., Kennedy, S., Pekár, S. & Gillespie, R. G. A cost-efficient and simple protocol to enrich prey DNA from extractions of predatory arthropods for large-scale gut content analysis by Illumina sequencing. <em>Methods Ecol. Evol.</em> <strong>8</strong>, 126–134 (2017).</p> <p>3. Cuff, J. P. <em>et al.</em> Money spider dietary choice in pre- and post-harvest cereal crops using metabarcoding. <em>Ecol. Entomol.</em> <strong>46</strong>, 249–261 (2021).</p> <p>4. Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. <em>Environmental DNA</em>. (Oxford University Press, 2018).</p> <p>5. Drake, L. E. <em>et al.</em> An assessment of minimum sequence copy thresholds for identifying and reducing the prevalence of artefacts in dietary metabarcoding data. <em>Methods Ecol. Evol.</em> <strong>in press</strong>, (2021).</p> <p>6. R Core Team. R: A language and environment for statistical computing. (2020).</p> <p>7. Deagle, B. E., Thomas, A. C., Shaffer, A. K. & Trites, A. W. Quantifying sequence proportions in a DNA-based diet study using Ion Torrent amplicon sequencing: which counts count? <em>Mol. Ecol. Resour.</em> <strong>13</strong>, 620–633 (2013).</p> <p>8. Deagle, B. E. <em>et al.</em> Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? <em>Mol. Ecol.</em> <strong>28</strong>, 391–406 (2019).</p> <p>9. Wang, Y., Naumann, U., Wright, S. T. & Warton, D. I. mvabund – an R package for model-based analysis of multivariate abundance data. <em>Methods Ecol. Evol.</em> <strong>3</strong>, 471–474 (2012).</p> <p>10. Oksanen, J. <em>et al.</em> vegan: Community Ecology Package. (2016).</p> <p>11. Neuwirth, E. RColorBrewer: ColorBrewer palettes. (2014).</p> <p>12. Zeileis, A. & Hothorn, T. Diagnostic checking in regression relationships. <em>R News</em> <strong>2</strong>, 7–10 (2002).</p> <p>13. Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. (2020).</p> <p>14. Vaughan, I. P. <em>et al.</em> econullnetr: an r package using null models to analyse the structure of ecological networks and identify resource selection. <em>Methods Ecol. Evol.</em> <strong>9</strong>, 728–733 (2018).</p>
Kinetochore life histories reveal an Aurora B dependent error correction mechanism in anaphase
<p>Dataset of kinetochore tracks in human RPE1 cells showing chromosome dynamics and segregation from prometaphase through to anaphase as described in detail in Sen, Harrison, Burroughs and McAinsh, 2021, https://doi.org/10.1101/2021.03.30.436326 Tracks correspond to 3D time-lapse movies of Ndc80-eGFP and were acquired in the 488nm channel using 1\% laser power, 50 ms exposure time/z-plane, 93 z-planes, 307 nm z-step, which results in 4.7 s/z-stack time frame. Cells are subject to nocodazole arrest-and-release or equivalent treatment with DMSO as indicated in the folder names, and some cells are subject to additional treatment with ZM to inhibit Aurora B (also indicated in folder names). Tracks were produced using kinetochore tracking software, KiT v2.3 (see Armond et al., 2016, Bioinformatics), available from https://github.com/cmcb-warwick/KiT/ </p>
Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse
<p>Datasets and R source code of the article Depeux C, Branger A, Moulignier T, Moreau J, Lemaître J-F, Dechaume-Moncharmont F-X, Laverre T, Paulhac H, Gaillard J-M, Beltran-Bech S (2023) Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse. <strong><em>Peer Community Journal</em></strong> 3:e7 http://dx.doi.org/<a href="https://doi.org/10.24072/pcjournal.228">10.24072/pcjournal.228</a></p> <p>This article previously appeared as preprint Depeux C, Branger A, Moulignier T, Moreau J, Lemaître J-F, Dechaume-Moncharmont F-X, Laverre T, Pauhlac H, Gaillard J-M, Beltran-Bech S (2022) Deleterious effects of thermal and water stresses on life history and physiology: a case study on woodlouse. <em><strong>bioRxiv</strong>, 2022.09.26.509512 </em> https://doi.org/10.1101/2022.09.26.509512</p> <p><em>Peer-reviewed and recommended by <strong>Peer Community in Ecology</strong>: </em> Belsare A (2022) An experimental approach for understanding how terrestrial isopods respond to environmental stressors. <em>Peer Community in Ecology, 100506. </em><a href="https://doi.org/10.24072/pci.ecology.100506"><strong>https://doi.org/10.24072/pci.ecology.100506</strong></a></p>
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>
Modeling Early Life Histories of Marine Organisms
<p>This is a recorded presentation to introduce students to ecosystem modeling. The presentation was developed for students of an early life histories class so discusses lagrangian individual-based modeling but the supporting material for understanding eulerian physical and lower trophic level models is also introduced.</p> <p>If you use part or all of this educational material as part of your lesson content it would be appreciated if you could inform the author (gagibson@alaska.edu) for tracking purposes.</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>
Data for 'Phenological shifts in a warming world affect physiology and life history in a damselfly'
<p>In this analysis we studied, in laboratory conditions, the impact of warming and hatching dates on key life history and physiological traits in a cannibalistic damselfly, <em>Ischnura</em> <em>elegans</em>. Larvae were reared in groups from hatching to emergence through one or two growth seasons, depending on the voltinism. Larvae were equally divided by hatching dates (early and late) and temperature treatment (current and warming). Early and late hatched groups were not mixed. This data set includes:</p> <ul> <li>survival until emergence and emergence success data</li> <li>development time (from hatching to emergence, in days)</li> <li>mass of adult insects</li> <li>growth rate (mass of adult insect/development time in days)</li> <li>protein content (μg of protein/μl of prepared homogenate)</li> <li>phenoloxidase activity (PO, value of activity curve slope)</li> <li>PO activity/protein (value of activity curve slope/(μg of protein/μl of prepared homogenate)</li> <li>insects voltinism (univoltine/semivoltine)</li> </ul>
Mesquita et al, 2015: Life History Data
Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1<p></p>
Mesquita et al, 2015: Life history data of lizards of the world (1014) DwCA
Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1<p></p>Daniel O. Mesquita, Guarino R. Colli, Gabriel C. Costa, Taís B. Costa, Donald B. Shephard, Laurie J. Vitt, and Eric R. Pianka. 2015. Life history data of lizards of the world. Ecology 96:594. <p></p>http://dx.doi.org/10.1890/14-1453.1
Morgan Ernest, 2003: Life history characteristics of placental non-volant mammals
S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.<p></p>S. K. Morgan Ernest. 2003. Life history characteristics of placental non-volant mammals. Ecology 84:3402.
Data for "Ecosystem size filters life-history strategies to shape community assembly in lakes"
<p>Dataset 1. List of 71 fish species collected from north temperate lakes in Wisconsin USA. Data include critical life-history data used for strategy classifications according to Winemiller and Rose (1992), principal component scores, and strategy classification according to the cluster analysis.</p> <p>Dataset 2. Species occurrence data in all study lakes along with results from the 'soft classification" according to Euclidean distance.</p> <p>Dataset 3. Limnological and fish community characteristics of study lakes including species richness, lake area, estimated lake volume, and convex hull statistics for the overall fish community and each life-history strategy type.</p>
Hydraulic Constraints on Two Life History Stages of Larrea tridentata in a Chihuahuan Desert Creosote Shrubland at the Sevilleta National Wildlife Refuge, New Mexico (2002-2003)
Maintaining high rates of water loss during times of high resource availability could allow establishing woody desert perennials to grow quickly by allowing them to take advantage of the fleeting but abundant monsoonal moisture typical of warm deserts like the Chihuahuan. However, a plant cannot endlessly increase water loss in order to grow faster --there are hydraulic constraints on rates of water loss. The hydraulic properties of each particular plant xylem and soil microsite, as well as the AR:AL absorbing root area to transpiring leaf area ratio) interact to set limits on rates of water loss. If transpiration rates become too high, cavitation may limit the ability of the xylem to supply water to the leaves. The main objective of this study was to test two hypotheses on a population of Larrea tridentata at the Sevilleta LTER in central New Mexico (1) do small plants grow faster and use water less conservatively than large, and (2) are there differences in the hydraulic constraints on small and large plants. Measurements were made every six weeks in the spring, summer and fall from April 2002 - August 2003. Field measurements of shoot growth, gas exchange and plant and soil water potentials were made to determine growth rates and water use. Measurements of leaf specific conductance determined the ability of the xylem to supply water to the leaves. Excavation findings were used to estimate (AR:AL). Xylem vulnerability curves and soil texture analysis were used to determine the hydraulic properties of the plant xylem and soil. A model determined where the limiting conductance occurred in the plant-soil continuum.
Fig. 2 in Growth and reproduction in captivity unveils remarkable life-history plasticity in the smallnose fanskate, Sympterygia bonapartii (Chondrichthyes: Rajiformes)
Fig. 2. Egg cases and neonate of Sympterygia bonapartii born at Temaikèn Aquarium (Argentina). ah, anterior horns; mt, mucous tendrils; ph, posterior horns. Scale bar: 20 mm.
Figure 8 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 8. Phyllocnistis maxberryi sp. n., pupa. A Ventral view of head B ventral view of cocoon-cutter C frons D lateral view of head E lateral view of cocoon-cutter F dorsal of sixth abdominal tergum G spines on sixth abdominal tergum H lateral view of spines on seventh abdominal tergum I view of abdominal tip Į dorsal view of A9–10 K lateral seta on sixth abdominal tergum L ventral view of A9–10. Scale bars 100 µm.
Figure 6 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 6. Phyllocnistis tropaeolicola sp. n., genitalia. A Male, ventral view B right valva, mesal view C aedeagus D female, lateral view E ventral view of terminal segments. (Scale bar 0.5 mm except for figure B, 0.25 mm.)
Figure 2 in Systematics, host plants, and life histories of three new Phyllocnistis species from the central highlands of Costa Rica (Lepidoptera, Gracillariidae, Phyllocnistinae)
Figure 2. Adults of three new Phyllocnistis species from Costa Rica. A Phyllocnistis drimiphaga sp. n., holotype female B P. maxberryi sp. n., holotype female (abdomen removed for dissection) C P. tropaeolicola sp. n., holotype male.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.