Find research datasets worth reusing

Detection Histories for Hemlock Woolly Adelgid Infestations at Cadwell Forest in Pelham MA 2008

Monitoring programs increasingly are used to document the spread of invasive species in the hope of detecting and eradicating low-density infestations before they become established. However, interobserver variation in the detection and correct identification of low-density populations of invasive species remains largely unexplored. In this study, we compare the abilities of volunteer and experienced individuals to detect low-density populations of an actively spreading invasive species and we explore how interobserver variation can bias estimates of the proportion of sites infested derived from occupancy models that allow for both false negative and false positive (misclassification) errors. We found that experienced individuals detected small infestations at sites where volunteers failed to find infestations. However, occupancy models erroneously suggested that experienced observers had a higher probability of falsely detecting the species as present than did volunteers. This unexpected finding is an artifact of the modeling framework and results from a failure of volunteers to detect low-density infestations rather than from false positive errors by experienced observers. Our findings reveal a potential issue with site occupancy models that can arise when volunteer and experienced observers are used together in surveys.

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.

Hemlock History Plots at Harvard Forest since 1995

Hemlock (Tsuga canadensis) forests in New England are changing rapidly with the invasion of the hemlock woolly adelgid (HWA, Adelges tsugae), a non-native insect pest that kills hemlock trees. The adelgid is just beginning to be observed at Harvard Forest, making this the right moment to begin intensive physiological, ecological and monitoring studies of our hemlock forests. We gathered detailed baseline information for several hemlock stands across Harvard Forest. We surveyed community vegetation structure and composition, and began to monitor soil nitrogen cycling. These measurements will allow us to link the long-term history of these hemlock stands to other current studies of hemlock response to adelgid infestation, and will provide the basis for intensive study of hemlock dynamics with the stands' anticipated decline.

Environment and History in a Rich Mesic Forest in Western Massachusetts 1999-2001

In rich mesic forests, modern vegetation varies among primary versus post-agricultural, secondary forests, in part as a result of differential rate and ability of forest herbs to colonize after disturbance. Species with seeds lacking morphological adaptations for dispersal (barochores) and those which produce seeds with elaisomes to encourage ant dispersal (myrmecochores) may remain less frequent in secondary forests for decades or more.

openCC (other)Aug 2025View details →

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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.

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History and Dynamics of American Beech in Coastal New England 1620-2006

Variation in forest response to hurricane disturbance in coastal New England Research on disturbance in forest ecosystems has generally focused on either catastrophic disturbances generating stand-replacing successional sequences, or small-scale disturbances (e.g. individual tree-fall gaps) resulting in tree-by-tree replacement. The role of moderate disturbances in forest development, in contrast, is poorly understood. While the most severe hurricanes can cause catastrophic disturbance, the vast majority of hurricanes that affect forests from the Caribbean to the northeastern United States are moderate in intensity. In this study we examine both individual and population level responses of beech (Fagus grandifolia) and oak species (Quercus spp.) to hurricanes of varying intensity in coastal Massachusetts. We characterize growth response to disturbance using a novel approach that explicitly compares the range of growth responses observed following known disturbances to the range of growth responses in non-event years. The tree species exhibited a wide range of growth and regeneration responses to hurricanes; however, only a single storm caused dramatic increases in growth and new establishment for beech. The results of this study highlight the importance of wind disturbance in the establishment and persistence of beech, and suggest that while some moderate disturbances have little or no effect on species growth and regeneration dynamics, individual storms may have substantial impacts. Forest response to wind storms of varying, but moderate intensities, depended on local site conditions, including environmental, meteorological, topographical, historical and biological factors. Beech dominance in a coastal New England forest Monodominant forests occur in a wide range of tropical and temperate ecosystems, but the mechanisms enabling their development are not well understood. This study examines the history and dynamics of beech-dominated forests in coastal New England i

openCC0Nov 2025View details →

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KFH01 Konza prairie fire history

The Konza burn history data is downloadable by year. Watershed names and codes listed are the current watershed designations (2010). Please note that several watershed designations have changed over the history of Konza. This is inevitable due to changes in research objectives but is problematic for those wanting to discover the full burn history of a given area. In some cases watersheds have simply been renamed to reflect changes in experimental burn treatments (e.g. R20A was formerly 1A). In other cases watersheds have been subdivided or aggregated from smaller watersheds (eg. in 1994 3B3UA was added to 20A (currently R1A) to form a larger watershed). In a few cases watershed names have been moved to new areas (e.g. 1D was moved from its original location in 1978 after the acquisition of new property. The original 1D watershed is now part of WB and 20C). Investigators should consult the proper watershed map for a given year to see watershed designations at the time of burning.

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Fruit, seed dispersal, and life history traits of tropical rainforest trees of the Anamalai Hills, Western Ghats, India

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: - 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>. Biotropica, 38: 143-160. https://doi.org/10.1111/j.1744-7429.2006.00118.x - 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>. Journal of Tropical Ecology, 33(4), 270-284. doi:10.1017/S0266467417000219 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>   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). References: 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. 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. Forest Ecology and Management 329: 375–383. PASCAL, J. P. 1988. Wet evergreen forests of the Western Ghats of India: Ecology, structure, floristic composition and succession. Institut Français de Pondichéry, Pondicherry. 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. Restoration Ecology 17:137–147. 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. Geographic Coverage: 1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India 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) Temporal Coverage: 1. Begins: 2003-03-01 (Year, Month, Day) 2. Ends: 2024-02-10 (Year, Month, Day) Besides the README.txt file, the dataset includes the following comma-delimited text (csv) file with the data in columns as explained below: Anamalai_tree_traits_2024.csv spec_name_ORIG: Scientific name of the species used during the data collection genus: Genus of the taxon specificEpithet: Specific epithet of the taxon in the Latin binomial name Accept_name_WFO: Updated scientific name of the species as in Plants of the World Online (POWO, https://powo.science.kew.org/) Habit: life form of the species(tree/shrub/cane/palm) Distribution: Distribution of the species in the study area (Native/Endemic/Introduced) IUCN_status: IUCN status of the species (CR-Critically Endangered,DD-Data deficient,EN-Endangered,LC-Least Concern,NT-Near Threatened,VU-Vulnerable,NA-Unknown) Wden_final: 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) wd_level: 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) fruit_type: Morphological type of fruit fleshy_dry: Whether fruit is a dry fruit or fleshy, with aril or other parts  seed_size: Species seed size: L = Large (>3 cm); M = Medium (1-3 cm); S = Small (<1 cm) disperser: Categories indicating seed dispersal mode: Bird, mammal, bird and mammal (Mammal_bird), gravity, wind, or unknown habitat: Habitat affinity category: EG_edg - evergreen forest edge; EG_for - evergreen forest; Dec_for - deciduous forest; Int – Introduced species; Unknown – Unknown habt_new: Habitat affinity new category: Mature – mature forest; Secondary – secondary forest, NA - unknown/Introduced species ad_ht: Species maximum adult height (m)

opencc-by-4.0Feb 2024View details →

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Ancient mitogenomes reveal the evolutionary history and biogeography of sloths

Supplementary Material for: Delsuc F., Kuch M., Gibb G.C., Karpinski E., Hackenberger D., Szpak P., Martínez J.G., Mead J.I., McDonald H.G., MacPhee R.D.E., Billet G., Hautier L., and Poinar H.N. (2019). Ancient mitogenomes reveal the evolutionary history and biogeography of sloths. Current Biology. doi:10.1016/j.cub.2019.05.043.   Delsuc-CurrBiol-2019_capture_baits.fasta: Sequence baits designed from living xenarthran mitogenomes and reconstructed ancestral sequences used to capture ancient sloth mitogenomes.   Delsuc-CurrBiol-2019_dataset.fasta: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in fasta format. Delsuc-CurrBiol-2019_dataset.phylip: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in phylip format. Delsuc-CurrBiol-2019_dataset_partitions.nex: Mitogenomic dataset used for phylogenetic reconstruction and molecular dating in nexus format with partitions. Delsuc-CurrBiol-2019_FigS2_RAxML_MLtree_100BP_nexus_for_FigTree.tree: Maximum likelihood mitogenomic tree inferred under the best-fitting partitioned model using RAxML. Related to Figure 1. Maximum-likelihood bootstrap percentages are indicating at nodes (100 replicates). Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree. Delsuc-CurrBiol-2019_FigS3_IQ-TREE_MLtree_100BP_nexus_for_FigTree.tree: Maximum likelihood mitogenomic tree inferred under the best-fitting partitioned model using IQ-TREE. Related to Figure 1. Maximum-likelihood bootstrap percentages are indicating at nodes (100 replicates). Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree. Delsuc-CurrBiol-2019_FigS4_MrBayes_consensus_nexus_for_FigTree.tree: Bayesian consensus mitogenomic tree inferred under the best-fitting partitioned model using MrBayes. Related to Figure 1. Clade posterior probabilities (PP) are indicated at nodes. Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree.  Delsuc-CurrBiol-2019_FigS5_PhyloBayes_consensus_nexus_for_FigTree.tree: Bayesian consensus mitogenomic tree inferred under the CAT-GTR+G4 mixture model using PhyloBayes. Related to Figure 1. Clade posterior probabilities (PP) are indicated at nodes. Tree is rooted on midpoint. Scale is in mean number of substitutions per site. Tree in nexus format viewable with FigTree. Delsuc-CurrBiol-2019_FigS6_PhyloBayes_chronogram_nexus_for_FigTree.tree: Bayesian mitogenomic chronogram. Related to Figure 2. This chronogram was inferred under the CAT-GTR+G4 mixture model and an autocorrelated lognormal model of clock relaxation using PhyloBayes. Tree in nexus format viewable with FigTree. Delsuc-CurrBiol-2019_Megatherium_bone_extraction_protocol.pdf: Detailed protocol for Megatherium americanum MAPB4R 3965 bone sample preparation. Delsuc-CurrBiol-2019_ML_ancestral_reconstruction_MOL_constraint.pdf: Maximum likelihood ancestral character state reconstruction. Related to Figure 3. Maximum likelihood estimation of ancestral states for six dental characters from Varela et al. (2019) under the Mk model on the maximum likelihood topology obtained using the molecular topology as a backbone constraint.  Delsuc-CurrBiol-2019_ML_ancestral_reconstruction_MORPH_constraint.pdf: Maximum likelihood ancestral character state reconstruction. Related to Figure 3. Maximum likelihood estimation of ancestral states for six dental characters from Varela et al. (2019) under the Mk model on the maximum likelihood topology obtained using the same topological constraint that these authors used in their Bayesian phylogenetic reconstructions.  Delsuc-CurrBiol-2019_MP_ancestral_reconstruction_MOL_constraint.pdf: Maximum parsimony ancestral character state reconstruction. Related to Figure 3. Maximum parsimony estimation of ancestral states for six dental characters from Varela et al. obtained using the molecular topology as a backbone constraint. Delsuc-CurrBiol-2019_MP_ancestral_reconstruction_MORPHO_constraint.pdf: Maximum parsimony ancestral character state reconstruction. Related to Figure 3. Maximum parsimony estimation of ancestral states for six dental characters from Varela et al. (2019) on the maximum parsimony topology obtained using the same topological constraint that these authors used in their Bayesian phylogenetic reconstructions.  Delsuc-CurrBiol-2019_TableS1_PartitionFinder_RAxML_best_partition_scheme.txt: Detailed results of the PartitionFinder analysis for RAxML. Delsuc-CurrBiol-2019_TableS2_ModelFinder_IQ-TREE_best_partition_scheme.txt: Detailed results of the ModelFinder analysis for IQ-TREE. Delsuc-CurrBiol-2019_TableS3_PartitionFinder_MrBayes_best_partition_scheme.txt: Detailed results of the PartitionFinder analysis for MrBayes.

opencc-by-4.0Jun 2019View details →

zenodo52/100

Dataset from: "Voluntary Control of Task Selection Does Not Eliminate the Impact of Selection History on Attention"

Dataset for Henare, D. T., Kadel, H., & Schubö, A. (2020). Voluntary Control of Task Selection Does Not Eliminate the Impact of Selection History on Attention. Journal of Cognitive Neuroscience, 32(11), 2159-2177. <a href="https://doi.org/10.1162/jocn_a_01609">https://doi.org/10.1162/jocn_a_01609</a>

opencc-by-4.0Jul 2021View details →

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Natural Regeneration of Puerto Rican Tropical Dry Forest Sites with Limited Burn History, Guánica Forest, 2012

This dataset documents the natural regeneration of tropical dry forest sites with limited burn history in Guánica Forest, Puerto Rico, following fire disturbance. Featuring a 29-year chronosequence, the dataset encompasses both short-term (2–5 months) and long-term (2–29 years) recovery, alongside mature forest control sites (including forest sites containing native grass). Data collection was conducted between May and August 2012 and focuses on woody tree species only. The dataset includes tree census data from seven sites (chrono_census.csv), recording species identity, stem diameter, aboveground biomass destruction, and resprouting dynamics. Additional data include species mean trait values, such as relative bark thickness and specific leaf area, to examine relationships with post-fire resprouting (chrono_traits.csv), and a species abundance matrix for evaluating community composition shifts over time (chrono_ndmsmatrix.csv). Field data were collected from circular 100 m² plots randomly placed at each site, with all woody plants tagged and identified. Stem diameters (≥1 cm) were measured at breast height (DBH) or ground height (DGH) in new-burn sites. Tree mortality was assessed, and aboveground biomass loss (0–100%) was estimated in new-burn sites. Resprouting was also quantified in short-term regeneration sites in mid-August 2012. In long-term sites, tree height was measured for the five tallest individuals. The dataset is relevant for researchers investigating tropical dry forest dynamics, fire ecology, and regeneration processes in Caribbean forest ecosystems. The dataset is complete and not ongoing.

openCC (other)Feb 2025View details →

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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

openCC (other)Mar 2025View details →

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Chamaecrista fasciculata Survival and Biomass in Response to Microbe Stress History and Contemporary Stress, 2018-2019

This dataset includes Chamaecrista fasciculata biomass and survival data collected as part of a greenhouse experiment that took place at Indiana University in 2018. Rhizosphere soil was collected from Chamaecrista fasciculata plants at the end of a field experiment in which plants were treated with four stress treatments: salt, herbicide, herbivory, and no stress. These field soils were used to inoculate a greenhouse experiment in which Chamaecrista fasciculata individuals from 50 manternal families were treated with these same four stress treatments in a full factorial design (4 microbe histories x 4 contemporary stress environments), plus a sterile microbial control treatment. We measured the days to first flower, noted when plants never flowered (i.e., did not survive to flower), and measured aboveground biomass.

openCC (other)Nov 2025View details →

opencc-by-4.0Feb 2024View details →

Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration

Supplementary Data for Wueller et al. (2024): Geologic History of the Amundsen Crater Region Near the Lunar South Pole: Basis for Future Exploration Data contains the georeferenced map plate of our geologic map that can be used in any geoinformation system (GIS). If you use these data, please cite BOTH the Planetary Science Journal publication and the Zenodo dataset. Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. The Planetary Science Journal, 5(6), 147. <a href="https://iopscience.iop.org/article/10.3847/PSJ/ad2c04">https://iopscience.iop.org/article/10.3847/PSJ/ad2c04</a> Wueller, L., Iqbal, W., Frueh, T., van der Bogert, C. H., & Hiesinger, H. (2024). Supplementary Data for Wueller et al. (2024): Geologic history of the Amundsen crater region near the Lunar South Pole: Basis for future exploration. Zenodo Dataset. <a href="https://doi.org/10.5281/zenodo.10693820" target="_blank" rel="noopener">https://doi.org/10.5281/zenodo.10693820</a> ----------------------------------------------------------------------------------------------------------------------------------------- Mapping Scale is 1:100,000 Print Scale is 1:1,000,000 ----------------------------------------------------------------------------------------------------------------------------------------- For further questions contact lwueller@uni-muenster.de Lukas Wueller, Institut für Planetologie, Universität Münster, Germany, June 2024

opencc-by-4.0Mar 2024View details →

Research data for "Hutters in the Zamoyski Family Entail - history of an environmentally conditioned social group"

Research data for "Hutters in the Zamoyski Family Entail - history of an environmentally conditioned social group" (v1_2024)

opencc-by-nc-4.0Mar 2024View details →

Database on the History of Participation and Engagement

The dataset presents a timeline and database of sustainability-related, innovative, and inclusive participation and engagement practices in Europe since the early days of digitalisation.  The data reported here was assembled from Democratic Innovations collected from publicly accessible sources (Partecipedia, OECD's database of Representative Deliberate Processes and Institutions, Knowledge Network on Climate Assemblies (KNOCA), G1000, and the International Observatory on Participatory Democracy), with a specific focus on their contribution to social and environmental sustainability. By mapping the dynamics of implementation of Democratic Innovations across Europe, the dataset provides valuable insights into the potential for these innovations to foster more inclusive and resilient societies in line with social and environmental development goals. Each of the cases collected here was categorised on specific criteria, like geographical distribution, scales of governance, policy areas, citizen involvement, and digitalization. INCITE-DEM is funded by the European Union (INCITE-DEM, GA nº 101094258). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or of the European Research Executive Agency (REA). Neither the European Union nor the granting authority (REA) can be held responsible for them

openapache2.0Apr 2024View details →

History, Adoption and Key impacts of precision agriculture

Precision agriculture technologies have revolutionized modern farming practices, offering innovative solutions to optimize crop production, minimize resource use, and enhance environmental sustainability. This research paper explores the historical evolution, adoption trends, and importance of precision agriculture technologies in contemporary agriculture.

opencc-by-4.0Nov 2023View details →

Data Product for "Toward a Cenozoic history of atmospheric CO2"

These data were vetted and revised from published paleo-CO2 data (original estimates archived at https://zenodo.org/uploads/8052599) by an international group of proxy experts supported through an NSF-funded Research Coordination Network. It brings together paleo-CO2 reconstruction data from terrestrial and marine archives, and the compilation includes estimates derived from multiple proxies including Phytoplankton, Boron, Stomatal Frequencies, Leaf Gas Exchange, Liverworts, Land Plant d13C, Paleosols, and Nahcolite. Data are visualized in an interactive product plot made available on the Paleo-CO2 project web page at (https://www.paleo-co2.org) and are also archived in the NCDC database (<a href="https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/product_files/">https://www.ncei.noaa.gov/pub/data/paleo/climate_forcing/trace_gases/Paleo-pCO2/product_files/</a>).

opencc-by-4.0Apr 2021View details →

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

Materials and Methods Fieldwork 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 m2 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 m2 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. 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).   Extraction and high-throughput sequencing of spider gut DNA Given their prevalence in field collections, dietary analysis was carried out for the linyphiid genera Erigone, Tenuiphantes, Bathyphantes and Microlinyphia (Araneae: Linyphiidae), and the Lycosidae genus Pardosa. Spiders were transferred to and washed in fresh 100 % ethanol to reduce external contaminants prior to identification via morphological key 1. 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 2. 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. For amplification of DNA, two primer pairs were used. BerenF-LuthienR 3 amplified a broad range of invertebrates including spiders, and TelperionF-LaureR, amplified a range of invertebrates but fewer spiders (modified from TelperionF-LaurelinR 3 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. 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 et al. (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).   Statistical analysis All analyses were conducted in R v4.0.0 6. Initial multivariate analyses used binary data (i.e., presence/absence) given the various problems inherent to quantifying metabarcoding data 7,8. 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 9 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. Coarse dietary differences were visualised by non-metric multidimensional scaling (NMDS) via metaMDS in the ‘vegan’ package 10 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 11. 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. 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 m2 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 12. 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 13. 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’. In situ spider prey choice was analysed using network-based null models in the ‘econullnetr’ package 14 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.   References 1.        Roberts, M. J. The Spiders of Great Britain and Ireland (Compact Edition). (Harley Books, 1993). 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. Methods Ecol. Evol. 8, 126–134 (2017). 3.        Cuff, J. P. et al. Money spider dietary choice in pre- and post-harvest cereal crops using metabarcoding. Ecol. Entomol. 46, 249–261 (2021). 4.        Taberlet, P., Bonin, A., Zinger, L. & Coissac, E. Environmental DNA. (Oxford University Press, 2018). 5.        Drake, L. E. et al. An assessment of minimum sequence copy thresholds for identifying and reducing the prevalence of artefacts in dietary metabarcoding data. Methods Ecol. Evol. in press, (2021). 6.        R Core Team. R: A language and environment for statistical computing. (2020). 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? Mol. Ecol. Resour. 13, 620–633 (2013). 8.        Deagle, B. E. et al. Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? Mol. Ecol. 28, 391–406 (2019). 9.        Wang, Y., Naumann, U., Wright, S. T. & Warton, D. I. mvabund – an R package for model-based analysis of multivariate abundance data. Methods Ecol. Evol. 3, 471–474 (2012). 10.      Oksanen, J. et al. vegan: Community Ecology Package. (2016). 11.      Neuwirth, E. RColorBrewer: ColorBrewer palettes. (2014). 12.      Zeileis, A. & Hothorn, T. Diagnostic checking in regression relationships. R News 2, 7–10 (2002). 13.      Hartig, F. DHARMa: residual diagnostics for hierarchical (multi-level/mixed) regression models. (2020). 14.      Vaughan, I. P. et al. econullnetr: an r package using null models to analyse the structure of ecological networks and identify resource selection. Methods Ecol. Evol. 9, 728–733 (2018).