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Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m in A Systematic Review Of Sulawesi Bunomys (Muridae, Murinae) With The Description Of Two New Species
Fig. 29. Tropical lowland evergreen rain forest along the Sungai Sadaunta, 750–850 m (in 1974). Typical forest composition on terraces just above the stream: dense undergrowth of shrubs and tree saplings, woody vines looping through the understory. Beneath the dense cover, the ground is wet, the air cool. Most Bunomys chrysocomus were trapped in this kind of stream terrace habitat, either on the ground beneath the shrubs, alongside decomposing, moss-covered trunks and limbs lying on the terrace, or among moss-covered rocks. Bunomys karokophilus, n. sp., was encountered in similar habitat.
Data from: Plant Community Structure in Tropical Rain Forest Fragments of the Western Ghats, India
<p><strong>DESCRIPTION</strong></p><p>This dataset includes vegetation plot data on trees, lianas, understorey plants, and regeneration, and related data and species name matching files in five rainforest sites collected in 2003 as part of the following study:</p><p>MUTHURAMKUMAR, S., AYYAPPAN, N., PARTHASARATHY, N., MUDAPPA, D., RAMAN, T. R. S., SELWYN, M. A. & PRAGASAN, L. A. 2006. <a href="http://doi.org/10.1111/j.1744-7429.2006.00118.x">Plant community structure in tropical rain forest fragments of the Western Ghats, India</a>. <i>Biotropica</i> 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.x</p><p>The regeneration data were analysed and presented in the following publication and related dataset:</p><p>OSURI, A. M., CHAKRAVARTHY, D., MUDAPPA, D., RAMAN, T. R. S., AYYAPPAN, N., MUTHURAMKUMAR, S. & PARTHASARATHY, N. 2017. Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India. <i>Journal of Tropical Ecology</i> 33(4): 270-284. DOI: <a href="http://doi.org/10.1017/S0266467417000219">10.1017/S0266467417000219</a></p><p>OSURI, A. M., CHAKRAVARTHY, D., MUDAPPA, D., RAMAN, T. R. S., AYYAPPAN, N., MUTHURAMKUMAR, S. & PARTHASARATHY, N. 2017. <a href="http://doi.org/10.5061/dryad.vd0nn">Data from: Successional status, seed dispersal mode and overstorey species influence tree regeneration in tropical rain-forest fragments in Western Ghats, India</a>, Dryad, Dataset, https://doi.org/10.5061/dryad.vd0nn</p><p><br><strong>CONTACTS</strong></p><p>CONTACT #1<br>1. Name: <a href="https://orcid.org/0000-0002-1347-3953">T. R. Shankar Raman</a><br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: trsr@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0002-1347-3953</p><p>CONTACT #2<br>1. Name: <a href="https://orcid.org/0000-0001-9708-4826">Divya Mudappa</a><br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: divya@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0001-9708-4826</p><p>CONTACT #3<br>1. Name: <a href="https://orcid.org/0000-0001-9909-5633">Anand M. Osuri</a><br>2. Work Address: Nature Conservation Foundation, 1311, 12th A Main, Vijayanagar 1st Stage, Mysuru 570017, Karnataka, India<br>3. Work Phone: +91 821 2515601<br>4. Email address: aosuri@ncf-india.org<br>5. ORCID: https://orcid.org/0000-0001-9909-5633</p><p>CONTACT #4<br>1. Name: <a href="https://orcid.org/0000-0003-4383-557X">N. Ayyappan</a><br>2. Work Address: French Institute of Pondicherry, No. 11, Post Box No. 33, Saint Louis Street, Pondicherry – 605 001, India.<br>3. Work Phone: + 91- 413-2231616<br>4. Email address: ayyappan.n@ifpindia.org<br>5. ORCID: https://orcid.org/0000-0003-4383-557X</p><p>CONTACT #5<br>1. Name: <a href="https://orcid.org/0000-0002-7791-8499">S. Muthuramkumar</a><br>2. Work Address: V.H.N.S.N. College, 3/151-1, College Road, Virudhunagar - 626001, Tamil Nadu, India.<br>3. Work Phone: + 91-4562-280154<br>4. Email address: muthuramkumar@vhnsnc.edu.in<br>5. ORCID: https://orcid.org/0000-0002-7791-8499</p><p>CONTACT #6<br>1. Name: <a href="https://orcid.org/0000-0002-4172-5441">N. Parthasarathy</a><br>2. Work Address: Department of Ecology and Environmental Sciences, Pondicherry University, R Venkat Raman Nagar, Kalapet, Pondicherry 605014, India<br>3. Work Phone: + 91-413-2654326<br>4. Email address: parthapu@yahoo.com<br>5. ORCID: https://orcid.org/0000-0002-4172-5441</p><p><br><strong>KEYWORDS</strong></p><p>Anamalai hills; biodiversity hotspot; disturbance; endemics; fragmentation; lianas; plant conservation; tree diversity; tropical rain forest; understory plants.</p><p><br><strong>GEOGRAPHIC COVERAGE</strong></p><p>1. Location/Study Area: Valparai Plateau, Tamil Nadu, India; Anamalai Tiger Reserve, Tamil Nadu, India</p><p>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><br><strong>TEMPORAL COVERAGE</strong></p><p>1. Begins: 2003-03-01 (Year, Month, Day)<br>2. Ends: 2003-04-30 (Year, Month, Day)</p><p><br><strong>METHODS</strong></p><p>Methods involved systematic vegetation plots for trees, lianans and understorey plants as described in Muthuramkumar et al. 2006 (<i>Biotropica</i> 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.x) and for tree and woody regeneration as described in Osuri et al. 2017 (<i>Journal of Tropical Ecology</i> 33(4): 270-284. DOI: 10.1017/S0266467417000219). The vegetation sampling methods are briefly described below.</p><p>The present study was conducted in five tropical wet evergreen forest fragments located on the Valparai plateau (Fig. 1): Akkamalai (AK, 2600 ha), Upper Manamboli (UM, 100 ha), Lower Manamboli (LM, 100 ha), Tata Finlay (TF, 32 ha), and Injipara (IP, 18 ha).</p><p>In each site, vegetation was sampled in randomly placed noncontiguous plots of 20 × 20 m located at least 50 m apart and at least 20 m into the fragment interior from the edges, major trails, or roads. We sampled 20 plots each in IP, TF, and LM, and 25 plots each in UM and AK. Within each plot, all trees ≥30cm girth at breast height (gbh, at 1.3 m; corresponding to DBH of 9.55 cm) and lianas ≥1 cm diameter at breast height (DBH) were identified to species, counted, and their girth/diameter measured. For multi-stemmed trees bole girths were measured separately, basal area calculated and summed. Each 20 x 20 m plot was divided into four 10 × 10 m quarters.</p><p>For understory plants, 2 × 2 m quadrats were laid at the four corners of the 20 × 20 m plot (one in each of the corresponding four quarters) and all shrubs, undershrubs, herbs, ferns, and small twiners found within the quadrats were enumerated and identified. The regeneration sampling was done in a 5 × 5-m plot (0.0025 ha) placed at the outer corner of the first (south-west) quarter of the 20 x 20 m plot. Within each regeneration plot, we identified, counted and measured all tree saplings >1 cm diameter at breast height (dbh, at 1.3 m) and <9.55 cm dbh (equivalent to <30 cm girth at breast height, gbh). Woody shrubs of 1–9.55 cm dbh were alsorecorded in the regeneration plots (but these were excluded in the Osuri et al. 2017 analysis).</p><p>For vegetatively propagating plants a clump of stems that is basally connected was considered as one individual. Canopy height was measured with a range finder and canopy closure was measured using a spherical densiometer. Vouchers were identified with regional flora and confirmed with the Western Ghats collections available in the herbarium of Salim Ali School of Ecology, Pondicherry University, from our previous works in the region.</p><p> </p><p><strong>ACKNOLWEDGEMENTS</strong></p><p>Funders and other supporters of the research are acknowledged in the original publications. The compilation and publication of this dataset was carried out as part of an NCF project supported by Fondation Franklinia.</p><p><br><strong>FILES INCLUDED</strong></p><p>Besides the 00_README.txt file that contains this metadata, the dataset includes the following 11 files, whose details and contents are explained below.</p><p><br><strong>01_all_sites.csv</strong></p><p><i>Description</i>: The file contains details of the five study sites (three continuous forest and two forest fragment sites).<br> <br><i>Note</i>: Current Name of TF (Tata Finlay) site is Old Valparai, current name of Akkamalai (AK) is Iyerpadi-Akkamalai complex. Sites and codes correspond to the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x).</p><p><i>Column names and descriptions:</i><br>eventDate: Date range when sampling was carried out in the sites<br>old_sitename: Name of the site as used in the Muthuramkumar et al. (2006) paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x)<br>sitecode: Site code as used in the Muthuramkumar et al. (2006) paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x)<br>site: Site name as at present and used in this dataset<br>decimalLatitude: latitude in decimal degrees North<br>decimalLongitude: longitude in decimal degrees East<br>geodeticDatum: Geodetic Datum WGS 84<br>coordinateUncertaintyInMeters: Uncertainty in metres of the GPS location (as only one location available for entire site where points were distributed)<br>type: Indicates whether site was continuous rainforest or rainforest fragment<br>Area_ha: Area in hectares<br>Altitude_min_m: Minimum altitude in metres of sampled plots<br>Altitude_max_m: Maximum altitude in metres of sampled plots<br>Ownership: Whether site is in privately owned land or within state-protected reserve<br>Average_canopy_height_m: average canopy height in metres<br>Canopy_closure_%: estimated canopy closure in percentage<br>Nearby_plantations: Adjoining plantations</p><p><br><strong>02_all_trees_adult_data.csv</strong></p><p><i>Description</i>: The file contains records of all adult trees >= 30 cm girth at breast height of 1.3 m (gbh) recorded within 20 m x 20 m plots across three continuous forests and two forest fragments.</p><p><i>Note</i>: Same as in the Osuri et al. (2017) dataset (https://doi.org/10.5061/dryad.vd0nn), with <i>Tithonia diversifolia</i> added back in Injipara and data from one additional site (Manamboli Lower) added back from the original dataset corresponding to the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x).<br> <br><i>Column names and descriptions:</i><br>x: Row index<br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site<br>q_no: An unique number assigned to each of four 10m x 10m quarters within each adult plot<br>t_no: An unique number assigned to each individual tree within each site.<br>old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset)<br>osuri_code: Revised species codes used in the Osuri et al. 2017 paper in <i>Journal of Tropical Ecology</i> 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn)<br>current_code: Species codes used at present<br>gbh_1 to gbh_16: Girth at breast height of single- (gbh_1) and multi-stemmed (gbh_2 – gbh_16) individuals, measured in centimetres (cm)<br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>03_all_liana_data.csv</strong></p><p><i>Description</i>: The file contains records of all lianas >= 1 cm diameter at breast height of 1.3 m (dbh) recorded within 20 m x 20 m plots across three continuous forests and two forest fragments.</p><p><i>Note</i>: Lianas were not included in the Osuri et al. (2017) dataset (https://doi.org/10.5061/dryad.vd0nn).</p><p><i>Column names and descriptions:</i><br>x: Row index<br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site<br>q_no: An unique number assigned to each of four 10m x 10m quarters within each adult plot<br>t_no: An unique number assigned to each individual tree within each site.<br>old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset)<br>osuri_code: Indicated as NA since these data were not used in the Osuri et al. 2017 paper in <i>Journal of Tropical Ecology</i> 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn)<br>current_code: Species codes used at present<br>dbh_1 to dbh_11: Diameter at breast height of single- (dbh_1) and multi-stemmed (dbh_2 – dbh_11) individuals, measured in centimetres (cm) <br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>04_all_herbs_data.csv</strong></p><p><i>Description</i>: The file contains records of all understorey plants (shrubs, undershrubs, herbs, ferns, and small twiners) recorded in 2 m × 2 m quadrats laid at the four corners of each 20 m × 20 m plot in three continuous forests and two forest fragments.</p><p><i>Note</i>: Understorey plants were not included in the Osuri et al. (2017) dataset (https: //doi.org/10.5061/dryad.vd0nn).</p><p><i>Column names and descriptions:</i><br>x: Row index<br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m plot within each site<br>corner_no: An unique number assigned to each of four 2 m x 2 m quadrat laid at the four corners of the 20 m x 20 m plot<br>t_no: A number assigned to each individual species recorded within the corner plot.<br>old_code: Species codes used at the time of data collection (refer to Appendix A of the main paper for full species names, and the 06_all_species_names.csv file with this dataset)<br>osuri_code: Indicated as NA since these data were not used in the Osuri et al. 2017 paper in <i>Journal of Tropical Ecology</i> 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn)<br>current_code: Species codes used at present<br>count: Number of individuals counted (for vegetatively propagating plants a clump of stems that was basally connected was considered as one individual)<br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>05_all_regeneration_data.csv</strong></p><p><i>Description</i>: The file contains records of woody seedlings and saplings (1-5 cm diameter at breast height at 1.3 m, dbh) and larger-stemmed trees (>5 cm dbh) recorded within single 5 m x 5 m regeneration plots nested within 20 m x 20 m plots. Plots were located in three continuous forests and two forest fragments. Data were filtered during analysis in Osuri et al. (2017, <i>Journal of Tropical Ecology</i>) to retain only seedling and saplings, defined as individuals with effective diameter <=5 cm.</p><p><i>Note</i>: Same as in the Osuri et al. (2017) dataset, with <i>Tithonia diversifolia</i> added back in Injipara from original dataset; and data from one additional site (Manamboli Lower) added back from the Muthuramkumar et al. 2006 dataset.<br> <br><i>Column names and descriptions:</i><br>x: Row index<br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site<br>q_no: The 5 m x 5 m plot was placed in the SW corner of the 20 m x 20 m plot in this q_no which indicates one of the four 10 m x 10 m quarters of the 20 m x 20 m plot, where each quarter was given a unique number in each site<br>t_no: An unique number assigned to each individual seedling, sapling or tree within each site.<br>old_code: Species codes used at the time of data collection (for full species names refer to 06_all_species_names.csv file with this dataset)<br>osuri_code: Revised species codes used in the Osuri et al. 2017 paper in <i>Journal of Tropical Ecology </i>33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn)<br>current_code: Species codes used at present<br>dbh_1 to dbh_12: Diameter at breast height of single- (dbh_1) and multi-stemmed (dbh_2 – dbh_12) individuals, measured in centimetres (cm) <br>eff_dbh: Effective diameter at breast height (cm)- calculated as ((dbh)^2 +(dbh_1)^2 +...+(dbh_12)^2)^(1/2),<br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>06_all_canopy_readings.csv</strong></p><p><i>Description</i>: The file contains canopy-related measurements taken in each 20 m × 20 m plot in three continuous forests and two forest fragments.</p><p><i>Note</i>: Units of light meter reading were not recorded</p><p><i>Column names and descriptions:</i><br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site<br>reading: A number assigned to the 1 to 4 readings taken in each plot<br>light: Light measurement taken with a light meter in the plot<br>canopy_openness: Canopy openness (scored from 0-100%) using a spherical densiometer (Canopy cover = 100 - canopy openness)<br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>07_all_extracanopy_trees_data.csv</strong></p><p><i>Description</i>: The file contains records of additional trees outside the 5 x 5 m plot whose canopy was overhead of the plot.</p><p><i>Note</i>: Species codes are used to denote presence (not count of stems) of that species in the overhead canopy.</p><p><i>Column names and descriptions:</i><br>site: Name of forest site<br>plot_no: An unique plot number assigned to each 20m x 20m adult tree plot within each site<br>q_no: The 5 m x 5 m plot was placed in the SW corner of the 20 m x 20 m plot in this q_no which indicates one of the four 10 m x 10 m quarters of the 20 m x 20 m plot, where each quarter was given a unique number in each site<br>old_code: Species codes used at the time of data collection (for full species names refer to 06_all_species_names.csv file with this dataset)<br>osuri_code: Revised species codes used in the Osuri et al. 2017 paper in J<i>ournal of Tropical Ecology </i>33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn)<br>current_code: Species codes used at present<br>P_ID: Unique plot ID created by combining columns site and plot_no</p><p><br><strong>08_all_species_names.csv</strong></p><p><i>Description</i>: This file provides species codes and species scientific names as originally used in the Muthuramkumar et al. 2006 paper (https://doi.org/10.1111/j.1744-7429.2006.00118.x), and as matched with the Global Biodiversity Information Facility (GBIF) species name matching tool</p><p><i>Note</i>: For plots that had no species occurrences (old_code = No herbs, Noliana), NA has been used for other columns</p><p><i>Column names and descriptions:</i><br>group: Code indicating main dataset group where species occurs (tree and regeneration data, liana data, understorey plants data)<br>old_code: Species codes used at the time of data collection (refer to traits data file for full species names)<br>osuri_code: Revised species codes if used in the Osuri et al. 2017 paper in <i>Journal of Tropical Ecology</i> 33: 270-284 (https://doi.org/10.1017/S0266467417000219) and related dataset (https://doi.org/10.5061/dryad.vd0nn) or else indicated as NA<br>current_code: Species codes used at present<br>original_name: Scientific name of plant species as used at the time of the original publication (Muthuramkumar et al. 2006)<br>original_fullname: Scientific name and authorship of plant species as used at the time of the original publication (Muthuramkumar et al. 2006)<br>original_family: Family of the plant species as used at the time of original publication<br>GBIFname: Scientific name as matched by GBIF species name matching tool<br>key: GBIF name matching tool key number<br>matchType: Type of match<br>confidence: Confidence returned by name matching tool<br>status: Whether accepted name or synonym<br>rank: Taxanomic rank (level) to which identified<br>kingdom: Taxonomic Kingdom<br>phylum: Taxonomic Phylum<br>class: Taxonomic Class<br>order: Taxonomic Order<br>family: Taxonomic Family<br>genus: Taxonomic Genus<br>species: Taxonomic Species<br>canonicalName: Canonical part of scientific name matched by GBIF<br>authorship: Authorship of scientific name matched by GBIF<br>scientificName: Current scientific name (from species, genus, or family columns)</p><p><br><strong>09_tabula_Biotropica_appendix1.csv</strong></p><p><i>Description</i>: This file contains tabled values extracted from Appendix 1 of Muthuramkumar et al. 2006 paper in Biotropica (DOI: 10.1111/j.1744-7429.2006.00118.x); extraction from PDF carried out using Tabula software (https://tabula.technology/)</p><p><i>Note</i>: Last 5 columns contain total abundance (count of individuals/stems) in the corresponding site.</p><p><i>Column names and descriptions:</i><br>slno: serial number<br>habit: Plant habit indicating trees, lianas, or understorey plants<br>species: species name as used in Appendix 1 of Muthuramkumar et al. 2006<br>asterisk: species endemic to Western Ghats are indicated by an asterisk (∗ ), and invasive species by double asterisk (∗∗ ).<br>voucher_number: voucher number of herbarium specimen deposited in the herbarium of Salim Ali School of Ecology, Pondicherry University, India.<br>family: plant family as in Appendix 1<br>Iyerpadi-Akkamalai: abundance (total number of individuals counted) in this site<br>Manamboli_Upper: abundance (total number of individuals counted) in this site<br>Manamboli_Lower: abundance (total number of individuals counted) in this site<br>Old_Valparai: abundance (total number of individuals counted) in this site<br>Injipara: abundance (total number of individuals counted) in this site</p><p><br><strong>10_Muthuramkumar et al 2006_Abstract and Appendix 1_extract_Biotropica.pdf</strong></p><p>Extracted PDF of first page with Abstract and Appendix 1 of Muthuramkumar et al. 2006 (DOI: 10.1111/j.1744-7429.2006.00118.x).</p><p><br><strong>11_figure_1_Biotropica_paper.jpg</strong></p><p>JPEG image of Figure 1 (map of study area) from the following publication:<br>MUTHURAMKUMAR, S., AYYAPPAN, N., PARTHASARATHY, N., MUDAPPA, D., RAMAN, T. R. S., SELWYN, M. A. & PRAGASAN, L. A. 2006. Plant community structure in tropical rain forest fragments of the Western Ghats, India. Biotropica 38: 143–160. DOI: 10.1111/j.1744-7429.2006.00118.x</p>
High-resolution tropical rain-forest canopy climate data
<p><span>Canopy habitats challenge researchers with their intrinsically difficult access. The current scarcity of climatic data from forest canopies limits our understanding of the conditions and environmental variability of these diverse and dynamic habitats. We present 307 days of climate records collected between 2019 and 2020 in the tropical rainforest canopy of the Yasuní National Park, Ecuador. We monitored climate with a 10-minute temporal resolution in the middle crowns of eight canopy trees. The distance between canopy climate stations ranged from 700 m to 10 km. Apart from air temperature, relative humidity, leaf wetness, and photosynthetically active radiation (PAR), measured in each canopy climate station, global radiation, rainfall, and wind speed were measured in different subsets of them. We processed the eight data series to omit erroneous records resulting from sensor failures or lack of the solar-based power supply. In addition to the eight original data series, we present three derived data series, two aggregating canopy climate for valleys or for ridges (from four stations each), and one overall average (from the eight stations). This last derived data series contains 306 days, while the shortest of the original data series covers 22 days and the longest 296 days. In addition to the data, two open-source tools, developed in RStudio, are presented that facilitate data visualization (a dashboard) and data exploration (a filtering app) of the original and aggregated records.</span></p>
Litterfall production and litter decomposition experiments: in-situ datasets of nutrient fluxes in two Bornean lowland rain forests associated with Acacia invasion
<p>This dataset contains the original data from which the figures and tables for the article "Differential impacts of <em>Acacia</em> invasion on nutrient fluxes in two distinct Bornean lowland tropical rain forests" were prepared. It documents parameters relevant to nutrient fluxes via litterfall production and leaf litter decomposition rates from 2016 to 2017 in two selected lowland rainforests in Brunei Darussalam that are associated with <em>Acacia</em> invasion. Both litterfall sample collection and litter decomposition bag experiments followed standard protocols. Leaf litterfall fractions from the litterfall production experiment were analysed for nutrient contents of nitrogen (N), phosphorus (P), potassium (K), magnesium (Mg), and calcium (Ca). Nutrient addition and nutrient use efficiency values were calculated based on nutrient concentration and monthly leaf litterfall production in the different habitat types studied. The mean percentage of litter mass remaining, K day<sup>-1</sup>, K year<sup>-1</sup>, half-life t<sub>0.5</sub>, pH values, and nutrient concentrations (N, P, K, Mg, Ca) were calculated for leaf litter samples collected after 336 days in the different habitats.</p>
Tahoe rain or snow precipitation phase observations
<p>These data include observations of rain, snow, and mixed precipitation from the Tahoe Rain or Snow citizen science project. Included with each observation is a set of ancillary variables, including latitude and longitude, elevation, modeled meteorological data, and additional info. Please see the metadata file for the description and units of each data column.</p> <p>For more info, please see Jennings et al. (2023) and Arienzo et al. (2021):</p> <ul> <li>Jennings, Keith S., Monica M. Arienzo, Meghan Collins, Benjamin Hatchett, Anne W. Nolin, and Graeme Aggett. "Crowdsourced Data Highlight Precipitation Phase Partitioning Variability in Rain-Snow Transition Zone." Earth and Space Science (2023). <a href="https://doi.org/10.1029/2022EA002714">https://doi.org/10.1029/2022EA002714</a> </li> <li>Arienzo, Monica M., Meghan Collins, and Keith S. Jennings. "Enhancing engagement of citizen scientists to monitor precipitation phase." Frontiers in Earth Science 9 (2021): 617594. <a href="https://doi.org/10.3389/feart.2021.617594">https://doi.org/10.3389/feart.2021.617594</a> </li> </ul> <p>For the code used to process these data: <a href="https://github.com/SnowHydrology/MountainRainOrSnow/tree/tahoe_ros">https://github.com/SnowHydrology/MountainRainOrSnow/tree/tahoe_ros</a></p>
A Complete Water Balance of a Rain Garden
<p>A bioinfiltration rain garden was retrofitted from an existing traffic island at Villanova University in 2001. It has been monitored continuously since 2003 at a five-minute timeseries resolution and with instrumentation that would enable a water balance calculation. This twenty-year dataset allows for an in-depth analysis of the hydrologic pathways and management in the rain garden. Using physical equations and modeled data (based on real-time measurements), a balance of all influent, stored, and effluent water within the rain garden was constructed.</p> <p>The water balance data (totals of individual water balance components) of all storms used in assessing the rain garden’s performance in the study are provided in this dataset. This dataset is associated with the forthcoming publication: <em>A Complete Water Balance of a Rain Garden</em> (McGauley et al. 2023). </p>
Data for: Bulk microphysics schemes may perform better with a unified cloud-rain category
Open the record for dataset details and reuse information.
Data from: Proximate cues of flowering in a subtropical rain forest
Open the record for dataset details and reuse information.
High-resolution tropical rain-forest canopy climate data
Open the record for dataset details and reuse information.
Tahoe rain or snow precipitation phase observations
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Data from: Quantifying seed rain patterns in a remnant and a chronosequence of restored tallgrass prairies in north central Missouri
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Tally of seeds collected in seed-rain traps and the trees around the traps in Guánica Forest, Puerto Rico
Tropical dry forests that experience severe disturbances often remain degraded for long time periods, during which non‐native grasses and trees dominate. One barrier to native tree regeneration in degraded areas may be seed dispersal limitation. To better understand how dispersal limitation influences recovery from degradation, we tested whether the mode and rates of seed dispersal differed in degraded sites dominated either by the exotic tree Leucaena leucocephala or open areas dominated by introduced pasture grasses. We also tested whether L. leucocephala stands facilitate the recruitment of native trees by increasing their seed input compared to open grass areas.
Bulk precipitation collected during summer months on a per rain event basis at Toolik Field Station, North Slope of Alaska, Arctic LTER 1988 to 2007.
Bulk precipitation was collected during summer months (June, July and August) on a per rain event basis at the University of Alaska Fairbanks Toolik Field Station, North Slope of Alaska (68 degrees 37' 42"N, 149 degrees 35' 46"W). Analysis of pH, NH4-N and phosphorus were performed at the field station. NO3-N were frozen and analyzed in Woods Hole, MA
Black spruce seed counts from seed rain traps in the 2004 burns off the Steese, Taylor, and Dalton Highways, collected in 2005-2007.
This dataset contains seed counts of black spruce seed rain collected in traps at 39 intensive study sites within the 2004 burns of interior Alaska. Data are presented as raw data from trap collections at each site. All sites were in communities dominated by black spruce before burning, and were located 100 to 600 m from the road, beyond the range of any visible road effects and away from any signs of other human disturbance.
Black spruce seed viability from seed rain traps in the 2004 burns off the Steese, Taylor, and Dalton Highways, collected in 2005-2007.
This dataset contains viability estimates of black spruce seed collected in traps at 39 intensive study sites within the 2004 burns of interior Alaska. Data are presented as raw data from trap collections at each site. All sites were in communities dominated by black spruce before burning, and were located 100 to 600 m from the road, beyond the range of any visible road effects and away from any signs of other human disturbance.
Eight Mile Lake Research Watershed, Thaw Gradient: Geochemical data collected daily in Panguingue Creek during spring thaw and summer rain events, 2018-2019
In this larger study, we are asking the question: Is old carbon that comprises the bulk of the soil organic matter pool released in response to thawing of permafrost? We are answering this question by using a combination of field and laboratory experiments to measure radiocarbon isotope ratios in soil organic matter, soil respiration, and dissolved organic carbon, in tundra ecosystems. The objective of these proposed measurements is to develop a mechanistic understanding of the SOM sources contributing to C losses following permafrost thawing. We are making these measurements at an established tundra field site near Healy, Alaska in the foothills of the Alaska Range. Field measurements center on a natural experiment where permafrost has been observed to warm and thaw over the past several decades. This area represents a gradient of sites each with a different degree of change due to permafrost thawing. As such, this area is unique for addressing questions at the time and spatial scales relevant for change in arctic ecosystems. Geochemical analysis of river waters complements the overarching aim of this study by targeting the organic component transported laterally from the catchment and understanding the association between this component and mineral elements. These mineral element-organic carbon associations must be accounted for when considering the stability of organic carbon transported laterally from the catchment.
Streamflow and rain event data from the Tromble experimental watershed weir in the Jornada Basin, southern New Mexico USA, during 2 periods: 1977-1985 and 2003-2011
This data package contains long-term hydrologic event data collected in the Tromble experimental watershed in the Jornada Basin of southern New Mexico, USA. Streamflow and precipitation data were collected at an instrumented flume below a 4.7 hectare shrub-dominated catchment during two periods: 1977-1985 and 2003-2011. This dataset was assembled to evaluate the effects of changes in rainfall on runoff in this Chihuahauan desert watershed. Four data files are available here, including event precipitation totals and sub-hourly runoff details for hydrologic events during both time periods. Variables measured include event precipitation, stage heights at the flume, and calculated discharge rates. This study is complete. For further information, refer to: Turnbull, L., A. J. Parsons, J. Wainwright, and J. P. Anderson. "Runoff responses to long-term rainfall variability in a shrub-dominated catchment." Journal of arid environments 91 (2013): 88-94.
The MATLAB code for "A kinematic model for understanding rain formation efficiency of a convective cell"
<p>Please check the code for the 1D model and the plotting commands. Please start from main.m </p>
Vertical profiles of Doppler spectra of hydrometeors from a Micro Rain Radar recorded during the austral summer of 2016/2017 in the Southern Ocean on the Antarctic Circumnavigation Expedition (ACE).
<p><strong>Dataset abstract</strong></p> <p>This dataset includes vertical profiles of the Doppler spectra and derived quantities of hydrometeors using a Micro Rain Radar (MRR-2) during the Antarctic Circumnavigation Expedition in 2016/2017. The MRR is a frequency-modulated-continuous-wave (FMCW) Doppler radar working at 24 GHz (K band). It measures the Doppler spectrum at vertical incidence with 31 range gates of 100 m. The data are processed to calculate rainfall rates and standard radar moments. For rain events, the drop size distribution and the rainfall rate are derived using the method by Peters et al. (2005). For snow events, the moments are computed from the Doppler spectrum as described in Maahn & Kollias (2012).</p> <p><strong>Dataset contents</strong></p> <ul> <li>RawSpectra/${year}${month}/MRR_ACE_${year}${month}${day}_RAW.nc: raw data of Doppler spectra for rainfall events. Null values are denoted as -99900.</li> <li>ProcessedData/${year}${month}/MRR_ACE_${year}${month}${day}_PRO.nc: 10-second averages (highest resolution) for specific rain events, using the standard products from Metek (MRR physical basics, 2009).</li> <li>AveData/${year}${month}/MRR_ACE_${year}${month}${day}_AVE.nc: one-minute averages, using the standard products from Metek (MRR physical basics, 2009).</li> <li>Processed_IMProToo/${year}${month}/mrr_improtoo_0.101_ACE_${year}${month}${day}.nc: processed data for snow events using IMProToo (Maahn & Kollias 2012) in one-minute averages.</li> <li>RR_timeline/${year}${month}/RR_MRR_ACE_${year}${month}${day}.csv: 10-minute running mean with one-minute resolution of rain rate for [100-200]m and [200-300]m range gate. Null values are denoted as ‘nan’.</li> <li>RR_timeline/${year}${month}/RR_MRR_ACE_${year}${month}${day}.png: daily plots of rain rates.</li> <li>PrecipitationEvents.txt: text file classifying the precipitation events according to hydrometeors (rain, snow or hail).</li> <li>Graphs_Metek/${year}${month}/moments_MRR_ACE_${year}${month}${day}_AVEnc.png: daily plots of Radar reflectivity and Doppler velocity for rain events.</li> <li>Graphs_IMProToo/${year}${month}/moments_mrr_improtoo_0101_ACE_${year}${month}${day}.png: daily plots of Radar reflectivity and Doppler velocity for snow events.</li> <li>RawSpectra_data_file_header.txt, metadata, text format</li> <li>Metek_ProcessedData_data_file_header.txt, metadata, text format</li> <li>IMProToo_ProcessedData_data_file_header.txt, metadata, text format</li> <li>AveData_data_file_header.txt, metadata, text format</li> <li>README.txt, metadata, text format</li> <li>change_log.txt, metadata, text format</li> </ul> <p><strong>Change log</strong></p> <ul> <li>v1.2 - Amended abstract text. Changed descriptions of files in dataset contents. Added dataset license to README. Updated README and change_log files.</li> <li>v1.1 - Added missing PrecipitationEvents.txt file. Added change_log.txt file.</li> <li>v1.0 - Initial version of dataset.</li> </ul> <p><strong>Dataset license</strong></p> <p>This vertical Doppler spectra profile dataset is made available under the Creative Commons Attribution 4.0 International License (CC BY 4.0) whose full text can be found at https://creativecommons.org/licenses/by/4.0/</p>
Data from: Low coverage genomic data resolve the population divergence and gene flow history of an Australian rain forest fig wasp
Population divergence and gene flow are key processes in evolution and ecology. Model-based analysis of genome-wide datasets allows discrimination between alternative scenarios for these processes even in non-model taxa. We used two complementary approaches (one based on the blockwise site frequency spectrum (bSFS), the second on the Pairwise Sequentially Markovian Coalescent (PSMC)) to infer the divergence history of a fig wasp, Pleistodontes nigriventris. Pleistodontes nigriventris and its fig tree mutualist Ficus watkinsiana are restricted to rain forest patches along the eastern coast of Australia, and are separated into northern and southern populations by two dry forest corridors (the Burdekin and St. Lawrence Gaps). We generated whole genome sequence data for two haploid males per population and used the bSFS approach to infer the timing of divergence between northern and southern populations of P. nigriventris, and to discriminate between alternative isolation with migration (IM) and instantaneous admixture (ADM) models of post divergence gene flow. Pleistodontes nigriventris has low genetic diversity (π = 0.0008), to our knowledge one of the lowest estimates reported for a sexually reproducing arthropod. We find strongest support for an ADM model in which the two populations diverged ca. 196kya in the late Pleistocene, with almost 25% of northern lineages introduced from the south during an admixture event ca. 57kya. This divergence history is highly concordant with individual population demographies inferred from each pair of haploid males using PSMC. Our analysis illustrates the inferences possible with genome-level data for small population samples of tiny, non-model organisms and adds to a growing body of knowledge on the population structure of Australian rain forest taxa.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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.