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edi48/100

Geospatial data for Luquillo Mountains, Puerto Rico: Mean annual precipitation, elevation, watershed outlines, and rain gage locations

The data archive is here: https://doi.org/10.5066/F74F1PM2 please use this DOI when citing this data set. These geospatial data sets were developed as part of a new analysis of all known current and historical rain gages in the Luquillo Mountains, Puerto Rico published in the journal article Murphy, S.F., Stallard, R.F., Scholl, M.A., Gonzalez, G., and Torres-Sanchez, A.J., 2017, Reassessing rainfall in the Luquillo Mountains, Puerto Rico: Local and global ecohydrological implications: PLOS One 12(7): e0180987, p. 1-26, https://doi.org/10.1371/journal.pone.0180987. That article provides a revised map of mean annual precipitation developed using elevation regression functions and residual interpolation, and that map is presented here in a raster file. Most previous forest- and watershed-wide estimates of precipitation (and evapotranspiration, as inferred by a water balance) have assumed that precipitation increases consistently with elevation in the Luquillo Mountains; therefore, precipitation in leeward Luquillo watersheds has been overestimated by up to 40%.Because the Luquillo Mountains often serve as a wet tropical archetype in global assessments of basic ecohydrological processes, these revised estimates are relevant to regional and global assessments of runoff efficiency, hydrologic effects of reforestation, geomorphic processes, and climate change. \<para\> Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.\</para\>

openCC (other)Apr 2023View details →
edi48/100

Springtails (Arthropoda, Collembola) from Greater Puerto Rico: species list and distribution

The data archive is here: https://doi.org/10.2737/RDS-2018-0063 please use this DOI when citing this dataset. The Collembola fauna of Puerto Rico is reasonably well known, but many recent reports are scattered in published literature and unpublished theses. Here we present a summary of all springtail species identified from the Bank of Puerto Rico since 1927 and 2011. This includes new, previously unpublished records. In the present review we list 119 species in 59 genera and 17 families. Most species (37) belong in family Entomobryidae, but this reflects the taxonomic expertise of specialists working in Puerto Rico rather than a real bias in the distribution of higher taxa in the islands. In addition to the new reports, these data provide information on the distribution of the species outside the island bank. This current list of species is an update to original species lists from Puerto Rico (Mari Mutt 1982 and Thibaud 2014). In addition to the list of species, we make available a data set that includes a catalog of species, their habitats, historical reports and distribution maps on Greater Puerto Rico. \<para\> Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.\</para\>

openCC (other)Apr 2023View details →
edi48/100

Rainfall and ion composition data from multiple weather stations along an elevation gradient in northeastern Puerto Rico (2009-2018)

The data archive is here: https://doi.org/10.2737/RDS-2021-0013 please use this DOI when citing this dataset. Rainfall and ionic composition data were collected at 21 sites along the elevational gradient of the Luquillo Mountains, in Puerto Rico. Stations were selected along the east coast of the island and follow the steep slope of the mountains until the highest peaks. Rainfall data were collected every two weeks and are provided in this data publication as monthly rainfall from January 2009 through May 2019. Also included are pH and conductivity which are provided monthly starting roughly in November 2011 and continue through May 2019. Monthly ionic composition data from rainwater samples collected during the last two weeks of each month are also included from January 2009 through December 2017. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Feb 2024View details →
edi48/100

Canopy damage and recovery following Hurricane Maria using multitemporal lidar data, Mar-2017 - Mar-2020, Puerto Rico

The data archive is here: http://dx.doi.org/10.15486/ngt/1797399 please use this DOI when citing this dataset. Hurricane Maria (Category 4) snapped and uprooted canopy trees, removed large branches, and defoliated vegetation across Puerto Rico. The magnitude of forest damages and the rates and mechanisms of forest recovery following Maria provide important benchmarks for understanding the ecology of extreme events. We used airborne lidar data acquired before (2017) and after Maria (2018, 2020) to quantify landscape-scale changes in forest structure along a 439-ha elevational gradient (100 to 800 m) in the Luquillo Experimental Forest. Damages from Maria were widespread, with 73% of the study area losing ≥1 m in canopy height (mean = -7.1 m). Taller forests at lower elevations suffered more damage than shorter forests above 600 m. Yet only 13% of the study area had canopy heights ≤2 m in 2018, a typical threshold for forest gaps, highlighting the importance of damaged trees and advanced regeneration on post-storm forest structure. Heterogeneous patterns of regrowth and recruitment yielded shorter and more open forests by 2020. Nearly 45% of forests experienced initial height loss (<-1 m, 2017-2018) followed by rapid height gain (>1 m, 2018-2020), whereas 21.6% of forests with initial height losses showed little or no height gain, and 17.8% of forests exhibited no structural changes >|1| m in either period. Canopy layers <10 m accounted for most increases in canopy height and fractional cover between 2018-2020, with gains split evenly between height growth and lateral crown expansion by surviving individuals. These findings benchmark rates of gap formation, crown expansion, and canopy closure following hurricane damage. Included in the attached zip file are four TIF and four KML files. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National

openCC (other)Apr 2023View details →
edi48/100

Soil phosphorus, litterfall mass, nitrogen and phosphorus in eight Puerto Rico forests affected by hurricanes Hugo, Bertha, Georges, Irma, and Maria.

Tropical cyclones are intensifying and occurring at higher latitudes in recent decades, but the mechanisms underpinning the resistance (ability to withstand disturbance-induced change) and resilience (pace of return to pre-disturbance reference values) of tropical forests to cyclones remains largely unexplored at the pantropical scale. We conducted a meta-analysis to investigate the role of soil resource availability (i.e., total soil phosphorus concentration) in mediating site-level forest canopy resistance and resilience to cyclones pan-tropically. We evaluated cyclone-induced and post-cyclone litterfall mass (g/m2/day), phosphorus (P) and nitrogen (N) fluxes (mg/m2/day), as well as concentrations (mg/g) across 73 case studies in Australia, Guadeloupe, Hawaii, Mexico, Puerto Rico, and Taiwan (Bomfim et al., in review). This dataset includes information related to 42 case studies in eight Puerto Rico forests affected by hurricanes Hugo, Bertha, Georges, Irma, and Maria between 1989 and 2017. This dataset also includes data for the canopy trimming experiment (CTE) in El Verde. - The compiled Litterfall Mass and Nitrogen and Phosphorus Flux and Concentration data from natural forest ecosystems across Puerto Rico prior to and after eight hurricanes are provided in Forest-Soil-Litterfall-Hurricane_Puerto-Rico.csv. This data file also includes site location, geographical characteristics, elevation, soil phosphorus concentration, geology, and several variables related to each hurricane disturbance. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Apr 2023View details →
edi48/100

Northeastern Puerto Rico open-canopy and under-canopy temperature and moisture data on an elevational gradient

The data archive is here:https://doi.org/10.2737/RDS-2022-0051 please use this DOI when citing this dataset. This data publication contains monthly means of temperature and moisture data collected from August 2006 through September 2021 from 22 locations along an elevational gradient, from 0 to 1045 meters, in Northeastern Puerto Rico. The higher elevational data are in the Luquillo Experimental Forest (El Yunque National Forest). Five kinds of data are included: air temperature and precipitation measured in the open (not under canopy) at 20 locations, air temperature and soil temperature both measured under the canopy at all 22 locations, and soil moisture under the canopy at 4 locations. Two locations have 3 sites each, measured in different canopy types at the same location. The other 20 locations have one site each, making a total of 26 measurement sites. Data are provided as monthly averages at each site. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Feb 2024View details →
edi48/100

Chemistry of coastal stream and lagoon water from Puerto Rico - 2021-2024

Water samples were collected from coastal streams and lagoons in Puerto Rico from February 2021 to March 2024 as part of ongoing coastal ecosystem monitoring. These samples were analyzed at the University of New Hampshire Water Quality Analysis Laboratory for comprehensive water chemistry including field parameters, major ions, nutrients, dissolved gases, and trace metals. Sampling sites included Quebrada Fajardo (QFJO) at multiple depths and distances upstream, Quebrada Pitahaya (Qpaya), Laguna Pitahaya (LPYHA), Luquillo streams (LUQA, LUQB), and Laguna Cartagena (LCART). Field measurements included pH, conductivity, dissolved oxygen, temperature, turbidity, and atmospheric pressure. Laboratory analyses encompassed dissolved organic carbon (DOC), total dissolved nitrogen (TDN), nutrients (NH4-N, PO4-P, NO3-N), major ions (Cl, SO4, Na, K, Mg, Ca), dissolved gases (CH4, CO2, N2O), and trace metals by Inductively Coupled Plasma (ICP) analysis. The ICP analysis provided enhanced detection capabilities for cations and metals including calcium, iron, manganese, silicon, strontium, sulfur, sodium, magnesium and potassium. Samples were collected as grab samples from the water surface. All samples were filtered through pre-combusted Whatman GF/F for nutrients and organic matter and Whatman WCN Cellulose Nitrate Membranes for metals. Values below detection limits are recorded as 1/2 the detection limit. This dataset provides comprehensive water quality data for Puerto Rican coastal watersheds, with particular focus on stratified sampling in Quebrada Fajardo to understand vertical water column structure and biogeochemical processes in coastal environments influenced by both terrestrial and marine inputs. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecol

openCC (other)Dec 2025View details →
edi48/100

Physical environment of the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

This file contains data that describe the physical and environmental attributes of the LFDP. The attributes include elevation, topography type, and percentage slope. All data are given for the 20 m by 20 m quadrat scale. Information on soils are taken form an interpolation of the soil map produced by the Natural Resources Conservation Service, US Department of Agriculture (Soil Survey 1995). Other information from the elevation of each of the corner posts defining the quadrats.The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and “cleaned”. The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Principal Investigators request that researchers intending to use this data comply with the requests below. Through complying with these requests we can ensure that the data are interpreted correctly, analyses are not repeated unnecessarily, beneficial collaboration between users is promoted and the Principle Investigators investment in this project is protected. Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.

openCC (other)Nov 2023View details →
edi48/100

Tree damage by Hurricane Hugo on the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

Hurricane Hugo struck the Caribbean national forest in September 1989. Files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT contain data on the damage to trees caused by the hurricane collected by Mr. R. DeLeon between August 1990 and September 1991. Mr. DeLeon walked throughout the plot to find stems &gt;= 10 cm diameter that had apparently been damaged or killed by the hurricane in an effort to collect information before the damaged stems rotted. The information on these stems was later combined with the results of the first census to reconstruct the forest, as it would have appeared, at the time of Hurricane Hugo. This file contains the hurricane damage data collected for stems damaged by Hurricane Hugo combined with data for the stems recorded subsequently in the first complete LFDP census starting in 1990. Some stems that were measured in Census 1 survey 2 and survey 3 or Census 2 that were believed to have been missed in Census 1 survey 1, are also included (see census history above) and are assumed to have been undamaged by Hurricane Hugo. The structure of the data files is the same for both files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT but the diameter of the trees in LFDP_HURRDAMa.TXT have been calculated by extrapolating diameters backwards from subsequent measurements to the time of the Census 1 survey 1. Diameters in file LFDP_HURRDAMa.TXT can not be used for growth measurements. For our publications we treat files LFDP_HURRDAM.TXT and LFDP_HURRDAMa.TXT as one data set. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these d

openCC (other)Nov 2023View details →
edi48/100

Tree Map for Census at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

This data set shows the Tag number, Quadrat location, Species code, diameter and XY coordinates of stems &gt;=10 cm D130 present at the time of Hurricane Hugo and in the first census. The data set is composed of two files both with the same file structure. In LFDP_C1treemap.txt the diameters (Fdiam) are as recorded in the field data. In LFDP_C1TREEMAPa.txt the stem diameters (Fdiam) were calculated to allocate "missed" stems (stems &gt;=10 cm D130) that were found in survey 2, 3 or Census 2 to Census 1 survey 1. We calculated the diameter the stem would have had, if it had been recorded at the same time the quadrat it was located in was assessed, in the appropriate survey for that stem size. To extrapolate the stem size back in time, we used the actual growth rate of that individual stem if more than one measurement was available. If only one diameter measurement was available we used the median growth rate for that species in the appropriate size class stems &gt;=10, &lt;30 cm D130). In our publications we will combine data sets LFDP_C1treemap.txt and LFDP_C1TREEMAPa.txt to make Census 1 and to reconstruct the forest for stems &gt;= 10 cm D130 at the time of Hurricane Hugo. We have divided the data into two separate files to ensure that when stem diameters are compared to future censuses the diameter data in LFDP_C1TREEMAPa.txt are not used to calculate growth rates. The last corrections to the Census 1 data were made in May 2001. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Princi

openCC (other)Nov 2023View details →
edi48/100

Canopy height profile starting 1992, 1994 and 1996 of the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

File LFDP_canopy contain the canopy heights for the Luquillo forest Dynamics plot. The first measurement started in 1992, and it was planned to measure the canopy height profile every 2 years. So far censuses starting in 1992, 1994, and 1996 have been completed. In the 1992 census the canopy height profile at points along the East and North limits of the plot were not included. In 1994 and 1996 these extra points were assessed. The National Science Foundation requires that data from projects it funds are posted on the web two years after any data set has been organized and "cleaned". The data from each census of the LFDP will be updated at intervals as each survey of the LFDP shows errors in the previous data collection. After posting on the web, researchers who are not part of the project are then welcome to use the data. Given the enormous amount of time, effort and resources required to manage the LFDP, obtain these data, and ensure data accuracy, LFDP Principal Investigators request that researchers intending to use this data comply with the requests below. Through complying with these requests we can ensure that the data are interpreted correctly, analyses are not repeated unnecessarily, beneficial collaboration between users is promoted and the Principle Investigators investment in this project is protected. Submit to the LFDP PIs a short (1 page) description of how you intend to use the data; · Invite LFDP PIs to be co-authors on any publication that uses the data in a substantial way (some PIs may decline and other LFDP scientists may need to be included); If the LFDP PIs are not co-authors, send the PIs a draft of any paper using LFDP data, so that the PIs may comment upon it; In the methods section of any publication using LFDP data, describe that data as coming from the "Luquillo Forest Dynamics Plot, part of the Luquillo Experimental Forest Long-Term Ecological Research Program"; Acknowledge in any publication using LFDP data the "The Luquillo Experim

openCC (other)Nov 2023View details →
zenodo44/100

Electric power outages from 900k simulated hurricanes in a changing climate, for the United States and Puerto Rico

<p>This dataset is described and explored in Rice et al. 2025, "<a href="https://doi.org/10.1088/1748-9326/adad85">Projected Increases in Tropical Cyclone-induced U.S. Electric Power Outage Risk</a>", published in Environmental Research Letters.</p> <p>This dataset collects peak outage levels modeled for 900,000 synthetic tropical cyclones (TCs; also commonly known as hurricanes) representative of a modeled historical (1980-2015) and future (2066-2100) period under SSP5-8.5 warming. Synthetic TCs are generated with the Risk Analysis Framework for Tropical Cyclones (RAFT; see Xu et al. 2024 and Balaguru et al. 2023), forced by climate simulation data from the Coupled Model Intercomparison Project phase 6 (CMIP6; see Eyring et al. 2016). Outages are modeled with the newly introduced Electric Power Outages from Cyclone Hazards (EPOCH) model, which was trained on county-level outage data from 23 historical TC events in the EAGLE-I dataset (Brelsford et al. 2024).&nbsp;</p> <p>The EPOCH model predicts outages based on county population and the maximum wind speed and rainfall rate experienced during the TC. Predicted outage levels are provided in the form of peak outage fraction: the maximum fraction of electricity customers expected to experience an outage at any one time during the storm's lifetime. Although we do not model outage duration, other research suggests peak outage level is strongly correlated with duration (Jamal and Hasan, 2023).</p> <p><strong>Data Format</strong></p> <p>The data is provided in NetCDF4 files, one for each CMIP6 model and time period. Each NetCDF4 files has the following:</p> <p>Dimensions:</p> <ul> <li>ncounties = 2715. The counties in the study domain</li> <li>ntracks = 50000. The number of storms</li> </ul> <p>Variables:</p> <ul> <li>int pseudofips(ncounties). The FIPS code for each county. Puerto Rico data is not available at county level, but instead for six utility-defined regions. We assign "pseudo-FIPS" codes to these region starting at 100000</li> <li>double centroid_lons(ncounties). Longitude of approximate center of county, in the range [-180, 0].</li> <li>double centroid_lats(ncounties). Latitude of approximate center of county, in the range [0, 90].</li> <li>float outage_prediction(ntracks, ncounties). The predicted peak outage fraction for each county, for each storm. Due to the particularities of ensemble models, some predictions may be slightly below zero or above one; we clip these values to the range [0,1] before any analysis in our study.</li> <li>ubyte prediction_complete_flag(ntracks). A verification flag used during dataset generation. This flag should equal 1 everywhere for complete data.</li> </ul> <p>Each file also contains the raw predictors at a county level for every storm, inside the 'predictors' group, for feature analysis.</p> <p>Also provided for convenience is 'counties_pseudofips.csv', which maps the pseudo-FIPS codes to the the name and spatial extent (WKT format) of each county. It can be read easily by Python GeoPandas, or other software.</p>

opencc-by-4.0Jul 2024View details →
zenodo44/100

National Checklists 2017: Puerto Rico Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details<p></p>A list of species from Puerto Rico collected using effechecka and geonames polygons

opencc-zeroAug 2024View details →
zenodo44/100

National Checklists 2019: Puerto Rico Species List

Lists of taxa for each country and a few other administrative zones harvested from effechecka using simplified versions of geonames polygons. See <p></p>https://github.com/diatomsRcool/checklists for details.<p></p>A list of species from Puerto Rico collected using effechecka and geonames polygons

opencc-zeroAug 2024View details →
edi44/100

Odonata Assemblage in Metropolitan Area of Puerto Rico (2018-2019, Wet and Dry Season)

Data comes from a project that aimed to identify the effects of urbanization on stream habitat quality and associated odonate assemblages in Puerto Rico. In this study, 16 streams along a rural to urban gradient in the San Juan Metropolitan Area were sampled. Each stream was characterized using the Stream Visual Assessment Protocol (SVAP) for Puerto Rico and by analyzing their surrounding land cover. A 100-m segment of each stream was surveyed to assess adult odonate richness and abundance during the rainy and dry seasons. Adults were identified visually, and their abundance was recorded. Data is a product of: Maldonado-Benítez, Mariani-Ríos & Ramírez (2022): Effects of urbanization on Odonata assemblages in tropical island streams in San Juan, Puerto Rico. International Journal of Odonatology, 25, 31–42 doi:10.48156/1388.2022.1917163

openCC (other)Aug 2022View details →
edi44/100

Species names and codes of the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico

File LFDP_spp contains the current species list with family for the Luquillo Forest Dynamics plot and the codes for these species found in LFDP1 and LFDD1a As new species are encountered or renamed and species renamed then this list will be updated Species identifications are assisted by reference to Liogier (1985, 1988, 1994, 1995, 1997), Little and Wadsworth (1964) Little, et al (1974), Little and Woodbury (1976). \<para\> Support for this work was provided by grants BSR-8811902, DEB-9411973, DEB-9705814 , DEB-0080538, DEB-0218039 , DEB-0620910 , DEB-1239764, DEB-1546686, and DEB-1831952 from the National Science Foundation to the University of Puerto Rico as part of the Luquillo Long-Term Ecological Research Program. Additional support provided by the University of Puerto Rico and the International Institute of Tropical Forestry, USDA Forest Service.\</para\>

openCC (other)Nov 2023View details →
edi44/100

Measurements of height, diameter at breast height and basal diameter for Prestoea acuminata at the Luquillo Forest Dynamics Plot (LFDP), Puerto Rico in January 2020.

Data were collected in January 2020 in Puerto Rico, within and outside the boundaries of LFDP. For each of these palms, we measured stem height from the ground to the base of the crown (Hbc; height of the youngest internode), diameter at 130 cm above ground (D130), and basal diameter (DB; just above the top of the roots). These are the data which accompany the publication: Height-diameter allometry for a dominant palm to improve understanding of carbon and forest dynamics in forests of Puerto Rico.

openCC (other)Dec 2023View details →
edi44/100

Statistically downscaled future precipitation for the Luquillo Mountains, Puerto Rico

This dataset contains climate predictions that serve as the basis for the analysis in Ramseyer et al. (2019), which projected a trend toward drier conditions in eastern Puerto Rico during the mid- and late-21st century. The analysis was informed by computing nine atmospheric variables, which had been shown by previous research to related to precipitation in Puerto Rico (Ramseyer and Mote 2016) from four GCMs. These nine variables were used to train an artificial neural network (ANN) to predict the binary occurrence of a wet (>= 5 mm of precipitation) versus dry (<5 mm) day using in-situ daily precipitation observations from El Verde Field Station in northeast Puerto Rico. The nine atmospheric variables used to train the ANN were: 1000- 850-, 700-, and 500-hPa daily specific humidity, 1000–700-hPa bulk wind shear (BWS), the Gálvez-Davison Index (GDI), and the GDI's three component terms (the column buoyancy index, mid-level warming index, and a trade-wind inversion index). These same nine variables were then extracted on a daily basis from four GCMs for the eastern Caribbean early rainfall season (April-July) between 2041-2060 and 2081-2100, and fed through the ANN. These data are the daily predicted values of wet (1) or dry (0) conditions for each of the four GCMs in the ensemble. Because ERS total precipitation at El Verde is strongly correlated with the percentage of ERS dry days (R2=0.95 for years with <10% missing data), the GCM predictions were used to estimate future ERS precipitation using the following formula: ERS precipitation (mm) = 3373-37.6*(ERS dry-day percentage) Applying this formula to each of the GCM dry-day projections yielded an ensemble mean ERS precipitation total of 771 mm by 2041-2060 and 974 mm by 2081-2100. See Ramseyer et al. (2019) for a complete description of the neural network and its predictions. Ramseyer, C., P. Miller, and T. Mote, 2019: Future precipitation variability during the early rainfall season in the El Yunque National Fore

openCC (other)Mar 2024View details →
zenodo40/100

FIGURE 16 in Tergoceracris, a new genus and six new species of montane grasshoppers (Orthoptera: Acrididae: Ommatolampinae) from Dominican Republic and Puerto Rico

FIGURE 16. Genitalia complex of T. cerropunta. A, B, entire complex (with epiphallus removed) showing lateral and dorsal views. C, D, epiphallus showing dorsal and posterior views.

opencc-zeroDec 2003View details →
zenodo40/100

FIGURE 10 in Tergoceracris, a new genus and six new species of montane grasshoppers (Orthoptera: Acrididae: Ommatolampinae) from Dominican Republic and Puerto Rico

FIGURE 10. Genitalia complex of T. ocampensis. A, B, entire complex (epiphallus removed) showing lateral and dorsal views. C, D, epiphallus showing dorsal and posterior views. Abbreviations: bpf, basal phallic fold; ls, lateralsclerite of basal phallic fold; apc, apodeme of cingulum; ap, anteriorplate of epiphallus; lo, lophi of epiphallus; en, endophallic plate.

opencc-zeroDec 2003View details →

ScienceDex guides

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

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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.

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

Annotated Behaviour and Observability Dataset (ABODe)

ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.

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

DANDI Archive for NWB datasets

DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.

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

International Brain Laboratory public data

The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.

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

OpenNeuro

OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.

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