Find research datasets worth reusing

Conservation and management of migratory fauna and dams in tropical streams of Puerto Rico

1. Compared to most other tropical regions, Puerto Rico appears to have dammed its running waters decades earlier and to a greater degree. The island has more large dams per unit area than many countries in both tropical and temperate regions (e.g., 3x that of the U.S.), and the peak rate of large dam construction occurred two and three decades prior to reported peak rates in Latin America, Asia and Africa.2. Puerto Rico is a potential window into the future of freshwater migratory fauna in tropical regions, given the island's extent and magnitude of dam development and the available scientific information on ecology and management of the island's migratory fauna.3. We review ecology, management and conservation of migratory fauna in relation to dams in Puerto Rico. Our review includes a synthesis of recent and unpublished observations on upstream effects of large dams on migratory fauna and an analysis of patterns in free crest spillway discharge across Puerto Rican reservoirs. Analyses suggest that large dams with rare spillway discharge cause near, not complete, extirpation of upstream populations of migratory fauna. They also suggest several management and conservation issues in need of further research and consideration. These include research on the costs, benefits and effectiveness of simple fish/shrimp passage designs involving simulating spillway discharge and the appropriateness of establishing predatory fishes in reservoirs of historically fishless drainages. 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.

openCC0Nov 2023View details →

Does the River Continuum Concept apply on a tropical island? Longitudinal variation in a Puerto Rican stream

We examined whether a tropical stream in Puerto Rico matched predictions of the River Continuum Concept (RCC) for macroinvertebrate functional feeding groups (FFGs). Sampling sites for macroinvertebrates, basal resources, and fishes ranged from headwaters to within 2.5 km of the fourth-order estuary. In a comparison to a model temperate system where RCC predictions generally held, we used catchment area as a measure of stream size in order to examine truncated RCC predictions (i.e., cut off to correspond to the largest stream size sampled in Puerto Rico). Despite dominance of generalist freshwater shrimps, which use more than one feeding mode, RCC predictions held for scrapers, shredders, and predators. Collector-filterers showed a trend opposite that predicted by the RCC, but patterns in basal resources suggest that this is consistent with the central RCC theme: longitudinal distributions of FFGs follow longitudinal patterns in basal resources. Alternatively, the filterer pattern may be explained by fish predation affecting distributions of filter-feeding shrimp. Our results indicate that the RCC generally applies to running waters on tropical islands. However, additional theoretical and field studies across a broad array of stream types should examine whether the RCC needs to be refined to reflect the potential influence of top-down trophic controls on FFG distributions. 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.

Effects of a tropical stream poisoning: do they reflect effects of small-scale experiments?

Small-scale experiments in tropical streams have suggested that freshwater shrimps play a critical role in determining the quality and quantity of benthic organic matter and overall nutrient dynamics. We quantified the effects of a whole-reach shrimp poisoning event in the Sonadora, a second-order stream draining the Luquillo Experimental Forest in northeastern Puerto Rico. The illegal poisoning (for shrimp harvest) caused massive mortality of shrimps and aquatic insects. Atyid and xiphocaridid shrimp abundances in pools of the poisoned reach were reduced by ~95%, relative to abundances in an upstream reference reach. A survey of poisoned vs. reference pools, combined with a manipulative experiment (in which atyid and xiphocaridid shrimps were added to 3 poisoned pools), showed that reduced shrimp abundances due to the poisoning had strong impacts on benthic resources. The benthos of poisoned pools, where shrimp abundances were reduced, had 4 times more chlorophyll a, 6 times more algal biovolume, 4 times more fine particulate organic matter, 14 times more fine particulate inorganic matter, 5 times more carbon, and 4 times more nitrogen than did the benthos of pools in the reference reach. These increases in benthic resources were consistent with increases in algae, organic/inorganic matter, and nutrients in previous small-scale shrimp exclusion experiments conducted in the study river and tributaries. Effects of shrimp poisoning on the benthos varied by habitat, with riffles showing fewer significant differences than did pools. Compared to reference riffles, poisoned riffles had higher standing stocks of fine particulate inorganic matter, nitrogen, and biovolume of filamentous algae, and lower epilithic C:N ratios. Overall, previous small-scale exclusion experiments were highly predictive of the direction of effects due to large-scale shrimp removal by poisoning. Our study provides a tropical data set to add to the short list of stream studies that examine the pred

openCC (other)Apr 2023View details →

Tropical green roofs vegetation dynamics data

The data archive is here: https://doi.org/10.2737/RDS-2021-0024 please use this DOI when citing this dataset. This publication contains data collected in 2017 from three green roofs at the International Institute of Tropical Forestry in San Juan, Puerto Rico and one green roof at the Social Sciences Faculty of the University of Puerto Rico in Río Piedras. Data from these extensive green roofs include substrate depth as well as species counts within a sampled quadrant, as well as species identification information. 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 →

fungal interactions during tropical leaf decomposition

Fungal interactions during leaf decomposition can facilitate or inhibit other fungi. This experiment focused on whether preconditioning of leaf litter by microfungi that were confined to one leaf (Unit-Restricted) made leaf litter less likely to be colonized and decomposed by basidiomycetes that bind litter into mats (Non-Unit- Restricted) than non-preconditioned litter. Leaves of Manilkara bidentata in litterbags were preconditioned by incubating them for 0, 1, 2 or 3 months in flat litter/seed rain baskets 10 centimeters above the forest forest floor to avoid colonization by basidiomycete fungi. Preconditioned and non-preconditioned leaves were transferred to 5 replicate basidiomycete fungal mats of Gymnopus johnstonii for 6 weeks. Both attachment by basidiomycete fungi and percent mass loss after 6 weeks decreased significantly with increasing preconditioning time. In non-preconditioned leaves, gamma irradiation did not affect mass loss or percent white-rot despite having significantly increased numbers of basidiomycete fungal connections as compared to non-irradiated leaves. In non-preconditioned leaves, more basidiomycete attachments to non-irradiated than irradiated leaves suggest facilitation by phyllosphere microfungi. While basidiomycete colonization was initially facilitated by phyllosphere fungi, we inferred that degradation of resource quality led to fewer fungal attachments and less mass loss after 1-3 months of preconditioning by microfungi. There is a 1-month time window for basidiomycete fungi to incorporate fallen leaves into their litter mats. 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 Forest

Earthworms in tropical tree plantations and secondary forests

We compared patterns of earthworm abundance and species composition in tree plantations and secondary forests of Puerto Rico. Tree plantations included pine (Pinus caribaea Morelet) and mahogany (Swietenia macrophylla King) established in the 1930s, 1960s, and 1970s; secondary forests were naturally regenerated in areas adjacent to these plantations. We found that (1) earthworm density and fresh weight in the secondary forests were twice those in either of the tree plantations, and did not differ between the plantations, and (2) the exotic earthworm species, Pontoscolex corethrurus M ller, dominated both plantations and the secondary forests, but native earthworm species, Pontoscolex spiralis Borges & Moreno, Estherella montana Gates, and E. gatesi Borges & Moreno, occurred only in the secondary forests. Our results suggest that naturally-regenerated secondary forests are preferable to pine and mahogany plantations for maintaining a high level of earthworm density, fresh weight, and native species. 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.

Earthworms in abandoned tropical pastures

Plant community succession alters the quantity and chemistry of organic inputs to soils. These differences in organic input may trigger changes in soil fertility and faunal activity. We examined earthworm density and community structure along a successional sequence of plant communities in abandoned tropical pastures in Puerto Rico. The chronological sequence of these plant communities were pasture, grass-vine-fern, shrub-small tree, and forest. Earthworm density was the highest in pasture (831 worms/m2 in top 0.25 m soil), decreased as secondary succession proceeded, and reached the lowest (32 worms/m2) in the forest. Whereas only soil feeding Pontoscolex corethrurus was present in the pasture and grass-vine-fern communities, both soil and litter feeding worm species were found in the shrub-small tree and forest communities. Ground litter biomass had a negative correlation with earthworm density. Soil water content differed slightly among the successional communities, but were unlikely to play an important role in triggering differences in worm density among these abandoned lands. Soil pH values did not differed along the successional changes. These results suggest that decrease in earthworm density and increase in worm community diversity during secondary succession may result from changes in the quantity and chemistry of organic inputs, rather than in soil properties. We conclude that successional development from grass-dominated pastures to woody species-dominated forests reduces earthworm density and diversifies worm community structure in humid tropical soils. 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 F

opencc-by-4.0Jul 2020View details →

Data from: Trade-off between standing biomass and productivity in species-rich tropical forest: evidence, explanations and implications

These files are the R code and plot data files used for calculating species population turnover of biomass and abundance in a tropical forest plot. This dataset is a processed subset of the original dataset used in our analysis of biomass turnover across tree populations as demonstrated in <a href="https://doi.org/10.1111/1365-2745.13485">the main paper</a>. Readers interested in using the Pasoh 50-ha plot data for purposes other than reviewing our analysis are advised to contact the <a href="https://www.frim.gov.my/">Forest Research Institute Malaysia (FRIM)</a> and the <a href="https://forestgeo.si.edu/">Center for Tropical Forest Science-Forest Global Earth Observatory (CTFS-Forest GEO)</a>, Smithsonian Tropical Research Institute.

opencc-by-4.0Aug 2020View details →

The datasets used in the manuscript named "Dynamical Seasonal Prediction of Tropical Cyclone Activity Using a Global Ensemble Prediction System FGOALS-f2 V1.0"

The hindcast and real-time prediction output of FGOALS-f2 V1.0 used in the study named "Dynamical Seasonal Prediction of Tropical Cyclone Activity Using a Global Ensemble Prediction System FGOALS-f2 V1.0"

opencc-by-4.0Jan 2022View details →

Model outputs from the study "A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce region"

Model outputs from the study "A scalable framework for soil property mapping tested across a highly diverse tropical data-scarce region". The study is published as open access and can be found at the following link: <a href="https://www.sciencedirect.com/science/article/pii/S2950289625000326">https://www.sciencedirect.com/science/article/pii/S2950289625000326</a>   The file "SWAT_USERSOIL.csv" was included to facilitate the assimilation of the soil mapping data into the Soil & Water Assessment Tool (SWAT, https://swat.tamu.edu/) for hydrological modeling.    Regarding the raster files, please note: a) All values in these datasets have been multiplied by 10,000 to optimize file sizes. b) Files are named using the variable acronym, followed by the corresponding soil layer. For outputs derived from pedotransfer functions (PTFs), the PTF reference is appended after the variable acronym. c) Available data decrease with increasing soil layer number. This occurs because not all locations (grid cells) have the same soil depth or number of soil layers.   If you have any questions about the dataset or its use, please don't hesitate to contact us.

opencc-by-4.0Dec 2023View details →

CamTrapAsia: a dataset of tropical forest vertebrate communities from 239 camera trapping studies

Dataset containing data from 239 camera trap studies conducted in tropical Asia. A total of 278,260 independent records were compiled, from 371 distinct species, comprising 232 mammals, 132 birds, and 7 reptiles. The accumulated trapping effort was 876,606 trap nights, distributed among Indonesia, Singapore, Malaysia, Bhutan, Thailand, Myanmar, Cambodia, Laos, Vietnam, Nepal and far-eastern India.

opencc-by-4.0Nov 2021View details →

Supplemental Data for "Eyewall Asymmetries and Their Contributions to the Intensification of an Idealized Tropical Cyclone Translating in Uniform Flow"

The repository contains a set of files required to reproduce the idealized tropical cyclone simulation analyzed in the manuscript entitled "Eyewall asymmetries and their contributions to the intensification of an idealized tropical cyclone translating in uniform flow", submitted to the Journal of the Atmospheric Sciences. See the README file for brief descriptions about the content of each file within this repository. The simulation was produced with the Cloud Model 1 (CM1) version 19.7, and CM1 can be downloaded at https://www2.mmm.ucar.edu/people/bryan/cm1/.

opencc-by-4.0Nov 2021View details →

Dataset from: 'Tropical deforestation accelerates local warming and loss of safe outdoor working hours'

Abstract: 'Climate change has increased heat exposure in many parts of the tropics, negatively impacting outdoor worker productivity and health. Although it is known that tropical deforestation causes local warming, the extent to which this warming affects people across the tropics is unknown. Here, we combine worker health guidelines with satellite, reanalysis, and population data to investigate how increases in local temperatures associated with recent deforestation (2003-2018) affects outdoor working conditions across low-latitude countries, and how future global climate change will magnify heat exposure for people in deforested areas. We find that the local warming associated with just 15 years of deforestation has caused losses in safe thermal working conditions for 2.8 million outdoor workers. We also show recent large-scale forest loss caused particularly large impacts on populations in locations such as the Brazilian states of Mato Grosso and Pará. Future global warming and additional forest loss will magnify these impacts.'

opencc-by-4.0Nov 2021View details →

United States tornado reports in landfalling tropical cyclones used in Paredes et al. (2021)

These data include all tropical cyclone tornado reports used in Paredes et al. (2021) plus an additional year (e.g., 2020).  These data will not be updated regularly.  For the latest version, users should refer to https://www.spc.noaa.gov/misc/edwards/TCTOR/ or contact roger.edwards@noaa.gov. Each specific tropical cyclone tornado record has been extracted from the broader Storm Prediction Center tornado database, for all Atlantic and Gulf of Mexico tropical cyclones to affect the continental United States from 1995–2020. The tornado records were analyzed individually to determine their presence within the circulation envelope of either a classified or remnant tropical cyclone, without regard to fixed radii from tropical cyclone center, inland extent, temporal cutoffs before or after landfall, or other such arbitrary thresholds that may either exclude tropical cyclone events or include non-tropical cyclone tornadoes unnecessarily. Unlike other climatologies previously published in the literature, the chosen time period for this examination essentially covers only the full national deployment of the WSR-88D radar network in the United States. This permits consistent comparisons of a very large sample size of tropical cyclone tornado events (>1600) during the era of modernized National Weather Service warning and verification practices.

opencc-by-4.0Dec 2021View details →

Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest

Dataset was used for the article "Can Artificial Intelligence help in the study of vegetative growth dynamics from herbarium collections? An evaluation of the tropical flora of the French Guiana forest". The related work proposes to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Abstract of the paper: A better knowledge of tree vegetative growth patterns and their relationship to environmental variables is crucial in understanding forest growth dynamics and how climate change may affect them. Generally less studied than reproductive structures, the phenology of tree vegetative growth mainly focuses on the analysis of growing shoots, from vegetative buds development to leaf fall. This growth process usually strongly differs between temperate and tropical regions. In temperate regions, this pattern is quite well known. Low winter temperatures impose a stop of the vegetative growth shoots and lead to the typical expression of an annual growth cycle for the vast majority of tree species. In moist tropical regions, on the other hand, the seasonality is much less marked. In addition, these regions contain a much wider variety of tree species. These two aspects lead to a tremendous diversity of phenological patterns that are still poorly known and understood. In particular, not much is known on the periodicity and timing of growth at individual trees, population, or community levels. The work carried out in this study aims to advance knowledge in this area, focusing more particularly on herbarium scans, as herbarium collections offer the promise of monitoring plant phenology over long time periods. However, such a study requires the ability to detect a sufficiently large number of growing shoots in herbarium collections to draw statistically relevant conclusions, which can be very costly if the work is done manually. Furthermore, herbarium collections traditionally focus on reproductive organs, and herbarium specimens showing growing shoots are pretty rare. We propose in this paper to study to what extent the use of automated visual analysis techniques, based on deep learning, can help not only to detect these relatively rare vegetative structures in herbarium collections but also to automatically classify them by type of growing shoot (continuous or rhythmic). Our results show the relevance of using herbarium data for vegetative phenology research, as well as the potential of deep learning approaches for growth shoot detection.

opencc-by-4.0Jan 2022View details →

Influence of the tropical Indian Ocean tripole on summertime cold extremes over central Siberia

These experiments are used to study atmospheric circulation responses to SST forcing related to Indian Ocean tripole mode, including the precipitation, zonal and meridional winds.

opencc-by-4.0Feb 2022View details →

PEATCLSM_Trop: Integrating peat-specific land surface hydrology of natural and drained tropical peatlands in the GEOS CLSM framework

The datasets archived here include simulation results shown in the peer-reviewed article “Tropical peatland hydrology simulated with a global land surface model“, published in the open access AGU Journal of Advances in Modeling Earth Systems (JAMES; Apers et al., 2022). The output was produced using the Catchment land surface model (CLSM), the land model component of the NASA Goddard Earth Observing System (GEOS) modeling framework, and various versions of peatland-specific adaptations of CLSM, i.e. PEATCLSM. Here, we provide netCDF files (*.nc or *.nc4c) for CLSM, the natural (PEATCLSMTrop,Nat), and drained (PEATCLSMTrop,Drain) tropical versions of PEATCLSM. The simulations are at a 9-km spatial resolution (EASEv2 grid) for the three major tropical peatland regions in Central and South America, the Congo Basin, and Southeast Asia, using a peat grid cell distribution that is a combination of the PEATMAP distribution from Xu et al. (2018) and the peat distribution from De Lannoy et al. (2014). Simulations with the northern version of PEATCLSM (PEATCLSMNorth,Nat) are not included in the archived dataset but can be obtained upon request. We provide three types of netCDF files: •    daily_images_*.nc4c: daily land states and fluxes for variables discussed in Apers et al., (2022; Table 1), provided as netCDF image-chunked image stack; •    daily_mean_*.nc: 20-year mean of the land states and fluxes (Table 1), provided as a single netCDF image; •    daily_std_*.nc: 20-year standard deviation of the land states and fluxes (Table 1), provided as a single netCDF image. The file content is described in the file PEATCLSM_Trop-Simulations.pdf. Please contact Sebastian Apers (sebastian.apers@kuleuven.be) or Michel Bechtold (michel.bechtold@kuleuven.be) for any questions. References: Apers, S., De Lannoy, G. J. M., Baird, A. J., Cobb, A. R., Dargie, G. C., del Aguila Pasquel, J., … others (2022). Tropical peatland hydrology simulated with a global land surface model. Journal of Advances in Modeling Earth Systems. https://doi.org/10.1029/2021MS002784 Bechtold, M., De Lannoy, G. J. M., Koster, R. D., Reichle, R. H., Mahanama, S. P., Bleuten, W., ... others (2019). PEAT-CLSM: A specific treatment of peatland hydrology in the NASA Catchment Land Surface Model. Journal of Advances in Modeling Earth Systems, 11(7), 2130–2162. https://doi.org/10.1029/2018MS001574 De Lannoy, G. J. M., Koster, R. D., Reichle, R. H., Mahanama, S. P. P., & Liu, Q. (2014). An updated treatment of soil texture and associated hydraulic properties in a global land modeling system. Journal of Advances in Modeling Earth Systems, 6(4), 957– 979. https://doi.org/10.1002/2014MS000330 Xu, J., Morris, P. J., Liu, J., & Holden, J. (2018). PEATMAP: Refining estimates of global peatland distribution based on a meta-analysis. Catena, 160, 134–140. https://doi.org/10.1016/j.catena.2017.09.010

opencc-by-4.0Feb 2022View details →

Uncovering major types of deforestation frontiers across the world's tropical dry woodlands

These datasets provide maps of deforestation frontier classsification into three themed typologies (severity, spatio temporal patterns and development stage) and archetypes of major frontier patterns. We do this for tropical dry woodland worldwide, for the period of 2000 to 2020, at ~3-km spatial resolution (Coordinate System: WGS_1984_Mollweide, float format). Datasets used for this analysis are publicly available, forest cover and loss data are available at: https://data.globalforestwatch.org/. Deforestation frontiers metrics were calculated and typologies developed in RStudio 1.3.1056. We share the code used to develop frontier metrics, frontier typologies, and archetypes, together with a sample dataset summarized from the originally publicly available dataset. Further details of the datasets can be found in Buchadas et. al. (2022): https://doi.org/10.1038/s41893-022-00886-9   For further questions or issues with the datasets, please contact Ana Buchadas at ana.buchadas@geo.hu-berlin.de.

opencc-by-4.0Mar 2022View details →

Data from: Lianas decelerate tropical forest thinning during succession

The well-established pattern of forest thinning during succession predicts an increase in mean tree biomass with decreasing tree density. The forest thinning pattern is commonly assumed to be driven solely by tree-tree competition. The presence of non-tree competitors could alter thinning trajectories, thus altering the rate of forest succession and carbon uptake. We used a large-scale liana removal experiment over 7 years in a 60-to-70-year-old Panamanian forest to test the hypothesis that lianas reduce the rate of forest thinning during succession. We found that lianas slowed forest thinning by reducing tree growth, not by altering tree recruitment or mortality. Without lianas, trees grew and presumably competed more, ultimately reducing tree density while increasing mean tree biomass. Our findings challenge the assumption that forest thinning is driven solely by tree-tree interactions; instead, they demonstrate that competition from other growth forms, such as lianas, slow forest thinning and ultimately delay forest succession.