ABSTRACT:

This is a watershed delineation for the Rio Mameyes watershed in northeastern Puerto Rico.

ABSTRACT:

This file has been modified from Bawiec, 1999 to include "HA Volcanoclastic" - Hydroydrothermally altered “HA Volcanoclatic” or feldspar from Seiders, 1971 by georectification.

Bawiec, W.J., ed., 1999, Geology, geochemistry, geophysics, mineral occurrences and mineral resource assessment for the Commonwealth of Puerto Rico: U.S. Geological Survey Open-File Report 98-038, available online only.

Seiders, V.M., 1971a, Geologic map of the El Yunque quadrangle, Puerto Rico: U.S. Geological Survey Miscellaneous Investigations Map I-658.

This product was created by Miguel Leon, Data Manager (leonmi@sas.upenn.edu) for the Luquillo CZO. NSF EAR Grant 0722476.

ABSTRACT:

Clark, K.E., Shanley, J.B., Scholl, M.A., Perdrial, N., Perdrial, J.N., Plante, A.F., McDowell W.H. (Water Resource Research) Tropical river suspended sediment and solute dynamics in storms during an extreme drought.

5 minute resolution - Turbidity, Specific Conductance, Discharge, and Rainfall- derived data including fraction new water, pre-event discharge, quickflow.

ABSTRACT:

Clark, K.E., Shanley, J.B., Scholl, M.A., Perdrial, N., Perdrial, J.N., Plante, A.F., McDowell W.H. (Water Resource Research) Tropical river suspended sediment and solute dynamics in storms during an extreme drought.

Rio Mameyes and Icacos discharge, suspended sediment, particulate organic carbon (POC), particulate nitrogen (PN), stable isotopes of particulate C and N, C/N, particulate mineralogy, dissolved organic carbon (DOC), anions and cations from 8-24-2015 to 9-2-2015.

Weekly water isotope sampling for Rio Mameyes with mean discharge and z-scores (see paper for full description) 2007 to 2015, storm water isotope sampling for Rio Mameyes with mean discharge and z-scores (see paper for full description) 8-24-2015 to 8-29-2015.

ABSTRACT:

This is an ipython notebook script which uses the ODM2API and SQLAlchemy to load time series data from a file. This can also be viewed from github through nbviewer https://nbviewer.jupyter.org/github/miguelcleon/ODM2API-ipython-notebooks/blob/master/Using%20ODM2API%20and%20SQLAlchemy%20to%20load%20time%20series%20data%20from%20a%20file.ipynb

ABSTRACT:

This script demonstrates how to use ODM2API, ipython widgets, and matplotlib to display time series data in an ipython notebook.
This can also be viewed from github through nbviewer https://nbviewer.jupyter.org/github/miguelcleon/ODM2API-ipython-notebooks/blob/master/Using%20ODM2API%2C%20ipython%20widgets%2C%20and%20matplotlib%20to%20display%20time%20series%20data%20in%20an%20ipython%20notebook.ipynb

ABSTRACT:

This is an introductory example of how to create a connection to an ODM2 database create, retrieve and delete a variable from the variables table.
This can also be viewed from github through nbviewer https://nbviewer.jupyter.org/github/miguelcleon/ODM2API-ipython-notebooks/blob/master/Connect%20to%20an%20ODM2%20database%20and%20create%20a%20variable.ipynb

ABSTRACT:

This Jupyter Notebook allows a user to generate annotations and relate them to time series result values. ipython widgets are used to select time series, start and end dates. Bokeh is used to display result values and allows a user to select values to make an annotation for them. You can also view the notebook here: https://nbviewer.jupyter.org/github/miguelcleon/ODM2API-ipython-notebooks/blob/master/load%20result%20values%20using%20ODM2API%20-%20select%20values%20with%20bokeh%20and%20add%20annotations.ipynb

ABSTRACT:

These data and collection and analysis methods are described in Hall et al. 2015, Biogeosciences
doi:10.5194/bg-12-2471-2015
Biogeosciences, 12, 2471–2487, 2015
www.biogeosciences.net/12/2471/2015/

ABSTRACT:

Data from https://www.digitalglobe.com/opendata/hurricane-maria/pre-event

2017-05-12 -> 103001006AB78C00

ABSTRACT:

Data from https://www.digitalglobe.com/opendata/hurricane-maria/post-event

2017-09-24 -> 1030010072069C00

ABSTRACT:

ODM2 Admin Result Series Barometric pressure - Atmospheric pressure - 1698- QS-Quebrada_Sonadora - 3- Stream gage - Quebrada Sonadora - Observation | Hobo U20 Water Level , Observation | Observation by HOBO U20 W - ID: 16154 , 15.0, Minutes- Minutes data values from: 2017-09-18 ending on: 2017-09-28

ABSTRACT:

This file includes orginal data that support the manuscript, titled 'Phosphorus fractionation responds to dynamic redox conditions in a humid tropical forest soil'
Authored by Yang Lin, Amrita Bhattacharyya, Ashley N. Campbell, Peter S. Nico, Jennifer Pett-Ridge, and Whendee L. Silver
Please contact yanglin@berkeley.edu or pettridge2@llnl.gov.
This project was supported by a US Department of Energy Early Career Award to J. Pett-Ridge (SCW1478) administered by the Office of Biological and Environmental Research, Genomic Sciences Program. Work at LLNL was performed under the auspices of the U.S. Department of Energy under Contract DE-AC52-07NA27344. Work at UC Berkeley was supported by DEB-1457805 (WLS), Luquillo CZO (EAR-1331841), and LTER (DEB-0620910). WLS was also supported by the USDA National Institute of Food and Agriculture, McIntire Stennis project CA-B-ECO-7673-MS.

ABSTRACT:

NOAA's National Geophysical Data Center (NGDC) is building high-resolution digital elevation models (DEMs) for select U.S. coastal regions. These integrated bathymetric-topographic DEMs are used to support tsunami forecasting and warning efforts at the NOAA Center for Tsunami Research, Pacific Marine Environmental Laboratory (PMEL). The DEMs are part of the tsunami forecast system SIFT (Short-term Inundation Forecasting for Tsunamis) currently being developed by PMEL for the NOAA Tsunami Warning Centers, and are used in the MOST (Method of Splitting Tsunami) model developed by PMEL to simulate tsunami generation, propagation, and inundation. Bathymetric, topographic, and shoreline data used in DEM compilation are obtained from various sources, including NGDC, the U.S. National Ocean Service (NOS), the U.S. Geological Survey (USGS), the U.S. Army Corps of Engineers (USACE), the Federal Emergency Management Agency (FEMA), and other federal, state, and local government agencies, academic institutions, and private companies. DEMs are referenced to the vertical tidal datum of Mean High Water (MHW) and horizontal datum of World Geodetic System 1984 (WGS84). Grid spacings for the DEMs range from 1/3 arc-second (~10 meters) to 3 arc-seconds (~90 meters).
Dataset Identifier: gov.noaa.ngdc.mgg.dem:tigp_puerto_rico_3s

See 'puerto_rico_3s_metadata.htm' file for additional source information.

ABSTRACT:

Data are from https://www.digitalglobe.com/opendata/hurricane-maria/post-event

ABSTRACT:

Luquillo Critical Zone Observatory sensor database 153 time series from 40 sensors at 9 sites with 5 million + time series values.

Sites with data are:
EP1 - Observation well - East Peak 1
Bisley-Q3 - Stream gage - Bisley Quebrada 3
Icacos-Pulse-RI -Stream gage - Icacos Pulse Installation
Prieta - Stream gage - Prieta
QS-Quebrada_Sonadora - Stream gage - Quebrada Sonadora
RESSH - Stream gage - Rio Espiritu Santo Stream House
RESL - Stream gage - Rio Espritu Santo Launch
Rio_Icacos_Trib-IO - Stream gage - Rio Icacos Tributary
El-Verde-Weather - Weather station - El Verde Field Station NDAP

Many of the data values contained in this database are raw values taken directly from instruments, use with caution.

ABSTRACT:

A JupyterNotebook describing Luquillo CZO and USGS discharge data from Hurricanes Irma and Maria

ABSTRACT:

This JupyterNotebook discribes how to connect to The Luquillo CZO Sensor database hosted on Hydroshare.

ABSTRACT:

This JupyterNotebook provides an interactive means for viewing data from the Luquillo CZO Sensor database hosted on Hydroshare.

ABSTRACT:

This Jupyter Notebook demonstrates how to interact with Luquillo CZO water one flow web services.

ABSTRACT:

Game camera still photos and videos from the Luquillo CZO, at the stream sites Quebrada Sonadora and Rio Icacos

Composite video of Sonadora Upstream 9-19-17 to 9-25-17 Hurricane Maria
https://www.youtube.com/watch?v=gEOM-gP-wGk

ABSTRACT:

Presentation on Environmental data topics for Hurricane Maria by Miguel Leon.

A recording of this meeting is available at: https://youtu.be/JBzFWNfJufU
The power point used for the meeting is here https://www.hydroshare.org/resource/5b423fd666174214962afe905873f308/

meeting chat log:

From Chris Lenhardt to Everyone: 03:13 PM
Where is the jupyter notebook running?
From Martin Seul to Everyone: 03:17 PM
jupyterhub.cuahsi.org runs on Hydroshare hardware at RENCI
From Chris Lenhardt to Everyone: 03:18 PM
thx
From Martin Seul to Everyone: 03:27 PM
I will need to sign off, have to join another call.
From jphuong to Everyone: 03:28 PM
Fyi: http://bioportal.bioontology.org/annotator
From peckhams to Everyone: 03:52 PM
The video I mentioned was actually on the Luquillo LTER (vs. CZO) website. I think the website also changed recently, but the video is called “Water from the Mountain” and is on the Luq. LTER FaceBook page.
Also see the shorter video “Shrimp Inc.”
From cband to Everyone: 03:58 PM
Can you paste that link in here Scott?
From peckhams to Everyone: 04:01 PM
https://www.facebook.com/luquillo.lter/posts/1755183038123544
https://vimeo.com/247903869
From jphuong to Everyone: 04:02 PM
Algal bloom time-lapsehttps://www.hydroshare.org/resource/4c8ecb05a72647339df0df6e9a87718f/
https://www.hydroshare.org/resource/4c8ecb05a72647339df0df6e9a87718f/
From peckhams to Everyone: 04:07 PM
https://vimeo.com/247903869
https://vimeo.com/162427775
https://www.youtube.com/watch?v=7cDjPrkMU4E
From Me to Everyone: 05:06 PM

ABSTRACT:

A collection of notebooks for interacting with Luquillo CZO generated environmental sensor data. Data are aggregated into a SQLite ODM2 database also hosted on Hydroshare here https://www.hydroshare.org/resource/e049f19dc8ba46c98754711da2ab6030/

These notebooks demonstrate how to connect to the Hydroshare hosted database, display data stored in the database and how to compare data to data from other datasources.

ABSTRACT:

This resource links to the Hurricane Maria Story Map https://arcg.is/00f1ij This story map provides access to a number of Hurricane Maria datasets not hosted on hydroshare.org. Maps with FEMA damage, USGS landslide, forest disturbance, power outages, and health data are browsable here. Additional photos from the event and links to other resources are also presented. Other resources include datasets from NASA, NOAA, FEMA, USGS, as well as other organizations.

ABSTRACT:

Data are from https://www.digitalglobe.com/opendata/hurricane-maria/pre-event

ABSTRACT:

Presented here are remotely sensed images of Puerto Rico before and after Hurricane Maria, collected by Digital Globe, these also available here https://www.digitalglobe.com/opendata/hurricane-maria/pre-event

Additional Hurricane Maria remotely sensed images are available via these resources:
NOAA Post Event Imagery are available here: http://disasterresponse.maps.arcgis.com/apps/webappviewer/index.html?id=067398b89217462096fe51cc3a5f3beb

A composite USGS Landsat 8 data from before and after Hurricane Maria https://www.usgs.gov/media/images/puerto-rico-after-hurricane-maria
Landsat 8 data products (and data from other Landsat satellites) are also available via the Google Earth Engine data catalog https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C01_T2_SR

Imagery from Digital Globe are available both pre and post hurricane https://www.digitalglobe.com/ecosystem/open-data This includes data from the QuickBird, WorldView-1/-2/-3, and GeoEye-1 constellation of satellites

NASA power outage maps are available here: https://arcg.is/1ru4qT

ABSTRACT:

Soil organic matter (SOM) often increases with the abundance of short-range-ordered iron (SRO Fe) mineral phases at local to global scales, implying a protective role for SRO Fe. However, less is known about how Fe phase composition and crystal order relate to SOM composition and turnover, which could be linked to redox alteration of Fe phases. We tested the hypothesis that the composition and turnover of mineral-associated SOM co-varied with Fe phase crystallinity and abundance across a well-characterized catena in the Luquillo Experimental Forest, Puerto Rico, using dense fractions from 30 A and B horizon soil samples. The d13C and d15N values of dense fractions were strongly and positively correlated (R2 = 0.75), indicating microbial transformation of plant residues with lower d13C and d15N values. However, comparisons of dense fraction isotope ratios with roots and particulate matter suggested a greater contribution of plant versus microbial biomass to dense fraction SOM in valleys than ridges. Similarly, diffuse reflectance infrared Fourier transform spectroscopy indicated that SOM functional groups varied significantly along the catena. These trends in dense fraction SOM composition, as well as D14C values indicative of turnover rates, were significantly related to Fe phase crystallinity and abundance quantified with selective extractions. Mo¨ssbauer spectroscopy conducted on independent bulk soil samples indicated that nanoscale ordered Fe oxyhydroxide phases (nanogoethite, ferrihydrite, and/or very-SRO Fe with high substitutions) dominated (66–94%) total Fe at all positions and depths, with minor additional contributions from hematite, silicate and adsorbed FeII, and ilmenite. An additional phase that could represent organic-FeIII complexes or aluminosilicate-bearing FeIII was most abundant in valley soils (17–26% of total Fe). Overall, dense fraction samples with increasingly disordered Fe phases were significantly associated with increasingly plant-derived and fastercycling SOM, while samples with relatively morecrystalline Fe phases tended towards slower-cycling SOM with a greater microbial component. Our data suggest that counter to prevailing thought, increased SRO Fe phase abundance in dynamic redox environments could facilitate transient accumulation of litter derivatives while not necessarily promoting long-term C stabilization.

publication can be found here https://doi.org/10.1007/s10533-018-0476-4

ABSTRACT:

Phosphorus (P) is a key limiting nutrient in highly weathered soils of humid tropical forests. A large proportion of P in these soils is bound to redox‐sensitive iron (Fe) minerals; however, little is known about how Fe redox interactions affect soil P cycling. In an incubation experiment, we changed bulk soil redox regimes by varying headspace conditions (air vs. N2 gas), and examined the responses of soil P and Fe species to two fluctuating treatments (4‐ or 8‐day oxic followed by 4‐day anoxic) and two static redox treatments (oxic and anoxic). A static anoxic headspace increased NaOH‐extractable inorganic P (NaOH‐Pi) and ammonium oxalate‐extractable total P (AO‐Pt) by 10% and 38%, respectively, relative to a static oxic headspace. Persistent anoxia also increased NaHCO3‐extractable total P (NaHCO3‐Pt) towards the end of the experiment. Effects of redox fluctuation were more complex and dependent on temporal scales. Ammonium oxalate‐extractable Fe and Pt concentrations responded to redox fluctuation early in the experiment, but not thereafter, suggesting a depletion of reductants over time. Immediately following a switch from an oxic to anoxic headspace, concentrations of AO‐Pt, AO‐Fe, and HCl‐extractable Fe (II) increased (within 30 min), but fell back to initial levels by 180 min. Surprisingly, the labile P pool (NaHCO3‐Pt) decreased immediately after reduction events, potentially due to resorption and microbial uptake. Overall, our data demonstrate that P fractions can respond rapidly to changes in soil redox conditions, and in environments where redox oscillation is common, roots and microbes may benefit from these rapid P dynamics.

The full paper is available here https://doi.org/10.1029/2018JG004420

ABSTRACT:

R scripts presented as Jupyter Notebooks and data to generate load and concentration estimates produced for the journal publication:
McDowell, W. H., McDowell, W. G., Potter, J. D. and Ramírez, A. (2018), Nutrient export and elemental stoichiometry in an urban tropical river. Ecol Appl. Accepted Author Manuscript. doi:10.1002/eap.1839

Find the publication here: https://doi.org/10.1002/eap.1839

We recommend running the JupyterNotebooks on a local JupyterHub instead of the online CUAHSI JupterHub. You will need to run install.R in order to load the needed R packages for the R script.

A prerender version of the Quebrada Sonadora Jupyter Notebook is available here https://nbviewer.jupyter.org/github/miguelcleon/River-nutrient-exports-Puerto-Rico-/blob/master/Sonadora%20%28QS%29%20flux%20and%20concentrations%202009-2014.ipynb

An interactive version of the Jupyter Notebooks maybe available on mybinder, mybinder is in beta and has been functioning inconsistently https://beta.mybinder.org/v2/gh/miguelcleon/River-nutrient-exports-Puerto-Rico-/master

The script 'Sonadora (QS) flux and concentrations 2009-2014.ipynb' in the contents below contains nicely formatted tables that match the tables in the publication. We suggest running this script first if you are interested in how the results were generated. The other two scripts 'Mameyes- Puente Roto (MPR) flux and concentrations 2009-2014.ipynb' and 'Rio Piedras flux and concentrations 2009-2014.ipynb' are raw scripts without formatted output.

The journal publication abstract is presented here:

Nutrient inputs to surface waters are particularly varied in urban areas, due to multiple nutrient sources and complex hydrologic pathways. Because of their close proximity to coastal waters, nutrient delivery from many urban areas can have profound impacts on coastal ecology. Relatively little is known about the temporal and spatial variability in stoichiometry of inorganic nutrients such as dissolved silica, nitrogen, and phosphorus (Si, N, and P) and dissolved organic matter in tropical urban environments. We examined nutrient stoichiometry of both inorganic nutrients and organic matter in an urban watershed in Puerto Rico served by municipal sanitary sewers and compared it to two nearby forested catchments using samples collected weekly from each river for 6 years. Urbanization caused large increases in the concentration and flux of nitrogen and phosphorus (2- to 50-fold), but surprisingly little change in N:P ratio. Concentrations of almost all major ions and dissolved silica were also significantly higher in the urban river than the wildland rivers. Yield of dissolved organic carbon (DOC) was not increased dramatically by urbanization, but the composition of dissolved organic matter shifted toward N-rich material, with a larger increase in dissolved organic nitrogen (DON) than DOC. The molar ratio of DOC:DON was about 40 in rivers draining forested catchments but was only 10 in the urban river. Inclusion of Si in the assessment of urbanization’s impacts reveals a large shift in the stoichiometry (Si:N and Si:P) of nutrient inputs. Because both Si concentrations and watershed exports are high in streams and rivers from many humid tropical catchments with siliceous bedrock, even the large increases in N and P exported from urban catchments result in delivery of Si, N, and P to coastal waters in stoichiometric ratios that are well in excess of the Si requirements of marine diatoms. Our data suggest that dissolved Si, often neglected in watershed biogeochemistry, should be included in studies of urban as well as less developed watersheds due to its potential significance for marine and lacustrine productivity.

ABSTRACT:

Luquillo LTER/CZO Schoolyard Data Jam

The Luquillo LTER/CZO Data Jam invites high and middle school students to find interesting ways to present scientific data to non-scientist audiences.

Students use ecological data collected at the El Yunque National Forest by the Luquillo Critical Zone Observatory, Luquillo LTER and USGS Water to create a project that presents the data in a non-traditional way. An important component of the activity is encouraging students to get creative. Project examples include children’s books, raps, videos, models, presentations, and infographics. Students will present their project at the Luquillo LTER Schoolyard Symposium hosted by the University of Puerto Rico in May, 2019.

ABSTRACT:

Additional Hurricane Maria remotely sensed images are available via referenced resources in the content below and at the links here:
NOAA Post Event Imagery are available here: http://disasterresponse.maps.arcgis.com/apps/webappviewer/index.html?id=067398b89217462096fe51cc3a5f3beb

A composite USGS Landsat 8 data from before and after Hurricane Maria https://www.usgs.gov/media/images/puerto-rico-after-hurricane-maria
Landsat 8 data products (and data from other Landsat satellites) are also available via the Google Earth Engine data catalog https://developers.google.com/earth-engine/datasets/catalog/LANDSAT_LC08_C01_T2_SR

Imagery from Digital Globe are available both pre and post hurricane https://www.digitalglobe.com/ecosystem/open-data This includes data from the QuickBird, WorldView-1/-2/-3, and GeoEye-1 constellation of satellites

NASA power outage maps are available here: https://arcg.is/1ru4qT

ABSTRACT:

Concentration-discharge relationships are a key tool for understanding the sourcing and transport of material from watersheds to fluvial networks. Storm events in particular provide insight into variability in the sources of solutes and sediment within watersheds, and the hydrologic pathways that connect hillslope to stream channel. Here we examine high-frequency sensor-based specific conductance and turbidity data from multiple storm events across two watersheds (Quebrada Sonadora and Rio Icacos) with different lithology in the Luquillo Mountains of Puerto Rico, a forested tropical ecosystem. Our analyses include Hurricane Maria, a category 5 hurricane. To analyze hysteresis, we used a recently developed set of metrics to describe and quantify storm events including the hysteresis index (HI), which describes the directionality of hysteresis loops, and the flushing index (FI), which describes whether the mobilization of material is source or transport limited. We also examine the role of antecedent discharge to predict hysteretic behavior during storms. Overall, specific conductance and turbidity showed contrasting responses to storms. The hysteretic behavior of specific conductance was very similar across sites, displaying clockwise hysteresis and a negative flushing index indicating proximal sources of solutes and consistent source limitation. In contrast, the directionality of turbidity hysteresis was significantly different between watersheds, although both had strong flushing behavior indicative of transport limitation. Overall, models that included antecedent discharge did not perform any better than models with peak discharge alone, suggesting that the magnitude and trajectory of an individual event was the strongest driver of material flux and hysteretic behavior. Hurricane Maria produced unique hysteresis metrics within both watersheds, indicating a distinctive response to this major hydrological event. The similarity in response of specific conductance to storms suggests that solute sources and pathways are similar in the two watersheds. The divergence in behavior for turbidity suggests that sources and pathways of particulate matter vary between the two watersheds. The use of high-frequency sensor data allows the quantification of storm events while index-based metrics of hysteresis allow for the direct comparison of complex storm events across a heterogeneous landscape and variable flow conditions.

Additional scripts for hysteresis analysis are available here in the 'python scripts for analysis' folder and at https://github.com/miguelcleon/HysteresisAnalysis/

ABSTRACT:

This resource links to the Hurricane Maria Story Map https://arcg.is/00f1ij This story map provides access to a number of Hurricane Maria datasets not hosted on hydroshare.org. Maps with FEMA damage, USGS landslide, forest disturbance, power outages, and health data are browsable here. Additional photos from the event and links to other resources are also presented. Other resources include datasets from NASA, NOAA, FEMA, USGS, as well as other organizations.

ABSTRACT:

Lithologic differences give rise to the differential weatherability of the Earth’s surface and globally variable silicate weathering fluxes, which provide an important negative feedback on climate over geologic timescales. To isolate the influence of lithology on weathering rates and mechanisms, we compare two nearby catchments in the Luquillo Critical Zone Observatory in Puerto Rico, which have similar climate history, relief and vegetation, but differ in bedrock lithology. Regolith and pore water samples with depth were collected from two ridgetops and at three sites along a slope transect in the volcaniclastic Bisley catchment and compared to existing data from the granitic Río Icacos catchment. The depth variations of solid-state and pore water chemistry and quantitative mineralogy were used to calculate mass transfer (tau) and weathering solute profiles, which in turn were used to determine weathering mechanisms and to estimate weathering rates.

Regolith formed on both lithologies is highly leached of most labile elements, although Mg and K are less depleted in the granitic than in the volcaniclastic profiles, reflecting residual biotite in the granitic regolith not present in the volcaniclastics. Profiles of both lithologies that terminate at bedrock corestones are less weathered at depth, near the rock-regolith interfaces. Mg fluxes in the volcaniclastics derive primarily from dissolution of chlorite near the rock-regolith interface and from dissolution of illite and secondary phases in the upper regolith, whereas in the granitic profile, Mg and K fluxes derive from biotite dissolution. Long-term mineral dissolution rates and weathering fluxes were determined by integrating mass losses over the thickness of solid-state weathering fronts, and are therefore averages over the timescale of regolith development. Resulting long-term dissolution rates for minerals in the volcaniclastic regolith include chlorite: 8.9 × 10−14 mol m−2 s−1, illite: 2.1 × 10−14 mol m−2 s−1 and kaolinite: 4.0 × 10−14 mol m−2 s−1. Long-term weathering fluxes are several orders of magnitude lower in the granitic regolith than in the volcaniclastic, despite higher abundances of several elements in the granitic regolith. Contemporary weathering fluxes were determined from net (rain-corrected) solute profiles and thus represent rates over the residence time of water in the regolith. Contemporary weathering fluxes within the granitic regolith are similar to the long-term fluxes. In contrast, the long-term fluxes are faster than the contemporary fluxes in the volcaniclastic regolith. Contemporary fluxes in the granitic regolith are generally also slightly faster than in the volcaniclastic. The differences in weathering fluxes over space and time between these two watersheds indicate significant lithologic control of chemical weathering mechanisms and rates.

ABSTRACT:

The thick regolith developed in the humid tropics represents an endmember of critical zone evolution, where shallow and deep biogeochemical cycles can be decoupled in terms of the predominant source of trace elements (atmospheric input at the surface, weathering at depth) and of the processes that control their cycling. To investigate the influence of lithology on trace element behavior and in this potential decoupling, we studied two deep (9.3 and 7.5 m), highly-leached, ridgetop regolith profiles at the Luquillo Critical Zone Observatory, Puerto Rico. These profiles have comparable internal (degree of weathering, topography) and external (vegetation, climate) characteristics, but differ in their underlying bedrock (andesitic volcaniclastic and granitic). At these two sites, we analyzed a large suite of trace elements and used the rare earth elements and yttrium (REY) as tracers of critical zone processes because they are fractionated by the chemical reactions involved in weathering and pedogenesis (e.g., sorption, dissolution, colloidal transport) and by redox fluctuations.

We found that both regolith profiles show atmospheric inputs of trace elements at the surface and evidence of bedrock dissolution at depth, as expected. We also found noticeable differences in the re-distribution of trace elements and REY within the profiles, indicative of different geochemical environments with depth and lithology. In the volcaniclastic profile, trace element and REY behavior is controlled mainly by redox-mediated, sorption/desorption reactions, whereas pH-controlled dissolution/precipitation and sorption reactions predominate in the granitic profile. The most noticeable difference between the two regolith profiles is in the long-term redox conditions, inferred from redox-sensitive elements and Ce anomaly variations, which are more variable and stratified in the volcaniclastic profile and change gradually with depth in the granitic profile. The contrasting redox conditions and the different sources of elements (dust vs. bedrock) produce a decoupling between the surface and deep geochemical environments of the volcaniclastic regolith. The difference in redox conditions between the two lithologies likely stems from the finer grain size and higher clay content of the volcaniclastic regolith.

ABSTRACT:

Ferrous iron (FeII) oxidation is an important pathway for generating reactive FeIII phases in soils, which can affect organic carbon (OC) persistence/decomposition. We explored how pO2 concentration influences FeII oxidation rates and FeIII mineral composition, and how this impacts the subsequent FeIII reduction and anaerobic OC mineralization following a transition from oxic to anoxic conditions. We conducted batch soil slurry experiments within a humid tropical forest soil amended with isotopically labeled 57FeII. The slurries were oxidized with either 21% or 1% pO2 for 9 days and then incubated for 20 days under anoxic conditions. Exposure to 21% pO2 led to faster FeII oxidation rates and greater partitioning of the amended 57Fe into low-crystallinity FeIII-(oxyhydr)oxides (based on Mössbauer analysis) than exposure to 1% pO2. During the subsequent anoxic period, low-crystallinity FeIII-(oxyhydr)oxides were preferentially reduced relative to more crystalline forms with higher net rates of anoxic FeII and CO2 production—which were well correlated—following exposure to 21% pO2 than to 1% pO2. This study illustrates that in redox-dynamic systems, the magnitude of O2 fluctuations can influence the coupled iron and organic carbon cycling in soils and more broadly, that reaction rates during periods of anoxia depend on the characteristics of prior oxidation events.

R-code for Spectral Subtraction for 57Fe-spiked samples developed for:

Chen, Chunmei, Christof Meile, Jared Wilmoth, Diego Barcellos, and Aaron Thompson (2018): Influence of pO2 on iron redox cycling and anaerobic organic carbon mineralization in a humid tropical forest soil. Environmental Science & Technology 52 (14): 7709-7719. DOI: 10.1021/acs.est.8b01368

ABSTRACT:

In order to assess the effects of critical zone processes on Mg concentrations and isotopic signatures of tropical streams, we studied a well constrained, highly weathered andesitic volcaniclastic catchment in the Luquillo Critical Zone Observatory, Puerto Rico. Our results indicate that dissolved Mg concentrations and isotope ratios in the regolith pore water are mainly controlled by rain input, with weathering inputs being more important at sites with thinner regolith (2.7–0.9 m deep) and at depth (>8 m) on a thick ridgetop regolith (∼10 m). In addition to mixing of precipitation and weathering-sourced Mg, an isotopic fractionation process is taking place between dissolved Mg and the regolith, likely during dissolution or recrystallisation of Fe(III)-(hydro)oxides under alternating redox conditions. Bulk regolith is isotopically heavier than both the bedrock and the exchangeable fraction (δ26Mgregolith-bedrock = +0.03 to +0.47‰), consistent with the preferential incorporation of heavy 26Mg into secondary minerals with some exchange of sorbed Mg with isotopically lighter pore water. Magnesium concentrations in the stream show a typical dilution behaviour during a storm event, but the [Mg] – δ26Mg pattern cannot be explained by mixing of rain and pore water; the data are best explained by a steady-state fractionation model with α = 1.00115. During baseflow the stream has δ26Mg = +0.01‰, higher than any of the water samples or the bedrock. In-situ analysis of the Mg isotopic composition of bedrock minerals points at the dissolution of Mg-rich chlorite (δ26Mg = +0.19‰) as the most likely source of this isotopically heavy Mg, with mass balance calculations indicating chlorite dissolution is also the main source of Mg to the stream. Overall, our study highlights the importance of atmospheric input of nutrients to the vegetation in tropical areas covered by thick, highly leached regolith, whereas the Mg flux and Mg isotopic signature of watershed exports are dominated by bedrock dissolution delivered to the stream through deeper, usually un-sampled critical zone pathways.

ABSTRACT:

The Sabana meteorological station is located in the Luqullio Experiment Forest at 18.32°N 65.73°W at an elevation of 100 meters. The station collects and records on the hour: total rainfall, relative humidity, mean sea level pressure, temperature, wind direction, and wind speed. The instrument was installed in 2013.

ABSTRACT:

Geophysical surveys conducted during the summer of 2014 followed on previous work that investigated the nature and spatial variability of ground penetrating radar (GPR) reflections in the Rio Icacos watershed (Figure 1a). GPR surveys using a variety of shielded (160 MHz) and unshielded (50, 100 and 200 MHz) antennas (Figure 1e) was combined with multi-frequency terrain conductivity measurements to upscale previous measurements.
Figure 1a shows a 2 km long transect (red line) across a trail in the Rio Icacos watershed. The transect in the northern edge had an approximately elevation of 640 m, and ended in the southern edge below 540 m elevation and close to the knickpoint. The GPR data along the transect revealed a series of vertical zones with presence of chaotic reflectors (Figure 1b, between 240-265m, 270-300 m, and 320-350 m along the transect; and Figure 1c, between 690-750 m along the transect). These areas repeated at several locations along the 2 km transect (white lines in Figure 1a). Other GPR reflector facies signatures (not shown here) included two landslide locations (yellow lines in Figure 1a); and an area of laterally continuous reflectors (blue line in Figure 1a) towards the end of the transect and close to the knickpoint.
Terrain conductivity surveys consistently depict a) increases in terrain conductivity; and b) decreases in magnetic susceptibility that coincide with the vertical zones of chaotic GPR reflectors described above (shaded areas in Figures 1b and 1c)
We attribute these areas of enhanced GPR reflections to vertical fracturing within the bedrock-regolith interface associated with the formation of corestones. Water infiltration may cause regolith wash off (resulting in a decrease in electrical conductivity) and concentration of corestones (resulting in increases in magnetic susceptibility). This preliminary hypothesis is confirmed by the presence of large corestones adjacent to the transect (Figure 1d) and following topographic valley areas (Figure 1a).
These results confirm the potential of hydrogeophysical measurements for understanding variability of bedrock-regolith interface in the Icacos watershed at large (i.e. km) scales and have direct implications for the controls on subsurface fluid circulation and presence of preferential groundwater flow.

GPR data found here in the second link are raw data, data was processed and interpreted in Orlando et al. 2016 ((DOI: 10.1002/esp.3948):

“GPR data processing was performed using ReflexW by Sandmeier Scientific. Steps were limited to: (a) a ‘dewow’ filter over a 10 ns time-window; (b), application of a time-varying gain; (c) a bandpass filter; (d) a static correction; and in some cases, (e) Kirchhoff migration based on a single EM wave velocity as determined from the CMP profiles.”

ABSTRACT:

Hydrological mapping in the Luquillo Experimental Forest: Opportunities and challenges to improve watershed ecological knowledge

The streams and rivers of the Luquillo Experimental Forest, Puerto Rico, have been the subject of extensive watershed and aquatic and research since the 1980’s. This research includes understanding stream export of nutrients, physicochemical constituents, coarse particulate organic matter export dynamics, and aquatic fauna populations. However, many of these studied streams and watersheds do not show up in standard hydrological maps. We document the recent collaborative work delineating long-term research watersheds and identifying gaps in hydrological network information. We describe the trade-offs and caveats of achieving appropriate stream densification to represent sites of on-going research. The methods used to delimit and densify stream networks include incorporation of updated new vertical datum for Puerto Rico, LIDAR derived elevation, and a combination of visual-manual and automated digitalization processes. The outcomes of this collaborative effort have resulted in improved watershed delineation, densification of hydrologic networks to reflect the scale of on-going studies, and the identification of constraining factors such as unmapped roadways, culverts, and other features of the built environment that interrupt water flow and obstruct runoff identification. This work contributes to enhance knowledge for watershed management, including riparian areas, road and channel intersections, and ridge to reef initiatives with broad application to other watersheds.

This dataset contains watershed delineations, and stream networks for El Verde Research Area and the Bisley Experimental Watershed (BEW)
This data can also be viewed via this story map:
https://arcg.is/1S5qSX

ABSTRACT:

Microcuenca de San Juan Zitácuaro
landcover for San Juan Zitácuaro watershed Mexico

ABSTRACT:

Luquillo Experimental Forest stream water chemistry sampling locations

ABSTRACT:

These are the tables in the main text and supplementary material of the article: ‘Secondary minerals drive extreme lithium isotope fractionation during tropical weathering’, published in the Journal of Geophysical Research - Earth Surface in 2022 (DOI: 10.1029/2021JF006366). The samples were collected at the Luquillo CZO Bisley 1 catchment, most of them from a regolith profile located in a ridgetop (B1S1). They include Li concentrations and Li isotopic composition, Nb, Cs, and Chemical Index of Alteration of bulk regolith and bedrock; Li and Li isotopic composition in porewater and in the exchangeable fraction of the regolith and other ancillary information.

ABSTRACT:

Topography is commonly viewed as a passive backdrop on which vegetation grows. Yet, in certain circumstances, a bidirectional feedback may develop between the control of topography and the spatial distribution of vegetation and landform development, because vegetation modulates the erosion of the land surface. Therefore, if reinforcing feedbacks are established between erosion and land cover distribution over timescales relevant to landform development, then the interactions between vegetation and topography may create distinctive landforms, shaped by vegetation. We expose here a strong correlation between the spatial distribution of vegetation, erosion rates, and topography at a characteristic length scale of 102-103m (mesoscale topography) in the Luquillo Experimental forest (LEF) of Puerto Rico. We use high-resolution LiDAR topography to characterize landforms, satellite images to classify the vegetation into forest types, and in-situ produced cosmogenic 10Be in the quartz extracted from soils and stream sediments to document spatial variations in soil erosion. The data document a strong correlation between forest type and topographic position (hilltop vs. valleys), and a correlation between topographic position and 10Be-derived erosion rates over 103-104 years. Erosion is faster in valleys, which are mostly covered by monocot Palm Forest, and slower on surrounding hills mostly covered by the dicot Palo Colorado Forest. Transition from one forest type to the next occurs across a break-in-slope that separates shallowly convex hilltops from deeply concave valleys (coves). The break-in-slope is the consequence of a longer-lasting erosional imbalance whereby coves erode faster than hills over landscape-shaping timescales. Such a deepening of the coves is usually spurred by external drivers, but such drivers are here absent. This implies that cove erosion is driven by a process originating within the coves themselves. We propose that vegetation is the primary driver of this imbalance, soil erosion being faster under Palm forest than under Palo Colorado forest. Concentration of the Palm forest in the deepening coves is reinforced by the better adaptation of Palm trees to the erosive processes that take place in the coves, once these develop steep slopes. At the current rate of landscape development, we find that the imbalance started within the past 0.1-1.5 My. The initiation of the process could correspond to time of settlement of these mountain slopes by the Palm and Palo Colorado forests.

S2-Shapefile1- Study Area
S2-Shapefile2 - Cove And Ridge Tops On Quartz Diorite
S2-Shapefile3 - Ground Proofing Tracks

S1-Grid1.tif - Elevation
S1-Grid2.tif - Elevation in Study Area
S2-Grid1.tif- Forest Classification; Sierra Palm is classified with #2 on each raster cell, Palo Colorado is classified with #3 in each grid cell.

ABSTRACT:

Topography is commonly viewed as a passive backdrop on which vegetation grows. Yet, in certain circumstances, a bidirectional feedback may develop between the control of topography and the spatial distribution of vegetation and landform development, because vegetation modulates the erosion of the land surface. Therefore, if reinforcing feedbacks are established between erosion and land cover distribution over timescales relevant to landform development, then the interactions between vegetation and topography may create distinctive landforms, shaped by vegetation. We expose here a strong correlation between the spatial distribution of vegetation, erosion rates, and topography at a characteristic length scale of 102-103m (mesoscale topography) in the Luquillo Experimental forest (LEF) of Puerto Rico. We use high-resolution LiDAR topography to characterize landforms, satellite images to classify the vegetation into forest types, and in-situ produced cosmogenic 10Be in the quartz extracted from soils and stream sediments to document spatial variations in soil erosion. The data document a strong correlation between forest type and topographic position (hilltop vs. valleys), and a correlation between topographic position and 10Be-derived erosion rates over 103-104 years. Erosion is faster in valleys, which are mostly covered by monocot Palm Forest, and slower on surrounding hills mostly covered by the dicot Palo Colorado Forest. Transition from one forest type to the next occurs across a break-in-slope that separates shallowly convex hilltops from deeply concave valleys (coves). The break-in-slope is the consequence of a longer-lasting erosional imbalance whereby coves erode faster than hills over landscape-shaping timescales. Such a deepening of the coves is usually spurred by external drivers, but such drivers are here absent. This implies that cove erosion is driven by a process originating within the coves themselves. We propose that vegetation is the primary driver of this imbalance, soil erosion being faster under Palm forest than under Palo Colorado forest. Concentration of the Palm forest in the deepening coves is reinforced by the better adaptation of Palm trees to the erosive processes that take place in the coves, once these develop steep slopes. At the current rate of landscape development, we find that the imbalance started within the past 0.1-1.5 My. The initiation of the process could correspond to time of settlement of these mountain slopes by the Palm and Palo Colorado forests.

S2-Shapefile1- Study Area
S2-Shapefile2 - Cove And Ridge Tops On Quartz Diorite
S2-Shapefile3 - Ground Proofing Tracks

S1-Grid1.tif - Elevation
S1-Grid2.tif - Elevation in Study Area
S2-Grid1.tif- Forest Classification; Sierra Palm is classified with #2 on each raster cell, Palo Colorado is classified with #3 in each grid cell.

ABSTRACT:

Sensor based environmental monitoring data from across the Luquillo Mountains stored in an SQLite ODM2 database.

data collected using Hobo U20-001-04 Water Level, HOBO Light and Air Temperature Sensor UA-002-64, HOBO U26 DO Probe DO and Water Temperature, and HOBO U24 conductivity loggers collect data at a 15 minute time interval.

Data are available from the following sites:
Bisley-Q3, Icacos-Pulse-RI, QP, QS-Quebrada_Sonadora, RESSH
For more details see the metadata in "LUQDBDatabaseinfo.xlsx"
Also see our website: https://luquillo.lter.network/

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 was provided by the USDA Forest Service International Institute of Tropical Forestry and the University of Puerto Rico.