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Miguel Leon

University of Pennslyvania | Data Manager

Subject Areas: Data Management

 Recent activity

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.

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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 at https://github.com/miguelcleon/HysteresisAnalysis/

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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

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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.

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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.

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 Contact

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Resources
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Geographic Feature (ESRI Shapefiles) Geographic Feature (ESRI Shapefiles)
Rio Mameyes Watershed
Created: Dec. 2, 2016, 5:57 p.m.
Authors: Miguel Leon

ABSTRACT:

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

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Geographic Feature (ESRI Shapefiles) Geographic Feature (ESRI Shapefiles)
Geology of Northeastern Puerto Rico
Created: Dec. 21, 2016, 4:22 p.m.
Authors: Miguel Leon

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.

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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.

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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.

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

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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

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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

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Generic Generic

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

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Generic Generic
Connect to an ODM2 database and create a variable
Created: Jan. 25, 2017, 9:03 p.m.
Authors: Miguel Leon

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

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Generic Generic

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

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Generic Generic
Extreme storms drive riverine particulate organic matter export from tropical mountians of estern Puerto Rico
Created: June 23, 2017, 7:37 p.m.
Authors: Kathryn E Clark · Robert Stallard · Martha Scholl · Alain F. Plante · Sheila F. Murphy · Grizelle Gonzalez · William H. McDowell

ABSTRACT:

Erosion, transport and deposition of riverine suspended load are pivotal processes in the terrestrial carbon cycle and function of the critical zone. In order to better understand the response of these drivers to changes in land cover and climate, it is critical to characterize these drivers. In montane rivers, such as the Luquillo Mountains, Puerto Rico, extreme storm events erode and transport clastic and organic material from mountain slopes to rivers, dominating annual export. Riverine particulate organic carbon (POC) and particulate nitrogen (PN) exports are not as well understood, especially at high runoff rates. Over 25 years, river POC export was 75±20 tC km-2 yr-1 for Rio Icacos and 22±8 tC km-2 yr-1 for the Mameyes. Caribbean river POC yields were higher in relation to their SS yields, suggesting that these rivers have greater terrestrial OM supply on the landscape to be eroded and transported into rivers, than what is expected based on data for world rivers. Additionally, we determined that 50% of the suspended load flux occurred during extreme rainfall events, spanning just over 2 days a year, but only exporting <10% of the annual runoff and rainfall. These results emphasize the important role of extreme rainfall events as drivers of POM export from the Luquillo Mountains.

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Composite Resource Composite Resource
Hall et al. LCZO landscape-scale soil biogeochemistry and enzymes (2012)
Created: March 13, 2018, 6:20 p.m.
Authors: Hall, Steven

ABSTRACT:

Metadata: See Hall and Silver 2015, Biogeochemistry for details on soil analyses and sites; See Hall et al. 2014 Ecology for details on enzyme analyses and phenolic substances
Biogeochemistry (2015) 125:149–165 DOI 10.1007/s10533-015-0120-5
Ecology, 95(10), 2014, pp. 2964–2973 DOI 10.1890/13-2151.1

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Hall et al. LCZO Bisley catena soil biogeochemistry and 14C (2012)
Created: March 13, 2018, 8:43 p.m.
Authors: Hall Steven

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/

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Composite Resource Composite Resource

ABSTRACT:

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

2017-05-12 -> 103001006AB78C00

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Composite Resource Composite Resource

ABSTRACT:

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

2017-09-24 -> 1030010072069C00

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Generic Generic

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

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Phosphorus fractionation responds to dynamic redox conditions in a humid tropical forest soil
Created: April 3, 2018, 3:03 p.m.
Authors: Yang Lin · Amrita Bhattacharyya · Ashley N. Campbell · Peter S. Nico · Jennifer Pett-Ridge · Whendee L. Silver

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.

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Composite Resource Composite Resource

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.

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Composite Resource Composite Resource
Post Maria Digital Globe Images
Created: April 16, 2018, 1:49 p.m.
Authors: Miguel Leon

ABSTRACT:

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

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Composite Resource Composite Resource

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.

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ABSTRACT:

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

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

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ABSTRACT:

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

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Interact with Luquillo CZO water one flow web services
Created: April 20, 2018, 4:37 p.m.
Authors: Miguel Leon

ABSTRACT:

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

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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

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Collection Resource Collection Resource

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.

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Web App Resource Web App Resource
Hurricane Maria 2017 Story Map
Created: May 24, 2018, 5:26 p.m.
Authors: Miguel Leon

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.

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Pre Maria Digital Globe Images
Created: June 20, 2018, 5:03 p.m.
Authors: Miguel Leon

ABSTRACT:

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

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Collection Resource Collection Resource
Hurrican Maria remotely sensed images
Created: June 20, 2018, 6:12 p.m.
Authors: Miguel Leon

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

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Order from disorder: do soil organic matter composition and turnover co-vary with iron phase crystallinity?
Created: Aug. 7, 2018, 7:17 p.m.
Authors: Steven Hall · Asmeret A. Berhe · Aaron Thompson

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

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Phosphorus fractionation responds to dynamic redox conditions in a humid tropical forest soil
Created: Aug. 24, 2018, 1:28 p.m.
Authors: Yang Lin · Amrita Bhattacharyya · Ashley N. Campbell · Peter S. Nico · Jennifer Pett-Ridge · Whendee L. Silver

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

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ABSTRACT:

[description]
Climatological data were collected from a ridgetop climate station East of Niwot Ridge (B1 at 2591 m) throughout the year using a Hobo Pro V2 data logger mounted in a Stevenson screen. Parameters measured were air temperature and relative humidity Site History to view logs for complete site history Missing Data to view complete log of missing data.

[comments]
Data were recorded using a HOBO Onset Pendant starting in 2009, but the site was not maintained or routinely visited until November 2011. At this time, the Stevenson Screen housing the data logger was found knocked over and the sides damaged. All temperature values during this time period are suspect due to increased exposure of logger to wind and sunlight. It is impossible to know when the Stevenson Screen was damaged and thus to know what portion (if any) of these data are usable. The Stevenson Screen was reinstalled on July 18, 2012, when data collection resumed. Metadata for related data sets are in:https://niwot.colorado.edu/meta_data/b-1mtape.ml.meta.txt https://niwot.colorado.edu/meta_data/b-1preci.ml.meta.txt https://niwot.colorado.edu/meta_data/b-1dp219.ml.meta.txtThe decrease in temperature and increase in humidity beginning September 9th 2013 reflect a large rain/flood event. NOTE: While we strive to produce high-quality accurate data, sometimes errors may occur and data is subject to revision at any time. If you notice an error, please contact the data manager at bcczodata@colorado.edu

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Data and R scripts for: Nutrient export and elemental stoichiometry in an urban tropical river
Created: Oct. 11, 2018, 8:50 p.m.
Authors: William McDowell · William G. McDowell · Jody Potter · Alonso Ramírez · Miguel Leon

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.

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Puerto Rico - Precipitation, Soil Moisture, Reservoir Height, Streamflow / Discharge - Schoolyard Data Jam (1994-2016)
Created: Jan. 17, 2019, 3:11 p.m.
Authors: Steven McGee · Miguel Leon · Martha A . Scholl · Whendee Silver

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.

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Hurricane Maria referenced remotely sensed data
Created: March 4, 2019, 3:34 p.m.
Authors: Miguel Leon

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

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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 at https://github.com/miguelcleon/HysteresisAnalysis/

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Hurricane Maria 2017 Story Map
Created: April 15, 2019, 1:42 p.m.
Authors: Miguel Leon

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.

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