Examples and opportunities for syntheses of long-term cross site data

LTER NetworkExperimental Forest Network

PR (tropical forest)

NC (southern deciduous forest)

MA (northern mixed forest)

MI (northern deciduous forest)

KS (tallgrassprairie)

SW (shrub desert)

WY (shrub steppe)

OR (wet coniferous forest)

Temperate rain forest

Chaparral

Northern mixed forest

Deciduous forest

Montane coniferous forest

Temperate grassland

Shrub desert

Tropical forest

PR (tropical forest)

NC (southern deciduous forest)

MA (northern mixed forest)

MI (northern deciduous forest)

KS (tallgrassprairie)

SW (shrub desert)

WY (shrub steppe)

OR (wet coniferous forest)

Temperate rain forest

Chaparral

Northern mixed forest

Deciduous forest

Montane coniferous forest

Temperate grassland

Shrub desert

Tropical forest

Temperate rain forest

Chaparral

Northern mixed forest

Deciduous forest

Montane coniferous forest

Temperate grassland

Shrub desert

Temperate rain forestTemperate rain forest

ChaparralChaparral

Northern mixed forestNorthern mixed forest

Deciduous forestDeciduous forest

Montane coniferous forestMontane coniferous forest

Temperate grasslandTemperate grassland

Shrub desertShrub desert

Tropical forestTropical forest

Lotic Intersite Nitrogen Experiment

Early Efforts in LTER Climate Committee

1986 Objectives

• Establish baseline meteorological measurements– Characterize each LTER site– Enable intersite comparisons

• Document both cyclic and long-term changes

• Provide a detailed climatic history– Correlate with bio-ecological phenomena– Provide data for modeling

Climate and Hydrology Database harvester Objectives

– Promote use of data for science, management and education

– Maintain a current data warehouse of multi-site, multi-network, long-term climate and streamflow data

– Provide critical background data in learning about and mitigating environmental change on the continental scale

– Provide accessibility to data through a single portal – Provide a web interface to download, graphically

display, and view data– Facilitate intersite science and foster development of

multi-network datasets

ClimDB/HydroDB Web Pages

http://www.fsl.orst.edu/hydrodb/

Implemented in 2002

Funded provided by LTER and USFS

Small amts of funding to sites to organize datainto format for harvester

Funding for programmingof harvester

ClimDB and HydroDB

41 Sites– 24 LTER sites + 2 International LTER sites– 22 USFS sites – 12 sites include USGS gauging stations

327 Measurement Stations– 154 meteorological– 173 stream gauging (includes 65 USGS)

21 daily measurement parameters– Primarily streamflow, air temperature, precipitation

Over 10 million daily values

ClimDB/HydroDBUser downloads by year:

Year Total Files Plots Views

2003 1840 309 1240 291

2004 931 267 566 98

2005 1737 717 829 191

2006 3199 1886 978 335

2007 1972 946 816 210

2008 2494 1259 888 347

2009* 1597 856 537 204

Total 13,770 6240 5854 1676* Through 8-19-2009

Parameter Parameter Code

Units

Air Temperature airtemp Degrees Celsius (C)Atmospheric Pressure atmpressure Hectopascals (hPa)Dew point Temperature dewpoint Degrees Celsius (C)Global Radiation globalrad Megajoules per square meter (MJm-2)

Precipitation precip Millimeters (mm)Relative Humidity rh Percent (%)Resultant Wind Direction

reswinddir Degrees Azimuth

Resultant Wind Speed reswindsp Meters per second (m/sec)Snow Depth (water equivalence)

snowh2o Millimeters (mm)

Soil Moisture sm Megapascal (MPa)Soil Temperature soiltemp Degrees Celsius (C)Stream Discharge discharge Liters per second (l/sec)Vapor Pressure vappressure Hectopascals (hPa)Water Temperature watertemp Degrees Celsius (C)Wind Direction winddir Degrees AzimuthWind Speed windsp Meters per second (m/sec)

Metadata categories about sites

• Research Area Information

• Watershed Spatial Characteristics

• Watershed Ecological Characteristics

• Watershed Descriptions

• Hydrologic Gauging Station

• Meteorological Station

Data Aggregation Rules

• Values flagged with “Q” or “M” will not be included in monthly or yearly aggregation. Values tagged with “E” will be included. The number of valid values used in the aggregation will be displayed. Sites are encouraged to estimate data values rather than reporting questionable or missing data.

•  • If all data values (e.g., data values listed in the header line) are all missing for a period of days,

it is not necessary to “fill in” these periods with null data and “missing” flags. •  • Each field in the data is parsed and has its leading and trailing spaces removed before

inspection. Then in this order these operations occur:•  • If a data value of 9999 is encountered, its flag will be forced to M.• If an invalid flag code is encountered, an error message will be logged and the record ignored.• If a data value of NULL (nothing) is encountered, the flag will be forced to M • If a flag value is G, the flag will be forced to NULL.• If a flag value is M, the data value will be forced to NULL,• In the case of precipitation, if the flag is T but the data value is NULL (e.g., blank), the flag will

be forced to M and a warning message will be logged.

Data Acquisition

Download or Graphical Display

More cross-site comparisons LTER Network

LTER EcoTrendsData summary and comparison across sites

LTER EcoTrends

Problem!

Lots more issues than expected

LTERECOTRENDSEXAMPLE

Interest in exploring stream chemistry responses to environmental gradients and

land use change across continent

Beginning cross site synthesis of long-term stream

biogeochemistry across 10 Experimental Forests

Priority solutes San Dimas Experimental ForestFernow Experimental ForestCoweeta Hydrologic LaboratoryBonanza Creek Experimental Forest/Caribou-Poker Creeks Research WatershedH.J Andrews Experimental ForestHubbard Brook Experimental ForestTenderfoot EFLuquillo EF Fraser EF Marcell EF SanteeNitrate 1979 1969 1971 1986 1968 1964 1992 1983 1982 1966 1976Ammonium 1979 1970 1971 1995 1968 1964 1993 1983 1982 1977 1976

Dissolved Kjeldahl Nitrogen 1968 1968 1976Total Kjeldahl Nitrogen 1978 1993 1968Total Dissolved Nitrogen 2005 1995 2005 1995 1988 2005 1997 1994Total Nitrogen 2005 1997

Soluble Reactive Phosphorus 1999 1968 1972 1989 1976Orthophosphate measured by IC 1971 1982 1996

Total Dissolved Phosphorus 1968 1983 1968 2003Total Phosphorus 2008 1974 1992 1968

Dissolved Organic Carbon 2005 1995 2001 1995 2007 1983 1990 2004Calcium 1969 1969 1986 1968 1963 1992 1983 1982 1968 1976Potassium 1969 1969 1986 1968 1963 1992 1983 1982 1968 1976

Additional analytes

Magnesium 1969 1969 1986 1968 1963 1992 1983 1982 1980 1976

Sodium 1969 1969 1986 1968 1963 1992 1983 1982 1980 1976

Sulfate 1979 1969 1971 1986 1970 1964 1992 1983 1982 1980 1976

Chloride 1971 1971 1986 1978 1964 1992 1983 1982 1980 1976

Conductivity 1960 1995 1970 1992 1983 1982 1980 1976

ANC/alkalinity 1971 1986 1968 1992 1984 1980

pH 1960 1971 2002 1968 1963 1992 1983 1982 1980 1976

Silica 1971 1986 1969 1964 1983

Total Aluminum 1995 1964

Dissolved Inorganic Carbon 2002 1983

Particulate Organic Carbon 1983

Total Organic Carbon 1992

Color (Pt-Co) 1966

Nitrite 1993

Hardness 1992

Bicarbonate 1971? 1992 1976

Carbonate 1971? 1992

Flouride 1982

Manganese 1995

Total Iron 1986

Drowning in Data

Current Experimental Forest Synthesis Database Design

Sites

Site web sites

Contacts

Site disclaimers & agreements

Status of data

Basins

Disturbances

Disturbance details

Names

Standardized methods

Labs

Equipment

Methods

Discharge

Data tables

Chemistry parameters tables

Chem data – instantaneousconcentrations

Chem data – integrated & aggregated

concentrations

Samples - instantaneous

Samples – integrated & aggregated

Chem data – fluxes

ChallengesStandardizing data & issues of comparability

Standard units and nomenclature

Methods

Time steps / aggregation methods

Detection limits

Nitrate

Ammonium

Dissolved Kjeldahl Nitrogen

Total Kjeldahl Nitrogen (unfiltered)

Total Dissolved Nitrogen

Total Nitrogen (unfiltered)

Soluble Reactive Phosphorus

Orthophosphate measured by IC

Total Dissolved Phosphorus

Total Phosphorus (unfiltered)

Dissolved Organic Carbon

Total Organic Carbon

Dissolved Inorganic Carbon

Calcium

Potassium

Magnesium

Sodium

Sulfate

Chloride

Silica

Bicarbonate

Carbonate

ANC/alkalinity

pH

Hardness

Conductivity

Total Aluminum

Preliminary ListOf Analytes

Hierarchical parameter categoriesImportance of standard terminology

Example: Total Nitrogen is ambiguous– Total Nitrogen (unfiltered) and – Total Dissolved Nitrogen

chemistry databases can become unwieldy without organized parameters

Chemistry data standardizationExamples of difficult issues

Chemistry data standardizationExamples of difficult issues

Converting to standard unitsClear labels of original & standard units are important

Example: NO3 (mg/L) is ambiguous

– nitrate as nitrogen, NO3-N (mg N/L)

– nitrate as nitrate, NO3 (mg NO3/L)

Pre-population conversion vs. stored procedures to convert on the fly

Chemistry data standardizationExamples of difficult issues

Detection LimitsDocumenting the detection limit of below detection values

is important

– different researchers /labs’ policies on reporting machine-read values below detection and detection limits vs. only reporting detection limits needs to be reconciled

– a code indicating “below detection” is insufficient

– treatment of historic data for which detection limits are unknown needs to be determined

Question driven, collaborative approach and harvester as a product

Synthesis Papers and Products

Topic 1: Informing national nutrient criteria using long term reference basin data

Topic 2: Examining effects of forest disturbance on stream chemistry dynamics, concentrations and fluxes

Topic 3: Cross site comparison of effects of different calculations of fluxes

Products: peer reviewed papers, metadata on sites and methods, databases structured to allow future cross site harvesting

Poster presented at NAFEW, Logan UT, June 2009

Chem DB

Developed from desire for cross site stream chemistry

synthesis

Idea to build on Clim/HydroDB

harvester but with increasing

complexity

HydroDesktop Hydrologic Information System (HIS)

Observations

Models

Climate

GIS

Remote Sensing

Synthesis and Networks

• Challenges involved in integrating

legacy data

• Planning for synthesis at the beginning easier

• Importance and value of metadata

• Automated data scripts to keep data current

• Huge benefits and learning from comparing dynamics cross site

Organizing from the start:Critical Zone Observatories

Opportunities for and syntheses of long-term cross site data

• Air temperature; daily minimum, maximum, and mean in degrees Celsius (C)

• Atmospheric pressure; daily mean in hectopascals (hPa)

• Dewpoint temperature; daily mean in degrees Celsius (C)

• Global solar radiation; daily total in MegaJoules per square meter (MJm-2)

• Precipitation; daily total in millimeters (mm)

• Relative humidity; daily mean in percent (%)

• Snow depth (water equivalence); daily instantaneous observation in millimeters (mm of water).

• Soil Moisture; daily mean in megapascals (MPa)

• Soil temperature; daily mean in degrees Celsius (C)

• Stream Discharge; daily mean in liters per second (l/sec)

• Vapor pressure; daily mean in hectopascals (hPa)

• Water Temperature; daily minimum, maximum, and mean in degrees Celsius (C)

• Wind direction and resultant wind direction; daily mean in degrees azimuths (deg)

• Wind speed and resultant wind speed; daily mean in meters per second (m/sec)

ClimDB Parameters