A DATA SET is a series of observations collected by the same methodology. Each data set should have documentation sufficient for someone unfamiliar with the research to replicate the study. Data sets may be broken into subsets (data files) that are discrete in space and time, in that order. The documentation for a data set should include all spatial and temporal subdivisions of the data.

(Data, Abstract, Methods, Variables)

NOTES:

• Add rows to tables or lines to paraghaphs as you need them for entering your data.
• Contact emelendez@lternet.edu, if you have any question.

PERSON(S) COMPLETING THIS FORM: E-MAIL ADDRESS:

DATA SET IDENTIFIER: Patterns in soil and physical properties of the Bisley Watersheds 1 and 2 (Big Dig 1988, Big Dig 1990)

PROJECT TITLE: Soil Nutrient Dynamics in Bisley

PROJECT DESCRIPTION: Soils and forest floor were sampled quantitatively from a montane wet tropical forest in Puerto Rico to determine the spatial variability of soil nutrients, the factors controlling nutrient availability, and the distribution of nutrients in soils and plants following Hurricane Hugo

LTER CORE AREAS: (Annotate all that apply)

Inorganic Inputs and Nutrient Movement

Organic Matter Accumulation

Disturbance Patterns

LEF LTER 1 RESEARCH TOPIC: (Annotate all that apply)

Recovery after disturbance

Environmental monitoring

Disturbance regime

We define a data file as a component of a data set. A data set can have only one data file or more. Basically, different data files have different data structures or format.
DATA SET FILES (SUBSETS):

Data File No.	Data File Identifier	On-Line Filename	Starting Date	Periodicity of sample	End Period
1	Soil chemical and physical properties (1988)	BigDigdata88.txt	June 1988	once	July 1988
2	Effects of Hurricane Hugo on soil chemical and physical properties (Big Dig 1990)	BigDigdata90.txt	June 1990	once	July 1990

RESEARCH LOCATION: Bisley Watersheds 1 and 2. The Bisley watersheds 1 and 2 are on the windward side of the mountains, have a mean annual precipitation of approximately 3500 mm, and occur in the subtropical forest life zone (Scatena, 1989).

INVESTIGATORS:

PRINCIPAL INVESTIGATORS E-MAIL address

Whendee Silver

wsilver@nature.berkeley.edu

OTHER RESEARCHERS E-MAIL address

Fred Scatena	fns@sas.upenn.edu
Art Johnson	ahj@sas.upenn.edu
Tom Siccama	Thomas.Siccama@yale.edu

CONTACT PERSONS E-MAIL address Phone Number (Include area code)

Whendee Silver

wsilver@nature.berkeley.edu

(510) 643-3074

SOURCE OF FUNDING (SPONSOR): Mellon Foundation, NSF LTER, USDA Forest Service

DATA SET ABSTRACT:
(1) Exchangeable cation concentrations were measured using different soil extracting procedures (fresh soil and air-dried and ground soil) to establish a range of nutrient availability in the soil, and to determine the relationship between different, but commonly used laboratory protocols.

(2) Soils extracted using fresh soils generally yielded significantly lower exchangeable Ca , Mg, and K concentrations than soils which were dried and ground prior to extraction. Soil nutrients generally decreased with depth in the soil.

(3) Several soil properties varied predictably across the landscape and could be viewed in the context of a simple catena model. In the surface soils, exchangeable base cation concentrations and pH decreased along a gradient from ridge tops to riparian valleys, while soil organic matter, exchangeable Fe and acidity increased along this gradient. On the ridges, N,P, and K were positively correlated with soil organic matter; on slopes, N and P were positively correlated with organic matter, and Ca, Kg, and pH were negatively correlated with exchangeable Fe.

(4) Soil nutrient availability in the upper catena appears to be primarily controlled by biotic processes, particularly the accumulation of organic matter. Periodic flooding and impeded drainage in the lower catena resulted in a more heterogeneous environment. Drying and grinding the soil prior to extraction had a greater impact on exchangeable cations from the upper catena than in the valley positions, probably due to greater soil organic matter content. See Silver, W.L., F.N. Scatena, A.H. Johnson, T.G. Siccama, and M.J. Sanchez. 1994. Nutrient availability in a montane wet tropical forest in Puerto Rico: spatial patterns and methodological considerations. Plant and Soil 164:129-145.

DATA SET METHODS: In 1988, prior to sampling, the watersheds were surveyed and permanently marked with stakes on a 40 m grid. A description was made of each grid point including information about tree species composition, basal area, and classification of the topography as either ridge, side slope, valley, or riparian valley (Scatena, 1989; Scatena et al., 1993) - See LTERDBAS #31: 40 X 40 grid vegetation and site characteristics, Bisley at http://luq.lternet.edu/data/lterdb31/metadata/lterdb31.htm. In June 1988, forest floor and surface soils were sampled on Watersheds 1 and 2. Two 15 X 15 X 10 cm pits, one for chemistry and one for root and rock volume, were dug at each grid point, 1 m east and 1 m west of the stake. Pits were excavated by first securing a 15 X 15 cm template (insiude area) with long nails and removing all live vegetation. Forest floor material (composed of all recognizable dead plant material) was collected from within the sqaure and placed in a separate bag for processing. A 10 cm deep block of mineral soil was then carefully excavated and placed in a bag. Multiple soil samples from the 10-35 cm and 35-60 cm depths were collected from inside the excavated pit using a 2.5 cm diameter soil corer. At a few sites, it was not possible to collect samples from one or both of these lower horizons due to large rocks or roots.

To determine bul density of the 10-35 cm and 35-60 cm depths, eight large quantitative pits (50 X 50 cm) were located in four elevation bands along the ridge dividing the two watersheds. Forest floor was removed and soils were excavated by depth (0-10 cm, 10-35 cm, 35-60 cm) using a technique outlined in Hamburg (1984). Soil from each depth of the big pits was weighed in the field using a spring balance and subsampled for dry weight conversions (105° C).

Fresh samples were stored in air-tight bags at approximately 4° C for less than one week prior to extractions and pH determinations. A subsample from all chemistry pits and the two lower depths from the 'roots and rocks pit' was given to the International Institute of Tropical Forest (IITF) in Puerto Rico. (For Lab and Satatistical analyses methos see publication, Silver et al., 1994)

REFERENCES:

Hamburg, S. P. 1984. Effects of forest growth on soil nitrogenand organic matter pools following release from subsistence agriculture. Pages 145-148 in Forest Soils and Treatment Impacts Proceedings of the North American Forest Soils Conference. Knoxville.

Silver, W.L., F.N. Scatena, A.H. Johnson, T.G. Siccama, and M.J. Sanchez. 1994. Nutrient availability in a montane wet tropical forest in Puerto Rico: spatial patterns and methodological considerations. Plant and Soil 164:129-145.

Scatena, F.N. 1989. An introduction to the physiography and history of the Bisley Experimental Watersheds in the Luquillo Mountains of Puerto Rico. General Technical Report SO-72. USDA Forest Service, Southern Forest Experiment Station, New Orleans, Louisiana.

CROSS-REFERENCES (other data sets related to this one):

SAMPLE LOCATION: Yale University, School of Forestry and Environmental Studies IITF, USDA Forest Service, Call Box 25000,, Rio Piedras, PR

STORAGE SITES (of data files): UC Berkeley

INVESTIGATOR'S ASSIGNED KEYWORDS: Nutrient cycling, nutrient availability, tropical forest ecology, plant/soil interactions

LEF LTER OFFICIAL KEYWORDS (See table): BISLEY WATERSHEDS: Q1, Q2, RIVER, BIOGEOCHEMICAL CYCLES, SOILS, HIGHER PLANTS, PEER REVIEWED JOURNAL

PUBLICATIONS:
Silver, W.L., F.N. Scatena, A.H. Johnson, T.G. Siccama, and M.J. Sanchez. 1994. Nutrient availability in a montane wet tropical forest in Puerto Rico: spatial patterns and methodological considerations. Plant and Soil 164:129-145.

DISSEMINATION: UNRESTRICTED

REASONS TO RESTRICT DATA IN THIS DATA SET BEYOND ITS TWO YEAR POLICY PERIOD*:

*WILL HAVE TO BE APPROVED BY LTER PRINCIPAL INVESTIGATORS: N. BROKAW, A. LUGO

SITES DESCRIPTIONS: The study site is in the tabonuco (Dacryodes excelsa Vahl) forest zone of the Bisley Research Area

Geographical positional system (GPS) Coordinates for each location:

location	latitude	longitude
Bisley Watershed 1
Bisley Watershed 2

VARIABLES:

FILE NAME OR #ABOVE (all in which the variable appears)	1, 2	1, 2	1, 2	1, 2	1, 2	1, 2
ABBREVIATION (as it appears on the data file)	X	Y	TOPOGRAPHY	DEPTH	WD	Ca cml
NAME OF VARIABLE	Grid number (X)	Grid number (Y)	topography	depth of soil	Wet/Dry Extractions	Calcium in cmol+ kg-1
DEFINITION OF VARIABLE	geographic X coordinates of plot center. Each grid point is a 10M diameter circle that was measured in 1988 prior to Hurricane Hugo (LTERDBAS #31)	geographic Y coordinate of plot center. Each grid point is a 10M diameter circle that was measured in 1988 prior to Hurricane Hugo (LTERDBAS #31)	topographic classification	Depth of extracted soil		Calcium concentration in cmol+ kg-1 determined on a DCP-Spectrumraspan V spectrophotometer from a KCl ground soils solutions.
UNIT	N/A	N/A	N/A	cm	N/A	centimoles of charge per kilogram of dry soil (cmol+ kg-1)
PRECISION	N/A	N/A	N/A	N/A	N/A	±.01
RANGE OR LIST OF VALUES	0,…,360	240,…,260	R=Ridge S=Slope VU=Upland Valley VR=Riparian Valley	1=0-10 cm 2=10-35 cm 3=35-60 cm	1=wet extractions  2 = dry extractions
DATA TYPE	integer	integer	alphabetic	integer	integer	decimal
MISSING DATA CODES	none	none	none	none		999

VARIABLES CONTINUES:  

FILE NAME OR #ABOVE (all in which the variable appears)	1, 2	1, 2	1, 2	1, 2	1, 2	1, 2
ABBREVIATION (as it appears on the data file)	Mg cml	K cml	N %	P µg g-1	SOM %	pH
NAME OF VARIABLE	Magnesium in cmol+ kg-1	Potassium in cmol+ kg-1	Percent of Nitrogen	Extractable Phosphorus	Percent of Soil Organic Mater	pH
DEFINITION OF VARIABLE	Magnesium concentration in cmol+ kg-1	Potassium concentration in cmol+ kg-1	Percent of Nitrogen	Phosphorus concentration in µg g-1
UNIT	centimoles of charge per kilogram of dry soil (cmol+ kg-1)	centimoles of charge per kilogram of dry soil (cmol+ kg-1)	percent	microgramsPerGram (ug /g)	percent
PRECISION	±.01	±.01	±.01	±.1	±.01	±.01
RANGE OR LIST OF VALUES
DATA TYPE	decimal	decimal	decimal	decimal	decimal	decimal
MISSING DATA CODES	999	999	999	999	999	999

VARIABLES CONTINUES:  

FILE NAME OR #ABOVE (all in which the variable appears)	1, 2	1, 2	1, 2	1, 2	1, 2	1, 2
ABBREVIATION (as it appears on the data file)	Al cml	Exacid	Ca kg ha-1	Mg kg ha-1	K kg ha-1	N kg ha-1
NAME OF VARIABLE	Aluminium in cmol+ kg-1	Exchangeable acidity	Kilograms of Calcium per hectare	Kilograms of Magnesium per hectare	Kilograms of Potassium per hectare	Kilograms of Nitrogen per hectare
DEFINITION OF VARIABLE	Aluminium concentration in cmol+ kg-1	Exchangeable acidity	Kilograms of Calcium per hectare	Kilograms of Magnesium per hectare	Kilograms of Potassium per hectare	Kilograms of Nitrogen per hectare
UNIT	centimoles of charge per kilogram of dry soil (cmol+ kg-1)	centimoles of charge per kilogram of dry soil (cmol+ kg-1)	kilogramsPerHectare (Kg/ha)	kilogramsPerHectare (Kg/ha)	kilogramsPerHectare (Kg/ha)	kilogramsPerHectare (Kg/ha)
PRECISION	±.01	±.01	±.01	±.01	±.01	±.01
RANGE OR LIST OF VALUES
DATA TYPE	decimal	decimal	decimal	decimal	decimal	decimal
MISSING DATA CODES	999		999	999	999	999

VARIABLES CONTINUES:  

FILE NAME OR #ABOVE (all in which the variable appears)	1, 2	1, 2	1, 2
ABBREVIATION (as it appears on the data file)	P kg ha-1	Al kg ha-1	Bulk Density
NAME OF VARIABLE	Kilograms of Phosphorus per hectare	Kilograms of Aluminium per hectare	Bulk Density per grid point/depth/topography classification
DEFINITION OF VARIABLE	Kilograms of Phosphorus per hectare	Kilograms of Aluminium per hectare	Weight of soil contained within a given volume from soils excavated by depth after forest floor was removed using a technique outlined in Hamburg (1984)
UNIT	kilogramsPerHectare (Kg/ha)	kilogramsPerHectare (Kg/ha)	gramsPerCubicCentimeter (g/cm3)
PRECISION	±.01	±.01	±.01
RANGE OR LIST OF VALUES
DATA TYPE	decimal	decimal	decimal
MISSING DATA CODES	999	999	blank

COMPUTATIONAL METHODS:

Variable Name	Formula

DATE OF LAST REVIEW: September 30, 2004
DATE OF LAST ENTRY: 1988
STAGE OF DATA SET MANAGEMENT (dates):
RECEIVED ENTERED: Aug 2000 Jan 2001
FILED ON-LINE Jan 2001
REVIEWED BY RESEARCHER

Rev. date of this form: 23 January 2001