Minimum Data Set and the Framework for Sampling Dynamic Soil Properties

Arlene TugelSoil Scientist

Interpretations Staff, NSSC

National State Soil Scientist WorkshopMarch 17-21, 2008

Florence, KY

Outline

• Overall strategy

• Minimum data set

• Comparison studies

• Sampling framework using conceptual models

• Sampling Guide

• Responsibilities

Soil Change Leadership Team

• Karl Hipple, National Leader, Interpretations• Chris Smith, National Leader, Technical Soil Services• Susan Andrews, Director, Soil Quality Team• Larry West, National Leader, Investigations• Arlene Tugel, Soil Scientist, Interpretations• Jeff Herrick, Research Soil Scientist, ARS

Vision

Enhance NCSS data and products with information about how soils change.

Overall strategy

• Select priority benchmark soils

• Gather dynamic soil property data

• Populate a point database

• Develop interpretations of management effects on soil function and the consequences of change

• Use models and pedotransfer functions to populate the soil map unit data base.

IVShort-interval

monitoring

IIPhase

distinctions

ITaxonomic

classesRelatively unaltered control section Eroded Drained etc.

Drastically altered Transported (Minesols) Horizons destroyed Horizons mixed

Regular, periodic and cyclic fluctuationsSoil moistureTemperatureWater tables

IIIModels of change

Dynamic management effects on soilDynamic soil properties

Conventions for soil change

IVShort-interval

monitoring

IIPhase

distinctions

ITaxonomic

classesRelatively unaltered control section Eroded Drained etc.

Drastically altered Transported (Minesols) Horizons destroyed Horizons mixed

Regular, periodic and cyclic fluctuationsSoil moistureTemperatureWater tables

IIIModels of change

Dynamic management effects on soilDynamic soil properties

Conventions for soil change

Change in function

IVShort-interval

monitoring

IIPhase

distinctions

ITaxonomic

classesRelatively unaltered control section Eroded Drained etc.

Drastically altered Transported (Minesols) Horizons destroyed Horizons mixed

Regular, periodic and cyclic fluctuationsSoil moistureTemperatureWater tables

IIIModels of change

Dynamic management effects on soilDynamic soil properties

Conventions for soil change

Minimum data set of dynamic soil properties

(March 15, 2008)– Organic C– pH– EC– Bulk density/Soil

porosity– Structure and macro-

pores– Aggregate stability (wet)– Total N (for C:N ratio)– Soil aggregate stability

(field kit)

Weighted Rankings

2.5

3.0

3.5

4.0

4.5

5.0

Also: Particle sizeRock fragments

Administered by ARS, Las Cruces, NM

OC

pH

EC

Bu

lk d

en

sity

Str

uct

ure

Ag

g.

sta

bili

ty NS

oil

ag

gre

g.

sta

bili

tyC

a/M

g/K

/Na

eC

EC

Po

t M

in N P

KC

l-Al

Act

ive

CP

OM

B-g

luco

sid

ase

Infil

tra

tion

Ksa

tM

icro

b-b

iom

ass

Criteria for selecting properties

1. Sensitive to management

2. Clearly represent soil function

3. Relatively insensitive to environmental fluctuations (or response can be modeled)

4. Easy to measure repeatably, and accurately

5. Low cost

Supplemental and experimental properties

• Supplemental (situation-specific)– CaCO3, KCl-Al, Ksat, etc.

• Experimental – Biological properties– New techniques

Collecting the data:

Comparison studies

Each horizon to 40 cm

Utah PilotArches National Park

Winter fat, perennial grass

PGS

Cheat grass

AG

Weed invasion

A. Compare various management systems or plant communities

B. Document the central tendency and range of variation

Bulk density

       

Central tendency of plot means

Central range Variation

   Depth/horizon

full state phase range Mean Median

Interquartile range of plot

means CV

Begay fsl, 0-6%

PGS 0 - 2 cm 1.27 - 1.91 1.51 1.53 1.47 - 154 2.7

A not 0-2 1.27 - 1.68 1.51 1.53 1.44 - 1.56 4.5

    B 1.46 - 1.62 1.55 1.55 1.52 - 1.58 2.0

AG 0 - 2 cm 1.01 - 1.68 1.42 1.46 1.32 - 1.47 6.9

A not 0-2 1.29 - 1.54 1.42 1.41 1.38 - 1.48 3.9

    B 1.42 - 1.59 1.51 1.51 1.48 - 1.54 2.0

Bulk density

0-2

cm2

cm t

o ba

se o

f A

B t

o 25

cm

PG-S = perennial grass-shrub sub-state; AG = Annual grass (cheat grass) sub-state; n=4 = Median = Mean

High and low values of reference

state

C. Report differences between the inherent potential (reference state) and other management systems or land uses.

Framework to organize projects: Conceptual models

• State and transition models (STM) – from Ecological Site Descriptions

• Cropland management models

What is a conceptual model?

“A purposeful representation of reality.”• Provides mental picture of how something works. • Used to communicate that explanation to others.

– (Starfield et al., 1993)

Represents key: – processes, – interactions, and – feedbacks.

– (Gross, 2003)

Post oak/blackjack oak/little bluestem

Hot summer burn and /or long-term grazing

Burn, Site prep & Planting / Seeding.

No grazing or limited controlled grazing

Post oak/flowering dogwood/ tick trefoil-goldenrod. Multi-story. Canopy: 30-90%

Post oak/buckbrush (or similar) Lacks mid-story. Understory single species woody dominatedCanopy: open 30-90%

Pasture (improved)Non-native grass sod

Abandonment for 20+ yr with recruitment of woody natives

Harvest, site prep, seeding

PastureForest

Missouri PilotSTM by:

D. Wallace, J. Robinson,B. White, M. Kennedy

Uses of conceptual models in soil change projects

• Stratify the map unit component phase into multiple states that can be sampled;

• Help verify suitable sample locations;• Facilitate data extension to similar soils;• Organize relationships among management,

DSP’s, and plant communities (where present); – for interpretation, storage, and data delivery;

• Serve as a decision aid for conservation planning;– illustrates alternative states and predicted soil

responses to practices.

Soil Survey and Resource Inventory

Guide for Dynamic Soil Properties and Soil

Change VER. 1.1

2008

Soil Survey and Resource Inventory

Guide for Dynamic Soil Properties and Soil

Change VER. 1.1

2008

Procedures

• Comparisons studies• Conceptual models• 6 steps of a project• Interpreting soil change

and soil function

Cropland sampling design to be added

Six project steps

1. Project Planning – what

2. Sampling Design -- how

3. Sampling Requirements – how many/where

4. Field Work

5. Data Preparation

6. Data Analysis and Interpretation

Data storage

• SBAAG Ad-hoc committee (Sept. 2007)– Alan Price, Darrell Kautz, George Peacock,

Susan Andrews, Arlene Tugel

• Business requirements– For point data – Draft available on SBAAG sharepoint site– Work-in-progress

Stable medium for plant growth

Hydrologic cycle

Nutrient cycling

Organic C

N (for C:N ratio)

EC

pH

Aggregate stabilityStructure

Bulk density

Also Particle sizeRock fragments

Interpretations of management effects on soil function

Interpretations

• What is the condition of my soil?

• How does it compare to what is possible?

• If degraded, can it be restored it?

• How long will it take (and how much $)?

• What lands are at risk of irreversible (and undesirable) change?

• How will soil changes affect future management options?

Suggested responsibilities

MLRA Regional Offices (MO) and State Offices (SO)

– Identify resource management needs– Select priority benchmark soils– Set project priorities– Assist with project workplan development– Assist with new interpretations– ?????

Suggested responsibilitiesMLRA Project Offices (SSO) and discipline specialists

– Identify resource management needs– Develop project workplans– OJT– Collect data – Quality control– Enter and prepare data

for analyses– ????

NOTE: As much of data summary and analyses as possible will be automated. Specialist assistance is needed for statistical tests.

Assistance roles

Resource soil scientists, State discipline specialists, cooperators, NSSL/NSSC

– Identify resource management needs– Workplan development– Training– New methods– Data analysis, statistical tests – Interpretations

Questions?Mini-session topics

– Prioritizing benchmark soils (and important Ecological Sites)

– Management systems to be documented

– Operational questions

Summary• Populating the point database comes first.

– Data will be collected as a part of projects– Conceptual models will be used to design projects and

organize results.– Where present, vegetation data will be collected at the same

time as soils data

• Interpretations will emphasize management effects on soil functions.

• Other discipline specialists and cooperators have important roles.

• This is the orientation phase. We will improve our approach as we learn.