terrestrial/aquatic microbes at neon

© 2012 National Ecological Observatory Network, Inc. ALL RIGHTS RESERVED.

The National Ecological Observatory Network is a project sponsored by the National Science

Foundation and managed under cooperative agreement by NEON Inc.


SCIENCE DESIGN FOR

TERRESTRIAL MICROBIAL

ECOLOGY AT NEONJacob Parnell


Terrestrial Observation System (TOS) Field

Design

• Climate change• Land-use dynamics• Invasive species

• Biogeochemical cycles• Biodiversity and ecosystem function• Hydrological forecasting• Infectious diseases and environment

Drivers of biological and ecological change

Effects on organisms, populations, and

communities

Responses

Drivers

Interactions,Feedbacks



Design



Design

10

12

Time [s]

100

103

106

109

1012

Len

gth

[μ

m]

10

0

10

-3

10

3

10

6

10

9

Terrestrial & aquatic field sampling

Terrestrial & aquatic sensors

Airborne remote sensing

Satellite and external data

Metabolic processes,

CO2, O2, H2O exchange

Phenology,

productivity

Population dynamics, gas

and nutrient fluxes

Succession, biodiversity

Biogeochemical

cycles

Land surface interactions

500+ data products


What to measure & Frequency of measurements

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For the first 2 years, samples will be

collected every month in order to

determine seasonal variation at each

site. Three time points will be selected

that maximize the seasonal variability

for the duration of the project.



Material 16S ITS Meta-

transcriptome

Meta-

genome

qPCR Cell count

Soil 5400 5400 5400 1800 5400 0

Water 324 324 324 108 324 324

Sediment 324 324 324 108 324 324

Benthic 324 324 324 108 324 324

Total/yr 6372 6372 6372 2124 6372 972

Total 19116

0

191160 191160 63720 191160 29160


Spatial design:

Author: Leslie Goldman

www.neoninc.org

A Scalable Strategy for Terrestrial Biological Measurements

Authors: Paul Duffy, Dave Barnett, Becky Kao, David Schimel and Elena Azuaje

One of the challenges facing the Terrestrial Biological

Measurement team is the development and

implementation of a scalable sampling framework that

satisfies multiple constraints that can vary among sites.

By utilizing multiple lines of evidence, this approach

provides a framework to be utilized for the deployment of

an iterative probability based sample design.

Introduction

Spatial Balance for Probability-Based Design Minimum Sample Size Q’s for Relative Allocation Among Strata

Multiple Constraints Guide the Design

Contact Information: [email protected]

Initial Vegetation Classification

A primary constraint is to

obtain sufficient data from

each vegetation type

sampled. To bound the

minimum number of samples,

a test of the difference in

slopes of a response through

time was considered. A mixed

effects, repeated measures

model with slopes as random

effects was used. Assuming a

compound symmetric

correlation structure, a

minimum sample size of 10

was selected.

What is the smallest percentage of total site area that

a vegetation class can occupy and still be sampled?

We assessed relative sample allocation using the

constraints of both 5% and 10% as the minimum relative

area for a vegetation type within a stratum. The 10%

minimum tends to result in sample allocation that is

consistent with the constraints from the classical sample

size calculation.

What assumptions can be used to develop an initial

allocation? As a starting point, we assumed that the area

of a given stratum was proportional to the standard

deviation of species richness. Initial data collection will

refine this assumption and reallocate sample size among

strata according to estimates based on site specific data.

• Classical approach used for minimum

sample size determination

• Stratification among vegetation types

• Homogeneous variability approach used

to determine relative allocation among

strata

• Generalized Random Tessellations

Sampling to obtain spatial balance with a

probability based design

• Complete sample provides alternative

plot locations and allows integration with

other investigations

• Approach is general and scalable

• Initial data collection will validate the

design assumptions and feedback to

refine calculations regarding sample

number, allocation, and frequency

LANDFIRE vegetation classes are simplified to create

strata that are used to guide the first stage of the design.

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Initial Data Collection for

Design Validation

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Hierarchical-recursive

subdivision Morton addresses Reverse Morton

addresses

Sequential ordering Reverse

Morton addresses

Randomized reverse

sequential ordering

Modified

Figure 1

taken from

Theobald

et al. 2007


Spatial design:



Design

40m

40m


Aquatic Observation System (AOS) Field Design


Acknowledgements

Microbial Working Group:

G. King, L. Kinkel, L. Zeglin, C. Blackwood, N. Fierer, J. Gilbert

M. Allen, J. Tiedje, E. Triplett, D. Nemergut

Current/Previous NEON Scientists:

R. Gallery, K. Docherty, E. Hinckley, C. Meier, D. Barnett

terrestrial/aquatic microbes at neon

Science

ecological changeeffects

scale ecology

national science foundation

puerto rico

sampling algorithm

terrestrial microbial

time points

science design