Response to the NEON RFI
TITLE: STREON Stream observational network
Assessing the resistance and resilience of aquatic ecosystems to global change
1. Submitting Domain(s) or Consortia:
STREON, a group of 60 doctoral stream research scientists with interests in
continental patterns in stream ecology and terrestrial/ aquatic interfaces
2. RFI Response: Research Design Observational
3. Lead Scientists
Dr. Walter K. Dodds
Division of Biology
Kansas State University
Manhattan, KS 66506
785 532 6998
wkdodds@ksu.edu
Dr. Margaret A. Palmer
Chesapeake Biological Lab
University of Maryland Center
for Environmental Science
Solomons, MD 20688
410 326 7241
mpalmer@umd.edu
Dr Bradley J. Cardinale
Dept of Ecology, Evolution &
Marine Biology
University of California Santa Barbara
Santa Barbara, CA 93106
805 893 4157
cardinale@lifesci.ucsb.edu
4. Key Contributing Scientists: Steering Committee
Dr. Nancy B. Grimm
Dr. Sherri L. Johnson
School of Life Sciences
USFS PNW Research Station
Arizona State University
3200 SW Jefferson Way
Corvallis, OR 97331
PO Box 874501
541 758 7771
Tempe, AZ 85287-4501
480 965 4735
johnsons@fsl.orst.edu
nbgrimm@asu.edu
Dr. Stephen K. Hamilton
Dr. Matt Whiles
Michigan State University
Southern Illinois University
Kellogg Biological Station
Department of Zoology
3700 E. Gull Lake Dr.
Life Sciences II, Room 351
Hickory Corners, MI 49060
Carbondale, IL 62901-6501
616 671 2231
618 453 7639
hamilton@kbs.msu.edu
mwhiles@zoology.siu.edu
1
Additional Affiliated Scientists
Scientists
J. Dunham
B. Bowden
J. Melack
J. Jones
T. Tsegaye
C. Pringle
M. Valett
S. S. Kaushal
J. Boyer
J. Trexler
D. McKnight
D. White
M. Bernot
C. Hargrave
S. Earl
J. Tank
K. Gido
G. Tribble
M. Kido
W. McDowell
M. Whiles
E. Stanley
J. Vander Zanden
P. Mulholland
B. Peterson
L. Deegan
J. Ehleringer
T. Crowl
E. Strauss
C. Dahm
K. Miller
J. Sabo
A. Huryn
A. Ward
C.C. Vaughn
L.J. Weider
R. O. Hall
L. Wei
Institution
Oregon State Univ.
Univ. of Vermont
Univ. of California, Santa Barbara
Univ. of Alaska, Fairbanks
Alabama A & M Univ.
Univ. of Georgia
Virginia Polytechnic Institute and
State Univ.
Univ. of Maryland
Florida International Univ.
Florida International Univ.
Univ. of Colorado
Murray State Univ.
Murray State Univ.
Sam Houston State Univ.
Arizona State Univ.
Univ. of Notre Dame
Kansas State Univ.
Univ. of Hawaii
Univ. of Hawaii
Univ. of New Hampshire
Southern Illinois Univ.
Univ. of Wisconsin
Univ. of Wisconsin
Oakridge National Laboratory
Marine Biological Laboratory
Woods Hole
Marine Biological Laboratory
Woods Hole
Univ. of Utah
Utah State Univ.
Fort Hays State Univ.
Univ. of New Mexico
Univ. of New Mexico
Arizona State Univ.
Univ. of Alabama
Univ. of Alabama
Univ. of Oklahoma
Univ. of Oklahoma
Univ. of Wyoming
South Dakota State Univ.
Site
Andrews Experimental Forest
Arctic
California
Caribou Poker Creek
Cole Spring Branch
Coweeta
Coweeta
Code
AND
ARC
SNV
CPC
CSB
CWT
CWT
Eastern Coastal Plain
Everglades
Everglades
Green Lakes Valley; Albion townsite
Hancock Biological Station
Hancock Biological Station
Harmon Creek
Indian Bend Wash
Kellogg Biological Station
Konza Prairie Biological Station
Limahuli Stream, Kauai, Hawaii
Limahuli Stream, Kauai, Hawaii
Luquillo
Middle Mississippi River Wetlands
Northern Lake District
Northern Lake District
Oak Ridge Walker Branch
Plum Island
ACL
FCE
FCE
GLV
HBS
HBS
HAR
IBL
KBS
KNZ
LIM
LIM
LUQ
MMW
NTL
NTL
ORW
PIE
Plum Island
PIE
Red Butte Creek
Red Butte Creek
Saline River
Sevilleta
Sevilleta
Sycamore Creek
Talladega Forest
Talladega Forest
Univ. of Oklahoma Biological Station
Univ. of Oklahoma Biological Station
Upper Snake River
Williston Research Extension Center
RBC
RBC
SAL
SEV
SEV
SYC
TAL
TAL
UOBS
UOBS
SNK
WRE
2
I. Abstract/Summary
Human activities have greatly altered freshwater ecosystems, including depletion and
degradation of freshwater supplies, increased nutrient loads, and diminished biodiversity. We
know little of how these changes will individually and collectively influence the resistance and
resilience of ecosystems in light of climate change. Accordingly, we propose a long-term,
continent-wide observational network to detail the mechanisms by which aquatic ecosystems
resist and recover from three of the most pervasive forms of human-induced disturbance. This
information is central to accurate ecological forecasting. We will focus on streams, rivers, and
wetlands, hereafter collectively referred to as streams. Streams are disproportionately important
for biodiversity, ecosystem services, and economic, recreational and aesthetic values. Our
overarching question is: how will chronic nutrient inputs (nitrogen or phosphorus), higher
probabilities of extreme events (droughts and floods), and simplification of food webs (loss of
consumers) impact the resistance and resilience of stream ecosystem function (stream-wide
respiration, production, and nutrient retention)? We define resistance and resilience as the
proportional change in ecosystem functions following a disturbance and the return interval,
respectively. There is strong justification for linking the ecosystem drivers that are the subject of
this proposal. Streams and other running waters are ideal ecosystems for the proposed
network because they (i) have well delimited inputs and outputs, and thus allow quantification
of the resistance and resilience of the focal ecosystem-level processes, (ii) are dynamic systems
that respond to disturbances over periods of weeks to months - time scales amenable to
observation and experimentation, (iii) can be studied with comparable methods spanning the
entire continent, (iv) are important sites of nutrient retention and (v) integrate watershed
processes that occur on the same scales as those investigated by NEON network sensor
platforms. Many of these attributes are unique and allow some types of cross continental
observations that are simply not feasible with other ecosystems.
We propose 30 observational sites distributed across the continent to capture variation in
hydrology, temperature, nutrient loading, elevation, and biogeographical context. Each
observational site will require two aquatic sensor packages to enable study of the effects of instream ecosystem processes on water in transit through the study reach. We will also require
additional measurements not in the ISEP including total N and total P, decomposition rates,
nutrient limitation assays, dissolved gas analyses, and food web analyses using natural
abundance of stable isotopes. These additional measurements are required to adequately
characterize aquatic community structure and ecosystem function.
This ecological observatory network will complement emerging networks related to
water bodies that focus on physical and chemical properties (i.e., EPA-WATERS), and existing
networks of long-term ecological studies that have used a variety of methods and site selection
protocols (i.e., LTER, USGS hydrologic benchmark stations).
This is one of two linked responses to the NEON RFI’s for observational and
experimental continental networks of stream research. Some sections of these two responses
are very similar (Scientific Challenge, table of measurements) and others are different given the
different requirements of the two RFI’s (e.g. site information, education and outreach,
experimental design). The observational network will rigorously assess major drivers
influencing streams and wetlands and how they link to other habitats. The experimental network
strengthens the inference for a relatively low added cost.
3
II. Scientific Challenge
Human impacts on Earth's ecosystems are now so pervasive that few systems can be considered
‘pristine’. Transformation of natural landscapes has benefited society (e.g., food and energy
production), but comes at a high cost including a more extreme and unpredictable climate
(Zachos et al. 2001), depletion and degradation of freshwater (Postel et al. 1996), and a
catastrophic loss of biological diversity (Sala et al. 2000, MEA 2005). We know much about the
drivers of ecological change, but far less about the potential for ecological systems to adapt,
recover, resist further change, or enter irreversible trajectories. Societal responses depend on an
adequate understanding of how our actions constrain our options in the future. Thus, ecological
forecasting requires identification of the mechanisms underlying ecosystem resistance change
and internal feedbacks contributing to resilience (MA 2003).
Here we propose a 10-year, continent-wide observational network to detail the
mechanisms by which aquatic ecosystems resist and recover from three of the most
pervasive forms of human-induced disturbance. Our observational network will link divers
of ecological change in streams. We focus on streams, rivers, and wetlands (hereafter streams
for brevity) because they are the most economically valuable per unit area of any ecosystem and
are primary sources of food and drinkable water (Baron et al. 2002). Streams integrate the
effects of human activities on the landscape indicating environmental change across spatial
scales. Forms of human-induced disturbance we will focus on are (i) chronic nutrient
enrichment, (ii) altered frequencies of floods & droughts, and (iii) alteration of food-web
structure. Humans have roughly doubled the availability of nitrogen (N) and phosphorus (P) in
stream networks, leading to eutrophication of streams and downstream water bodies (Meybeck &
Helmer 1989, Kemp et al. 2005). As the climate changes over the next century, streams will
experience a greater frequency of floods and droughts due to an accelerated hydrologic cycle
(Poff et al. 2002, Nelson & Palmer in press). Furthermore, the extinction rate of freshwater biota
exceeds that for most marine or terrestrial fauna with top trophic levels at highest risk (Allan &
Flecker 1993, Ricciardi & Rasmusen 1999).
Streams are ideal ecosystems for the proposed network because they (i) have well
delimited inputs and outputs, and thus allow quantification of the resistance and resilience of the
focal ecosystem-level processes (Peterson et al. 2001), (ii) are dynamic systems that respond to
disturbances over periods of weeks to months - time scales amenable to observation (iii) can be
studied with comparable methods spanning the entire continent, (iv) are important sites of
nutrient retention (Alexander et al. 2000, Wollheim et al. 2006) and (v) integrate watershed
processes that occur on the same scales as those investigated by NEON network sensor
platforms. Many of these attributes are unique and allow some types of cross continental
observations that are infeasible in other ecosystems.
II.1 Our overarching question is: how will chronic nutrient inputs (nitrogen or
phosphorus), higher probabilities of extreme events (droughts and floods), and simplification
of food webs (loss of consumers) impact the resistance and resilience of stream and wetland
ecosystem function indicated by whole ecosystem respiration, production, and nutrient
retention? We define resistance and resilience as the proportional change in ecosystem
functions following a disturbance and the return interval, respectively. Strong justification exists
for linking the ecosystem drivers (independent variables) that are the subject of this proposal.
First, theoretical and empirical work has shown that community structure and ecosystem
function are jointly influenced by disturbances, and nutrient loading can regulate rates of
recovery (Wilson & Tilman 1993, Amarasekare et al. 2004, Cardinale et al. 2006). Similarly,
4
nutrients and consumers interact because top-down and bottom-up controls have opposing
impacts on community structure and function (Kneitel & Chase 2004, Borer et al. 2006).
Furthermore, biodiversity and ecosystems are linked because resource capture and community
production depend on numbers and types of resources and species (Tilman 1999, Chapin et al.
2000, Swan & Palmer 2006).
When combined, this prior research leads to at least two related predictions that have not
been broadly approached at the continental scale or across major biomes as we propose. First,
the biomass and activity of basal species (autotrophs and microbial heterotrophs at the base of
food webs) depend on the relative impacts of two opposing forces: (i) hydrologic disturbance and
primary consumers that reduce producer biomass and mediate species coexistence, vs. (ii)
nutrient loading that promotes biomass production and favors basal species with high turnover
(Dodds et al. 2004) and growth rates (traits that favor resilience). Second, as (i) and (ii) alter
activity and biomass of basal species, they alter ecosystem functions, such as productivity,
respiration, and nutrient retention. As such, they can also alter the relative importance of the two
main pathways of energy flux through a foodweb – the producer vs. detrital pathways.
II.2 Our hypotheses (below) are directly related to both of NEON’s Grand Challenges. By
assessing the direction and pace by which stream ecosystems respond to and recover from
human-induced stressors (nutrient loading & altered hydrology), H1 (II.4) squarely addresses
Grand Challenge I. We even go a step further to examine interactions among drivers that may
limit ecosystem response. H2 and H3 (II.4) are directed at Grand Challenge II because we will
observe all 3 main drivers across a wide variety of sites. Importantly, our cross-domain
approach will capture patterns of responses across most major biomes in North America, as well
as sites within biomes that differ in terms of historical context.
II.3 Toolbox Each of the 30observational sites will require two aquatic sensor packages and
include biodiversity assessment.
II.4 Hypotheses and expected results
H1 Interactions among key drivers: The resistance and resilience of ecosystem functioning
(stream productivity, respiration, nutrient cycling and retention) are jointly determined by the
frequency of extreme hydrologic events (droughts/floods), the rate of nutrient loading, and food
web structure. We expect both nutrient loading and pulsed hydrologic disturbances to decrease
nutrient retention. Primary and secondary production should increase with greater nutrient
loading as should rates of microbial decomposition, leading to more rapid recovery (resilience)
from pulsed disturbances compared to an undisturbed state. However, with greater flood and
drought frequency, primary and secondary production and consumer control on basal system
ecosystem functions will decrease. Interaction between loading and disturbance will thus amplify
ecosystem variability. Increasing the frequency of extreme events will promote dominance by a
subset of disturbance resistant taxa or resilient species with high growth and colonization rates.
Increased nutrients will make detrital food sources more available to consumers, shifting the
food web to a more heterotrophic state (Johnson et al. 2006).
H2 Time scales of ecosystem feedbacks and regime shifts: Long term nutrient loading and
increased frequency of hydrological disturbance interact to promote irreversible ‘regime’ shifts
that alter resistance and resilience of ecosystem functioning to droughts/floods (hydrologic
disturbance). Nutrient loading will shift algal community structure to favor taxa that are less
5
palatable to herbivores (mostly invertebrates and fish), while also increasing the quality of
detritus that is consumed primarily by fungi and bacteria (e.g., C:N detrital ratios decrease with
nutrient loading, Dodds et al. 2004). Loss of primary consumers may be further exacerbated by
increasing frequency of hydrologic disturbances that preclude the recovery of larger primary
consumers. As top-down control by herbivores is jointly reduced by nutrient loading and
hydrological disturbances, ecosystem-level processes will shift from producer to decomposer
pathways, the resistance of ecosystem functioning to hydrologic disturbance will decrease, and
the resilience increase (see H1). Regime shifts resulting from the extinction of consumers may
take years to occur, and long-term studies are required to detect more than just the transient
phases of ecosystem response.
H3 Spatial scales of response: The resilience and recovery of ecosystem functioning over large
(continental) scales will vary with regional context including local species composition and
diversity, climate and hydrological disturbance regime. Community structure and ecosystem
function vary with both local conditions, as well as across biogeographic scales. Thus, a
continental-scale observational network is needed to elucidate the context dependency of
ecological responses. Nutrient loading and flow disturbance vary greatly across the gradient of
sites we have selected, allowing us to test hypotheses that would be impossible to test at single
sites. We predict that sites with chronic nutrient loading (e.g., U.S. farm belt) are closest to
critical points for regime shifts in response to added loading. We predict ecological context will
be important. For example, streams with closed canopies have detritus-dominated food webs
while open-canopy systems have prominent algal producers supporting food webs. Evolutionary
context also matters; herbivorous fish and invertebrate grazers dominate in southern and northern
streams respectively and are expected to react differently when exposed to floods and drought.
II.5 Why is NEON required for the proposed work? The interaction between altered flow
regimes and biotic communities under chronic nutrient pollution (Peterson et al. 1985) has
received little attention and has not been studied broadly across systems with standard
instrumentation. Development of broadly applicable predictive frameworks of ecological
resilience require observations at continental scales (Palmer and Bernhardt 2006). A long-term
observational network is necessary because some effects such as nutrient saturation and changes
in species composition may take decades to manifest themselves (Slavik et al. 2004) and
historical and existing differences influencing ecological response (context-dependency)
typically occur over fairly broad regions. These differences include many human impacts (e.g.
atmospheric vs. terrestrial N loading), as well as gradients of precipitation, temperature and
hydrologic regimes that form the adaptive template freshwater organisms have experienced over
evolutionary time (Poff 1996). The standard NEON aquatic instrumentation with some
modification is ideally suited for the proposed network, and a modest number of auxiliary
measurements coordinated through a common NEON facility will allow for comprehensive
quantification of stream ecosystem properties. II.6 How the measurements collected will be used in predictive models for forecasting The
conceptual approach of our observation network is ultimately tied to valuable ecosystem goods
and services (e.g., water purification, biodiversity, production of exploitable species, nutrient
cycling and retention). We require a continental observational network because of the complex
interactions and potential feedbacks between ecosystem function and community structure.
6
Predictive modeling cannot capture system dynamics without accounting for these feedbacks.
Our observational network has a high probability of documenting the pace and extent of impacts
of human alterations on freshwater ecosystems, and providing information useful to predictive
forecasting models.
Number of sites
Discharge (L/s)
III. Deployment Configuration
III.1 Spatial arrangement of gradient sites
Our observational network will take advantage of continental gradients in nutrient loading and
climatic regimes (e.g., arid to humid), We will focus on effects of: 1) chronic nutrient enrichment
via atmospheric deposition of nitrogen (high rates in the northeast and lower in many areas of the
rest of country); 2) diversity of consumers (context dependence of sites driven by biogeographic
patterns, invasive species, and stresses from human induced change); and, 3) hydrologic
variation among regions. Stream ecosystem responses to hydrologic variability including floods
and drought will be measured as the events naturally occur. We include sites representing a wide
range of mean discharge, stream permanence, and watershed area. The graphs below illustrate
the distribution of watershed area, discharge, mean air temperature, and precipitation for the
selected observational sites.
Sites span a number of other geomorphologic
100000
and biotic gradients that will help us untangle the
10000
context-dependent nature of stream responses to global
change. These include gradients of temperature (north1000
south), precipitation (east-west), elevation (sea level to
100
3200 m) and evolutionary history (species-poor areas in
10
northern glaciated areas, species-rich areas associated
1
1
10
100
1000
10000
100000 1000000
with the southeastern US). Sites are distributed across
Watershed area (ha)
all NEON domains. We also focus on particular areas of
9
rapid
change
or human impact (urban, cropland, hydrologic
8
modification).
For example, sites within the Prairie Peninsula
7
domain have similar annual temperatures but differ in N
6
deposition, and urban sites such as those in Phoenix and the
5
Midwest were selected to be in regions of rapid groundwater
4
withdrawal. Core wild land sites will be interspersed with
3
human impacted sites to assess more localized gradients of
2
human impacts.
1
0
We have also planned that some of the sites within
-15 -10 -5
0
5
10 15 20 25 30
Air temperature ( C)
domains will represent areas of rapid environmental change
14
(urban sites such as Phoenix, Midwest sites in regions of rapid
groundwater withdrawal, and agricultural sites in the Central
12
US). Core wild land sites will be interspersed with human
10
impacted sites to assess more localized gradients of human
8
impacts.
Number of sites
o
6
4
2
0
0
500
1000 1500 2000 2500 3000 3500
Pre ci pitation (m m)
7
III.2 Spatial arrangement of infrastructure
The figure above demonstrates the large scale placement of observational sites with respect to
NEON domains. Several smaller scale considerations for sites will apply. When possible sites
will be placed near locations where historic data are available or experiments have been
performed. Examples include sites that are part of the LTER network or are near USGS gauging
stations. Whenever possible sites will be placed in a watershed containing the footprint of
NEON terrestrial tower/sensor systems, or at least in a comparable watershed. At the smallest
spatial scale sites will be chosen where discharge can be estimated with pressure transducers
(either in areas with channel constrictions or construction of small weirs). At this scale sites will
also be chosen where equipment can be secured against flooding and tampering. Each site will
have two aquatic sensor packages to allow for input/output budgeting. At the smallest scale,
the two sensor packages and auxiliary measurement sites will be placed about one uptake length
(Sw) apart for the dominant limiting nutrient. The distance will also be chosen to be appropriate
based upon gas exchange (reaeration) rates.
8
Proposed sites span wide gradients of precipitation, N deposition, and mean maximum
temperature. Plots at right refer to transects depicted as lines on maps at their left. Letter name
codes give approximate locations of sites (indicated by purple dots on map) along the gradient.
These are only a few of the potential gradients and are presented here for illustrative purposes.
9
III.3a,b,c,d Proposed locations at core sites
Name of location
Dom.
Property owner
Latitude
Longitude
Primary
property
access
point
Road
Road
Andrews Experimental Forest
Arctic
16
18
44.207340
68.633333
-122.256965
-148.283333
Caribou Poker Creek
19
US Forest Service
BLM Research Natural
Area
University of Alaska
65.160000
-147.500000
Road,
ATV
trails
Green Lakes Valley
Konza/ Kings Creek
Northern Lake District
Luquillo/ Bisley
13
6
5
4
City of Boulder, CO
Nature Conservancy
State of Wisconsin
USFS
40.042875
39.103807
46.012000
18.316330
-105.592296
-96.595539
-89.672000
-65.748020
Road
Road
Dirt road
Road
Oak Ridge Reservation / Walker
Branch
Rio Salado
Talladega Forest
7
US Department of Energy
35.573168
-84.164504
Road
14
8
BLM
US Forest Service
34.3358
32.953200
-107.0392
-87.409000
Road
Road
Candidate gradient sites.
Name of location
Dom
Property owner
California Sierra Nevada
17
Cole Spring Branch
Coweeta
Eastern coastal plain
8
7
2
Entrada Field Station
Everglades
Hancock Biological
Station/Ledbetter Creek
Harmon Creek
13
4
8
Indian Bend Wash
14
Kellogg/ Augusta Creek
Limahuli Stream, Kauai,
Hawaii
5
20
Los Angeles Dept of Water
& Power,
Nature Conservancy
UDSA Forest Service
American Chestnut Land
Trust
USGS
NPS, Department of Interior
Commonwealth of
Kentucky/TVA
Sam Houston State
University
numerous private and
municipal
Michigan State University
National Tropical Botanical
Garden
Middle Mississippi River
Wetlands Field Station
6
Plum Island
1
Red Butte Creek in Red
Butte Canyon RNA
Saline River
San Pedro River
Sycamore Creek
University of Oklahoma
3
Lat.
Long.
Primary property
access point
37.611900
-118.872700
Road
34.677423
35.058633
38.525000
-86.323447
-83.445144
-76.525833
38.800000
25.468206
36.739484
-109.270000
-80.853276
-88.154249
30.744800
-95.471500
Road
33.631261
-111.890227
Road
42.366200
22.219930
49
-85.356300
-159.5765763
Road
Road
37.266666
-89.450000
Road
Road
Road
Road/trails
Road
Road/boat/helicopter
Road
42.722128
-70.847136
Boat
15
Illinois Department of
Natural Resources
(managed by SIUC)
Town of Ipswich
Conservation
US Forest Service
40.800000
-111.780000
Road
10
14
14
11
Fort Hays State University
Grayhawk Nature Center
Tonto National Forest
Army Corps of Engineers
39.070000
31.625833
33.694100
33.982240
-99.115000
-110.173889
-111.541000
-96.432000
Road
Road
Road
Road/trails/boat
10
Biological Station
Upper Snake River
Williston Research
Extension Center
12
9
and University of Oklahoma
Commonwealth of
Kentucky/TVA
North Dakota State
University
43.658300
-110.711300
Road/boat
48.160000
-103.630000
Road
IV. Measurements and Resources
IV.1 Key ecosystem-level processes will be measured at the inflow and outflow of each
experimental reach. This two-station approach is required to account for transport of materials
and to assess the importance of in-stream processing (Alexander et al. 2000, Bernhardt et al.
2005, Darracq and Destouni 2005, Wollheim et al. 2006). We will thus require 2 full aquatic
sensor packages for all sites (60 packages) and 1 Biodiversity sentinel unit per site. Ten of
our sites have been proposed as core wildland sites, so given the allotment of one aquatic sensor
package per wildland site, we will require 10 more sensor packages. We will need an additional
40 sensors to instrument each of 20 gradient sites. The original ISEP specified only one set of
aquatic sensors per stream site, but this does not allow separation of terrestrial and in-stream
ecosystem processes. We thus recommend allocation of sensor packages to provide maximum
ecological information.
IV.2 Ecosystem functions to be measured include stream metabolism (ecosystem productivity
and respiration), secondary productivity, nutrient retention and cycling (uptake, denitrification),
and decomposition rates. To help interpret why these ecological functions vary over among
sites, or within a site though time, we will track several structural response variables such as
species composition and diversity of algae, macrophytes, macroinvertebrates, and vertebrates, as
well as food web structure. We will use standard core biodiversity measurements as outlined in
the ISEP, with more intensive sampling where necessary as noted below. More frequent
measurements will be required to assess resilience to flood and drought, and to establish
secondary production of aquatic insects. Contemporary methods (e.g., stable isotopes coupled
with gut analyses) will be used to trace food webs and ecosystem process rates. Food web
structure will be established by sampling natural abundance of C and N stable isotopes, with
additional isotopes (sulfur, oxygen) where required.
Table 1. Independent and Dependent Variables to be Assessed Using Gradients
Independent Variables across Gradients
Climate – temperature, precipitation (mean, variance)
Nutrient deposition and loading
Extreme events (magnitude, frequency of flood and
drought)
Geomorphological context
Biological context (community composition)
Temperature
Elevation
Dependent Variables (level and resilience*)
Nutrient processing (N, P)
Decomposition
Respiratory metabolism and ecosystem production
Secondary production (inverts, fish)
Native and non-native species diversity
Food web structure (stable isotope studies)
*each dependent variable will be evaluated in terms of magnitude (e.g., rate of denitrification or primary
production, number of native species) and resilience following flow disturbances (e.g., rate and magnitude of
recovery following flow disturbances).
We propose central facilities for measurements of water chemistry, isotope analyses, and
macroinvertebrate and algal diversity so quality control and quality assurance can be maintained.
These could be at a national NEON facility or housed in laboratories of experts who would
11
oversee the individual facilities. Jan Stevenson at Michigan State University is willing to
supervise algal taxonomy, Matt Whiles at Southern Illinois University Carbondale is willing to
manage a macroinvertebrate diversity facility and Walter Dodds at Kansas State University is
willing to oversee water chemistry and isotope analyses.
Each observational site reach will also require some measurements not in the ISEP.
Dissolved gas measurements are necessary to allow for calculation of denitrification rates
(dissolved N2) as well as reaeration and production rates of greenhouse gasses (N2O, methane,
CO2). Total nutrient concentrations are needed to estimate ecosystem transport, retention, and
cycling. Natural abundance of stable isotopes in chemical fractions is required to establish
differences in biogeochemical cycling pathways. Stable isotope abundance in organisms and
food sources will allow for quantification of food web structure (e.g. path strengths in food webs,
not just linkages) and movement of nutrients into the biota under the different observational
conditions.
IV.2a,b,c,d Measurements to be performed currently specified in the Integrated Science
and Education Plan.
Measurement
Spatial Distribution
Water level in reach and nearby
groundwater
Dissolved organic carbon
concentration
Bottom of each reach
Nutrient concentrations: NO3 Sensor
Riparian groundwater levels
Conductivity
Turbidity
Chlorophyll
Surface PAR and UV
Automated water sample
collection for additional
chemical profiles (dissolved
and particulate N , P, and C)
Dissolved oxygen
Temperature
pH
Sampling
Frequency
Direct or Aggregate
Every 10
minutes
Daily
Aggregate mean daily plus
minimum and maximum
Direct
Top and bottom of each
reach
In groundwater wells
Daily
Top and bottom of each
reach
Top and bottom of each
reach
Top and bottom of each
reach
Middle of each reach
Hourly
Aggregate mean daily plus
minimum and maximum
Aggregate to mean monthly
plus minimum and
maximum
Aggregate mean daily plus
minimum and maximum
Aggregate mean daily plus
minimum and maximum
Aggregate mean daily plus
minimum and maximum
Aggregate mean daily plus
minimum and maximum
Aggregate flow weighted
daily
Top and bottom of each
reach
Weekly
Hourly
Hourly
Hourly
Top and bottom of each
reach
Hourly
Top and bottom of each
reach
Top and bottom of each
reach
Top and bottom of each
reach
Hourly
Hourly
Hourly
Aggregate mean daily plus
minimum and maximum
Aggregate mean daily plus
minimum and maximum
Aggregate mean daily plus
minimum and maximum
12
IV.3 Remote sensing needs
Streams and wetlands are the vital interface between terrestrial and aquatic habitat, and as such
trends in land use/ land cover in the watershed above each observational point will be a key
explanatory variable for ecological processes, as will more detailed information on riparian
vegetation characteristics. Remote sensing can serve two different purposes relative to our
stream observations. First, observations at observational sites will be influenced by changes in
watershed land use and cover. We propose to use Landsat NLCD data to characterize catchment
cover for each observational site.
Additionally, we posit that riparian vegetation can dictate light availability for aquatic
primary production, provides a key energy source to stream food webs, and will respond to longterm fertilization. Vegetation greenness, LAI, above-ground biomass, and canopy density are
variables of interest that could be sensed remotely. We therefore request a subset of the remote
sensing coverage associated with the “Continental Prime Package” outlined in the document
“Remote Sensing and Spatial Data Acquisition for the NEON Network and Integrated Thematic
Gradient Studies”. Our specific request appears in the Table below. These data are requested for
permanent transects oriented along and upstream of each observational stream reach. In many
cases the watershed remote sensing will also serve for other NEON purposes and has likely been
proposed for terrestrial monitoring of core and gradient sites.
Sensor
Type
Resolution
Spectral
Spatial
Temporal
Spatial
Extent
Landsat5 or
alternative
400-2500nm
5 Bands
30m
1/year
Drainage
Basin
Hyperspectral
Imager
400-3000nm
2m
2
times/growing
season
1km
0.5m
1/year (peak
growth)
1km
No. Bands:
200-350
Full Waveform
Lidar (flown
with VNIR
imager or
camera)
NIR, 1 band
Image
Processing
Level
Most
Important
Variable/Meas.
OrthoGeoregistered
Radiance
Standard products
OrthoGeoregistered
Radiance
Surface
Reflectance
Standard products
NLCD Land Cover
OrthoGeoregistered
Calibrated
Elevation
3-d data cubes
Biomass
LAI
Tree density
3-d land cover
(topography of
ground and canopy)
Aboveground
biomass
Tree density
Leaf area density
Vegetation species
maps
% cover, LAI , fPAR
Land cover classes
Species/community
maps
BGC states
(pigments, water
content, dry plant
matter; soil minerals,
clay, organic matter)
13
IV.4. Additional measurements not currently included in the NEON designs acquired using manual means.
Measurement
Type
Post-Processing
Skill
Level
Stream geomorphology
Isotope natural abundance in
water
Isotope natural abundance in
biomass compartments
Biomass of compartments
In situ
Grab
Data entry
Extensive chemical
Grab
Dry, grind, weight
Field tech
BS
chemistry
Lab tech
Grab
Dry, grind, weight
Lab tech
Dissolved and particulate N, P
and C
Benthic chlorophyll
Grab
Digest, autoanalyze
Grab
Collect and extract
BS
chemistry
Lab tech
Reaeration rates using SF6
tracer gas release
grab
Trace gas flux (diffusive
evasion of CO2, CH4, N2O)
grab
N2 flux (15N tracer studies)
Grab
Nutrient limitation bioassays
In situ
incubation
Leaf decomposition rate
Algae
In situ
incubation
Grab
Extract gas from water, send
to central lab to analyze gas
on GC
Extract gas from water, send
to central lab to analyze gas
on GC
Extract gas from water, send
to central lab to analyze gas
on MIMS
Measure metabolic rates of
substrata, analyze for
chlorophyll
Incubate leaf packs, weigh
before and after
Lab ID
Macroinvertebrates
Grab
Lab ID
Fish
Grab
Field ID and release
Spatial
Distribution
Sampling Frequency
Direct or
Aggregate
All of site
1 sample
Once after every major flood
from daily combined water sample
Direct
Aggregate
Combined across
reach
Combined across
reach
Combined across
reach
Combined across
reach
Combined across
reach
Seasonal (every 4 months)
Direct
Seasonal (every 4 months)
Direct
From daily combined water sample
Aggregate
Monthly plus every 3 days after a
disturbance
Over a range of discharges for each
site, redone after major floods
Direct
Field tech
Combined across
reach
Monthly plus every 3 days after a
disturbance
Direct
Field tech
Combined across
reach
Monthly plus every 3 days after a
disturbance
Direct
Field tech/
lab tech
1 set each reach
Once per site per season
Direct
Field tech
Triplicate each reach
Direct
Field tech/
systematic
expert
Field tech/
systematic
expert
Field tech
Combined across
reach
Every fall using on replicate riparian
leaves and “standard” leaves
Seasonal (every 4 months), and more
frequently after disturbance
Combined across
reach
Seasonal (every 4 months), and more
frequently for secondary production
Direct
Combined across
reach
Seasonal (every 4 months), and more
frequently after disturbance
Direct
Field tech
Aggregate
Direct
14
Budget Estimates for additional measurements
These estimates are for first year costs. We require 60 aquatic sensor units from the ISEP
standard aquatic sensor package for observational sites (2 per site). We have not estimated fringe
benefit rates for any salaries, nor have we estimated overhead rates. We suggest that salaries and
operating costs should increase by 5% per year. The NSF budget pages at the end of this
proposal combine operation and build costs in year 1, and yearly operation costs in the second
page.
One time costs, overhead not included
Item
OI Flowsolution IV Nutrient
autoanalyzer
IC with nutrient regenerator
Millipore SuperQ Water purification
system
Shimadzu TOV-V Combustion
analyzer
SpeX Certiprep 8000 mill
Cahn C-35 microbalance
Metler Toledo analytical balance
Metler Toledo Pan balance
Thelco Precision Drying oven
Thermolyne Muffle furnace
Thermo Electron IRMS Delta V
MS-200 Membrane Inlet Mass
Spectrometer
Varian CP3800 gas chromatograph
Compound microscope/ image
analysis system
Dissecting scope/ image analysis
Dissecting scopes
M11 Ultraclave steam sterilizer
Turner Fluorometer aquaflour
Pipettes
Computers
Site preperation
Power (solar or extensions)
Sampling gear
Innova 2350 shaker table
Use
cost per
#
needed
cost
analyze dissolved nutrients
analyze nitrate and phosphate
70000
45000
1
1
$70,000
$45,000
provide water for nutrient lab
13000
1
$13,000
analyze dissolved carbon
mill solid samples for isotope
analysis
weigh solid samples
Reagent preparation
weigh fertilizer, field samples
for biomass
Process biomass samples
dissolved carbon sampling
gear/ ash free dry mass
Mass spec natural abundance
of dissolved and particulate
materials
Analyze dissolved N2
concentration
analyze dissolved gasses
40000
1
$40,000
6000
16000
3500
1
1
1
$6,000
$16,000
$3,500
2500
2718
29
29
$72,500
$78,822
4000
29
$116,000
2000000
1
$2,000,000
75000
70000
1
1
$75,000
$70,000
25000
1
$25,000
15000
1500
4000
2500
1
5
1
29
$15,000
$7,500
$4,000
$72,500
1000
2500
5000
29
29
29
$29,000
$72,500
$145,000
5000
1000
29
29
$145,000
$29,000
7000
29
$203,000
$3,353,322
15000
29
$435,000
Algal identification
Macroinvertebrate
identification
Macroinvertebrate picking
Digestion
Chlorophyll, rhodamine
calibration standard
preparation
data storage/ download
Site and secure equipment
variable across sites, averaged
here
Nets, seines, corers
dissolved nitrogen isotope
chemistry
Annual costs, upkeep, materials and supplies overhead not
included
materials, supplies, shipping,
upkeep, probe replacement
Individual sites
15
Individual sites
Algal identification facility
Macroinvertebrate facility
Water chemistry facility
Isotope analysis facility
total
travel (to site, to annual
meetings)
materials, supplies, upkeep
materials, supplies, upkeep
materials, supplies, upkeep
materials, supplies, upkeep
Annual personnel needs: note fringe rates not included
Full time, doctoral level
scientist
Project Director
Data managers
full time data managers
Education coordinator
full time
Individual sites
field tech half time
Individual sites
Lab tech half time
Algal identification facility
Taxonomist
Algal identification facility
lab tech
Macroinvertebrate facility
Taxonomist
Macroinvertebrate facility
lab tech
Water chemistry facility
Analyst
Water chemistry facility
lab tech
Isotope analysis facility
Analyst
Isotope analysis facility
lab tech
2000
4000
3000
5000
7000
29
1
1
1
1
$58,000
$4,000
$3,000
$5,000
$7,000
$512,000
70000
50000
40000
15000
15000
40000
30000
40000
30000
40000
30000
50000
30000
1
1
1
29
29
1
1
1
1
1
1
1
1
$70,000
$50,000
$40,000
$435,000
$435,000
$40,000
$30,000
$40,000
$30,000
$40,000
$30,000
$50,000
$30,000
$1,320,000
IV.5. Cyberinfrastructure required
We will require standard database assistance. If individual laboratories are sited away
from NEON, they will need the help of a data manager to set up the laboratories to ensure the
data-stream capture and archiving are appropriate and consistent with NEON protocols. We will
model our cyberinfrastructure and data repositories after NSF’s LTER program in which all data
is summarized and made public in a web-accessible format within 3 years of collection. We will
use EML format for our data.
IV.6 Additional Resources, Administration and Review
The observational network will create vital infrastructure for future experiments that
could examine microbial biodiversity, cycling of minor elements, stoichiometric analyses, effects
of invasive species, efforts to scale to larger watersheds (e.g. by linking to USGS sites or future
CUAHSI sites), and other human stressors on freshwaters. This ecological observatory network
will complement emerging networks of water bodies that focus on physical and chemical
properties (i.e., EPA-WATERS), and existing networks of long-term ecological studies that have
used a variety of methods and site selection protocols (i.e., LTER, USGS hydrologic benchmark
stations). Managing this infrastructure will require substantial planning and an effective
administrative structure. It will also require travel support from NEON to bring together the
administrative team.
We will pattern our administrative and experimental planning after the cross-site LINX I
and LINX II models, which represent a highly successful long-term collaboration among a large
group of stream ecologists. LINX has been a continental-scale effort that has coordinated,
complex experiments entailing whole-ecosystem stable isotope additions to streams. This group
has published numerous papers in high-profile journals. The original LINX I project ran from
16
September 1996 through August 2001 and resulted in 26 publications, 7 theses and dissertations,
and 69 presentations. The LINX II project started in 2001 and generated 14 peer reviewed
publications as of 2005. Thirteen synthetic manuscripts are now being prepared. Our group will
include prior LINX participants, but also expand to include other sites and investigators.
In the first year we will have three, two-day workshops to finalize protocols and plans
and start pre-sampling. At this point we will also establish publication policies. We will meet
annually to review progress of the experiment to assess the possibility of unexpected interactions
resulting from the treatments. This will allow for interpretation of results and possibilities for resiting any experiments or changes in protocols considering that replicates occur across the
continent.
We will establish an executive committee that makes decisions on hiring, and more
importantly on the planning of auxiliary experiments that occur at our sites. This long-term
experiment will provide very strong infrastructure and we anticipate numerous requests to
perform complementary experiments using the extensive background data and manipulations.
We will hire a doctoral-level scientific project coordinator to deal with day-to-day
decisions on scientific direction. The executive committee will oversee the project coordinator.
We will also require laboratory personnel for core analytical facilities, water chemistry, isotope
analyses, algal taxonomy, macroinvertebrate taxonomy.
We have developed this response to RFI in conjunction with Consortium for
Connectivity at Continental Scales. Many of our sites match the location of their sites. We
are addressing key issues of connectivity at continental scales, explicitly how terrestrial systems
connect to aquatic ecosystem as streams are one of the dominant routes of material transport on
all but the most xeric landscapes. The stream sites will monitor watersheds that are of similar
area to the footprints of the proposed terrestrial sensor systems.
We note that a separate response to the RFI proposes a continental-scale network of
instrumented lakes and reservoirs (GLEON). Like streams, lakes and reservoirs are sensitive to
changes in climate, landuse, and biotic structure. We view our proposed network as
complementary to the lake network yet able to examine a different set of questions. Some of the
central laboratory analytical facilities would be similar across the networks, and should both
networks be supported we would expect to combine facilities wherever possible to make
resource use rates the most efficient.
V. Education and Outreach
V.1 Streams are naturally appealing ecosystems for education and outreach. It is our experience
that many K-12 science programs use streams in their environmental education programs. These
programs include stream-teams that are often funded by the state or local conservation
organizations. A number of the scientists involved in this proposal have helped develop such
programs in the past. Stream teams are composed of members of the general public as well as
students. The research proposed here would provide a point of comparison for these local groups
and school programs. We would also attempt to coordinate our network with the EPA Surf your
Watershed outreach initiative.
A number of our proposed sites have NSF Schoolyard LTER projects and we will model
our education/outreach on this program (see http://schoolyard.lternet.edu/). These sites make
heavy use of Internet data sets that can be accessed by students remotely. An example would be
a student who visits one of our observational sites, makes auxiliary measurements, then goes
online to compare the results to similar results from other observational sites. The strength of
17
our observational network is that is dispersed across the continent, affording students the ability
to access local data and to put their data in the context of results obtained from other parts of the
country.
We will require funding for an educational coordinator, presumably housed in the NEON
educational center, to foster interaction with K-12 educators and other sectors of the public. The
educational facilitator will encourage applications of our data in education and outreach and also
help create programs in locations that do not have a schoolyard LTER or comparable effort
(obtaining funding for such programs will be incumbent upon individual sites).
Each of the observational sites will provide valuable infrastructure for individual research
programs. Thus the sites will provide infrastructure for undergraduate (many of our sites are
REU site research areas or have other undergraduate participation programs) and graduate
students. The network will assist the students in meeting scientists from a wide array of sites that
are working on related projects, and provide opportunities for cross site research.
V.2 Most of the institutions involved have programs to stimulate research by underrepresented
groups at graduate and undergraduate levels. The educational coordinator will also help link
these groups across institutions. The educational coordinator will create a web site that has
opportunities for support for students from underrepresented groups across the network. This
will be the first nation-wide network to provide information on research and support for students
interested in stream ecosystems.
18
References
Alexander, R. B., R. A. Smith and G. E. Schwarz. 2000. Effect of stream channel size on the delivery of nitrogen to
the Gulf of Mexico. Nature 403:758-761.
Allan, J. D. and A. S. Flecker. 1993. Biodiversity conservation in running waters. BioScience 43:32-43.
Amarasekare, P, M. F. Hoopes, N. Mouquet and M. Holyoak. 2004. Mechanisms of coexistence in competitive
metacommunities. American Naturalist 164:310-326.
Baron, J. S., et al. Meeting ecological and societal needs for freshwater. 2002. Ecological Applications 12:12471260.
Bernhardt, E. S., et al. 2005. Can't see the forest for the stream? In-stream processing and terrestrial nitrogen
exports. BioScience 55:219-230.
Borer, E. T., B. S. Halpern and E. W. Seabloom. 2006. Asymmetry in community regulation: Effects of predators
and productivity. Ecology 87:2813-2820.
Cardinale, B. J., H. Hillebrand and D. F. Charles. 2006. Geographic patterns of diversity in streams are predicted by
a multivariate model of disturbance and productivity. Journal of Ecology 94:609-618.
Chapin, F. S. I., E. S. Zavaleta, V. T. Eviners, R. L. Naylor, P. M. Vitousek, H. L. Reynolds, D. U. Hooper, S.
Lavorel, O. E. Sala, S. E. Hobbie, M. C. Mack, and S. Diaz. 2000. Consequences of changing biodiversity.
Darracq, A. and G. Destouni. 2005. In-stream nitrogen attenuation: model aggregation effects and implications for
coastal nitrogen impacts. Environmental Science and Technology 39:3716-3722.
Dodds, W. K. 2006. Eutrophication and trophic state in rivers and streams. Limnology and Oceanography 51:671680.
Dodds, W.K., E. Martí, J. L. Tank, J. Pontius, S. K. Hamilton, N. B. Grimm, W. B. Bowden, W. H. McDowell, B. J.
Peterson, H. M. Valett, J. R. Webster, and S. Gregory 2004. Carbon and nitrogen stoichiometry and
nitrogen cycling rates in streams. Oecologia 140:458-467.
Johnson, B. R., J. B. Wallace, A. D. Rosemond and W. F. Cross. 2006. Larval salamander growth responds to
enrichment of a nutrient poor headwater stream. Hydrobiologia DOI 10.1007/s10750-006-0272-3.
Kemp, W. M., et al. 2005. Eutrophication of Chesapeake Bay: historical trends and ecological interactions. Marine
Ecology Progress Series 303: 1-20.
Kneitel, J. M. and J. M. Chase. 2004. Disturbance, predator, and resource interactions alter container community
composition. Ecology 85:2088-2093.
MA. 2003. Millennium Assessment: Ecosystems and Human Well-being: An Assessment Framework.
http://maweb.org/en/index.aspx.
MEA. 2005. The Millennium Ecosystem Assessment, Ecosystems and Human Well-being: Biodiversity Synthesis.
World Resources Institute, Washington D.C.
Meybeck, M. and R. Helmer 1989. The quality of rivers: from pristine stage to global pollution, p. 283-309.
Palaeogeography, Palaeoclimatology, Palaeoecology. Elsevier Science Publishers, B. V.
Palmer, M. A. and E. S. Bernhardt. 2006. Hydroecology and river restoration: ripe for research and synthesis. Water
Resources Research 42: W03S07, 10.1029/2005WR004354.
Peterson, B. J., J. E. Hobbie, A. E. Hershey, M. A. Lock, T. E. Ford, J. R. Vestal, V. L. McKinley, M. A. J. Hullar,
M. C. Miller, R. M. Ventullo and G. S. Volk. 1985. Transformation of a tundra river from heterotrophy to
autotrophy by addition of phosphorus. Science 229:1383-1385.
Peterson, B.J., W. F. Wollheim, P. J. Mulholland, J. R. Webster, J. L. Meyer, J. L. Tank, E. Martí, W. B. Bowden,
H. M. Valett, A. E. Hershey, W. H. McDowell, W. K. Dodds, S. K. Hamilton, S. Gregory, and D. D.
Morrall 2001. Control of nitrogen export from watersheds by headwater streams. Science 292:86-90.
Poff, N. L. 1996. A hydrogeography of unregulated streams in the United States and an examination of scaledependence in some hydrological descriptors. Freshwater Biology 36:71-91.
Poff, N.L., J. D. Allan, M. B. Bain, J. R. Karr, K. L. Prestegaard, B. D. Richter, and R. E. Sparks and J. C.
Strolmberg 1997. The natural flow regime. A paradigm for river conservation and restoration. BioScience
47:769-784.
Poff, L., M. M. Brinson and J. W. Day Jr. 2002. Aquatic Ecosystems and global climate change. Potential impacts
on inland freshwater and coastal wetland ecosystems in the United States. Prepared for the Pew Center on
Global Climate Change 44 pp.
Postel, S. L., G. C. Daily, and P. R. Ehrlich. 1996. Human appropriation of renewable fresh water. Science 271:785788.
19
Ricciardi, A. and J. B. Rasmussen. 1999. Extinction rates of North American freshwater fauna. Conservation
Biology 13:1220–1222.
Sala, O. E., F. S. Chapin, J. J. Armesto, E. Berlow, J. Bloomfield, R. Dirzo, E. Huber-Sanwald, L. F. Huenneke, R.
B. Jackson, A. Kinzig, R. Leemans, D. M. Lodge, H. A. Mooney, M. Oesterheld, N. L. Poff, M. T. Sykes,
B. H. Walker, M. Walker, and D. H. Wall. 2000. Global biodiversity scenarios for the year 2100. Science
287:1770-1774.
Slavik, K., B. J. Peterson, L. A. Deegan, W. B. Bowden, A. E. Hershey, and J. E. Hobbie.2004. Long-term
responses of the Kuparuk River ecosystem to phosphorus fertilization. Ecology 85:939-954.
Swan, C. M. and M. A. Palmer. 2006. Preferential feeding by an aquatic consumer mediates non-additive
decomposition of speciose leaf litter. Oecologia. 149:online first.
Tilman, D. 1999. The ecological consequences of changes in biodiversity: a search for general principles. Ecology
80:1455-1474.
Wilson, S. D. and D. Tilman. 1993. Plant competition and resource availability in response to disturbance and
fertilization. Ecology 74:599-611.
Wollheim, W. M., C. J. Vörömarty, B. J. Peterson, S. P. Seitzinger and C. S. Hopkinson. 2006. Relationship
between river size and nutrient removal. Geophysical Research Letters 33:L06140-06144.
Zachos, J., M. Pagani, L. Sloan, E. Thomas, and K. Billups. 2001. Trends, rhythms, and aberrations in global
climate 65 Ma to present. Science 292:686-693.
20
FOR NSF USE ONLY
54
Year 1 Build and operating SUMMARY BUDGET
ORGANIZATION
PROPOSAL NO.
DURATION (MONTHS)
STREON Stream Observational Network
Proposed
AWARD NO.
NSF-Funded
PRINCIPAL INVESTIGATOR/PROJECT DIRECTOR Walter Dodds
A. SENIOR PERSONNEL: PI/PD, Co-PIs, Faculty and Other Senior Associates
List each separately with name and title. (A.7. Show number in brackets)
Person-months
CAL ACAD SUMR
1. Program coordinator
12
2.
3.
4.
5.
6. (
) OTHERS (LIST INDIVIDUALLY ON BUDGET EXPLANATION PAGE)
7. (
) TOTAL SENIOR PERSONNEL (1-6)
B. OTHER PERSONNEL (SHOW NUMBERS IN BRACKETS)
1. (
) POSTDOCTORAL ASSOCIATES
2. (40) OTHER PROFESSIONALS (TECHNICIAN, PROGRAMMER, ETC.)
12
3. (
) GRADUATE STUDENTS
4. (
) UNDERGRADUATE STUDENTS
5. (
) SECRETARIAL - CLERICAL (IF CHARGED DIRECTLY)
6. (
) OTHER
TOTAL SALARIES AND WAGES (A + B)
C. FRINGE BENEFITS (IF CHARGED AS DIRECT COSTS) assume 35%
TOTAL SALARIES, WAGES AND FRINGE BENEFITS (A + B + C)
D. EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR EACH ITEM EXCEEDING $5,000.)
Granted
Funds
Funds
Requested By
Granted by NSF
Proposer
(If Different)
$70000
$
1280000
1350000
472500
1825000
Detail in response, does not include sensor packages or biodiversity sampling
TOTAL EQUIPMENT
E. TRAVEL
1. DOMESTIC (INCL. CANADA, MEXICO AND U.S. POSSESSIONS)
2. FOREIGN
F. PARTICIPANT SUPPORT
1. STIPENDS
$
2. TRAVEL
3. SUBSISTENCE
4. OTHER
TOTAL NUMBER OF PARTICIPANTS (
)
G. OTHER DIRECT COSTS
1. MATERIALS AND SUPPLIES
2. PUBLICATION/DOCUMENTATION/DISSEMINATION
3. CONSULTANT SERVICES
4. COMPUTER SERVICES
5. SUBAWARDS
3158000
60000
TOTAL PARTICIPANT COSTS
1302322
6. OTHER
TOTAL OTHER DIRECT COSTS
H. TOTAL DIRECT COSTS (A THROUGH G)
I. INDIRECT COSTS (F&A) (SPECIFY RATE AND BASE)
6342822
unknown
TOTAL INDIRECT COSTS (F&A)
J. TOTAL DIRECT AND INDIRECT COSTS (H + I)
K. RESIDUAL FUNDS (IF FOR FURTHER SUPPORT OF CURRENT PROJECT SEE GPG II.D.7.j.)
L. AMOUNT OF THIS REQUEST (J) OR (J MINUS K)
$
$
M. COST SHARING: PROPOSED LEVEL $
PI/PD TYPED NAME AND SIGNATURE*
AGREED LEVEL IF DIFFERENT: $
DATE
FOR NSF USE ONLY
ORG. REP. TYPED NAME & SIGNATURE*
DATE
NSF Form 1030 (10/99) Supersedes All Previous Editions
*SIGNATURES REQUIRED ONLY FOR REVISED BUDGET (GPG III.C)
INDIRECT COST RATE VERIFICATION
Date Checked Date of Rate Sheet
Initials-ORG
FOR NSF USE ONLY
54
Annual costs SUMMARY PROPOSAL BUDGET
ORGANIZATION
PROPOSAL NO.
DURATION (MONTHS)
STREON Stream Observational Network
Proposed
PRINCIPAL INVESTIGATOR/PROJECT DIRECTOR
Granted
AWARD NO.
Walter Dodds
A. SENIOR PERSONNEL: PI/PD, Co-PIs, Faculty and Other Senior Associates
NSF-Funded
List each separately with name and title. (A.7. Show number in brackets)
Person-months
CAL ACAD SUMR
1. Program coordinator
12
2.
3.
4.
5.
6. (
) OTHERS (LIST INDIVIDUALLY ON BUDGET EXPLANATION PAGE)
7. (
) TOTAL SENIOR PERSONNEL (1-6)
B. OTHER PERSONNEL (SHOW NUMBERS IN BRACKETS)
1. (
) POSTDOCTORAL ASSOCIATES
2. (40) OTHER PROFESSIONALS (TECHNICIAN, PROGRAMMER, ETC.)
12
3. (
) GRADUATE STUDENTS
4. (
) UNDERGRADUATE STUDENTS
5. (
) SECRETARIAL - CLERICAL (IF CHARGED DIRECTLY)
6. (
) OTHER
TOTAL SALARIES AND WAGES (A + B)
C. FRINGE BENEFITS (IF CHARGED AS DIRECT COSTS) assume 35%
TOTAL SALARIES, WAGES AND FRINGE BENEFITS (A + B + C)
D. EQUIPMENT (LIST ITEM AND DOLLAR AMOUNT FOR EACH ITEM EXCEEDING $5,000.)
Funds
Funds
Requested By
Granted by NSF
Proposer
(If Different)
$70000
$
1280000
1350000
472500
1822500
Detail in response, does not include sensor packages or biodiversity sampling
TOTAL EQUIPMENT
E. TRAVEL
1. DOMESTIC (INCL. CANADA, MEXICO AND U.S. POSSESSIONS)
2. FOREIGN
F. PARTICIPANT SUPPORT
1. STIPENDS
$
2. TRAVEL
3. SUBSISTENCE
4. OTHER
TOTAL NUMBER OF PARTICIPANTS (
)
G. OTHER DIRECT COSTS
1. MATERIALS AND SUPPLIES
2. PUBLICATION/DOCUMENTATION/DISSEMINATION
3. CONSULTANT SERVICES
4. COMPUTER SERVICES
5. SUBAWARDS
60000
TOTAL PARTICIPANT COSTS
469000
6. OTHER
TOTAL OTHER DIRECT COSTS
H. TOTAL DIRECT COSTS (A THROUGH G)
I. INDIRECT COSTS (F&A) (SPECIFY RATE AND BASE)
23515000
unknown
TOTAL INDIRECT COSTS (F&A)
J. TOTAL DIRECT AND INDIRECT COSTS (H + I)
K. RESIDUAL FUNDS (IF FOR FURTHER SUPPORT OF CURRENT PROJECT SEE GPG II.D.7.j.)
L. AMOUNT OF THIS REQUEST (J) OR (J MINUS K)
$
$
M. COST SHARING: PROPOSED LEVEL $
PI/PD TYPED NAME AND SIGNATURE*
AGREED LEVEL IF DIFFERENT: $
DATE
FOR NSF USE ONLY
ORG. REP. TYPED NAME & SIGNATURE*
DATE
NSF Form 1030 (10/99) Supersedes All Previous Editions
*SIGNATURES REQUIRED ONLY FOR REVISED BUDGET (GPG III.C)
INDIRECT COST RATE VERIFICATION
Date Checked Date of Rate Sheet
Initials-ORG