Update on Development of a
National Phenology Network
for the U.S.A.
Julio L. Betancourt, USGS & U. Arizona
Mark D. Schwartz, UW-Milwaukee
& the NPN Implementation Team
http://www.uwm.edu/Dept/Geography/npn/
MTNCLIM
2006
Mt. Hood, OR
USA-NPN Implementation Team
Baenziger, P. Stephen
Betancourt, Julio
Breshears, David
Brewer, Carol
Cayan, Dan
Cecil, L. DeWayne
Crawford, Ken
Crow, Tom
Dettinger, Mike
Easterling, William
Frazer, Gary
Gross, John
Inouye, David
Jones, Bruce
Law, Bev
LeDuc, Sharon
Mazer, Susan
Morisette, Jeffrey
Pielke, Roger
Post, Eric
Reed, Bradley
Schwartz, Mark
Sheffner, Ed
Turner, Woody
Van Vliet, Arnold
Waide, Jack
Waide, Robert
Wolfe, David
University of Nebraska, High Plains Phenology Initiative
USGS
University of Arizona
University of Montana
Scripps Institution of Oceanography/USGS
USGS (currently on IPA at NASA)
NOAA
USDA Forest Service
USGS/Scripps Institution of Oceanography
Penn State University
US Fish & Wildlife Service
National Park Service
University of Maryland
USGS
AmeriFlux/Oregon State University
NOAA
University of California, Santa Barbara
NASA
Colorado State University
Penn State University
USGS
University of Wisconsin-Milwaukee
NASA
NASA
Wageningen Univ., European Phenology Network
USGS
LTER Network/University of New Mexico
Cornell University
http//www.neoninc.org
Convened by
Julio Betancourt
Pat Mulholland
Dave Breshears
James S. Clark, Duke University
Clifford M. Dahm, Univ. New Mexico
Christopher B. Field, Stanford Univ.
Catherine A. Gehring, N. Arizona Univ.
Paul J. Hanson, Oak Ridge Natl. Lab.
John Harte, Univ. California, Berkeley
Bruce P. Hayden, Univ. of Virginia
Alfredo R. Huete, Univ. of Arizona
Travis E. Huxman, Univ. of Arizona
Stephen T. Jackson, Univ. of Wyoming
Linda A. Joyce, U.S. Forest Service
Alan K. Knapp, Colorado State Univ.
W. Arthur McKee, Univ. of Montana
Steven J. McNulty, U.S. Forest Service
James A. MacMahon, Utah State Univ.
John M. Melack, Univ. Calif-SB
Barbara J. Morehouse, Univ. of Arizona
Richard J. Norby, Oak Ridge Natl Lab.
Dennis J. Ojima, Colorado State Univ.
Jonathan T. Overpeck, Univ. of Arizona
Debra P. Peters, USDA ARS, Jornada
N. LeRoy Poff, Colorado State Univ.
Eric Post, Penn State University.
Hank J. Shugart, Univ. of Virginia
Stanley D. Smith, Univ. Nevada-LV
Robert G. Striegl, USGS
Thomas W. Swetnam, Univ. of Arizona
Susan L. Ustin, Univ. California-Davis
Thomas G. Whitham, N. Arizona Univ.
Xubin Zeng, University of Arizona
Recommendations from NEON Climate Workshop
•Establish a National Phenology Network that includes
public observers and leverages existing ecological networks
•Explore integration of NPN w/ Coop Network (NERON)
•develop a working group that includes phenology & remote
sensing experts
– a continental-scale network for regionally appropriate
native plant species & cloned indicator plants (e.g., lilac)
– thorough understanding of phenological cycles &
relationship to climate, hydrology, ecosystem processes
– comprehensive ground-truthing of green-up & other
remotely sensed phenology
– detect & discriminate long-term phenological trends
in response to long-term climate variability & global
warming
N
E
PH
GY
LO
O
Study of the timing of recurring
biological phases, the causes of their
timing with regard to biotic and abiotic
forces, and the interrelation among
phases of same or different species
Phenophase-- budbreak, unfolding of
first leaf, flowering, fruiting,
turning of leaves, animal migration,
emergence, growth stages, breeding,
nesting, hibernation, etc.
I. Why phenology is
important
PREAMBLE: Phenology is a far-reaching component of
environmental science but is poorly understood. Critical
questions include how environmental factors affect the
phenology of different organisms, and how those
factors vary in importance on different spatial and
temporal scales. We need to know how phenology
affects the abundance and diversity of organisms, their
function and interactions in the environment, especially
their effects on fluxes in water, energy, and chemical
elements at various scales. With sufficient
observations and understanding, phenology can be used
as a predictor for other processes and variables of
importance at local to global scales, and could drive a
variety of ecological forecast models with both
scientific and practical applications.
USA-NPN Implementation Team 4/16/06
PHENOFIT: A process-based tree distribution model
What you need to know to run model:
phenology: budburst, flowering, fruit
maturation, leaf coloring
frost hardiness: minimum temperature
sustained during active growth and
dormancy
drought tolerance
90°0'0"O
80°0'0"O
70°0'0"O
60°0'0"O
90°0'0"O
80°0'0"O
70°0'0"O
60°0'0"O
3 6 °0 '0 "N
2 6 °0 '0 "N
Populus
Tremuloides-
Quaking aspen
170°0'0"O 160°0'0"O 150°0'0"O 140°0'0"O 130°0'0"O 120°0'0"O 110°0'0"O 100°0'0"O
1 6 °0 '0 "N
1 6 °0 '0 "N
2 6 °0 '0 "N
3 6 °0 '0 "N
4 6 °0 '0 "N
4 6 °0 '0 "N
5 6 °0 '0 "N
5 6 °0 '0 "N
6 6 °0 '0 "N
6 6 °0 '0 "N
170°0'0"O 160°0'0"O 150°0'0"O 140°0'0"O 130°0'0"O 120°0'0"O 110°0'0"O 100°0'0"O
Morine and Chuine (2005) Global Change Biology
Phenology influences
distribution, abundance &
diversity of organisms, as well
as their interactions
Rocky Mtn. Biol. Laboratory
Mertensia
virginica (bluebell)
Milbert’s
tortoishell
First sighting to first Mertensia flower (days)
Courtesy of David Inouye
Nymphalis milberti
60
Emergence is
changing relative to
flowering
50
40
30
r2 = .192, p = .03
20
1980
1985
1990
1995
2000
2005
Years-To-Centuries
Aerodynamics
Energy
Water
Climate
Temperature, Precipitation,
Radiation, Humidity, Wind
Heat
Moisture
Momentum
Biogeophysics
Evaporation
Transpiration
Snow Melt
Infiltration
Runoff
Intercepted
Water
Snow
Chemistry
CO2, CH4, N2O
ozone, aerosols
CO2 CH4
N2O VOCs
Dust
Biogeochemistry
Carbon Assimilation
Microclimate
Canopy Physiology
Hydrology
Soil
Water
Days-To-Weeks
Minutes-To-Hours
Phenology is an essential component of the biosphere
Decomposition
Mineralization
Phenology
Bud Break
Leaf Senescence
Species Composition
Ecosystem Structure
Nutrient Availability
Water
Watersheds
Surface Water
Subsurface Water
Geomorphology
Hydrologic
Cycle
GPP, Plant &
Microbial
Respiration
Nutrient
Availability
Ecosystems
Species Composition
Disturbance
Fires
Ecosystem Structure
Hurricanes
Vegetation
Ice Storms
Dynamics
Windthrows
Bonan (2002) Ecological Climatology: Concepts and Applications. Cambridge University Press
II. Other Phenology Networks
Elisabeth Beaubien
Plantwatch National Coordinator
University of Alberta, Edmonton
www.naturewatch.ca
ns
e
z
i
it
c
om e!
r
f
on
ns
l
o
a
i
t
a
5
v
0
r
0
e
2
s
b
g
o
n
i
0
pr
0
s
0
,
n
157 n U K i
i
http://www.phenology.org.uk
III. History of Phenological
Monitoring in U.S.A &
Examples of Applications
Hu, Q., Weiss, A., Feng, S., &
Baenziger, P.S. (2006) Early
winter wheat heading dates and
warmer springs in the U.S. Great
Plains. Agricultural and Forest
Meteorology 135:284.
1946
Heading date: when head
(spike) on 50% of the
Kharkof cultivar emerges
from the flag leaf.
HISTORY OF WESTERN REGIONAL
PHENOLOGY NETWORK
By
Joseph M.
Caprio
• Joe Caprio Agricultural
Climatologist at Montana State
Univ., Bozeman beginning in 1955
• Started lilac network in 1956;
added honeysuckles in 1968
• Climatological observers, agric.
& forest stations, garden clubs
• Grew from 1000 observers in 11
states in 1956 to 2500 observers
in 12 states by 1970
• WRPN terminated when Caprio
retired in 1994
• Eastern US Network started by
W.L. Coville 1961, lost funding
1986, but continued since by
Mark Schwartz
• Dan Cayan & Mike Dettinger
contacted Caprio in late 1990’s &
reactivated network at two dozen
sites
•Cayan et al. (2001) BAMS
Lilac West Meets Lilac East: Joe Caprio and Mark
Schwartz meet for first time at 1st Planning
Workshop, August 24-26, 2005, Tucson, AZ
Spring index based on first leaf date for lilacs
Syringa vulgaris
(common lilac)
Syringa chinensis
(cloned lilac)
Schwartz and Reiter 2000
International. J. Climatology
First Leaf = widest part of green
leaf past brown winter bud tips)
Spring index based on first leaf date for lilacs
Syringa vulgaris
(common lilac)
Syringa chinensis
(cloned lilac)
Schwartz and Reiter 2000
International. J. Climatology
Mean length of historical (1950-1999)
growing season, defined as the longest
interval in a given year with no daily
mean temp. in 3-day periods < 5ºC
0
91 182 273 366
Days per year
Different sensitivities with uniform
3ºC warming, probably due to relative
importance of advective vs. radiative
freezing
0
15
30
60
Days longer
90
Historical data from Variable Infiltration Capacity
model input fields (Maurer et al., 2002 )
Courtesy of Mike Dettinger, USGS
V. Monitoring Structure
of USA-NPN
The predictive potential of phenological phenomena
requires a new data resource- a national network of
integrated phenological observations and the tools to
analyze them at multiple scales. This network is
essential to evaluate ongoing environmental changes.
It can now capitalize on integration with other
observation networks and remote sensing products,
emerging technologies and data management
capabilities, myriad educational opportunities, and a
new readiness of the public to participate in
investigations of nature on a national scale.
USA-NPN Implementation Team 4/16/06
USA-NPN Vision Statement
USA-NPN will provide phenological information that
can be used to understand the role of the
timing of life cycle events in the biosphere. It will
establish a nationwide network of phenological
observations with simple and effective means to
input, report, and utilize these observations,
including the resources to provide the right
information at the right time for a wide range of
decisions made routinely by individual citizens and by
the Nation as a whole.
USA-NPN Implementation Team 4/16/06
AmeriFlux, AgriFlux
NSF LTER, NEON
USGS WEBB
Intensive
USDA FS Exp. F & R
Sites
Spatially Extensive
Science Networks
NWS Coop
NPS Inv. & Mon.
USDA FIA
State Ag. Exp. Sta.
GLOBE
Garden clubs
Spatially Extensive
Nat. Plant Soc.
Volunteer & Education Networks
Campuses
Remote Sensing and
Synoptic (wall-to-wall) Data
NASA
USGS
NOAA
Increasing Process Knowledge
Data Quality
# of Measurements
Decreasing Spatial Coverage
USA-NPN Monitoring Framework
Long-Term
Ecological
Research
LTER
Network
USDA FS
Experimental
Forest & Range
Stations
AmeriFlux: Goal is to characterize processes by which
ecosystems exchange CO2, water and energy with atmosphere
115 active sites
7 countries
50 research teams
Disturbance/
Climatic/Vegetation
gradients
NPN Tier 1: Example of Intensive Sites
Colocation with NWS
Cooperative Observer
Program (COOP)
Tier 2: Example
of Spatially
Extensive
Science Network
Priority for Modernization of NOAA HCN sites
~1000 stations/20 per state 2008-2013
3
2
4
8
9
6
1
5
Alaska – Priority 2
Hawaii – Priority 3
7
National Park Service
Inventory & Monitoring
Tier 2: Example
of Spatially
Extensive
Science Network
http://www.obfs.org/
~180 stations
Tier 2: Example
of Spatially
Extensive
Science Network
http://tiee.ecoed.net/
Community Colleges in the United States
Tier 3: Example
Of Volunteer &
Education
Networks
Tier 3: Example
Of Volunteer &
Education
Networks
Tier 3: Example
Of Volunteer &
Education
Networks
http://www.uwm.edu/Dept/Geography/npn/
http://www.uwm.edu/Dept/Geography/npn/
Want to track global warming in your own
backyard?
Tuesday, May 30, 2006
A program funded in part by the National
Science Foundation is recruiting citizen
scientists to note when lilacs, honeysuckles and
other plants first leaf out and bloom.
The data will help scientists track the arrival of
spring, which since 1955 is coming about six
days earlier in the Northern Hemisphere, says
Mark Schwartz, a climatologist at the
University of Wisconsin-Milwaukee.
Coordinated by Schwartz and Julio Betancourt,
a senior scientist with the U.S. Geological
Survey, the program aims to build a network of
observers to track changes in how plants
respond to the weather. Several universities
and federal agencies also are participating, as
are elementary and high school students across
the country.
Lilacs know what day it is
To find out more, check the home page of the
National Phenology Network.
NPN-Tier 4: REMOTE SENSING can fill gaps between
ground observations to produce a continuous surface of
phenology estimates at the continental scale
Land surface phenology metrics, based on
time-series Vegetation Index
Start of season
End of season
Duration of season
Peak season
Seasonally integrated vegetation
index
Satellite SOS vs. GPP estimates (USDA-AgriFlux)
30
25
20
16
0.8
0.7
14
0.7
0.6
12
0.8
+5
0.5
10
0.4
0.3
15
0.2
10
0.1
GPP avPg
8
0.6
-10
0.5
0.4
0.3
NDVI
6
0.2
4
0.1
0
5
2
0
0
-0.1
-0.2
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
0
1999
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
-0.1
Mandan, ND
2000
GPP avPg
NDVI
Days offset
n = 13
x = 2.23
std = 8.21
Remote Sensing
Objectives
Of USA-NPN
•
provide ground truth to
make the most of the
public investment in
remote sensing data
•
relate remote sensing
estimates to meaningful
biophysical attributes
•
allow detailed
biophysical inputs into a
variety of models (move
from on/off parameters
to nuanced values)
• facilitate thorough
understanding of
phenological phenomena,
including causes and
effects
Two levels of satellite data sets:
(1) Intensive data collection to support research in
technique development
- correspond to USA-NPN intensive sites
- cooperative with CEOS WGCV
- will follow WGCV protocols
- subset of high frequency MODIS data and higher
resolution data
- moderate resolution (Landsat and SPOT)
- high resolution (IKONOS, QuickBird) for
site characterization and scaling studies
(2) Wall-to-wall data collection
-MODIS observations = “backbone” of NPN
-MODIS Direct Broadcast antenna (DBS) at EROS
permits control of processing for USGS-related
applications (e.g., compositing schedule, lag-time, etc.)
Milestones for USA-NPN
8/24-25/2005
1st NPN Planning Workshop, Tucson funded
by NSF, USGS, NPS, FS, & EPA
3/22-24/2006
6/12/2006
NPN Implementation Team meeting
8/15/2006
USGS Bureau Planning Council approves
Presentation USGS Exec. Leadership Team
$275K/yr for Natl. Coordinating Office
9/1/2006
9/8/2006
Univ. of AZ offers free space + Asst. Dir.
USGS approves plan to locate Natl. Office
at Univ. of Arizona
10/1/2006
10/9-13/2006
USGS advertises Exec. Direction position
2nd NPN Planning Workshop, Milwaukee
funded by NSF, USGS, FWS & NASA
Fall/2006
1/01/2007
NSF RCN grant $500K/5 yrs hopefully funded
National Coordinating Office staffed and
located in Tucson
Spring 2007
First set of observations nationwide
Goals of the National Coordinating Office, USA-NPN
Ensure NPN responds to needs of USGS &
other federal agencies
Develop, coordinate and advocate
phenological research
Serve as nucleus for research &
applications in broader scientific and user
communities
Secure funding for network implementation
Extend phenological observations across existing environmental
networks through negotiation and interagency agreements
Direct data management & dissemination
Coordinate integration of spatial, analytical and climate data to achieve
the wall-to-wall objectives of this continental network
Promote Citizen Science and formal & informal science education
Advisory Board
Data Management
(website, database
design, standard
reports)
NPN Office
Exec. Director & Assoc. Director
Science
Communications
Data quality assessment
Politicians, media,
NGOs
Track discoveries
Identify new questions
Outreach & Training
for data collection
Informal science
education and public
education institutions
Scientific and Societal Benefits & Users
Agriculture
Farmers
timing of mgt.
Ativities, e.g.,
planting,
harvesting,
pollination),
drought
monitoring,
range mgt.,
harvest
projection,
pest &
disease
control
Cooperative
Extension
Research
Effects of
climate var. &
change,
ecological
synchrony,
biogeochemical
cycling,
remote sensing
conservation
biology,
Academic &
Agency
Researchers
Educators
Human health
Public
Health workers &
commercial
diagnosticians
Disease projection
(Hanta virus,
WNV, Avian flu,
Lyme disease,
Equine
encephalitis)
Allergy prediction
Gardeners
(plan planting
dates and pest
control)
Air quality &
Pollen monitors
Allergy sufferers
Travelers
(allergy planning)
Tourists
Timing of
wildflowers, fall
colors, bird
migrations
Resource
management
Land managers
Fire managers
Identify habitats or
locations sensitive
to climate change;
project primary
productivity
Invasive spp. mgt.
Watershed mgt.
Other
observational
networks
LTER, NWS
COOP, NPS I &
M, FS R & E
Ameriflux,
Agriflux
Cornell Bird
Lab, Breed.
Bird Survey,
Frogwatch,
Hummingbird
watch, Journey
North
Talking points for CIRMOUNT-MTNCLIM 2006
• NPN seeks institutional partners & individual volunteers in West
•Revitalize Western States Phenological Network, this time focused on
lilac/honeysuckle + native + non-native species
• Criteria for selection and siting of NPN observations for westernmountains regions?
• list of target species & protocols from CIRMOUNT perspective.
• NPN is working with NOAA and NWS to integrate phenological
observations in data entry system WXCoder III. What about MONET?
• Finally, what can NPN do for CIRMOUNT in terms of monitoring,
research, & applications of phenology, or for organizational support?
• eg., Srategic location of phenological monitoring for calibrating treering chronologies, particularly near upper treeline.