Transcript Mark D. Schwartz "Integrating Phenological Measurements into

Integrating Phenological
Measurements
into
Climate Monitoring
USA-NPN 2006
Definition of Phenology

Phenology which is derived from the Greek word
phaino meaning to show or to appear, is the study of
periodic plant and animal life cycle events that are
influenced by environmental changes, especially
seasonal variations in temperature and precipitation
driven by weather and climate. Thus, timings of
phenological events are ideal indicators of global
change impacts.

Seasonality is a related term, referring to similar nonbiological events, such as timing of the fall formation and
spring break-up of ice on fresh water lakes.
USA-NPN 2006
Examples of Phenology
 Sprouting,
leafing, and flowering of
plants in spring
 Leaf color change in autumn
 Bird migration and nesting
 Insect hatches
 Animal emergence from hibernation
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Lilac First Leaf
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Lilac First Bloom
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History of Phenology
Ancient and traditional uses related to
agriculture, due to the connection of
changes in the local environment to plant
development.
 Specific events can serve as “indicators” to
guide other activities. This can be useful for
garden planting in the spring, especially for
early season crops, or if some early planting
risk is needed to ensure success.

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New Uses of Phenology
Global Change Science—phenological
observations serve as an independent
measure of the effect of climate change on
biological organisms.
 Ecosystem linkages—phenological
observations at different levels of the food
chain (plant growth, insect hatching, bird
feeding/nesting) can shed light on “ripple
effects” of climate change.

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Critical Research Areas
Atmosphere-Biosphere
Interactions
Long-term Organism
response to Climate Change
Global Phenology Databases
for monitoring and
management
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Climate
Temperature, Precipitation,
Radiation, Humidity, Wind
Chemistry
CO2, CH4, N2O
ozone, aerosols
CO2 CH4
N2O VOCs
Dust
Biogeochemistry
Carbon Assimilation
Aerodynamics
Energy
Water
Heat
Moisture
Momentum
Biogeophysics
Evaporation
Transpiration
Snow Melt
Infiltration
Runoff
Phenology
Intercepted
Water
Snow
Decomposition
Mineralization
Microclimate
Canopy Physiology
Hydrology
Soil
Water
Years-To-Centuries Days-To-Weeks
Minutes-To-Hours
Phenology is an essential component of the biosphere
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
Ecosystem Structure
Vegetation
Dynamics
Disturbance
Fires
Hurricanes
Ice Storms
Windthrows
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Bonan (2002) Ecological Climatology: Concepts and Applications. Cambridge University Press
Global Change Influences & is Influenced by Phenology
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Global Phenological Monitoring
Issues: Few Networks, Multiple Standards, and Little Coordination
 Europe
 Asia
 North
America
 Southern Hemisphere
 Role of ISB Phenology Commission
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Jill Attenborough, Woodland Trust
http://www.phenology.org.uk
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Elisabeth Beaubien
Plantwatch National Coordinator
University of Alberta, Edmonton
www.naturewatch.ca
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Example Benefits of Phenological Research/Data
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Example Phenological
Applications
(emphasizing advantages
of co-location/coordination
with climate data)
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Integrated Approach
(to Data Collection)
Satellite
Observations
(MODIS-NDVI/EVI in USA)
Indicator Species Phenology
Native Species Phenology
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Cloned lilac first leaf and first bloom dates
at a single station in Vermont
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Spring indices based on first leaf date for lilacs
Syringa vulgaris
(common lilac)
Syringa chinensis
(cloned lilac)
Schwartz and Reiter 2000
International. J. Climatology
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Spring Index based on Simulated First Leaf Date: Slope from 1961-2000
Schwartz et al.
2006 Global
Change Biology
Spring Index based on Damage Index Value (First Leaf – Last Frost)
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Integrated Species Indices (ISI)
southwestern Wisconsin
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Diurnal Range Change with Lilac First Leaf
15.5
14.5
Snow Date
Mean = -27.9
s.e. = 1.6
+
Diurnal Range (°C)
13.5
12.5
11.5
10.5
Freeze Date
Mean = +12.5
s.e. = 0.9
+
9.5
8.5
7.5
-56
-42
-28
-14
0
14
Days After First Leaf Date
Source: Schwartz 1996, Figure 3
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28
42
56
Comparative Net Ecosystem Exchange
6
4
Mean Daily NEE (umol/m2/s)
2
0
-2
-4
-6
-8
-10
-12
Park Falls, WI
-14
M-Monroe, IN
H. Forest, MA
Oak Ridge, TN
-16
-18
-70
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-56
-42 -28 -14
0
14
28
42
Days after Spring Index First Bloom
56
70
Spring Phenology Campaign 2006

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Spatially: 3/7 cyclic sampling; 25m unit distance;
300m×600m Area; 216 trees
Start-of-Season Comparisons
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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
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Heading date: when head (spike)
on 50% of the Kharkof cultivar
emerges from the flag leaf.
Phenology can help in detecting/anticipating climate
change effects on the synchrony between organisms
Plants and pollinators
90
80
70
60
50
Host
40
Parasite
30
20
10
0
1
3
5
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Natural enemies of
insect pests
Changes in Wildfire and the Timing of Spring in Western US Forests
A.L. Westerling, H.G. Hidalgo, D.R. Cayan, T.W. Swetnam. Science (in press)
Correlation between large (>
400 ha) forest wildfire
frequency & streamflow
center timing.
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Forest wildfire frequency for
early, mid and late tercile
timing of spring since 1970.
Fire Vulnerability
associated with earlier
spring onset.
Vulnerability = % change
moisture deficit with
delayed spring onset,
scaled by fraction of forest
area
Vision of a USA National
Phenology Network (NPN)
a
continental-scale network observing
regionally appropriate native plant species,
cloned indicator plants (lilac +?), and
selected agricultural crops
 designed to complement remote sensing
observations
 data collected will be freely available to the
research community and general public
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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
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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
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Intensive
Sites
AmeriFlux, AgriFlux
NSF LTER, NEON
USGS WEBB
USDA FS Exp. F & R
Spatially Extensive
Science Networks
Increasing Process Knowledge
Data Quality
# of Measurements
Decreasing Spatial Coverage
USA-NPN Monitoring Framework
NWS Coop
NPS Inv. & Mon.
USDA FIA
State Ag. Exp. Sta.
Spatially Extensive
Volunteer & Education Networks
Remote Sensing and
Synoptic (wall-to-wall) Data
GLOBE
Garden clubs
Nat. Plant Soc.
Campuses
NASA
USGS
NOAA
Colocation with NWS
Cooperative Observer
Program (COOP)
Tier 2: Example of
Spatially Extensive
Science Network
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Tier 3: Example
Of Volunteer &
Education
Networks
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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
15
0.3
0.2
GPP avPg
8
0.6
-10
0.5
0.4
0.3
NDVI
6
0.2
10
0.1
4
0.1
0
5
2
0
0
-0.1
1
2
3
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-0.2
1999
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-0.1
0
Mandan, ND
2000
GPP avPg
NDVI
Days offset
n = 13
x = 2.23
std = 8.21
http://www.uwm.edu/Dept/Geography/npn/
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Milestones for USA-NPN
8/24-25/2005
3/22-24/2006
6/12/2006
8/15/2006
9/1/2006
9/8/2006
10/1/2006
10/9-13/2006
Fall/2006
1/01/2007
Spring 2007
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1st NPN Planning Workshop, Tucson funded
by NSF, USGS, NPS, FS, & EPA
NPN Implementation Team meeting
Presentation USGS Exec. Leadership Team
USGS Bureau Planning Council approves
$275K/yr for Natl. Coordinating Office
Univ. of AZ offers free space + Asst. Dir.
USGS approves plan to locate Natl. Office
at Univ. of Arizona
USGS advertises Exec. Direction position
2nd NPN Planning Workshop, Milwaukee
funded by NSF, USGS, FWS & NASA
NSF RCN grant $500K/5 yrs hopefully funded
National Coordinating Office staffed and located in Tucson
First set of observations nationwide
Global Phenological Monitoring:
Implementation Challenges
 Development of Protocols—in good shape thanks to
BBCH standardization
 Species selection/coordination—careful study and
implementation using a nested approach
 Data
sharing agreements—non-trivial issue
 Site Colocation and Integration Issues—being
addressed by COST 725 action in Europe, different challenges
in other regions
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Recommendations
 Draw
from NPN and EPN/COST experience as
templates for starting phenology networks in
other places
 Consider funding a study of how to best
establish phenology networks, accounting for
existing environmental networks and potential
for volunteer observers (best by country or
continent?)
 First step could be promotion of phenological
observations by national weather networks
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