Diversity and abundance of terrestrial mammals in the northern periphery of ...
Huete Training Phenology Kku
1. Satellite Phenology
GY
Study of the timing of recurring
biological phases, the causes of their
LO timing with regard to biotic and abiotic
O
EN
forces, and the interrelation among
phases of same or different species
PH
Phenophase-- budbreak, unfolding of
first leaf, flowering, fruiting,
turning of leaves, animal migration,
emergence, growth stages, breeding,
nesting, hibernation, etc.
2. The upper panel (A) shows molar extinction coefficient spectra for mixed
carotenoids, chlorophyll a+b and anthocyanin. Lower panel (B) shows
representative leaf reflectance spectra for yellow, red and green L. styraciflua
leaves
Sims & Gamon, 2002, Remote Sens Environ. 81, 337.
4. Introduction
• Phenology (greek word phaino; to show or to appear) is
the study of periodic biological evebts as influenced by the
environment. It includes the timing of biological events,
particularly in response to climatic changes to the
environment.
Sprouting and flowering of plants; color changes of leaves in autumn,
insect hatches, hibernation, bird migrations
Certain biological events, such as the time of the start of the growing
season, have a key role in changing land surface/atmosphere
boundary conditions such as surface roughness, albedo, humidity,
etc. The phenology of ecosystems and its connection to climate is a
key to understanding ongoing global change.
– Phenology has historically been studied as direct observations of the
timing of leaf opening, flowering, leaf fall and such events.
5. Phenology
Phenology “reflects” the interactions (responses,
feedbacks) of organisms with their environment,
Phenologic variations depict a canopies’
integrated response to environmental change and
influence local biogeochemical processes,
photosynthesis, water cycling, soil moisture
depletion, and canopy physiology,
Phenology is an important indicator of climate
change, global change, and disturbance
(anthropogenic signal),
Phenological data and models are used in
agricultural production, drought monitoring,
wildfire risk assessment, archaeology, and
treatment of pollen allergies.
6. Phenology is an essential component of the biosphere
Adapted from Bonan (2002)
Ecol. Climatology
8. Global Change Influences & is Influenced by Phenology
lc ycle
na
easo
n of s
c atio
p lifi
Am
ial
str
te rre
tes iple
ula ult
od t m
m a les
gy les
olo yc l sca
n
he on c tia
P b spa
r
ca por al &
tem
9. NPN Network
Structure
Increasing Process Knowledge
Decreasing Spatial Coverage
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
Adapted from CENR-OSTP 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
TERRA
Dec. 18, 1999
25. Atmospheric and Sensor noise
• Cloud contamination
– throughout composite period
– sub-pixel clouds
• Illumination angle and viewing geometry
• Atmospheric aerosols
26. Atmospheric and Sensor noise
• Cloud contamination
– throughout composite period
– sub-pixel clouds
• Illumination angle and viewing geometry
• Atmospheric aerosols
• Water vapor, haze, other contaminants
27. Atmospheric and Sensor noise
• Cloud contamination
– throughout composite period
– sub-pixel clouds
• Illumination angle and viewing geometry
• Atmospheric aerosols
• Water vapor, haze, other contaminants
• Sometimes unreliable calibration
34. What aspect of the vegetated
land surface are we measuring?
DMA – first sustained flush of greenness?
Half-max – primary leaf expansion?
Greatest Increase – early season growth peak
(perceived spring)?
Inflection pt. – environmental conditions preceding
first flush?
…what biophysical phenomena should be
represented? Application specific.
37. East- West Transect (seasonal dry to perhumid)
In this study we
examine
disturbance &
regenerating forests
and
a north-south
transect from
humid rainforest -
ecotone- cerrado
38. At the landscape
level, many climate
and growth models
characterize tropical
rainforests as having
no seasonal variation
in vegetation
dynamics.
Much of what is known about tropical forest seasonal vegetation
dynamics comes from the AVHRR data,
in which the phenology is often characterized as “flat”.
41. Summary
The right combination of spectral, spatial, and temporal
detail are needed for improved tropical forest phenology
characterization for use in carbon and production models.
More intense drought periods, combined with land
degradation, may stress these ecosystems beyond a
threshold resulting in the widespread forest drying with
wildfires becoming a more dominant force.
The dynamics and interplay of climate change, land-use
activities, and socio-ecologic sustainability will largely
determine the fate of these biologic rich ecological
systems.
This is in part due to the complexity of tropical forest canopies, where a highly diverse tree species population can result in a wide variety of phenology responses to the same or common environmental factors, such as rainfall, temperature, and photoperiod (Wright and Schaik, 1994; Reich et al., 2004; Prior et al., 2004; Kushwaha and Singh, 2005). Satellite observations with high temporal frequency AVHRR measurements are also constrained by poor spatial resolution (>4 km), limited spectral content with low optical depth of penetration through densely vegetated forest canopies, cloud contamination, and sensitivity to seasonally variable atmosphere water vapor and aerosol conditions , resulting in low spectral sensitivity for tracking temporal and spatial variability in tropical forest characteristics, including phenology (Goward et al., 1991; Kobayashi and Dye, 2005). Kobayashi and Dye (2005) found strong seasonal signals from clouds and aerosols in the AVHRR- normalized difference vegetation index (NDVI) data sets over the Amazon, which dominated the relatively weak ヤapparentユ seasonal signal from the tropical forests themselves. The NDVI essentially becomes メsaturatedモ and insensitive to the chlorophyll signal, forest biophysical properties, and more subtle phenology characteristics (Skole and Qi, 2001).