Remote sensing of grazing intensity: Case studies in the short and midgrass steppes

1
Remote sensing of grazing intensity Case studies
in the short- and midgrass steppes
Grasslands are important biomes all over the
world both in spatial extent (40 of land mass)
and in ecosystem function. Understanding
grassland production dynamics necessitates
detailed knowledge of how these areas are managed
currently and in the past. Grassland management
influences spatial and temporal production
regimes across grassland types in addition to
other production determinants like soil type,
climate and species. Assessment of how management
will influence grassland dynamics can be
facilitated by using remote sensing.
CPER The Central Plains Experimental Range is a
long term ecological research (LTER) site in
northern Colorado. Three grazing intensity
paddocks are used in this study Light , 17
heifer-d ha-1 (35 utilization) Moderate 27
heifer-d ha-1 (50 utilization) Heavy 37
heifer-d ha-1 (70 utilization) There are some
ungrazed Conservation Reserve Program (CRP) lands
close to the CPER which we compare with
treatments at CPER for remote sensing purposes
only.

• CLNWR
• At the Crescent Lakes Wildlife refuge, this study
  investigates effects of resting periods between
  grazing on aboveground production. There are 4
  paddocks sampled each as a different treatment
• Long term rested - Reserved Natural area (RNA)
  ungrazed since 1958
• Paddock 98 last grazed in 1998
• Paddock 00 last grazed in 2000
• Paddock 02 last grazed in 2002

Effects of grazing intensity on aboveground
biomass
This project aims to develop techniques to
characterize grassland management at Central
Plains Experimental Range (CPER, in eastern
Colorado) and at Crescent Lakes National Wildlife
Refuge (CLNWR, in central Nebraska) using
remotely sensed data from EOS-MODIS. Knowledge
about how various grasslands are managed and
detection of this may now be possible with remote
sensing which enables collection of land data
that are spatially explicit, broad in extent and
repeatable. In many cases grazing leads to
decreased net primary production (NPP), but under
certain conditions rangeland grazing of moderate
intensity (30-50 of NPP consumed) in grasslands
can increase NPP by as much as 10. Grazing leads
to decreased standing biomass, leaf area index
(LAI) and absorbed photosynthetically active
radiation (APAR), even as an increase in NPP may
occur. We hypothesize that biomass production and
standing biomass follow patterns like those
illustrated below

• Methods
• At each of these sites the following is done
  during each field trip
• clipping for biomass measurements in three 100 m
  transects at each of the 4 paddocks (grazing
  treatments)
• Leaf area index estimates using a Licor-2000
  every 10 meters for each of the 100 m transects
  at all paddocks.
• GPS coordinates of the transects recorded to
  assist in locating sampled areas in satellite
  imagery.

• Methods
• clipping for biomass measurements in three 100 m
  transects at the 3 grazing treatments
• Leaf area index estimates were made using a laser
  point frame every 10 m for each of the transects
  at all the grazing intensities.
• GPS coordinates of the transects were recorded to
  assist in locating sampled areas in satellite
  imagery.

Effects of historical grazing on grassland
aboveground production
Results With just the preliminary data there
seems to be no particular trends in above ground
production across the continuum of resting
periods. Immediately after being grazed measured
biomass was significantly less (02 June data)
whereas the rest of the measurements reveal no
trends. LAI measurement from June 2002 show a
predictable trend of reducing LAI as time of last
grazing reduces. The LAI increases sharply in
paddocks most recently grazed between the 2
sampling periods in 2002. This could form a
strong basis for tracking aboveground production
based on grazing history by calculating the
biggest NDVI differences within a season.
Effects of grazing intensity on aboveground
biomass
Results There is a trend of differences in
biomass estimated in the field depending on
intensity of grazing. We expect these differences
to be identifiable using remote sensing products
especially due to seasonal variation in LAI in
each of the grazing treatments.

Effects of historical grazing on grassland
aboveground production
Grazing history impacts current ecology,
economics, and policies in grasslands. Grazing
practices can change species composition (e.g.,
shifts from C3 to C4 or from grass- to
forb-dominated), which may in turn be manifested
by shifts in the seasonal distribution of NPP.
Shifts in seasonal ANPP (aboveground NPP) may be
detectable by remote sensing using changes in
indicators of standing biomass (e.g., LAI). This
suggests that history of grazing intensity and
duration of rests could be detected using remote
sensing.

green biomass
brown biomass
Grazing impacts on interannual ANPP variation
Results Preliminary remote sensing data analyses
suggest that production varies due to differences
in interannual variables such as precipitation.
Are there differences in magnitude of response to
moisture depending on the grazing intensity? This
requires much more satellite data analysis that
is not yet complete, but these early data suggest
that interannual variation is least for CRP land.
Grazing management impacts on interannual ANPP
variation
Since ANPP is directly dependent upon
precipitation in semiarid grasslands, large
interannual precipitation variation leads to
dramatic production pulses and declines from year
to year. We know that grazing management, in
this case stocking rate, can impact production,
but does grazing management affect capacity of
vegetation to respond to precipitation?
Generation of information on magnitude of
response to the interannual variation in climatic
factors, especially precipitation, could help
determine what grazing intensity to apply in
order to meet management objectives. Use of
remote sensing products will assist in large
scale determination of the interannual ANPP
variation that could serve as useful
regional-scale resource for management and policy
formulation.
Light
Q3 Can we quantify the magnitude of above ground
production change under different grazing
intensities as interannual climatic conditions
(precipitation) vary? H3 Moderately grazed
areas will have greater capacity to increase
aboveground productivity as moisture increases
while heavily grazed areas will have a reduced
capacity to respond to moisture increase. Areas
grazed more recently have a greater capacity to
respond compared to long rested areas.

• Future work
• Field data is going to be used for ground
  truthing of MODIS LAI/FPAR and NPP data by
  comparing the sampled areas in the field and
  satellite pixel data coinciding with the transect
  coordinates
• This will help characterize grazing impacts on
  standing biomass and also to characterize
  seasonality of standing biomass using MODIS data
• Evaluate impacts of grazing management (time
  since grazing and exclusion from grazing) on
  climate-driven interannual variation in biomass
  and seasonality.
• Use detailed production characteristics by
  grazing type to improve carbon modeling
  especially in spatial and temporal dynamics of
  grasslands.

• Future work
• More satellite data analysis to establish whether
  differences in grazing intensity are perceptible
  by remote sensing. This will be validated by past
  and continuing field data collection. Remote
  sensing data provides a means to cover wider
  grassland areas surrounding the field sites and
  also a possibility to track what happens all
  season long not just the specific field sampling
  dates. From this, more detailed characterization
  of effects of management will be derived.
• Comparison of production differences from both
  field data and remotely sensed data to determine
  whether varying grazing intensities result in
  varying capacity of grasslands to respond to
  interannual conditions.