Ecological Applications, 13(3), 2003, pp. 629–648
q 2003 by the Ecological Society of America
DESERTIFICATION IN CENTRAL ARGENTINA: CHANGES IN ECOSYSTEM
CARBON AND NITROGEN FROM IMAGING SPECTROSCOPY
GREGORY P. ASNER,1,3 CARLOS E. BORGHI,2
1Department
AND
RICARDO A. OJEDA2
of Global Ecology, Carnegie Institution of Washington, Stanford University, Stanford, California 94305 USA
2Biodiversity Research Group, CONICET-IADIZA, CC 507, (5500) Mendoza, Argentina
Abstract. Many arid and semiarid (dryland) regions are subject to desertification from
intensive land-use pressures such as cattle ranching. However, the lack of quantitative
approaches required to assess desertification has slowed our understanding of how vegetation and soils are changing in dryland regions. Using airborne high-fidelity imaging
spectroscopy and field measurements, we developed the first regional assessment of vegetation structural and soil biogeochemical properties in the Monte Desert biome, Argentina.
We evaluated the long-term impacts of grazing on vegetation cover and soil carbon (C)
and nitrogen (N) storage, which are core indicators of biogeochemical status and change
in drylands. A comparative analysis was carried out on vegetation and soil properties in
four major Monte Desert plant communities, as well as within the U.N. Nacunan Man-andBiosphere Reserve and adjacent areas subjected to long-term grazing.
The four dominant plant communities differed substantially in vegetation cover, leaf
area index, foliar N concentration, and soil organic C and N stocks. Imaging spectroscopy
with Monte Carlo spectral mixture analysis provided accurate estimates of fractional photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare soil cover at
,5-m spatial resolution throughout a 763-km 2 region. Hotspots of grazing management
(e.g., ranch centers, water sources) have undergone some woody vegetation encroachment,
but the spatial patterns were localized and variable. More clearly, a widespread NPV decrease and bare soil increase was common outside of the reserve. Soil organic C and N
stocks were highly correlated with PV 1 NPV cover fractions. Soil organic C and N storage
was 25–80% lower in areas subjected to long-term grazing, as compared to protected
ecosystems within the Nacunan Reserve. Long-term grazing has depleted stores of C and
N in soils and dramatically altered vegetation structure in the Monte Desert. A persistent
lack of NPV due to grazing has likely impaired C and N cycles considered central to the
biogeochemical functioning of the region. This study demonstrates a novel approach to
remotely measure both surface and soil properties most indicative of progressive land
degradation and desertification in dryland regions.
Key words: Argentina; AVIRIS; desertification; imaging spectroscopy; land degradation; landuse change; Monte Desert; over-grazing; soil carbon; soil nitrogen.
INTRODUCTION
Arid and semiarid ecosystems (hereafter called ‘‘drylands’’) cover .45% of the global land surface. The
most common human activities in these regions are
cattle and sheep grazing, wood collection, and cultivation. Ranching is by far the most common form of
land use, extending over .3.75 3 107 km2 of drylands
or 25% of the total global land surface (Dregne 1983).
Modern land-use practices change many dryland characteristics such as vegetation cover and biomass, floral
and faunal community structure, water availability, soil
erosion and compaction, and nutrient status (Schlesinger et al. 1990, Roig 1991, Sharma 1998). These
changes can be linked to altered fire regimes, vegetation removal or introduction, and over-grazing (Hill et
Manuscript received 13 May 2002; revised 16 September
2002; accepted 27 September 2002. Corresponding Editor: D.
Peters.
3 E-mail: [email protected]
al. 1998, Manzano and Navar 2000). Other likely contributors to ecosystem change in drylands include climate change, nitrogen deposition and CO2 fertilization
(Archer et al. 1995, van Auken 2000). Independent of
the causes, there are now many documented cases of
land degradation and desertification in dryland ecosystems worldwide (UNEP 1992a, b).
Desertification has been defined in many ways, often
confusing researchers and policy developers alike (Darkoh 1998). The United Nations Conference on Desertification (UNEP 1992b) defined desertification
vaguely as ‘‘land degradation in arid, semi-arid and
dry sub-humid areas resulting from various factors including climatic variations and human activities.’’
However, when desertification is described in the scientific literature, often there is mention of land degradation and a loss of vegetation (and thus human)
productivity. Land degradation involves the ‘‘diminution or destruction of the biological potential’’ of ecosystems by climate change, land use and other inter-
629
630
GREGORY P. ASNER ET AL.
acting factors (Darkoh 1998). Indicators of land degradation include water and wind erosion, crop losses,
soil salinization or sodification, and most clearly, the
destruction or major reconfiguration of vegetation
types, plant communities, and ecosystems. Based on
these definitions, field and remote sensing approaches
have attempted to detect, monitor, and mitigate land
degradation and desertification in dryland regions (e.g.,
Pickup and Chewings 1994, Hill et al. 1998).
Vegetation phenology presents a major challenge to
efforts focused on monitoring land use, degradation,
and desertification in drylands. Climate variation is a
dominant force driving the ecology and habitability of
drylands. Cycles of intense rain and prolonged drought
are common but are spatially complex due to the predominance of convection-driven precipitation (Sharma
1998). Seasonal and interannual temperature cycles are
also highly variable, causing chronic vegetation stress.
The phenology of dryland vegetation is thus tightly
coupled to climate variability, resulting in complex mosaics of plant phenological states at landscape and regional scales. Spatial and temporal variation of live
and senescent vegetation complicates assessments of
ecosystem condition, biogeochemistry (including carbon dynamics), and hydrology.
While local-scale studies have documented the effects of land use in dryland ecosystems, quantitative
spatial information on the vegetation and biogeochemical changes associated with regional land-use policies
in these regions remains elusive. The United Nations
Environment Programme (UNEP 1992b) notes: ‘‘Assessment of the current global status of desertification
and land degradation has shown that accurate hard data,
which would allow it to be stated with some preciseness
to which degree and with what rate desertification is
taking place in various parts of the world, are still
lacking.’’ This statement resonates with the current level of uncertainty in most land-use and climate change
studies of drylands. Ideally, remote sensing should be
a key contributor to understanding these issues, but
progress toward an operational capability for monitoring ecosystem changes specific to desertification has
been hindered by the spatial and temporal complexity
of vegetation phenological mosaics.
Many land-use studies of drylands have focused on
ecosystems in the Northern Hemisphere and Australia
(e.g., Fredrickson et al. 1998, Puigdefabregas et al.
1998). Less is known regarding the ecological effects
of land use in arid and semiarid regions of South America (but see examples in Parsons 1980, Beeskow et al.
1995). One unique dryland biome is the Monte Desert
(Morello 1958). Stretching along the eastern foot of
the Andes, the Monte Desert is located within the Chaco–Monte–Patagonia lowlands of Argentina (Fig. 1).
Many elements of this biome—ranging from basic vegetation community composition to the endemic fauna—
are considered highly endangered due to human activities (Ojeda et al. 1998, 2002). Land-use practices in
Ecological Applications
Vol. 13, No. 3
this region include deforestation for fuel wood, cattle
and sheep grazing, agriculture, mining, and oil exploration (Schofield and Bucher 1986). Land use has affected the Monte Desert for more than 150 years, leading to documented cases of desertification, habitat loss,
and changes in biological diversity (Roig 1991).
Although a variety of field studies have highlighted
human-caused land degradation in the Monte Desert
biome, none have provided regional information on
vegetation status and change. Similarly, no studies have
documented regional changes in key biogeochemical
properties, such as soil carbon (C) and nitrogen (N)
stocks, that may result from land use. In comparison
to vegetation with highly variable phenology, soil C
and N may be a more integrative and temporally stable
indicator of ecosystem condition in drylands. Soil organic matter content indicates the long-term balance of
C and N inputs and outputs resulting from litterfall and
root mortality, microbial decomposition, runoff, and
other factors.
A shortage of large-scale ecological and biogeochemical information on the Monte Desert is surprising
given the unique biodiversity and spatial extent of this
biome. However, it is also understandable, given the
scarcity of approaches available to assess the ecological
status of this and any other drylands of the world. For
decades, traditional multispectral satellite systems,
such as the Landsat sensors, have provided land-cover
information deemed valuable for monitoring arid and
semiarid regions (see reviews by Verstraete and Pinty
1991, Hill et al. 1995, Asner 2002). However, multispectral data and methods have had limited successes
in measuring key vegetation structural and biogeochemical properties of dryland ecosystems. Past studies
often cite problems of too little spectral information,
insufficient spatial resolution, and soil brightness variability as the dominant limitations to surface biophysical mapping (Huete and Jackson 1987, Smith et
al. 1990, Verstraete and Pinty 1991). Highly varied
phenological mosaics in drylands challenge multispectral studies that are predominantly sensitive to vegetation greenness (Myneni et al. 1995, van Leeuwen and
Huete 1996).
New remote sensing approaches have opened the
door for regional studies of ecological change in drylands. In particular, the advent of high-fidelity imaging
spectroscopy (HFIS) in the late 1990s allows remote
measurement of land surface properties that may prove
key to regional desertification programs. HFIS is the
measurement of solar radiation reflected from the
Earth’s surface in contiguous, narrow spectral channels
spanning the wavelength region from 0.4 to 2.5 mm.
‘‘High fidelity’’ distinguishes those instruments providing these measurements with signal-to-noise, stability, and dynamic range performance matching laboratory spectrometers (Asner and Green 2001). The
measurements are collected as three-dimensional data
‘‘cubes’’ that have two spatial and one spectral dimen-
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DESERTIFICATION AND IMAGING SPECTROSCOPY
631
FIG. 1. Map showing the Nacunan Man-and-Biosphere Reserve and four major plant communities that occur in the Monte
Desert biome. The continental extent of the Monte Desert is shown in the upper left inset. Landscape views of the four
communities are provided in the upper right. The reserve map was created from a vegetation survey conducted in the 1920s
and is only generally accurate (R. Ojeda, personal observation).
GREGORY P. ASNER ET AL.
632
sion. These data cubes can be thought of as stacks of
images, with each image representing the light reflected
from a narrow wavelength region, or as assemblages
of spectra, where a reflected light spectrum is measured
for each point in the image. In these data, the spectra
record the molecular absorption and constituent scattering effects of the surface. The high dimensionality
of the spectral measurements (.200 spectral channels)
allows identification of materials with overlapping, but
distinct, spectral signatures.
Using a combination of airborne HFIS observations
and field measurements, we developed the first regional
assessment of vegetation structural and soil biogeochemical properties in the central Monte Desert biome.
We focused our study on a quantitative assessment of
vegetation and soil properties among four major plant
communities found throughout the region, since, to our
knowledge, this information has never been acquired.
We also combined the HFIS and field analyses to assess
the effects of long-term grazing on vegetation structure
and soil organic C and N stocks, as these are baseline
indicators of biogeochemical status and change in drylands (Schlesinger and Pilmanis 1998). The study
served to prototype a new approach for determining
the regional status of dryland ecosystems worldwide,
with a central focus on biophysical and biogeochemical
indicators of progressive land degradation and desertification.
METHODS
Study region
The study area encompassed the Nacunan Man-andBiosphere Reserve and a surrounding 650-km2 region
of unprotected land in the central part of the Monte
Desert, Argentina (Fig. 1). Nacunan Reserve was established in 1961 and became a core site within the
United Nations (UNESCO) Man-and-Biosphere Network in 1986 (InfoMAB 1992). The reserve is 12 800
ha and surrounds the small town of Nacunan, located
at 348029 S, 678589 W in the Mendoza Province, Santa
Rosa. Land use is dominated by cattle ranching
throughout the region, but other important agents of
land-cover change are fire, logging, and nonnative species introductions. A fence was constructed around the
reserve in 1970, protecting its ecosystems from grazing
and logging, and promoting the recovery of vegetation
following release from long-term grazing pressure.
Ojeda et al. (1998) give a detailed social and ecological
history of the reserve.
The region is classified as undulating plains, with
mean elevation of 540 m. Soils vary from shallow clays
to sandy loams. Mean annual precipitation is 326 mm,
with a strong seasonal distribution (most rain in November–March) and high interannual variability. Mean
monthly temperatures range from ,108C in June–July
to .208C in December–February (Ojeda 1989).
Ecological Applications
Vol. 13, No. 3
There are four major plant community types within
the central Monte Desert biome and Nacunan Reserve
(Fig. 1). Algarrobal: mesquite woodlands dominated
by the leguminous tree Prosopis flexuosa. These woodlands also contain a rich diversity of shrub and subshrub species (e.g., Geoffroea decorticans (Gill. ex.
Hook.), Larrea divaricata and L. cuneifolia (Cav.)),
and herbaceous species (e.g., Digitaria californica, Aristida spp.). Jarillal: creosote shrublands dominated by
Larrea divaricata Cav. and L. cuneifolia Cav. In comparison to the algarrobal woodlands, the jarillal has few
secondary woody plant species but many herbaceous
life forms such as Aristida spp. and a variety of forbs.
Peladal: creosote (L. cuneifolia) shrublands containing
no secondary woody or herbaceous species. This community is differentiated from Jarillal by high surface
clay content. Medanal: sand dune patches containing
a sparse matrix of woody and herbaceous plants. Common species of the medanal include L. divaricata, P.
flexuosa, G. decorticans, Ximenia americana, and Aristida spp.
Field measurements
An ensemble of vegetation and soil measurements
were selected to characterize each plant community
inside and outside of the Nacunan Reserve. A stratified
random sampling scheme was employed by establishing three 100-m transects in algarrobal, jarillal, medanal, and peladal communities found within the reserve. Due to constraints of time and access, two 100m transects were employed in each community type
outside of the reserve boundaries. All sampling was
conducted along these transects.
The fractional cover of green, live plant tissues (photosynthetic vegetation; PV), senescent, woody, or dead
tissues (nonphotosynthetic vegetation; NPV), and bare
soil was recorded along each transect in 10-cm intervals using the point-intercept method (Canfield 1941).
Other occasional surface constituents such as rock were
also recorded. Leaf area index (LAI) was measured in
1-m intervals along each transect using plant canopy
analyzers (LAI-2000; Licor, Incorporated, Lincoln, Nebraska). The canopy analyzers were used with a 3/4
optical block to remove the operator from the instrument field-of-view. LAI data were collected under diffuse-sky conditions, on cloudy days and at predawn or
postsunset, as is required to collect the measurements
(Welles and Norman 1991). The dominant species present was recorded for each LAI measurement, which
was taken directly under each vegetation canopy (e.g.,
shrub, tree) or cluster (e.g., bunchgrass).
Foliar C and N concentrations were determined for
the major species present in each plant community. Ten
individuals per species were randomly selected within
a 10-m zone along each transect (n 5 10 individuals
per species 3 3 transects 5 30 individuals per species
per community). The foliage was air-dried for 72 h,
then transported to the laboratory for oven drying and
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DESERTIFICATION AND IMAGING SPECTROSCOPY
633
FIG. 2. Schematic of the AutoMCU spectral
mixture analysis algorithm. Remote spectroscopic measurements form an observation vector for each image pixel. The pixel is unmixed
into subpixel cover fractions using bundles of
reflectance spectra for photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV),
and bare soil (Fig. 3). Endmember spectra are
randomly selected from each bundle, and the
pixel deconvolution is calculated iteratively using a Monte Carlo technique.
grinding. Total C and N values were determined using
a combustion elemental analyzer (EA1108; Carlo-Erba,
Incorporated, Milan, Italy).
Soil C and N samples were collected along each
transect. Soil collections were made to a depth of 10
cm, and were partitioned into groups from inside and
outside of the canopy drip-line of the vegetation. The
soils were air-dried in the field for 72 h, then transported to the laboratory for oven drying and grinding
to a fine powder. CaCO3 was removed from the soils,
and total C and N were measured using an EA1108
combustion elemental analyzer. Soil pH was measured
in deionized water, and bulk density was measured on
soil subsamples.
Spectral mixture analysis
Spectral mixture analysis (SMA) is a technique for
deriving subpixel cover fractions of surface materials
using high spectral resolution reflectance measurements collected from airborne or spaceborne spectrometers. The method is ideal for use in arid and semiarid
systems where subpixel cover variation is high. Each
endmember component contributes to the pixel-level
spectral reflectance, r(l)pixel:
e51
e
e
5 [Cpv 3 rpv (l) 1 Csoil 3 rsoil (l)
1 Cnpv 3 rnpb (l)] 1 «
Imaging spectrometer data
Imaging spectrometer data were collected on 5 February 2001 over a 763-km2 region, including the entire
Nacunan Reserve (113 km2) and an additional 650-km2
area of surrounding, unprotected land. The NASA Airborne Visible and Infrared Imaging Spectrometer
(AVIRIS), one of the few high-fidelity imaging spectrometers in existence, was flown onboard a Twin Otter
aircraft at an altitude of 5900 m, providing image data
with a 4.5-m spatial resolution and a swath of 2.8 km.
The data were geo-rectified using an onboard global
positioning–inertial navigation system (GPS-INS) and
a postprocessing algorithm developed by Boardman
(1999). Five 56.7-km flightlines were then made into
mosaics using an algorithm developed for this study.
The AVIRIS data were calibrated to apparent surface
reflectance using Gao et al. (1993) and further corrected
using a 13.5 3 13.5 m ground calibration target containing 100% bare soil cover. Surface reflectance measurements (0.4–2.5 mm range) were collected near in
time to the AVIRIS overflight using a portable spectroradiometer (ASD Fieldspec-Pro; Boulder, Colorado)
and a reference panel (Labsphere Incorporated, Sutton,
New Hampshire). The reflectance spectra were collected at 1 m above the surface under clear-sky conditions and within 1 h of solar noon.
O [C 3 r (l)]
n
r(l)pixel 5
O [C ] 5 1
n
e51
e
(1)
where re(l) is the reflectance of each land-cover endmember e at wavelength l, C is the fraction of the pixel
composed of e, and « is the error of the fit. The second
equation shows that the endmembers sum to unity.
Because there are a number of endmember combinations that can produce a particular spectral signal
(r(l)pixel), a wide range of numerically acceptable unmixing results for any image pixel are possible (Asner
et al. 2000). SMA techniques that use endmember
(re(l)) reflectance ‘‘bundles’’ account for this natural
variability (Bateson et al. 2000). Asner and Lobell
(2000), Asner and Heidebrecht (2002), and Lobell et
al. (2002) used a general probabilistic linear spectral
mixture model based on Monte Carlo analysis, which
accounts for endmember reflectance variability (Fig. 2).
The model, known as Automatic Monte Carlo Unmixing
(AutoMCU), uses three spectral endmember ‘‘bundles’’
to decompose each image pixel using Eq. 1.
For this study, endmember bundles for PV, NPV, and
bare soil (rpv(l), rnpv(l), rsoil(l)) were constructed from
field spectra collected in and around Nacunan Reserve
(Fig. 3). The SWIR2 region of the spectrum (2.0–2.3
634
GREGORY P. ASNER ET AL.
Ecological Applications
Vol. 13, No. 3
FIG. 3. Spectral endmember bundles collected during a field campaign in January 2001 and used for the AutoMCU
analysis. The full spectral range data shown to the left are for: (A) photosynthetic vegetation (PV), (B) nonphotosynthetic
vegetation (NPV), and (C) bare soil. The tied-SWIR2 spectra for each bundle are shown in panels (D)–(F).
mm) was used to isolate the unique spectral features of
the surface materials, as described in detail by Asner
and Heidebrecht (2002). Briefly, the approach uses
SWIR2 spectra that are ‘‘tied’’ at 2.03 mm to isolate
the shapes of the PV, NPV, and bare soil spectra, which
are very distinct in this wavelength region (Fig. 3D–
F). These tied spectra are highly sensitive to small variations in the subpixel fractional cover of PV, NPV, and
bare soil, as documented by Asner et al. (2000) and
Asner and Heidebrecht (2002). Furthermore, based on
field and radiative transfer studies, tied-SWIR2 spectra
of PV and NPV are less susceptible to variation in
canopy biomass, architecture, and leaf biochemistry
(Asner 1998). Tied-SWIR2 spectral bundles of bare
soils accommodate variation in geochemical properties
that cause the distinctive 2.2-mm soil hydroxyl (OH2)
absorption feature to shift in width, shape, and depth
(Ben-dor et al. 1999). Any persisting variation in endmember reflectance spectra is subsequently propagated
to the subpixel cover fraction estimates (and their calculated uncertainty) via the Monte Carlo algorithm
(Fig. 2).
June 2003
DESERTIFICATION AND IMAGING SPECTROSCOPY
TABLE 1.
Landscape, canopy, and leaf properties in major plant communities of the Monte Desert, Argentina.
635
Major communities†
Parameters
Species‡
Jarillal
Surface cover§ (n 5 5 3 100 m transects with 10-cm sampling)
Photosynthetic vegetation (PV) (%)
31
46
Nonphotosynthetic vegetation (NPV) (%)
25
Bare soil (%)
Leaf area index (m2/m2) (n 5 25–50 individuals or clusters)
Lacu
Ladi
Prfl
Gede
Dica
Xiam
Herb
Leaf carbon and nitrogen (n 5 30 per species)
Carbon (%)
Nitrogen (%)
C:N
Lacu
Ladi
Prfl
Gede
Dica
Xiam
Herb
Lacu
Ladi
Prfl
Gede
Dica
Xiam
Herb
Lacu
Ladi
Prfl
Gede
Dica
Xiam
Herb
(5)a
(8)a
(9)a
Algarrobal
32
43
26
(8)a
(8)a
(11)a
1.8 (0.1)a
1.9 (0.2)a
···
···
···
···
0.5 (0.1)a
2.1
2.3
2.1
1.7
1.3
···
2.9
(0.1)b
(0.1)b
(0.1)a
(0.2)a
(0.1)
(0.2)a
(0.2)a
(0.1)a
(0.1)a
47.9
46.9
48.4
45.0
43.5
···
42.6
2.1
2.6
4.0
3.4
1.9
···
1.6
22.9
18.2
12.1
13.1
22.9
···
26.6
(0.2)b
(0.1)b
(0.1)b
(0.1)b
(0.1)
49.0
47.7
47.4
44.2
···
···
42.4
1.9
2.4
3.7
3.2
···
···
1.5
26.5
19.5
12.9
13.7
···
···
28.3
(0.1)a
(0.2)a
(0.1)a
(0.1)a
(0.1)a
(0.1)a
(1.8)a
(1.6)a
(0.5)a
(0.8)a
(0.3)a
(0.2)b
(0.1)a
(0.01)a
(0.01)a
(0.04)a
(0.01)a
(0.01)
(0.1)a
(0.3)b
(0.4)a
(0.3)a
(0.2)a
(0.1)
(0.2)b
Medanal
26
38
38
···
1.6
1.6
1.4
···
1.2
1.8
···
48.7
48.7
45.2
···
47.8
43.9
···
1.8
3.9
3.3
···
1.9
1.3
···
26.3
12.6
13.5
···
27.9
33.2
(5)a
(7)b
(8)b
(0.1)c
(0.2)b
(0.1)b
(0.2)
(0.1)c
(0.3)c
(0.1)b
(0.1)b
(0.2)
(0.1)b
(0.02)b
(0.01)a
(0.02)a
(0.01)
(0.01)b
(1.2)b
(0.2)a
(0.3)a
(0.2)
(0.3)c
Peladal
12
20
59
(5)b
(6)c
(10)c
1.5 (0.1)c
1.2 (0.2)d
···
···
···
···
···
48.7
49.3
···
···
···
···
···
2.4
2.0
···
···
···
···
···
20.4
20.7
···
···
···
···
···
(0.2)a
(0.1)c
(0.1)b
(0.1)b
(1.2)b
(0.5)a
Notes: Values shown are means (with one standard error in parentheses) for all data collected inside and outside of the Nacunan
Reserve boundaries. Different superscript letters show statistically significant differences for surface cover, LAI, and leaf
carbon/nitrogen, as compared between the four major communities (e.g., within each row in the table; t tests, P , 0.05).
† Community types: Jarillal 5 creosote shrublands; Algorrabol 5 mesquite woodlands; Medanal 5 sand dune scrub; Peladal
5 sparse creosote shrublands on hardpan clayey soils.
‡ Lacu 5 Larrea cuneifolia; Ladi 5 Larrea divaricata; Prfl 5 Prosopis flexuosa; Gede 5 Geoffroea decorticans; Dica 5
Digitaria californica; Xiam 5 Ximenia americana; Herb 5 Aristida spp. and other unidentified herbaceous species.
§ Not specified by species.
RESULTS
Field measurements
Averaging over all transects inside and outside of
the reserve, combinations of PV, NPV, and soil fractional cover indicated some distinctions between the
major plant community types found in the Monte Desert (Table 1). The creosote shrublands (jarillal) and
mesquite woodlands (algarrobal) had similar overall
combinations of surface cover, with 31–32% PV, 43–
46% NPV, and 25–26% bare soil. In comparison to
these systems, the sand dune areas (medanal) had significantly lower NPV (mean 6 1 SD 5 38 6 7%) and
higher soil (38 6 8%) cover, but no significant difference in PV cover (26 6 5%) (t tests, P , 0.05). Among
all communities, the sparse shrubland areas (peladal)
had the lowest PV (12 6 5%) and NPV (20 6 6%) and
highest bare soil (59 6 10%) cover fractions.
LAI results revealed clear differences between jarillal and algarrobal communities, with the latter areas
containing plants of significantly higher LAI (Table 1;
t tests, P , 0.05). In addition, several species found
in the algarrobal, such as P. flexuosa and G. decorticans, had higher LAI values than in medanal. A creosote species, L. divaricata, was present in all communities. It had an LAI (mean 6 1 SD) LAI of 2.3 6
0.1 in the mesquite woodlands, but a lower value of
1.2 6 0.2 in the sparse peladal shrublands t test, P ,
0.01). LAI of the herbaceous matrix was lowest in the
jarillal (0.5 6 0.1), but was higher in the algarrobal
(2.9 6 0.2) (t test, P , 0.01).
Foliar C and N concentrations varied by species as
well as by plant community type (Table 1). Although
there was no clear pattern among or between species
for %C, the variation in foliar N was more pronounced.
The highest foliar N concentrations were found in a
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Vol. 13, No. 3
GREGORY P. ASNER ET AL.
636
TABLE 2. Soil properties (0–10 cm depth) for major plant communities in the Monte Desert,
Argentina.
Major communities†
Soil properties
Jarillal
Algarrobal
Medanal
Peladal
Bare soil
Carbon (%)
Nitrogen (%)
C:N
pH
0.84
0.07
12.0
7.9
(0.22)a,1
(0.02)a,1
(0.1)a,1
(0.2)a,1
0.83
0.07
11.9
7.6
(0.24)a,1
(0.02)a,1
(0.1)a,1
(0.2)a,1
0.18
0.01
15.8
8.1
(0.05)b,1
(0.01)b,1
(0.1)b,1
(0.1)b,1
0.56
0.05
11.2
8.2
(0.12)c,1
(0.01)c,1
(0.1)c,1
(0.2)b,1
Under canopy
Carbon (%)
Nitrogen (%)
C:N
pH
1.88
0.16
11.8
7.4
(0.53)a,2
(0.05)a,2
(0.2)a,1
(0.1)a,2
1.61
0.13
12.4
7.3
(0.07)a,2
(0.01)a,2
(0.1)b,2
(0.1)a,2
0.62
0.05
12.4
7.6
(0.09)b,2
(0.01)b,2
(0.2)b,2
(0.2)a,2
1.02
0.09
11.3
7.8
(0.37)c,2
(0.03)c,2
(0.2)c,1
(0.2)b,2
Bulk density (g/cm3)‡
1.35 (0.05)
1.41 (0.05)
1.45 (0.04)
1.33 (0.04)
Notes: Values are shown as means (with one standard error in parentheses) for all data
collected inside and outside of Nacunan Reserve boundaries. Different superscript letters show
statistically significant differences between major communities, as compared within a row (t
tests, P , 0.05). Different superscript numbers show statistically significant differences between
soils collected in bare areas and under canopies; n 5 30 for all measurements.
† Communities types: Jarillal 5 creosote shrublands; Algorrabol 5 mesquite woodlands;
Medanal 5 sand dune scrub; Peladal 5 sparse creosote shrublands on hardpan clayey soils.
‡ Not partitioned between bare soil and canopy.
known N-fixing legume, P. flexuosa, with values ranging from 3.7–4.0% and no significant differences between plant communities (t tests, P . 0.1). The lowest
foliar N concentrations were measured in one creosote
species, L. cuneifolia (1.9–2.4%) and in mixed herbaceous species (1.3–1.6%).
Calculated foliar C:N ratios provided another means
to compare and contrast the plant communities found
in the Monte Desert. One creosote species, L. divaricata, had significantly lower C:N values in the more
dense algarrobal (18.2 6 0.4) and jarillal (19.5 6 1.6)
systems than in the sparse, sandy medanal areas (26.3
6 1.2) (t tests, P , 0.05). Similarly, the herbaceous
matrix had the lowest C:N values in the algarrobal (26.6
6 0.2) and highest in the medanal (33.2 6 0.3) (t tests,
P , 0.01). The sparse peladal communities did not
sustain an herbaceous layer. In contrast, the legume P.
flexuosa showed no difference in foliar C:N by community type. Foliar C:N of most species were not different between the algarrobal and jarillal areas, but they
were different by species within each community (e.g.,
P. flexuosa , L. divaricata , L. cuneifolia).
The algarrobal woodlands and jarillal shrublands had
similar soil organic C and N values (Table 2). Neither
the under- nor between-canopy measurements proved
statistically different between these two communities
(same superscript letters in Table 2). However, soil C
and N was 200–300% higher in soils collected from
beneath than between canopies within each community
(t tests, P , 0.01). Medanal areas had significantly
lower soil C and N values than algarrobal or jarillal (t
tests, P , 0.05). The lowest soil C and N results were
obtained from the sparse peladal shrublands (Table 2).
Soil C:N ratios for ecosystems went in the following
order from highest to lowest: medanal . algarrobal .
jarillal . peladal. Soils located between canopies in
the medanal sites had the lowest recorded soil organic
C and N values, owing to the poor stabilization of
organic matter in sandy soils (Burke et al. 1989, Davidson 1995). Soil pH was well correlated with soil C
concentration across all study sites (r2 5 0.64, P ,
0.01).
Imaging spectroscopy
The spectral mixture analyses resulted in 763 km2 of
subpixel (,4.5 m) fractional cover estimates of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and bare soil (Fig. 4). There were three
basic regional trends immediately accessible from the
results. First, a general north-to-south trend of increasing PV and NPV and decreasing bare soil cover, likely
resulted from a regional precipitation gradient (Ojeda
et al. 1998). Second, the major Monte Desert communities—algarrobal, jarillal, medanal, and peladal—
were distinct in the spectral mixture results (Fig. 1 vs.
Fig. 4). Third, there were apparent differences in PV,
NPV, and bare soil fractions inside vs. outside of the
Nacunan Reserve.
PV fractions from imaging spectroscopy were highly
correlated with field-based PV measurements (r2 5
0.84; P , 0.05), and the uncertainties in the results
were comparable between the two methods (Fig. 5A).
Error bars for the field measurements resulted from
fractional cover variations along the 100-m transects.
Error bars for the spectral mixture measurements resulted from uncertainty in spectral endmember selection, derived as shown in Fig. 2. Algarrobal areas with
the highest PV values generally had the highest uncertainty in AVIRIS-derived cover fractions, peaking
at 0.09 (Fig. 5A). Sparsely populated peladal shrub-
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637
FIG. 4. Left: Regional mosaic of spectral unmixing results derived from airborne imaging spectrometer measurements.
Fractional surface cover of PV, NPV, and bare soil are shown in shades of red, green, and blue, respectively. The outer fence
demarcating the Nacunan Reserve is shown with yellow lines. Right: Three focus study regions to the north (N), east (E),
and west (W); additional analyses were carried out on these feature areas.
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Vol. 13, No. 3
ments (r2 5 0.86; P , 0.05); many of the sites across
plant communities had similar bare soil fractional cover
values (Fig. 5C). An exception was the high soil values
found in all peladal communities.
Cover inside vs. outside reserve
FIG. 5. Comparison of (A) photosynthetic vegetation, PV,
(B) nonphotosynthetic vegetation, NPV, and (C) bare soil
derived from field measurements (x-axes) and spectral mixture analyses of AVIRIS imaging spectrometer data (y-axes).
Major plant communities found in the Monte Desert and the
Nacunan Reserve are shown with different symbols. Error
bars represent 6 1 SD. The dotted lines represent the 95%
confidence interval.
lands showed the lowest PV fractions, with uncertainty
values ranging from 0.02 to 0.05. Subpixel NPV fractions from spectral unmixing were also highly correlated with field-based NPV results (r2 5 0.83; P ,
0.05); uncertainty estimates were similar between remotely sensed and ground-based measurements (Fig.
5B). Fractional cover of bare soil derived from AVIRIS
was also highly correlated with the ground measure-
Both ground and AVIRIS measurements of PV, NPV,
and soil fractional cover were partitioned by plant community inside and outside of the reserve (Fig. 6). In
general, the PV fraction was not a consistent indicator
of ecological change following long-term heavy grazing outside or following 25 years of protection inside
the reserve (Fig. 6A). The exception was that, in all
peladal areas, the PV fractions were higher outside the
reserve (denoted by asterisk; t tests, P , 0.05). In
contrast, the field data consistently indicated higher
NPV and lower bare soil fractions within the reserve
for nearly all community types (t tests, P , 0.05; Fig.
6B,C). Only the algarrobal sites showed similar bare
soil fractions inside and outside of the reserve (t test,
P 5 0.11), due to the already low soil cover fractions
in these areas.
Three 25–40 km2 focus regions were extracted from
the spectral mixture results to calculate additional statistics for PV, NPV, and bare soil cover fractions across
fence line boundaries (Fig. 4: N, E, W). Areas to the
east (E) and west (W) crossing the reserve boundaries
were selected based on our field measurements and
surveys. Each area crossed fences, with a large ranching operation located just outside of the reserve boundaries. A third north (N) area was also selected to highlight differences in vegetation and soil cover between
two typical ranches, both located outside of the Nacunan Reserve.
There were clear differences in NPV and bare soil
fractions across fencelines in the E and W regions (t
tests, P , 0.05; Fig. 6E,F). Like the field measurements, the PV fractions were not reliable indicators of
differences in and out of the reserve within the W focus
area (Fig. 6D). In the N region, higher NPV and lower
bare soil cover fractions were found to the south of the
fence, but no difference in PV (t test, P . 0.1; Fig. 4:
N).
Only the E region had PV cover fractions that were
statistically higher outside than inside the reserve (t
test, P , 0.05). Subsets of the E region were used to
focus only on the area immediately surrounding the
ranch containing high densities of PV (Fig. 4:E). Subpixel PV and bare soil fractions were significantly higher and the NPV fraction was lower in this area outside
of the reserve (t tests, P , 0.05; Fig. 6D–F).
Plotting PV against NPV cover fractions for both
field (open symbols) and AVIRIS (closed symbols) data
demonstrated the independence of these surface measurements (Fig. 7). While algarrobal areas consistently
had the highest PV and NPV fractions, the other communities had relatively similar PV cover values. The
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DESERTIFICATION AND IMAGING SPECTROSCOPY
639
FIG. 6. (A–C) Fractional cover of PV, NPV, and bare soil from field transects inside (I; solid bars) and outside (O; open
bars) of Nacunan Reserve. Data are partitioned by major community type. Asterisks (*) indicate statistically significant
differences at the P , 0.05 confidence level. (D–F) Fractional cover of PV, NPV, and bare soil from spectral mixture analyses
of AVIRIS imaging spectrometer data. Bars and asterisks are defined as in the left-hand panels. Data are partitioned by the
focus study regions located east (E), north (N), and west (W) of the reserve (see Fig. 4). Error bars represent 6 1 SD.
addition of the NPV estimate from AVIRIS thus provided unique, additional means to separate community
types, although some of the medanal and jarillal sites
were similar in terms of PV and NPV combined.
Soil organic C and N stocks
Field measurements of soil organic C (SOC) and N
(SON) concentration were combined with soil bulk
density values to calculate SOC and SON mass; these
values were partitioned by community type inside and
outside of the reserve (Fig. 8). SOC was highest under
canopies in jarillal areas (mean 6 1 SD 5 3.9 6 0.2
kg C/m2) and lowest in medanal areas away from canopies (0.2 6 0.03 kg C/m2) (Fig. 8A). Soil organic N
values generally paralleled the SOC results (Fig. 8B).
Soil C and N stocks were much lower outside than
inside the reserve; all differences reported here were
statistically different at the P , 0.01 confidence level.
In jarillal communities, SOC and SON mass were
;200% greater inside the reserve, independent of
whether the soil was collected under or away from
canopies (Fig. 8A). Soils from algarrobal areas showed
less dramatic differences when comparing soils collected under canopies from protected and unprotected
areas; SOC and SON values were only 10% higher
inside the reserve. However, for soils collected between
canopies, soil organic C and N was roughly 200% higher in algarrobal sites inside the reserve. Significantly
higher SOC values were also measured in the protected
medanal and peladal areas. However, these differences
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GREGORY P. ASNER ET AL.
Ecological Applications
Vol. 13, No. 3
FIG. 7. Relationship between PV and NPV
for remotely sensed subpixel fractional cover
values (solid symbols) and field-based cover
values (black symbols). Field data were convolved to 4 m spatial resolution for comparison
to remotely sensed data. Error bars represent 6
1 SD.
were less pronounced in the jarillal or algarrobal communities.
Regional soil C–N stocks from imaging spectroscopy
Soil organic C (in kilograms per square meter) was
plotted against fractional cover values of PV, NPV, and
bare soil derived from imaging spectroscopy (Fig. 9).
A strong positive exponential relationship was found
between SOC and fractional PV 1 NPV measured
along the field transects (r2 5 0.92, P , 0.01; Fig. 9A).
Conversely, a negative exponential relationship was established between SOC and fractional bare soil cover
(r2 5 0.94, P , 0.05; Fig. 9B). Notably, the relationship
between SOC and PV (r2 5 0.41) or NPV (r2 5 0.68)
was significant, but much weaker than those derived
for PV 1 NPV or bare soil (Fig. 9C,D).
The equation derived for the PV 1 NPV cover fraction vs. SOC (Fig. 9A) was applied to the spectral
mixture analysis results in Fig. 4. The three focus regions (Fig. 4:N, E, W) were used to calculate statistics
for soil C content across fence line boundaries separating no/low grazing and high grazing areas (Fig. 10).
Soil organic C stocks were highest in the W region
inside the reserve, with values of 1.2 6 0.6 kg C/m2.
In Fig. 10, the standard deviation values represent the
general spatial variability of SOC. In the west (W)
region outside the reserve, SOC pools were nearly half
and the spatial variability nearly one-third that of areas
inside the reserve (Fig. 10C). The east (E) region was
somewhat different, with 20% larger SOC pools inside
than outside the reserve but similar spatial variability
(Fig. 10B). In the north (N) region, SOC was roughly
10% higher to the north side of the fence, but the spatial
variation of SOC stocks was .300% higher to the south
(Fig. 10A).
DISCUSSION
Monte Desert communities in Nacunan Reserve
The four dominant communities found in the Monte
Desert—jarillal (dense shrubland), algarrobal (mes-
quite woodland), medanal (dune shrubland), and peladal (sparse shrubland)—each has a distinctive appearance (Fig. 1), yet little is known of the physical
and chemical attributes of these areas (Ojeda et al.
FIG. 8. Field-based soil organic (A) carbon and (B) nitrogen stocks by ecosystem. Soils are partitioned by underand between-canopy areas as well as by inside (I) vs. outside
(O) of Nacunan Reserve. Errors bars represent 11 SD.
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641
FIG. 9. Nonlinear regression results for remotely sensed variables and soil organic carbon stocks: (A) fractional photosynthetic vegetation (PV) 1 nonphotosynthetic vegetation (NPV); (B) fractional bare soil; (C) fractional PV; and (D) fractional
NPV. Error bars represent 61 SD.
1998). These attributes bear on a range of ecological
functions including carbon and nutrient cycling, hydrology, and mammal abundance and diversity. The
biophysical and biogeochemical properties of each
community also affect their response to land use.
The total C and N capital of arid and semiarid ecosystems is a broad indicator of its productivity, material
cycling, and biological carrying capacity. The goals of
this study did not include an assessment of total ecosystem C and N pools. However, several spatially integrated indicators do provide insight to relative differences in the functioning of communities within Nacunan Reserve.
Area-weighting the soil organic C and N mass data
(Fig. 7) by the mean fractional cover data for PV 1
NPV (Fig. 6) yielded a clear trend in ecosystem-level
SOC: jarillal (3.6 kg C/m2) . algarrobal (2.3 kg C/m2)
. medanal (1.0 kg C/m2) . peladal (0.8 kg C/m2).
Area-weighted values for soil organic N mass did not
follow the same trend: algarrobal (0.16 kg N/m2) .
jarillal (0.13 kg N/m2) . peladal (0.05 kg N/m2) $
medanal (0.04 kg N/m2). All differences were significant (t tests, P , 0.05), except for the comparison
between peladal and medanal soil N stocks.
Given that the fractional surface cover of vegetation
(PV, NPV, or PV 1 NPV) was similar between the
algarrobal and jarillal communities (Table 1), the observed 56% higher soil organic C in the jarillal suggests
that either productivity is higher or decomposition is
slower in these areas. We did not measure productivity,
but both LAI and leaf N are known correlates of plant
growth (Aber and Melillo 1991). Comparing species
that occur in both algarrobal and jarillal sites, LAI was
consistently higher among algarrobal species (Table 1).
Similarly, leaf N was consistently higher among woody
and herbaceous species in the algarrobal relative to
jarillal. This combination of findings suggests that productivity is not higher in the jarillal, and thus that higher SOC in this community results from slower decomposition. This hypothesis is supported by greater relative abundance (data not shown) of high foliar C:N
ratio species (Larrea spp.; Table 1) and higher soil clay
content in jarillal areas (Ojeda et al. 1998), both of
which would favor lower decomposition rates in this
community. In summary, while the jarillal contains the
most SOC, the algarrobal may be the most productive,
as it has the highest N capital. Note that two species
found in the algarrobal (P. flexuosa and G. decorticans)
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GREGORY P. ASNER ET AL.
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Vol. 13, No. 3
FIG. 10. Regional amount and spatial variability of soil organic carbon stocks from airborne imaging spectroscopy and
PV 1 NPV regression in Fig. 9. Graphs A, B, and C show spatial mean and standard deviation estimates for focus regions
N, E, and W, respectively (Fig. 4).
are known nitrogen fixers, providing an additional reason for higher soil N levels in this community type.
Overall the field data yielded a suite of vegetation
and soil characteristics that define the basic biogeochemical status of Monte Desert plant communities in
Nacunan Reserve. While there were strong gradients
in surface cover, LAI, leaf chemistry, and soil organic
C and N among the four dominant community types,
the information contained in any single measure was
not readily interpretable without considering the other
biophysical and biogeochemical properties.
Surface indicators of desertification
Detection and quantification of the surface conditions that best indicate dryland degradation are challenged by spatial and temporal variation in vegetation
structure and phenology. Distinct topo-edaphic and
vegetation assemblages define basic communities and
ecosystems within the larger regional context, such as
in the Monte Desert biome. However, rainfall is particularly patchy in dryland regions, causing the phenological status of plants to vary locally. Distinctions
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DESERTIFICATION AND IMAGING SPECTROSCOPY
between ecosystems, land-use patterns, phenology, and
the vegetation changes that indicate desertification become blurred or inseparable. What are the major indicators of land degradation, and how do they vary
over space and time relative to these other factors?
There is likely no single metric of surface condition
indicating desertification. However, several observations employed in this study can be used to monitor
vegetation conditions in drylands, and those conditions
can be used to estimate the onset or persistence of land
degradation.
Woody vegetation encroachment is often cited as an
indicator of land degradation in arid and semiarid regions. In the past century, the balance between woody
and herbaceous plants has shifted to favor trees and
shrubs in many drylands (Archer et al. 1995). Factors
contributing to these life form transitions are subject
to debate but focus mostly on human-induced alterations of fire frequency and grazing intensity (e.g.,
Grover and Musick 1990, van Auken 2000). Regional
assessments of changes in grass–woody plant abundance are complicated by the fact that the rates and
dynamics are strongly influenced by spatial rainfall variability, topo-edaphic heterogeneity, and land management practices. Range management practices that may
enhance woody plant encroachment in some areas (e.g.,
fire suppression and heavy livestock grazing) may be
offset by practices favoring grass domination in other
areas (e.g., prescribed fire, chemical, or mechanical
treatments targeting woody plants). Assessing land
degradation in terms of woody encroachment is very
difficult at the regional level. The process of woody
vegetation change can take decades in dryland systems,
yet the historical data are not available from remote
sensing systems in use today. Aerial photographs do
provide a valuable historical perspective on rates and
patterns of woody vegetation change (e.g., Archer
1995, Schlesinger and Gramenopoulos 1996). However, historical aerial photography is available for only
a tiny fraction of the world’s drylands.
The pattern of woody vegetation observed today can,
at times, indicate long-term dryland degradation. Buffington and Herbel (1965) and many others have documented major changes in the spatial heterogeneity of
woody plants and herbaceous vegetation in the Chihuahuan Desert during the past century. Overgrazing
was cited as the major cause of the observed change
from historically dominant grasslands to modern
shrub–dune systems supporting little herbaceous vegetation. Schlesinger et al. (1990) indicated that desertification in this and other regions of the world involved important hydrological and biogeochemical
feedbacks acting to perpetuate spatial clustering of resources on the landscape. Once the woody vegetation
is established, important ecosystem resources such as
nutrients and organic matter maintain ‘‘islands of fertility,’’ ultimately forming regional mosaics of highly
aggregated vegetation clusters seen from remote sen-
643
sors (Asner and Lobell 2000, Rango et al. 2000). Not
all dryland degradation scenarios occur this way. In
mesic environments, woody plant proliferation may decrease herbaceous vegetation production, but replacement and spatial aggregation may or may not occur
depending upon soil conditions and the woody species
composition (Archer et al. 1988).
In our study, there were pronounced but highly variable effects of long-term grazing on woody vegetation
cover. The focus region bordering the east edge of Nacunan Reserve showed a distinct pattern of dense photosynthetic vegetation (PV) surrounding a ranching
center (red tones, Fig. 4:E). The west focus area also
had increased PV cover immediately surrounding a water source and corral used for cattle management (Fig.
5:W). These high PV areas correspond to P. flexuosa,
whose fruits are consumed by cattle that disperse and
increase the germination of its seeds (Campos and Ojeda 1997). At the time of the AVIRIS overflights, the
herbaceous matrix was predominantly senescent, while
the woody vegetation was green. The red rings of high
PV values thus show woody vegetation in thick clusters, but with much higher densities outside of the reserve (Fig. 6D).
In each of these focus regions, it is unknown if the
woody thickening immediately inside the reserve is a
remnant patch of high cover established prior to the
fence installation, or if it results from proximity to the
increased woody plant seed source provided outside of
the reserve. Site visits to the E and W focus regions
indicated that woody plants had not displaced herbaceous vegetation, as seen in more arid ecosystems undergoing desertification (Frederickson et al. 1998). The
much higher bare soil cover fractions found among the
woody plant clusters, shown as increased blue tones
among the red PV clusters in Fig. 4, had instead resulted from persistent and heavy grazing in the area
(discussed in the following paragraphs). However, it is
unknown whether woody plant proliferation has decreased production in the herbaceous matrix, as seen
in mesic grassland systems undergoing woody encroachment (Archer 1995). Such a decrease is possible,
since shading in the dense overstory woodlands was
substantial, as indicated in measured shrub and tree
LAI values (Table 1).
In the west focus region (Fig. 4:W), it is important
to note that the PV fractions were only higher in areas
immediately surrounding the corral and water source.
In fact, the general area to the west of the reserve had
a lower PV cover fraction than inside the reserve (Fig.
6D). In contrast, the PV fraction was statistically higher
outside of the reserve in the east region, independent
of distance from the ranch center (Fig. 4:E). Moreover,
the north focus area showed no difference in PV fraction to either side of the fence separating two ranches
(Fig. 4:N). In combination, these results indicate the
variable effects of grazing and land management on
woody vegetation cover. They highlight the difficulties
644
GREGORY P. ASNER ET AL.
of assessing land degradation and desertification via
temporally static observations of green vegetation patterns alone. This is likely a source of great uncertainty
in conventional remote sensing studies designed to detect changes in greenness via the NDVI or other multispectral techniques.
An alternative dryland degradation indicator is the
spatial patterning of nonphotosynthetic vegetation
(NPV) and bare soil on the landscape. At any given
locale, NPV is intimately linked to both the regional
phenology and the intensity of grazing. However, the
spatial pattern of NPV–soil fractions can provide strong
indications of overgrazing, degradation, and desertification. For example, NPV was statistically lower outside of the Nacunan Reserve in all focus regions (Fig.
6E). Bare soil cover fractions were reciprocally higher
outside of the reserve (Fig. 6F). In fact, this was the
general case everywhere around the reserve, as indicated in blue rather than green background tones in the
spectral mixture analysis images (Fig. 4).
The spatial persistence of low NPV over hundreds
of square kilometers indicates a chronic break in the
cycling of carbon and nutrients in the region. Nutrients
bound in NPV must be returned to the soil, where they
are mineralized and made available again for plant uptake. Large-scale removal of NPV from the region thus
indicates a reduction in nutrients ultimately returned
to plant-available inorganic forms, potentially feeding
back to decrease ecosystem productivity. The surface
litter and standing senescent herbaceous species that
comprise the remotely sensed NPV fraction also serve
as an important barrier to soil evaporation and dust
generation. Increased evaporation following NPV removal can exacerbate the desertification process
through accelerated desiccation of surface soil layers
(Novikoff 1983, Monteith 1991). In such cases, only
deep-rooted species such as woody plants may survive,
further enhancing woody plant proliferation and the
loss of herbaceous and other shallow-rooted species.
Surface soil is mobilized when NPV is removed (Okin
et al. 2001), causing erosion and lateral movement of
nutrients and other elements. Desiccation, dust generation, and nutrient losses from persistent NPV removal form a coupled system of ecological stresses that
imperil dryland regions subjected to desertification.
It is important to acknowledge the value of shortterm vegetation phenological observations as an avenue for detecting land degradation, although this technique was not employed in our study. Pickup (1996)
isolated degraded rangelands in Australia by observing
the phenological response of vegetation to rainfall
events. They used a multispectral satellite index of
greenness, and connected a small response in the satellite data following rainfall to land degradation. A
large response indicated that the vegetation was rapid
to green up and thus that the ecosystem was functioning
well. Postrainfall vegetation response is a powerful
way to estimate ecosystem condition over large re-
Ecological Applications
Vol. 13, No. 3
gions, but it is challenged by the fact that different
plant functional groups often coexist in dryland regions. Functional groups such as shallow-rooted and
deep-rooted shrubs, subshrubs, grasses, and forbs have
widely varying capacities to respond to rainfall events
(Breshears et al. 1997, Breshears and Barnes 1999).
The response of a given group can even vary seasonally
or at different growth stages. Short-term greenness responses to rainfall are also difficult to interpret because
of the spatial heterogeneity of precipitation events
(Sharma 1998, Williams and Ehleringer 2000). Higher
spatial resolution (,60 m) remote sensing observations
of drylands inherently resolve the patchy nature of rainfall events across a region. Observed green-up responses may be readily apparent, but a small response could
also simply mean that precipitation was minimal in a
given location on the landscape. Despite these limitations, the rainfall-response approach to land degradation assessment appears to work in drylands dominated by herbaceous plants (Williamson and Eldridge
1993, Pickup and Chewings 1994, Pickup et al. 1994).
In summary, the surface conditions that may indicate
the onset or progression of ecological degradation in
dryland regions include woody plant encroachment,
spatially extensive losses of NPV, and poor phenological response to rainfall (not considered in this study).
No single observation will clearly indicate desertification, but two or more indicators do provide quantitative evidence that degradation is underway. In the
case of the Monte Desert biome near Nacunan Reserve,
hotspots of grazing management (e.g., ranch centers,
water sources) have undergone some woody vegetation
encroachment, but the spatial patterns are localized and
variable. More clearly, it is the widespread NPV decrease and bare soil increase outside of the reserve that
indicates a break in carbon and nutrient cycles considered central to the biogeochemical functioning of the
region. If persistent over time, this break would cause
a measurable decrease in soil organic carbon and nutrient stocks.
Soil indicators of desertification
From a biogeochemical perspective, an indication of
long-term ecosystem degradation should be observable
in the amount and chemistry of soil organic C. SOC
is an integrator of ecosystem processes because it is a
product of plant litter inputs, microbial decomposition,
nutrient dynamics, faunal activities, hydrological processes, and other factors. In contrast to vegetation with
highly dynamic phenology and sensitivities to land use,
SOC is more stable, since the turnover time of soil
carbon is on the order of years to centuries (e.g., Shang
and Tiessen 1998). Observed changes in SOC can
therefore indicate major changes in the functioning of
an ecosystem. This is especially true in dryland regions, where natural rates of SOM change are slow due
to relatively low litter production and decomposition
rates.
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DESERTIFICATION AND IMAGING SPECTROSCOPY
Our soil organic C and N studies indicated strong
spatial correlation with the vegetation (Fig. 8). Soils
collected beneath plant canopies had 20–60% more
organic C and N than those collected from the canopy
interspaces. These results support previous studies
highlighting the spatial correlation between vegetation
and soil organic C and N in drylands (Schlesinger et
al. 1996, Dougill et al. 1998, Schlesinger and Pilmanis
1998). More importantly, our field surveys showed that
SOC and SON stocks were 25–80% higher inside the
protective fence of Nacunan Reserve than in outside
areas subjected to continual grazing (Fig. 8). These
results suggest a substantial 30-year recovery of soil
resources inside the reserve, a continued loss of SOC
outside of the reserve, or mostly likely, both processes
occurring simultaneously. These processes result directly from the presence (or absence) of vegetation and
the subsequent inputs of plant litter to soils.
Soil organic C and nutrient stocks cannot be directly
measured from remotely sensed data, although there
are research efforts to estimate SOC levels in agricultural systems (Galvao et al. 2001). However, SOC
stocks were spatially well correlated with fractional
cover of PV 1 NPV (Fig. 9). Notably, the linkage
between soil C stocks and PV alone was less than half
as strong as with PV 1 NPV (Fig. 9c vs. a). This finding
supports the hypothesis that widespread, persistent removal of NPV disrupts biogeochemical processes such
as carbon cycling, soil organic matter formation, and
nutrient storage.
Application of these findings to the imaging spectroscopy data provided a window into the regionalscale impacts of desertification on soil organic C storage. Protected areas inside the Nacunan Reserve had
;20–50% more SOC than grazed areas outside of the
reserve (Fig. 10). The regional analysis also suggested
that the spatial heterogeneity of SOC was higher inside
the reserve, as depicted in higher standard deviations
in Fig. 10b and c. This result suggests that desertification can decrease the spatial partitioning of resources
across the landscape, which contrasts with observations
in more arid environments that have undergone grassland replacement by shrublands (Buffington and Herbel
1965, Schlesinger et al. 1990, Frederickson et al. 1998).
A decrease in SOC variation could be caused by widespread increases in bare soil cover in the absence of
vegetation cluster formation as observed in other studies. Aside from the areas immediately around ranch
centers and water sources, there was no evidence of
PV aggregation in the region (Fig. 1). Additional studies are needed to further test this hypothesis.
Regional monitoring with imaging spectroscopy
Until recently, quantitative remote sensing analyses
of vegetation, surface litter (NPV), and bare soil cover
have been difficult to carry out in dryland regions.
Imaging spectroscopy now provides access to land surface measurements historically inaccessible from other
645
remote sensing systems. Analysis of the overlapping
spectral absorption features of different surface materials allows quantitative determinations of their relative abundance within image pixels. While conventional multispectral systems have provided estimates
of vegetation greenness using the NDVI and related
indices, these estimates required empirical calibration
to surface properties such as green vegetation cover or
leaf area index. Spectral mixture analysis with highquality shortwave–IR (2.0–2.4 mm) imaging spectrometer data (Fig. 2) allows accurate measurement of surface properties with little field calibration.
In this study, quantitative measurements of PV, NPV,
and bare soil fractional cover were achieved at sub-4.5
m spatial resolution using airborne high-fidelity imaging spectroscopy (HFIS) with a probabilistic spectral
mixture model. The measurements were collected at a
spatial resolution commensurate with the vegetation
structural variability of the Monte Desert biome of Central Argentina. Our experience indicates that similar
measurements would work well in other sparse shrublands, savannas, or dense woodlands because the approach is not dependent upon in situ biophysical conditions (Asner and Heidebrecht 2002).
The PV, NPV, and bare soil estimates proved highly
accurate in comparison with field measurements (Fig.
5). In turn, these estimates were nonlinearly correlated
with soil organic C and N stocks in soils (Fig. 9). These
linkages provided the means to regionalize a formerly
inaccessible but crucial measure of ecosystem condition in drylands subjected to degradation and desertification. In particular, it is the quantitative analysis of
NPV fractional cover that best bridges the gap between
remotely sensed vegetation and soil organic C and N
stocks.
High-fidelity imaging spectroscopy (HFIS) is a
unique technology. Imaging spectroscopy has existed
for over a decade (e.g., Rock et al. 1986, Vane and
Goetz 1988), but the instrumentation has evolved during that period. Hyperspectral reflectance measurements now collected from aircraft are equivalent in
quality to laboratory spectroscopy; such results were
not available just 5–6 years ago (Asner and Green
2001). HFIS measurements are available from only a
few airborne instruments worldwide, and the need for
rapid expansion of the technology to spaceborne vantage points is now warranted. The recent launch of the
Earth Observing-1 (EO-1) satellite into low Earth orbit
makes this a possibility, and we are currently testing
the approach presented in this study with EO-1 data.
However, EO-1 is a technology demonstration, and thus
it is not designed for operational monitoring of ecosystems. The Hyperion imaging spectrometer onboard
EO-1 also does not have the signal-to-noise performance and thus data quality of an HFIS system. Our
study and a diverse array of other applications dependent upon HFIS indicate a clear and present need for
global HFIS measurements on a more routine basis
Ecological Applications
Vol. 13, No. 3
GREGORY P. ASNER ET AL.
646
(e.g., Jacquemoud et al. 1995, Rollin and Milton 1998).
Until the technology is widely available from Earth
orbit, our ability to quantitatively measure and monitor
desertification in dryland regions will remain limited.
CONCLUSIONS
Using a combination of airborne imaging spectroscopy and field measurements, we developed the first
regional assessment of vegetation structural and soil
biogeochemical properties in the Monte Desert, Argentina. Our study provided a quantitative assessment
of vegetation and soil properties among the major plant
communities found in the region. We also evaluated
the impacts of long-term grazing on both vegetation
structure and soil organic C and N stocks, as these are
basic indicators of biogeochemical status and change
in drylands. In doing so, we demonstrated a new approach to integrative assessment of the surface and soil
properties indicative of progressive land degradation
and desertification in dryland regions.
Desertification affects more than 3.6 3 109 ha and
nearly 109 people worldwide (Fu 2000), yet no methods
have existed for quantitatively measuring and monitoring land surface and subsurface characteristics needed to assess ecological or biogeochemical status in drylands. While the approach presented in this paper requires additional testing and refinement across a range
of biogeophysical environments, our study presents a
potentially viable approach to desertification monitoring on a quantitative basis. The specific findings of this
effort were:
1) The four dominant plant communities of the central Monte Desert biome differ substantially in vegetation cover, leaf area index, foliar N concentration,
and soil organic C and N stocks. The combination of
these properties indicated the structural uniqueness of
each community.
2) Airborne high-fidelity imaging spectroscopy
(HFIS) and Monte Carlo spectral mixture modeling
provided accurate estimates of photosynthetic vegetation (PV), nonphotosynthetic vegetation (NPV), and
bare soil fractional cover in Monte Desert ecosystems.
These surface cover fractions indicated the unique biophysical structure of each plant community type and
quantitatively defined the effects of long-term grazing
on these communities.
3) In the Monte Desert biome near Nacunan Reserve,
hotspots of grazing management (e.g., ranch centers,
water sources) have undergone some woody vegetation
encroachment, but the spatial patterns are localized and
variable. More clearly, a widespread NPV decrease and
bare soil increase is common outside of the reserve.
Persistently low NPV due to grazing has likely impaired C and N cycles that are key to the biogeochemical functioning of the region.
4) Soil organic C and N stocks were highly correlated
with the combination of PV and NPV surface cover, as
measured in the field and from airborne imaging spec-
troscopy. The linkage between surface cover and soil
organic constituents was significantly stronger when
NPV was measured remotely.
5) Soil organic C and N stocks were substantially
lower in areas subjected to long-term grazing in the
Monte Desert. In each dominant vegetation community
found in the region, soil organic C and N mass were
higher in soils under canopies than in the canopy interspaces. For both under- and between-canopy soils,
C and N stocks were lower in unprotected areas
throughout the region.
ACKNOWLEDGMENTS
We thank B. Constance, K. Heidebrecht, S. Parks, B. Sawtelle, and S. Tabeni for field, remote sensing, and GIS assistance. We thank I. McCubbin, R. Green, and the AVIRIS team
for their efforts to acquire the imagery. Thanks to T. Harris,
D. Peters, J. Paruelo, A. Townsend, and an anonymous reviewer for helpful comments on the manuscript. We also
thank S. Ungar, C. Moyano, and the Institute for Aridlands
Research (IADIZA) for logistical support. R. Ojeda and C.
Borghi were supported by CONICET and SECYT grants PIP
4684 and PICT 03281. G. Asner was supported by a NASA
EO-1 (New Millenium Program) grant NCC5-480 and NASA
New Investigator Program grant NAG5-8709. This is CIWDGE publication 013.
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