SESolid EarthSESolid Earth1869-9529Copernicus PublicationsGöttingen, Germany10.5194/se-9-63-2018The hidden ecological resource of andic soils in mountain ecosystems: evidence from ItalyTerribileFabioterribilesci@gmail.comIamarinoMichelaLangellaGiulianohttps://orcid.org/0000-0001-7210-0906MannaPieroMiletiFlorindo AntonioVingianiSimonaBasileAngelohttps://orcid.org/0000-0002-6238-0278Department of Agricultural Sciences, University of Naples Federico II, Via Università 100, 80055 Portici (Naples), ItalyCRISP, Interdepartmental Research Centre on the Earth Critical Zone, University of Naples Federico II, Via Università 100, 80055 Portici (Naples), ItalyInstitute for Mediterranean Agricultural and Forestry Systems, National Research Council of Italy, Via Patacca 85, 80056 Ercolano (Naples), ItalyFabio Terribile (terribilesci@gmail.com)31January20189163749June201720November20171November20179August2017This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit https://creativecommons.org/licenses/by/4.0/This article is available from https://se.copernicus.org/articles/9/63/2018/se-9-63-2018.htmlThe full text article is available as a PDF file from https://se.copernicus.org/articles/9/63/2018/se-9-63-2018.pdf
Andic soils have unique morphological, physical, and chemical properties that
induce both considerable soil fertility and great vulnerability to land
degradation. Moreover, they are the most striking mineral soils in terms of
large organic C storage and long C residence time. This is especially related
to the presence of poorly crystalline clay minerals and metal–humus
complexes. Recognition of andic soils is then very important.
Here we attempt to show, through a combined analysis of 35 sampling points
chosen in accordance to specific physical and vegetation rules, that some
andic soils have an utmost ecological importance.
More specifically, in Italian non-volcanic mountain ecosystems (>600m a.s.l.) combining low slope (<21 %) and highly active green
biomass (high NDVI values) and in agreement to recent findings, we found the
widespread occurrence of andic soils having distinctive physical and
hydrological properties including low bulk density and remarkably high water
retention. Most importantly, we report a demonstration of the ability of
these soils to affect ecosystem functions by analysing their influence on the
timescale acceleration of photosynthesis estimated by NDVI measurements.
Our results are hoped to be a starting point for better understanding of the
ecological importance of andic soils and also possibly to better consider
pedological information in C balance calculations.
Introduction
Andic soils (i.e. soils with evident andosolization process) are known to
have a unique set of morphological, physical, and chemical soil properties.
Andosolization (Ugolini et al., 1988; Shoji et al., 1993) is a major soil-forming
process regardless of whether these soils meet or do not meet the soil
classification criteria for Andosol/Andisol. Among the peculiar soil
properties of andic soils are (i) high porosity (bulk density generally
<0.90gcm-3), (ii) friable consistency, (iii) high water
retention capacity, (iv) large reserves of easily weatherable mineral and
glass components, and (v) high susceptibility to liquefaction (Nanzyo,
2002; Iwata, 1968; Furuhata and Hayashi, 1980; Saigusa et al.,
1987;
Nanzyo et al., 1993). Moreover, Andosols are among the mineral soils having
the largest C storage capacity (e.g. within 100 cm of depth the
highest values found are on average 29.4 kgm-2 in Humic
Andosols; Batjes, 1996) and long C residence time (Post, 1983; Batjes, 1996;
Amundson, 2001). These peculiar properties can be ascribed to the presence of
poorly crystalline clay minerals (Basile-Doelsch et al., 2005) and fungal and
arthropodal soil organic matter (Nierop et al., 2005), but also to the specific physical and
chemical properties that make these soils some of the world's most fertile
(Leamy, 1984; Shoji et al., 1993; McDaniel et al., 2005). Despite these
characteristics associated with C storage, andic properties are simply not
considered in global carbon balance estimates (e.g. IPCC, 2006; Luo et al.,
2016). In fact in these estimates – in the best cases – the contribution of
soils (Parton et al., 1987) is limited to organic C and soil texture
parameters, ignoring other important chemical and physical properties.
Furthermore, the use of texture data for soils difficult to disperse, such as
Oxisols and Andisols (Bartoli et al., 1991; Churchman et al.,
1999; Bartoli and Burtin, 2007), introduces an analytical artefact in the
global carbon balance.
This lack of acknowledgment of andic soils is becoming more important
considering that in recent years andic soils have been found along with well-established volcanic landscapes (Shoji et al., 1993; Arnalds and Stahr, 2004;
Lulli, 2007), in many non-volcanic mountain ecosystems (NVME) throughout the
world (e.g. in Bhutan: Baumler et al., 2005; in Brazil: Dümig et al.,
2008; in California: Graham and O'Geen, 2010; Rasmussen et al., 2010; in
the Pacific Northwest, USA: McDaniel and Hipple, 2010; in Spain: Estevez et al.,
2016; and also in Italy: Iamarino and Terribile, 2008; Scarciglia et al.,
2008; Vingiani et al., 2014; Raab et al., 2017; Mileti et al., 2017).
The above lack of acknowledgment of the andic properties in carbon balance estimates
is indeed unfortunate considering that (i) 2 or 3 times more C is
stored in soils (Dixon et al., 1994) than occurs in the atmosphere as
CO2, and most importantly (ii) that Andosols have such important C
storage abilities (Torn et al., 1997) – being among the mineral soils having
the largest C stock capabilities (Batjes, 1996).
Moreover, in view of their large C storage capability, the danger of
degradation of andic soil is indeed high because they are some of the most
vulnerable soils in the world in terms of soil erosion (Arnalds, 2001) and
rapid-flow landslides (Basile et al., 2003; Terribile et al., 2007; Vingiani
et al., 2015).
Aim and rationale
All the above shows the need for a much better understanding of the importance
of andic soils and their ecological role. In this context, we focused on the
Italian territory where andic soils in Italian NVME have been extensively
addressed in terms of both their occurrence (Iamarino and Terribile, 2008)
and genesis (Mileti et al., 2013). Thus, the aim of this contribution is to
attempt to gain insight into the influence of andic soil in Italian NVME over
(i) vegetation, through remotely sensed vegetation indices, and (ii) soil
hydrological properties of utmost importance for plant growth.
To achieve the above, a combined approach has been undertaken, evaluating
chemical and hydrological properties of 35 soils having different values of
important parameters for identification of andic properties (such as
Alo+0.5Feo index and phosphate retention) in NVME
(Fig. 1), as well as the NDVI dynamics of their sites.
Location of the sampling points (black triangles).
All sites were chosen in order to select mountain soils (most of them are >600ma.s.l.) in conservative geomorphological settings (slope of
the landscape <21 %) and in areas with high primary productivity
(estimated using time series max NDVI value) from different parts of Italy
(see methods in Iamarino and Terribile, 2008).
The background to this approach is that (i) the above environmental factors
can promote andosolization and (ii) most importantly, the great
fertility of andic soils positively affects plant primary productivity in
natural ecosystems. Hence the use of remotely sensed vegetation indices (i.e.
NDVI, EVI, etc.) can be a valuable tool to address this topic. NDVI (Rouse at
al., 1973) is strongly related to photosynthetic activity and has been widely
used to estimate landscape patterns of primary production (Wang at al., 2004;
Fensholt et al., 2012) and even net primary production (Tucker and Sellers,
1986). Moreover, time series of NDVI and the related NDVI metrics have proved
to be a powerful tool for addressing plant dynamics and yield prediction in
both agriculture and natural ecosystems at different scales (Reed et al.,
1994; Zhang et al., 2003; Bolton and Friedl, 2013).
MaterialsStudy area
This specific work refers to the whole Italian mountain territory (Fig. 1).
Italy lies between the 35 and 47∘ north parallel and is located
in the middle of the temperate zone of the Northern Hemisphere. It has an
extremely complex territory. Two major mountain chains occupy more than
35 % of the entire national surface: (i) the Apennines, with
predominantly sedimentary rocks, spanning almost the entire Italian
territory from S to N, with altitude reaching 2900 ma.s.l. (Gran
Sasso), and (ii) the Alps, having predominantly metamorphic and igneous rocks,
separating Italy from the rest of Europe, with maximum altitude over
4000 ma.s.l. (Monte Bianco, Monte Rosa, Monte Cervino). The remaining
territory is mainly occupied by hilly systems (about 40 %) including
those portions of the Apennines slowly degrading towards the sea, both at east and
west. Plain systems only occupy just over 20 % of the entire territory.
In general terms the climate – known to be mild (well known as
Mediterranean) – is heavily influenced by the sea. With respect to Italian
mountain areas it can be assumed that for soil climate (Soil Survey Staff,
2014) the mean moisture regime is udic (it may become ustic at lower
elevation), whereas the mean temperature regime is generally mesic (it may
become frigid and cryic at high elevation) (Costantini et al., 2004, 2013).
Soil sampling
Soil sampling was designed to collect fertile mountain soils in conservative
geomorphological settings from different parts of Italy. The soils were
sampled from (i) mountain environments (most soils were sampled >600ma.s.l. estimated by a 270 m spatial resolution DEM
obtained from the Italian Geological Service), (ii) geomorphological
conservative landscapes with moderately low slopes (slope <21 %
evaluated by the DEM) to minimize the risk of sampling eroded soils, and
finally (iii) areas with high primary productivity estimated using the max
NDVI value (NDVI threshold 0.65) obtained from MODIS Images MVC
(https://modis.gsfc.nasa.gov/data/atbd/atbd_mod13.pdf) at 230 m
spatial resolution for the period 28 July–13 August 2014 (which is a strong
vegetative growth period in Italy). Morphological and chemical data
(aggregated) of these pedons (28 soils after the selection reported in
Sect. 2.3), along with the background to this methodology, are given in
Iamarino and Terribile (2008). These information were further supplemented
with data of seven additional soils: five newly surveyed and analysed soils, and
two
soils reported in the scientific literature and consistent with the
previously stated rules. In detail, regarding the soils from the literature,
one soil concerns research work in the Abruzzo region (Frezzotti and Narcisi,
1996) and
one soil was retrieved from the ISRIC database (ISRIC, 2005).
NDVI and land use data
In-depth analysis on time-based NDVI was performed using a MODIS VI algorithm,
which operates on a per-pixel basis and relies on multiple observations over
a 16-day period to generate a maximum composite vegetation index (VI) based
on the maximum value compositing (MVC) technique. In order to extract the NDVI
metrics (maximum NDVI, integrated NDVI sum over the growing period,
acceleration of photosynthesis or rate of green-up, NDVI derivatives) some
pre-processing of the data were necessary (i.e. cloud contamination)
following established procedures (Reed et al., 1994). After such processing,
about 15 % of the NDVI observations had to be discarded and the
corresponding data set was excluded from this work. This is related to
well-known problems in remote sensing, due to high and persistent cloud
contamination and in some cases also to the presence of rock outcrops inside
the area of the investigated pixels.
NDVI data were chosen to incorporate years having marked contrasting climate
(wet/dry) and then, potentially contrasting vegetation indices trends and
metric. After performing an analysis of the climatic database published by
the Italian Ministry of Environment for the whole country
(http://www.isprambiente.gov.it/), we chose the very dry year
2003, the very wet year 2014, and the 2005 year having an intermediate
rainfall. More specifically, these years have the following climatic trends
(values below are ranked in the order 2003, 2005, 2014 respectively):
similar yearly mean temperature: 13, 12, 13 ∘C;
evident differences in yearly mean maximum temperature: 36, 35, 33 ∘C;
most importantly, marked differences in yearly cumulated rainfall 766 mm
(SD: 172 mm), 870 mm (SD: 231 mm), 1143 mm (SD: 540 mm);
marked differences in standardized precipitation index (McKee et al., 1993),
varying in the range -0.5–0.5; 0.5–0.0;
1.0–2.0. This index is a well-known simplified indicator for monitoring drought and periods of anomalously wet events and it shows
droughts for year 2003 but also for 2005.
The CORINE Land Cover (CLC hierarchical levels 4, 5) classification (EEA, 2007, and subsequent update EEA, 2012) was used to produce a preliminary evaluation of the main land covers.
CLC classes were locally validated for each of the sampled
sites. The reported land cover classes of chestnut, beech, and broadleaf oak
must be considered classes of land cover where these species are dominant (>80 %) but not exclusive. The grassland class refers to natural grassland
having both continuous (tree and shrubs <15 %) and discontinuous
(tree and shrubs 15–40 %) pattern.
Methods
All the statistical analysis was performed using two-tailed tests; ANOVA
(Tamhane method by Yosef and Tamhane, 2008) was performed for multiple
comparisons of means. The reported test of significance for the latitude was
performed on a “metres from the equator” basis.
At each site a soil profile was dug, described, and sampled (FAO, 2006). Bulk
samples were collected (trowel) from all the soil horizons (126 horizons) for
chemical analyses. Steel cylinders of about 200 cm3 were carefully
inserted in the selected A and B horizons by an impact-absorbing hammer in
order to collect undisturbed soil samples for hydrological analysis. The
samples were collected on representative pedons (see Table S2 in the
Supplement) of the three encountered soil types (Andosols, Cambisols,
Phaeozems).
Bulk samples after air drying (25 ∘C) for 2 weeks were sieved to
less than 2 mm and used for further analyses (USDA-NRCS, 2004):
organic matter was determined following the Walkley–Black procedure (Walkley,
1947); Al / Fe / Si in the poorly crystalline oxides/hydroxides and
in the organic matter were extracted with ammonium oxalate
(Feo, Alo, Sio,) treatment at pH =3
(Schwertmann, 1964; Blakemore et al., 1987) and their contents were determined
by inductively coupled plasma atomic emission spectroscopy (ICP-AES) Varian
Liberty model 150. Values of Al and Fe extracted with ammonium oxalate were
used to calculate the Alo+0.5Feo index. This index is
the key parameter for the assessment of andic soil properties (IUSS Working
Group WRB, 2015; SSS, 2014). Then we use it to evaluate the andosolization
process. The Alo+0.5Feo index can be considered weak in
the range 0.4–1.0 %, moderate in the range 1.0–2.0 % and
well expressed over 2.0 %. The value of 0.4 % of
Alo+0.5Feo index is the “key out” requirement for
entering in the Andosols both in WRB (IUSS Working Group WRB, 2015) and USDA
Soil Taxonomy (SSS, 2014) classifications. Phosphate retention was determined
according to Blakemore et al. (1987).
In order to simplify the comparison between soil features and land use or
NDVI metrics it was necessary to aggregate chemical data obtaining a single
representative value for the whole soil. Therefore, the contents of
Alo+0.5Feo, P retention, and organic carbon were
weighted according to horizon thickness for each of the pedons. Soils were
classified using the WRB system (IUSS Working Group WRB, 2015).
With respect to the hydrological analysis, 10 experimental points of the soil
water retention curve θ(h), ranging from saturation to
-30 kPa of potential, were determined through the use of a tension
table and five points at -100, -500, -800, -1200, and -1500 kPa
were determined through use of a pressure plate apparatus (Dane and Hopmans,
2002). The soil samples were then dismantled and dried for 24 h in
the oven at 105 ∘C in order to determine the water content from the
weight data set and the bulk density.
The water retention experimental data were parameterized according to the
unimodal θ(h) relationship proposed by van Genuchten (1980),
expressed here in terms of the scaled water content:
Se=[1+(α|h|)n]1-1/n,
with Se=(θ-θr)/(θ0-θr), and in which α (cm-1) and n are curve
shape parameters. θ0 and θr respectively
represent the saturated water content (at h=0) and the residual water
content, and may either be fixed or treated as parameters to be optimized.
To obtain a synthetic description of water retention for an easy comparison
with soil chemical analysis, we used a numeric index (IRI) integrating the
whole water retention function (Basile et al., 2007).
The integral retention index, IRI, is defined by
IRI=1wp∫0.1wpθd(log10|h|),
where wp=4.2 is the wilting point. This adimensional index (0<IRI<1) represents the average value of the function θ(log10|h|) on the interval [0,wp] and allows simple
comparisons of the whole water retention by coalescing it in a single
characteristic value.
Results and discussionSoil and landscape
The outcome results of our procedure in terms of soil analysis and soil
classification (IUSS Working Group WRB, 2015) show that Andosols and
Cambisols alone account for more than 80 % of the observations. Most
interestingly, despite differences in soil classification, in the vast
majority of cases (about two-thirds) there is a moderate and well-expressed
andosolization process as estimated by Alo+0.5Feo index
(Fig. 2). Iamarino and Terribile (2008) have reported further data as
horizon-based means on these pedons proving the general absence of
podsolization and depicting a scenario where andosolization is the main soil
process.
Soil type (IUSS Working Group, WRB, 2015) plotted against
Alo+0.5Feo % (weighted mean according to
horizon thickness for each of the studied pedons). The value of 0.4 % in Alo+0.5Feo is the “key out”
requirement for entering in the Andosol (and/or Andisol) classes both in WRB (IUSS Working Group WRB, 2015) and USDA Soil Taxonomy
(SSS, 2014) classifications. The Alo+0.5Feo index can be considered weak in the range 0.4–1.0, moderate in the
range 1.0–2.0, and well expressed over 2.0.
Main geographical, land cover, soil and NDVI features of the studied soils.
aα<0.05, bα<0.01 (two-tailed test).
n, number of observations; broad., broadleaf species. The symbol
± after the mean value shows the SD. The (n) values refer to the number
of observation available for NDVI analysis (see methods); in some sites
because of strong cloud contamination not all the data could be used for NDVI
analysis. The upper part of the table refers to soil types (IUSS Working
Group WRB, 2015) and the lower part refers to land cover (CORINE Land Cover
classes by APAT, 2000) after site validation. NDVI MODIS metrics refer to
a whole 2003, 2005, 2014 time series (16-day step).
Table 1 reports the main geographical and land cover features of the
studied soils along with NDVI metrics over three contrasting climatic years.
As the data show (Table 1), Andosols, Cambisols, and Phaeozems occur at
similar latitudes and elevations and beech, oak, chestnut, and grassland are
the main land use. More specifically, the main land cover unit associated
with Andosols and Cambisols is the beech forest, but they also occur with
less frequency in other land uses (grassland, chestnut, and oak), whereas
Phaeozems are mostly associated with grassland.
In all years, in sites where Andosols occur, the mean value of max NDVI,
integrated sum of NDVI, and NDVI green-up is always the highest compared to
other soil classes. This finding is very interesting and consistent with the
high fertility of these soils. NDVI max and NDVI integrated sum
(June–August) show significant differences between the different land cover
classes, following clear diversity in plant biology.
The analysis of NDVI trend among the 3 investigated years shows that, as
expected, NDVI max and NDVI sum values in the wetter 2014 (cumulated
rainfall: 1143 mm) are always higher than in the drier 2003 and 2005
(cumulated rainfall 766 and 870 mm, respectively). Differently, the
NDVI green-up values are typically higher in 2003–2005 as compared to 2014
and this NDVI green-up difference is even more pronounced moving towards the
most andic soils (Andosols). All the above clearly suggest that andic soils
– typically having higher water storage as compared to other soils –
enabled the production of a higher green-up. Here we must also add that further
analysis would be required to evaluate at each site trends in soil water
storage and temperature before the green-up phase.
Main features of the studied soils.
Soils/landnSoil depthStructure of surface AOrganic CAlo+0.5FeoP retentioncover(solum) meanhorizon modemeanmeanmean(cm)%‰%%All soils3588±37Friable Gr. Cr. medium3738.0±23.02.0±1.762.9±26.0Andosols13115b±34Friable Gr. Cr. medium6945.3±26.63.6b±1.890.2b±14.6Cambisols1675±31Friable Gr. Cr. fine; Cr. coarse2127.3±15.11.0±0.446.9±17.2Phaeozems666b±21Friable Gr. Cr. medium5750.9±22.81.0±0.449.1±16.5Beech11102±28Friable Gr. Cr. medium4140.6±22.92.6±1.783.6±21.6Castanea1095±38Friable Gr. Cr. coarse4023.5±10.81.8±2.142.7±21.9Oak broad.670±55Friable Gr. Cr. Fine2534.2±22.31.8±1.861.3±27.5Grassland875±25Friable Gr. Cr. medium5055.6±25.41.5±0.757.5±16.7
aα<0.05, bα<0.01, (two-tailed
test). n, number of observations; broad., broadleaf species; Gr.,
granular; Cr., crumb; fine: <2mm; medium: 2–5 mm;
coarse: 5–10 mm; very coarse: >10mm. The symbol ±
after the mean value shows the SD. The upper part of the table refers to soil
types (IUSS Working Group WRB, 2015) and the lower part refers to land cover
(CORINE Land Cover classes, by APAT, 2000) after site validation. Chemical
analyses are integrated over soil depth (solum).
Table 2 reports the main features of the studied soils. The soil data
show that all soils are deep, and have a friable granular/crumb soil structure
at the surface. Moreover, organic C, the Alo+0.5Feo
index (always higher than 0.4 %, thus compatible with
vitric/silandic/aluandic), and P retention range from moderate to high (mean
org. C: 3.8 %; mean Alo+0.5Feo %: 2.0 %;
mean P ret: 63 %). Of all the soils, Andosols have the highest (i) soil
depth, (ii) Alo+0.5Feo % (weighted mean), and
(iii) P retention % (weighted mean). Phaeozems have the highest organic
C (weighted mean) content.
Although Alo+0.5Feo and P retention values in Andosols
differ significantly, there are no such important differences between the
various land cover classes, suggesting that in our case study vegetation is
of little importance in determining the andosolization process – but of course
this finding cannot be extrapolated to other settings. In fact there are many
cases where vegetation type has a very close connection with soil type or
soil properties (e.g. Ciarkowska and Miechowka, 2017).
Scatterplot between Alo+0.5Feo index and
integrated retention index (IRI) determined in reference A and
B horizons. Coefficient of determination R2 along with points (n) is reported.
Scatterplot between Alo+0.5Feo index (weighted
mean Alo+0.5Feo % according to
horizon thickness for each of the studied pedons) and the maximum value of the NDVI derivative. From left to right: grassland,
beech, oak, and chestnut. From bottom to top: year 2003, 2005, and 2014. The dashed lines show the linear regression for each land
cover. Coefficient of determination R2 along with data points (n) is reported for each panel.
In general terms, the investigated soils can be considered rather homogeneous
in their morphological, chemical, and physical properties, although they occur
in very diverse geological and climatic mountain ecosystems; a preliminary
cautious estimate (Iamarino, 2005) of their distribution in Italy has shown
their presence on about 7×105 ha.
This finding parallels similar ones in other parts of the world where mountain
andic soils (not necessarily Andosols) have been reported in Bhutan (Baumler
et al., 2005), in Brazil (Dümig et al., 2008), in California (Graham and
O'Geen, 2010; Rasmussen et al., 2010), the Pacific Northwest, USA (McDaniel and
Hipple, 2010), NW Spain (Estevez et al., 2016), and also in Italy (Iamarino and
Terribile, 2008; Scarciglia et al., 2008; Vingiani et al., 2014).
Main physical parameters of selected soil horizons.
Mean bulk Mean WC Mean WC IRI density at pF =4.2at pF =0Horizonsngcm-3ncm3cm-3ncm3cm-3n–All350.87±0.21830.25±0.09160.79±0.10160.51±0.06A160.79±0.17550.27±0.09070.85±0.07070.55±0.04B190.93±0.22270.19±0.07100.75±0.10100.48±0.06
n: number of observations; WC: volumetric water content; IRI:
integrated water retention index. The symbol ± after the mean value shows
the SD. The table reports for soil horizons A and B mean bulk density, water
retention at two different values of pF (0 and 4.2) corresponding to the
pressure head of -0.1 and -1500 kPa, respectively, and the
integrated retention index (IRI) which coalesces the water retention curve in
a single value (Basile et al., 2007).
Andosolization process and soil hydrology
Given the finding on the importance of andic soils (albeit not Andosols) in
Italian non-volcanic uplands, the question is raised as to whether the
andosolization process is also connected to those physical properties
considered of key importance for plant growth, namely bulk density and water
retention due to their crucial role in water availability. In order to
address this issue, a selection of horizons A and B of the previously
investigated soils was analysed. The data (in Table 3) clearly show the
occurrence of very porous soils (low bulk density) and very high water
retention capability over the complete range of pressure head values. Surface
A horizons generally have lower bulk density and higher water retention (as
shown in Table 3) than the subsoil B horizons, which must be ascribed to the
contribution of organic carbon in improving the soil structure (Kutilek and
Nielsen, 1994) and therefore increasing water retention and decreasing bulk
density.
The positive high correlation (Fig. 3) between
Alo+0.5Feo index and IRI – determined in selected
A and B horizons – indicates that the more advanced the andosolization process, the
higher the integrated water retention, and hence very good soil physical
properties. This result is already established (Basile et al., 2007) but only
for soils having Alo+0.5Feo larger than 2 %, while
there is no positive evidence for soils having much lower
Alo+0.5Feo index values (e.g. in the range
0.4–2.0 %). All the above emphasizes that poorly ordered clay minerals
greatly affect soil physical properties even at moderate to low content,
which in turn could greatly affect water storage and then water availability
for plant ecosystem growth.
Such finding is important because it does not refer to soils in a unique
location but rather to a large variety of soils developed at different
latitudes and over different bedrocks and land uses.
aα<0.05bα<0.01 (two-tailed
test). Correlation (r Pearson) performed between andosolization process
(Alo+0.5Feo %) and NDVI metrics for each of the observed
land cover classes (CORINE Land Cover classes, by APAT, 2000) after site
validation. The chemical analyses are integrated over soil depth (solum).
Andosolization process and elevation against NDVI metrics
To investigate this question further, bivariate correlation (Table 4) and
regression analyses (Fig. 4) were performed between
Alo+0.5Feo index and NDVI metrics for each of the
observed land cover classes. In the vast majority of climatic years and land
cover classes, the Alo+0.5Feo index has a positive
correlation with NDVI metrics but, generally, not significant for (i) NDVI
max value and (ii) integrated sum of NDVI (Table 4). By contrast, rather
astonishingly, the Alo+0.5Feo index is always well correlated
with the rate of green-up (first derivative of NDVI); this correlation is
significant for the driest years 2003 and 2005 and not for the wettest 2014.
Highest significant correlations are found when each land use is considered
separately. For instance, in 2003 the Pearson's correlation coefficient r
between Alo+0.5Feo index and green-up is 0.82 for beech
and 0.83 for grassland, while in the year 2005 it is 0.86 for beech and 0.90 for
grassland. These results show that beech and grassland are the land use types where the ecological importance of the andosolization process is more evident;
furthermore, the data producing this high correlation span a high range
of Alo+0.5Feo index values (see Fig. 4). This
performance could be explained considering that (i) beech and grassland are
more spatially homogeneous land uses as compared to oak broadleaves (e.g. oak
land use is more heterogeneous, being a potential mixture of very different
species, sometimes even including grassland), (ii) beech and grassland land
uses are less affected by strong land management practices as compared to
chestnut (which in the Italian landscape is often managed as coppice), and
(iii) moreover, it is well known that beech is very susceptible to severe
water stress (Teissier et al., 1981).
All the above can well explain the more responsive NDVI signal of beech and
grassland to water stress as compared to oak broadleaves and chestnut.
This is the first time that a close connection between NDVI metrics and the
andosolization process has been shown. This result can have important consequences
in terms of better understanding the ecology of Italian mountain ecosystems.
Differently, in many different environments often a positive variation of
NDVI against elevation has been reported (Zhan et al., 2012; Walsh et al.,
2001; Chen et al., 2006). Thus, since the andosolization process has been
assessed in mountain areas, it was important to test whether the observed
relationship between NDVI metrics and the Alo+0.5Feo index
disguises a possibly even closer relationship between NDVI metrics and
elevation.
In relation to this, Table 4 shows that the correlation between NDVI metrics and
elevation is confused, with much lower r values as compared with
that between NDVI and the Alo+0.5Feo index. Overall, both
the low and negative r values between many NDVI metrics and elevation show
that altitude (and possibly its covariates, i.e. temperature and rainfall) do
not adequately explain variations in green active biomass parameters.
Moreover, r values between Alo+0.5Feo index and
elevation show very low values (e.g. r=0.16 for all sites) and do not
show any consistent trend (data not shown).
Thus we can state that, for the first time, here the
ecological importance of the andosolization process over different land use
canopies in a large part of the Italian mountains has been demonstrated. Most probably this finding is
connected to the unique hydropedological properties of these soils. In
fact, this result is especially evident in the driest years (2003, 2005),
while it is less important in the wettest year (2014), suggesting that the water
storage of these soils may play a key controlling role.
Our findings are also important to better acknowledge the occurrence and the
importance of andic soils in C sequestration/storage estimates. All our soils
had a high organic C content (mean 3.8 %), regardless of whether they were
Andosols or Cambisols or Phaeozems.
Indeed, deep andic soils have much higher (Batjes, 1996; Matus et al., 2014)
mean organic C content of (i) deep Regosols (3.1 %), (ii) Cambisols
(5.0 %), and (iii) still higher than Humic and Leptic Podzols
(respectively 10.3 and 12.8 %) which are considered as the main soil
types as observed in previous soil inventories (Mancini, 1966; EuDASM, 2007)
of the investigated landscapes.
Conclusive remarks and future perspectives
Our study shows a close relationship between the andosolization process and NDVI
metrics and especially with metrics describing the acceleration of photosynthesis
(green-up). This finding demonstrates that there is still much to be
understood about the ecological importance of soils in mountain ecosystems, at
least for the Italian territory.
Moreover, acknowledgment of the importance of these soils may also have
consequences in terms of both soil protection in mountain environments (andic
soils are known to be among the most vulnerable soils in the world in terms
of soil erosion) and for better understanding of the impact of climate change.
In this respect, this study suggests that the unique water retention features
of the andic soils play an important ecological role when comparing
contrasting climatic years.
The above results are perhaps even more pronounced considering that the current
study employed a rather simplified NDVI approach including data at coarse
resolution (MODIS) and no algorithm to mitigate the well-known saturation
effect of NDVI (Buschmann and Nagel, 1993). Thus it is likely that in future,
better focused studies may demonstrate even better and closer relationships
between andic soils and green biomass indicators.
Generally, our results indicate the large potential in using remote sensed
vegetation index metrics to ameliorate soil spatial inventories. A question
still arises as to whether the general absence of strong significant
correlation between Alo+0.5Feo index with both “NDVI
max” and “integrated NDVI sum” may be caused by the quoted NDVI saturation
effect.
Regarding our results, we want to also emphasize that the importance of
andosolization process in affecting ecosystem function is undoubtedly poorly
expressed by soil classification: in fact strict classification rules dealing
with how/where to expect “andic properties” (IUSS Working Group WRB, 2015:
starting within 25 cm from the soil surface; SSS, 2014: within
60 cm) can lead to non-Andosols with very high
Alo+0.5Feo index. However, the
Alo+0.5Feo index, rather than soil class criterion, seems
to better explain variability in NDVI metrics and plant ecosystem dynamics,
and this finding must be of major interest for ameliorating soil
classification.
Although the importance of this key mineral soil in Italian mountain
ecosystems is demonstrated to produce in turn large organic C storage and
long C residence time, proper implementation of these new data in terms of C
balance calculation, reducing uncertainties in carbon sequestration estimates
and carbon sink national ecosystems inventory, is indeed a major issue to be
addressed.
Moreover, the given wide recognition of andic soils has important
consequences both in terms of C sequestration potentialities and C loss risks
associated with this finding. Suitable land management techniques are then
required to match the exclusive properties and problems connected to the
presence of these soils.
Considering the many recent finds of andic soils worldwide, it is of great
importance to ascertain whether a wider occurrence of this hidden resource
applies also to mountain environments in other parts of the world.
Finally, we must emphasize that this study – focused on only 35 points over
the Italian landscape – is a methodological basis for producing statements
that could be valid at the national scale where, accordingly, much more data
are indeed required.
Data used in this paper are reported in the Supplement. Moreover in this paper we have used soil data of some specific pedon;
these data have been obtained by selected publication already quoted in this paper.
The Supplement related to this article is available online at https://doi.org/10.5194/se-9-63-2018-supplement.
The authors declare that they have no conflict of
interest.
Acknowledgements
We would like to thank Andrea Vacca, Giuseppe Maugeri and Antonio Mingo for helping us with sampling at
some of the sites; Nadia Orefice and Roberto De Mascellis for performing the
hydrological analysis; and Luciana Minieri for producing some
of the chemical analysis.
Edited by: Marc Oliva
Reviewed by: two anonymous referees
References Amundson, R.: The carbon budget in soils, Annu. Rev. Earth Pl. Sc., 29, 535–562, 2001. Arnalds, O. and Stahr, K.: Volcanic soil resources: occurrence, development and properties, Catena (special issue) 56,
56, 1–2, 2004. Arnalds, O., Thorarinsdottir, E. F., Metusalemsson, S., Jonsson, A., Gretarsson, E., and Arnason, A.: Soil erosion in
Iceland, Soil Conservation Service and Agricultural Research Institute, Reykjavik, Iceland, 2001. Bartoli, F. and Burtin, G.: Organo-mineral clay and physical properties in COST 622 European volcanic soils, in: Soils of
Volcanic Regions in Europe, edited by: Arnalds, O. et al., Springer Verlag, Berlin Heidelberg, 469–491, 2007. Bartoli, F., Burtin, G., and Herbillon, A.: Disaggregation and clay dispersion of Oxisols: Na-resin, a recommended
methodology, Geoderma, 49, 301–307, 1991. Basile, A., Mele, G., and Terribile, F.: Soil hydraulic behaviour of a selected benchmark soil involved in the landslide of
Sarno 1998, Geoderma, 117, 331–346, 2003. Basile, A., Coppola, A., De Mascellis, R., Mele, G., and Terribile, F.: A comparative analysis of the pore system in COST
622 volcanic soils by means of soil hydrology and image analysis, in: Soils of Volcanic Regions in Europe, edited by:
Arnalds, O., Bartoli, F., Buurman, P., Oskarsson, H., Stoops, G., and Garcia-Rodeja, E., Springer Verlag, Berlin Heidelberg, 493–514, 2007. Basile-Doelsch, I., Amundson, R., Stone, W. E. E., Masiello, C. A., Bottero, J. Y., Colin, F., Masin, F., Borschneck, D.,
and Meunier, J. D.: Mineralogical control of organic carbon dynamics in a volcanic ash soil on la Réunion, Eur. J. Soil Sci., 56,
689–703, 2005. Batjes, N. H.: Total carbon and nitrogen in the soils of the world, Eur. J. Soil Sci., 47, 151–163, 1996. Baumler, R., Caspari, T., Totsche, K. U., Dorji, T., Norbu, C., and Baillie, I. C.: Andic properties in soils developed
from nonvolcanic materials in Central Bhutan, J. Plant Nutr. Soil Sc., 168, 703–713, 2005. Blakemore, L. C., Searle, P. L., and Daly, B. K.: Methods for Chemical Analysis of Soils, New Zealand, Soil Bureau,
Scientific Report 80, 1987. Bolton, D. K. and Friedl, M. A.: Forecasting crop yield using remotely sensed vegetation indices and crop phenology
metrics, Agr. Forest Meteorol., 173, 74–84, 2013. Buschmann, C. and Nagel, E.: In vivo spectroscopy and internal optics of leaves as basis for remote sensing of vegetation,
Int. J. Remote Sensing, 14, 711–722, 1993. Chen, Y., Xu, X., and Zhang, D.: Correlation of vegetation distribution and terrain factors in northwestern of Sichuan
Longmen mountain [J], Chinese J. Ecol., 25, 1052–1055, 2006.
Churchman, G. J., Bartoli, F., Burtin, G., Rouiller, J., and Weismann, D.: Comparison of methods using sodium for the size fractionation of soil, 11th Int Clay Conf Proc, 15–21 June 1997, Ottawa (Canada), 331–338, 1999. Ciarkowska, K. and Miechówka, A.: The role of bilberry and Alpine lady-fern in soil formation within the Carpathian
subalpine spruce forest stands, Geoderma, 305, 162–172, 2017.Costantini, E. A. C., Urbano, F., and L'Abate, G.: Soil Regions of Italy, available at:
www.soilmaps.it (last access: 12 January 2018), 2004. Costantini, E. A. C., Fantappie' M., and L'Abate, G.: Climate and pedoclimate of Italy, in: The Soils of Italy, World
Soils Book Series, Springer Science, Business Media, Dordrecht, 2013. Dane, J. H. and Hopmans, J. W.: Water retention and storage, in: Methods of Soil Analysis: Part 4 – Physical Methods,
edited by: Dane, J. K., Topp, G. C., SSSA Book Ser. 5. SSSA, Madison, WI, pp. 671–720, 2002. Dixon, R. K., Brown, S., Houghton, R. A., Solomon, A. M., Trexler, M. C., and Wisniewski, J.: Carbon pools and flux of
global forest ecosystem, Science, 263, 185–190, 1994 Dümig, A., Schad, P., Kohok, M., Beyerlein, P., Schwimmer, W., and Kögel-Knabner, I.: A mosaic of nonallophanic
Andosols, Umbrisols and Cambisols on rhyodacite in the southern Brazilian highlands, Geoderma, 145, 158–173, 2008.EEA (European Environmental Agency): CLC2012Addendum to CLC2006 Technical Guidelines, available at: https://land.copernicus.eu/user-corner/technical-library/Addendum_finaldraft_v2_August_2014.pdf, last access: 12 January
2018. Estevez, M. A., Cid, and McNunez, R. P.: Poorly-crystalline components in aggregates from soils under different land use
and parent material, Catena, 144, 141–150, 2016.EuDASM: European Digital Archive on Soil Maps of the World, available at:
http://www.isric.org/projects/eudasm-european-digital-archive-soil-maps
(last access: 12 January 2018), February 2007. FAO (Food and Agriculture Organization): Guidelines for Soil Profile Description (Revised), 4th Edn., Rome, 2006. Fensholt, R. and Proud, S. R.: Evaluation of Earth Observation based global long term vegetation trends – comparing GIMMS
and MODIS global NDVI time series, Remote Sensing Environ., 119, 131–147, 2012. Frezzotti, M. and Narcisi, B.: Late quaternary tephra-derived paleosols in central Italy's carbonate Apennines range:
stratigraphical and paleoclimatological implications, Quaternary Int., 34–36, 147–153, 1996. Furuhata, A. and Hayashi, S.: Relation between soil structure and soil pore composition: case of volcanogenous soils in
Tokachi district, Res. Bull. Hokkaido Natl. Agric. Exp. Stn., 126, 53–58, 1980. Graham, R. C. and O'Geen, A. T.: Soil mineralogy trends in California landscapes, Geoderma, 154, 418–437, 2010. Iamarino, M.: Andosuoli e suoli con proprietà andiche in aree non vulcaniche: un approccio a scala nazionale, PhD
Thesis (Gestione e Valorizzazione delle risorse agro-forestali; XVII ciclo), Università degli Studi di Napoli Federico II,
Napoli, Italy, 2005. Iamarino, M. and Terribile, F.: The importance of andic soils in mountain ecosystems in Italy: a pedological
investigation, Eur. J. Soil Sci., 59, 1284–1292, 2008.IPCC: Guidelines for National Greenhouse Gas Inventories Volume 4 Agriculture, Forestry and Other Land Use, available at:
http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html (last access: 12 January 2018), 2006. IUSS Working Group WRB: World Reference Base for Soil Resources 2014, update 2015 International soil classification system
for naming soils and creating legends for soil maps, World Soil Resources Reports No. 106, FAO, Rome, 2015. Iwata, S.: Soil moisture in volcanic ash soils. Soil physical conditions and plant growth, Japan, 18, 18–26, 1968. Kutilek, M. and Nielsen, D. R.: Soil Hydrology, Catena Verlag, Geoscience Publ., Amsterdam, 370 pp., 1994. Leamy, M. L.: Andisols of the world, in: Congreso Internacional de Suelos Volcánicos. Comunicaciones Secretariado de
Publicaciones, La Universidad de La Laguna (Ed.), La Laguna, Spain, Serie Informes, 13, 368–387, 1984. Lulli, L.: Volcanic soils in Italy, in: Soils of Volcanic Regions in Europe, edited by: Arnalds, O., Bartoli, F., Buurman, P., Oskarsson, H., Stoops, G., and Garcia-Rodeja, E., Springer
Verlag, Berlin Heidelberg, 51–67, 2007.
Luo, Y., Ahlstrom, A., Allison, S. D., Batjes, N. H., Brovkin, V., Carvalhais, N., Chappell, A., Ciais, P., Davidson, E. A., Finzi, A.,Georgiou, K., Guenet, B.,
Hararuk, O., Harden, J. W., He, Y., Hopkins, F., Jiang, J., McGuire, A. D., Parton, W., Peng, C., Randerson, J. T., Salazar, A., Sierra, C. A., Smith, M. J.,
Tian, H., Todd-Brown, K. E. O., Torn, M., van Groenigen, K. J., Wang, Y. P., West, T. O., Wei, Y., Wieder, W. R., Xia, J., Xu, X., Xu, X., and Zhou, T.: Towards more realistic projections of soilcarbon dynamics by earth system models, Global Biogeochem. Cy., 30,
40–56, 2015. Mancini, F.: Breve commento alla carta dei suoli d'Italia in scala 1:1.000.000, Ed. Coppini, Firenze, 80 pp., 1966. Matus, F., Rumpel, C., Neculman, R., Panichini, M., and Mora, M. L.: Soil carbon storage and stabilization in andic soils:
a review, Catena, 120, 102–110, 2014. McDaniel, P. A. and Hipple, K. W.: Mineralogy of loess and volcanic ash eolian mantles in Pacific Northwest (USA)
landscapes, Geoderma, 154, 438–446, 2010. McDaniel, P. A., Wilson, M. A., Burt, R., Lammers, D., Thorson, T. D., Mcgrath, C. L., and Peterson, N.: Andic soils of
the inland Pacific Northwest, USA: properties and ecological significance, Soil Sci., 170, 300–311, 2005.
McKee, T. B., Doesken, N. J., and Kleist, J.: The Relationship of Drought Frequency and Duration to Time Scales, Proceedings of the 8th Conference on Applied Climatology, 17–22 January 1993,
Anaheim, CA. Boston, MA, American Meteorological Society, 1993. Mileti, F. A., Langella, G., Prins, M. A., Vingiani, S., and Terribile, F.: The hidden nature of parent material of Italian
mountain ecosystems, Geoderma, 207–208, 291–309, 2013. Mileti, F. A., Vingiani, S., Manna, P., Langella, G., and Terribile, F.: An integrated approach to studying the genesis of
andic soils in Italian nonvolcanic mountain ecosystems, Catena, 159, 35–50, 2017. Mizota, C. and van Reeuwijk, L. P.: Clay mineralogy and chemistry of soils formed in volcanic material in diverse climatic regions, Soil Monograph 2, Wageningen: ISRIC, 186 pp., 1993. Nanzyo, M.: Unique properties of volcanic ash soils, Global Environ. Res.,
6, 83–97, 2002. Nanzyo, M., Shoji, S., and Dahlgren, R.: Physical characteristics of volcanic ash soils, in: Volcanic Ash Soils. Genesis,
Properties and Utilization, edited by: Shoji, S., Nanzyo, M., and Dahlgren, R., Elsevier, Amsterdam, London, New York, Tokyo,
189–207, 1993.Nierop, K. G. J., van Bergen, P. F., Buurman, P., and van Lagen, B.: NaOH and Na4P2O7 extractable organic
matter in two allophanic volcanic ash soils of the Azores Islands – a pyrolysis GC/MS study, Geoderma, 127, 36–51, 2005. Parton, W., J., Schimel, D. S., Cole, C. V., and Ojima, D. S.: Analysis of factors controlling soil organic matter levels
in Great Plains grassland, Soil Sci. Soc. Am. J., 51, 1173–1179, 1987. Post, W. M.: Organic carbon in soils and the global carbon cycle, in: The Global Carbon Cycle, edited by: Heinmann, M.,
Springer, Berlin, 277–302, 1983. Raab, G., Halperna, D., Scarciglia, F., Raimondi, S., Nortond, K., Pettkee, T., Hermanne, J., de Castro Portesa, R., and
Aguilar Sanchez, A. M.: Linking tephrochronology and soil characteristics in the Sila and Nebrodi mountains, Italy, Catena, 158,
266–285, 2017. Rasmussen, C., Dahlgren, R. A., and Southard, R. J.: Basalt weathering and pedogenesis across an environmental gradient in
the southern Cascade Range, California, USA, Geoderma, 154, 473–485, 2010. Reed, B. C., Brown, J. F., VanderZee, D., Loveland, T. R., Merchant, J. W., and Ohlen, D. O.: Measuring phenological
variability from satellite imagery, J. Veg. Sci., 5, 703–714, 1994. Rouse, J. W., Haas, R. H., Schell, J. A., Deering, D. W., and Harlan, J. C.: Monitoring the Vernal Advancement of
Retrogradation of Natural Vegetation, NASA/GSFC type II, Progress Report RSC 1978-1, Greenbelt,
MD, 371 pp., 1973.
Saigusa, M., Shoji, S., and Nakaminami, H.: Measurement of water retention at 15 bar tension by pressure membrane method and available moisture of Andosols, Jap. J. Soil Sci. Plant Nutr., 58, 374–377,
1987 (in Japanese). Scarciglia, F., De Rosa, R., Vecchio, G., Apollaro, C., Robustelli, G., and Terrasi, F.: Volcanic soil formation in
Calabria (southern Italy): the Cecita Lake geosol in the late Quaternary geomorphological evolution of the Sila uplands,
J. Volcanol. Geoth. Res., 177, 101–117, 2008. Shoji, S., Nanzyo, M., and Dahlgren, R.: Volcanic Ash Soils: Genesis, Properties and Utilization, Development in Soil
Science, Elsevier, Amsterdam, vol. 21, 288 p., 1993. Soil Survey Staff: Keys to Soil Taxonomy, 12th Edn., USDA-Natural Resources Conservation Service, Washington, DC, 2014. Schwertmann, U.: Differenzierung der Eisenoxide des Bodens durch photochemische Extraktion mit saurer
Ammoniumoxalat-Lösung, Z. Pflanzenernähr., 105, 194–202, 1964. Teissier du Cros, E., Le Tacon, F., Nepveu, G. Pard, J., Perrin, R., and Timbal, J.: Le Hetre, INRA Department des
Reserches Forestieres, Paris, France, 1981.Terribile, F., Basile, A., De Mascellis, R., Iamarino, M., Magliulo, P., Pepe, S., and Vingiani, S.: Landslide processes
and Andosols: the case study of the Campania region, Italy, in: Soils of Volcanic Regions in Europe, edited by: Arnalds, O., Bartoli, F., Buurman, P., Oskarsson, H., Stoops, G., and Garcia-Rodeja, E.,
Springer Verlag, Berlin Heidelberg, 545–563, 2007.
Torn, S. M., Trumbore, S. E., Chadwick, O. A., Vitousek, P. M., and Hendricks, D. M.: Mineral control of soil organic
carbon storage and turnover, Nature, 389, 170–173, 1997. Tucker, C. J. and Sellers, P. J.: Satellite remote sensing of primary production, Int. J. Remote Sensing, 7, 1395–1416,
1986.
Ugolini, F. C., Dahlgren, R. A., Shoji, S., and Ito, T.: An example of andosolization and podsolization as revealed by soil solution studies, southern Hakkoda, northeastern Japan, Soil Sci., 145, 111–125,
1988. USDA-NRCS: Soil Survey laboratory methods manual, Soil Survey Investigation Report 42, Version 4, 700 pp.,
2004. van Genuchten, M. T.: A closed-form equation for predicting the hydraulic conductivity of unsaturated soils, Soil
Sci. Soc. Am. J., 44, 892–898, 1980. Vingiani, S., Scarciglia, F., Mileti, F. A., Donato, P., and Terribile, F.: Occurrence and origin of soils with andic
properties in Calabria (southern Italy), Geoderma, 232–234, 500–516, 2014.Vingiani, S., Mele, G., De Mascellis, R., Terribile, F., and Basile, A.:
Volcanic soils and landslides: a case study of the island of Ischia (southern
Italy) and its relationship with other Campania events, Solid Earth, 6,
783–797, 10.5194/se-6-783-2015, 2015. Walkley, A.: A critical examination of a rapid method for determining organic carbon in soils – effect of variations in
digestion conditions and of inorganic soil constituents, Soil Sci., 63, 251–265, 1947. Walsh, S. J., Crawford, T. W., Walsh, S. J., Crawford, T. W., Welsh, W. F., and Crews-Meyer, K. A.: A multi-scale analysis of
LULC and NDVI variation in Nang Rong district, northeast Thailand[J], Agr. Ecosyst. Environ., 85, 47–64, 2001. Wang, J., Rich, P. M., Price, K. P., and Kettle, W. D.: Relations between NDVI and tree productivity in the central great
plains, Int. J. Remote Sensing, 25, 3127–3138, 2004.Yosef, H. and Tamhane, A. C.: Multiple Comparison Procedures, John Wiley and Sons, Inc., 450 pp., 10.1002/9780470316672, 2008. Zhan, Z.-Z., Liu, H.-B., Li, H.-M., Wu, W., and Zhong, B.: The relationship between NDVI and terrain factors – a case
study of Chongqing, Proc. Environ. Sci., 12, 765–771, 2012. Zhang, X., Friedl, M. A., Schaaf, C. B., Strahler, A. H., Hodges, J. C. F., Gao, F., Reed, B. C., and Huete, A.:
Monitoring vegetation phenology using MODIS, Remote Sens. Environ., 84, 471–475, 2003.