Utilization of near infrared reflectance

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Utilization of near infrared re

ﬂ

ectance spectroscopy (NIRS) to quantify the impact of

earthworms on soil and carbon erosion in steep slope ecosystem

A study case in Northern Vietnam

Pascal Jouquet

a,b,

⁎

_{, Thierry Henry-des-Tureaux}

a,b

_{, Jérôme Mathieu}

b,c

_{, Thuy Doan Thu}

a

_,

Toan Tran Duc

a

, Didier Orange

a,b

a_SFRI

–IWMI–IRD, Dong Ngac, Tu Liem, Hanoï, Vietnam

b_{IRD, UMR 211 Bioemco, Equipe Transferts, Centre IRD Bondy, 32 Avenue H. Varagnat, 93143 Bondy Cedex, France} c_UPMC

–UMR 7618 Bioemco, NCEAS, 735 State Street, Santa Barbara, 93101-5504 California, USA

a b s t r a c t

a r t i c l e

i n f o

Article history:

Received 10 September 2009

Received in revised form 18 January 2010 Accepted 28 January 2010

Keywords: Soil erosion Carbon loss Earthworm activity

Near Infrared Reﬂectance Spectroscopy Vietnam

Amynthas khami

This work focuses on a new approach to quantify the effects of above-ground earthworm's activity on soil erosion in steep slope ecosystems such as in Northern Vietnam. In these areas and in many others in the world, soil erosion becomes a major issue while the factors that determine it are still misunderstood. Earthworm's activity is believed to inﬂuence soil erosion rate, but we are still unable to precisely quantify their contribution to soil erosion. In this study, we used Near Infrared Reﬂectance Spectroscopy (NIRS) to quantify the proportion of soil aggregate in eroded soil coming from earthworm activity. This was done by generating NIRS signatures corresponding to different soil surface aggregates (above-ground soil casts produced by earthworms vs. surrounding topsoil).

In order to test the proposed approach, we compared the NIRS-signature of eroded soil sediments to those of earthworms' casts and of the surrounding soils. Our results strongly supported that NIRS spectra might be used as“_ﬁngerprints”to identify the origin of soil aggregates. Although earthworms are generally assumed to play a favorable role in promoting soil fertility and ecosystem services, this method shows that cast aggregates constitute about 36 and 77% of sediments in two tropical plantations,Paspalum atratumandPanicum maximum plantations, respectively. In light with these results, we estimated that earthworms led to an annual loss of 3.3 and 15.8 kg of carbon ha−1_yr−1_{, respectively in}_{P. atratum}_and_{P. maximum}_{agroecosystems.}

1. Introduction

Darwin published“The formation of vegetable Mould through the action of worms, with some observations of their habits”(Darwin, 1881) 128 years ago. Although less known than his scientific master-work“on the origin of species”(Darwin, 1859), this scientific book was considered as a “best-seller” at its time. This book might be considered as the_first scienti_fic essay stressing the importance of earthworm activity on soil dynamic, and especially the topsoil formation (i.e., the vegetable mould). With this work, Darwin also highlighted the in_fluence that earthworms might have on landscape evolution through their effects on erosion–sedimentation cycle via the creation of surface casts which might be eroded by wind and/or

water. Yet on the 200th anniversary of his birth, controversy still surrounds exactly how earthworms affect soil erosion.

Soil erosion is a worldwide environmental and public health problem leading to direct losses of soil fertility and other on-site and off-site negative impacts such as dam siltation and biodiversity loss (Pimentel, 2006). It is especially a problem in sloping lands of the tropics which are characterized by rapid biogeochemical cycling. When earthworms are abundant it is clear that they can signi_ficantly affect soil erodibility and erosion through their burrowing activities and especially the creation of vertical galleries that enhance water in_filtration (Blanchart et al., 2004; Shipitalo and Le Bayon, 2004). Earthworms also produce deposit stable above-ground casts that increase soil surface roughness and then can both decrease runoff water velocity, and increase soil detachment and erosion (Blanchart et al., 2004; Shipitalo and Le Bayon, 2004; Jouquet et al., 2008a). The net influence of earthworms on soil erosion and nutrient losses, however, remains unclear and is probably site speci_fic (e.g., dependent on the earthworm species, soil properties and land slope).

Catena 81 (2010) 113–116

⁎Corresponding author. SFRI–IWMI–IRD, Dong Ngac, Tu Liem, Hanoï, Vietnam. E-mail address:pascal.jouquet@ird.fr(P. Jouquet).

Contents lists available atScienceDirect

Catena

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An important obstacle for quantifying the inﬂuence of earthworms on soil erosion is our limited ability to differentiate the old earthworm casts and the soil matrix. When freshly emitted, earthworm casts are usually easily discriminated from the surrounding soil aggregates based on their rounded shapes compared to the angular to sub-angular aspect of soil aggregates that has not been processed by earthworms for a long time. However, it remains impossible to visually distinguish the two types of soil once they have become fragmented (Jouquet et al., 2009). As a consequence, we are still unable to quantify the role of earthworms on soil erosion and resulting carbon losses. In order to overcome this problem, several analytical approaches have been compared for identifying the origin of soil aggregates and the Near Infrared Reﬂectance Spectroscopy (NIRS) has emerged as a promising analytical tool to determine the origin of soil macroaggregates (Hedde et al., 2005; Velasquez et al., 2007; Jouquet et al., 2008c). Recently, Jouquet et al. (2009) also showed that NIRS allowed clear discrimination of casts from their surrounding soil regardless of size or appearance. This present study aimed to answer essential questions raised from Darwin's study (Darwin, 1881) using NIRS analyses: How much do earthworms contribute to soil erosion? And what is the consequence in terms of carbon loss?

2. Materials and methods

2.1. Study site

Our study was carried out in the experimental catchment (46 ha) of the MSEC (Management Soil Erosion Consortium of the Interna-tional Water Management Institute, IWMI) project (Valentin et al., 2008). This study site is located in Dong Cao village, in north-eastern Vietnam, approximately 50 km south-west of Hanoi (20° 57′N, 105° 29′E). The annual rainfall ranges from 1500 to 1800 mm, of which 80-85% occurs from April to October. The air humidity is always high, between 75 and 100%. The mean daily temperature varies from 15°_C to 25°_{C. The soil is an Acrisol (}_{WRB, 2006}_{) with more than 50%} clay, mainly kaolinite, with a low pH of around 5, and a low CEC (b10 cmol kg−1_{) (}_{Jouquet et al., 2008a,b; Podwojewski et al., 2008}_). Experiments were carried out in two fodder plantations:Paspalum atratumandPanicum maximum, growing in steep plots with a 45% slope. Cattle's grazing was excluded in the study site.

The most abundant earthworm species found at the study site is

Amynthas khami, which is considered an anecic earthwormsensu

Bouché (1977).A. khamivaries in size and adults can reach up to more than 50 cm in length. It builds casts that areﬁrst deposited on the soil surface then enlarged by days of deposition of globular cast-units at the top edge of the structure (Fig. 1). Casts are globular and characterized by a very high soil structural stability (Jouquet et al., 2008b). These biogenic structures can reach 20 cm in height but are often slowly broken, probably by livestock trampling, human trafﬁc and raindrop impacts, and then release free water stable aggregates on the soil surface.

2.2. Measurement of soil erosion and carbon loss

Soil detachment was assessed from 1-m² plots (n= 3 in each fodder plantation) under natural rainfall, as described byJaneau et al. (2003). Plots were bordered by rigid metal frames inserted to a depth of 0.10 m. Runoff water and sediments were collected after each rainfall event, from May to October 2008, in a collector at the outlet each plot. Sediment loss was measured through the sediment weight after ﬁltration from runoff water and oven-drying at 105 °C. This sediment weight is assumed to represent the quantity of soil lost during the rainfall event on 1-m² plots.

The organic carbon (C) was determined by the dry combustion method using a CHN elemental-analyser (CHN NA 1500, Carlo Erba)

on each soil sample after NIRS analyses. Analytical precision was ±0.1 mg for C.

2.3. Soil sampling and preparation

Soil aggregates were collected from May to October 2008, which corresponds to the rainy season in northern Vietnam, in the two fodder plantations. Soil aggregates were differentiated according to their origin: (i) physicogenic: soil aggregates without obvious visible biological activity collected by scraping the soil surface, and (ii) biogenic aggregates: above-ground earthworm casts (Bullock et al., 1985; Pulleman et al., 2005). Biogenic and physicogenic aggre-gates were mixed in order to generate samples which contained an increasing proportion of cast-originating soil (0, 25, 50, 75 and 100% of cast soil,n= 9 for 0 and 100% andn= 3 for the other classes).

2.4. NIRS analysis

Near Infrared Reﬂectance Spectroscopy (NIRS) analysis was used to characterize the physicochemical signature of soil aggregates and sediments (Cecillon et al., 2009). Soil aggregates and sediments were air-dried, crushed and sieved at 250 μm. Five grams of each of the samples were scanned with a FossNIRSystems 5000 spectrophotom-eter (FossNIRSystems, Silver Spring, MD, USA) in the 1100–2500 nm spectral range. The spectral data obtained were recorded as the logarithm of the inverse of reﬂectance [log (1/R)]. They were analyzed using WinISI III-version 1.50e software (Foss NIRSystems, Infrasoft International). A 20-nm sampling interval was used for data analysis.

2.5. Statistical analyses

Principal component analysis (PCA) was done using the matrix of 27 samples and 69 variables from NIRS wavelengths quantifying Fig. 1.Casts produced byAmynthas khamiat the base ofPanicum maximumplants. New fecal aggregates are deposited one on top of the other [photo, P. Jouquet, 2008].

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the absorptions between 1100 to 2500 nm. Partial Least Squares Regression (PLSR) was used for _ﬁtting NIRS absorbance to the percentage of cast aggregates in the soil samples (0, 25, 50, 75 and 100%). All statistical calculations were carried out using Rversion 2.6.2 (R Development Core Team, 2008), packages ade4 and pls, respectively for PCA and PLSR analyses.

3. Results and discussion

Several studies emphasize the ability of NIRS analysis for the prediction of many soil physical, chemical and biological properties (Cecillon et al., 2009). In our study, this method was used to determine the optical signature of soil aggregates and sediments. PCA performed from the NIRS-data allowed casts to be clearly differentiated from the surrounding soil (Fig. 2A,B). Biogenic (100% casts) and physicogenic (0% casts) soil aggregates were clearly separated along the_first axis which explained 56 and 62% of the total variability, respectively for soil samples collected underP. atratumandP. maximum. PLSR models reached accurate prediction of the percentage of cast in the soil samples (Fig. 3A,B), with cross-validation coefficients of determina-tion above 0.90. The propordetermina-tion of casts in the sediments was then quanti_fied from the PLSR models. Surprisingly, althoughA. khamiis considered to play a positive role in increasing water infiltration and decreasing water runoff in this studied watershed area (Jouquet et al., 2008a), ourfindings show that sediments contained a high proportion of casts in P. atratum(36.42%, Standard Error, SE: 5.03) and were almost entirely constituted of cast aggregates inP. maximum(85.06%, SE: 18.71).

Fig. 2.Results of the principal components analysis showing the eigenvalue diagram (upleft) and the evolution of the absorbance in the NIR according to the concentration in cast aggregates (0, 25, 50, 75 and 100% of casts) and that of sediments collected at the outlet of the 1-m². Samples were collected inPaspalum atratum(A) andPanicum maximum(B).

Fig. 3.Scatter plots of predicted vs. actual values for the percentage of cast weight in soil samples. Abbreviation: Q², cross-validatedR²; RMSECV, root mean squared error of cross-validation. (A) InPaspalum atratum. (B) InPanicum maximum.

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Even if earthworms mostly play a favorable role in regards to soil fertility, carbon sequestration and plant growth, this study highlights that the inﬂuence of earthworms remains site speciﬁc. At our study site, soil erosion was estimated to reach 2.89 Mg ha−1_yr−1_{(SE: 1.38) in}

P. atratum and 5.54 Mg ha−1_yr−1 _{(SE: 2.61) in} _{P. maximum}_fi_elds. Considering an average of 3.33 mg C g−1_{soil in earthworm cast} aggre-gates (Table 1), earthworms are estimated to lead to the loss of 3.34 and 15.85 kg of C ha−1_yr−1_{, respectively in}_{P. atratum}_and_{P. maximum} fields. Introducing fodder crops on sloping lands is very effective against runoff and soil erosion by locally reducing slope length and creating steps that lower water velocity and favour sediment deposition (Karlen et al., 2006). Thus, they are generally considered as interesting alternatives to annual crop plantations, which are known to have dramatic environmental consequences in sloping lands (Valentin et al., 2008). In these ecosystems, earthworms appear to have both positive and negative effects on ecosystem functioning. They probably improve soil properties such as water in_filtration and soil nutrient cycling, and plants' growth like in many other regions of the world (Lavelle and Spain, 2001) but they are also responsible for an important proportion of soil and C loss via erosion. In order to optimise agro-ecosystem functioning (to ensure plant growth, decrease soil erosion, favour C sequestration in soil…), an understanding of the balance between the positive and negative effects of earthworms is required.

Acknowledgements

We would like to thank Patrick Lavelle, Nicolas Bottinelli, Leigh Gebbie, Didier Brunet and Pascal Podwojewski for constructive discussions. We would like also to thank Mr Din Van Tuyen and Ms Bui Thi Thu Hien from the National Institute of Animal Husbandry (NIAH, Vietnam) who helped us with the NIRS analyses. This project was ﬁnancially supported by CNRS/INSU (VERAGREGAT research program under the framework of the EC2CO program) and IRD (unit research UMR 211 BIOEMCO) French institutes and the Management of Soil Erosion Consortium (MSEC) from the International Water Management Institute (IWMI).

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n°103. FAO, Rome, 145 pp. Table 1

Soil organic carbon content (mg C g−1_{soil) in casts and control soils in}_Paspalum

atratumandPanicum maximumplantations. Standard errors are in parentheses,n= 9.

Control Cast

Paspalum atratum 3.22 (0.14) 3.44 (0.25)

Panicum maximum 3.14 (0.22) 3.20 (0.16)