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European Journal of Soil Biology 66 (2015) 24e31

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European Journal of Soil Biology

journal homepage: http: / /www.elsevier .com/locate/ejsobi

Original article

Spatial heterogeneity of soil quality around mature oil palms receivingmineral fertilization

M.P. Carron a, *, Q. Auriac a, b, D. Snoeck a, C. Villenave c, E. Blanchart d, F. Ribeyre e,R. Marichal a, M. Darminto f, J.P. Caliman a, f

a Cirad, UPR Syst�emes de p�erennes, F-34398 Montpellier, Franceb SupAgro-Irc, Agropolis Avenue, F-34093 Montpellier, Francec Elisol-Environnement, place Viala, F-34060 Montpellier, Franced Ird, UMR Eco&Sols, F-34060 Montpellier, Francee Cirad, UPR Bioagresseurs, F-34398 Montpellier, Francef Smart-RI, P.O. Box 1340, 28000 Pekanbaru, Riau, Indonesia

a r t i c l e i n f o

Article history:Received 21 August 2014Received in revised form4 November 2014Accepted 10 November 2014Available online 11 November 2014

Keywords:Soil qualitySoil macrofaunaSoil nematofaunaElaeis guineensis

* Corresponding author. Cirad, UPR Syst�emes de pAgropolis, F-34398 Montpellier Cedex 5, France.

E-mail address: marc-philippe.carron@cirad.fr (M.

http://dx.doi.org/10.1016/j.ejsobi.2014.11.0051164-5563/© 2014 Elsevier Masson SAS. All rights res

a b s t r a c t

The African oil palm (Elaeis guineensis Jacq.) is grown on a total area of 16 million ha; but data on soilquality in mature oil palm plantations are fragmentary and data concerning biota are almost non-existent. Consequently, no well-tested sampling method is available for soil diagnoses. We studied thespatial heterogeneity of the soil around the palm by measuring comprehensive soil quality in a 24-year-old oil palm plantation. Soil quality and litter were assessed in five zones with different plant cover, anddifferent applications of herbicide or fertilizer. Physical-chemical characteristics, macrofauna, andnematofauna were analysed. A sampling method was developed and adapted to the way the cultivationpractices are implemented: sampling by zone and weighting the plot mean by the respective area of eachzone. The total density of macrofauna in the litter and in the 0e15 cm soil layer followed a gradient fromthe harvest pathway (29 ind m�2) to the windrow (1003 ind m�2). Ants (13e237 ind m�2), earthworms(11e120 ind m�2), Dermaptera (0e35 ind m�2), Coleoptera (3e24 ind m�2) and Chilopoda (0e43 ind m�2) were the main taxa. The termite population was very poor (3e4 ind m�2). The density ofnematofauna was also heterogeneous (268e805 ind 100 g�1 of soil). Heterogeneity between zones wasalso reflected in the density of the functional groups, mainly soil engineers, detritivores and predators formacrofauna and bacterial feeders, and phytoparasites for nematofauna. The weeded circular zone aroundthe palm had the highest soil nutrient content (P, K, Ca, Mg, Corg CEC, base saturation). Its biodiversitywas average but it contained the highest density of earthworms and nematofauna. Possible relationshipsbetween chemicals and biological groups in the food web are discussed.

© 2014 Elsevier Masson SAS. All rights reserved.

1. Introduction

The African oil palm (Elaeis guineensis Jacq.) is cultivated in anarea totalling 17 million ha [1]; its economic, social, and environ-mental importance is well known, especially in East Asia. Inresponse to new constraints resulting from global change, i.e.environmental concerns and in particular an increase in the cost ofmineral fertilizers, the principles and criteria for the sustainability

�erennes, TA B-34/02, Avenue

P. Carron).

erved.

of oil palm were laid down by the Roundtable for Sustainable PalmOil (RSPO e http://www.rspo.org) in 2007 and encouraged pro-ducers to assess the environmental impacts of their practices [2e4].Soil quality was one of the main targets. The concept of soil qualityin agro-ecosystem is the subject of controversy [5]. For us, soilquality is related to its role as life-support in general, in plantdevelopment in particular. Most authors agreed that physical,chemical and biological parameters are required to evaluate it andare looking for a multiparametric index ([6,7]). In the same line ofthought, the density of soil macrofauna has been shown to besignificantly correlated with soil services in deforested Amazonia[8].

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e31 25

The chemical fertility in a mature plantation is indirectlyassessed by leaf diagnosis, which is used for the management ofchemical inputs [9]. The abiotic soil conditions are only assessedwhen the plantations are being established to determine limingrates and the early fertilization requirements of the young palms(until leaf diagnosis becomes possible). Afterwards, the quality ofsoils is no longer an issue unless problems of erosion or compactionarise [10]. Currently, only fragmentary data are available on soilquality in a mature oil palm plot or on the impacts of fertilization,and practically no data at all is available on soil biota. Consequently,no well-tested sampling method is available, that is sensitive tospatial heterogeneity in a perennial plantation.

To respect the framework of ecological intensification, theassessment and management of soil quality necessarily include soilbiota, particularly with respect to fertility as an ecosystem service[11e13]. This assessment thus requires the measurement of soilbiodiversity through taxonomic biodiversity, an indicator of envi-ronmental richness, and through functional biodiversity, an indi-cator of the permanence of soil functions. The study of the soilmacrofauna beneath oil palms was first addressed by experimentsconducted by Lasebikan [14] on arthropods in decomposing palmtrunks and in the neighbouring soil. More recent work has focusedon isopods [15] and earthworms in several oil palm plantations inMalaysia [16]. Soil invertebrates have also been studied in relationto palm pests [17,18].

Spatial heterogeneity is a crucial issue in the study of soilbiodiversity, particularly in perennial systems, such as agroforestrysystems in India [19], the Amazon [20] or mono species stands ofeucalyptus in the Congo [21]. These systems provide ecologicalniches for soil organisms and these will necessarily differdepending on the availability of nutrients and habitats, resulting inthe heterogeneous distribution of macrofauna. In the case of oilpalm, while studying soil respiration, Adachi [22] observed markedspatial heterogeneity within oil palm plantations. The issue ofspatial heterogeneity has been addressed at the field or territoryscale [23,24], but efficient sampling methods still need to bedefined at the tree scale [25].

In this study, we assessed spatial heterogeneity around the palmby measuring comprehensive soil quality. We hypothesise that theheterogeneous plant cover around the oil palm and the spatialheterogeneity of the application of mineral fertilizers and organicresidues have an impact on the quality of the underlying soil andthat, to evaluate the impact of cultivation practices at the plot scale,we need to understand this heterogeneity. In this paper, we reportthe results we obtained on physical-chemical characteristics,macrofauna and nematofauna. Results concerningmicrobiology arereported in Situmorang et al. [26].

Fig. 1. Diagram of planting pattern in the field (left) and the five zones defined in the elemPC ¼ intermediate zone between zones P and C, zone C ¼ weeded circle, CW ¼ intermediateground.

2. Materials and methods

2.1. Study site

The present study was conducted in the province of Riau on theisland of Sumatra, Indonesia (0� 550 32.8200 N; 101� 110 37.2000 E).This province produces more raw palm oil than any other in theIndonesian archipelago. The study plots are located in an industrialplantation belonging to PT-Smart (Golden Agri-Resources). Theregion has a humid equatorial climate with approximately2600 mm of well-distributed rainfall throughout the year, butincluding two drier seasons (February and June/July, inwhichmeanmonthly precipitation is 130 mm). Sampling was performed in May2012 at the end of the wet season, which is a favourable period forthe study of macrofauna [27]. The plantation was established 24years ago after forest on a ferralitic soil with gibbsite and kaolinite(Ferric Acrisol according to the FAO classification) [28]. All the plotschosen for the study are located on flat terrain on hilltops.

2.2. Experimental design

Tree density in the industrial blocks is 147 trees ha�1. Trees areplanted in staggered rows with equilateral triangular spacing(Fig. 1). We examined five treatments corresponding to fivedifferent zones around the palm tree, which represent spatialheterogeneity in an elementary plot measuring 9.0 m � 7.6 m:

� P¼ Path, the harvest path, which is compacted by the passage ofplantation workers.

� C¼ Circle, a circular zone with a radius of 1.8 m directly aroundthe palm trunk, which is kept “clean” by chemical weed control(glyphosate or paraquat) to facilitate the collection of fruitbunches

� W¼Windrow, the zone where the palm fronds pruned duringharvest (approximately 18 fronds tree�1 year�1) are placed onthe ground forming a U-shaped windrow around the tree. Thiszone is kept free from all disturbances during the entire crop-ping cycle (30e35 years) and is mainly populated by ferns(Nephrolepis bisserata).

� PC is the intermediate zone between the path and the circle,which has little plant cover.

� CW is the intermediate zone between the circle and thewindrow, which has little plant cover.

These five zones were distinguished by the different amounts oforganic and mineral fertilizers they received, as well as by weedingand soil compaction. The plot was the subject of conventional

entary plot to study spatial heterogeneity (right) e zone P ¼ harvest pathway, zonezone between zones C and W, W ¼ Windrow where pruned palm fronds are left on the

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e3126

fertilization, which mainly meant that mineral fertilizer wasapplied to zones P, C orWevery sixmonths (Table 1). The fronds lefton the ground during harvesting also supply minerals in zone W.The quantities of nutrients were calculated based on mean valuescalculated by Ng et al. [29].

Treatments were repeated in six elementary plots (six repli-cates) around non-neighbouring trees. The plant cover and the soilwere analysed in each of the five zones in each of the six elemen-tary plots, i.e. 6� 5 ¼ 30 sampling points.

2.3. Soil chemical and physical parameters

Soil was sampled from the five zones (P, PC, C, CW andW) alonga diagonal transect within the elementary plot (Fig. 1). Soil coresweighing 300 g were removed with an auger to a depth of 15 cm ineach of the six replicates in each zone, i.e. 6� 5¼ 30 sampled units.The following analyses were performed: total N and organic C (Corg)by dry combustion; pHH2O (soil:water ratio ¼ 1:2.5); total K;phosphorus: total P and available P (Bray 1); exchangeable cationsCa, Mg, K, Na and CEC: extraction with ammonium acetate at pH 7;Hþ and Alþþ: in KCl (1 mol L�1). Base saturation was calculated:[sum (K þ Ca þ Mg)$CEC�1]$100.

2.4. Biota characterisation in litter and soil

2.4.1. Macrofauna samplingThe Tropical Soil Biology and Fertility (TSBF)method [30,31] was

used for the assessment of macrofauna. A 25 cm � 25 cm quadratwas delimited, withinwhich litter was removed andweighed (freshweight). In the present study, litter was considered in its widersense, i.e. including moss and small emerging plants, to measurethe quantity of organic cover (living and dead) in each zone. Withineach quadrat, a second sample (soil monolith) was taken from the0 to 15 cm soil layer. The litter and soil monoliths were sorted andmacrofauna removed by hand; 6 � 5 � 2 ¼ 60 units were sampled.Organisms >2 mmwere removed with tweezers and placed in vialsof 70% ethanol. In the laboratory, the organisms were identifiedusing an identification key [32] and then weighed and counted tocalculate biomass (g m�2, fresh weight) and density (ind m�2,where “ind” means individual), respectively. Macrofauna were alsoanalysed in the 15e30 cm soil layer, where their density was 5e10times lower than in the 0e15 cm soil layer, but with no difference inthe balance between the groups. Results for the 15e30 cm soil layerare not presented here.

Table 1Mineral (Min) and organic (Org) inputs per zonea during the last year. Mineral inputswere from urea, KCl, kieserite fertilizers and triple superphosphate fertilizer appliedin zones P and C and W. Organic inputs were from palm fronds pruned duringharvest and left on the ground in zone W.

Nutrient inputs/zone(kg tree�1 year�1)

P C W Total

N Org e e 0.33 1.48Min 0.86 0.29 e

P Org e e 0.07 0.25Min e e 0.18

K Org e e 0.69 2.13Min 1.07 0.36 e

Mg Org e e 0.20 0.36Min 0.12 0.04 e

Ca Org e e 0.45 0.67Min e e 0.22

B Min e 0.009 e 0.009

a Zones around the palm tree in the elementary plot were defined in Fig. 1.

2.4.2. Nematofauna samplingTo analyse nematofauna, composite soil samples were taken in

each of the six elementary plots but only from the three main zonesPC,CandW, i.e. 6� 3¼18samplingpoints.Ateachsamplingpoint, sixcore samples were taken from the 0e15 cm soil layer and pooledbeforebeing sievedat2mm.Acomposite300gsampleof themixwaskept for analysis. Free nematodes were extracted (according to normNF ISO 23611-4) by elutriation, followed by active passage through acotton filter. The nematodes were then counted and identified to thefamily level and grouped according to their feeding behaviour.

2.5. Data analyses

According the respective areas of the five zones, plot weightedmeans were calculated with the formula: Plot mean¼ [(0.03� P)þ(0.16 � PC) þ (0.14 � C) þ (0.02 � CW) þ (0.65 � W)] for phys-icalechemical parameters and macrofauna. For nematofauna,zones P and PC and zones CW and W were merged; the formulaused was then [(0.19 � PC) þ (0.14 � C) þ (0.67 � W)].

Differences between means were assessed by analysis of vari-ance (ANOVA), followed by multiple comparison tests using Bon-ferroni correction for physical and chemical parameters. An indexof soil quality (SQI) was calculated to compare the zones. The for-mula and the coefficients proposed by Amacher and al [7]. wereused, which take seven parameters into account: Corg, Ntot, pHwater

and exchangeable Ca, Mg, K and P: each parameter received anindex value.

SQI, % ¼ (P

individual soil property index values/maximumpossible total SQI for properties measured) � 100.

Since the errors in biological parameters were not normallydistributed, they were compared using the Friedman non-parametric test, associated with a bilateral test [33]. Correlationsweremeasured with the Pearson productemoment coefficient, andonly those with p < 0.05 are mentioned hereafter. For all the tests,differences in means were considered significant at p < 0.05.

Centred and non-normalised principal component analysis(PCA) was performed on log-transformed soil macrofauna data.PCA was supplemented with a between-class analysis [34], whichestimated a percentage of inertia between classes (zones), whosesignificance was tested with the MonteeCarlo method (999 simu-lations). This analytical method seeks to identify what most dif-ferentiates zones as a function of their macrofauna. It combines PCAaxes so as to maximise variance between zones. Multivariate ana-lyses were performed with R software and its ade4 package [35].

Shannon and Simpson indices were calculated to quantify thediversity and evenness of the abundances of faunal groups. TheSimpson index measures the probability that two individualsrandomly selected from the same habitat belong to the same spe-cies. Functional groups were organised according to Ruiz et al. [32],as follows: [Soil engineers] ¼ ants, earthworms, Isoptera;[Detritivores] ¼ Dermaptera, Coleoptera, Diplopoda, Blattodea,Isopoda, Acari, Diptera; [Herbivores] ¼ Hemiptera, Orthoptera,Lepidoptera larvae, Mollusca; [Predators] ¼ Araneae, Chilopoda.

3. Results

3.1. Physical-chemical characteristics

The superficial (black organic) O horizon of the topsoil profile inthe study plots was a few cm thick. This was followed by an Ahorizon down to a depth of 40 cm. Based on colour, the latter wasdivided into horizon A1 down to a depth of 15 cm (grey/browncolour) and horizon A2 from 15 to 40 cm in depth (completelybrown). Below 40 cm, an ochre coloured B horizon with more claywas observed. Only the A1 horizon was studied.

Fig. 2. Results of principal component analysis (PCA) of soil macrofauna. (Left) Variables: soil macrofaunal taxa. (Right) Ordination of sampled points along the first two axesrepresenting 49.7% and 12.6% of explained inertia, respectively. Letters correspond to centroids of sample points in each zone (P, PC, C, CW and W). Zones around the palm tree inthe elementary plot were defined in Fig. 1. MonteeCarlo test of zones, p < 0.01, observation ¼ 0.48.

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e31 27

The physicalechemical analyses showed that the A1 horizonhad a loamy-sand texture with a pHH2O close to 5.0. Zone W wassignificantly more clayey than the other zones (Table 2). All thezones had similar soil N content and pHH2O.

Zone C was most fertile chemically (SQI¼ 46%); it had high totaland available P and K contents, high Ca, Corg and Mg, as well as ahigh CEC and base saturation. The parameters in zone C differedfrom the other four zones, which can be explained by the mineralinputs it received. Zone P was poor in most of the minerals despitethe fact fertilizers were applied in this area.

3.2. Total biomass and density of macrofauna in the litter and in thesoil and of nematofauna in the soil

Total macrofauna density in the litter and soil (0e15 cm) fol-lowed a gradient from zone P to zone W

Table 2Physical and chemical properties of the 0e15 cm soil layer in the 5 zones around thepalm tree.a

Zone P PC C CW W Plotweightedmeanb

Sand (%) 78.2 78.9 79.5 78.4 76.8 76.5Silt (%) 9.4 8.4 7.9 8.7 8.5 8.4Clay (%) 12.4a 12.7a 12.6a 12.9a 14.8b 13.9Corg (%) 1.6a 1.6a 2.3b 1.8ab 2.0ab 1.9Ntot (%) 0.11 0.11 0.18 0.14 0.14 0.13pHwater 5.0 5.1 4.9 5.1 4.8 4.8Ptot (ppm) 140a 318a 2832b 153a 50a 464Ktot (ppm) 17a 28a 56b 25a 24a 28PBray (ppm) 38a 93a 471b 40a 23a 92CEC (me%) 3.30a 3.64a 8.46b 4.27a 4.73a 4.94Ca (me%) 0.38a 0.45a 1.77b 0.76a 0.54a 0.68Mg (me%) 0.15a 0.13a 0.50b 0.26a 0.16a 0.20K (me%) 0.04a 0.08a 0.12b 0.06a 0.07a 0.07Al (me%) 0.53a 0.54a 0.72b 0.44a 0.82b 0.74Base saturation

(%)16.0a 18.0a 25.5b 24.4b 17.2a 18.2

SQI (%) 31a 31a 46b 39ab 39ab 39

Mean data of 6 elementary plots. The letters a and b indicate significant differencesbetween treatments according to analysis of variance (ANOVA), followed by mul-tiple comparison tests using the Bonferroni correction.

a Zones around the palm tree in the elementary plot were defined in Fig. 1.b The plot weighted mean was calculated according to the respective area of each

zone: [(0.03 � P) þ (0.16 � PC) þ (0.14 � C) þ (0.02 � CW) þ (0.65 � W)].

(29< 171 < 503 ¼ 485 < 1003 ind m�2 respectively for zonesP < PC < CCW <We Tables 3 and 4). The density of the macrofaunawas correlatedwith themass of organic cover, in the litter (r¼ 0.63)and in the soil (r ¼ 0.51). Macrofauna biomass was correlated withorganic cover in the litter (r ¼ 0.72) but not in the soil (r ¼ �0.09),probably due to earthworm group. Taxonomically, total ants(r ¼ 0.44), Coleoptera (r ¼ 0.61), Acari (r ¼ 0.79), Diplopoda(r ¼ 0.62) and Chilopoda (r ¼ 0.74) were correlated with thebiomass of the organic cover, but not total earthworms. Dermap-tera, Coleoptera, Blattodea, Araneae, Acari, Diplopoda and Isopodawere more abundant in the litter (organic cover) than in the soil,whereas earthworms were more abundant in the 0e15 cm soillayer. Total nematode density (Table 5) in the 0e15 cm soil layerwas similar in zones PC andW (around 270 ind 100 g�1 of soil), butzone C had a much higher nematode density (805 ind 100 g�1 ofsoil).

3.3. Taxonomic diversity and abundance of macrofauna andnematofauna in the soil

Organisms from 16 taxonomic groups of macrofauna (classesand orders) were identified in all samples. Seven out of thesegroups were significantly present (�9 ind m�2 in the plot weightedmean e Table 4).

Heterogeneous spatial distribution was observed for half thegroups of macrofauna due to the biotic paucity of zones P and PC,which contained mostly ants and earthworms. Taxonomic biodi-versity varied along a gradient from zone P to zone W, with aprogressive increase in the density of earthworms, Dermaptera,Coleoptera and Chilopoda. In soil, ants (r ¼ 0.38), Coleoptera(r ¼ 0.38), Acari (r ¼ 0.49), Diplopoda (r ¼ 0.53) and Chilopoda(r ¼ 0.59) were also correlated with the biomass of organic cover,but earthworms were not. Zone C differed from the other zones inits high density of earthworms (120 ind m�2). Shannon indices forthe 0e15 cm horizon provided the following ranking:W¼CW � C > PC¼ P (Table 4). The high heterogeneity of macro-fauna in zone PC was highlighted by the Simpson index (0.51),which was much higher than for the other zones.

The first two axes of the PCA of macro-invertebrate commu-nities (Fig. 2) represented 49.7% and 12.6% of explained inertia. Afactorial map of sample points suggests that axis 1 separates zonesP and PC (low macrofauna densities) from the other zones (highdensities of Aranea, Chilopoda, Blattodea, ants). Axis 2 ranked the

Table 3Mean biomass of the organic cover, mean biomass and density of macrofauna in thelitter of the 5 different zones around the palm tree.a

Litter P PC C CW W Plotweightedmeanb

Fresh weight of theorganic cover(g m�2)

0a 72ab 333bc 326bc 1016c 724

Macrofauna Density(ind m�2)

0a 13ab 285c 184bc 581c 425

Fresh weight of themacrofauna(g m�2)

0a 0a 0.71ab 0.68ab 2.53b 1.77

Mean data of 6 elementary plots. The letters a, b and c indicate significant differ-ences between zones according to the Friedman non-parametric test, combinedwith a bilateral test.

a Zones around the palm tree in the elementary plot were defined in Fig. 1.b The plot weighted mean was calculated according to the respective area of each

zone: [(0.03 � P) þ (0.16 � PC) þ (0.14 � C) þ (0.02 � CW) þ (0.65 � W)].

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e3128

zones mainly according to earthworm densities and separated zoneC from the other zones. The differences between the communitiesin the zones were significant (observation ¼ 0.49, p < 0.01, Mon-teeCarlo test).

The analysis of nematofauna identified 37 families. Few differ-ences were observed in the structure of nematode communitiesamong the three zones. The higher density in zone C compared tozones PC and W mainly, but not only, concerned four families: onefamily of plant-feeder Tylenchidae and three families of bacterial-feeders Rhabditidae, Rhabdolaimidae and Cephalobidae. Enrich-ment opportunists (Rhabditidae) were 4 fold more numerous inzone C than in zones PC and W whereas dominant general oppor-tunists (Cephalobidae) were 2.5 fold more abundant in zone C thanin zones PC and W.

3.4. Functional diversity

The spatial distribution of soil engineers, detritivores, andpredators around the palmwas heterogeneous, mainly due to theirlow densities in zone P (all three), zone PC (detritivores andpredators) and zone C (detritivores) (Table 6).

The trophic group ‘bacterial feeders’wasmost common group inthe nematode community, followed by fungal feeders and phyto-parasites; other trophic groups were rare. Zone C had the highestdensity of bacterial feeders, phytoparasites, and omnivores. The

Table 4Total density, total biomass and taxonomic biodiversity of macrofauna in the 0e15 cm s

Macrofauna groups (ind m�2) P PC C

Ants 12 106 8Earthworms 11a 35a 1Dermaptera 3a 0a 3Coleoptera 3 3 1Araneae 0 8 1Diplopoda 0 0 3Chilopoda 0a 5a 1Other groupsc 0a 0a 2Total density (ind m�2) 29a 157ab 2Total biomass (g m�2) 1.4a 6.0bc 6Shannon index 0.94a 0.93a 1Simpson index 0.33a 0.51b 0

Mean data of 6 elementary plots. The letters a, b and c indicate significant differences betwtest.

a Zones around the palm tree in the elementary plot were defined in Fig. 1.b The plot weighted mean was calculated according to the respective area of each zonc Other groups ¼ Isopoda, Blattodea, Acari, Isoptera, Hemiptera, Orthoptera, Diptera, L

high density of nematodes in zone C was thus not due to a singletrophic group. Moreover, the functional composition of the soilnematofauna in zones PC andWwas very similar even though onlyzone W received organic inputs.

4. Discussion

This study describes for the first time the overall soil qualitythrough the composition of macrofauna and nematode commu-nities beneath mature oil palms, together with physical andchemical soil characteristics.

4.1. Soil biodiversity in oil palm plantations

The overall density of soil macrofauna in our study(29e1003 indm�2) was lower than that found by Lavelle et al. [4] inyoung oil palm plantations in Colombia (2394 ± 491 ind m�2). Thedensities of soil nematodes (268e805 ind 100 g�1 soil) were alsolow compared to other tropical plantations and agrosystems[36,37].

In contrast, higher densities of some taxa such as earthwormswere found in our study: 11 to 120 ind m�2 in our study vs.37 ind m�2 in the study by Lavelle et al. op. cit.. Sabrina et al. [38]measured earthworm density in several oil palm plantations inMalaysia and found 0 to 24 ind m�2; but only identified oneearthworm species: Pontoscolex corethrurus (Müll.). They showedthat earthworm density varied with the type of soil and with theage of the plantation. We found a very low termite density in ourstudy (3e4 ind m�2) in agreement with Luke et al. [39] whoshowed that termites occurred less frequently in converted habitatssuch as oil palm plantation than in old growth forest in Malaysia.However, Lavelle et al. [4] found a termite density of 2022 ind m�2

in a Colombian oil palm plantation. The availability of decayingwood could be one reason for these differences, as forest residuesavailable at planting became scarce as the plantations aged. In ourstudy the plantation was 24 years old, whereas the plantationsstudied by Lavelle et al. [4] were younger, 3e10 years old. Thedifferences in termite densities can thus be compared to the vari-ations observed in rubber plantations by Gilot et al. [40], whomeasured high termite densities in five-year-old plantations andlower densities in older ones. Kon et al. [18] also reported that therelative density of termites increased with increasing soil depth(max. 20e30 cm) which could help avoid being predated by ants.Actually, the study by Luke et al. focused on the superficial soil layer(0e10 cm), while the top layer in the study presented here was

oil layer in the 5 zones around the palm tree.a

CW W Plot weighted meanb

7 133 237 18020b 51a 43a 500b 35b 16ab 163 13 24 183 3 11 10

11 13 91ab 35b 43b 31a 20ab 39b 2679bc 301bc 426c 348.8c 4.1b 3.4b 3.9.47ab 1.74b 1.63b 1.48.30a 0.25a 0.34a 0.36

een zones according to the Friedman non-parametric test, combined with a bilateral

e: [(0.03 � P) þ (0.16 � PC) þ (0.14 � C) þ (0.02 � CW) þ (0.65 � W)].epidoptera, molluscs.

Table 5Total density and taxonomic biodiversity (ind 100 g�1 of soil) of nematofaunacommunities in the 0e15 cm soil layer in the 3 main zones around the palm tree.a

Nematofauna families/zone PC C W Plot weighted meanb

Tylenchidae 50ab 120b 27a 44Rhabditidae 36 196 47 65Rhabdolaimidae 6a 60b 31ab 30Leptonchidae 23 25 19 20Cephalobidae 49 149 49 62Others 104a 255b 101a 121Total density 268a 805b 274a 342

Mean data of 6 elementary plots. The letters a and b indicate significant differencesbetween zones according to the Friedman non-parametric test, combined with abilateral test.

a Zones around the palm tree in the elementary plot were defined in Fig. 1.b The plot weighted mean was calculated according to the respective area of each

of the 3 zones (P þ PC, C, CW þ W) by the formula[(0.19 � PC) þ (0.14 � C) þ (0.67 � W)].

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e31 29

0e15 cm. However we did not find more termites in the 15e30 soillayer (data not shown). The termite: earthworm ratio was low inour study which, according to Senapati et al., suggest rather goodsoil quality, as these authors used this ratio to assess soil degra-dation [41].

Ants were the faunal group with the highest density in both thelitter and the 0e15 cm soil layer. These results are in agreementwith Luke et al. [39] who showed that ants occurred morefrequently in disturbed areas than in old growth forest. These au-thors also showed that the relative density of ants to termites wasmuch higher in oil palm plantations than in old growth forest. Fayleet al. [42] identified up to 110 different ant species in an oil-palmplantation in Malaysia. Despite this diversity, these authors re-ported that the decrease in species richness compared to that in aprimary rainforest was greatest in the litter (reduction of 82%) butlower in the trunk and canopy of oil palms. In our study, theShannon index for all macrofauna groups ranged from 0.93 to 1.74,which can be interpreted as expressing a certain imbalance infaunal groups compared to those observed in a variety of agricul-tural and natural ecosystems in the Amazon [43].

Table 6Density of functional groups of macrofauna (indm�2) and nematofauna (ind 100 g�1

of soil) in the 0e15 cm soil layer of the 5 zones around the palm tree.a

Functional groups P PC C CW W Plot weightedmeanb

Macrofaunac Eng. 24a 141ab 207b 192b 283b 232Det 5a 3a 48ab 67b 77b 59Herb 0 0 0 5 13 9Pre 0a 13ab 24bc 37bc 53c 40

Nematofaunad Ba e 132a 514b e 176a 214Fu e 61 93 e 40 51PhF e 50ab 120b e 27a 44O e 15ab 23b e 7a 11Pre e 4 14 e 4 5Herb e 3 20 e 10 10Ent e 3 22 e 10 10

Mean data of 6 elementary plots. The letters a, b and c indicate significant differ-ences between zones according to the Friedman non-parametric test, combinedwith a bilateral test.

a Zones around the palm tree in the elementary plot were defined in Fig. 1.b The plot weighted mean was calculated according to the respective area of each

zone: [(0.03 � P) þ (0.16 � PC) þ (0.14 � C) þ (0.02 � CW) þ (0.65 � W)] formacrofauna and [(0.19 � PC) þ (0.14 � C) þ (0.67 � W)] for nematofauna.

c Macrofaunal functional groups: Eng: soil engineers; Det: detritivores; Herb:herbivores; Pre: predators.

d Nematofaunal functional groups: Ba: bacterial feeders; Fu: fungal feeders; PhF:phytoparasites; O: omnivores; Pre: predators; Herb: facultative herbivores; Ent:entomopathogenic.

4.2. Spatial heterogeneity

Knowledge of the heterogeneity of communities, biologicalprocesses and physical and chemical soil properties is crucial tounderstand soil functioning and to design more efficient manage-ment of agricultural plots. Based on the practices implemented inour study area, five zones were defined in an elementary plotaround the base of the palm trees. This approach, which was basedon habitat and on zones inwhich different practices were used, waseasy to implement. It was also appropriate because the oil palmshad been planted 24 years previously, and the cultivation practicesremained the same for many years. Compared to a sampling grid,based on a mathematical model, as proposed by Nelson et al. [25],our approach could thus be a good compromise. The grid is moreaccurate but more burdensome to implement, and may conse-quently be better suited for the fine geolocation of gradients aroundtrees. In our case, zones P and CWrepresented only 3% and 2% of thearea around the tree, respectively. The harvest pathway, i.e., zone P,the path the plantations workers took, had no organic cover. Thedensity of macrofauna was very low and soil nutrient content waspoor. The organic cover, total macrofauna and ant density in zoneCW were similar to those in zone C, but soil nutrient content, totalmacrofauna and earthworm density were close to those in zone W.To increase the efficiency of data analysis, zone P could be mergedwith zone PC, and zone CW could be merged with zone W. Becauseof the way practices were implemented at our study site, samplingcould only be carried out in the three zones: PC, C and W, whichrepresented 19%, 14% and 67% of the elementary plot, respectively.The number of significant zones and their respective areas maydiffer depending on the study area and should be adapted to theway practices are implemented in each individual case.

In our study area, zone C was the most fertile, which is consis-tent with the results of Fraz~ao et al. in Brazil [44], who reportedhigher concentrations of N and Corg near the trunks of the palmtree. Such spatial heterogeneity is accentuated in old plantations,and the abundance of Corg has been attributed to root turnover[45,46]. The high Corg content resulting from root turnover is thefavourite food of earthworms [47], which explains the high earth-worm density we measured in zone C. In our study, earthwormdensity was also correlated with CEC (r ¼ 0.37) and exchangeableCa (r ¼ 0.25); these results are in agreement with those of Sabrinaet al. [38]. Earthworm casts are a fertile medium for bacterialgrowth [48]. This hypothesis was supported by Situmorang et al.[26], who studied the same plots as those we used in our study:their results revealed the highest bacterial diversity in zone C (182genera) compared with zones PC and W (139 genera). The highernematode density found in zone C compared to zones PC and Wwas mainly linked to a high abundance of bacterial-feeding nem-atodes. The total abundance of soil nematodes was correlated withthe concentration of available P (r ¼ 0.41) in the three zones, whichwas highest where inputs of mineral fertilizers were highest.Higher nematode density also reflected a higher mineral nitrogen(NH4

þ þ NO3�) content in zone C than in zones PC and W, as shown

previously [49]. Bacterial-feeding nematodes and particularlyenrichment opportunists such as Rhabditidae are widely reportedto be more abundant under enriched conditions [50].

Corg content was not very high in zone W, despite the factpruned fronds were left on the ground there in addition to anabundant plant cover. Some authors have reported that very little ofthe Corg that results from the decomposition of the fronds in thewindrow is incorporated in the pool of soil organic carbon [45,46].Our results on soil nematode abundance confirm this hypothesis, asnematode abundance was as low in zone W as in zone PC. Soilnematode communities reacted as if available resources in the soil(0e15 cm depth) were no higher in zone W than in zone P. In

M.P. Carron et al. / European Journal of Soil Biology 66 (2015) 24e3130

contrast, applications of mineral fertilizers in zone C led to signif-icant changes in the soil micro-foodweb (0e15 cm depth).

Despite the application of mineral fertilizers, zones P and PCdisplayed low soil nutrient content, and low densities of macro-fauna and nematofauna.

5. Conclusion

This is the first time the taxonomic and functional biodiversityof macrofauna and nematofauna has been assessed in the soil un-der mature oil palm. In our experiment, the total density of mac-rofauna in litter ranged from 0 to 581 ind m�2; and in the 0e15 cmsoil layer, from 29 to 421 ind m�2 depending on the zone aroundthe palm. Sixteen taxonomic groups of macrofaunawere identified.The main taxa in the soil were ants (13e237 ind m�2), earthworms(11e120 ind m�2), Dermaptera (0e35 ind m�2), Coleoptera(3e24 ind m�2) and Chilopoda (0e43 ind m�2). The population oftermites was very low (3e4 ind m�2). The Shannon index for soilmacrofauna ranged from 0.93 to 1.74. PCA analysis separatedearthworms from the other taxa. The density of nematofauna alsovaried depending on the zone around the palm (between 268 and805 ind 100 g�1 of soil). The difference between the zones wasreflected in the density of the functional groups, the group ofmacrofauna mainly comprised soil engineers, detritivores andpredators and the group of nematofauna mainly bacterial feeders.

Our results support the division of the area around the tree intozones with specific organic ground cover and inputs: the weededcircle (zone C) around the palm had the highest chemical fertility (P,K, Ca, Mg, Corg CEC, base saturation) and accounted for 14% of theplot. The biodiversity of this zonewas average but it had the highestdensity of earthworms and soil nematofauna. The biomass of theorganic cover in the windrow (zoneW), which received the prunedfronds, was clearly the highest. Zone W was the biggest zone, andaccounted for 65% of the plot. Total macrofauna density in the soiland litter was double that in zone C and six times higher than thatin zone PC. However, soil nutrient content and the density ofearthworms and soil nematofauna in zone W were no higher thanin zone PC. Zone PC, the zone between zone P and zone C,accounted for 16% of the plot. The organic cover, macrofauna den-sity and soil nutrient content were low in this zone. The macro-fauna were mainly ants, earthworms and Aranea. PCA analysisclearly separated zones P and PC from the other zones. To increasethe efficiency of sampling and analysis, we recommend mergingzone P with zone PC and zone CW with zone W. In the presentstudy, the mean of the parameters for the plot was weighted ac-cording to the respective area of each zone. It would also have beenpossible to calculate the plot weighted mean with the simplifiedformula: [(PC � 0.19)þ (C � 0.14) þ (W � 0.67)]. The number ofzones and their respective area may differ depending on the waythe practices are implemented. Consequently, the formula shouldbe adapted to each individual case.

Acknowledgements

We are grateful to PT-Smart for providing financial support forthis study. We warmly thank the technical team of Smart ResearchInstitute at Libo for their help in sampling field data and for soilchemical analysis. We also thank D. Goodfellow for English lan-guage correction.

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