Are the spatio-temporal dynamics of soil-feeding termite colonies shaped by intra-specific...

Ecological Entomology (2011), 36, 776–785 DOI: 10.1111/j.1365-2311.2011.01328.x

Are the spatio-temporal dynamics of soil-feedingtermite colonies shaped by intra-specific competition?T H O M A S B O U R G U I G N O N,1,! M A U R I C E L E P O N C E 2 and Y V E SR O I S I N1 1Evolutionary Biology and Ecology, Department of Organism Biology, Universite Libre de Bruxelles, Brussels,Belgium and 2Section of Biological Evaluation, Department of Education and Nature, Royal Belgian Institute of NaturalSciences, Brussels, Belgium

Abstract. 1. Soil-feeding termites are abundant and diversified in neotropical forests,where they are among the major decomposers of the soil macrofauna. While nichespecialisation along the humification gradient may reduce inter-specific competition,some species are represented by numerous colonies likely to be involved in intra-specific competition, but the subterranean nesting habits of most species of soil-feedingtermites make direct observations difficult.

2. The soldierless species Anoplotermes banksi Emerson was studied, which, unlikeother Anoplotermes-group species, builds arboreal nests that can be easily detected.To infer the biological processes driving the spatial distribution of this species, weconducted a 3-year survey of the dynamics of colonisation of a 1-ha plot by A. banksi.Ripley’s L-function, detecting aggregation or dispersion at various spatial scales, wasused to investigate the distribution pattern of A. banksi nests, as well as the distributionof new and established nests.

3. Only one-fourth of the nests recorded the first year were still alive after 3 years,highlighting a rapid turnover of the A. banksi nest population. Age classes weredifferentially affected by mortality, which was higher in young nests than in large,established nests.

4. Established nests were overdispersed at a short range, whereas young nestshad a random or clumped distribution. Young nests tended to be overdispersed fromestablished ones and were more abundant in areas with recently dead nests. Dead nestspredominantly occurred where A. banksi nests were particularly abundant. Altogether,the present results indicate a negative interaction between neighbouring coloniessuggesting intra-specific competition.

Key words. Apicotermitinae, humivorous termites, Isoptera, point pattern, Ripley’sL-function, termite nest, Termitidae.

Introduction

The most diverse termite family, the Termitidae, includesmany conspicuous species which may build huge moundsexceeding a man’s height (Grasse, 1984; Noirot & Darlington,

Correspondence: Yves Roisin, Evolutionary Biology and Ecology,CP 160/12, Department of Organism Biology, Universite Libre deBruxelles, Avenue F.D. Roosevelt 50, 1050 Brussels, Belgium. E-mail:[email protected]

!Current address: Division of Biosphere Science, Graduate Schoolof Environmental Science, Hokkaido University, Sapporo 060-0810, Japan.

2000; Korb, 2011). When established, the colonies of somespecies can live for several decades (Nutting, 1969). How-ever, besides a few records highlighting long-lasting coloniesof fungus-growing termites and some xylophagous termitids,it is likely that many species have shorter-lived colonies. Inthe humivorous termite Cubitermes speciosus Sjostedt, thelife expectancy of young settled colonies was estimated at3.5 years, with a rapid colony turnover (Soki et al., 1996).Unfortunately, information on other humivorous species isscarce and we do not know whether a quick turnover ofcolonies is commonplace or not.

An important factor influencing colony establishment,development, and survival in social insects is intra-specific

! 2011 The Authors776 Ecological Entomology ! 2011 The Royal Entomological Society

Spatio-temporal dynamics of soil-feeding termites 777

competition. In ants, individuals from different colonies of thesame species generally interact agonistically, often resultingin nest overdispersion (e.g. Levings & Traniello, 1981;Ryti & Case, 1986; Folgarait et al., 2007; Boulay et al.,2010), although sometimes, competition does not lead tothis pattern (Pielou, 1960; Gordon, 1997). Other mechanisms,such as a limited availability of nesting sites, may alsoconstrain the distribution of colonies and produce such apattern (Foitzik & Heinze, 1998). Although nest overdispersionis widespread in many ant species, random or clumpeddistributions occasionally occur as well. The former casesuggests an absence of an interaction between colonies whichspread over a homogeneous area (e.g. Kenne & Dejean,1999), whereas the latter is typical of polydomous species(Debout et al., 2007), or species specialised in a particularmicrohabitat (Soares & Schoereder, 2001). The distributionpattern may also depend on species abundance (Gordon, 1997);for example, mounds of the ant Formica altipetens Wheelesare clumped when the nest density is low but overdispersedwhen the density is high (Ryti, 1991). Like ants, termitecolonies often interfere agonistically. In arboreal-nestingNasutitermes, colonies defend their foraging area during fightswhich can involve intra- or inter-specific opponents (Thorne,1982; Levings & Adams, 1984; Thorne & Haverty, 1991),either leading to neighbour colony shunning or to activeelimination of the weaker contestant (Levings & Adams, 1984;Leponce et al., 1996, 1997). These mechanisms are likely tolead to nest overdispersion, a pattern observed in fungus-growing and in grass- and wood-feeding termites (Wood &Lee, 1971; Spain et al., 1986; Buschini, 1999; Grohmannet al., 2010). Soil-feeding termites form an abundant butunderstudied component of tropical rainforests (Braumanet al., 2000; Jones & Eggleton, 2010), but most of them livein subterranean colonies and almost nothing is known aboutinteractions between their colonies. Species may be segregatedfrom each other by the selection of different food sources(Bourguignon et al., 2009), but whether or not intra-specificcompetition occurs and may lead to nest overdispersion isnot known.

Investigating nest spatial distribution can bring power-ful evidence of competition, polydomy, nest site limita-tion or specialisation towards heterogeneously distributedresources. However, one has to recognise hierarchical levelsand apply the right model to interpret the spatial structure.For example, Macrotermes nest distribution was alternativelyreported aggregated, random or overdispersed, using nearest-neighbour analysis (Collins, 1981; Lepage, 1984; Pomeroy,1989; Schuurman & Dangerfield, 1997). These inconsistentresults may reflect a true pattern, but could also be arti-facts caused by (i) uncorrected edge effects for mounds closeto the limits of the studied area, or (ii) a lack of dis-crimination between age classes. Taking these two factorsinto account, Korb and Linsenmair (2001) found that largenests of Macrotermes bellicosus Smeathman were overdis-persed whereas small ones were aggregated, probably reflect-ing, respectively, competition and microhabitat selection. Asimilar pattern was observed by Grohmann et al. (2010) forM. subhyalinus Rambur.

Fig. 1. Mature nest of Anoplotermes banksi. Scale bar represents10 cm.

Nest temporal dynamics and spatial distribution are intrin-sically linked, but have rarely been investigated together,although young and old colonies are likely to be influencedby different factors (see Korb & Linsenmair, 2001; Grohmannet al., 2010). In the present study, we investigated the nestdistribution and demography of Anoplotermes banksi Emer-son, which differs from species whose spatial pattern waspreviously investigated in being a soil-feeder. Soil-feedingtermites form an abundant but understudied component of trop-ical rainforests (Brauman et al., 2000) with a generally crypticlifetype, making them difficult to study via direct observa-tion. In this respect, A. banksi is a particularly suitable modelbecause it is among the few species building conspicuousaboveground nests on trees (Fig. 1), which are easy to map.Here, we monitored a 1-ha plot for 3 years in order to shedsome light upon small-scale population dynamics. Our aim wastwofold:

1 Demographic studies have seldom been carried out onsoil-feeding species (Soki et al., 1996). In the presentstudy, we describe the evolution of A. banksi nests ina demographic perspective through estimations of nestfounding, death, and replacement rates. We also estimatedthe nest growth rate and the density of A. banksi in a1-ha plot.

2 Termite nest distribution might be influenced by severalfactors, among which intra-specific competition is oneof the most commonly cited (e.g. Korb & Linsenmair,2001). We investigated the nest distribution of A. banksi,distinguishing age classes to test the influence of intra-specific competition.

! 2011 The AuthorsEcological Entomology ! 2011 The Royal Entomological Society, Ecological Entomology, 36, 776–785

778 Thomas Bourguignon, Maurice Leponce and Yves Roisin

Materials and methods

Study site

Fieldwork was carried out in a rainforest-covered valleynear Petit Saut dam (N 05"04#, W 052"59#) in French Guiana.The Petit Saut area experiences a humid tropical climate withabout 3000 mm of rainfall per year, mostly distributed duringa rainy season occurring between January and June, and witha comparatively drier season from September to November.The mean annual temperature is 26 "C. Petit Saut was almostfree of human disturbance until 1994, when the area waspartially flooded by the hydroelectric dam (for further details,see Cosson et al., 1999). The study area is relatively flatwith a maximum difference in altitude of about 5 m and issituated on the bottom of a valley. During intensive rains,water flows from surrounding hills, soaks the soil and floodsthe area in shallow water. Besides these sporadic events, thearea was free of water except for several small creeks, running

through the area with a flow depending on recent rain intensity(Fig. 2). The vegetation consisted of palm trees of variousgenera, including some rare Euterpe, as well as many treeswith pneumatophores. One sampling transect near to the studysite revealed a characteristic termite fauna comprising severalAnoplotermes species, including three nest-building species:A. banksi, A. parvus Snyder, and A.nr. distans (site Pswain Bourguignon et al., 2011a). In the present study, we onlystudied the first species because the other two were far lesscommon.

Nest sampling

The study site consisted of a 100 m $ 100 m plot, dividedinto a grid of 400 squares of 5 m $ 5 m (Fig. 2). The gridwas set up in February 2007 and carefully inspected forA. banksi nests in February 2007, January 2008, February2009 and January 2010. Each nest was labelled, located onthe grid, measured, and checked for live termites. If alive,

Fig. 2. Maps of the 1-ha studied plot, depicting the nest population of Anoplotermes banksi during the four consecutive samplings between February2007 and January 2010. Black circles: nests recorded in 2007 (history unknown). Open squares: dead nests (recorded alive the previous year); fulldiamonds: established nests (already present the previous year); grey triangles: new nests (not recorded the previous year). The continuous doublelines represent the creek.



a voucher sample of a few workers was placed into 80%ethanol after scraping off a small piece of the nest envelope orgalleries departing from the nest. Specimens were examinedin the lab under a stereomicroscope to confirm the speciesidentity and avoid any confusion with A. parvus and A.

nr. distans, and to verify that the nest was still inhabitedby the original builders. Nest measurements included height(herein H ), width (W ), and thickness (T ). Their volume (V )was then estimated assuming that nests have an ellipsoidalshape using the formula:

V = !HWT

6(1)

Demography

As we sampled the nests four times over consecutive years,we could from the second year on recognise three categories ofnests: live nests were labelled ‘established nests’ if they werealready present the year before, and ‘new nests’ if they werenot; nests that were alive the year before but died were recordedas ‘dead nests’. We calculated the following demographicparameters for nests: death rate (" ), founding rate (#), and thenatural increase rate of the population (R). These parameterswere estimated using the formulas:

" = 1t

lnN0

S, (2)

# = 1t

lnN

S(3)

and

R = # % " (4)

with t being the time elapsed between the two records, N0the total number of live nests at time 0, N the total numberof live nests at time (0 + t) and S the number of establishednests at time (0 + t) (see Soki et al., 1996). To allow a directcomparison between years, we chose to express t in months.These parameters were estimated for each period between twoconsecutive sampling years, as well as between the first andthe last one.

To test whether the death rate, founding rate, and the totalnumber of nests differed between years, we computed $2-testson the total number of dead and new nests and on the totalnumber of nests recorded each year, respectively. To testwhether the average nest volume differed between years, wecarried out a Kruskal–Wallis test using estimated nest volumeas data input. We also tested whether the volume of nestsin the years 2007, 2008, and 2009 differed between neststhat survived and nests that died during the following year(Mann–Whitney U -tests). The nest growth rate was visuallyestimated with box plots, using new nests as starting points.Finally, we estimated the total termite number in our 1-haplot for each year using the following formula, establishedby Josens and Soki (2010) for A. banksi on the basis ofMartius and Ribeiro’s (1996) data: for any given nest, log10N = 4.73 + 0.67 log10V , with N being the number of indi-viduals and V the nest volume.

Nest distribution

Maps of nest position were generated for each samplingyear (Fig. 2). We used Ripley’s L-function to investigatethe nest distribution using the grid-based approach with thefreeware Programita (Wiegand & Moloney, 2004). The edgecorrection used numerical implementation for a grid-basedapproach as described in Wiegand and Moloney (2004).Ripley’s L-function can detect aggregation or dispersion up toa given distance r and is, therefore, suited to study the negativeeffect of competition. The analyses were carried out for eachyear separately. Distribution patterns were emphasised aftercomparison of the L-function to 5% confidence envelopes,computed according to the complete spatial randomness (CSR)null model. The envelopes were calculated from the 50thlowest and highest estimation taken from 999 Monte Carlosimulations of the CSR model. The L-function curve goesbelow the 5% lowest confidence envelope when nests areoverdispersed up to distance r , whereas the curve goes abovethe 5% highest envelope when the pattern is aggregated.We investigated the distribution of all A. banksi nests, aswell as the distribution of new nests and established nestsseparately, using the univariate L-function for homogeneouspoint pattern. We also studied the interaction between differentcomponents of the main pattern using the bivariate L-function,L12. To determine the relationship between new nests andestablished nests, and between new nests and dead nests,we computed the L12-function and we calculated confidenceenvelopes using 999 Monte Carlo simulations. In both cases,we kept the latter pattern fixed, because it represented theantecedent condition, and randomized the former. Finally, weinvestigated how dead nests are distributed in the populationusing a random labelling model. The question here was: wheredo nests die within a population of established nests? To doso, we calculated the pair-correlation function g21(r) – g22(r)

and g21(r) – g2,1+2(r) using the random labelling model and999 Monte Carlo simulations to obtain confidence envelopes(pattern one was live nests whereas the pattern two wasdead nests). The first function investigated whether there weremore dead nests around dead nests than around live nests,suggesting the influence of a local condition; the secondfunction investigated whether dead nests occurred in areasmore densely populated by A. banksi nests.

Results

Demography

Overall, 151 nests of A. banksi were recorded betweenFebruary 2007 and January 2010, with an average numberof 63 nests each year (Fig. 3). The nest founding ratewas higher than the death rate every year, resulting ina natural increase of the population (Table 1). However,we did not find any significant difference in the numberof nests present during each sampling event ($2 = 5.17,

d.f. = 3, P = 0.159). The same was true for dead nests($2 = 1.01, d.f. = 2, P = 0.602) and new nests ($2 = 4.56,



Year

2007 2008 2009 2010

Num

ber

of li

ving

nes

ts

0

20

40

60

80

2007200820092010

Fig. 3. Survivorship curves of Anoplotermes banksi nests for consec-utive years.

d.f. = 2, P = 0.102) whose number did not significantly dif-fer between January 2008 and 2010, in spite of an apparentincrease in the founding rate. Comparison of the nest volumewith the Kruskal–Wallis test indicated a marginally signifi-cant variation between years (H3,251 = 7.72, P = 0.052). Thesame analysis carried out with the median test suggested adifference between years ($2 = 10.98, d.f. = 3, P = 0.012).Comparison of nest volumes for the years 2007, 2008, and2009 showed that the nests that died during the followingyear were on average smaller than the ones that survived(2007: U21,34 = 265, P = 0.11; 2008: U28,29 = 204.5, P =0.001; 2009: U24,38 = 304, P = 0.04). The nest growth rateis depicted in Fig. 4b. Nests recorded for the first time hadan average volume of 0.43 l, which increased to 0.76 l after1 year and to 1.39 l after 2 years. In contrast, their medianvolume was about half as high, rising from 0.20 l for newlyrecorded nests to 0.37 l after 1 year and 0.62 l after 2 years.Finally, the total volume of the nests varied between 62.7 and68.7 l ha%1 and the population density was estimated between337 and 369 individuals m%2.

Table 1. Demographic parameters of the population of Anoplotermesbanksi nests in the 1-ha plot calculated from each pair of successiveyears and for the whole observation period (February 2007 to January2010).

Sampling periodNumberof months

Numberof nests # " R

February 2007 toJanuary 2008

11 55–57 0.047 0.044 0.003

January 2008 toFebruary 2009

13 57–62 0.057 0.052 0.005

February 2009 toJanuary 2010

11 62–78 0.065 0.045 0.021

Febraury 2007 toJanuary 2010

35 55–78 0.039 0.049 0.010

(February 2007 to January 2010): foundation rate (#, proportion ofnew nest per month), death rate (" , proportion of dead nest permonth), and rate of natural increase (R, nest population increase permonth).

Nest distribution

Maps of A. banksi nests for each year are representedin Fig. 2. When considered all together, nests were initiallyoverdispersed in the first 2 years, from 10 to 20 m in 2007and from 10 m up to 50 m in 2008, but this trend almostdisappeared in 2009 and was only slightly significant between5 and 10 m, whereas in 2010 the distribution was completelyrandom (Fig. 5a). By retaining only the established nests, wefound an overdispersed pattern for all years (Fig. 5b). Nestswere overdispersed between 10 and 20 m in 2008, at 10 and15 m in 2009, and at 5 and 10 m in 2010. In contrast, newnests were randomly distributed in 2008 and 2009, except fora slight clumped distribution at 40 m and 45 m in the latteryear, whereas in 2010, nests were slightly clumped at 10 and15 m and then again at 25 m (Fig. 5c).

New nest establishment and nest death did not occurrandomly in the area. We found a negative association betweenestablished nests and new nests for the years 2008 and 2009,from 15 to 45 m and at 5 and 10 m, respectively. In contrast,the patterns were independent in 2010 (Fig. 6a). When wecarried out the same analysis for dead nests and new nests, wefound no interaction in 2008 but a slight positive associationthe two subsequent years, from 10 to 25 m and then to35 m again in 2009, and at 5 and 10 m in 2010 (Fig. 6b).There was no spatial association between dead nests, exceptin 2009 when dead nests were aggregated from 20 to 35 m(Fig. 6c). However, this larger-scale aggregation is unlikely toreflect direct interactions between nests. Finally, dead nestsoccurred predominantly in areas with a more intense joinedpattern in 2008 and 2009, that is, in areas where A. banksinests were particularly abundant (Fig. 6d). Indeed, we founda positive association at 10 and 20 m in 2008, and at 10 m in2009.

Discussion

Demography

In the present study, we investigated the colonies whichsucceeded in establishing their nests on aboveground supports.However, incipient colonies do not establish themselvesdirectly aboveground, but rather in the soil where the founderscan rear brood from their fat reserves and possibly throughfeeding on soil themselves (Nutting, 1969). During thisfoundation phase, many colonies presumably die, makingobserved nest mortality an underestimated measure of colonymortality. Similarly, newly recorded nests have to be youngerthan the colonies themselves. However, the lapse of timebetween colony founding and aerial nest building is probablynot longer than 6 months, because nest establishment on anelevated support represents a specific mechanism to avoidsporadic flooding during the rainy season (Martius, 1994). InA. banksi, nuptial flights occur between May and June, aswe only observed nymphs in April, although we surprisinglyfound alates once at the end of January. In May to June, therain intensity drops considerably and only returns to the rainyseason level 6 months later.



2007 2008 2009 2010

Vol

ume

(L)

0

1

2

3

0

1

2

3

new nests 1 year 2 years

n = 56

n = 27

n = 7

n = 55n = 57 n = 62

n = 78

(a) (b)

Fig. 4. (a) Volume of Anoplotermes banksi nests for each observation period; (b) volume of new nests (2008 + 2009 + 2010 pooled), of nestsestablished for 1 year (new in 2008 or 2009 and recorded the following year, two series pooled), and of nests established for 2 years (new in 2008and still recorded in 2010). Solid lines represent the median and dotted lines the mean nest volume. Box plots delimit the first and the third quartilesand the whisker caps the 10th and 90th percentiles.

2007

5 10 15 20 25 30 35 40 45 50

Rip

ley’

sL(

r)

-0.4-0.3-0.2-0.10.00.10.20.30.4(a)

(b)

(c)

2008

5 10 15 20 25 30 35 40 45 50-0.4-0.3-0.2-0.10.00.10.20.30.4

2009

5 10 15 20 25 30 35 40 45 50-0.4-0.3-0.2-0.10.00.10.20.30.4

2010

5 10 15 20 25 30 35 40 45 50-0.4-0.3-0.2-0.10.00.10.20.30.4

2008

5 10 15 20 25 30 35 40 45 50

Rip

ley’

sL(

r)

-0.6

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0.0

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2010

5 10 15 20 25 30 35 40 45 50-0.6

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2008

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5 10 15 20 25 30 35 40 45 50

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ley’

sL(

r)

-0.8

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2009

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5 10 15 20 25 30 35 40 45 50-0.6

-0.4

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Spatial scale r (m)

5 10 15 20 25 30 35 40 45 50-0.6

-0.4

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0.6

Fig. 5. Temporal change in spatial pattern for (a) all nests, (b) established nests, and (c) new nests. Open circles represent the Ripley L-function.Full circles represent the 95% confidence envelopes computed under the complete spatial randomness (CSR) null model (). Results below the lowerconfidence envelope indicate nest overdispersion at the given spatial scale; results above the higher envelope indicate aggregation.

The population of A. banksi nests was stable during our3-year survey. We did not find any significant differencesbetween years in total nest number, death rate, and foundingrate, although a slight increase in the nest population wasobserved. However, nest volume slightly varied from year toyear, especially when the median value was considered. Thiswas mainly caused by the 2010 sampling, when many newnests were found, decreasing considerably the median nestvolume value.

On average, we found 63 nests ha%1 and estimated thetotal population at about 350 individuals m%2, which is,respectively, four and ten times more than the previousrecords from the central Amazonian terra firme rainforest(Martius & Ribeiro, 1996). This suggests that nests of A.banksi were on average larger and more populous in ourstudied plot. Other records of nest density in Anoplotermesspecies or related genera mentioned up to 362 nests ha%1 inan unidentified species of Anoplotermes in flooded forests



2008

5 10 15 20 25 30 35 40 45 50

g21

– g2

2(r)

-0.8

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2008

Spatial scale r (m)5 10 15 20 25 30 35 40 45 50

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– g2

.1+2

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(b)

(c)

(d)

Fig. 6. The temporal change in the spatial pattern of (a) established nests of A. banksi (fixed pattern) against new nests (randomized pattern),(b) dead nests (fixed pattern) against new nests (randomized pattern), (c) dead nests against other dead nests, and (d) the joined pattern (dead nestsand live nests) against dead nests. Open circles represent the L12-function. Full circles represent the 95% confidence envelopes either computedunder (a, b) the complete spatial randomness (CSR) null model, or (c, d) under random labelling. Results (a, b) below the lower confidence envelopeindicate pattern 2 repulsion (randomized pattern) compared with the pattern 1 (fixed pattern) at the given spatial scale; results above the higherenvelope indicate attraction. Results (c, d) below the lower confidence envelope indicate a negative association of the two patterns, results abovethe higher envelope indicate a positive association.

(Martius, 1997), whereas in the African rainforest, anotherhumivorous termite, Cubitermes fungifaber Sjostedt, can reacha density of 875 nests ha%1 (Lepage & Darlington, 2000).

Between one-third and one-half of the nests of A. banksidied every year and only 25% of the nests recorded in 2007were still alive 3 years later (Fig. 3). Nest turnover is thus quiterapid in A. banksi and similar to, or even slightly faster than,C. speciosus in which one-fourth of the nests died every year(Soki et al., 1996). In contrast, records from wood-feeding orfungus-growing termites suggest a lower death rate, although

the results are contrasted and vary according to the species(Lepage & Darlington, 2000). However, the death rate isdependent on age classes and we found that young nests do notface the same ecological constraints as large, established nests,but a higher mortality from predation and other causes. Thiswas also observed in Macrotermes jeanneli Grasse (Darlingtonet al., 1992) and Nasutitermes acajutlae Holmgren (Jeyasingh& Fuller, 2004) and could result from factors such as exclusionby competition, a higher vulnerability of small colonies topredators or diseases, or environmental heterogeneity resulting



in large, old nests developing in the best places while newcolonies settle at random, independently of site quality. Whenthey survive, new nests grow rapidly and are able to doubletheir volume during the first year and again during the secondone, until they become large nests which may almost stopgrowing for several years. Some nests of A. banksi hardly grewfor 3 years, between our first and last monitoring campaigns. Inthe same way, large nests of the African species Cubitermesspeciosus can retain the same size for 4 years (Soki et al.,1996); nest size is thus a poor indicator of colony age, apartfrom indicating that large nests are already several years old.

Spatial distribution

Our main assumption is that nest distribution is notinfluenced by colony migration, as nests are completely sessileand do not move once established. Indeed, we did not find anysigns of colony migration after nest establishment in A. banksi,although this has been reported in a few other species (Grasse& Noirot, 1951; Noirot et al., 1986).

When considered all together, no matter their age class,nests of A. banksi were overdispersed at a short scale. Thiswas true for all years excepted for 2010 when nests were ran-domly distributed in the area. The same year, we found abouttwice as many new nests as in 2008, thus increasing the rationew nests/old nests. The population of colonies may thereforevary considerably from year to year, affecting the spatial dis-tribution. In the case of 2010, new nests were abundant andpresented a clumped distribution at various distances below50 m, whereas established nests were overdispersed below10 m and random at larger distances, making the overall nestpattern random. This highlights the importance of distinguish-ing age classes in point pattern analysis, because juveniles arenot subject to the same constraints as mature nests (Korb &Linsenmair, 2001; Grohmann et al., 2010) and their relativeproportion may greatly affect the overall spatial pattern.

Overall, A. banksi colonies seem to interact negatively,causing nest overdispersion in our studied plot: (i) Analysesof the spatial pattern of established nests revealed that theywere overdispersed every year at a short scale, which mayreflects negative interactions between neighbouring colonies.Overdispersed patterns can also result from nesting sitelimitations (Soares & Schoereder, 2001), but for A. banksi,adequate supports, which include trees, palms or lianas, arein large excess and distributed at a much smaller scale thanthe nest themselves. Additionally, young nests did not presentoverdispersed patterns at any scale, as would be expected inthe case of nesting site limitation. Established nests are largeand populous, and thus supposedly interact more strongly thanyoung nests, whose distribution patterns were random in 2008and 2009 and aggregated at many scales in 2010. (ii) After theyearly swarming event, mating pairs must found their colonyin a habitat already occupied by established nests. We foundthat young nests apparently minimise the interaction with largeones as young nests were overdispersed from established onesat all scales in 2008 and below 10 m in 2009, although theirdistribution was random in 2010. Also, new nests tended to

appear in the 10 m surrounding freshly dead nests in 2009 and2010. This suggests that new colonies preferentially develop inplaces recently left free from conspecific interactions. Possibly,mating pairs establish their nests at random and then areeliminated in areas already densely inhabited by A. banksi ;or, alternatively, young colonies select a nest site in order todiminish interactions with established nests. This site selectionwould probably occur during the establishment of the definitiveaboveground nest. (iii) Nest death did not occur randomlyin our studied plot. We found that nests were more likelyto die in areas with a high density, as reflected by thepositive association between dead nests and new nests at the10-m scale in 2008 and 2009. In these areas, workers fromdifferent colonies are more likely to meet, which increasesinteractions between colonies. On the contrary, diseases spreadbetween neighbours or other local effects were unlikely factorsof mortality during our 3-year survey, as we did not findany spatial association between dead nests. However, evenalthough the interaction between nests seems to play animportant role in shaping the dead nest distribution pattern,other causes such as predation, destruction of the nest support,and senescence are probably involved in nest mortality (Lepage& Darlington, 2000), but probably occur randomly in the area.Interestingly, although different patterns follow similar trendsfrom year to year, they are not always completely similar,possibly reflecting fluctuations in environmental conditionssuch as those related to the El Nino climatic oscillation. Forexample, the high number of new nests in 2010 could resultfrom particularly favourable conditions, as the climate wasespecially dry during the preceding year (Global PrecipitationClimatology Centre: http://kunden.dwd.de/GPCC/Visualizer).

Although competition does not necessarily imply individualoverdispersion (Pielou, 1960; Ryti, 1991; Gordon, 1997),the presence of this pattern is often interpreted as evidenceof competition. Indeed, the negative interaction betweenA. banksi colonies may reflect competition, either throughdirect interaction and agonistic behaviour between differentcolony members, or through indirect depletion of limitingresources. In this way, nest overdispersion might be aconsequence of colony interactions, taking place in theforaging area. One possible resource over which colonies couldcompete is obviously their main food source. In the wood-feeding genus Nasutitermes, the nest volume is correlated withwood availability (Jeyasingh & Fuller, 2004) and the regulardistribution of Macrotermes nests seems to be indirectlycaused by food deprivation (Korb & Linsenmair, 2001).Limited humus availability could also limit soil-feeding termitepopulations and indirectly generate a regular distributionof established nests through competition. Another possibleresource over which colonies of A. banksi could compete issoil nutrients. Kaspari et al. (2009) recently found that termiteabundance increased seven-fold on plots that averaged three-fold more sodium, suggesting that this element is an indirectlimiting factor.

We estimated that A. banksi density was about 350individuals m%2. This makes an important part of thetotal termite abundance which is often estimated at about2000–3000 individuals m%2 in primary rainforests (Bignell &



Eggleton, 2000). Anoplotermes banksi colonies, which relyupon a definite state of humification of the organic matter(Bourguignon et al., 2009), might actually saturate the habitat.Their niche specialisation minimises interference with othertermite species, although some feed at the same level inthe humification gradient and may, therefore, compete withA. banksi (Bourguignon et al., 2009, 2011b).

Although A. banksi nests tend to be overdispersed at ashort scale (generally below 10–20 m) in our studied plot,the selection of an appropriate habitat might produce differentdistribution patterns at another spatial scale. For example,Dangerfield (1990) found that nests of Cubitermes sankurensisWasmann show an aggregated pattern because they concentratein forest patches with an open rather than a closed canopy. AsA . banksi nests are particularly abundant at the bottomof valleys or near creeks (Bourguignon et al., 2011a), theirdistribution pattern is probably aggregated at the landscapescale, reflecting an association with their preferred habitat.Intrinsic species characteristics such as polydomy (Levings &Adams, 1984; Holt & Easey, 1985; Spain et al., 1986) mayalso influence nest distribution, but do not fit with our data onA. banksi.

Acknowledgements

We are grateful to Philippe Cerdan and the staff of theLaboratoire Environnement de Petit Saut for logistical help.Financial support was provided by the Fund for ScientificResearch (F.R.S.–FNRS), Belgium, through travel grants anda FRIA predoctoral fellowship to T. Bourguignon, and bythe CNRS-Guyane, through project Amazonie (Prof. AlainDejean).

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Accepted 5 October 2011


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