Obstacle Size and Trail–Clearing Activity in Leaf–Cutter Ants, Atta colombica

Tropical Ecology • February 2015 • Ecology and Evolutionary Biology

Obstacle Size and Trail–ClearingActivity in Leaf–Cutter Ants, Atta

colombica

Maxson Jarecki

Princeton [email protected]

Abstract

This study on Atta colombica leaf obstacle removal found that there is a power curve relationshipbetween leaf obstacle length and its removal time. Leaf obstacles over 5cm long were cut using the sametechniques as used in leaf harvesting. This study was conducted across 3 forests of varying rainfall levelsin Panamá. Though there were no significant differences found between forests and time periods (morningand afternoon), a larger study may reveal differences based on humidity, elevation, temperature, sunexposure, and microclimate variation due to weather and vegetation. Further research must be conductedto fully examine the effect these variables have on the individual obstacle removal rates of these forests.

Keywords: Atta colombica; rainfall gradient; Panamá; trail maintenance; obstacle removal.

I. Introduction

Atta colombica is a species of fungus grow-ing leaf–cutter ant; its range reachesthroughout the Neotropics (Ghazoul

and Sheil 2010). It is distinguished from itsrelative, Atta cephalotes, by a missing tuft ofreddish hair, and by its aboveground refusedumps, as cephalotes dump underground. Theyare part of the myrmicine tribe Attini, alongwith macrotermitine termites and some wood–boring beetles, members of which are distin-guished by their unique ability to cultivate andconsume fungi (Wirth et al. 2003). Atta colom-bica colonies can contain several million ants,and they can build large nests as deep as 6meters underground (Ghazoul and Sheil 2010).Their farmed fungus, Leucoagarius gongylopho-rus, only exists in the wild within leaf–cutterant nests (Ghazoul and Sheil 2010).

Atta colombica antennae, mouthparts, andlegs each contribute to the obstacle removalprocess that this study investigates. Dr. M.V.Brian provides a good summary of ant phys-iology in his book, Ants (1977). Their anten-

nae allow Atta to process the size and shapesof objects in their environment. They can bemoved, and can be spread wide apart to com-prehend large objects, or brought close togetherto sense objects less than a millimeter in diam-eter. The antennae also detect chemicals andpheromones laid down by other foragers, in ad-dition to sensing vibrations in the substratum.Atta mouths are surrounded and enclosed byseveral pairs of articulated appendages, themost prominent of which are the mandibles(Brian 1977). These main jaws are hollow, butare composed of thick walls. They are solidlyattached to the ant head and can be openedwidely, and closed tightly. Finally, Atta legseach have five main joints. The outermost joint,however, is finely articulated by further smalljoints to make a flexible “foot.” Each leg is ex-ceptionally maneuverable, and can move overrough and irregular terrain; even up verticaland overhanging surfaces. The ant’s hind legsare the longest, and are long enough to lifttheir body clear off the ground (Brian 1977).

These leaf–cutting ants are the most dom-inant herbivores in the New World tropics

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(Wilson 1986), and as “generalist herbivores,”Colombica ants have an enormous effect on theecosystems they inhabit (Wirth et al. 2003).Their role as agricultural pests have promptedleaf–cutting ants like Atta colombica to beamong the most studied tropical insects (We-ber 1972; Hölldobler and Wilson 1990; Fowleret al. 1990). Because of their role as pests, mostof the research surrounding these tropical antsrevolves around their control (Vander Meer etal. 1990). Their yearly neotropical agriculturaldamage has been valued to cost thousands ofmillions of dollars (Cherrett 1986). However,there is also much research regarding Atta be-havior.

Specifically, their foraging strategies havebeen a topic of inquiry. The distribution of Attaforaging over a large area through trails, ratherthan simply foraging around the nest, has beena major subject of study (Cherrett 1986; Fowlerand Styles 1980; Rockwood and Hubbell 1987;Shepherd 1982). Foraging efforts are arrangedthrough these trails to promote the discoveryof items in productive areas (Shepherd 1982).Also, the recruitment pheromone laid downon these trails can convey information aboutlocation and quality of resources (Hangartner1969). There is research on the performance ofworkers utilizing trails (Lutz 1929; Hubbell etal. 1980; Rudolph and Loudon 1986, Lightonet al. 1987, Waller 1989; Shutler and Mullie1991; Wetterer 1994; Burd 1995). There arealso many studies on the use of trail systems(Fowler and Robinson 1979; Fowler and Stiles1980; Shepherd 1982; Rockwood and Hubbell1987). There is less information, though, on theorigins of these foraging trails: where they are,how they are constructed, and how they aremaintained (Shepherd 1985; Farji Bener andSierra 1993; Howard 2001).

Foraging trails allow Atta ants to locate re-sources once they have exited the nest (Höll-dobler 1977; Shepherd 1982; Fowler and Stiles1980). Trails have also been linked to reduc-ing aggressive encounters between neighboringcolonies whose resource areas overlap (Vilelaand Howse 1986; Farji Bener and Sierra 1993).Their trails are broken into two types, “trunk”

trails (like the trunk of a tree), and ephemeraltrails (Howard 2001). These trunk trails arefairly permanent, persisting from a few monthsto several years (Howard 2001). Colombicacolonies manage trail systems that average267 meters in length, and build an estimated2.7 kilometers of trail per year (Howard 2001).Through his calculations, Howard concludedthat the energetic costs of trail clearing arenegligible in the context of the vast numberof available workers and their rate of harvest(2001). It is interesting to note that these long–lasting trails persist despite Atta’s foraging onpatchy and ephemeral leaf resources (Rock-wood 1975; Fowler and Stiles 1980; Shepherd1985). These trails can be easily identified inthe forest, as they are often clear of debris. Thistrail clearing has been shown to facilitate moreeffective locomotion (Rockwood and Hubbell1987). In fact, Rockwood and Hubbell foundthat colony investment in trail–making repaidbetween four– and ten–fold in reduced travelcost (1987). Also, the more effective applica-tion of trail pheromones to the smoother sub-strate offered by a cleared trail may increasethe strength and persistence of these trunktrails, which may allow ants to relocate andexploit resources more effectively (Wirth et al.2003). Hölldobler and Lumsden developed acost–benefit equations to examine the energeticfrictional cost of trail locomotion and trail con-struction (1982).

Cf = gNtot

Cf is frictional cost, Ntot is the number ofloads carried, and g is a cost–per–ant coeffi-cient. G is higher in a litter–covered forest floorand lower in a cleared area (Hölldobler andLumsden 1980) (Fig. 1).

Ct = aNmax + bNmaxT

Ct is the cost of clearing and maintaininga trail. It increases with the area of the trail,aNmax, and the amount of time the trail is used,bNmax (Hölldobler and Lumsden 1980) (Fig. 1).

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Figure 1: Visual representation of the costs and benefitsof trail–clearing in Atta colombica.

Atta ants in a colony are divided into dif-ferent castes, primarily based on head size(Wirth et al. 2003). Lugo et al. (1973) esti-mated that up to 75% of ants on trails at agiven time do not carry leaves. They supposethat these ants are the ones most involved intrail–clearing. The most frequent head widthamong leaf carriers is between 2.0 and 2.2mm(Wirth et al. 2003). Howard found that largerworkers whose headwidths measure between2.2 and 2.9mm are most likely to be involvedin trail clearing (2001). His study confirmedthat ants clearing trails are significantly largerthan those carrying leaves. Ants involved intrail–clearing exhibit high task fidelity; clearerstend to clear, while foragers forage (Howard2001). Small litter items are carried off trails,while larger items are made smaller throughthe same leaf–cutting techniques Atta colombicaants use during foraging.

This investment in altering the obstaclegreatly increases its removal energy cost, butmakes its removal possible (Howard 2001). Hisstudy outlined the time and energy costs oftrail–clearing on a macro scale; those of acolony. He found that the costs of removing akilogram of litter were approximately 3,359 ant–hours and 4.6 kJ of collective energy (Howard2001). He then estimated that the total costof trail–clearing to a colony averaged 11,000ant–days of work (2001). The yearly energeticcost, though, was the equivalent of just 8,000

leaf–loads (Howard 2001). There is a majordiscrepancy between the importance of trail–clearing activity and its cost. Rockwood andHubbell (1987) found that there can be a ten–fold reduction in travel cost when a trail isproperly cleared. However, this instrumentalactivity takes only 8,000 leaf–burdens of en-ergy yearly. This annual cost can be recoveredin less than a day by an average–size colony(Howard 2001)! If these findings are correct,then trail–clearing may be one of the most ef-fective productivity–enhancing behaviors thesesocial insects perform. While Howard’s studywas a colony–wide investigation into time in-vestment, my own study involves an in–depthlook at this phenomenon on a micro scale. I in-vestigated the relationship between leaf lengthand obstacle removal time in Atta colombicacolonies during trail–clearing.

II. Methods

I conducted this study through three forests inPanamá over a rainfall gradient:

Pipeline Road: A lowland wet evergreen for-est with 2,131 mm rainfall per year at27m elevation.

Parque Natural Metropolitano: A lowlandsemi–deciduous forest with 1,850 mmrainfall per year at 30m elevation.

San Lorenzo: A lowland wet evergreen forestwith 3,152 mm rainfall per year at 130melevation.

Over the course of 9 study days during themonth of February, I located 5 Atta colombicacolonies per forest. I used these sites to testtheir leaf obstacle removal speed. I selected per-manent “trunk” trails and excluded all trailsthat were not approximately 75% cleared; trail

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clearance level was determined visually. I laidleaves of lengths between 1 cm and 24 cm downin the middle of these trails and timed colonies’obstacle removal times (ORTs henceforth).

Leaves were selected from the Swieteniamacrophylla, the big–leaf mahogany tree. Macro-phylla is an endemic tree species that offers awide range of leaf lengths in a standard shape.I gathered a large batch of macrophylla leavesof various sizes and stored them flat in plas-tic bags, creating a vacuum by sucking the airfrom each bag, and storing them in the dark.This was to minimize day–by–day variations inmoisture content.

I also performed an in–lab analysis on Swi-etenia macrophylla leaf length, width, mass, andsurface area correlations (Fig. 1). This workverified that there was a consistent linear rela-tionship between these variables. Leaf lengthsand widths were determined with a ruler, andleaf mass was determined with a scale. Fi-nally, surface area calculated using computer–analyzed photos of each leaf, through the pro-gram ImageJ R�.

Finding complete macrophylla leaves lessthan 4 cm long proved impossible, so I cre-ated leaf fragments by cutting larger leavesinto the correct shape. I selected removal sitesat least 10 feet apart from one another to min-imize the effect obstacles may have on eachothers’ ORT. Leaves were laid down horizon-tally across the trail to maximize blockage; eachleaf was placed upside–down to create a smallhill, increasing each obstacle’s effect on foragermovement.

I began ORT timing from the moment thefirst unladen ant touched the leaf, and endedwhen 95% of ants involved left the site. I alsonoted the occurrence of leaf–cutting behavioron the obstacle, as some obstacles were cut andsome were not.

Figure 2: Length and width, mass, and surface area havelinear relationships (N = 60). Linear regres-sion in JMP 11 found significance of r2 = 0.79,r2 = 0.91, and r2 = 0.90, respectively. Eachregression revealed a P < .0001.

I analyzed my leaf length and ORT mea-surements using CurveExpert Professional Ver-sion 1.2.2 (2011), a comprehensive data analysissoftware by D.G. Hyams.

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III. Results

All data gathered during the study reflects apower curve relationship between leaf lengthand obstacle removal time (n = 104, r2 = 0.619)(Fig. 1a). The power curve equation is:

y = axb

Each location and time period indepen-dently had power curve relationships betweenleaf length and obstacle removal time (Fig. 1b–1f).

Figure 3: Figures 1a—-1f, left to right. Each curvefollows the power equation y = axb. Theouter shaded area represents “b” standard er-ror, while the inner represents that of “a".

The variables a and b for each data set’sy = axb equation are located in Table 1. Theirstandard errors are included in italics.

Table 1: Regression values for each data set, to be inputto the power equation y = axb.

I projected average ORTs for for 3 leaflengths in Table 2 using the above data. Bychecking the ranges of these values accordingto their standard error I discovered that thereis no significant difference between these lo-cations and time periods. However, a largersample size may reveal significance.

Table 2: ORT estimations for 3 different leaf sizes. Thesetimes were calculated from regressions of y =axb from each site and time period.

Leaf length and presence or absence of cut-ting were highly correlated (Kruskall–Wallisnon–parametric t–test: Z = –7.21, p<0.001) (Fig.2). Leaves above 12 cm in length were alwayscut. The two outlying data points above 12cm in the “no” column were the only onesplaced on a severe incline, which allowed antsto remove them quickly and without cutting.Leaves between 12 cm and 5 cm varied, pos-sibly due to factors outlined in the discussion.Leaves below 5cm were never cut.

Figure 4: Leaf length and presence or absence of cutting.

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IV. Discussion

The most significant finding of this study is thepower curve relationship found between leaflength and ORT. One would assume that thistrail-clearing phenomena would increase lin-early: a 5 cm object taking 5 minutes, and a 25cm object taking 25. Instead, this exponentialincrease causes a drastic difference betweenobjects of of different sizes; a 5 cm leaf takes 5minutes, but a 25 cm leaf actually takes 82 (Ta-ble 2). If there is such a significant presence ofobstacle-removing ants patrolling these trunktrails (Lugo et al. 1973) then why is there sucha time discrepancy between the removal andsmall and large leaves?

Ants can carry up to 10x their own weight(Brian 1977); this implies that their combinedefforts should be extremely effective in movinglarge objects. However, the random movementof individual ants involved in trail-clearingrenders this strength futile, as they are oftenpulling against each other. Ants communicateby sight and smell (Shutler 1991), and have noeffective method of communication with whichto coordinate their trail-clearing efforts. Theirsolution to this disharmony is to break the ob-stacle into smaller pieces, at which point theirrandom movements can effectively cart off theobjects.

Atta colombica ants were consistently cuttingleaf over 12 cm long (Fig. 4). In addition toreducing the weight of the obstacle, this actionalso pared down the leaf shape to make theload less cumbersome. Ants have difficultybalancing carried loads properly (Wirth et al.2003) so this cutting may help sculpt the obsta-cle into an easier-to-balance shape. I did notrecord the presence of “spine-breaking” behav-ior in my notes, but this phenomenon was amajor component of large object removal strat-egy. “Spine-breaking” is the cutting of leafobstacles all the way through the leaf midrib,cutting the leaf in two. In addition to lesseningthe weight of the load and shaping the obstacleto be better balanced, spine-breaking also re-duces the distance between ants involved in theobject’s removal. This increased proximity may

allow the trail-clearers to visually identify eachother, and may even allow them to coordinatethe direction they pull. This spine-breakingwas only present in extremely large leaves (18-24cm), but happened consistently through thisobstacle group.

It is certainly possible, though, that thisspine-breaking doesn’t allow for increased antcommunication. Instead, it may facilitate largeobstacle removal simply by reducing the num-ber of ants needed to pull on each sub-object.Fewer ants making random removal directionchoices would increase the likelihood that theydrag in the same direction.

My sample size (N= 104) in this study didnot show any significant difference in ratesbetween forests, or between the morning andafternoon time periods (Table 1). However, amore comprehensive analysis may reveal dif-ferences. Pipeline Road, Parque Metropolitano,and San Lorenzo forests had differing levelsof rainfall, elevation, and temperatures. A dis-crepancy in rates could be attributed to thisrainfall gradient. Ants are highly susceptibleto desiccation (Wirth et al. 2003) and thereforeare attuned to water loss, which can be sub-stantial even in humid rainforest conditions(Brian 1977).

Foraging is affected by seasonal and diur-nal variations in sunshine, temperature, hu-midity, wind, and rainfall, in addition to mi-croclimate variation due to weather and lo-cal vegetation (Brian 1977). If studied moreclosely, any of these factors may play a rolein controlling the rate of obstacle removal inAtta colombica. Though the morning and af-ternoon data sets showed no significant differ-ence (Table 1), further study may reveal a dis-crepancy. Forager slackness in the afternoonhas been seen in many species of ant (Brian1977). Air temperature also affects ant move-ment rates; Formica aqiulonia move 2.5 timesfaster for every 10C rise (Brian 1969). Finally,the moisture content and age of of leaves mayvary between forests and time periods. It takesapproximately 4x as long for foragers to cutand harvest older leaves (Nichols-Orians andSchultz 1989), which would also affect obstacle

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removal.Further study will be necessary to test the

significance of these variables on any differ-ence in removal rate between forests and timeperiods. It would also be insightful to collectdata on spine-breaking behavior during thesefuture studies, as it may actually shed light onant communication strategies and group effort.Trail-clearing and maintenance is an extremelyeffective productivity-enhancing behavior inAtta colombica, and may be responsible for theirsuccess in the Neotropics. Maximizing removaltime is essential for maximizing obstacle re-moval effort, but also may even limit predationand parasitism on these colonies (Wirth et al.2003).

V. Acknowledgments

I would like to thank Yves Basset, IoannaChiver, and Paula Gomez for their invaluableguidance during this amazing course, in ad-dition to my research partners Jen Zhou andRachel Updike. I would also like to thank theants.

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Obstacle Size and Trail–Clearing Activity in Leaf–Cutter Ants, Atta colombica