Density Estimates and Nesting‐Site Selection in Chimpanzees of theNimba Mountains, Côte d’Ivoire, and Guinea
NICOLAS GRANIER1*, ALAIN HAMBUCKERS2, TETSURO MATSUZAWA3, AND MARIE‐CLAUDE HUYNEN1
1Biology Ecology and Evolution, University of Liège, Liege, Belgium2Biology Ecology and Evolution, University of Liège, Liege, Belgium3Primate Research Institute, Kyoto University, Inuyama, Japan
Chimpanzee societies are organized in a fission–fusion system in which individuals of a samecommunity frequently gather together and splitinto sub‐groups that vary greatly in size, composition,and duration [Lehmann & Boesch, 2004]. Groupingpatterns considerably vary across communities andyears, which is interpreted as resulting from adelicate balance between ecological (food availability,presence of danger‐predators) and social parameters(demography, community size and sex ratio, presenceof receptive females) [Doran, 1997; Lehmann &Boesch, 2004], but also activity or cultural behaviors(e.g., cooperative hunting) [McGrew, 2004]. Such anadaptive community organization, in addition to theparticularly elusive behavior of non‐habituatedchimpanzees and their relatively low populationdensities, explain the difficulty of conducting cen-suses based on social group counts [Ghiglieri, 1984].However, each weaned chimpanzee builds a new nest(also called bed or sleeping platform) every night, and
occasionally a day‐nest in which to rest, socialize oreat, most nests being built in trees and not reused[Plumptre & Reynolds, 1997]. Nests constitute tangi-ble evidence of chimpanzee presence and abundanceused to develop nest count methods [Ancrenazet al., 2004]. These methods are particularly welladapted to census non‐habituated populations over
Contract grant sponsor: Ministry of Education, Culture, Sports,Science and Technology ‐ Japan; contract grant numbers:16002001, 20002001, 24000001; contract grant sponsor: JSPS‐ITP‐HOPE
�Correspondence to: Nicolas Granier, Behavioral Biology Unit,Quai Van Beneden 22, 4020 Liège, Belgium. E‐mail: [email protected]
Received 16 October 2013; revised 12 February 2014; revisionaccepted 24 February 2014
DOI: 10.1002/ajp.22278Published online 5 August 2014 in Wiley Online Library(wileyonlinelibrary.com).
American Journal of Primatology 76:999–1010 (2014)
wide areas [Tutin & Fernandez, 1984], such as theNimba Mountains, a 40km long and 10km widemassif stretching along the border between Guinea,Côte d’Ivoire and Liberia (Fig. 1). Despite earlyreport of chimpanzee presence in Nimba forests[Lamotte, 1942], data on population abundance ofthis endangered species are still strikingly lacking,which is of foremost conservation concern. Under-standing chimpanzee habitat preference and particu-larly criterions of sleeping‐site selection is anothercrucial conservation issue [Anderson, 1984; McGrew,2004]. Earlier studies have shown that selection ofnest implantation (nesting‐site, nesting‐tree, andsituation within nesting‐tree) can be influenced by amyriad of factors such as vegetation structure andcomposition [Furuichi & Hashimoto, 2004; Tutin &Fernandez, 1984], location and physical character-istics of trees [Hernandez‐Aguilar et al., 2013], sea-
sonality and food resources [Basabose & Yamagiwa,2002; Doran, 1997], predator and human avoidance[Marchesi et al., 1995; Stewart & Pruetz, 2013],thermoregulation [Koops et al., 2012; McGrew, 2004],comfort [Stewart et al., 2007], topography [Furuichiet al., 2001], or parasite avoidance [Samson et al.,2013]. Thus, studyingnest distributionand character-istics over time provides valuable scientific informa-tion on the behavioral ecology of chimpanzees,particularly on their habitat‐use, grouping patterns,diet, and on seasonal variation of these behaviors[Anderson, 1984]. This knowledge is an essentialprerequisite to leading further inter‐communitycomparisons, and implementing efficient and pur-pose‐built in situ conservation.
Preliminary investigations we conducted on non‐habituated chimpanzees of the Nimba southern slopein 2006–2008 suggested that their presence was
Fig. 1. Study area and survey itineraries in the Nimba Mountains.
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seasonal and preferentially in altitude habitats[Granier, 2011]. In the present study, we used recentand solid methodologies to go further and achieve atwofold objective. We first aimed at filling theknowledge gap on chimpanzee abundance [Kormoset al., 2003] by applying and comparing twotechniques of nest count from line transects: thestanding crop and marked nest count methods[Hashimoto, 1995; Plumptre & Reynolds, 1996]. Wethen aimed at characterizing the ecological factorsthat best predict nesting‐site distribution of thisparticular population. Building on our preliminaryfindings, we formulated the hypotheses that chim-panzees would nestmore frequently in the study areaduring the dry season, that they would prefer nestingat high altitude, in places with high ground declivity,and in gallery or mountain forests of either old‐growth or good‐quality secondary types. We usedlogistic regression to model nest presence as afunction of 12 ecological variables characterizingvegetation structure, topography and seasonality.
METHODS
Study SiteThe northeastern part of the Nimba Mountains
ridge culminates above 1,500m. It is covered byaltitude grasslands from 800 to 1,000m high, tightlyintertwined with various formations of evergreenrainforests on slopes and foothill. The crest progres-sively descends to 1,000m altitude toward thesouthwestern part of the mountain, and forest risesover the top to cover the entire massif from the YanRiver (Fig. 1). This particular vegetation mix and theharsh topography fostered the emergence of multipleecological niches with rich biodiversity and notableendemism [Lamotte & Roy, 2003]. To ensure sus-tainability of these exceptional ecosystems, theGuinean and Ivorian sections of Nimba (180 km2)were integrally protected in the early 1940s, andtoday benefit from several other conservation status-es [Granier & Martinez, 2011].
Since 1976 sporadic studies have been carried outto survey Nimba chimpanzee populations or addressinter‐community behavioral variations [Granier,2011; Humle & Matsuzawa, 2001; Marchesi et al.,1995; Matsuzawa & Yamakoshi, 1996; Shimada,2000]. More systematic research was initiated in2003with the establishment of a permanent researchsite at Seringbara (Nimba northern slope, Fig. 1)where Koops et al. [2012] study the influences ofhabitat ecology on elementary technology use bychimpanzees. The present study has focused on thelesser‐studied southern slope of Nimba, centered onits Ivorian section (50 km2) and extending beyond theGuinean border (10 km2). The southwestern part ofour study area was named “Yealé area” (following thename of Yealé village), and the northeastern part
“Gouéla II area” (in keeping with the small settle-ment of Gouéla II; Fig. 1).
Data Collection
Surveying methodThis research adhered to the American Society of
Primatologists principles for the ethical treatment ofprimates.We used three types of survey itineraries tomonitor the study area (Fig. 1). (1) Three parallel linetransects drawn from where the three main riversoutflow from the reserve following the north azimuth,up to altitude grasslands, or as high as topographyallowed (mean length¼ 4.15�SD 0.27 km). (2) Twocontour recces stretching between the Liberian andGuinean borders following the contour lines 750 and450 (mean length¼ 17�SD 0.71 km); and (3) threeloop recces starting where the three main secondaryrivers outflow from the reserve, extending up to thealtitude grassland edge and back down in a large “u‐turn” forming a loop (mean length¼ 10.90�SD2.27 km). When opening these approximately 80kmof itineraries in 2009–2010, we measured distanceswith a hip‐chain (topofil) and tied tapes every 100mon transects—500m on recces. Surveying effort wasspread over 19 months divided into two field surveyperiods. From June to December 2009, we walkedcontour and loop recce each month (seven visits), andfrom May 2010 to April 2011, we walked allitineraries every 24 days following a fixed sequenceof 14 days, except in December (11 visits).
Vegetation and nestsSurvey itineraries were used to describe the
structure and composition of vegetation, and torecord nest data. The composition of woody specieswas assessed on a 10m‐width strip along the threetransects, identifying and measuring diameter atbreast height (DBH) of all trees >10 cm DBH.Vegetation structure was described according tonine variables characterizing the different vegetationstrata (Table I): forest type, forest disturbance,canopy closing, plus 6 dichotomous non‐exclusivevariables describing understory: open understoryand/or understory containing sapling, liana, Maran-taceae, Zingiberceae, and/or Chromolaena species[Duvall, 2008; Marchesi et al., 1995]. As each surveyitinerary was opened, we continuously recorded thelevels of these nine variables and the distances atwhich they changed. Each observed nest wasgeoreferenced and we systematically noted thefollowing information: (1) location; (2) height aboveground; (3) age‐class following Tutin & Fernandez[1984] criteria; (4) species and DBH of nesting‐tree;(5) size of nest group, defined as nests of the same age‐class within 20m; (6) vegetation structure accordingto the above‐described criteria; (7) altitude andground declivity under the nest; and (8) season ofnest construction—rainy (May–November) or dry
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(December–April). For nests seen on transects,we also recorded the perpendicular distance (PD)between transect and nest.
Data Analysis
Chimpanzee density estimatesWe used Distance 6.0 software to estimate
chimpanzee density from the standing crop (SCNC)and marked nest count methods (MNC), based onboth nest groups and individual nests [Furuichiet al., 2001; Plumptre & Reynolds, 1996]. Nestdensity d is the ratio of the number of detected nestsn, to the area surveyed multiplied by the probabilityof detecting a randomly chosen nest [Tutin &Fernandez, 1984]. A detection function g(x) is createdas the probability of detecting a nest at distance x oftransect, and characterized by the effective stripwidth, m, or distance for which the number of nestsdetected beyond equals the number of nests missedwithin [Buckland et al., 1993]. Nest density d is givenby the formula, where L is the transect length:
d ¼ n2mL
Post‐hoc determination of m was made on thebasis of lowest Akaike’s information criterion (AIC)
by selecting between 4 mathematical keys availablein Distance, the model of g(x) that fitted the best ourdistribution of PD frequency [Buckland et al., 2010].We set truncation distance w at PD¼ 20m, consider-ing that beyond this point measures were notaccurate enough [Buckland et al., 2010]. Given thatsome day‐nests may have been counted as night‐nests and that contrarily, some night‐nests couldhave been reused, we assumed the chimpanzee dailynest production rate to be 1nest/chimp/day[Hashimoto, 1995]. In the SCNC method, whichrequires just one census per transect, nest density iscorrected by the average length of time nests remainvisible to obtain the total number of nest builders[Ghiglieri, 1984]. We used the nest life‐span estimat-ed in Taï forest National Park (Côte d’Ivoire) byKouakou et al. [2009]: 91.22�SE 5.89 days. All nestscollected during the 11 passages on transects wereincluded to increase sample size [Plumptre &Reynolds, 1996]. Repeated counts on each transectwere processed as non‐independent replicates bypooling line data following Buckland et al. [1993]. Inthe MNC method only new nests are counted, whichallows getting rid of the nest life‐span [Plumptre &Reynolds, 1996]. Density of new nests is corrected bythe number of day elapsed between two consecutivepassages (which must be shorter than the minimum
TABLE I. Variables and Effects Used to Model Nest Presence, With Their Levels
Categories Variables and effects Levels
Vegetation structure Forest type Lowland forestMontane forestGallery forest
The 16 effects of 12 habitat variables (italic) used to build upmodel of nesting‐site selection; all variables and effects characterizing vegetation structure andseasonality are categorical, the two variables and two effects describing topography are continuous (range of recorded values provided). In data analysis,three and four levels qualitative variables were recoded using binary dummy variables to produce the appropriate level numbers.
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nest life‐span) to obtain the density of nest‐buildingchimpanzees [Hashimoto, 1995; Plumptre&Reynolds,1997]. During the opening of transects and the firstpassage we marked all nests, and used only new nestsrecorded during the 10 ensuing passages to estimatedensity. For both methods we calculated individualnest density using the PD frequency, and nest groupdensity using themeanPDof nests belonging to a samegroup, plus group size [Kouakou et al., 2009; Marchesiet al., 1995].
Nesting‐tree selectionWe used a G‐test for goodness‐of‐fit to compare
distributions of tree species used for nesting to overalltree availability [Sokal & Rohlf, 1995]. Overall treediversity and abundance recorded on the threetransects were used as theoretical values to generatethe expected sample. We excluded from this analysisnests recorded in tree with DBH <10 cm and nestsfor which we did not record theoretical value. Ourdata set was then truncated in such a way as torespect the assumption of having 80% of expectedvalues >5 [Agresti, 2002]. Similarly, we used G‐testfor goodness‐of‐fit to compare the DBH distributionsof trees used for nesting to trees sampled on trans-ects, grouped in classes of 5 cm DBH. In order tointerpret chimpanzee selectivity for each tree speciesand each DBH class, we calculated the adjusted(normalized) Pearson’s residuals for each cell of atwo‐way table according to the following formula[Agresti, 2002]:
Res: ¼ ðO� EÞ½Eð1� PiÞð1� PjÞ�1=2
With O the observed frequency, E the standard-ized expected frequency, Pi the proportion of line iand Pj the proportion of the observed column. Thefarthest is residual value from 0, the most preferred(positive value)/avoided (negative value) is the treespecies/DBH.
Nesting‐site selectionWeused logistic regression to model influences of
habitat structure, topography, and seasonality onnesting‐site selection by chimpanzees. Initial vari-able selection was made of 16 effects produced by 12predictor variables sensed to influence nesting‐sitechoice (Table I) according to our preliminary recon-naissance results [Granier, 2011] and literatureanalysis [Basabose & Yamagiwa, 2002; Furuichiet al., 2001; Tutin & Fernandez, 1984].
We used all nests as presence data, together withdouble number of absence data randomly selectedamongst habitat description data. Spatial autocorre-lation estimated with theMoran’s I test in ArcGIS 9.3showed highly clustered data. A generalized linearmodel with a logit link function and binomial errordistribution generated in Statistica 10 revealed that
residuals were also spatially autocorrelated. Weconsequently used a generalized linear mixed model,which takes into account spatial autocorrelation ofdependant variable [Bolker et al., 2009]. TheglmmPQL function of the R free software MASSpackage was used [Venables & Ripley, 2002], includ-ing a random effect of the dependent variable with anexponential spatial correlation structure, accordingto Dormann et al. [2007]. Model building strategyfollowed the hierarchical backward eliminationprocedure for sequentially removing non‐significantvariables on the basis of Wald t‐test P‐value (P)[Kleinbaum & Klein, 2010]. Variable removal wasstopped when all P‐values were inferior to 0.20, inorder to minimize the type II error risk (acceptingfalse null hypothesis). We evaluated the discrimina-tory and predictive performances of each generatedmodel by introducing their estimated values intoROC_AUC software to calculate the Area Underthe ROC‐Curve (AUC) [Schroeder, 2006]. Finally,estimated parameters of the most parsimoniousmodel were used to compute the odds ratios (OR),which are measures of the association strengthbetween the dependent and explicative variables[Kleinbaum & Klein, 2010]. In our study, theprobability of observing nest in inappropriate con-ditions has been considered close to zero, whichallowed interpreting OR in terms of probability[Schmidt & Kohlmann, 2008] (for analysis in epide-miological context). We calculated OR by comparingtwo levels of each explanatory variable, followingKleinbaum & Klein [2010]:
ORa vs: b ¼ expXki¼1
ðai � biÞbi" #
for one or several variables of two or more‐than‐twolevels (ai compared to bi level), of k effects and bicoefficients. OR of continuous variables were calcu-lated for discreet values: we empirically set a 25mincrement for altitude, compared to altitude 500mwhich was the lowest nest observed. In the samemanner we calculated OR by 5% increment of grounddeclivity under nest, in comparison to a null declivity.
Sampling effort per vegetation category and persurvey itinerary is presented in Table II. Mountainforest was the most represented formation with 42%of sampling effort; two‐thirds of habitat sampledwereold‐growth forest and two other thirds had a closedcanopy.Understory ofmost crossed habitat containedwoody species (92.6%), 2 thirds contained lianas, and52.4% contained Marantaceae. DBH of 8,463 trees
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measured along the 12.5 km of the three transectsranged between 10 and 625 cm (mean¼ 24.61�SD26.81 cm; median¼ 16 cm). Amongst these, we iden-tified 8,403 trees belonging to 368 species and 64families, and classified 60 as “undetermined.” Sixty‐eight additional species were identified on recces,bringing the total tree diversity to 437 species.Transects contained 84% (368/437) of the tree speciesidentified in this study, and all levels of the ninevariables of vegetation structure.
NestsOverall N¼ 764 nests were observed in 338
groups constituted of 1–11 nests (mean group size¼ 2.23�SD 1.57 nests; 85% of groups constituted of1–3 nests). Nests were mainly observed in the upperpart of transects and loop recces, and in the highercontour recce (mean altitude¼ 757�SD 83.9m; 50%of nests between 706 and 789m), preferentially insteep locations (mean ground declivity¼ 15.54�SD10.81%; 50% between 6.5 and 23.5%). Figure 2 showsthe distribution of nest groups spread out in twodistinct clusters: a larger one in the Yealé area(N¼ 227 groups, 529 nests), separated by a gap westof TouaRiver from theGouéla II area cluster (N¼ 111groups, 235 nests).
Nests were constructed between 0 and 26mabove the ground, half of them between 5 and 10mhigh in trees (mean¼ 8.02�SD 4.57m).We observed63 ground nests (8.2% of total) distributed in bothclusters, including 17 particularly elaborated nestsmade of saplings—sometimes mixed with terrestrialherbaceous vegetation (THV)—which were recordedas night‐nests. The 46 others, mainly composed ofTHV and often reduced to simple leaf‐cushions[Matsuzawa & Yamakoshi, 1996], were considered
as day‐nests (rest‐nests) and discarded, bringing thetotal number of nests considered for analyses toN¼ 718 distributed in 322 groups.
Density EstimatesA total of N¼ 66 nests partitioned in n¼ 34
groups were observed on transects and used fordensity estimations with SCNC; for theMNCmethodwe used N¼ 53 new nests grouped in n¼ 28 groups.The negative exponential curve was the model fittingthe best our PD distributions. Results presented inTable III show values of density included between0.14 (range: 0.04–0.53) and 0.65 (range: 0.32–1.33) chimpanzee/km2.
Based on lower AIC, the MNCmethod applied tonest group gave the most reliable estimate which is0.46 chimpanzee/km2 (range: 0.19–1.11). More gen-erally, estimations based on nest group had a lowerAIC than those based on individual nest, so did thoseobtained with the MNC in comparison to SCNC.Extrapolations of density estimates to the entirestudy area (60 km2) gave a population of nest‐building chimpanzees included between 8 and 39individuals; the most reliable estimate being 28individuals.
Nesting‐Tree Selection
One hundred fourteen vegetal species were usedfor nesting (108 woody, 3 Marantaceae, and 3Zingiberaceae), but 10 tree species accounted for52% of the total N¼ 718 nests. Whereas 40% of nests(287/718) were made of vegetal species at leastoccasionally consumed by chimpanzees, 17% of nests(124/718) were recorded in tree species producingfruits eaten by chimpanzees, and just 0.7% (5/718) in
TABLE II. Sampling Effort Per Category of Vegetation Structure and Per Survey Itinerary
Itinerary
Vegetation structure
Total(km)
Forest type Forest disturbance Canopy Presence in understory
Vegetation structure: LF, lowland forest; MF, mountain forest; GF, gallery forest; Old growth, old‐growth forest; Old 2ry, old secondary forest; Young 2ry,young secondary forest. Canopy was Cl, closed; P, partially closed; L, lightly closed or O, open. Presence in understory (non‐exclusive) of S, sapling; L, liana;M, Marantaceae sp.; Z, Zingiberaceae sp.; Chr, Chromolenae odorata and/or O, open understory. Itinerary: T, transect; Loop, loop recce; H Recce, highercontour recce; L Recce, lower contour recce.
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food trees bearing ripe fruits. We used 635 nestsrecorded in 95 tree species (and N¼ 5,468 treesidentified on transects as theoretical sample) tocompute the expected sample, then truncated to438 nests and 42 species for calculation of G‐value.
Chimpanzees highly significantly selected theirnesting‐tree species independently of overall speciesavailability (G¼ 577.49, df¼ 41, P< 0.00001). Weidentified 21 preferred nesting‐tree species (adjustedPearson’s residual value> 2) and 15 species signifi-cantly less used than expected (avoided species, with
residual value<�2). Figure 3 plots the 10 mostpreferred species and the 10 most avoided sorted outper decreasing residual values. Three preferrednesting‐tree species (Carapa procera,Mangbeulügon(Yakouba name), Anthonotha macrophylla) and fiveavoided (Funtumia elastica, Hannoa klaineana,Maesobotrya barteri, Piptadeniastrum africanum,Rinorea oblongifolia) are components of chimpanzeediet, strengthening the idea that nesting‐tree selec-tion did not depend on the edible characteristics ofspecies. DBH of nesting‐trees ranged between 1 and
Fig. 2. Nest groups were observed in the upper section of the study area. They were divided in two distinct clusters—a bigger one on theleft (Yealé area, N¼227 groups), and a smaller one on the right (Gouéla II area, N¼111 groups).
D, density of nest‐building chimpanzees; CV, coefficient of variation; ESW, effective strip width and AIC, Akaike information criterion. Estimates werecomputed using the standing crop nest count (SCNC) and the marked nest count (MNC) methods with both individual nests and group of nests.
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235 cm (mean¼ 27.9�SD 24.01 cm; median¼ 23).The expected sample was computed for 13 classesof 5 cm DBH (range: 10–74 cm) with 642 nests andN¼ 8,463 trees as theoretical sample. DBH distribu-tions of nesting‐trees and of overall trees differed in ahighly significant manner (G¼ 366, df¼ 12,P< 0.00001), showing that tree DBH influencedchimpanzees’ choice of nesting‐tree regardless ofthe general availability.
Trees of 10–14 cm DBH were rather avoided tobuild nests (Fig. 4), whereas trees of DBH includedbetween 20 and 64 cm were preferred (except DBH55–59 cm), with highest selectivity for the 25–29 cmclass.
Nesting‐Site Selection
A total ofN¼ 2210 nest data (718 presence, 1,492absence) were used to build up the logistic model ofnest presence. The selected model contained eightvariables/effects with P< 0.05 (forest type, forestdisturbance, altitude and altitude2, ground declivity,presence/absence in the understory of woody species,of lianas and season alternation), and one variablewith P< 0.2 (presence/absence of Zingiberaceae inthe understory). Evaluation of this model’s perfor-mance by means of the AUC indicated an acceptablecapacity of discrimination (AUC¼ 0.746) [Hosmer &Lemeshow, 2000]. On thebasis ofORvalue it appeared
that forest type was the variable having the strongestinfluence on nesting‐site choice (Table IV): chimpan-zees overwhelmingly nested more in gallery forest(OR¼ 6.83) and Montane forest (OR¼ 6.73) in com-parison to lowland forest. Altitudewas the secondmostinfluent factor. Nest presence likelihood varied as afunction of altitude in a bell‐shaped curve, with amaximum at 770m and an OR approaching 3 (Fig. 5).Over altitude 1,050m, the probability of observingnests fell below initial level (OR< 1).
Figure 5 also shows the curvilinear positiveinfluence of ground declivity on nest presence. Thesteeper was the ground, the greater was theprobability of observing nests, with maximum ORvalue of 1.99 for the steepest slope encountered (85%).Probability of finding nest was higher in old‐growthforest than in young secondary (OR¼ 1.36) and oldsecondary forests (OR¼ 1.24, Table IV). Old second-ary forest was slightly preferred compared to youngsecondary forest (OR¼ 1.1).
Two components of forest understory (out of 6)significantly explained the observed nest distribution(Table IV). Presence of lianas rather prevented chim-panzees from nesting (OR¼ 0.93), whereas understorycontaining saplings constituted a preferred nesting‐habitat (OR¼ 1.28). Finally, comparing expected valuesof dry season to rainy season gave an OR¼ 1.28:chimpanzeesnestedmore frequently in the study areaduring the dry than during the rainy season.
Fig. 3. The 10 most preferred (and avoided) nesting‐tree species contained more (fewer) nests than expected from general availability,they have the highest (lowest) residual values. All absolute values are >2, indicating that they constitute the most relevant differencesbetween observed and expected frequencies [Agresti, 2002].
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DISCUSSIONNests
During a survey conducted around the NuonRiver in the Yealé area of Nimba, Matsuzawa &Yamakoshi [1996] recorded 35.4% of ground nests
(164/464), all above 800m altitude. They distin-guished two categories: some ground nests exclusive-ly made of saplings, and others mainly composed ofTHVwith a cushion‐like appearance. In this studywerecorded 8.2% of terrestrial nests (63/764), including62% (39/63) exclusively composed of THV. Koopset al. [2012] reported 9.5% of ground nests (144/1,520)from the Seringbara region of Nimba with only 13.8%(15/108) exclusively made of THV. The low predationpressure reported in Nimba is a necessary conditionto have such a relatively high proportion of terrestrialnests, but it is insufficient to explain what motivatechimpanzees to nest on the ground. Further studiesare needed to sort out and describe influences ofthe intermingled ecological and socio‐culturalfactors shaping this behavior [Koops et al., 2012;Matsuzawa & Yamakoshi, 1996]. On average, nestswere built slightly lower in the Ivorian Nimba (meanheight¼ 8.02�SD 4.57m) than in Seringbara (meanheight¼ 11.3�SD 6.3m), but both values are in therange of those reported from most research sites.However, mean size of nest groups was relativelylow in our study area (2.23�SD 1.57nests/group)compared to Seringbara (3.7�SD 3.96nests/group)[Koops et al., 2012], Kalinzu Forest Reserve inUganda(mean¼ 3.68nests/group) [Furuichi et al., 2001], orKahuzi‐BiegaNational Park inDemocratic Republic ofCongo (4.31nests/group) [Basabose & Yamagiwa,2002]. In a study of three habituated communities ofthe Taï forest (200km south from Nimba), Kouakouet al. [2009] showed that chimpanzees tend to travel insmaller parties in peripheral parts of their home rangein comparison to core areas. The small size of nestgroups suggests that our study area constitutes theperipheral part of a community territory.
Density Estimates
Despite the small sample of nests recordedfrom transects, our density estimates are noteworthy
Fig. 4. Grey dots indicate absolute values of residual>2 (signinglack of fit (P<0.05) between observed and expected frequencies),that is, themost preferred nesting‐treeDBH (classes between20–49 and 55–64 cm) and most avoided DBH (10–14 cm). White dotsindicate absolute values of residual<2, which designate the non‐significantly preferred and avoided nesting‐tree DBH [Agresti,2002].
TABLE IV. Odds ratios of categorical variablescomputed from the logistic model
Forest type
MF GF LF
compared to MF 1.01 0.15GF 0.99 0.15LF 6.73 6.83
Forest disturbance
Old growth Old 2ry Yg 2ry
compared to Old growth 0.81 0.74Old 2ry 1.24 0.91Yg 2ry 1.36 1.10
Understory
Presence of Sapling Liana Zingib.
compared to Absence 1.28 0.93 1.06
Season
Dry
compared to Rainy 1.28
Comparison between forest type levels (MF, mountain forest; GF, galleryforest; LF, lowland forest); comparison between forest disturbance levels(Old growth, old‐growth forest; Old 2ry, old secondary forest; Yg 2ry, youngsecondary forest); comparison between understory containing sapling,liana and/or Zingib.: Zingiberaceae species, and understory from whichthey are absent; comparison between dry season and rainy season.
Fig. 5. Bell‐shaped curve of altitude odds ratio (OR Alt) showingthe maximum probability of nest presence at altitude 770m.Ground declivity odds ratio (OR Decl) increasing in a curvilinearmanner with steepness.
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in that they fill the knowledge gap on this priorityarea for the conservation of Pan troglodytes verus[Kormos et al., 2003]. Two former studies publishedestimates of chimpanzee abundance in Nimbabased on the SCNC method. Marchesi et al. [1995]have sampled two sites located at both edges of ourstudy area, and extrapolated their data to theforested surface of the entire Ivorian Nimba; theyreported a density of 1.31 chimpanzees/km2 (for 59weaned individuals). Hoppe‐Dominik [1991] estimat-ed a density of 0.5 chimp/km2 (50 individuals) in azone restricted to the Libero‐Ivorian border. Thelimited sampling effort (in time and space) of thesesurveys combined to the seasonal variation ofchimpanzee presence could explain the high valuesreported in comparison to ours based on the SCNCmethod (0.14–0.19 chimp/km2, 8–11 individuals).Nevertheless with the MNC method, we obtaineddensities close to Hoppe‐Dominik’s result (0.46–0.65 chimp/km2, corresponding to a smaller popula-tion of 28–39 individuals partly because ourstudy area was larger). Based on SCNC and MNCmethods from three known communities of theTaï forest, Kouakou et al. [2009] estimated densitiesof 2.19 chimps/km2 in core area of territories, and0.15 chimp/km2 in peripheral area. Our estimates arecomparable to density value of peripheral area ofchimpanzee territory, suggesting that our study areais a peripheral part. In this respect, our results need tobe refined with broader scale censuses before beingextrapolated to the entire Nimba.
Nesting‐Tree Selection
In many research sites, chimpanzees appear toselect nesting‐tree species independently of theiravailability. In Kalinzu, this selectivity was charac-terized by the fact that chimpanzees constructednests in 43 of 111 tree species [Furuichi &Hashimoto, 2004], including 14 species harboringover 90% of nests. Stanford & O’Maley [2008] foundthat chimpanzees of the Bwindi Impenetrable forest(Uganda) were using 38 tree species out of 163available to build nests, with 72.1% of nests built injust four tree species. In Kahuzi‐Biega, nests wereobserved in just 28 tree species, with 90% of themmade in 17 tree species, all bearing fruits eaten bychimpanzees [Basabose & Yamagiwa, 2002]. Koopset al. [2012] reported that chimpanzees of SeringbaraNimba were using 115 of 216 available tree speciesfor nesting, with 56% of nests in 10 tree species. In theIvorian Nimba, chimpanzees used 108 tree speciesout of 437 described (52% of nests in 10 tree species).Both studies on Nimba chimpanzees report the use of10 tree species to build slightly more than half ofnests, and evoke that nesting‐tree selectivity isindependent of species and fruit availability. Theyalso suggest that the relatively high tree diversity ofNimba favors the use of a larger panel of species than
in other sites. Despite important variation in DBH ofnesting‐trees, chimpanzees in this study showedhighest selectivity for trees of 25–29 cm DBH. Thelow predation pressure may enable them to nest atlow height (mean nest height¼ 8.02m) in sufficientlysturdy and stablemedium‐sized trees, while reducingthermoregulation constraints and climbing efforts[Stanford&O’Malley, 2008; Stewart &Pruetz, 2013].
Nesting‐Site Selection
In the Ivorian Nimba chimpanzees markedlynested more in gallery and mountain forests than inlowland forest. They also favored old‐growth forestcompared to old secondary forest, and avoidedyoung secondary forest. In Seringbara Nimba andKahuzi‐Biega alike, chimpanzees preferred nestingin primary forest compared to secondary forest[Basabose & Yamagiwa, 2002; Koops et al., 2012].We found that altitude strongly influenced nesting‐site selection as well, with a maximum probability ofobserving nests at 770m altitude. Koops et al. [2012]reported that chimpanzees in Seringbara preferrednesting above 1,000m and avoided nesting below800m (range: 681–1,169m). Despite the discrepancyin altitude values, both these results show preferencefor nesting in altitude habitats, as those reportedfrom the Nuon River area of Nimba by Matsuzawa &Yamakoshi [1996]. The altitude discrepancy mayresult from the higher elevation of the mountain inSeringbara compared to Yealé, and higher forestedge. The fact that chimpanzees nested morefrequently in the study area during the dry seasonimplies greater habitat‐use, which may be explainedin part by seasonal variation in food resourceavailability. As Doran [1997] showed, ranging pat-terns of chimpanzees in the Taï forest variedseasonally in relation to food availability. Chimpan-zees adapted to the fruit scarcity of the dry season byspendingmore time feeding, reducing their day rangeand party size, and spending more time solitarilythan during the rainy season.
Small size of nest groups (mean¼ 2.23 nests),seasonality detected in nest presence, and lowchimpanzee density estimates (D¼ 0.46 indiv/km2),constitute converging arguments for peripheral areaof chimpanzee territory. Furthermore, the gap in nestpresence between Yealé and Gouéla II areas (Fig. 2)suggests a zone chimpanzees avoid. We hypothesizethat our study area is actually located at the junctionof two distinct chimpanzee communities. Thesepreliminary findings do not support Matsuzawa &Yamakoshi [1996] conclusions, that three chimpan-zee communities populate the Ivorian section ofNimba. However, our results bring new evidence tosupport their idea of one community’s core arealocated behind the Nuon River (in Liberia). They alsosuggest that most of the Yealé area constitutes theperipheral zone of this territory. The Gouéla II area
Am. J. Primatol.
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would then be part of the peripheral zone of anothercommunity whose core area would be located in theupper Mien and Guégué Rivers (upright corner inFig. 2) where we observed large nest groups at eachvisit during preliminary surveys.
Conservation Perspectives
If these findings are verified, Nimba chimpanzeepopulations, which have proven to be particularlywell adapted to their specific habitat, would be lessabundant than previously estimated. This wouldhave major conservation implications, since even ifchimpanzees are not hunted in Nimba, their survivalis critically jeopardized by habitat loss and fragmenta-tion under increasing pressures from local populationlivelihood (slash and burn agriculture, uncontrolleduse of fire, non‐sustainable use of resources), and ironoremining in the Liberian andGuinean sections.Morejoint efforts between research and conservation areneeded to mitigate and find alternatives to thiscomplex multi‐layered issue. Applied studies aimingto achieve a tri‐national cohesive view on Nimbachimpanzees’ status are an essential preliminary stepin the elaboration and implementation of an efficientsite‐specific conservation policy.
ACKNOWLEDGMENTSWe thank the “Office Ivoirien des Parcs et
Réserves” in Côte d’Ivoire, along with the ‘DirectionNationale de la Recherche Scientifique et de l’Inno-vation Technologique’ and the “Institut de RechercheEnvironnementale de Bossou” in Guinea for researchauthorizations. Thanks are also due to the 8 fieldassistants: David, Anatole, Philibert, Anthony,Alexis, Pascal, Ferdinand and Michel. We aregrateful to two anonymous reviewers and Mara, fortheir helpful comments on the manuscript. Financialsupport for research was provided by MEXT(#16002001, #20002001, #24000001), JSPS‐ITP‐HOPE grants awarded to T. Matsuzawa, and ascholarship from the Japanese Society for thePromotion of Science to N. Granier.
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