Edge Effects and Their Influence on Lemur Densityand Distribution in Southeast Madagascar

Shawn M. Lehman,1* Andry Rajaonson,2 and Sabine Day2

1Department of Anthropology, University of Toronto, Toronto, Ontario M5S 3G3, Canada2Department of Paleontology, University of Antananarivo, Antananarivo, Madagascar

KEY WORDS forest fragmentation; diet; food quality; predation; protected areas

ABSTRACT Edge effects are caused by the penetra-tion of abiotic and biotic conditions from the matrix intoforest interiors. Although edge effects influence the bio-geography of many tropical organisms, they have notbeen studied directly in primates. Edge effects are par-ticularly relevant to lemurs due to the loss of 80–90% offorests in Madagascar. In this study, data are presentedon how biotic edge effects influenced the distribution anddensity of lemurs in the Vohibola III Classified Forest insoutheastern Madagascar. In total, 415 lemur surveyswere conducted during June–October 2003 and May–September 2004 along six 1,250-m transects that ranperpendicular to the forest edge. Data were also collectedon lemur food trees along the six transects (density,height, diameter at breast height, area, volume, and dis-tance to forest edge). Four nocturnal species (Avahi

laniger, Cheirogaleus major, Lepilemur microdon, andMicrocebus rufus) and four diurnal species (Eulemurrubriventer, Eulemur fulvus rufus, Hapalemur grisesusgriseus, and Propithecus diadema edwardsi) weresighted during surveys. Regression analyses of lemurdensities as a function of distance to forest edge providededge tolerances for A. laniger (edge-tolerant), M. rufus(edge-tolerant), E. rubriventer (edge-tolerant or omnipre-sent), and H. g. griseus (omnipresent). The density anddistribution of M. rufus and their foods trees were corre-lated. Edge-related variations in food quality and preda-tion pressures may also be influencing lemurs in Vohi-bola III. Tolerance for edge effects may explain, in part,how lemurs have survived extreme habitat loss and for-est fragmentation in southeastern Madagascar. Am JPhys Anthropol 129:232–241, 2006. VVC 2005 Wiley-Liss, Inc.

Forest habitats are becoming increasingly fragmentedin most tropical regions of the world (Laurance, 1999).One of the most significant consequences of forest frag-mentation is an increase in amount of habitat edge (Love-joy et al., 1986; Laurance and Yensen, 1991; Chen et al.,1992). Edges are dynamic zones characterized by the pene-tration, to varying depths and intensities, of conditionsfrom the surrounding environment (matrix) into the forestinterior (Malcolm, 1994). Hypothetically, if edge effectspenetrate 300 m into a 100-ha square-shaped forest frag-ment, then approximately only 16% of the total forestamount will be unaffected by edge effects. For example,Curran et al. (1999) found that edge effects reduced theabundance of Dipterocarp seedlings up to 5 km from theedge into forests in Borneo. These edge-related changes inforest dynamics may have deleterious effects on residentprimate populations by reducing the distribution andabundance of food trees near the forest edge. Changes inspecies interactions (e.g., herbivory, frugivory) as a conse-quence of edge effects were defined as indirect biologicaleffects (Murcia, 1995). Indirect biological effects representa significant but poorly studied aspect of the ecologicalconsequence of edge effects for primates in tropical forests(Norconk and Grafton, 2003). Although some researchersinvoked edge effects as a significant determinant of pri-mate distributions (Mbora and Meikle, 2004; Tweheyoet al., 2004), the associated data were based on relativeamounts or presumed limits of forest edges. Therefore, wehave few data on how the distribution and density of pri-mates are affected directly by edge effects.Edge effects may be particularly relevant to studies of

forests and primates in Madagascar. Lemurs are one ofthe most threatened primate taxa in the world due to the

loss of 80–90% of forest habitats in Madagascar (Greenand Sussman, 1990; Du Puy and Moat, 1998). The remain-ing forest is highly fragmented and, therefore, may beprone to extreme edge effects. However, there are few dataon how edge effects influence lemur biogeography inMadagascar. Lidicker (1999) constructed an ecologicalmodel of how species respond indirectly to variables, suchas changing resource conditions, associated with edgeeffects. This model predicts that the response of a targetspecies to edge effects can be measured as matrix or ecoto-nal effects. A matrix effect occurs when the target speciesresponds directly to some aspect of the edge. Thus, lemurspecies that have their highest densities near the edgewere defined as edge-tolerant. Conversely, lemur speciesthat avoid forest edges were defined as edge-intolerant.Conversely, ecotonal effects occur when the organismshows little or no response to the edge. In this case, alemur species can be referred to as being omnipresentbecause it will range between the edge and forest interior

Grant sponsor: NSERC; Grant sponsor: Connaught Foundation;Grant sponsor: University of Toronto.

*Correspondence to: Dr. Shawn M. Lehman, Department ofAnthropology, University of Toronto, 100 St. George St., Toronto,Ontario M5S 3G3, Canada. E-mail: slehman@chass.utoronto.ca

Received 17 March 2004; accepted 17 November 2004.

DOI 10.1002/ajpa.20241Published online 1 December 2005 in Wiley InterScience

(www.interscience.wiley.com).

VVC 2005 WILEY-LISS, INC.

AMERICAN JOURNAL OF PHYSICAL ANTHROPOLOGY 129:232–241 (2006)

in a random pattern (Lehtinen et al., 2003). These defini-tions follow the classic multidimensional niche modeldescribed by Hutchinson (1957). The multidimensionalniche concept is a theoretical explanation of how differentenvironmental factors limit abundance and distribution.Because each species has a range of tolerances along everyniche axis, a species can only occur in those areas whereniche axes are within ranges of tolerance. Moreover, indi-rect edge effects should be particularly strong during theJune–September period of food scarcity in southeasternMadagascar.Using the model by Lidicker (1999) and data on lemur

feeding ecology, predictions were generated on how lemursmay respond to forest edges in the Vohibola III SpecialReserve in southeastern Madagascar. There are in total10 lemur species in Vohibola III: one nocturnal folivore(Avahi laniger), three nocturnal omnivores (Cheirogaleusmajor, Daubentonia madagascariensis, and Microcebusrufus), one nocturnal folivore/frugivore (Lepilemur micro-don), two cathemeral frugivores (Eulemur fulvus rufusand Eulemur rubriventer), one diurnal folivore (Hapale-mur griseus griseus), and one diurnal folivore/frugivore (Pro-pithecus diadema edwardsi). If edge effects negatively influ-ence the distribution and density of lemur food trees, aswas observed in other tropical forests (Laurance et al.,1997; Norconk and Grafton, 2003), then these patchdynamics may be of particular consequence for frugivoresand other lemurs in which fruit is an important compo-nent of their diet. Fruiting trees tend to occur at low den-sities and produce few fruit crops in Madagascar (Ganz-horn, 1995a). Moreover, fruit crops tend to be lost due toincreased wind turbulence near the forest edge, particu-larly during the annual January–March cyclone season.For example, cyclonic winds resulted in the total devasta-tion of most fruit patches in the Manombo Special Reserve(Ratsimbazafy, 2002). Therefore, the frugivores (E. f. rufusand E. rubriventer) were predicted to be edge-intolerant.Bamboo specialists (H. g. griseus) and folivores (A.laniger) may not face the same challenges of resourceacquisition because of the relatively high abundance andavailability of leaves and bamboo compared to fruits inhumid forests (Overdorff, 1993; Tan, 2000; Powzyk, 2003).H. g. griseus and A. laniger were predicted to be omnipre-sent in forest fragments. Omnivores are often the organ-isms least affected by edge effects (Malcolm, 2001). Thus,M. rufus, C. major, and D. madagascariensis should beomnipresent in forest fragments. Insectivores may preferforest edges because of abundant insect prey in this micro-habitat (Passamani and Rylands, 2000; Spironello, 2001).Based on these assumptions, omnivores with a diet com-posed of insects (M. rufus) should range nearer to forestedges than omnivores that rarely eat insects (C. majorand D. madagascariensis). Changes in the availability oflarge fruit trees may influence ranging patterns in foli-vore/frugivores (P. d. edwardsi and L. microdon). There-fore, P. d. edwardsi and L. microdon should tend to rangeat relatively intermediate distances from the edge com-pared to folivores (A. laniger and H. g. griseus) and frugi-vores (E. f. rufus and E. rubriventer).In this paper, data are presented on how biotic edge

effects may influence the density and distribution oflemurs in the Vohibola III Special Reserve in southeasternMadagascar. Specifically, we sought to answer the follow-ing questions: 1) do the distribution and density of lemursand lemur food trees vary as a function of proximity to for-est edges, and 2) are there ecological correlates betweenthe distributions of lemurs and lemur food trees?

METHODS

The data presented here were collected from June 1–October 29, 2003 and May 28–September 26, 2004 atCamp Mangiatsika in the Vohibola III Classified Forest insoutheastern Madagascar. These data were used specifi-cally to avoid conflating seasonal variations in rangingpatterns with edge effects (Fortin et al., 1996). Moreover,this time period is associated with a period of foodresource scarcity for lemurs in southeastern Madagascar(Overdorff, 1993). Thus, edge effects should be particu-larly relevant to the ranging patterns and feeding ecologyof lemurs during June–October. Vohibola III is a 2,034-haforest fragment located at 208 430 South and 478 250 East,200 km southeast of the capital city of Antananarivo(Fig. 1). Vohibola III is at the southern end of the Fandri-ana-Marolambo forest corridor (Lehman, 2000). CampMangatsiaka is located at 208 410 32@ South, 478 260 15@East (1,180-m altitude) in the central section of VohibolaIII. Rainfall amounts average 2,650 mm per year, and theheaviest rains tend to come during the October–Marchwarm, wet season in southeastern Madagascar (Wright,1999). Average annual temperature is 218C, with annuallows (48C) occurring between June–September (Overdorff,1993).Vohibola III is located in the midaltitude humid forest

region of southeastern Madagascar (Nicoll and Langrand,1989). Midaltitude humid forest tends to be composed ofendemic species of Tambourissa (Monimiaceae), Ephip-

Fig. 1. Location of study site in Vohibola III Classified For-est. Triangle indicates location of Camp Mangiatsika.

233LEMUR RESPONSES TO EDGE EFFECTS

piandra (Monimiaceae), Ocotea (Lauraceae), Breonia(Rubiaceae), Oncostemum (Myrsinaceae), and Cyathea(Cyatheaceae). The shrub and herb layers include variousspecies of Compositae, Rubiaceae, and Myrsinaceae.There is also a high diversity of Pandanus species (Panda-naceae), bamboos (Poaceae), and epiphytic plants (Nicolland Langrand, 1989; Lowry et al., 1997). The canopy iscontinuous and low (ca. 10 m in height), and the tallesttrees are 25 m in height.The matrix is composed entirely of intensive cultivation

in the area surrounding Vohibola III. Cultivation involvesrice paddies and agricultural crops such as sugar cane(Saccharum officinarum, Poaceae) and tobacco (Nicotianatabacum, Solanaceae). Most cultivation involves slash-and-burn agriculture, known locally as tavy, in whichnative and secondary forests are cleared and burned. Vari-ous crops, mostly dry land rice and sugar cane, areplanted for approximately 3–5 years and then abandonedfor approximately 15 years. Colonizing species, includingwoody plants such as Harongana madagascariensis (Clu-siaceae), form a secondary thicket in abandoned cultivatedareas. The tavy cycle is repeated until all vegetation isreduced to an impoverished secondary grassland. There islimited farming that involves tiered rice fields, and thusno burning of local vegetation, but this type of agricultureis not located near Vohibola III.In total, six 1,250-m transects were set up for lemur and

botanical surveys in Vohibola III. Following Chen et al.(1992) and Malcolm (1994), each of the six transects ranperpendicular from the forest edge into the forest interior.The first tree trunk encountered on each transect wasused as the edge point for a transect. Numbered flaggingtape was used to mark 10-m increments from the forestedge (0-m mark) into the forest interior (1,250 m) for eachtransect. Botanical surveys were conducted along bothsides of each transect to a depth of 1 m, for a total areasampled of 1.5 ha. For all trees over 5 cm diameter atbreast height (dbh), data were collected on height (m), dbh(cm), local name, and distance to forest edge (m). Thesedata were used to determine the area (m2) and volume(m3) of each tree. Voucher specimens were collected fortrees identified by local name with the assistance of localguides. Specimens were deposited for scientific identifica-tion by botanists at Parc Tsimbazaza in Antananarivo.Transects were walked slowly (0.5–1.0 km/hr) during

the times of day best suited for locating lemurs (0700–1100 hr and 1400–1700 hr). Surveys for nocturnal lemurswere conducted from 1900–2230 hr along four of thetransects (I, II, III, and V). Nocturnal surveys of transectsIV and VI were not conducted due to the steep terrain (ca.808 slopes) and heavy rainfall. Starting points for all sur-veys were rotated between the forest edge and the 1,250-m mark to ensure that data were not biased. The followingdata were collected whenever lemurs was seen: date, time,transect number, participants, distance along trail fromfirst animal seen/middle of group, species/subspecies,group composition and size, sighting distance from trail at908, height (m) of first animal seen, group spread, andmethod of detection. Species and subspecies characteris-tics described in Mittermeier et al. (1994) and Garbut(1999) were used for field identification. No animals werecaptured.Density (number of individuals per km2) was estimated

only for species that had at least 80 total sightings of indi-viduals. These values were chosen to ensure that smallsample sizes did not bias the density analyses. Lemur den-sities were obtained by dividing the number of individuals

surveyed by the total survey area. Densities were deter-mined for 100-m increments (i.e., 0–100 m, 101–200 m,etc.) from the forest edge into the interior. Species-specificsighting widths for each 100-m increment were estimatedusing the perpendicular distance (m) from the group tothe transect and the histogram inspection technique, witha 50% criterion for falloff distance (Whitesides et al.,1988). This method was found to provide accurate densityestimates for lemurs in southeastern Madagascar (John-son and Overdorff, 1999).Tree species that form an important component (>10%

of monthly feeding scores) of the May–October diet oflemurs were identified using data from conspecifics atRanomafana National Park (Overdorff, 1993; Atsalis,1999; Tan, 2000; Faulkner, 2005). Ranomafana is in thesame biogeographic zone, is similar in plant composition,and contains the same lemur species as Vohibola III (Leh-man, 2000). Botanical data on lemur food trees were alsoused to estimate densities (number of trees per hectare)for 100-m increments. The density method used forlemurs was replicated for trees, except that the perpendic-ular distance was fixed at 2 m for botanical data. Eachdensity estimate used only those trees specific to the dietof each lemur species. The following mean botanical varia-bles were also used: height (m), dbh (m), area (m2), andvolume (m3).Chi-square (v2) tests were used to determine if there

were significant differences in survey efforts betweentransects for diurnal surveys and nocturnal surveys.Mann-Whitney U-tests were used to determine if therewere significant: 1) between-year variations in edgeeffects for each lemur species, 2) differences in sightingdistances from the forest edge for M. rufus vs. omnivores,and 3) differences in sighting distances from the forestedge for folivore/frugivores vs. folivores and frugivores.Kruskal-Wallis tests (H) were used to determine if therewere significant between-month and between-transectvariations in proximity to forest edge for each lemur spe-cies. Spearman rank correlations (rs) were used to deter-mine if lemur sightings were an artifact of survey effortand if body size correlated with mean proximity to forestedge. Body mass was included in analyses as an additionalmeasure of resource requirements (Smith and Jungers,1997). Linear and polynomial (quadratic and cubic)regression models were used to determine how lemurdensities and species-specific food tree characteristics(dependent variables) varied as a function of distancefrom forest edge (independent variable). Polynomialregression analyses were used because there is no reasonto assume that edge effects and response variables varymonotonically (Murcia, 1995). If more than one modelreturned a statistically significant result, then a specificmodel was chosen when it explained the greatest amountof variation in the dependent variable(s). Spearman rankcorrelations were used to determine correlates betweenlemur densities and species-specific food trees (density,mean height, mean dbh, mean area, and mean volume) asa function of distance from the forest edge. Statisticalanalyses were conducted using SPSS 11.5. The alpha levelwas set at 0.05 for all analyses.

RESULTS

In total, 415 diurnal (N ¼ 321) and nocturnal (N ¼ 94)lemur surveys were conducted in Vohibola III (Table 1).There were no significant differences in the distribution ofdiurnal surveys across the six transects (v2 ¼ 3.26, df ¼ 5,

234 S.M. LEHMAN ET AL.

P ¼ 0.19). The frequency distribution of nocturnal surveysalso did not differ across the four transects (v2 ¼ 0.02, df ¼3, P ¼ 0.99).In total, 589 individuals representing four nocturnal

species (A. laniger, C. major, L microdon, and M. rufus)and four diurnal species (E. rubriventer, E. f. rufus, H. g.griseus, and P. d. edwardsi) were sighted during surveys(Table 2). Bite marks on tree branches and trunks indi-cated the possible presence of D. madagascariensis inVohibola III; however, no sightings were made of thisunique species. No sightings were made of V. v. variegata.There was no correlation between number of lemur sight-ings and survey effort (rs ¼ �0.551, N ¼ 6, P ¼ 0.25),indicating that statistical results are not an artifact ofvariations in survey effort. There were no annual ormonthly variations in proximity to forest edge for any ofthe lemur species in Vohibola III. Moreover, there wereno significant between-transect variations in edge prox-imity for any of the lemur species seen in Vohibola III.Because the data presented here are not an artifact oftemporal or spatial variations in ranging patterns, spe-cies-specific lemur data were pooled across years andtransects.Minimum sample size requirements for computing den-

sity estimates were met only for E. rubriventer, H. g. gri-seus, A. laniger, and M. rufus (Table 3). There were no sig-nificant relationships between density and proximity toforest edge in E. rubriventer (Fig. 2 and Table 4). However,removal of the low density data point at 100 m for E.rubriventer resulted in a highly significant cubic relation-ship between the distribution of this species and proximityto the forest edge (R ¼ 0.898, ANOVA F0.006 [3, 7] ¼ 9.72).Therefore, E. rubriventer was classified as omnipresentor edge-tolerant. There was no significant relationshipbetween density and proximity to forest edge in H. g. gri-seus. H. g. griseus was classified as omnipresent. A cubicregression model revealed that proximity to the forestedge was a major determinant of density for A. laniger (R¼ 0.860, ANOVA F0.01 [3, 8] ¼ 7.59), explaining 74.0% of thevariation in distribution and density of this species. A.laniger was classified as edge-tolerant. There was a linear,negative relationship between proximity to forest edgeand density for M. rufus (R ¼ 0.641, ANOVA F0.02 [1, 10]

¼ 6.98). M. rufus was classified as edge-tolerant because itshighest densities occurred at the forest edge.M. rufus ranged significantly closer to forest edges than

C. major (U ¼ 104.0, z ¼ �2.45, P ¼ 0.014). For folivores,there were no significant differences in sighting distancesbetween A. laniger and H. g. griseus (U ¼ 1,258.0, z¼ �1.589, P ¼ 0.112). For frugivores, average proximity tothe forest edge was 530.0 6 413.5 m in E. f. rufus (N ¼ 5)and 590.2 6 405.3 m in E. rubriventer (N ¼ 91). These val-ues did not differ significantly (U ¼ 205.0, z ¼ �0.371, P¼ 0.711). For the frugivore/folivores, proximity to forest

edge did not differ between P. d. edwardsi and L. micro-don (U ¼ 101.0, z ¼ �1.919, P ¼ 0.057). Thus, data werepooled for species that exhibit similar dietary patterns toproduce data sets specific to folivores, frugivores, and foli-vore/frugivores. There were no significant differences insighting distances for folivore/frugivores compared to fru-givores (U ¼ 1,874.5, z ¼ �0.633, P ¼ 0.527) or folivores(U ¼ 1,585.5, z ¼ �0.728, P ¼ 0.46). Mean distanceto forest edge was not correlated with average body sizefor either males (rs ¼ �0.455, N ¼ 7, P ¼ 0.25) or females(rs ¼ �0.476, N ¼ 7, P ¼ 0.23).Of 7,546 trees measured along the six transects, 10.7%

(N ¼ 813) were identified as being exploited as foodresources by A. laniger, M. rufus, E. rubriventer, and H. g.griseus during the June–October time period (Tables 5and 6). Proximity to forest edge was a significant lineardeterminant of the density of A. laniger food trees (R ¼0.590, ANOVA F0.044 [1, 10] ¼ 5.34), explaining 34.8% of thevariation in tree density. For food trees used by M. rufus,distance to forest edge was significantly correlated withdbh (R ¼ 0.598, ANOVA F0.040 [1, 10] ¼ 5.59), height (R ¼0.778, ANOVA F0.049 [3, 8] ¼ 4.11), area (R ¼ 0.787, ANOVAF0.043 [3, 8]¼ 4.36), and volume (R¼ 0.665, ANOVA F0.018 [1, 10]

¼ 7.91). The area (R ¼ 0.799, ANOVA F0.035 [3, 8] ¼ 4.71)and volume (R ¼ 0.809, ANOVA F0.029 [3, 8] ¼ 5.08) of foodtrees used by E. rubriventer varied as cubic functions ofdistance from forest edge. Food trees exploited by H. g.griseus varied as a function of distance from forest edgefor density (R ¼ 0.683, ANOVA F0.014 [1, 10] ¼ 8.76), area(R ¼ 0.815, ANOVA F0.026 [3, 8] ¼ 5.30), and volume (R¼ 0.828, ANOVA F0.021 [3, 8] ¼ 5.80).The density of M. rufus was positively correlated with

the density of trees used as food resources by this lemurspecies (rs ¼ 0.589, df ¼ 12, P ¼ 0.04; Table 7). There wereno significant correlations between the distribution anddensity of A. laniger, E. rubriventer, or H. g. griseus andany characteristics of species-specific food trees. Removalof the low density outlier for E. rubriventer did not resultin any significant correlations with food trees exploited bythis species.

DISCUSSION

The first prediction was that E. rubriventer, the onlyfrugivore for which density estimates could be computed,would be edge-intolerant due to the loss of fruit trees nearforest edges. However, E. rubriventer ranged widely (5–1,250 m from the edge) throughout Vohibola III, andregression analyses revealed that this species is eitheredge-tolerant or omnipresent. Although the area and vol-ume of food trees exploited by E. rubriventer showedmarked edge effects, there were no botanical correlateswith the distribution and density of this lemur species.Lack of covariation between E. rubriventer and its foodtrees may be because the survey data were collected dur-ing the period of relatively low fruit feeding and relativelyhigh exploitation of leaves for conspecifics at nearby Rano-mafana National Park. For example, Overdorff (1993)found that overall feeding time and percentage of feedingtime on fruits were lowest from August to mid-October.Conversely, the percentage of feeding time E. rubriventerspent feeding on leaves was highest during July to mid-September. Thus, dietary patterns of E. rubriventer weremore like those of a folivore/frugivore during the timeperiod of this study, in which case this lemur should havebeen predicted to be omnipresent in Vohibola III. An inter-esting question that cannot answered at this time is if E.

TABLE 1. Frequency distribution of lemur surveys conductedalong six transects in Vohibola III

Transect

Lemur survey frequency

Diurnal Nocturnal Total

I 62 24 86II 55 23 78III 47 23 70IV 50 0 50V 64 24 88VI 43 0 43Total 321 94 415

235LEMUR RESPONSES TO EDGE EFFECTS

rubriventer will be edge-intolerant during the period ofmaximum fruit exploitation (ca. November–early June)?Data are being collected during this time period, and thisquestion will be investigated in future studies.The second prediction was that H. g. griseus (bamboo

specialist) and A. laniger (folivore) would be omnipresentin Vohibola III. H. g. griseus was found to be omnipresent,and there were clear negative edge effects associated withthe area and volume of food trees eaten by this lemur spe-cies. Despite this evidence of edge effects for food trees,none of the botanical variables covaried with the distribu-tion and density of H. g. griseus. Lack of correlationsbetween food trees and the distribution and density of H.g. griseus is not unexpected, given that Tan (1999) foundthat 72% of the annual diet of this lemur is comprised ofgiant bamboo (Cathariostachys madagascariensis). Bam-boo was not included in botanical surveys in Vohibola III.A. laniger was clearly tolerant of forest edges, and thusrefuted the a priori prediction of its being omnipresent.For example, three separate sightings were made of indi-viduals resting in the canopies of trees that overhung thematrix. However, none of the botanical measures corre-lated with the distribution and density of A. laniger. Clinalvariations in food quality rather than abundance repre-sent a possible covariate to the distribution and abun-dance of A. laniger. Ganzhorn (1995) documented thatlow-intensity logging increased light levels in western dryforests, which resulted in higher protein concentrations inleaves. Elevated light levels were documented near forestedges in Vohibola III (Lehman, unpublished findings).

Thus, the quality of leaves may be highest near forestedges in Vohibola III. These edge-related variations in foodquality are particularly relevant to A. laniger. A. laniger isa small-bodied (600–1,300 g) folivore with a simple mono-gastric stomach. This lemur species lacks two of the keymorphological adaptations associated with folivory: largebody size and a complex sacculated stomach (Faulkner,2005). If edges do contain higher-quality food sources forfolivores, then A. laniger should be expected to be edge-tol-erant. Future studies will seek to test this hypothesis bycomparing leaf chemistry at differing proximities to forestedges in Vohibola III.M. rufus was predicted to be omnipresent and to range

nearer the forest edge than C. major. However, M rufuswas classified as edge-tolerant. Moreover, the density anddistribution of this lemur species were positively corre-lated with the density and distribution of its food trees inVohibola III. Tolerance for edge effects may also be due tothe abundance of insect prey near the forest edge (Corbinand Schmid, 1995), although ecological patterns of insectabundance have not been studied directly in southeasternMadagascar. Previous surveys noted an abundance of M.rufus near forest edges and secondary forests at sites inthe main forest corridor 35 km north of Vohibola III (Leh-man and Ratsimbazafy, 2000). Furthermore, M. rufustended to preferentially consume arthropods during theperiod of this study (Atsalis, 1998). Malcolm (1997) notedsimilar patterns in the distribution of insectivorous mam-mals in Brazil. Specifically, he documented higher arthro-pod populations near forest edges, which explained why

TABLE 2. Descriptive and comparative statistics on proximity to forest edge for eight lemur species in Vohibola III1

Species

Number of sightings Distance from edge (m) Temporal and spatial variations

Individuals Groups Mean SD Range Month2 Year3 Transect2

A. laniger 85 573.9 432.0 0–1,250 3.39 (0.33) �1.15 (0.24) 1.40 (0.30)C. major 6 888.3 418.1 90–1,250 2.14 (0.14) �1.46 (0.33) 1.42 (0.69)E. f. rufus 16 5 530.0 413.5 140–1,080 3.80 (0.28) NA 3.80 (0.28)E. rubriventer 212 91 590.2 405.3 5–1,250 4.59 (0.33) �0.475 (0.63) 5.01 (0.41)H. g. griseus 109 47 684.3 419.3 15–1,250 6.94 (0.13) �0.427 (0.66) 4.07 (0.53)L. microdon 19 677.5 427.2 80–1,234 2.51 (0.47) �0.399 (0.74) 5.64 (0.06)M. rufus 96 437.7 287.8 0–1,230 2.84 (0.58) �0.507 (0.61) 6.78 (0.06)P. d. edwardsi 46 17 396.4 337.3 90–1,250 5.24 (0.26) �1.64 (.013) 1.83 (0.76)

Total 589 160 568.3 396.8 0–1,250

1 Statistics for group-living primates are based on sighting distance for group rather than individuals.2 Kruskal-Wallis H (P-value).3 Mann-Whitney z-score (P-value); E. f. rufus surveyed only in 2004.

TABLE 3. Density estimates (number of individuals/km2) as function of proximity to forest edge for four speciesof lemurs in Vohibola III

Distance (m)

E. rubriventer H. g. griseus A. laniger M. rufus

Mean SD Mean SD Mean SD Mean SD

0–100 11.1 6.6 8.3 1.7 67.5 18.1 40.6 6.5101–200 75.0 15.7 10.7 2.7 10.0 3.9 21.9 20.5201–300 46.9 17.2 17.9 15.2 0.0 0.0 46.9 15.2301–400 20.8 7.4 11.9 7.1 7.5 5.4 12.5 14.3401–500 16.2 2.9 17.9 18.4 7.5 5.3 59.4 15.3501–600 15.3 16.5 7.1 15.1 12.5 6.3 43.8 11.4601–700 31.3 19.0 21.4 9.4 7.5 4.4 9.4 13.7701–800 6.3 5.0 2.4 5.7 10.0 5.7 12.5 5.6801–900 8.3 4.7 19 16.8 12.5 2.5 12.5 5.8901–1,000 27.8 26.5 9.5 18.9 25.0 8.6 12.5 2.4

1,001–1,100 16.7 25.7 8.9 15.4 25.0 7.8 6.3 0.01,101–1,250 37.1 36.0 21.2 13.8 15.0 3.9 4.2 10.6

Total 26.7 10.2 13.4 12.2 16.6 6.6 24 5.8

236 S.M. LEHMAN ET AL.

insectivorous mammals were unaffected by edge effects.This hypothesis is supported by the fact that M. rufusranged significantly closer to the forest edge than C.major, which do not rely heavily on insects. Ultimately,detailed studies must be conducted on how edge effectsinfluence the abundance and availability of insects eatenby lemurs in Vohibola III.The final prediction tested in this paper was that foli-

vores/frugivores (P. d. edwardsi and L. microdon) shouldtend to range at relatively intermediate distances fromthe edge compared to folivores (A. laniger and H. g. gri-seus) and frugivores (E. f. rufus and E. rubriventer). Thedata presented here do not support this prediction. Thereasons that this prediction were not supported are diffi-

cult to determine, given the small sample sizes for P. d.edwardsi, L. microdon, and E. f. rufus. However, each ofthese three species tended to range widely throughout theforest (80–1,250 m from the forest edge). Although thespecies-specific mean distances from the forest edgeranged from a minimum of 396.4 m for P. d. edwardsi to amaximum of 677.5 m for L. microdon, the associatedstandard deviations were very large (337.3 m and 427.2m, respectively). These descriptive statistics tend to indi-cate that P. d. edwardsi, L. microdon, and E. f. rufus aremore likely to be omnipresent than edge-intolerant. Fur-ther surveys should increase sample sizes to the pointwhere more detailed comparative analyses can be con-ducted.

Fig. 2. Density variations and polynomial regression coefficients as function of distance from forest edge for four lemur speciesin Vohibola III. Arrow in plot for E. rubriventer indicates outlier value removed for subsequent analyses.

TABLE 4. Linear and polynomial regression models of relationship between lemur density and proximity to forest edge,with statistically significant models in bold

Species Model Model R Model R2 df F P b0 b1 b2 b3

E. rubriventer Linear 0.276 0.076 1, 10 0.82 0.386 35.69 �4.70Quadratic 0.437 0.191 2, 9 1.06 0.385 53.45 �8.90 0.560Cubic 0.565 0.319 3, 8 1.25 0.354 25.16 12.28 �3.000 0.190

E. rubriventer(outlier removed)

Linear 0.456 0.208 2, 9 2.36 0.159 46.34 �2.68Quadratic 0.872 0.761 3, 8 12.71 0.003 106.01 �23.65 1.000Cubic 0.898 0.807 3, 7 9.73 0.007 141.08 �43.86 4.386 �0.146

H. g. griseus Linear 0.155 0.024 1, 10 0.25 0.629 11.29 2.66Quadratic 0.164 0.027 2, 9 0.13 0.883 12.21 �1.25 0.029Cubic 0.477 0.228 3, 8 0.79 0.534 9.88 8.32 �0.147 0.0742

A. laniger Linear 0.170 0.029 1, 10 0.30 0.596 21.98 �8.10Quadratic 0.600 0.360 2, 9 2.53 0.134 48.85 �1.20 0.850Cubic 0.860 0.740 3, 8 7.59 0.010 92.32 �44.61 6.667 0.000

M. rufus Linear 0.641 0.411 10 6.98 0.025 45.28 �3.34Quadratic 0.657 0.431 2, 9 3.41 0.079 37.90 �3.10 �0.200Cubic 0.680 0.463 3, 8 2.30 0.154 24.36 9.83 �2.000 0.089

b refers to beta coefficients.

237LEMUR RESPONSES TO EDGE EFFECTS

Lemur body size was not correlated with proximity toforest edge in our study. Body size is associated allometri-cally with metabolic rate, energetic demands, and physicalperformance in animals (Schmidt-Nielsen, 1997). In termsof energetic demands and body size, large animals tend torequire larger home ranges and feeding areas than smallanimals (Calder, 1984). Thus, it is hypothesized thatlarger-sized animals are more at risk of extinction, and itcould be argued that smaller-bodied primates would bebest suited to exploit habitat edges (Gaston and Black-burn, 1996). However, there is little support for relation-

ships between body size and edge responses, forest frag-mentation, and habitat loss (reviewed in Davies et al.,2000). Ultimately, the lack of relationship between bodysize and edge effects may be a consequence of the manyecological and phylogenetic covariates to body size in pri-mates (Gittleman and Purvis, 1998).Understanding generalized lemur responses to edge

effects may explain how they have survived dramatic hab-itat loss and forest fragmentation in Madagascar. Becauselemurs are one of the world’s top conservation priorities,there is considerable research being focused on why cer-

TABLE 5. Scientific and local names of plants eaten by four lemur species during June–October1

Scientific name2 Family Local name E. rubriventer2 H. g. griseus A. laniger M. rufus Total

Anthocleista madagascariensis Loganiaceae Variahy � � � X 1Aphloia theiformis Aphloiaceae Ravimboafotsy � � � X 1Canthium sp. Rubiaceae Fantsikahitra � � X � 1Canthium sp. Rubiaceae Ravimboanjo � � X � 1Dombeya laurifolia Sterculiaceae Hafibalo � � X � 1Erythroxylum nitidulum Erythroxylaceae Ravimbolo � � X � 1Eugenia sp. Myrtaceae Ratrifotsy X � � � 1Ficus soroceoides Moraceae Ravosa � X � X 2Gambeya madagascarensis Sapotaceae Famakilela X � 1Gaertnera sp. Rubiaceae Taolagnana � X � X 2Grewia humblotii Tiliaceae Hafipotsy � X � � 1Harungana modagascariensis Clusiaceae Harongana X � X � 2Memecylon aff. delphinense Melastomataceae Tomenjy � � X � 1Musaenda sp. Rubiaceae Fatora � X � � 1Nuxia pachyphylla Loganiaceae Lambinana � � � X 1Oconstemon leprosum Myrsinaceae Hazotohoka � � X X 2Ocotea cymosa Lauraceae Varongifinga X � � � 1Ocotea laevis Lauraceae Varongy X � � � 1Psychotria polyphylla Rubiaceae Voafotsiala � � � X 1Syzygium phyllyreifolium Myrtaceae Rotra � � X � 1

Total 5 4 8 7 24

1 X, plant species eaten by that lemur species; �, not eaten by that lemur species.2 E. rubriventer from Overdorff, 1993; H. g. grisesus from Tan, 2000; A. lanifer from Faulkner, 2005; M. rufus from Atsalis, 1999.

TABLE 6. Linear and polynomial regression models of relationship between characteristics of species-specific lemur food trees andproximity to forest edge1

Species Variables Model Model R Model R2 df F P b0 b1 b2 b3

E. rubriventer Mean area Cubic 0.799 0.638 3, 8 4.71 0.035 0.59 �0.003 4.706 �0.209Mean volume Cubic 0.809 0.655 3, 8 5.08 0.029 10.04 �0.520 9.036 �0.423

H. g. griseus Density Linear 0.683 0.467 1, 10 8.76 0.014 35.70 0.430Mean area Cubic 0.815 0.665 3, 8 5.30 0.026 0.24 �0.009 0.0001 �0.0006Mean volume Cubic 0.828 0.685 3, 8 5.80 0.021 3.45 �0.015 0.0022 �0.0092

A. laniger Density Linear 0.590 0.348 1, 10 5.34 0.044 159.15 �6.110M. rufus Mean dbh Linear 0.598 0.358 1, 10 5.59 0.040 31.72 �1.220

Mean height Cubic 0.778 0.606 3, 8 4.11 0.049 10.47 �2.100 3.200 �0.142Mean area Linear 0.763 0.582 1, 10 13.91 0.004 0.12 �0.008Mean area Quadratic 0.771 0.595 2, 9 6.60 0.017 0.13 �0.011 0.000Mean area Cubic 0.787 0.620 3, 8 4.36 0.043 0.15 �0.000 0.000 0.000Mean volume Linear 0.665 0.442 1, 10 7.91 0.018 1.40 �0.001

1 Only statistically significant relationships are presented.b refers to beta coefficients.

TABLE 7. Spearman rank correlations between lemur densities and characteristics of species-specific food trees,both measured as function of distance from forest edge

Species Density Mean dbh Mean height Mean area Mean volume

E. rubriventer �0.403 (0.19) �0.342 (0.27) �0.112 (0.72) �0.336 (0.28) �0.307 (0.33)E. rubriventer1 �0.296 (0.37) �0.300 (0.37) �0.086 (0.79) �0.291 (0.38) �0.281 (0.40)H. g. griseus 0.037 (0.98) 0.408 (0.18) 0.122 (0.70) 0.049 (0.87) 0.171 (0.593)A. laniger 0.218 (0.41) �0.304 (0.33) �0.474 (0.11) �0.320 (0.30) �0.361 (0.24)M. rufus 0.589 (0.04) 0.377 (0.22) 0.386 (0.21) 0.557 (0.06) �0.520 (0.08)

1 100-m outlier removed.

238 S.M. LEHMAN ET AL.

tain species are rare, and whether or not we can predictwhich species are most likely to go extinct (Jernvall andWright, 1998). Studies of extinction probabilities ofteninvoke some aspect of species-area relationships. Species-area relationships predict a positive relationship betweennumber of species and size of an area (Rosenzweig, 1995).This relationship is expressed as the equation S ¼ CAz,where S is species richness, C is a fitted constant thatvaries among taxa and types of ecosystems, and z is a con-stant that tends to range from 0.10–0.50. It is surprisingin light of recent theoretical work on thresholds of forestloss and fragmentation that dramatic landscape changeshave not resulted in the extinction of lemur species inMadagascar (Fahrig, 2002), although there have beenmany species extirpations (Godfrey et al., 1999). The abil-ity of lemurs to tolerate edge effects may have enabledthem to survive such dramatic landscape changes.Lemurs may not be the only tropical taxa unaffected byedge effects. Malcolm (1997) found that the abundance ofmany species of arboreal mammals was not affected byforest fragmentation, matrix conditions, or edge effects inBrazil.The generally positive or negligible influences that for-

est edges have on lemurs are being offset by deterioratingcharacteristics of their forest habitats. Only one regres-sion model returned a positive relationship between a bot-anical measure and proximity to the forest edge (densityof H. g. griseus food trees). All other significant botanicalregression models indicate that the density and dendro-metrics of food trees are being negatively influenced byedge effects in Vohibola III. Thus, both the density andsize of lemur food trees are decreasing near the forestedge. Continued deforestation may result in forest frag-ments being composed entirely of edge habitats. AlthoughGanzhorn (1995) noted that low-intensity logging in-creased light levels and the quality of food resources indry forests, he also documented that more intense loggingresulted in a decline in lemur populations. For example,increased temperatures near forest edges may be deleteri-ous to nocturnal lemurs, such as Microcebus murinus,that enter energy-saving torpor during the dry season indry forests (Ganzhorn and Schmid, 1998). These data indi-cate that there may be a threshold of habitat disturbanceand possibly edge effects for lemurs. Determining whatthis edge threshold is may hold important answers forquestions about extirpation and extinction patterns inlemurs.Finally, edge-related variations in predation on lemurs

may influence their distribution and density in VohibolaIII. Numerous studies of predator-prey relationships andedge effects indicated variations in predation pressures inforest fragments (reviewed in Lahti, 2001). In many stud-ies, predation rates were heightened for nesting birdsnear forest edges. All lemurs species experience predationpressures from raptors (e.g., Accipter henstii and Polybor-oides radiatus), reptiles (e.g., Acrantophis madagascar-iensis), and/or carnivores (e.g., Cryptoprocta ferox) insoutheastern Madagascar (Goodman et al., 1993, 1998;Wright et al., 1997; Rakotondravony et al., 1998; Burney,2002; Goodman, 2003). Furthermore, Karpanty (2003)documented that lemurs can distinguish between differ-ent types of predators (aerial or terrestrial) and then altertheir activity patterns to avoid predation. Thus, if thereare edge effects associated with the distribution and abun-dance of predators, then lemurs may be responding to thiseffect in conjunction with the distribution and quality offood resources. One possible method of testing for varia-

tions in predation rates as a function of edge effects wouldbe to conduct a series of mark-and-release experimentswith M. rufus at different distances from the forest edge.Although such an experiment would not directly measurepredation, it should provide data on edge-related varia-tions in mortality. Following Karpanty (2003), experi-ments could also be conducted using playbacks of predatorvocalizations for conspecific lemurs at differing distancesfrom the forest edge. These data may reveal important dif-ferences in how lemurs respond to predation risks relativeto proximity to forest edges.

CONCLUSIONS

The first question addressed in this paper related tolemur and food tree responses to edge effects. Althoughlemurs responded either positively or not at all to edgeeffects, there was an overwhelming negative influence ofedge effects on the density and dendrometrics of lemurfood trees. The second question related to ecological corre-lates between the distribution of lemurs and their foodtrees. These correlates were found only for the density ofM. rufus and its food trees. The predictions tested hereinrelated to food abundance as a function of edge effects.However, edge-related variations in food quality and pre-dation pressures may occur in Vohibola III. Thus, relation-ships between edge effects and lemur biogeography reflectcomplex and varying causalities in Vohibola III, and per-haps in all humid forests in southeastern Madagascar.Increased sample sizes, chemical data on food quality, andexperimental studies of predation pressures in forest frag-ments will provide a greater understanding of how lemursrespond to edge effects in southeastern Madagascar.Finally, data are needed on how forests and lemurs areinfluenced by edge effects in other biogeographic regionsin Madagascar. These data will be critical to an increasedunderstanding of how edge effects influence the biogeog-raphy and conservation biology of lemurs in the rapidlyvanishing forest landscapes of Madagascar.

ACKNOWLEDGMENTS

We thank the Association Nationale pour la Gestion desAires Protegees, le Ministere de l’Eau et de Foret, l’OfficeNational pour l’Environnement a Madagascar, and theUniversity of Antananarivo for permission to conduct ourresearch in Madagascar. We thank Patricia Wright, Ben-jamin Andriamahaja, and the staff at Institute for theConservation of Tropical Environments (ICTE) and Mala-gasy Institute for the Conservation of Tropical Environ-ments (MICET) for their support, advice, and hospitality.We are extremely grateful to Andriamihanta ‘‘Lekely’’Harison, Zafimamonjy, Andriaharizaka Johnson, Andria-mampiakatra ‘‘Ndrema’’ Rajaoarivony, Andriaharizaka‘‘Tsiamidy’’ Andry, Randrianjandrimalalason Celestine,Razatharimalaladraimy William, Razafimananjara Sam-uel, and Randriaharimanana Joelson for sharing theirknowledge of the forest, for assisting us with data collec-tion, and for their friendship and support. We greatlyappreciate the hospitality and kindness of the Mayor andpeople of the villages of Ambohimitombo and Sahanato.We thank the Geographic Information System (GIS) unit ofthe Royal Botanic Gardens at Kew for access to the GIS data-base on forest cover in Madagascar, Angel Vats for assistancewith data collection, and Natasha Bijelich and Serena Parkfor data entry. A previous draft of the manuscript benefited

239LEMUR RESPONSES TO EDGE EFFECTS

greatly from the comments of Colin Chapman, Robert Suss-man, and two reviewers.

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