Spatiotemporal Interactions Among Three Neighboring...

Spatiotemporal Interactions Among ThreeNeighboring Groups of Free-RangingWhite-Footed Tamarins (Saguinusleucopus) in Colombia

Lilian Alba-Mejia & Damien Caillaud &Olga L. Montenegro & Pedro Sánchez-Palomino &Margaret C. Crofoot

Received: 20 June 2013 /Accepted: 26 August 2013 /Published online: 24 November 2013# Springer Science+Business Media New York 2013

Abstract Successful conservation requires an understanding of animal movementpatterns and space use. Such data are hard to obtain, however, when difficult terrain,nocturnal habits, or lack of habituation make direct observation impractical. White-footed tamarins (Saguinus leucopus) are small primates endemic to Colombia that arein danger of extinction due to habitat loss, fragmentation, and the illegal pet trade. Here,we report the results of the first study to use radio-tracking to investigate white-footedtamarin ranging behavior. We recorded the movements of three neighboring tamaringroups simultaneously for 3 month using radio-telemetry. Home range sizes (estimatedusing both minimum convex polygon and fixed kernel contour methods) were

Int J Primatol (2013) 34:1281–1297DOI 10.1007/s10764-013-9740-6

L. Alba-Mejia : O. L. Montenegro : P. Sánchez-PalominoGrupo en Conservación y Manejo de Vida Silvestre, Instituto de Ciencias Naturales y Departamento deBiología, Universidad Nacional de Colombia, Bogotá 11001000, Colombia

L. Alba-Mejia :M. C. Crofoot (*)Smithsonian Tropical Research Institute, Apartado Postal 0843-03092, Balboa, Ancón, Panamá, Republicof Panamáe-mail: [email protected]

D. CaillaudSection of Integrative Biology, The University of Texas at Austin, Austin, Texas 78712, USA

D. CaillaudThe Dian Fossey Gorilla Fund International, Atlanta, Georgia 30315, USA

M. C. CrofootDepartment of Migration and Immuno-Ecology, Max Planck Institute of Ornithology, 78315 Radolfzell,Germany

M. C. CrofootDepartment of Ecology and Evolutionary Biology, Princeton University, Princeton, New Jersey 08544,USA

substantially larger than reported in previous studies that did not use remote-tracking.Monte Carlo resampling procedures revealed that home range size differed significantlyamong the three groups but that the mean daily path length did not. As in other tamarinspecies, the degree of range overlap between neighboring social groups was high,ranging from 27 to 81%. Using a randomization test, we showed that the observedmean distance between groups was significantly lower than expected by chance for twoof the three group dyads. This pattern of intergroup “attraction,” in conjunction withsubstantial range overlap and high population density, implies that the BellavistaForest, one of the few remaining habitats of Saguinus leucopus, may be saturated,and promoting habitat restoration should be a priority for the conservation of thisspecies.

Keywords Home range overlap . Radio-telemetry . Spatial attraction . Territoriality

Introduction

Effective conservation planning requires a clear understanding of species’ movementpatterns and space-use needs. Studying the movement ecology of individuals inthreatened populations is important for understanding and predicting population dy-namics (Kernohan et al. 2001; Morales et al. 2010) because of the fundamental rolethat individual movement plays in connecting spatially structured populations (Revillaand Wiegand 2008). This information is also necessary to determine whether a givenhabitat is suitable for reintroduction programs. Although food and/or water are oftenlimiting resources, species also compete directly for space (Morales et al. 2010). It istherefore important not only to determine how much space individuals or groups use,but also to understand how they share space.

Colombia is home to as many as 34 species of nonhuman primates (see Defler 2010for a full review of the taxonomic status of Colombian primates), at least 40% of whichare categorized as threatened according to the IUCN. Five of these (Saguinus oedipus,S. leucopus, Callicebus caquetensis, C. ornatus, and Aotus brumbacki) are endemic(Defler 2004; IUCN 2011). Despite their threatened status and restricted distribution,comparatively little is known about Colombia’s endemic primate species (Stevensonet al. 2010), and research is needed to inform conservation planning.

The white-footed tamarin (Saguinus leucopus) is one such species; it is in danger ofextinction due to the threats posed by habitat loss, forest fragmentation and the illegalpet trade (IUCN 2011). Its distribution range is the smallest of any Saguinus species,encompassing only 29,000 km2, and coincides with a zone of heavy human activity inColombia. Moreover, only a very small proportion of its remaining habitat is currentlyprotected by the Colombian National Natural Parks System (0.34%—10,019 ha—inthe Florencia Forest National Park). The development and implementation of effectiveconservation strategies have been hampered by a lack of information about manyaspects of the behavior and ecology of these primates (cf. Poveda and Sánchez-Palomino 2004; Roncancio et al. 2011; Sánchez-Londoño et al. 2009). For example,basic data on their ranging behavior and space use have not been collected because thechallenging terrain in their remaining habitat makes it difficult for human observers tomaintain contact with study groups.

1282 L. Alba-Mejia et al.

Callitrichids show extreme variation in their ranging patterns, both among speciesand among populations of the same species (Sussman 2003). Many species showextensive home range overlap, e.g., 70–99% in Callithrix jaccus (Mendes Pontes andMonteiro da Cruz 1995) and 76% in Saguinus fuscicollis (Peres 2000) even thoughencounters between groups are characterized by behavioral expressions of territoriality,including vigilance, vocal exchanges, chases, and physical aggression (Garber 1988;Lazaro-Perea 2001; Raboy et al. 2008). Thus, in addition to measuring basic rangingparameters such as home range size and day range length, studies of white-footedtamarin ranging behavior must also consider how groups share space. Traditional,“static” measures used to assess spatial interaction reveal the extent of the overlapbetween neighboring groups’ ranges, but tell us nothing about how groups influenceeach other’s movements. Primate groups may, for example, share large portions of theirranges but only rarely encounter one another, e.g., Cercocebus albigena (Waser 1976)or, conversely, may interact intensely and frequently in a small disputed region betweenmutually recognized territorial boundaries, e.g., Cercopithecus mitis stuhlmanni (Cords2002, 2007). “Dynamic” measures of spatial interaction, on the other hand, considerwhether two animals use the same space simultaneously or at different times(Doncaster 1990; Kernohan et al. 2001; Minta 1992), and thus can be importanttools for understanding the role that intergroup relationships play in shaping patternsof space use.

Remote tracking technology can be used to overcome the logistical difficultiesassociated with observing unhabituated animals and following them over challengingterrain. It also makes it easier to study multiple groups, simultaneously. Here, we reportthe results of the first study to use radio-telemetry to investigate the movement andspace use patterns of white-footed tamarins. We radio-tracked the movements of threetamarin groups living in the Bellavista Forest in Caldas, Colombia over a 3 monthperiod. With these location data, we evaluated the home range size and day rangelength of the neighboring groups. Because the total number of location estimatesobtained varied among groups, we used a simple resampling procedure to test if thedifferences in space use we observed were simply an artifact of our sampling, or werelikely to be real biological phenomena. We also assessed patterns of static and dynamicinteraction among neighboring groups and tested whether groups influenced eachother’s movement patterns. Because they belong to a genus known for its territorialbehavior (Garber 1998), we predicted that white-footed tamarin groups would avoidone another, spending less time in close proximity than expected by chance.

Methods

Study Area

We conducted this study in the Bellavista Forest in Caldas, Colombia (N5º18′59.4′W74º54′45.9″) near the southern limit of the range of Saguinus leucopus. The forestis jointly owned by the municipality and private citizens, but the regional environ-mental agency is currently working to place a government-held conservation ease-ment on the forest and designate it as a Natural Reserve of the Civil Society (Morales-Jiménez et al. 2008). The reserve covers an area of ca. 128 ha of tropical humid forest

White-Footed Tamarin Ranging Behavior 1283

in a landscape matrix transformed by agricultural activities such as cultivation andstockbreeding. The majority of the reserve (70%) is a mature forest located on an80% slope; the remaining 30% is in various stages of succession and is almost flat.Sánchez-Londoño and colleagues (2009) estimated that nine groups of white-footedtamarins inhabit this forest, corresponding to a population density of 35–38 ind./km2.The reserve is home to a wildlife rehabilitation center, CRFSOC (Centro deRehabilitación de Fauna Silvestre del Oriente de Caldas), which in 2007reintroduced three rehabilitated tamarins (a male and two females) into the reserve;three additional individuals accidentally escaped the same year (Morales-Jiménezet al. 2008). We recaptured one of these reintroduced individuals during our study(see Results).

Capture and Radio-Tagging

Before the start of this study, one of us (L. Alba-Mejia) underwent training inmethods for capturing and radio-collaring tamarins at the Proyecto Titi Foundation(http://proyectotiti.com) in Luruaco, Atlántico, Colombia (February 2009). FromMay to September, 2009, we trapped individuals from three neighboring, free-ranging white-footed tamarin groups following the methods suggested byBuchanan-Smith (1991), Garber and colleagues (1993), and Savage and colleagues(1993). Veterinarians from CRFSOC carried out all physical and chemical restraintof the captured individuals. After removal from the traps, the veterinarians anesthe-tized each tamarin with a combination of Tiletamine and Zolazepam (5 mg/kg)(Zoletil 50®, Virbac Laboratories, Carros, France), administered intramuscularly. Inaddition to a general medical examination, we also implanted a radio frequencyidentification (FID) microchip (Trovan Ltd., Melton, East Yorkshire, U.K.) under theskin on the interscapular zone to identify each individual. The regional environmentalgovernment agency CORPOCALDAS (Corporación Autónoma Regional de Caldas)approved all tamarin-capture and handling procedures. This study was carried out underthe auspices of The National Program for the Conservation of the Endemic Species ofColombia: Saguinus leucopus.

We fitted one adult female in each group we captured with a VHF radio-transmitter(Telonics, Inc., Mesa, AZ), using a backpack-style harness constructed of nylon tubing(3 mm in diameter). Each package measured 4.26 × 2.03 × 1.27 cm, weighed 20 g, andincluded a 15-cm antenna. We chose this attachment system because it is consideredwell suited for small bodied primates. Previous studies of tamarins report that back-pack style harnesses did not affect behavior or mobility of radio-tagged individuals(Savage et al. 1993), whereas other attachment systems, including collars and hip belts,have been reported to cause chaffing, infection, and, in the case of hip-belts, may causeproblems for pregnant individuals (Müller and Schildger 1994). Radio-tagged tamarinswere released at the same location as where they were captured to make it easier forthem to rejoin their group. After the end of the tracking period, we made extensiveefforts to recapture the study animals, and were able to remove one of the harnesses.One of the groups had shifted its home range to an area with extremely difficulttopography, making it impossible for us to recapture the radio-tagged group member.Despite intense efforts over a period of 2 mo, we were unable to induce the female inthe third group to reenter a trap.


http://proyectotiti.com/

Data Collection

Data collection took place between mid-September and mid-December, 2009. Exceptfor brief interruptions due to rain or unexpected circumstances such as researcherillness, groups were tracked daily during this period (see Table I for the total numberof tracking days and sample size of location estimates for each focal group). Althoughwe were unable to systematically collect observational data on our focal groups, weregularly sighted the radio-marked individuals traveling with their groups throughoutthe study. We thus feel confident that our radio-tracking data and space use estimatesare for groups, not for single individuals.

We used analog receivers and two-element directional antenna (Telonics, Inc., Mesa,AZ) to detect the signal emitted by the radio-transmitter each tamarin was carrying. Togenerate location estimates, two observers recorded compass bearings for the estimateddirection of each focal individual simultaneously from different points (telemetrystations) in the forest, every hour from 05:00 to 18:00. After recording the first setof bearings, observers quickly moved to different telemetry stations and recordeda second set of bearing estimates. This made it possible to triangulate the positions of theradio-tagged individuals. Most bearings (>90%) were recorded within the first half ofevery hour. The Universal Transverse Mercator (UTM) coordinates of the telemetrystations were obtained using a handheld GPS unit (GPSmap 60CSx: Garmin, Olathe,KS). To minimize error in the location estimates, observers used the same set ofprocedural rules when collecting data, and trained with the equipment using a set ofstationary transmitters until their bearing estimates fell within a ±5° range of the truedirection.

We examined our data with Locate III (Nams 2006) and discarded bearings thatwere flagged as problematic in the field notes, i.e., showing evidence of signal bounce,weakness, or interference. We then estimated individual point locations and their 95%maximum likelihood confidence ellipses using the maximum likelihood estimator(MLE) method implemented in Locate III. We obtained a total of 2,253 locations byeither biangulation or triangulation (see Table I for sample size by group and timeperiod). The distribution of the biangulated points was not statistically different acrossthe three groups (χ2 = 4.09, df = 2, P-value = 0.13) and the mean of the error ellipsesfor the three groups was 92.39 m2 ± SD 167.03 m2 (group A), 73.95 m2 ± SD 143.38m2 (group B), and 117.54 m2 ± SD 185.15 m2 (group C).

Table I Number of location estimates obtained for three groups of white-footed tamarins inhabiting theBellavista Forest in Caldas, Colombia, that were radio-tracked from September, 2009 to December 2009

Group A B C (Prea) C(Postb)

Total number of locations 798 812 470 173

Number of sampling days 70 72 40 21

Locations/day (avg.) 11.4 ± SD 2.2 11.3 ± SD 2.3 11.8 ± SD 2.4 8.2 ± SD 2.8

Locations/day (range) 6–14 5–14 6–14 2–12

a Premigrationb Postmigration


Home Range Estimation and Comparison

We used the AdehabitatHR Package (Calenge 2006) for R (R Development CoreTeam 2011) to calculate 95% minimum convex polygon (MCP; Mohr 1947) and 95%fixed kernel (FK; Worton 1989) home range estimates for each focal group. We splitgroup C’s data into two parts because it moved out of the study area 40 days into ourdata collection period. Including pre- and post-shift data in the calculation of group C’shome range inflated the size of the range and gave an incorrect impression of the areathey actually used at any given period of time. We thus used the data from before therange shift for all home range size comparisons. To verify that our sample size wassufficient to produce reliable home range estimates, we graphed each group’s cumu-lative home range size against the number of sampling days. The curve approached anasymptote at days 44, 48, and 28 for groups A, B, and C respectively, indicating thatour sampling effort was sufficient. Following current best-practice recommendations(Seaman et al. 1999), we used least squares cross validation (LSCV) to calculate thebandwidth (or smoothing parameter, denoted h) for the fixed kernel estimates. Wealso reran all analyses using a fixed value (h = 50) for the three groups. We chose thisvalue based on a visual inspection of the data, selecting the lowest h value thatyielded a contiguous 95% isopleth for at least one group. This selection criteriashould be relatively conservative, avoiding oversmoothing the data, a factor weconsider to be important given the high fragmentation of our study site. We performedthese additional analyses because all the h values obtained via LSCV broke theestimated utilization distribution up into numerous small peaks that we felt did notaccurately reflect the space use patterns of this species. The MCP method is the mostwidely used method of home range estimations in studies of primate ranging, but it issensitive to sample size and outliers can cause home range estimates that containareas where the subject never goes (Kernohan et al. 2001; White and Garrott 1990).We report MCP estimates only to allow comparisons with other studies, although forsuch comparisons to be valid, sample sizes and treatment of outliers must be comparable(Kernohan et al. 2001).

The accuracy of home range estimates can be affected by the number oflocations used (Seaman et al. 1999). In our study, the sampling days among thethree groups became uneven after we excluded group C’s post emigration data fromthe analysis. Therefore, to ensure the comparability of home range size estimates,we performed a Monte Carlo resampling procedure of 1000 iterations. We de-signed a stratified sampling procedure that randomly selected three locations perday from each of 40 sampling days (creating data sets of 120 locations estimates).We report the mean home range size of each group based on these resampled datasets, for each of the three methods of home range estimation described in thepreceding text.

To test whether the groups differ significantly in their home range sizes weperformed a similar bootstrapping procedure. However, because statistical testingrequires independent data points and relocation data are often autocorrelated, wesampled only one location per day from 40 randomly chosen sampling days for thisprocedure. We thus created 1000 data sets of statistically independent locationestimates and compared mean home range sizes for each pair of groups using two-sample permutation tests.


Home Range Overlap

We assessed the static interaction among the three focal groups by superimposingtwo-dimensional home range maps (HR1 and HR2) for every pair of groups (A+B,A+C, B+C). The degree to which neighboring groups share space is measured asthe proportion of the home range of one group (HR1) covered by that of the other(HR2):

HR1;2 ¼ A1;2A1 and HR2;1 ¼A1;2A2

where HR1,2 is the proportion of individual 1’s home range overlapped by indi-vidual 2’s home range, HR2,1 is the proportion of individual 2’s home rangeoverlapped by individual 1’s home range, and A1,2 is the area of overlap amongHR1 and HR2 (Kernohan et al. 2001). We repeated these overlap analyses for eachset of home range estimates: MCP, FK (h = LSCV); FK(h = 50).

Average Daily Path Length

To estimate each group’s daily travel distance, we used only the days for which we had13 location measurements, taken one each hour between 05:00 and 17:00. To avoidunexplained variation, we used the same 21 days for all three groups. We calculated thedistance between successive locations and summed the straight-line distances betweendata points to estimate the total distance traveled per day. Although this method doesnot consider vertical displacement and assumes straight movements between datapoints, it represents a minimum estimate of an individual’s daily travel distance. Giventhat our three groups ranged primarily in a flat part of the study area, we consider this tobe a reasonable estimate. In addition, it is the measure of day range that is most directlycomparable with previous studies of primate ranging behavior. We tested assumptionsof randomness, normality, and homoscedasticity. Our data do not violate randomnessand normality but they do violate homoscedasticity. Therefore, we used Kruskal–Wallisto test for the differences in the mean daily path length between the three groups oftamarins.

Defensibility Index

To allow us to compare the movement and space use patterns of the white-footedtamarins in this study to other territorial and nonterritorial primate species, we calcu-lated Mitani and Rodman’s defensibility index (1979), a measure that has often beenused as a proxy for whether or not territorial range defense is a feasible strategy(Heymann 2000; Nunn and Dokey 2006; Wich and Nunn 2002). The index (D),defined as

D ¼ d=d0;

relates the average distance a group travels per day (d) to the distance they would haveto travel to traverse their home range if it were perfectly circular, i.e., the radius of acircle whose area, A, is equal to the group’s home range size; d′ = (4A/π)0.5).


Patterns of Space Use Within the Home Range

In describing how primates use the area within their range, studies of ranging behavioroften report the size of a group’s “core area” (commonly defined as the 50% kernel orMCP home range isopleth). The selection of this cutoff (50%), however, is arbitraryand thus unlikely to be biologically meaningful. To investigate more fully variation inthe intensity with which tamarin groups used different parts of their home range, wemodeled the density of location estimates for each group (using a kernel home rangeestimator, h = 50) as a function of the distance to the center of their home range(defined as the median x- and y-coordinates for each group).

Dynamic Interaction Analyses

To determine whether the three groups influence each other’s movement behavior, wecomputed the mean distance between simultaneous observations of each pair of groups.We then generated a theoretical distribution of this statistic under the null hypothesisthat both groups move independently by repeatedly randomizing each group’s reloca-tion data set with respect to time and compared the mean intergroup distance calculatedfrom these data sets to the observed mean distance. To maintain the same degree oftemporal autocorrelation in the randomized data as in the observed data, our random-ization procedure consisted of shifting the relocation data of one of the groups by arandom number of time steps, forward or backward. The order of the observations thusremained unchanged.

We tested the null hypothesis that neighboring groups move independently of oneanother against the alternative hypothesis that they influence one another’s movementpatterns. This pattern of interaction could be negative, i.e., avoidance (observed meanintergroup distance is large compared to expected mean intergroup distance) or posi-tive, i.e., attraction (observed mean intergroup distance is small compared to expectedmean intergroup distance). The two-sided P-value was calculated as the probability thatthe observed mean distance was as or more extreme (within the top or bottom 2.5%)than the expected distribution of mean intergroup distances we derived from ourresampling procedure.

All statistical analyses were performed using R 2.14.2.

Results

Capture Success and Group Composition

We captured 5 of the 10 adult white-footed tamarins belonging to our three focal groupsbetween May and September, 2009. Four individuals were recaptured. Group mem-bership was highly variable; even in the short duration of our study we observed bothdeaths and group transfers. Before beginning animal capture, we identified three focalgroups. It is not possible to distinguish between male and female white-footed tamarinsbased on visual appearance alone but we counted three adults in group A, four adults ingroup B, and at least three adults in group C. Group A, the first group we captured,consisted of two males and one female. One of the males showed evidence of having


been kept in captivity: His canine teeth were filed down and he had been implantedwith an RFID microchip. Shortly after this initial capture, the two males in group Awere attacked by what we assume was a predator (based on their wounds) and died.Two other adults took their place in the group before the start of systematic datacollection, but toward the end of the study, one of these new individuals either leftthe group or died. We were able to capture only two of the four adults in group B, bothof which were female. Before we started tracking the group’s movements, one of thesefemales left and joined another group: group C. She was replaced in group B by a newadult whose sex we were unable to determine. Group C consisted of the adult femalewe had captured and implanted with an RFID microchip and two other adults ofunknown sex.

Home Range Size and day Range Length

Regardless of the estimator we used, the overall pattern of home range sizes among thefocal groups remained the same: Group C had the largest estimated home range,followed by groups B and A (Fig. 1). There was substantial variation in the estimatesof each group’s home range size depending on the estimation methodwe used, e.g., 40%difference between the smallest and largest estimate for the size of group A’s range; seeFig. 1. Nonetheless, we found significant differences in home range size for each pair ofgroups under all three estimation methods (two sample permutation test, P < 0.001 forall dyads). Despite differences in overall range size, daily travel distances did not differamong the study groups (Kruskal-Wallis H-test, H = 4.50, P = 0.10, N = 63). The meandaily path length for the three groups was 1,946 m ±756 m (Table II).

Patterns of Space Use Within the Home Range

Two of the three groups in this study focused their activity around a single home rangecenter, and the intensity with which they used space decreased as a function of distancefrom this center (see Fig. 2a–c). However, the degree to which this was true varied.Group A’s space use intensity declined steeply and smoothly (Fig. 2a), showing noevidence of a core area that was used differently than other portions of the range. Fiftypercent of group A’s location estimates occurred within 159 m of the center of theirrange, corresponding to an area of ca. 8 ha. In contrast, the intensity with which groupB used space remained relatively high from the center of their range out to a distance of250 m, and then declined sharply (Fig. 2b). This intensely and relatively homoge-neously used area in the center of group B’s range is consistent with the existence of acore area, as traditionally conceived, encompassing ca. 20 ha. Interestingly, the distri-bution of group C’s density estimates shows two distinct peaks and more spread thaneither group A or B. The density curve thus shows comparatively poor fit to the data.Fifty percent of group C’s location estimates fall within 390 m of the center of theirrange, corresponding to an area of 47.9 ha.

Defensibility Index and Range Overlap

Based on these measures of home range size and day range length, all three groups inthe study had defensibility indices substantially >1 (range = 1.52–2.39; see Table II),


Fig. 1 Mean home range size in hectares of three groups of Saguinus leucopus in the Bellavista Forest, Caldas,Colombia, based on 3mo of radio-tracking (September, 2009–December 2009), estimated byminimum convexpolygon (MCP) and fixed kernel (FK) methods. FK is implemented with two smoothing parameters (h = 50,h = LSCV). Note that the utilization distribution calculated using kernel (LSCV) is discontinuous.

Table II Average, minimum and maximum daily path length (m) and defensibility index (DI) for three white-footed tamarin groups inhabiting the Bellavista Forest in Caldas, Colombia

Groups Path length (m)x� SD

Minimum pathlength (m)

Maximum pathlength (m)

Coefficient ofvariation (%)

Defensibilityindex (DI)

A 1975 ± 502 1093 2994 25.44 2.39

B 2191 ± 1050 934 4799 47.92 2.19

C 1671 ± 522 1016 3204 31.26 1.52


the cutoff which has been found to be related to “territoriality” in meta-analyses ofprimate ranging behavior (Mitani and Rodman 1979; although D = 0.98 was found tobe a better cutoff separating territorial from nonterritorial species in Lowen andDunbar’s 1994 meta-analysis). Nonetheless, the degree of range overlap among groupswas substantial (Table III). Depending on the home range estimator used, pairs ofneighboring tamarin groups shared 26–81% of their range.

Dynamic Interaction Analyses

Although they shared large portions of their range, neighboring tamarin groupsspent very little time in close proximity to one another (mean intergroupdistance = 515 m; time groups spent within 200 m of each other: A–B = 8%,B–C = 23%, A–C = 14%). We found that mean intergroup distance was smaller thanexpected based on independent movement patterns. Group C was closer thanexpected to both groups A and B (randomization test: two-tailed P-value < 0.025).Although the results for groups A and B were not within the bottom 2.5% of theexpected distribution of mean intergroup distances we derived from our resamplingprocedure (randomization test: two-tailed P-value = 0.047), the trend was in thesame direction.

Discussion

The home range size estimates produced in this study (95% MCP = 43–97 ha) differstrikingly from previous estimates for groups in the same area (95% MCP = 7.5–11.5ha; Sánchez-Londoño et al. 2009) as well as with the home range estimate for a groupof 11 individuals in a 120-ha secondary forest fragment (17.7 ha, calculated bysumming all the 50 × 50 quadrants visited by the tamarins; Poveda and Sánchez-Palomino 2004). One possible explanation for this discrepancy is that studies relyingsolely on direct observation to describe white-footed tamarin movement have seriouslyunderestimated the species’ spatial needs. In both previous studies, data collection waslimited by the observers’ ability to follow unhabituated tamarins. Poveda and Sánchez-Palomino (2004) reported that they were usually unable to maintain contact with theirfocal group for whole days, which may have led them to underestimate the size of theranges used by their focal groups. Such biases may be pervasive in studies of primateranging, especially if researchers tend to lose track of their focal individuals whengroups enter areas with difficult terrain, or if they are less likely find groups that leavecommonly used areas, i.e., move away from where researchers expect to find them.Most of the white-footed tamarins’ remaining habitat is located in areas wheredifficult topography has restrained the advance of the agricultural frontier. Thedifficulties with conducting observational studies in such areas, and the inabilityto recognize tamarins individually based on appearance alone mean that radio-telemetry and/or GPS tracking may be key tools in future studies of this poorlyknown primate species. However, special attention needs to be paid to the recaptureprocess. In contrast to Savage and colleagues’ experiences with Saguinus oedipus(1993), we were unable to recapture all of the individuals we radio-tagged at the endof our study, despite intense, prolonged efforts. We therefore recommend that in


a

b

c


future studies, researchers incorporate an automated breakaway mechanism in theirharness design, so that transmitters will fall off even if individuals cannot berecaptured. Using absorbable suture material instead of mercerized thread to fit theharness may be a viable solution to this problem. In a recent pilot study using thismethod, harnesses fell off after approximately 2 wk (Poches 2012 pers. comm.).Continued innovation to develop a better transmitter attachment system is needed,and should be a priority in any future studies of small-bodied primates that useremote tracking technology.

The home range size and average daily path length found in this study are within thevalues reported for other tamarin species (Garber 1993). However, our data on white-footed tamarin movement demonstrate that home range size can differ significantly,even among groups living in the same area. The magnitude of the variation in our homerange size estimates depending on the estimation methods we used also serves toillustrate why comparisons across species, sites, and even studies must be made withcaution. Our estimates of home range size differed by up to 40% for the same group,depending on the method of home range estimation we used (Fig. 1). We see the samepattern in our estimates of home range overlap (Table III). MCP estimates are sensitiveto sample size and outliers, while the selection of an appropriate smoothing parameter

Table III Home range overlap (%) between three groups of white-footed tamarins inhabiting BellavistaForest in Caldas, Colombia, calculated using minimum convex polygon (MCP) and fixed kernel (FK)estimation methods

Focal group

A B C

Neighboring group A FK (h = 50) – 33.17 34.26

FK (LSCV) 28.43 26.67

MCP 26.88 26.61.

B FK (h = 50) 49.20 – 56.91

FK (LSCV) 53.33 69.11

MCP 40.52 54.99

C FK (h = 50) 61.44 69.65 –

FK(LSCV) 72.95 61.15

MCP 61.99 81.29

FK is implemented with two smoothing parameters (h = 50, h = LSCV)

Fig. 2 a–c Intensity of Saguinus leucopus group (a) A, (b) B, and (c) C’s space use as a function of distancefrom the home range center. In each figure, the kernel densities estimated for 30 * 30 m quadrats (FK, h = 50)are plotted against the distance of each quadrat from the center of the group’s home range. The solid red linerepresents that best fit obtained by locally weighted scatterplot smoothing (LOESS). The dashed red linerepresents the cumulative density of location estimates. Thus, if value of the dashed line is 0.5 at 500 m fromthe center of a group’s home range (as is approximately the case for group C), this means that 50% of thelocation estimates for this group occurred within 500 m of the center of their home range. All groups lived inthe Bellavista Forest in Caldas, Colombia, and were radio-tracked for a period of 3 mo (September, 2009–December 2009).


(h) is widely recognized as the critical component in kernel density estimation(Kernohan et al. 2001). There is no consensus as to which method is best to estimatethis parameter. In this study, we used least squares cross validation (LSCV), followingbest practice recommendations (Seaman et al. 1999), but for two of our groups, the hvalues produced with this method broke the utilization distribution up into numeroussmall peaks (Fig. 1) that do not reflect a reasonable space use pattern for this species.This has been noted to be a problem when using LSCV with large data sets, i.e., 1000of locations estimates (Kie et al. 2010), so it is interesting that we encountered the sameproblem with our much smaller data sets. To obtain a kernel home range estimate thatproduced a more biologically relevant boundary, we selected the smallest smoothingparameter (h = 50) that produced a contiguous home range boundary for at least onegroup. Kie and colleagues (2010) have suggested that this kind of subjective approachis reasonable, as long as the biological questions are formulated prior to the analysis.However, it poses an obstacle for comparing space use patterns across time andbetween populations and highlights an urgent need for researchers to report more fullythe methods they use when calculating home range estimates and to make their rawmovement data accessible. Online repositories for animal tracking data that facilitatedata archiving now exist, e.g., www.movebank.org. Widespread use of such resourceswould allow researchers and governmental and nongovernmental environmentalorganizations to use data from a variety of sources to assess the movement patternsand space use requirements of target species in a directly comparable manner, and helpthem to make better management decisions for mitigating the negative effects of landuse and environmental change on vulnerable populations.

White-footed tamarins exhibit “territorial” behavior; i.e., they have aggressiveintergroup confrontations (Fuentes et al. 2013; Rueda and Zerda 2009). However, aswith many other tamarin species, including Saguinus fuscicollis (Peres 2000) and S.geoffroyi (Garber 1993), we found a high degree of home range overlap among groups(up to ca. 60–80%). This large degree of range overlap implies that neighboring groupsexploit many of the same resources, despite having ranges that, at least in theory,should be economically defensible. All three study groups have D-indices comparableto those of territorial primate species, i.e., D > 1 (Mitani and Rodman 1979). Contraryto our prediction for a species whose intergroup interactions are known to be aggres-sive, two of the three group dyads (C–A, C–B) show evidence of spatial attraction.They were, on average, significantly closer to one another than would be expected bychance. Although not statistically significant, the trend for the third dyad (A–B) was inthe same direction.

We hypothesize that the pattern of attraction among groups we observed may be theresult of environmental forcing. The landscape that our study groups inhabit has beenhighly transformed by agricultural activities. Based on previous research at this site,Sánchez-Londoño and colleagues (2009) have suggested that the edges of forestfragments represented barriers that white-footed tamarins cannot, or will not cross.Our results show that the matrix of human modified habitat surrounding the patches offorest in our study site did not prevent tamarins from passing from one fragment toanother (Fig. 1). During the course of data collection, we frequently observed tamarinsmoving through habitat transformed by agricultural activities including abandoned,overgrown fields cleared by slash and burn, as has been reported for other Saguinusspp. (Dawson 1979; Sussman 2003). However, it is possible that landscape features


http://www.movebank.org/

may constrain tamarin movement patterns, forcing individuals to use a limited set ofroutes as they move from part of the habitat to another, and thereby decreasing theaverage distance between groups. Alternately, demographic changes within groups mayhave been responsible for this somewhat surprising pattern of intergroup attraction.Two months into the study, group C—which had shown the highest levels of homerange overlap (Table III) and attraction to its neighbors—moved 3 km away from ourstudy area. Group C was a new group that had formed when a female from group B lefther group and started ranging with two, previously unknown individuals. This rangeshift, therefore, may reflect a failure by group C to successfully establish a home rangein the area, and an attempt by them to explore new areas in which to settle. Theextremely high levels of home range overlap between group C and its neighbors (60–80%) may have engendered too much competition to be sustainable in the long term,and shifting might have been a strategy to limit resource competition and avoid theterritorial aggression from established groups (Wauters et al. 1995).

Given the short duration of our study, our ability to make conclusive inferencesabout how tamarin social structure and intergroup relationships shape space usepatterns is limited. Our results, however, have some important conservation implica-tions. As noted previously, Saguinus leucopus currently lives in very fragmentedhabitats and only a very small portion of its range is within a protected area. The highlevels of home range overlap among groups found in this study combined with the highpopulation densities estimated in several forest remnants (up to 149 ind./km2;Roncancio et al. 2011), imply that the few existing white-footed tamarin populationsmay be crowding the last available habitats. If habitats of Saguinus leucopus are, infact, saturated, environmental and government agencies as well as nongovernmentalinstitutions working for the conservation of this species might use this information topromote tamarin habitat restoration in their agendas.

Acknowledgments We thank the regional environmental government authority CORPOCALDAS(Corporacion Autónoma Regional de Caldas) for permission to conduct this research and for financial support.We also thank Luis Soto (Proyecto Titi Foundation) for training in the capture and radio collaring of tamarins,and Asociación de Veterinarios de Vida Silvestre and the staff from Centro de Rehabilitacion de FaunaSilvestre del Oriente de Caldas (CRFSOC) for technical support. We thank Andrés, Efraín, Amilvia, Jose,Willy, and the family Carvajal Betancur for their support during the field work. We thank Oscar Ospina,Nestor Roncancio, Adriana Bilgray, and Oris Acevedo for logistical support; Vanessa Perez, Jesualdo Fuentes,and Egbert Leigh for helpful suggestions; and Ryan Chisolm for statistical advice. We also thank theanonymous reviewers whose comments have improved this manuscript. Funding for this project was providedby the Margot Marsh Foundation, the Wildlife Conservation Society, Fundación Biodiversa Colombia,Colciencias (Programa Jóvenes Investigadores e Innovadores “Virginia Gutierrez de Pineda”), Grupo enConservación y Manejo de Vida Silvestre (Universidad Nacional de Colombia), the Smithsonian TropicalResearch Institute, and the Max Planck Institute for Ornithology. D. Caillaud was supported by NSF grantDEB-0749097 to L. A. Meyers.

References

Buchanan-Smith, H. (1991). A field study on the red-bellied tamarin, Saguinus l. labiatus, in Bolivia.International Journal of Primatology, 12(3), 259–276.

Calenge, C. (2006). The package “adehabitat” for the R software: a tool for the analysis of space and habitatuse by animals. Ecological Modelling, 197(3–4), 516–519.


Cords, M. (2002). Friendship among adult female blue monkeys (Cercopithecus mitis). Behaviour, 139(2–3),291–314.

Cords, M. (2007). Variable participation in the defense of communal feeding territories by blue monkeys in theKakamega Forest, Kenya. Behaviour, 144, 1537–1550.

Dawson, G. A. (1979). The use of time and space by the Panamanian tamarin Saguinus oedipus. FoliaPrimatologica, 31, 253–284.

Defler, T. (2010). Historia natural de los primates colombianos (2nd ed.). Bogotá: Universidad Nacional deColombia. Facultad de Ciencias. Departamento de Biología.

Defler, T. R. (2004). Primates of Colombia. Bogotá: Conservación Internacional.Doncaster, C. P. (1990). Non-parametric estimates of interaction from radio-tracking data. Journal of

Theoretical Biology, 143(4), 431–443.Fuentes, J. A., Zerda-Ordóñez, E., & Muñoz-Durán, J. (2013). Vocal communication of white-footed tamarin

(Saguinus leucopus) in the wild. Caldasia, 35(1), 49–63.Garber, P. A. (1988). Diet, foraging patterns, and resource defense in a mixed species troop of Saguinus

mystax and Saguinus fuscicollis in Amazonian Peru. Behaviour, 105(1–2), 18–34.Garber, P. A. (1993). Feeding, ecology, and behaviour of the genus Saguinus. In A. Rylands (Ed.),Marmosets

and tamarins: Systematics, behaviour, and ecology (pp. 273–295). Oxford: Oxford University Press.Garber, P. A. (1998). One for all and breeding for one: cooperation and competition as a tamarin reproductive

strategy. Evolutionary Anthropology, 5(6), 187–199.Garber, P. A., Encarnacion, F., Moya, L., & Pruetz, J. D. (1993). Demographic and reproductive patterns in

moustached tamarin monkeys (Saguinus mystax)—implications for reconstructing platyrrhine matingsystems. American Journal of Primatology, 29(4), 235–254.

Heymann, E. W. (2000). Spatial patterns of scent marking in wild moustached tamarins, Saguinus mystax: noevidence for a territorial function. Animal Behaviour, 60(6), 723–730.

IUCN (2011). IUCN red list of threatened species. Version 2011.2. (Accessed August 6, 2011).Kernohan, B. J., Gitzen, R. A., & Millspaugh, J. J. (2001). Analysis of animal space use and movements. In J.

J. Millspaugh & J. M. Marzluff (Eds.), Radio tracking and animal populations (pp. 125–166). San Diego:Academic.

Kie, J. G., Matthiopoulos, J., Fieberg, J., Powell, R. A., Cagnacci, F., Mitchell, M. S., et al. (2010). The home-range concept: are traditional estimators still relevant with modern telemetry technology? PhilosophicalTransactions of the Royal Society of London. Series B, Biological Sciences, 365(1550), 2221–2231.

Lazaro-Perea, C. (2001). Intergroup interactions in wild common marmosets, Callithrix jacchus: territorialdefence and assessment of neighbours. Animal Behaviour, 62, 11–21.

Lowen, C., & Dunbar, R. I. M. (1994). Territory size and defendability in primates. Behavioral Ecology andSociobiology, 35(5), 347–354.

Mendes Pontes, A., &Monteiro da Cruz, M. (1995). Home range, intergroup transfers, and reproductive statusof common marmosets Callithrix jacchus in a forest fragment in North-Eastern Brazil. Primates, 36(3),335–347.

Minta, S. (1992). Tests of spatial and temporal interaction among animals.Ecological Applications, 2(2), 178–188.Mitani, J. C., & Rodman, P. S. (1979). Territoriality: the relation of ranging pattern and home range size to

defendability, with an analysis of territoriality among primate species. Behavioral Ecology andSociobiology, 5, 241–251.

Mohr, C. O. (1947). Table of equivalent populations of north American small mammals. American MidlandNaturalist, 37(1), 223–249.

Morales, J. M., Moorcroft, P. R., Matthiopoulos, J., Frair, J. L., Kie, J. G., Powell, R. A., et al. (2010). Buildingthe bridge between animal movement and population dynamics. Philosophical Transactions of the RoyalSociety of London. Series B, Biological Sciences, 365(1550), 2289–2301.

Morales-Jiménez, A., Vejarano, S., Rodríguez, C., Ospina, O. (2008). Programa Nacional para laConservación de la Especie Endémica de Colombia Tití Gris (Saguinus leucopus), Bogotá.

Müller, K., & Schildger, J. (1994). Capture and radio-telemetry of masked titi monkeys, Callicebus personatusmelanochir. Neotropical Primates, 2(4), 7–8.

Nams, V. O. (2006). Locate III user’s guide. Tatamagouche: Pacer Computer Software.Nunn, C. L., & Dokey, A. T. (2006). Ranging patterns and parasitism in primates. Biology Letters, 2, 351–354.Peres, C. A. (2000). Territorial defense and the ecology of group movements in small-bodied neotropical

primates. In S. Boinski & P. Garber (Eds.), On the move: How and why animals travel in groups (pp.100–123). Chicago: University of Chicago Press.

Poveda, K., & Sánchez-Palomino, P. (2004). Habitat use by the white-footed tamarin, Saguinus leucopus: acomparison between a forest-dwelling group and an urban group in Mariquita, Colombia. NeotropicalPrimates, 12(1), 6–9.


R Development Core Team. (2011). R: A language and environment for statistical computing. Vienna: Rfoundation for Statistical Computing.

Raboy, B. E., Canale, G. R., & Dietz, J. M. (2008). Ecology of Callithrix kuhlii and a review of easternBrazilian marmosets. International Journal of Primatology, 29(2), 449–467.

Revilla, E., & Wiegand, T. (2008). Individual movement behavior, matrix heterogeneity, and the dynamics ofspatially structured populations. Proceedings of the National Academy of Sciences of the United States ofAmerica, 105(49), 19120–19125.

Roncancio, N. J., Rojas, W., & Defler, T. (2011). Densidad poblacional de Saguinus leucopus en remanentesde bosque con diferentes características físicas y biológicas. Mastozoología Neotropical, 18, 105–117.

Rueda, L. E., & Zerda, E. (2009). Comunicación Vocal de un Grupo de Tití Gris (Saguinus leucopus) enMariquita, Colombia. Neotropical Primates, 16(1), 37–43.

Sánchez-Londoño, J., Arias, A., Barragán, K., & Montoya, M. (2009). Evaluación del estado de la poblacióndel tití gris, Saguinus leucopus, en el área de influencia del proyecto trasvase Guarinó y propuesta deestrategias para su conservación. Final report. Colombia: Asociación de Veterinarios de Vida Silvestre,Colombia.

Savage, A., Giraldo, L. H., Blumer, E. S., Soto, L. H., Burger, W., & Snowdon, C. T. (1993). Field techniquesfor monitoring cotton-top tamarins (Saguinus oedipus oedipus) in Colombia. American Journal ofPrimatology, 31(3), 189–196.

Seaman, D. E., Millspaugh, J. J., Kernohan, B. J., Brundige, G. C., Raedeke, K. J., & Gitzen, R. A. (1999).Effects of sample size on kernel home range estimates. Journal of Wildlife Management, 63(2), 739–747.

Stevenson, P. R., Guzman, D. C., & Defler, T. R. (2010). Conservation of Colombian primates: an analysis ofpublished research. Tropical Conservation Science, 3(1), 45–62.

Sussman, R. W. (2003). Primate ecology and social structure, vol. 2: New World Monkeys (revised firstedition). Boston: Pearson Custom Publishing.

Waser, P. M. (1976). Cercocebus albigena—site attachment, avoidance, and intergroup spacing. AmericanNaturalist, 110(976), 911–935.

Wauters, L. A., Lens, L., & Dhondt, A. A. (1995). Variation in territory fidelity and territory shifts among redsquirrel, Sciurus vulgaris, females. Animal Behaviour, 49(1), 187–193.

White, G. C., & Garrott, R. A. (1990). Analysis of wildlife radio-tracking data. San Diego: Academic.Wich, S. A., & Nunn, C. L. (2002). Do male ‘loud calls’ function in mate defense? A comparative study of

long-distance calls in primates. Behavioral Ecology and Sociobiology, 52, 474–484.Worton, B. J. (1989). Kernel methods for estimating the utilization distribution in home range studies.

Ecology, 70(1), 164–168.


Spatiotemporal...AbstractIntroductionMethodsStudy AreaCapture and Radio-TaggingData CollectionHome Range Estimation and ComparisonHome Range OverlapAverage Daily Path LengthDefensibility IndexPatterns of Space Use Within the Home RangeDynamic Interaction Analyses

ResultsCapture Success and Group CompositionHome Range Size and day Range LengthPatterns of Space Use Within the Home RangeDefensibility Index and Range OverlapDynamic Interaction Analyses

DiscussionReferences

Spatiotemporal Interactions Among Three Neighboring...

Documents

Transcript of Spatiotemporal Interactions Among Three Neighboring...