Population status of black and white colobus monkeys (Colobus guereza) in Kakamega Forest, Kenya: are they really on the decline?

Peter J. Fashing Department of Ecology, Evolution, and Environmental Biology, Columbia University, 1200 Amsterdam Avenue, New York, NY 10027, U.S.A. E-mail: [email protected] Received 11 October 2001. Accepted 11 January 2002 Eastern black and white colobus monkeys, or guerezas (Colobus guereza), are among the few that have traditionally been regarded as not being adversely affected by habi- tat degradation. This view was recently challenged by von Hippel et al. (2000) who, using data from short-term censuses in 1992 and 1998, reported a striking decline in guereza density over a six-year period of light to moderate degradation at Isecheno study site in the Kakamega Forest, Kenya. In this paper, I present evidence from my own more intensive study during the same period that suggests that the guereza population at Isecheno is actually quite robust and may in fact be increasing. I provide evidence to suggest that the census methods adopted by von Hippel and his colleagues are prone to overestimating density and that the decline in guereza density that they reported probably did not occur. My study suggests that brief censuses based on group counts over a given area, even when conducted by multiple observers, are not sufficient for accurately determining primate distributions and densities in environments. Data on distribution and density play a critical role in the development of conservation strategies and it is therefore important that these data be relatively accurate if biologists are to make informed conservation decisions. Key words: population density, census, block method, group count method, birth rate, interbirth interval, forest degradation, conservation.

INTRODUCTION reported to reach extraordinarily high densities in Most primate populations today face ongoing small East African forest fragments where few habitat disturbance, yet not all species respond to other primate species exist or are absent (Schenkel disturbance the same way. While many primate & Schenkel-Hulliger 1967; Leskes & Acheson 1971; species experience declines in population density Rose 1978; Dunbar 1987). These studies suggest when their are disturbed, there are that guerezas are particularly well adapted to life several that do not and these flexible species will in disturbed forests, though the ecological factors generally require less conservation attention that allow guerezas to flourish in these forests are (Johns & Skorupa 1987; Cowlishaw & Dunbar not entirely clear (Oates 1977, 1994; Johns & 2000). Conservation planners must therefore Skorupa 1986). consider variation among species in the ability to The traditional view that guerezas thrive in withstand disturbance if they are to make optimal disturbed areas has recently been challenged by use of the limited funds and personnel available von Hippel et al. (2000) who provide evidence that for conservation efforts. a guereza population in the Kakamega Forest, Eastern black and white colobus monkeys, or Kenya, experienced a striking decline in density guerezas (Colobus guereza), have traditionally been over a six-year period during which the forest was regarded as one of the few species whose popula- degraded by human activity. Over a two-month tion density is not adversely affected by habitat period in 1992, von Hippel (1996) counted 18 degradation. In fact, studies in both Kibale Forest, guereza groups in the Isecheno study area at Uganda and Budongo Forest, Uganda, have Kakamega, and calculated the population density demonstrated that guerezas exist at higher densi- to be 20.8 groups/km2. After returning to Isecheno ties in selectively logged areas than in unlogged for a one-day sweep census of the guereza popula- areas (Skorupa 1986; Plumptre & Reynolds 1994; tion in 1998, von Hippel et al. (2000) reported that Struhsaker 1997). Guerezas have also often been the original population of 18 groups had been

37(2): 119–126 (October 2002) 120 African Vol. 37, No. 2, October 2002 reduced to 12 groups (14.6 groups/km2) and that most of these losses had occurred in the eastern half of the study site where the number of groups had dropped from seven to two. Von Hippel et al. (2000) attributed this apparent reduction in guereza density to the degradation of their habitat by humans exploiting the forest for a variety of resources. While von Hippel et al. (2000) provide a timely description of the conservation threats facing the Kakamega Forest, their conclusion that habitat degradation has taken its toll on the guereza pop- ulation at Isecheno appears to be unfounded. In this paper, I provide long-term data from my own more extensive study that suggest that despite ongoing habitat degradation, the guereza popula- tion at Isecheno is quite robust. Guerezas at Isecheno exist at a high population density and have high birth rates, short interbirth intervals, and apparently high infant survival rates relative to other well-studied African colobine populations for which similar data are available. My results suggest that brief censuses, even Fig. 1. Isecheno study site in the Kakamega Forest, when conducted by multiple observers, are not western Kenya. sufficient to determine primate distributions or densities in forested areas. Given the importance study site. Three diurnal primate species, Colobus of distribution and density data in devising guereza, Cercopithecus ascanius, and C. mitis, are reg- conservation initiatives (Ganzhorn et al. 1996/97; ularly found at Isecheno, while Papio anubis are oc- Plumptre et al. 2002), it is critical that such data are casional visitors. reliable if the limited budgets and personnel avail- I conducted my research over a five-year period: able to conservation initiatives are to be used in July 1993, November/December 1995, Novem- wisely. ber 1996 – March 1998, and August 1998. My study therefore almost completely overlaps and fills in METHODS the spaces between von Hippel’s two-month study in 1992 and his team’s one-day census in Study site and duration 1998. Over the course of the study, I amassed more I conducted my research on guerezas at than 3000 hours of observation on guerezas. Isecheno study site in the Kakamega Forest, west- Group distribution and density estimation ern Kenya (Fig. 1). The most recent estimate based on satellite imagery shows that indigenous forest Data collection at Kakamega covers 101 km2,86km2 of which lies I used data from long-term research on home in the block that contains Isecheno (Brooks et al. range size and overlap (Struhsaker 1981) to 1999). My study area at Isecheno covered the cen- compute guereza densities at Isecheno. These data tral ~64 % of von Hippel et al.‘s (2000) 0.82 ha were collected on five study groups (O, T,GC, ML, study area. Light to moderate habitat degradation BS) over a one-year period towards the end of the has occurred in much of the study area, with the study (March 1997 – February 1998). During this most intensive disturbance occurring in the west- period, all-day dawn-to-dusk follows were ern half (von Hippel et al. 2000). An irregular grid conducted on 60 days for O Group, 59 days for T system of trails passes through much of the study Group, 23 days for GC Group, 22 days for BS area at intervals of 50–150 m for the north–south group, and 21 days for ML group (Fashing 2001a). trails (M-6 to M+5) and 200–350 m for the Additional data on the ranges of other groups, east–west trails (A,B,C) (Fig. 2). This trail system fa- which overlapped those of the five main study cilitates observational research on at the groups, were collected opportunistically during Fashing: Status of black and white colobus monkeys in Kakamega Forest, Kenya 121

Fig. 2. Guereza group distribution at Isecheno during my one-year study of ranging patterns in 1997/98 and in von Hippel et al.’s (2000) one-day sweep census in 1998. Groups in my study are indicated with letters, while groups sighted by von Hippel et al. are indicated with solid triangles. Trails are labelled with bold and italic lettering. Dashed lines represent regions outside my study area that were surveyed by von Hippel et al. this period, most often during encounters with number of quadrats used by study groups and one of the main study groups. only two non-study groups was divided by three, Movements by members of each study group and so forth. The values for each category of and the locations of groups they encountered quadrat were then summed to produce an were plotted on a modified version of a map of the adjusted home range size for the five study groups study site created by M. Cords in 1989 (Fashing combined. I then divided the adjusted home 2001a). Group ‘center of mass’ (Cords 1987; range size by 5 to produce an average adjusted Butynski 1990) and the pattern of movement home range size. Finally, I divided 1 by the average between consecutive centres of mass were plotted adjusted home range size (in km2) to produce a at half-hourly intervals (Fashing 2001a). Individ- density value of groups/km2. ual movements within the study groups were The description of the block method provided generally easy to monitor since group spread above can be condensed into the mathematical within guereza groups is usually quite small formula: (Fashing & Cords 2000). 1 D = (EVA++++ /2345 VB / VC / ...) / Data analysis Ranging data were analysed using the ‘block where D = density of groups; E = area used only method’ (Struhsaker 1981; Chapman et al. 1988; by study groups (in km2); VA = area used only by Whitesides et al. 1988; Fashing & Cords 2000). A study groups and one other group (in km2); VB = grid of 0.25 ha quadrats was superimposed over a area used only by study groups and two other map of the home ranges of the five study groups. groups (in km2); VC = area used only by study Quadrats of range overlap with non-study groups groups and three other groups (in km2). were identified and divided into categories based Because the block method uses data on the rang- on the number of non-study groups which shared ing patterns of individually recognized groups, each quadrat with at least one study group. The it is the method that most closely approximates total number of quadrats used only by study the ‘true’ density of in a given area groups was divided by one, the total number of (Struhsaker 1981; Fashing & Cords 2000). It yields quadrats used by study groups and only one particularly accurate results when applied to non-study group was divided by two, the total long-term data on the ranging patterns of multiple 122 African Zoology Vol. 37, No. 2, October 2002

Table 1. Infant birth dates and infant survival data for the 11 females in the three groups for which group composition was intensively monitored throughout the study.

Female Group Date gave birth1 Infant still alive at end of study?

D’arcy O 3 November 1997 Yes Saffron O 29 December 1996 Yes Veruca Salt O 13 March 1997 Yes TF1 T 10 July 1997 Yes TF2 T 3 June 1997 and No 17 March 1998 Yes TF3 T 10 July 1997 Yes TF4 T 10 August 1997 Yes TF5 T 2 November 1997 Yes Dolores GC2 6 Jaunuary 1997 Yes Harriet GC Did not give birth Yes Kelley GC 16 March 1998 Yes

1Birth dates listed here are accurate to within seven days or less of when an infant was actually born. 2A fourth female was present in GC group at the beginning of the study but disappeared soon thereafter. groups at a given study site (Struhsaker 1981; RESULTS Fashing & Cords 2000). However, for comparative purposes, I also estimated density using the Distribution of groups and population ‘group count method’ (i.e. divided the number of density groups regularly sighted in the study area by the The approximate epicentres of the home ranges size of the study area), as in von Hippel (1996) and of the five main study groups and the locations von Hippel et al. (2000). Unlike the block method, where seven non-study groups were regularly the group count method does not take into sighted are depicted on a map of the Isecheno trail account home range size or the amount of home system (Fig. 2). Several other groups were sighted range overlap between groups when computing once or twice in the study area as well but are not density. included on this map since they may have been temporary visitors entering the study area to gain Reproductive patterns access to eucalyptus or , food sources that Data collection groups occasionally travelled long distances to Data on group composition were collected exploit (Fashing 2001a,b). The approximate loca- opportunistically over a 17-month period from tions of the 12 groups von Hippel and his November 1996 to March 1998. In the three most colleagues detected in their 1998 census (of a larger intensively monitored groups (O, T, GC), data on area) are plotted in Fig. 2 as well for comparative infant births and deaths were collected for each purposes. Of the 12 groups that I regularly female throughout this study period. observed between trails M–6 and M+5, six were found west of M and six were found east of M. Data analysis Clearly, von Hippel et al. (2000) failed to detect I calculated annual birth rate (B) with the most, or even all, of the groups living between M formula: and M+5. This oversight during a one-day census is not surprising considering the greater distance ()(i 12 ) B = between census trails and lower level of habitua- ()()df tion of guerezas in the eastern half of the study where i is the number of infants born over the site. course of the study, d is the duration (in months) of The quadrats entered by each of the five study the study, and f is the number of females studied. groups and the patterns of range overlap between Interbirth interval (I) was calculated as the total these groups and non-study groups are pictured adult female months divided by the total number in Fig. 3. Based on these ranging data, the block of infants born during the study period (Siex & method yields a ‘true’ density of 11.5 groups/km2. Struhsaker 1999). By way of comparison, the group count method, Fashing: Status of black and white colobus monkeys in Kakamega Forest, Kenya 123

Fig. 3. Quadrat use by study groups (T, O, GC, ML, BS) and non-study groups (indicated by •). Routes used by groups to get to the quadrats in the lower right corner from other parts of the study area are unknown. using data from Fig. 2, yields a density of November 1997. 23.1 groups/km2, a density twice as large as that Six individuals disappeared from the three most obtained when home range size and overlap are intensively monitored groups during the study. taken into consideration. Three adult males and one large juvenile female disappeared from T group, most likely transfer- Birth rate, interbirth interval, and ring to groups outside the study area. One infant emigration/death rate (TF2’s first infant) also disappeared from T group Ten of the 11 females present throughout the and is believed to have died. Lastly, one visibly ill study in the three most intensively monitored adult female in GC group disappeared early in the groups (O, T, GC) gave birth during the main study and is believed to have died. No individuals 17-month study period (Table 1). All but one of immigrated into the three groups during the these infants survived until the end of the study. study. Since 11 individuals were born and only six The one female, TF2, whose infant disappeared individuals disappeared, the number of individu- during the study gave birth again in March 1998, als in the three most intensively monitored groups approximately eight months after she lost her increased from 28 to 33 over the course of the infant. study. Birth rate over the study period was 0.71 births per female year. Interbirth interval estimated over DISCUSSION the same period was 17 months. This value is consistent with my observation that a female in Limitations of estimating forest primate O group, D’arcy, with one infant estimated to be density using short-term data 4–6 months old when the study began in Novem- My results demonstrate the problems inherent ber 1996, gave birth to a second infant in early in calculating primate densities based on group 124 African Zoology Vol. 37, No. 2, October 2002 counts over a short period and without regard to results also suggest that a longer study not taking patterns of home range size and overlap. Using into account home range size and degree of home data collected during a one-day sweep census in range overlap provides a more complete list of the 1998, von Hippel et al. (2000) overestimated groups entering a study area, but is even less accu- guereza density by 27 % despite failing to detect rate at estimating densities than brief sweep most of the groups in the eastern half of Isecheno. censuses. Thus, the group count method appears This paradox of overestimating density despite to be a poor means of estimating forest primate undercounting groups can be explained by the densities. fact that von Hippel et al. did not consider the How can forest primate densities be more accu- ranging patterns of the groups they detected. rately estimated during short-term studies? In Without adequate ranging data, von Hippel et al. situations where only a short period is available greatly underestimated the area actually used by for primate censusing, line transect censuses are guereza groups at Isecheno. generally considered to be the method of choice. The degree of von Hippel et al.‘s overestimate However, it should be noted that even line- would have been much greater had they detected transect censuses must be undertaken repeatedly all of the groups in their study area. This point is over a period of several months or more if made particularly clear by the fact that when I reasonably accurate density estimates are to be used the group count method to estimate density achieved (Struhsaker 1981; Chapman et al. 1988; for the 12 groups regularly sighted in the study Whitesides et al. 1988; Brugiere & Fleury 2000; area during my long-term research, the density Fashing & Cords 2000). estimate I obtained (23.1 groups/km2) was two times greater than the ‘true’ density (11.5 groups/ Is the guereza population increasing at km2) calculated via the block method. Thus, using Kakamega? complete group counts to estimate primate den- My evidence that use of the group count method sity in the absence of ranging data can result in can result in large density overestimates suggests massive overestimates. that von Hippel (1996) greatly overestimated This point might explain why von Hippel (1996) guereza density in 1992 and that the Isecheno produced a much higher density estimate in 1992 guereza population may be increasing rather than than in 1998. Because he was at Isecheno for nearly declining. Patterns of female reproduction during two months in 1992, von Hippel was far less likely my long-term study also suggest that the Isecheno to have missed groups than during his team’s guereza population is robust and possibly increas- one-day census in 1998. Since the group count ing. The annual birth rate of 0.71 infants per female method yielded a 101 % overestimate when year at Isecheno is higher than the rates for all applied to my long-term data on group distribu- other African colobine populations for which the tion, it seems reasonable to infer that von Hippel’s relevant data have been published, including 1992 estimate of 20.8 groups/km2 may represent a guerezas at Kibale (0.6: Oates 1974) and red large overestimate as well. Assuming the group colobus monkeys at several sites (0.27–0.43: Jozani, count method produced a similar level of error for , Siex & Struhsaker 1999; 0.49: Kibale, von Hippel in 1992 as for me in 1997/98, the actual Uganda, Struhsaker & Pope 1991; 0.50–0.58: Tana density in 1992 was probably closer to 10–11 River, Kenya, Marsh 1978; Decker 1989). The birth groups/km2. If this inference is correct, then the rate for guerezas at Isecheno is also higher than population increased, not decreased, over the the rates for most well-studied cercopithecine six-year period between von Hippel’s censuses. populations (Andelman 1986). The fact that 10 of This conclusion would be consistent with the fact 11 infants survived through the end of the study that neither guenon researcher M. Cords nor I saw period is another testament to the health of the physical evidence of a guereza population crash Isecheno guereza population. despite the fact that Cords spent 2–3 months each Interestingly, the reproductive patterns of year and I spent more than 19 months at Isecheno guerezas at Isecheno bear a striking resemblance between 1992 and 1998 (Fashing & Cords 2000). to those of the red howler monkey (Alouatta In conclusion, my results suggest that a one-day seniculus) population at Hato Masaguaral, census, even by three observers working simulta- Venezuela. The birth rates and interbirth intervals neously, is simply too brief to accurately measure for these two populations are nearly identical (B = forest primate distributions and densities. These 0.73 infants per female year and I = 17 months at Fashing: Status of black and white colobus monkeys in Kakamega Forest, Kenya 125

Hato Masaguaral) and infant survival rates for Consortium in Evolutionary Primatology. I am both appear to be high as well (Crockett & Rudran grateful to the Kenyan government for permission 1987). Based on these reproductive parameters, to conduct research in Kenya, and the Zoology Crockett & Rudran (1987) concluded that the Department at the University of Nairobi for local howler population at Hato Masaguaral appeared sponsorship. to be increasing in size. The fact that the reproduc- tive parameters of guerezas at Isecheno mirror REFERENCES those of howlers at Hato Masaguaral suggests that ANDELMAN, S.J. 1986. Ecological and social the guereza population at Isecheno may also be determinants of cercopithecine mating patterns. In: increasing. Also suggestive that the Isecheno pop- Ecological Aspects of Social Evolution: Birds and ulation is increasing is the fact that the number of , (eds) D.I. Rubenstein & R.W. Wrangham, individuals in the three most intensively moni- pp. 201–216. 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