Estimating population density of primates in the Jama-Coaque Reserve Brian Whyte Spring 2015 Intern
INTRODUCTION Deforestation is one of the most pressing concerns for the ecological preservation of Ecuador today. Having lost around 50% of its original forests, Ecuador has the highest deforestation rate in all of South America, losing 1.7% of its forests each year (Mosandi et al. 2008). While this rate considers all forest types in Ecuador, some forest types are in more danger than others. On the coast of Ecuador, deforestation has been particularly excessive, leaving only 2% of the neotropical rainforests to remain. As these forests fade, so do their impressive animal diversities, which include the unique New World monkeys west of the Andes. On the western side of the Andes in Ecuador, two primate species are common: the mantled howler monkey (Alouatta palliata ssp. aequatorialis) and the white-fronted capuchin (Cebus albifrons ssp. aequatorialis). Research on these species in this region has been scarce, with only enough work to suggest we are in danger of losing them. White-fronted capuchins are of most concern. The IUCN red list considers C. a. aequatorialis to be critically endangered, largely as a result of losing 80% of its habitat in just the last three decades (Cornejo & de la Torre, 2008). As for A. p. aequatorialis, this species is considered vulnerable, but has been doing well in response to habitat loss due to its folivorous diet that does not depend on large, undisturbed forest patches. The average home range for A. palliata is only 28.75 ha (Estrada 1982). Despite this, there is concern for this species if habitat loss continues (Cuarón et al. 2008). The ideal scientific response to the challenge of conserving these primates is to monitor their population and figure out what they need to stay alive. This can be summarized as a four step process, where research questions are prioritized in the following order (suggested by Cowlishaw & Dunbar 2000): 1. Is the population declining and what is the evidence for that decline? 2. Are the other known populations of this species also in decline? 3. Could the decline lead to extinction? 4. What appears to be contributing to this decline? For the primate species located at the Jama-Coaque Reserve in Manabi, Ecuador, we are in the first phase, figuring out the density of our primate populations to see if they are in danger as other research suggests (Jack & Campos 2012, Cuarón et al. 2008). Therefore, a new long term survey on mantled howler monkeys and whitefronted capuchins has begun. The most accepted method for a survey to obtain population density of primates is line transect sampling (Sterling et al. 2013), but this method is not appropriate for the dense and often steep terrain in our reserve, so an alternative design is used. Here a method of systematic trail hikes for a total-count survey is used along with point transect distance sampling of howler calls to estimate population densities. The total-count survey estimates the group size and density of both howlers and capuchins through group sightings. The point-transect distance sampling (Dacier et al. 2009, Brockelman & Srikosamatara 1993, Whittaker 2005) estimates howler group density by detecting their territorial calls and establishing a detection function that extrapolates population density using Distance software (Thomas et al. 2010). Along with these analysis, data on monkey locations through sightings and point transect sampling is used for a mapping analysis that provides its own howler and capuchin group count.
METHODS Data Collection Data collection began on March 30 th, 2015 and ended after five weeks (on April 30 th ). This was during the wet season in Ecuador, when rainfall occurs most frequently throughout the year. There were four trail systems used in this study. Each day a trail system was hiked so four days of each week were spent hiking. Each trail system is a loop that begins and ends at the same point (the bamboo house at the center of the reserve) and on weeks 3 and 5 each trail system was walked in the reserve direction so as to test if there is no bias in the data based on which way the trail is walked. There was no data collected on the second week because of a foot injury I had, and the fourth week is considered incomplete because one of the trail systems was not covered. Thus, a total of 73.25 hours was spent surveying over 15 survey days. Survey Design Along the four major trail systems that covered our 422 ha reserve were placed 42 sound sampling points spaced 300ft from each other. Surveys entailed hiking these trail systems typically from 5:30am-11:00am, stopping at sound points for five minutes each, and recording a bearing and a distance toward any audible howler calls. Bearings were obtained with a compass, and distances were estimated into three classes: Near (<100m), Far (<300m) and Very Far (300-500m or more). While howler calls can travel across 1 km, calls at distances that extreme were quiet and difficult to get a bearing on, so only calls estimated to be within 0-500m were accounted for. Whether the calls involved one or multiple males was recorded as well, for sounds from single males cannot guarantee the presence of a group. During this sound sampling, any monkeys visible from the trail or reachable off trail were tracked down and their group data was recorded. Data recorded for monkey sightings included: GPS location, monkey species, time of day (begin-observing time & end-observing time), group count, age classes, sexes, identifiable features, and behaviors. Age classes consisted of three categories: adults, juveniles, and infants. Adults were monkeys of the largest size with visible, mature genitalia. Juveniles were about half to a third the size of adults, often found clinging to their mothers but also capable of climbing in the canopy on their own. Infants were a third to a quarter the size of adults, and were always clinging to their mothers. Identifiable features of individual monkeys (e.g. warts, boils, patches of bare skin) were recorded to distinguish groups during possible repeated sightings. Also groups with the same demography found in the same area repeatedly were considered the same group sighted multiple times. Once a group was sighted and initial data recorded, at least 20 minutes were spent observing behaviors and recounting the group for accuracy. Mapping Analysis Using GPS locations of monkey sightings in conjunction with estimated locations of howlers via distance and bearing from sampling points, maps displaying the estimated location of groups were drawn up for each survey week. Using QGIS (v.2.6.1), GPS points from monkey sightings and sound points were imported into a map of the reserve, and estimated locations from bearing + distance of sounds were manually input using the Azimuth & Distance QGIS plug-in. Maps were separated by week because it was too difficult to distinguish groups when looking at all four weeks of data on one map. It was too likely for groups seen or heard multiple times to be considered different groups over weeks of time. Sightings or sounds located near each other (100m) and recorded on the same day were considered evidence of only one group. Sightings and sounds separated slightly farther away from each other (100-200m) but recorded 1-3 days apart were considered evidence for only one group as
well. Estimated locations of sounds produced by only one male were not considered evidence for a group unless sightings or other sounds with evidence of a group shared the same estimated location. Distance Analysis A detection function is calculated using the probability of finding monkeys at points given their distance from these points. Once a detection function is established, it can extrapolate the density of monkeys across an entire survey area, and this is most easily done using the Distance v.6.2 software. Multiple models exist for establishing the detection function based on this distance-from-points data, so multiple models were used to analyze the sound sampling data, and the model with the lowest AIC score (Akaike s Information Criterion) was chosen as the best fit, unless it reported unreasonable or impossible results (e.g. a 100% detection probability, incredibly large coefficients of variation, etc.). All sound sampling data across the four survey weeks was used as one data set for this analysis. RESULTS Monkey Sighting Data A total of 26 sightings occurred, 23 of which were howlers, and 3 which were capuchins (Fig 1). From these 26 sightings, 136 monkeys were recorded, 90.5% of which were howlers (i.e. 123 howlers total). Most monkeys were sighted on the largest trail system (34.6% found on Aguas Frias -> Cerro Segrado). Accounting for possible repeated sightings and disregarding sightings of lone males and mothers, there were an estimated 15 separate groups of howlers observed in the 23 sightings of howlers. Average group size of howlers was 7.73 per group, ranging from a minimum of 4 to a maximum of 16 per group. Howler groups were primarily adults (77.8%), and those adults were primarily female (37.3%) (Table 1). As for capuchins, around 9-13 were sighted. An exact number is not given because it is possible that 4 capuchins were counted twice. Demography data for capuchins was not reported here because so few demography data were recorded.
Figure 1: QGIS Map of the Jama-Coaque reserve with all sound points (white dots), howler sightings (orange dots) and capuchin sightings (purple dots) displayed. Despite recording 26 sightings, 26 colored dots are not labeled on this map because some points had multiple sightings at different times. Table 1: Demography and other group data from the current study compared to the same data from past surveys at the Jama-Coaque reserve. Current Study Past Studies Age Class Sex (adults) Age Class Sex (adults) Adult 77.8% Male 37.3% Adult 74.5% Male 34.0% Juvenile 12.8% Female 29.6% Juvenile 5.8% Female 45.4% Infant 9.40% Unknown 32.9% Infant 17.6% Unknown 20.4% Unknown 0 Unknown 1.9% Group count 15 Group count 6 Group size 7.73 Group size 8.5 Population size 116 Population size 51 Mapping Analysis Based on the final maps created in QGIS (Fig 2), an average of 14 groups can be estimated, considering the group counts from weeks 1, 3, and 5 (since week 4 was incomplete). The most groups were found during week
5 (16 groups). Groups estimated to be just outside the boundaries of the reserve were still counted because their home ranges might overlap with the reserve
.
Figure 2: QGIS maps of howler and capuchin groups found in the Jama-Coaque reserve each survey week. The light gray lines are the trail systems of the JCR. Orange dots are howler sightings. Purple dots are capuchin sightings. Dotted lines are bearings leading to yellow triangles indicating estimated locations of howler calls, recorded from the white dot sound points. Yellow circles are estimated locations of groups (using multiple markers to prove the presence of a group). And gray circles are locations of loner males. An estimate of group count is reported as well for each week. Distance Analysis The model for the detection function with the best fit (i.e. lowest AIC score) was a negative exponential key function with a simple polynomial series expansion (AIC = 893.85). The population density extrapolated from the detection function (Fig. 3) was 0.036 groups/ha with a 95% confidence interval of 0.0016, suggesting around 15.1 groups in our 422 ha reserve (Table 2).
Figure 3: Detection function (orange line) fit by a negative-exponential model using sound sampling distance data. Green bars are the distance intervals recorded, multiplied by the inverse of the amount of monkeys detected at that distance. Numbers above the blue bars are the amount of monkeys detected at that distance. Table 2: Estimates of howler group count from various sources. Estimates from sightings, mapping analysis, and the negative-exponential model all use data from this present study. The fourth estimate, calculated from home range data, uses the average home range of mantled howler monkeys (A. palliata) suggested in Estrada 1982, which is 28.75 ha. Estimates from: Only sightings 15 Num. of howler groups in the JCR Mapping analysis (sound sampling + sightings) 14 (mean of week 1, 3, and 5) Negative-exponential model of detection function 15.1 Home range data (Estrada, 1982) 14.8 DISCUSSION Despite being unable to devote the same or more hours towards monkey surveying as past survey efforts in the JCR, I estimate to have found more than twice the amount of howlers as past research efforts. This could be because past efforts have claimed to recognize groups across multiple sightings, thus clumping more sightings together as single groups. Identifiable features weren t always found during this current survey, and demography data didn t often match demography from other groups sighted in the same area, so less sightings were clumped together as single groups. The evidence which justified the clumping of sightings in past surveys is vague and uncertain.
When comparing demography data with past surveys though, it appears that more infants have grown into juveniles since the last time the monkeys were surveyed (in July 2014), and slightly more juveniles have grown into adults. This shift in age class structure, as well as the difference in population size between surveys (from 51 howlers to 116) provides a rough suggestion that the howler population is increasing. While the white-fronted capuchins were witnessed three times, not enough data was collected from these sightings to make claims on their population density or demography. As for howlers, all sources both in this study and in the literature report a howler group density of about 14-15 groups in our reserve. The convergence of these separate sources onto such a small range of possibility gives support for the accuracy of the howler density estimated in this current survey. But some methods used in this current survey (mapping and distance analysis) had some flaws which need to be checked if the methodology in this paper is to be reliable and continue for a long time. For instance, using data from sound sampling and sightings to map locations of monkey groups is at the moment an unreliable way of estimating group density. There is no objective demarcation between single or multiple groups when multiple points (of sightings or sounds) are clumped on a map. Whether sightings and estimated locations of calls placed near each other are separate groups or one group is loosely determined and rather subjective. The biggest problem is when howler points were near each other but were recorded days apart. How do we know if these points are the same group or different groups moving around the same place? Because the often uncertain demarcation between single and multiple groups makes a group count from mapping analysis slightly faulty, the better method for estimating density would be through distance analysis. Distance analysis does not require any data but the distance of groups from points across the study area. No need to complicate the estimation with trying to claim where groups are based on their locations relative to each other. Though when it comes to distance analysis, we must be sure we are meeting the most vital assumptions of the analysis (Thomas et al 2010): 1. Monkeys on the point are detected 100% of the time 2. Monkeys do not move when you are recording their location 3. Distance measurements to monkeys are exact The first one is possibly not met, because while groups close to the point were always be found, no zeros were used to measure groups close by; 100m was as low as it went. The second assumption is met, because while howlers move, they often stay in the same tree you find them in for a good 20 minutes. Some groups were seen staying in the same cluster of trees for 3 days straight. The third assumption is not met, because only three distances were used in our study, and this certainly could not be exact distances. Fitting a detection function to point sampling data that only includes three possible distances can be troublesome. It causes a problem of rounding to favorable distances (Thomas et al. 2010), and it forces the detection probability curve to fit across gaps of distance data, as shown in Fig. 3 above. Distance software reports warnings of parameters being constrained to obtain monotonicity when fitting this detection function. More accurate estimations of distances which do not round to a few numbers would be more reasonable for this analysis. The other issue with distance sampling is that we did not account for a correction factor in this analysis. This is useful in point transect sampling of howler calls because it accounts for howler groups that did not shout as you sampled the points nearest them. A correction factor in this case would be a probability of hearing howlers during our sampling period. This could be established on our own, if time could be devoted to recording the frequency of howler calls from one spot and using that as a probability of hearing them at all sampling points.
Along with these corrections, there are two small additions to this survey design that could substantially improve our study of monkeys in the reserve. First, being able to record trees that monkeys eat from would be helpful in establishing habitat preferences for these species. Second, this same study design of using point transect sampling of sounds to estimate population density has worked before for other monkeys in Ecuador (Dacier et al. 2009), but involved playbacks (i.e. playing back recordings of monkey calls when visiting sound points). It is possible that playbacks of howler calls could induce shouting from howlers near points, thus helping make sure nearby howlers shout and are accounted for. This method used on howlers though is not described in the literature, so preliminary testing would have to be done to establish its validity. Given that point transect sampling for sounds has been used many times for estimating monkey densities (Brockelman & Srikosamatara 1993, Whittaker 2005), and that very similar studies have occurred at other biological stations in Ecuador (Dacier et al 2010), the methodology which began in this current study appears to be a step in the right direction, very close to producing reliable population data worthy in modern conservation science. In conclusion, the estimated population density of mantled howler monkeys is as expected given their average home range, so there are no signs yet that the population is in danger. The white-fronted capuchins though are still as rare as they have ever been in the reserve, and the few sightings made during this survey are not enough to make new claims on their population status. Ideally further surveys at the JCR will occur with the improvements mentioned above, and continue into a long term conservation study that will allow us to make stronger claims on the population status of our primates. As population densities are re-measured over the years by new interns, we may reach a point where enough has been collected over time for a population viability analysis (PVA) to be measured (Boyce 1992). PVA s are used to establish the status of IUCN red list candidates. Thus, establishing our own PVA would allow the Jama-Coaque reserve to find primate conservation information useful for conservation authorities such as the IUCN. CITATIONS Boyce, M. S. (1992). Population viability analysis. Annual review of ecology and systematics, 481-506. Brockelman, W. Y., & Srikosamatara, S. (1993). Estimation of density of gibbon groups by use of loud songs. American Journal of Primatology, 29(2), 93-108. Cornejo, F., & de la Torre, S. (2008). Cebus albifrons ssp. aequatorialis. IUCN 2010. IUCN Red List of Threatened Species Version 2014.3. Retrieved 3 March 2015, from www.iucnredlist.org Cowlishaw, G., & Dunbar, R. (2000). Primate Conservation Biology. University of Chicago Press, Chicago. Cuarón, A.D., Shedden, A., Rodríguez-Luna, E., de Grammont, P.C. & Link, A. (2008).Alouatta palliata ssp. aequatorialis. The IUCN Red List of Threatened Species. Version 2014.3. Retrieved 3 March 2015, from www.iucnredlist.org Dacier, A., de Luna, A. G., Fernandez Duque, E., & Di Fiore, A. (2011). Estimating population density of Amazonian titi monkeys (Callicebus discolor) via playback point counts. Biotropica, 43(2), 135-140. Estrada, A. (1982). Survey and census of howler monkeys (Alouatta palliata) in the rain forest of Los Tuxtlas, Veracruz, Mexico. American Journal of Primatology, 2(4), 363-372.
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