Comparación de las categorías de estudio entre los diferentes procesos

5.1 Summary

In the literature describing methods for surveying carnivores there is a wide range of techniques. For the carnivore survey described in chapter 4, two different methods were used to survey carnivores. However, during the study several other techniques were also used. Since this study required the comparison o f carnivore surveys carried out in two different areas (one without people present and one with people present) there was concern that different census techniques may suffer different biases in each area. This chapter therefore compares the “true” results from chapter 4 with some of the other most common techniques used in the literature for to test whether differences in study site can affect validity o f the survey method used. Alternative methods include estimates of relative abundance based on 179 questionnaires, an observation-based index covering 35,000 km, 8 line transect surveys and the results of density predictions based on prey biomass availability. The results show that all techniques agree generally on relative abundance, placing spotted hyaenas as the most abundant and lions as the second most abundant. However, sightings-based methods predicted far lower densities outside the park and prey biomass estimates overestimated cheetah abundance. Actual density estimates were more varied. Jackal estimates, based on transects and call-ins agreed on approximately 0.05-0.15 jackals per km^. Hyaena estimates outside the park were particularly low compared to call-in estimates o f around 0.5-1 / km^. However, if migrant species or livestock were included, biomass estimates predicted far higher hyaena estimates. Lion estimates were similar, underestimated by all methods compared to call-ins but overestimated when biomass included livestock and migrants. The results showed a particularly strong limitation of visual-based techniques outside the park, with estimates based on road sightings or transects working relatively well inside the park but poorly outside in comparison to call-ins. For lions, these methods predicted zero densities in Loliondo. This has serious implications for previous surveys o f carnivores outside parks, which generally rely on sightings-based methods. Biomass- based methods were also shown to be o f limited use depending on which prey were included. Biomass methods were particularly inaccurate for cheetahs.

5.2 Introduction

The range of carnivore monitoring techniques

Monitoring o f carnivore abundance is fundamental to carnivore research, conservation and management (Wilson & Delahay 2001). However, the apparently simple task of describing the size and extent o f population o f carnivores within a given area can be extremely difficult to achieve due to their low densities, cryptic and nocturnal behaviour, large home ranges, occupation o f a range o f habitats and varying social systems (Gese 2001), (Wilson & Delahay 2001). A wide range o f methods exists for surveying carnivore populations, allowing estimates to be made at a variety o f levels o f complexity. Firstly, predictions can be made for carnivore presence and even abundance based on known environmental variables and previous studies of species preferences. Secondly, data can be collected to show definite presence or absence and distribution o f a given species. Thirdly, information on relative abundance can be obtained using indices. Fourthly, actual abundance can be estimated using sampling or, ideally, total counts completed.

Indices of relative abundance

Indices can be used to describe a portion o f a population, giving information on presence or absence and limited information on abundance. Although the precise nature of the relationship between the index result and the actual population abundance might not be known, if it is constant it can allow comparisons o f relative density between different areas (Sutherland 1996). Generally indices are based on signs of carnivore presence. These include interviews with local wildlife workers,

residents or tourists and have been used to survey wild dogs (Ginsberg et al. 1997),

foxes (Heydon et al. 2000), cheetahs (Gros et al., 1996,, lions (Bauer et al. 2001) and

hyaenas (Mills 1998). Alternatively, tracks and spoor can be used to compare relative

abundance (e.g. (Mahon et al. 1998), (Stander 1998), (Scott 2000)), or counts o f calls

have been used (Hofer and East, unpublished, quoted in (Sutherland 1996)). Indices can also be based on actual observations by recording the number o f sightings whilst controlling for search effort (Gese 2001) and these have been used successfully for

various species e.g. cats, dingoes and foxes (Mahon et al. 1998). Although abundance

the only viable way o f obtaining information on some carnivore populations, they do depend upon the relationship between the relative estimate and the actual density being constant. Often this might not be the case due to variation in season, habitat, or other factors. Few indices have been compared with known density values and therefore often their reliability is not fully known (Gese 2001) although see (Stander

1998).

Estimating density

Transects

Estimates that are more useful can be made by calibrating indices based on signs or by taking into account the area searched when counting observations, thereby allowing actual density estimates to be calculated. The most common method is the use o f transects. Ideally transects would cover the entire study area to give a total count. Total counts are frequently used for large, conspicuous mammals such as large

herbivores {e.g. (Watson 1969), (Campbell & Bomer 1995)) but less frequently for

the more cryptic carnivores that require more intensive searching in restricted areas, although an exception is provided by a helicopter survey of lions in a Serengeti buffer zone (Bomer 1992). More commonly, transects sample a limited proportion o f the study area and extrapolate to calculate overall densities. Transects include strip transects, which carry out a total count in a number o f transects with a predefined width, such as used on ground-based surveys for a variety o f carnivores (Anon. 1977

quoted in (Hofer & East 1995)). They also include counts o f several species {e.g.

(Caro 1999a), (Caro 1999d)), use o f spotlighting for night surveys (Sharp et al. 2001),

(Scott et al., in submission) or from aircraft {e.g. (Campbell & Bomer 1986), (Bomer

1992)). A refinement o f the strip transect census are line transect surveys analysed

using the distance sampling method (Buckland et al. 1993) which do not predefine the

area censused but use the distance from the line o f each sighting to estimate unrecorded sightings on the survey. This technique has been used for foxes (Heydon

et al. 2000), however, although able to produce more accurate estimates o f abundance

(Cassey & McArdle 1999), (le Mar et al. 2001), distance sampling requires large

numbers o f sightings for accurate analysis (Buckland et al. 1993) thus limiting its use

Attracting carnivores

An alternative range o f methods relies upon attracting responses from carnivores. Using a lure such as a scent, a sound recording and/or sometimes bait to either attract or stimulate a response from carnivores, the study area is censused in a series o f point transects, recording the number of animals responding to, or approaching, the station to give an index of population size. If the responses are also calibrated, estimating the detectable range o f each playback or scent station and the proportion responding, calculation o f actual densities is also possible. Although response to recordings is generally limited to adults only, and both techniques are limited by the availability of suitable audio or scent cues, call-ins using recordings o f feeding hyaenas have been used successfully attract and survey lions (Ogutu & Dublin 1998) and spotted

hyaenas, (Mills et al. 2001). Scent stations have been used for a range of species

(Sargeant et al. 1998) and replies to lion roars have been used to survey lions,

although relatively unsuccessfully (Schaller 1972b).

Capture-mark-recapture

Other methods rely on capture-mark recapture methods, based on an initial survey round, marking individuals and subsequent survey rounds recording the number of marked individuals re-censused (Sutherland 1996). “Captures” can be physical

captures using traps or darting with anaesthetic {e.g. (Com & Conroy 1998), (Kmuk

1972)) with marking also a physical process such as use of ear tags {e.g. (Kmuk

1972), (Schaller 1972b) or “captures” can be sightings using natural markings for identification, removing the need for handling. Individual recognition based on natural markings has been successfully demonstrated for a range o f carnivores. Cheetahs (Caro 1994), spotted hyaenas (Hofer & East 1993a), tigers (Karanth 1995) and wild dogs (Maddock & Mills 1994) have all been identified based on coat patterns. Lions have been identified based on facial markings (Pennycuick 1970) and

mountain lions based on footprints (Grigione et al. 1999). High reliability of

distinguishing individuals has been shown in several o f these examples e.g.

(Pennycuick 1970), (Caro & Durant 1991). If sufficient sightings are obtained, individually known animals may be used to obtain a total count within a given area such as achieved with long-term studies o f cheetahs on the Serengeti plains (Caro

1994) and lions in parts o f the Serengeti and Ngorongoro crater {e.g. (Hanby et al.

available including the Lincoln index (whereby a closed population is assumed) as used for hyaenas (Kruuk 1972) or more complex methods taking into account immigration, emigration and unequal sighting probabilities as used for cheetahs (Cooper & Durant In press). A variation on methods using individual recognition is the analysis o f tourist photos as demonstrated for wild dogs (Maddock & Mills 1994)

or cheetahs (Bowland 1995), ( S . D u r a n t ,com) or the use o f camera traps that are

triggered bypassing animals e.g. (Karanth & Nichols 1998), (Carbone et al. 2001).

Estimates o f density based on environmental predictors

Because o f the various difficulties and effort required for surveying carnivores there is a strong interest in methods that can accurately predict population densities based

upon more easily measured variables (see Gros et al., 1996 for a review). Estimates of

carnivore distribution based on environmental parameters are quick and easy, allowing rapid estimates with little or no fieldwork. Identification o f the important variables required for prediction has been tricky, with densities for several species varying by a factor o f 100 depending on the conditions o f the study (Carbone & Gittleman 2002). However, parameters that have been used include prey availability, based on regression o f carnivore biomass against prey biomass, (Carbone &

Gittleman 2002), (Gros et al. 1996), habitat availability (Gros & Rejmanek 1999) and

estimates based on area availability and average range sizes (Gros et al. 1996), (Mills

1998). At minimum, use o f environmental parameters can predict likely presence and absence o f a species. However, with careful calibration environmental parameters may also be used to estimate likely densities o f certain species, a technique that has been applied to estimates based on prey availability (Carbone & Gittleman 2002). Concurrent to the interest in abundance estimates have been various theoretical ecology studies on biological scaling, relating population densities to body size and resource use or availability (see Carbone & Gittleman (2002) for a review). In both fields the relationship between prey population size and carnivore density has held great interest. The accuracy of using prey to estimate carnivore density has been questioned since it relies heavily on accurate identification and weighting o f the influential variables, and for cheetahs the results have been shown to underestimate

true densities (Gros et al. 1996). However, Carbone et al (2002) have shown that a

very strong, linear relationship exists between carnivore densities and average prey biomass, regardless o f other factors (Carbone & Gittleman 2002).

Chapter aims

The aim o f this chapter is to examine whether the choice o f survey method is important when measuring large carnivore abundance in semi-protected environments. In order to achieve this, three questions were examined:

1. What do the various methods predict for relative abundance o f each carnivore inside and outside the park? Do they each agree?

2. What does each method predict for actual densities inside and outside the park? Do all methods agree?

3. What do the results suggest for future and previous carnivore surveying? 5.3 Methods

Choice of methods

The chosen methods for chapter 4 were the use of call-ins, attracting scavengers to recordings o f hyaenas on a kill, to census lions, spotted hyaenas and jackals and individual recognition to survey cheetahs. Call-ins were chosen due to proven success and accuracy in similar habitats (Ogutu & Dublin 1998) whilst individual recognition has been established as the best method for surveying cheetahs in the Serengeti (Caro 1994) and both methods produced estimates of carnivore abundance inside and outside the park (Chapter 4). The choice o f comparative methods was limited partly by the conditions of the study (for example, camera trapping is unsuitable for open habitats with few pre-defined carnivore pathways; resources were not available for aerial surveys and the areas were too large to consider scent stations or indices based on spoor). However, the chosen methods cover the most commonly used in the literature, including indices o f relative abundance based on interviews and on direct observations, estimates o f density based on transects and a prediction o f density based on environmental parameters.

Call-ins and individual recognition

Methods and results for the call-in survey and individual recognition-based estimates are presented in chapter 4. The estimates o f density from call-in surveys conducted at three monthly intervals, starting in July 99 and ending in April 2001, together with

overall estimates o f cheetah abundance in each region are used for comparison for this study.

Questionnaire-based index of relative abundance

A survey of relative abundance based on questionnaires was incorporated into a social survey investigating Maasai relationships with carnivores in the two study sites outside the Serengeti (Chapter 7). The questionnaire was semi-structured and directed

at adult men and murran (teenage “warriors”) living in the vicinity o f the carnivore

surveys. Initial questions were asked to determine attitudes and knowledge o f the individual species, after which photographs were used to ensure that both the respondent and interviewer were discussing the same species. Questions were then asked on the last time each species had been sighted personally by the respondent. The survey was intended to quantify contact rates between Maasai and each of the carnivore species, but assuming equal sightability for each species, the relative timing of the most recent sightings was also taken to be a measure o f relative abundance. For full details on methods, see chapter 7.

Observations-based index of relative abundance

A predator population index was created by recording the time spent and distance travelled for each car trip undertaken in each region and noting all large predators seen during the trip. Trips were not undertaken specifically to compile the index; rather the data were collected opportunistically during almost any journey made during the study. Thus, a trip could include a journey between two points, or it could include a journey to survey prey density or search for cheetahs. Nevertheless, search rate was controlled for in the analysis. Only time spent travelling was included in the trip time and every trip was located entirely within the borders o f one o f the study areas. If a border between study areas was crossed, a new trip record was started. Only predators initially sighted by the author were included in the analysis. The few sightings made with the aid o f tourists or other researchers were excluded since few such aids were available outside the park.

Analysis was carried out individually for cheetah, lion and hyaena sightings only. Data were initially examined using mean sightings per kilometre to demonstrate the actual sighting frequencies during fieldwork. To account for variation between

individual trip conditions other than effect o f the study area, further analysis was then carried out using a Generalised Linear Model (GLM), defining Poisson errors and a log hnk function as appropriate for count data (Crawley 1993). Analysis was carried

out at two levels for each species; numbers of independent sightings or groups seen

per 100 km driven were analysed, to show sightings frequency and numbers of actual

individuals per 100 km, correcting for over-dispersion to account for non­ independence o f individual animals, were analysed to give an index o f actual population size. The effects o f four potential explanatory variables were incorporated as model terms (Table 30).

Table 30 - Explanatory variables used as model terms for explaining the variation in numbers of predators seen on logged trips.

Model term Description

Region Region describes the study areas Loliondo, Ngorongoro or Serengeti

Search rate (km/h) The average search rate for each trip was calculated as trip time / trip distance Season Seasons were defined as Short rains (November to February), Long rains (March

to May) and Dry (June to October) (Sinclair 1979)

Distance Although distance should not affect a response variable measured as predators per km, it was included as an explanatory variable for reasons explained in the cheetah sightings analysis.

All four variables were fitted to the response variable (the maximal model) and the model reduced using a backward stepwise method, removing each in turn, recording the effect on model deviance and permanently removing the variable with the lowest effect. This process was continued until all variables remaining explained a significant proportion o f the data (the minimal model). The results presented firstly show the significance of all terms in the maximal model, with probability values quoted for significant terms referring to their effect on the minimal model whilst values for non­ significant terms show their effect when re-added to the minimal model. Secondly, the minimal model is presented, showing the direction and strength o f the average effect o f each significant term. Finally, the minimal model is used to predict the actual values for a given variable whilst controlling for other significant variables. Controlled continuous variables were set at their mean value, so search rate was set at 22 km/h and distance at 95 km.

Transects

Line transects were carried out as part of a comprehensive survey of prey availability (Chapter 3), but large carnivores were also recorded when sighted. Transects were carried out in conjunction with call-in surveys, starting in July 99 and repeated every 3 months until April 2001 and surveying all three study areas, although transects in Ngorongoro were not started until July 2000. Transects were placed randomly where possible and on roads where random placement was limited by environmental obstructions and were carried out by Land Rover, driving below 20 kph and recording all sightings on either side o f the vehicle. Sightings were recorded by group, estimating the number in the group and the perpendicular distance from the geometric group centre to the transect line. Analysis was then carried out using distance

sampling (Buckland et al. 1993) and the DISTANCE software (Laake et al. 1998).

Histograms o f the data were initially examined to ensure they matched the specified

shape criteria (Buckland et al. 1993). Data were grouped into distance intervals for

analysis to remove the effect o f heaping (the increased likelihood o f recording convenient distances such as 100 metres as opposed to 103 or 98 metres) and truncated to remove extreme outliers if necessary. Detection functions were calculated by fitting various combinations of key and expansion terms, the best fit determined by a combination o f maximum likelihood and AIC scores. Since 60-80 sightings are generally required for a good estimate o f detection probability, data for each species were pooled across time and regions. The fit o f the resulting detection curve was then tested using a goodness-of-fit test and if acceptable (P>0.15) the detection function was used to calculate estimates o f group density. To calculate individual density, average group size was required. To account for the effect of distance on group size