TROPICS Vol. 2 (4): 199-208 Issued November, 1993

Methods Used in the Evaluation of Lowland Gorilla Habitat in the Lop6 Reserve, Gabon

Elizabeth A. WILLIAMSON Scottish Primate Research Group, Department of Biological and

Molecular Science, University of Stirling, Scotland FK9 4LA

ABSTRACT This paper presents methods chosen to sample forest structure and composition with a

view to understanding the ranging patterns and habitat use by great apes, and suggests how data may be

presented in simple yet meaningful ways. Straight-line transects were used to sample all tree >10 cm

DBH within a 10 m strip. Although it may be difficult to make direct comparisons between study sites,

it is relatively easy to compare some aspects of forest structure, species diversity, tree density, and the

density of important food-sources in different forests. Several measures of diversity and food

availability can be estimated using tree species frequencies and basal areas obtained from trancects,

some of which are described here.

Key Words: habitat description / food availability / fruit abundance / vegetation analysis / lowland gorilla / Lope Reserve / Gabon.

Now that long-tenn studies of African great apes are taking place at lowland sites in C. A. R,

Congo, Gabon and Zaire that appear to be superficially similar, we wish to compare these

forests and to identify which features lead to variance in the socioecological strategies of the

primates inhabiting them. Where do we begin to evaluate a habitat? Some basic features of

the physical environment to be described and quantified are climate and seasonality (rainfall,

temperatures, and humidity), structure and composition of the vegetation, and temporal

changes in primary production (phenology). This paper aims to promote compatibility

between methods of vegetation analysis used in the course of ecological studies. I present

methods used to sample lowland forest structure and composition in the LopeS Reserve,

Central Gabon, as part of an ongoing study of sympatric western lowland gorillas and

chimpanzees, and suggest how data may be presented in simple yet meaningful ways.

The study area is predominantly mature lowland forest, parts of which were selectively

logged in the 1960s with the removal of one to two stems per hectare of Aucoumea

klaineana. There are relatively small marshy areas; aerial roots, buttresses, palms and

epiphytes are not common, and lianes contribute less than 5% to the total forest leaf biomass

(Harrison, 1984).

E. A. Wu-lnMsoN

Herbaceous vegetation constitutes an important structural component of the study area at

Lop€. Mature forest has often been described as being relatively open at ground level with a

denser understorey in light gaps (e. g. Richards, 1952:5). However, a lack of understanding of

tropical forest dynamics has led to erroneous classifications of forest types (Hartshorn, 1978),

and the presence of herbaceous vegetation has been taken to indicate disturbance. A simple

distinction between primary and secondary forest is often made, and gorillas habitats have

been categorised in these superficial terms (e. g. Sabater Pi,1977)'

The classical view of succession (changes which take place in structure and composition)

in regenerating forest is that ultimately a stable or climax forest becomes established. But the

implication that mature forests are in equilibrium has been disputed (Connell, 1978) and

studies of gap dynamics have demonstrated that secondary colonisation on a small scale is

continuous, even within mature forest, following natural disturbance by animals and Eee falls

(HarShorn, 1978; Whitmore, 1978). Climax forest is an abstract state which will not be

attained in a dynamic environment, although changes in structure and composition occur at

slower rates as forests mature (Whimore, 1984). Tropical forests are intrinsically dynamic

and a high ftequency of Eee falls allows increased development of the understorey'

An evaluation should recognize the importance of the herb layer from the gorilla's

viewpoint, and in order to understand vegetation history. The nafi[e of the forest at Lop6 has

been influenced by the interaction of several factors: a savanna periphery, low-intensity

selective loggrng, and the impact of large mammals, especially elephants and gorillas' At the

interface between forest and savanna' humidity, temperature, and light levels will differ'

Increased penetration of sunlight to the fofest floor favours the growth of herbs and pioneer

tree species, such as Cola lizae which predominates in the study afea' For a general

description of the study site and climate in the Lopd Reserve, see Williamson (1988)' and see

White (1992) for an analysis of vegetation history.

During a study of gorilla ecology, I sought to: (i) describe the spatial and temporal

availability of plant species which provide food; (ii) define vegetation types within the study-

area and thus enable investigation of differential use of the environment; and (iii) provide a

general description of the habitat for comparison with other areas of tropical forest where

primates have been studied.

To understand the feeding, ranging behaviour and habitat use of any primate, systematic'

quantitative data on the availability and distribution of foods are needed. As habitat diversity

increases, resources become less predictably distributed in time and space' which has

important consequences for a species' feeding ecology (Milton, 1981)' Foraging theories

predict that when food density is low diet will be more diverse (Gaulin, 1979). The forest of

the Lopd study alea is similar to others in the lowland tropics, in terms of species densities

and diversity. The distribution of fiee species is characteristic of heterogeneous tropical

forests: individuals are widely spaced and some are clumped (williamson, 1988). The

gorillas'ranglng is stongly influenced by the seasonal production ofparticular food species:

when tree species occurring at low density are in fruit, gorillas travel relatively large

Methods used in the evaluation of lowland gorilla habitat 20r

disances in order to feed. Dfferences in feeding, rangrng and positional behaviour betweenthe subspecies of Gorilla seem to result from striking differences in their respective habitac,especially in the abundance and distribution of fruit sources (Tirtin e/ al., 1992; Williamson,1988).

Fruits and herbs are imporant foods for all populations of African apes so far studied inlowland forest (e. g. Badrian & Malenky, 1984; Nishihara, 1992: Tutin et al.,l99la). AtIop6, the density and distribution of plants which are eaten by gorillas have been measured

@ogers & williamson, 1987; unpub. data), but see Malenky et al. (1993, this volume) formethods of assessing the herb layer. The present paper will address sampling fiees: treedivenity, density and disnibution.

METHODS

A method commonly used to investigate free species composition and abundance is strip-sampling, by cutting straight lines through forest along predetermined compass bearings.Once these transects are established, we label, identify and measure the diameter of all fieesin a 10 mefie strip, that is, the centre of each trunk falls within 5 meters of either side of thetransect line. The diameter is measured 1.3 meters above ground using a diameter tape(available from Forestry Supplies, Inc. , U. S. A. ; tags and aluminium nails for labelling treesmay also be purchased from this supplier). Diameter at breast height or DBH should berecorded above any buttresses or aerial roots and multiple trunks should be measuredindividually, at the point of division if this is above 1. 3m. DBH not only provides importantinformation about relative biomass, but also about population structure and hence forestmaturity (Knight, 197 5).

The strip width and DBH threshold of transects may be varied, but in this study theminimum tree size recorded was 10 cm DBH. This threshold was chosen to include mosttrees of the mid-storey and all trees of the upper canopy, whilst excluding saplings. Theselatter are usually less important as sources offood for apes, and their inclusion could increasethe number of Fees sampled to an unmanageable size. Distance markers positioned every 50meten along hansects allow data to be analysed as contiguous ploS.

The number and length of transects to cut, and where they should be located will dependupon size of the study area, the drainage patt€rn, heterogeneity of the habitat and humanresour@s available (a discussion of sratified-random sampling is beyond the scope of thispaper but see Krebs, 1989). The National Research Council (1981) recommends samplinglOVo of a primare's home range, but a better means of evaluating the efficiency of samplingspecies composition in diverse forest is to draw a species-area curve. This is a cumulativeplot recording each new tree species encountered along transects, and sampling should becontinued until the curve forms a plateau (the rate at which new species are added declinesonoe an area sufficiently large and representative has been sampled).

If resources are limited, other characteristics of forest structure, such as canopy height and

E. A. WTU.NMSON

canopy cover axe less critical data. An analysis of the vertical structure of vegetation is

essential to the understanding of positional behaviour, and to compare the distibution and

availability of terresfial and arboreal foods, but a sub-sample of tees can be measured when

data on tree heights are desirable. All field studies are usually constrained by time or pennn-

power and forced to choose how to gain a maximal amount of information in minimal time.

As staled by Chapman et al. (1992), the method chosen will depend on "the nature of the

investigation and the effort required to carry out the estimates relative to accuracy and

precision demanded by the investigation". Such decisions can be difficult to make at the

beginning of a study, but will be made easier if variables are selected for comparability.

Already in any habitat assessment, the accurate identification of tree species demands a

great deal of effort and long-term investment. Tree identification is initially difficult,

especially in diverse lowland forest where a large number of species will be encountered'

Samples should be taken from all labelled trees: leaves and flowers should be pressed and

storcd in air-tight containers; fruits may be pressed, sectioned and dried, or preserved n lOTo

ethanol. It is important to collect fertile voucher specimens from each species and to have

them determined at herbaria with the requisite expertise, often by specialists for a particular

county or family of plants. In 4 ha sampled in 1985, I recorded 1,538 trees of 138 species

representing 33 families, and several of these still wait to be identified. At least tn'o of the

most common Eees, Cola lizae and a species of Dialium, were new to science and as yet only

one of them has been described (Hall6, 1987). One of the many advantages of long-term

study is that over time some of these unknowns can be addressed, and as Caroline Thtin and

Michel Fernandez enter theil tenth year atLnp6,,the botanical problems are being resolved'

TREATMENTS OF DATA

In descriptions of study sites, vegetation types may be defined using data collected along

transects, and analysing it with programs such as a Tbo-way Indicator species Analysis

(TWINSPAN, Hill, 1979). This progam distinguishes forest types by species composition

and density, and classifies species according to their ecological preferences, forming a

divisive hierarchy from all (here 50 m) segpents of the transects.

Meaningful comparisons of vegetation types acfoss sites are difficult, however, due to the

complexity of factors which are site specific and combine to determine species composition,

such as altitude, rainfall, drainage and soil type. But it is relatively easy to compare some

aspects of forest structure, species diversity, fee density, and the densrty of important food-

sources in different forests.

The number of trees per unit area provides a simple comparative measure' and the

proportions of trees in different size-classes indicates forest maturity (Knight, 1975) and can

be illusfiated gfaphically. If a particular size-class is absent, this may show secondarisation

(few or no large trees) or poor regeneration (a lack of recruitment, so fewer fiees in the

younger size classes). At l,op€, the distribution of size-classes wasi normal; over 507o of the

Methods used in the evaluation of lowland gorilla habitat

tree population measured 40 cm DBH, 35 tees/ha were >60 cm DBH (c. f. webb et al.,1967), while the largest tree in the sample measured 22O cm in diameter.

Several detailed studies have shown that topical trees are unevenly distributed and that

many species are highly clumped (e. g. Hubbell & Fostet 1983). Data from transects axe notindependent and so variance: mean ratios, which assume random sampling, cannot be

calculated. Statistical analyses of patlern require a threshold level of 20 individuals per

species (D. M. Newbery pers. cornm. ), which was met by only five of the 138 species in this

study. With the exception of Cola lizae, all food species occurred at low density:39Vo species

were each recorded once only in 4 ha. Spacing was judged to be patchy (or contagious) byproducing profile diagrams of the locations on transects of all individuals of the mostfrequently recorded species at Lop6.

DBH may be used to calculate basal area per tee, assuming circular cross-section of the

trunk, and summed to give the "stocking" of a unit area of forest. Basal area has been shownto correlate with tree height and crown volume (e. g. Oates et al., 1980) and is therefore the

quickest and easiest measlue of tree size obtainable. Basal area can be used to produce ameasure of relative biomass when combined with tree density. At39.4nflha,fiee biomass inthe study site is above the pan-tropical mean of 33 mlha (Dawkins, 1959, 1959, cited inBrunig, 1983).

Diversity Measures

A diverse habitat is likely to provide a wide variety of foods for primates, so we will wantcomparative measues of diversity. Many complex diversity indices have been devised and Ishall not explain them (e. g. Shannon-weaver: Pielou, 1966), but some past studies ofprimates have presented simple, easily understandable indicaton of tree diversity, such as thenumber of species per unit area, or the proportion of a tree population formed by the 10 most

conrmon species (e. g. Struhsaker,1975).

But what are the l0 "most common" species? Was species frequency or basal area

chosen? Some studies have sampled forest by ftee heights, which are not directly comparable

with diameters. A standardisation of measures is needed, and I suggest DBH with a lowerlimit of 10 cm, as already used in many studies. At Lop6, the 10 most common tree species

formed 54.8Vo of the relative biomass (in a forest made up of few species, the top 10 wouldform a large percentage of the population, but in forests with many species, l0 will represent

an increasingly smaller proportion).

A major problem with inter-site comparisons is that until recently there has been no

consistency in the criteria selected for sampling. A non-linear relationship exists between

number of species recorded and area sampled (Richards, 1952:249), thus a unit area ofperhaps I ha should be predetermined. This is a gross measure of habitat "richness" and

ranges from 20 to 223 in ropical forest (Whitnore et a1.,1985). Because one quarter of trees

at the Iopd site are of one species, Cola lizae, a mean of only 56 spfta was recorded. This islow compared to other samples ftom the Lopd Reserve (e. g. Reitsma, 1988; white, 1992).

204 E. A. WIu;EMSON

Food Availability

The information obtained for individual tree species is of most importance in analyses of

behavioural ecology, especially of frugivory. Data obtained from transects alone are of

limited use but once species densities, basal area and distribution are combined with a)

information about diet composition and b) phenology data, we can make estimales of food

abundance. The composition of gorilla diet at Lop6 was presented by Williamson et al.,

(1990), and phenology data have been collected since 1984 (for methods see Williamson,

1988; Ttrtin et at., I99lb). As research progresses, more subtle aspects of food availability

may be investigated, such as the chemical composition of plant parts (e. g. Rogers el al.,

1992').lnthis volume, the study of phenology is discussed by Malenky et al. (L993).

The present assessment focussed on fruit availability (the abundance of fruit-producing

trees) because the majority of feeding data were obtained by faecal analysis, and were thus

biased against non-ftuit items in the diet (see Tutin & Fernandez, this volume).

A first indication of availability is the number of "food-trees" in a population, where a

food-fiee is defined as any tree species whose fruits are known to be eaten by the primate

being studied. At LoF many species of food-tree are relatively rare: 26Vo spcies occur at

densities below I tree/ha. To look at fruit producers we should try to restrict the sample to

mature fiees by increasing the DBH threshold. A subset of tees with DBH >30 qn could be

chosen, as suggested by Hubbell and Foster (1986). At Lop6, 46Vo of the *adult" population

were food-trees, with a mean density of 59 food-trees/ha. Long-term study enables fine

tuning for exceptions to a 30 cm cut-off based on accumulated knowledge of fruit production

by particular species, for example, Porterandia cladantlw and several Diospyros species fruit

below this threshold and adjustnents were made accordingly.

Due to marked seasonality in production, no more thanL|To of individual trees studied

for phenology produced fruit in any single month (Williamson, 1988). Taking phenology into

account, we can calculate the number of trees likely to be in fruit at any one time for a unit

area. For Lop6 this was estimatedatl2.4 individuals per ha (ZlVo of 59 trees/ha). This

aver4ge is greater than 3.5 trees/ha trees fruiting during any one month in north-east Gabon

(Gautier-Hion et a1.,1981), although much less than 45-58 trees/ha recorded in Sumafra

(Whitten, 1982).

These measures do not yet incorporate tree size or individual yields. To devise an index of

fruit availability, we can incorporate basal area, as fruit production has been shown to be

generally proportional to crown volume, which is correlated with DBH (Hladik, 1978; Oates

et aI, 1980). For any single species we can estimate fruit abundance using basal area per

hectare multiplied by the mean phenology score of that species. And we can sum all species

for a relative estimate of fruit abundance for any one time period. Fruit Availability Index =

l@iomass/sp.xmean phenology score/sp.). [Biomass = m2lha; phenology scoro = G4

linear scale of fruiting intensityl.

Wrangham et at. (199t) calculated a similar index using the percentage of frees with

fruit, tee density and mean basal area, also summed across species, then calibrated to bring

Methods used in the evaluation of lowland gorilla habitat 205

the largest value up to 100. In my analysis, food-species were separated into two classes,

"major" and "minor" foods, depending on the relative contribution of each to the gorillas'diet, and these classes were weighted. I also calculated Importance Values, which incorporate

the relative frequency, relative density, and relative dominance of each fiee species (see

Badrian & Malenky, 1984; Kershaw & Looney, 1985). Fruit abundance within a community(not restricted to foods) and basal areas, rather than lmportance Values, may be moreappropriate and more easily compared across sites.

The indicators suggested are not sophisticated; many caveats could be added and

treaunents of data may become exfiaordinarily complex, but since few measures are available

to make meaningful inter-sile comparisons, we should start with a few simple pointers. Thepresent attempt to addrcss some of these issues came about tbrough the desire of researchers

studying African great apes to standardise methods. Increased communication between fieldprimatologists should be encouraged, with a view to developing a forum for discussion.Although gorillas were the subjects of my study, it is hoped that the approach described here

will have a wider application.

ACKNOWLEDGEMENTS I thank the L. s. B. Leakey Foundarion, L. s. B. IrakeyTrust, the Wenner-Gren Foundation for Anthropological Research, the Boise Fund, the CenfieInternational de Recherches Mddicales de Franceville, Gabon, and the University of Stirlingfor supporting this research; the Direction de la Faune, Gabon, for permission to work in theIop6 Reserve; and Michel Femandez and Caroline Tirtin for their hospitality, companionship

and use of the facilities at S. E. G. C. I am also grateful to Michel Fernandez, MichaelHarrison, Bill McGrew, Liz Rogers, Caroline Tirtin and l,ee White for help in the field, and to

Beth Kaplin and Caroline Tutin for comments on the manuscript.

SIJMMARYL Indicanrs of Forest Snrcture

a) number of stems per ha, and bar chart of trree size-class distribution to indicate maturity;b) profile diagrams o illusnarc species distribution and pattern;

c) basal area per ha calculated from DBH measu€ments;

2. Ittdicators of Tree Diversity

a) number of species per unit area (l ha);

b) proportion of relative biomass formed by 10 most common species (tree density x basal area mrlha);3. Irrdicators of Food Availability (Fruit Abundance)

a) number of food-rees in population per ha and as a proportion of "adult" population (% nws >30 cmDBH);

b) mean number of rees in fruit at one rime (individuals/ha);c) Index of Fruit Abundance - I @iomass nflhax mean phenology score) for all species (gives a measure

of fruit-source availability in the population and production of food by those nees).

206 E. A. WILLIAMSON

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(3) it!lm~ljfflTiJg~OC (*~;.) (7)~tio

a) 1 ha~ ~ (7)it!lm*:fMli<7)tit, -t(7)fflt* (J.J~@[q~~"30cm :a-g,Z.Q t (7), li~: J: -:J-C~ 1£) (7)~..g. 0

b) 1 ha~ ~ (7)1PJrt]:~:*B~ l-CII'.Qft*(7)Sf:tSj1l14'ti (phenology score)o

c) *~;'~ti (Index of Fruit Abundance) t l-C, T",,-C(7)it!lm*fHi<7) [J'\1;:f"<' A (m2/ha) X phenology score] (7)~D~13m l, -t(7)m~ ~ (7):!&~<7)*fH: J: .Qlt!lm1:,J£:

;., i t.:~;J:*~jtVffi~ljfflTiJg~OC(7)~'lft~ t It.:o ~ ni? (7)1J1*~;J:tllJ1!~ t (7)1"<b ~, iiJJ3!t:!&OO(7)1:,,~,~:I;lJt~~: t lf~:JJl"<b.Q t ~,Z i? n.Q 0