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Conservation research presence protects: a case study of
great ape abundance in the Dja region, Cameroon
N. Tagg1, J. Willie1,2, J. Duarte3,4, C.-A. Petre1,5,6 &J.E.Fa
7,8,9
1 Centre for Research and Conservation, Royal Zoological Society of Antwerp, Antwerp, Belgium
2 Terrestrial Ecology Unit, Ghent University, Ghent, Belgium
3 Grupo de Biogeografía, Diversidad y Conservación, Departamento de Biología Animal, Facultad de Ciencias, University of Málaga, Málaga,
Spain
4 Ofitecma, Málaga, Spain
5 Forest Resources Management, BIOSE Department, Gembloux Agro-Bio Tech, University of Liège, Gembloux, Belgium
6 Conservation Biology Unit, Royal Belgian Institute of Natural Sciences, Brussels, Belgium
7 ICCS, Imperial College London, Ascot, UK
8 School of Science and the Environment, Manchester Metropolitan University, Manchester, UK
9 Consultative Group on International Agricultural Research, CIFOR Headquarters, Bogor, Indonesia
Keywords
central chimpanzee; western lowland gorilla;
evaluation; active management;
conservation outcomes; research
programmes; community engagement.
Correspondence
Nikki Tagg, Centre for Research and
Conservation, Royal Zoological Society of
Antwerp, Koningin Astridplein 20-26,
Antwerp B-2018, Belgium.
Tel: +32 490 643327
Email: Nikki.tagg@kmda.org
Editor: Iain Gordon
Received 29 September 2014; accepted 28
March 2015
doi:10.1111/acv.12212
Abstract
Research programmes have been shown to exert a positive impact on faunal
communities, but few studies provide empirical evidence. In this study, we sur-
veyed three neighbouring sites, differing in terms of official protection status and
level of active management, in the Dja Conservation Complex, southeast Cam-
eroon. We recorded signs of human activity and anthropogenic pressures and
found that they significantly differed by site. We assessed chimpanzee and gorilla
relative abundance using nest count surveys. We found that chimpanzee nest
abundance was related to the presence of active management, but both active
management and availability of suitable habitat affected gorilla nest abundance.
Our results suggest that gorillas are more tolerant of human activity. We also
provide evidence that the presence and activities of the conservation research
project Projet Grands Singes served to actively deter poachers and limit hunting of
great apes as a result of researcher presence, community sensitization and of
valuing living apes and intact forests by local people. Such empirical evidence for
the positive effect of research activity on biodiversity preservation should encour-
age continued investment in such programmes as part of a landscape-wide, multi-
stakeholder conservation management of great ape habitats.
Introduction
Proof that researcher presence can have a positive influ-
ence on the faunal communities or species being studied is
still relatively limited. There is some evidence that
researchers provide both active and passive protective
effects, for example, by deterring poaching (Piel et al.,
2015) or by offering financial benefits to adjacent commu-
nities who in turn will support protected areas (PAs;
Laurance, 2013).
Non-governmental organizations (NGOs) and research
groups undertaking research on wild great apes in Africa
and Asia contend that their activities positively impact their
study populations (Plumptre & Williamson, 2001; Posa
et al., 2008; Wrangham & Ross, 2008; Brooks, Wright &
Sheil, 2009; Vermeulen et al., 2009). However, the impacts
of such benefits are largely unknown often because the
effects of field research on the conservation of species or PAs
are yet to be systematically assessed, or are in need of more
evidence-based appraisal (Ferraro & Patanayak, 2006;
Laurance, 2013).
Several methods for the standardized evaluation of con-
servation activities are available (e.g. Sutherland et al., 2004;
Kapos et al., 2008; Pullin & Knight, 2009). A number of
studies evaluating NGOs or research projects contribute a
varying degree of empirical evidence for their role in biodi-
versity protection (Köndgen et al., 2008; Campbell et al.,
2011; Tranquilli et al., 2012; N’Goran et al., 2012; Piel et al.,
2015).
A measurable and significant outcome of researcher activ-
ity would be how their continued presence in the field affects
wildlife abundances (Laurance, 2013). To achieve this,
regular monitoring of wildlife populations, for example,
repeated design-based surveys, could provide density and
abundance estimates of the studied species that may be used
to measure the success of conservation interventions (Kühl
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Animal Conservation. Print ISSN 1367-9430
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London 1
et al., 2008; Stokes et al., 2010; Campbell et al., 2011).
Whether or not the main factor causing an improvement in
the status of the study species is researcher activity requires
an assessment of the degree to which changes in outcomes
can be attributed to this intervention rather than to other
factors. Such attribution requires knowing what the out-
comes are likely to be in the absence of the intervention. This
counterfactual thinking is essential to drawing inferences
about programme effectiveness because environmental out-
comes are affected by many confounding factors correlated
with the timing and location of interventions (Ferraro, 2009).
In this study, we focused on western lowland gorillas
(Gorilla gorilla gorilla) and central chimpanzees (Pan trog-
lodytes troglodytes) in the Dja Conservation Complex. This
landscape covers over half a million hectares of moist
lowland forest in the South and East of Cameroon (Tutin
et al., 2005), and encompasses a core Dja Biosphere Reserve
(DBR) together with a wider periphery zone mosaic of for-
estry concessions, agricultural land, mines and community
forests. It is a UNESCO World Heritage Site and an IUCN
SCC conservation priority for threatened species such as the
African elephant, gorilla and chimpanzee (http://www.zsl
.org/conservation/regions/africa/dja-conservation-
complex). As in most other parts of the species’ ranges, the
main threat to great ape survival in the north of the Dja
Conservation Complex is bushmeat hunting, especially that
linked to the commercial trade (Tagg, Petre & Willie, 2011;
Tagg & Willie, 2013).
Our primary aim was to determine the impact of
researcher activity on ape populations by comparing the
relative abundance (using nest count surveys) of the two ape
species in three contrasting localities within the Dja Conser-
vation Complex (officially protected, unprotected and
actively managed as a research site). The research site (La
Belgique) is managed by Projet Grands Singes (PGS), which
began in 2001 (Dupain et al., 2004) and is an initiative of
Antwerp Zoo’s Centre for Research and Conservation
(CRC). PGS is a bottom-up community programme that
promotes primary (law enforcement) and secondary conser-
vation activities (education, tourism, alternative livelihoods;
Dupain, 2001; Dupain, Bombome & Van Elsacker, 2003;
Tagg et al., 2011), and simultaneously facilitates the CRC’s
great ape socio-ecology research programme within the
forest (Willie et al., 2014).
Whereas a number of studies have measured the effective-
ness of conservation efforts within PAs (e.g. Bruner et al.,
2001; Caro et al., 2009; Craigie, Baillie & Balmford, 2010;
Tranquilli et al., 2012), those evaluating conservation
efforts outside PAs are less common (see Morgan et al.,
2013). Here, we examined whether activities at La Belgique
and surrounding communities positively affected great ape
numbers in the Dja area by using the three localities and
their respective situations as counterfactuals. Previous
studies have shown that there are clear differences in habi-
tats associated with chimpanzee and gorilla presence; in this
region, more chimpanzee nests are built in near-primary and
old secondary forest, and more gorilla nests are found in
light gaps, young secondary forest and swamps (Dupain
et al., 2004; Willie et al., 2012; Tagg et al., 2013). Thus, the
frequency of occurrence of chimpanzee and gorilla suitable
nesting habitats at each site was determined. Based on these
observations, we then identified factors that could explain
the abundance of gorillas and chimpanzees in the three sites
by testing the following hypotheses: (1) given their close
proximity, there is no significant difference between sites in
the availability of suitable nesting habitats, and hence
potential chimpanzee and gorilla abundance (Anderson,
2000); (2) lower ape abundance will be correlated with a
higher human presence, greater density of logging roads/
transects and well-trodden trails, proximity to neighbouring
villages, and access to the Dja River (which may facilitate
hunting activities, Stokes et al., 2010); and (3) greater offi-
cial protection or higher levels of researcher activity (cf.
Stokes et al., 2010; Campbell et al., 2011) of a site will lead
to a higher abundance of the two ape species.
Methods
Study sites
The three study sites were Madjuh, La Belgique and Ekom
within the Dja Conservation Complex (Fig. 1). Madjuh is
situated in the northern periphery of the DBR, 10 km east of
the village of Madjuh I, and in the northern sector of a
previously logged area [forest management unit (FMU)
10 047]. At the time of our study, the FMU was allocated to
the Italian company FIPCAM (Fabrique Camerounaise de
Parquet). Madjuh was selectively logged in the 1970s, hence
resulting in a dense network of access roads and trails. The
site is unprotected and local people use it for subsistence and
commercial hunting. The second site, La Belgique, is in the
southern sector of FMU 10 047, 11 km east of the villages of
Mimpala, Malen V and Doumo Pierre. In this locality, vil-
lagers rely heavily on forest resources for their subsistence
and income (Tagg et al., 2011). Similar to Madjuh, La
Belgique has no legal protection. Some parts have been
subject to timber exploitation in past decades, though these
activities are currently negligible. Since 2001, conservation
activities, run by PGS, have been underway in this site
(Dupain, 2001). The third site, Ekom, is located inside the
official boundary of the DBR, 15 km southeast of Ekom
village. The site has never been logged, and official
ecoguards from the Ministry of Forests and Wildlife under-
take anti-poaching activities. Despite this, hunting, fishing
and collection of other forest products still occur within the
reserve.
Sampling design
Within each site, we opened 10 parallel rows of five 600 m
transects (50 transects per site, a total of 150 transects;
Fig. 1). Rows were set 600 m apart, and within each row, the
gap between two consecutive transects was also 600 m. We
used available digital maps to set transect positioning;
transects at Madjuh, La Belgique and Ekom were opened at
Conservation research presence protects great apes N. Tagg et al.
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London
2
a constant bearing of 90°, 45° and 180°, respectively, and
perpendicular to most watercourses. Transects traversed all
habitat types.
Habitat composition and forest structure
We distinguished six main habitat types, adapted from
Dupain et al. (2004): (1) near-primary forest, (2) old second-
ary forest, (3) young secondary forest, (4) light gaps, (5)
swamps and (6) riparian forest. The first four habitat types
were collectively referred to as terra firma habitats and the
latter two as (periodically) flooded habitats (Willie et al.,
2012).
Near-primary forest consisted of late successional
closed-canopy vegetation comprising large trees and little
undergrowth. Dominant tree species (>30 m height) of a
dbh >60 cm at 1.30 m (D1.30) height were Dabema
(Piptadeniastrum africanum Mimosaceae) and Movingui
(Distemonanthus benthamianus Caesalpiniaceae). Old sec-
ondary forest included late successional trees of D1.30
<60 cm, height 25–30 m in a more discontinuous canopy,
and with thicker undergrowth than near-primary forest.
Young secondary forest had relatively dense undergrowth
and was dominated by early successional trees (<25 m
height) such as Adam’s apple (Tabernaemontana crassa,
Apocynaceae) and umbrella tree (Musanga cecropioides,
Cecropiaceae). Light gaps were open-canopy environments
resulting from tree and branch fall or elephant activity.
Swamp forests were characterized by high densities of
Raphia palms, with occasional clearings (<5%) of raphia-
free areas, and water-saturated soils. Riparian forest,
found along transitional zones between swamp forests and
other forest types, contained a mixture of species from all
forest types (Willie et al., 2012).
Data collection and analysis
Ape nest encounter rates
During the period August–November 2008, we carried out
line transect nest count surveys at the three study sites to
estimate the abundance of sympatric gorillas and chimpan-
zees. A researcher and two local assistants walked at 1.0–
1.5 km h−1along newly opened transects in each site
(Buckland et al., 2001, 2005; Plumptre & Cox, 2006). We
recorded nests of all ages; for each nest, we noted height,
habitat type, tree species and nest type. We used criteria
such as footprints, urine, dung and smell to reliably confirm
Figure 1 Location of the three study sites Madjuh, La Belgique and Ekom within the Dja Conservation Complex, East region, Cameroon.
N. Tagg et al. Conservation research presence protects great apes
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London 3
nest builder identity (White & Edwards, 2000). Although
the perpendicular distance of the nest to the transect was
also measured, we did not use the measurements in the
present study. To avoid any possible bias arising from
grouping individual nests into nest sites, we used individual
nests instead of nest sites in our analysis.
Human activity and habitat features estimation
We noted signs of human activity along transects (Tagg &
Willie, 2013). These included the occurrence of snares,
machete cuts on trees, bark stripping and honey harvesting.
We also recorded presence of camps and access routes, such
as trails and logging roads. We determined the shortest
straight-line distance (km) from the transect origin to
human settlements, main trails and the Dja River, using
ArcGIS (Fig. 1). We used the sum of all human signs found
along each transect to correlate with nest abundance in the
statistical analyses. The occurrence of forestry exploitation
roads along each transect was used as a separate human
presence variable.
We noted the habitat type present at 50-m intervals along
each transect. The proportion of each habitat type was
determined as the relative frequency of occurrence of each
habitat type along the transect. Suitable chimpanzee nesting
habitat was the sum of near-primary and old secondary
forest (Dupain et al., 2004; Tagg et al., 2013), whereas suit-
able nesting habitat for gorillas was the sum of light gaps,
young secondary forest and swamps (Willie et al., 2014).
Statistical analyses
We tested the normality of the data matrix using a
Kolmogorov–Smirnov test and performed between-site
comparisons of chimpanzee and gorilla abundance, human
activity and habitat features using a non-parametric
Kruskal–Wallis analysis of variance (Fowler & Cohen,
1992).
We assessed differences in chimpanzee and gorilla indi-
vidual nest abundance (dependent variables) between sites
in terms of differing human activity levels and habitat fea-
tures using generalized linear mixed models (GLMMs) with
a Poisson error distribution and a log-link function. All
analyses were performed in SPSS 22.0 (IBM, Armonk, NY,
USA). The following predictors of nest abundance were
prepared: Site: 1 (Madjuh, unprotected), 2 (La Belgique,
unprotected with conservation activities) and 3 (Ekom, pro-
tected); Npf, percentage of near-primary forest; Osf, per-
centage of old secondary forest; Ysf, percentage of young
secondary forest; Lg, percentage of light gaps; Rf, percent-
age of riparian forest; Sw, percentage of swamps; ShC, per-
centage of suitable habitat for chimpanzees (Npf + Osf);
ShG, percentage of suitable habitat for gorillas
(Ysf + Lg + Sw); Dh, distance to human settlements (km);
Dt, distance to trails (km); Dr, distance to Dja River (km);
Hs, number of human signs; and Lr, number of logging
roads. We tested for normality of the residuals and
multicolinearity between all variables using the variance
inflation factor (VIF). Variables with VIF >5 were rejected
from subsequent analyses (O’Brien, 2007). Distance to
roads correlated highly with distance to human settlements,
as well as old secondary forest with suitable habitat for
chimpanzees, thus, were not included as a predictor in the
final matrix. The study sites were included in the models as
fixed factors; habitat and human features (habitat type and
suitable habitat for chimpanzees and gorillas; distance to
human settlements, to trails and to the Dja River; and
number of human signs and logging roads) were considered
covariables with each transect included as a random effect.
All two-way interactions between sites and other
covariables were also included in the models as possible
explanatory effects. We generated a series of possible
models and compared them using the AICc criterion
(Burnham & Anderson, 2002). We selected the models with
delta AICc <2 and calculated model-averaged parameter
estimates for variables in these models, as well as their rela-
tive variable importance (RVI), calculated as the sum of
Akaike weights across all the models in the set where that
variable occurred (Burnham & Anderson, 2002).
Finally, because of recent observations that gorillas nest
in trees in the Dja area (at a rate of 29%; Latour, 2010) and
chimpanzees build night nests on the ground in La Belgique
(at a rate of 3.47%; Tagg et al., 2013), we pooled all ape
nests and re-ran the model without the variable suitable
habitat, in order to assess the possible effect of an inaccurate
classification of chimpanzee and gorilla nests. If the
explanatory effects of individual species models remain the
same in the grouped model, we can presume that any poten-
tial bias would be negligible considering the aims of our
study.
Results
Habitat composition and human activity
Most habitat features did not vary significantly between
sites (Table 1), except for young secondary forest and suit-
able habitat for gorillas, which were significantly less abun-
dant in Ekom. Suitable habitat for chimpanzees showed a
nearly significant P-value. All human activity features were
significantly different between sites.
Great ape nest abundance
Ape nest abundance varied between sites (Table 1; Fig. 2).
Both chimpanzee and gorilla nests were more frequent in La
Belgique and Ekom than in Madjuh. Despite its unpro-
tected status, La Belgique (where conservation activities are
carried out) showed nest numbers similar to the protected
site, Ekom. Models tested to explain variation in chimpan-
zee nest abundance within values of delta AICc <2 included
the effect of site, suitable habitat, distance to Dja River,
human signs and logging roads (Table 2). Effect of site was
the most important in terms of its RVI, being significant
when controlling for the other variables. Ekom had slightly
Conservation research presence protects great apes N. Tagg et al.
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London
4
fewer chimpanzee nests than La Belgique, and Madjuh had
the lowest nest abundance. Site, distance to river, human
signs and suitable habitat were positively correlated, and
logging roads negatively correlated, with chimpanzee nest
abundance (Table 3).
In the case of gorilla nest abundance, only two models
were selected (delta AICc <2, Table 2); both included the
effects of site and distance to trails. As for chimpanzee nests,
site was the most important effect. This factor, as well as
distance to trails, was negatively correlated with gorilla nest
abundance, with a negative effect being found in Madjuh
(Table 3). The highest gorilla nest abundance was typical of
Ekom, followed by La Belgique and Madjuh again showed
the lowest abundance.
Models to explain grouped ape nest abundance within
values of delta AICc <2 also included site as the most
important factor in explaining the variance (Table 2). The
models revealed a negative influence of the interaction
between site and distance to Dja River, and a positive influ-
ence of distance to human settlements; however, both
factors have a lower relative importance than the effect of
site (Table 3). Thus, the grouped ape model showed the
same pattern of abundance as the individual species models.
Discussion
Evidence-based evaluation is required (Sutherland et al.,
2004; Ferraro & Patanayak, 2006; Laurance, 2013) to
support previous suggestions that researcher presence can
have a positive effect on the protection of faunal communi-
ties (Köndgen et al., 2008; Tranquilli et al., 2012; Piel et al.,
2015), as well as to understand the impacts of such benefits.
In this study, we found differences in the abundance of
chimpanzee and gorilla nests, the availability of suitable
nesting habitat and the levels of human activity features in
each site. We showed that chimpanzee and gorilla nest
abundance was largely explained by the variable ‘site’.
Explanatory variables
There was no evidence that sites differed in their overall
habitat composition as defined by habitat types. Despite
this, abundance of chimpanzee and gorilla nests varied
between sites. Chimpanzee nests were significantly more
numerous in La Belgique than Madjuh, and we found
gorilla nests were significantly more abundant in La
Belgique and Ekom than in Madjuh. We showed statisti-
cally that these differences were related to the levels of
human activity signs and availability of suitable habitats
reported at each site. Chimpanzees occur at lower densities
in areas closer to human settlements (Clark et al., 2009), and
Table 1 Observed values of analysed variables in the three study sites in the Dja Conservation Complex, East Region, Cameroon
Variable
Madjuh La Belgique Ekom Kruskal–Wallis test
Mean ±SE Mean ±SE Mean ±SE (d.f. =2)
Number of chimpanzee nests 0.68 ±0.18 1.50 ±0.33 1.43 ±0.27 –
Number of gorilla nests 0.08 ±0.04 0.48 ±0.18 0.67 ±0.30 –
Number of ape nests 0.76 ±0.18 1.98 ±0.39 2.10 ±0.38 –
Near primary forest 3.02 ±0.33 2.49 ±0.37 3.16 ±0.34 χ2=3.26, P=0.195
Old secondary forest 5.02 ±0.30 4.40 ±0.38 5.18 ±0.36 χ2=2.81, P=0.245
Young secondary forest 1.38 ±0.26 1.53 ±0.33 0.43 ±0.12 χ2=12.00, P=0.002**
Light gaps 0.66 ±0.13 0.57 ±0.12 0.49 ±0.10 χ2=0.73, P=0.694
Riparian forest 0.52 ±0.13 0.77 ±0.21 1.06 ±0.22 χ2=2.91, P=0.234
Swamps 1.40 ±0.33 2.23 ±0.37 1.69 ±0.24 χ2=4.47, P=0.107
Suitable habitat for chimpanzees 67.00 ±3.45 58.30 ±3.25 69.29 ±3.01 χ2=59.41, P=0.051
Suitable habitat for gorillas 21.56 ±2.89 22.92 ±3.38 10.39 ±1.62 χ2=12.68, P=0.002**
Distance to human settlements 10.88 ±0.25 11.38 ±0.19 15.18 ±0.24 χ2=84.76, P<0.001***
Distance to trails 1.41 ±0.13 1.31 ±0.12 3.88 ±0.14 χ2=66.60, P<0.001***
Distance to Dja River 13.09 ±0.24 4.56 ±0.23 12.03 ±0.34 χ2=102.04, P<0.001***
Number of human signs 1.04 ±0.20 0.34 ±0.09 0.86 ±0.20 χ2=8.385, P=0.015*
Number of logging roads 1.00 ±0.17 0.10 ±0.05 0.00 ±0.00 χ2=59.41, P<0.001***
Variables with significant differences between sites are displayed: *P<0.05; **P<0.01; ***P<0.001. Values are expressed as mean numbers
per transect.
Figure 2 Total number of occurrences of chimpanzee and gorilla
nests at the three study sites (Madjuh, unprotected; La Belgique,
unprotected with conservation activities; Ekom, protected) within the
Dja Conservation Complex, East region, Cameroon.
N. Tagg et al. Conservation research presence protects great apes
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London 5
avoid areas of human disturbance (Arnhem et al., 2008;
Rabanal et al., 2010; Stokes et al., 2010; Tagg & Willie,
2013), whereas gorilla populations can cope with low levels
of human activity in areas where suitable habitat is more
available (Matthews & Matthews, 2004). Previous studies
have demonstrated gorillas to have a greater tolerance to
disturbance – such as logging and proximity to roads and
settlements – than chimpanzees, as a result of their flexible
social, dietary and spatial requirements (Arnhem et al.,
2008; Clark et al., 2009; Stokes et al., 2010; Haurez et al.,
2014).
Despite being at a similar distance to trails and human
settlements, human activity signs were significantly more
frequent at Madjuh than at La Belgique, whereas Ekom is a
greater distance from such landmarks yet experienced
similar levels of human activity as La Belgique, therefore
implying that anthropogenic pressures are not determined
by site accessibility or remoteness. However, the grouped
ape model did tentatively suggest a higher abundance of ape
nests further away from human settlements and the impor-
tance of accessibility and remoteness should not be
neglected (e.g. Blom, Prins & Yamindou, 2004; Blom et al.,
2005; Struhsaker, Struhsaker & Siex, 2005): in our study, the
Table 2 Results of different GLMMs explaining variation in the number of great ape nests in relation to study site (n= 149)
kAICc Delta AICc Weight
Chimpanzee nests
St +Dr +Hs +Lr 5 675.49 0.00 0.59
St +ShC +Dr 4 676.43 0.94 0.37
St +Hs +Lr 4 682.39 6.90 0.02
St +Dr +Hs +Lr 5 684.69 9.20 0.006
St +ShC +Dr +St ×ShC +St ×Dr +St ×Hs +St ×Lr 9 686.77 11.28 0.002
St +ShC +Dr +St ×ShC 5 687.34 11.85 0.001
Hs +Lr 3 688.15 12.66 0.001
Hs +Lr 3 689.06 13.57 <0.001
Gorilla nests
St 2 912.035 0.00 0.423
Dt 2 912.056 0.02 0.419
ShG 2 914.006 1.97 0.158
Hs +ShG 3 916.469 4.43 0.001
ShG 2 919.072 7.04 <0.001
Ape nests
St 3 518.820 0.00 0.265
St +St ×Dr 3 518.962 0.14 0.247
St 3 519.170 0.35 0.223
St +Dh 4 520.740 1.92 0.102
Osf 2 521.115 2.29 0.084
Dr +Osf +Lg 4 522.652 3.83 0.039
St +Dr 3 523.472 4.65 0.026
St 2 525.394 6.57 0.009
St 2 527.662 8.84 0.003
St 2 529.513 10.69 0.001
Dr 2 531.745 12.93 <0.001
Variable codes are defined as follows: St, site; Dh, distance to human settlements (km); Dr, distance to Dja River (km); Dt, distance to trails (km);
Hs, number of human signs; Lr, number of logging roads; ShC, suitable habitat for chimpanzees (%); ShG, suitable habitat for gorillas (%); Osf,
old secondary forest (%); Lg, light gaps (%). Italics indicate models with values of delta AICc <2 and selected to explain variation in ape nest
abundance. k, number of parameters.
Table 3 Model-averaged estimates of the direction and magnitude of
the size and relative variable importance (RVI) of each effect
Variable
Parameter
estimates ±SE RVI
Chimpanzee nests
Site 4.049 ±0.373 0.99
Distance to Dja River 0.266 ±0.096 0.97
Human signs 0.064 ±0.008 0.62
Logging roads −0.147 ±0.047 0.61
Suitable habitat 0.015 ±0.0002 0.60
Gorilla nests
Site −0.282 ±0.239 0.423
Distance to trails −0.087 ±0.021 0.419
Suitable habitat 0.004 ±0.0001 0.158
Ape nests
Site 2.678 ±1.783 0.836
Site ×distance to Dja River −0.051 ±0.008 0.247
Distance to human settlements 0.013 ±0.004 0.102
Coefficients of variables resulting from all models with a total cumu-
lative weight of at least 90%.
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6
difference in these factors between sites (i.e. a difference of
∼5 km from the trail) is relatively small and unlikely to deter
use by rural-living people, corroborated by the elevated rate
of hunting signs in particular observed in Ekom compared
with La Belgique. In addition, the critical distances beyond
which remoteness no longer has an effect may be shorter
than the distances measured between sites and landmarks in
the present study. Furthermore, the global nature of our
analyses risks a mitigation of our ability to detect the
effect of potentially influential drivers of ape abundance if
overridden by a particularly strong influence in one of the
sites.
Our study offers no evidence that the potential facilita-
tion of hunter access or bushmeat transport afforded by
the proximity of a large navigable river influences human
activity levels and great ape abundance, as La Belgique is
closer to the Dja River than the other two sites but exhib-
ited lower human activity signs and similar or higher ape
abundances. Similarly, no influence of proximity to a navi-
gable river on ape abundance was previously found across
a range of great ape study sites (Stokes et al., 2010). The
grouped ape model suggests a higher abundance of ape
nests in sites located nearer to the Dja River, but this inter-
action is weak and may reflect the different locations of the
sites with respect to the river.
Our study is limited because our data do not allow us to
distinguish statistically between gorilla and chimpanzee
nests (Sanz et al., 2007). However, the majority of nests
recorded for the present study were still recent enough to use
footprints, urine, dung and smell to reliably confirm nest
builder identity (White & Edwards, 2000). Furthermore,
habitats where gorilla tree nesting is more likely to occur
(open-understorey and gallery-riparian forests; Tutin et al.,
1995) represent <10% of La Belgique, whereas density of
terrestrial herbaceous vegetation (commonly used in ground
nesting) is high (Willie et al., 2012, 2014), suggesting that
gorilla tree nesting is not likely to occur at a high rate. In
support of this, a 3-year study in La Belgique recorded a rate
of gorilla tree nesting of <10% (C.-A.P., unpubl. data). The
grouped ape model revealed the effect of site as the strongest
explanatory variable, similarly to the individual species
models, therefore indicating that any potential bias arising
from an inaccurate classification of ape nests is likely to
have had a negligible influence on our observed trends.
Given that the focus of our paper is to tease out the drivers
of ape abundance from three sites exhibiting differing
human activity and habitat features, an accurate distinction
between chimpanzee and gorilla nests is less crucial in the
present study; rather, the implications of the overall trends
arising from our models are important.
Official protection and active management
of the site
Ekom and Madjuh experienced comparable levels of
hunting activity, despite their difference in protected status,
whereas all types of human signs were significantly higher in
Madjuh than La Belgique, despite both being officially
unprotected. This specifically indicates a lack of manage-
ment of the Dja Biosphere Reserve and demonstrates that
assigning official protection to a site does not automatically
determine hunting levels (cf. the phenomenon of paper
parks; Blom et al., 2004): if wildlife abundance is to be
positively influenced, it is necessary to execute active man-
agement strategies and conservation initiatives (Stokes
et al., 2010).
Active management at La Belgique, that is, the presence
and activities of PGS since 2001, may explain the observed
lower rate of human activity and hunting, and higher ape
abundances, than those recorded at a neighbouring site with
similar physical characteristics (Tagg et al., 2011). In the
past, Madjuh experienced extensive logging disturbance and
the opening of a dense network of logging roads and trails;
and, in the absence of active management, this has resulted
in an intensive, long-term use by local people. Low great ape
abundances may reflect behavioural adaptations of apes to
avoid human activities perceived as a threat (Tagg & Willie,
2013), or be a direct result of hunting. Active management
can contribute to maintaining ape populations and prevent
rapid losses as seen elsewhere across their range (Stokes
et al., 2010; Tranquilli et al., 2012).
The specific mechanisms of wildlife protection through
research activity vary (Pusey et al., 2008; Wrangham &
Ross, 2008; Campbell et al., 2011). At La Belgique, PGS
offers a continual community sensitization of its main objec-
tive (to protect great apes) and the consequence of local ape
extirpation (departure of the project); semi-permanent
researcher presence since 2001 and a number of anti-
poaching patrols over the years have notably deterred
poaching; and a rare and direct link between wildlife pres-
ervation and personal gain is offered to the local community
through the regular or casual employment of many people
in the scientific programme. These are likely to have con-
tributed to a long-lasting amnesty on great ape killing in the
site. Protection could similarly be offered by the actions of
tourism or ranger training centres, for example, through
similar or other mechanisms.
Recommendations
We highlight the need for financial and logistic support to be
channelled into an expansion or replication of research pro-
grammes and other secondary conservation efforts through-
out ape ranges, alongside immediate and sustained primary
conservation initiatives. Conservation actions to reduce
hunting in buffer zones, where extinction rates are high
(DeFries et al., 2005), are crucial to reduce the pressures
experienced by the PA (Brashares, Arcese & Sam, 2001).
While supporting the continued existence of PAs is critical
to prevent dramatic biodiversity declines (Laurance et al.,
2012), we further advocate the support, training and moti-
vation of park management to reduce threats to great apes
and ensure their persistence in wide-scale human-disturbed
landscapes. We stress the need for targeted management
strategies by involved institutions because of the varying
threats and influences experienced in different land-use
N. Tagg et al. Conservation research presence protects great apes
Animal Conservation •• (2015) ••–•• © 2015 The Zoological Society of London 7
types. Conservation management strategies could include
ape-friendly extraction operations by timber companies
(Morgan et al., 2013), including blocking roads post-
extraction, and destroying bridges along these roads, as well
as landscape-scale measures that improve the compatibility
of human livelihoods and biodiversity conservation in areas
where wild great apes are still found.
Acknowledgements
We thank the Royal Zoological Society of Antwerp and the
Flemish Government, Belgium, for financial, technical and
logistic support, particularly Zjef Pereboom and Vera
Cuypers. We acknowledge Primate Conservation, Inc., for
part funding of the surveys, and express our gratitude to the
Ministry of Scientific Research and Innovation and the
Ministry of Forests and Wildlife, Cameroon, for permission
to conduct this research. Thanks are extended to Stéphanie
Bonnet, and to all scientific, technical and logistic staff of
PGS, with particular mention of Donald Mbohli, Berna-
dette Banyimbe, Guillaume Djang Djang, Jean-Baptiste
Tongo, Jean Assimentsel and Anicet Mabom for their hard
work and dedication to the project.
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