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Keywords:

  • biogeographic analyses;
  • bushmeat markets;
  • mammals;
  • protected areas;
  • threatened species;
  • análisis biogeográfico;
  • áreas protegidas;
  • especies amenazadas;
  • mamíferos;
  • mercados de vida silvestre

Abstract

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

Bushmeat markets exist in many countries in West and Central Africa, and data on species sold can be used to detect patterns of wildlife trade in a region. We surveyed 89 markets within the Cross–Sanaga rivers region, West Africa. In each market, we counted the number of carcasses of each taxon sold. During a 6-month period (7594 market days), 44 mammal species were traded. Thirteen species were on the International Union for Conservation of Nature (IUCN) Red List or protected under national legislation, and at least 1 threatened species was traded in 88 of the 89 markets. We used these data to identify market groups that traded similar species assemblages. Using cluster analyses, we detected 8 market groups that were also geographically distinct. Market groups differed in the diversity of species, evenness of species, and dominant, prevalent, and characteristic species traded. We mapped the distribution of number of threatened species traded across the study region. Most threatened species were sold in markets nearest 2 national parks, Korup National Park in Cameroon and Cross River in Nigeria. To assess whether the threatened-species trade hotspots coincided with the known ranges of these species, we mapped the overlap of all threatened species traded. Markets selling more threatened species overlapped with those regions that had higher numbers of these. Our study can provide wildlife managers in the region with better tools to discern zones within which to focus policing efforts and reduce threats to species that are threatened by the bushmeat trade.

Mapeo de Sitios Críticos para Especies Amenazadas Comercializadas en Mercados de Vida Silvestre en la Región de los Ríos Cross-Sanaga

Resumen

Los mercados de vida silvestre existen en muchos países en África Occidental y Central, y los datos de especies vendidas pueden ser utilizados para detectar patrones de comercialización de vida silvestre en una región. Muestreamos 89 mercados en la región de los ríos Cross-Sanaga, África Occidental. En cada mercado, contamos el número de individuos de cada taxón en venta. Trece especies estaban en la Lista Roja de la Unión Internacional para la Conservación de la Naturaleza (UICN) o protegidas bajo legislación nacional, y al menos una especie amenazada era comercializada en 88 de los 89 mercados. Utilizamos estos datos para identificar grupos de mercados que comercializaban ensambles similares de especies. Mediante el análisis de clúster, detectamos 8 grupos de mercados que también distintos geográficamente. Los grupos de mercados difirieron en la diversidad de especies y en las especies dominantes, prevalentes y características. Mapeamos la distribución del número de especies amenazadas vendidas en la región de estudio. La mayoría de las especies amenazadas eran vendidas en mercados muy cercanos a dos parques nacionales, Parque Nacional Korup en Camerún y Río Cross en Nigeria. Para evaluar si los sitios críticos de comercialización de especies amenazadas coincidía con los rangos de distribución conocidos para esas especies, mapeamos el traslape de todas las especies amenazadas comercializadas. Los mercados que vendían más especies amenazadas se superponían con aquellas regiones con mejores herramientas para definir zonas en las cuales enfocar esfuerzos de vigilancia y reducir presiones sobre las especies que están amenazadas por el comercio de vida silvestre.


Introduction

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

Throughout West and Central Africa, animal carcasses from a large variety of species are sold in bushmeat markets (Juste et al. 1995; Fa et al. 2000; Fa 2007). Mammals make up the bulk of the trade and there is compelling evidence that this negatively affects many species (Fa et al. 2003; Brashares et al. 2011). Overexploitation is more severe for large-bodied and slow-reproducing species, most of which are already classified as threatened by the International Union for Conservation of Nature (IUCN) and are prohibited as quarry for hunters by national legislation.

Bushmeat trading points exist in almost every town and village throughout West and Central Africa, and data collected from these have been used to elucidate patterns of bushmeat consumption in large regions (Macdonald et al. 2011, 2012b). Two main attributes of market dynamics are often measured: quantity and daily availability of each species (Juste et al. 1995). The markets are visited regularly (every day to once a week) and a sample of traders (or all, depending on the size of the market) is interviewed about the species, meat condition, and quantities sold.

Market studies in a number of west and central African countries have focused on effects of the bushmeat trade on biological sustainability (Fa et al. 1995; Cowlishaw et al. 2005). However, few multisite investigations have identified trade hotspots. Spatial modeling and biogeographical analyses are suitable for this purpose, where risk maps showing spatial visualizations of bushmeat trade are useful for prioritizing surveillance and control activities across large regions.

We explored the topology of a network of 89 bushmeat markets within the Cross–Sanaga region in southwestern Nigeria and southeastern Cameroon (Fa et al. 2006). Although these data were collected almost a decade ago, they are useful for investigating generic linkages between the species and numbers of animals traded and the distribution of threatened species in the region. We used simple biogeographic analyses to identify similarities in the assemblages of species sold across the sampled bushmeat markets. We then mapped trade hotspots for bushmeat species classified by IUCN (2011) as threatened. We used distribution maps of all IUCN threatened species sold in markets to determine locations of high concentrations of these species. By overlaying this richness map with recorded trade of these species, we sought to identify locations of higher hunting pressure as evidenced by the number of carcasses on sale in bushmeat markets. These sites are where surveillance and control activities might be required. Such information could lead to more effective use of the scarce wildlife resources in Nigeria and Cameroon and thus to the protection of species of high conservation value. The standardization of our methodology could serve as a model for bushmeat species monitoring and conservation prioritization in other African regions and elsewhere, where concentrations exist of species sold in open markets.

Methods

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

Study Area

Our study region (35,324 km2 total; 10,795 km2 in Nigeria and 24,529 km2 in Cameroon) stretches from the Cross River in southeastern Nigeria, along the coast as far south as the Sanaga River in Cameroon, and inland up to 300 km (Fig. 1). The area has low topographic relief, is covered by humid tropical forests at the eastern and western margins, and rugged topography with montane forests in the foothills of the Nigerian–Cameroonian Mountains (WWF 2006). High humidity is constant, and temperatures range from 15 °C to 33 °C. The wet season lasts from April to October. The region contains populations of the Cross-River gorilla (Gorilla gorilla diehli), Nigeria-Cameroon chimpanzee (Pan troglodytes ellioti), mainland drill (Mandrillus leucophaeus leucophaeus), and forest elephants (Loxodonta cyclotis) (Oates 1999). In both countries, hunting these and other threatened species is by national law prohibited.

image

Figure 1. Map of the study area between the Cross River in Nigeria and the Sanaga River in Cameroon. Only the protected areas that existed at the time of the study are demarcated.

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At the time of our study, there were 2 national parks (Cross River National Park [CRNP] in Nigeria and Korup National Park in Cameroon) and 2 wildlife sanctuaries (Afi Mountain in Nigeria and Banyang-Mbo in Cameroon). The CRNP is divided into 2 divisions, Oban and Okwangwo, and covers 3586 km2. Korup National Park is 1256 km2. As of 2013 there are 3 new national parks in the study area: Bakossi, Takamanda, and Mt. Cameroon. Hunting is not allowed in protected areas in either country.

At the start of the study, the human population in the study area was around 5 million people (1 million in Nigeria and around 4 million in Cameroon). The majority of the population was, and still is, concentrated in large conurbations (Calabar, Nigeria, and Douala, Cameroon) and their municipalities. Approximately 33% of the human population lives in Calabar, whereas about 37% are concentrated in Douala (Fa et al. 2006).

Bushmeat Data

We monitored the sale of mammals as bushmeat in 89 markets (42 in Nigeria and 47 in Cameroon) from August 2002 to January 2003. Although reptiles, amphibians, and birds were also sold as bushmeat, mammals made up >90% of all carcasses sold throughout the region (Fa et al. 2006). We sampled a mean of 142.3 market days (SE 5.0, range 29–148) in Nigeria and 152.2 market days (SE 1.40, range 100–167 d) in Cameroon. The total number of market days during the study period was 7594, 4936 in Nigeria and 2658 in Cameroon. Twelve local field assistants (5 in Cameroon, 7 in Nigeria) were trained and managed by the research team. Each field assistant was responsible for overseeing a group of bushmeat markets (4–9 each), where local reporters (over 300 total) collected data. Assistants recruited, paid, and monitored local reporters. They also assembled and checked the data sheets. At each market, reporters recorded the vendor, species, condition (dried, smoked, fresh, or live), and sale price (in Nigerian Nira or Cameroonian CFA francs) of each item. Reporters also recorded the hunting method used for each animal sold and whether the carcass was sold for local consumption or for a larger market.

Because markets were not active every day, we calculated the average number of carcasses per species per day from the total number of carcasses divided by all sample days (including the days when no trade was recorded). To estimate annual trade per species, we multiplied the average number of carcasses sold per day by 365. Annual biomass sold was then estimated from the total number of carcasses of each taxon sold in a year multiplied by the average body mass of the species (adult weights of male and female combined) (Fa & Purvis 1997). We calculated the mean body mass of all mammal species sold in each market and the average body mass of species traded during the study period.

For each market site, we counted the number of carcasses of species classified by the IUCN as near threatened, vulnerable, endangered, or critically endangered (Baillie et al. 2004). In both countries, these species were also listed as protected; thus, it was illegal to hunt them and they were banned from international trade (Cameroon, Djeukam [2007]; Nigeria, LAGA [2012a]). Six species of least concern were protected in one or both countries (Supporting Information). One species, the straw-colored bat (Eidolon helvum), considered near threatened by the IUCN, was not on the national lists of protected species for either Nigeria or Cameroon.

Market Similarities

We used the Jaccard similarity index (J) to create a matrix of faunistic similarities between bushmeat markets (Jaccard 1908):

  • display math(1)

where A is the number of bushmeat species sold in market a, B is the number of bushmeat species sold in market b, and C is the number of bushmeat species sold in both markets a and b. Completely coinciding species compositions produce a J value of 1, whereas dissimilarity is represented by 0. This index is unaffected by double absences and has an associated probabilities table to determine the significance of the similarity values obtained (Real & Vargas 1996).

We used the unweighted pair group in an arithmetic mean (UPGMA) cluster analysis to classify similarities between bushmeat markets. We represented these market similarities as a dendrogram (Kreft & Jetz 2010). The null model was that similarities between bushmeat markets are consistent with each species being equally likely to be found at each location. We used the table of critical similarity values of the Jaccard similarity index (Real 1999) to perform exact randomization tests, where the observed similarity values are compared with all possible outcomes (Sokal & Rohlf 1981). Similarity values >95% and <95% of outcomes were significant similarities and significant dissimilarities, respectively, and the rest of the values were consistent with the null hypothesis (0) (for more details, see Real et al. [1992], Márquez et al. [2001], and Olivero et al. [2011]).

By examining the classification tree from the lowest to the highest similarity node, we searched for strong boundaries, defined by significant dissimilarities between market groups (McCoy et al. 1986; Real et al. 1992; Márquez et al. 2001). In the dendrogram, a boundary between 2 market clusters was defined when DS = 1 (DS is the degree to which there is a strong boundary between 2 market clusters) or DS > 0 and DS was significant (p < 0.005). If the internal homogeneity (IH) value was >0 and significant, G(IH) indicated the presence of similarity clusters, where G is a G test of independence (Sokal & Rohlf 1981). These similarity clusters were regarded as the market. Details on how we estimated DS and IH are in Olivero et al. (2011, 2013).

For each market group, we also identified a species that was characteristic of the group (i.e., a preferred species) by comparing the observed frequency of each species in the market group (o) with its expected frequency e (i.e., the frequency of the species when all the markets were considered as a whole) (Carey et al. 1995). We used the preference index

  • display math(2)

which is related to the contribution to χ2 as indicated by the relation

  • display math(3)

where sums are taken over market groups and n is the number of markets in each market group. We considered a species a characteristic species for a market group if P for this market group was positive and P for all the other market groups was negative, provided that χ2 was statistically significant.

The number of dominant species (D) within each market, or the taxa most frequently sold relative to other species for sale, was obtained from the expression

  • display math(4)

where e is the basis of the natural logarithm and is the Shannon diversity index.

We considered a species was prevalent if it was sold in over 80% of markets and a species representative if it was traded in 50–80% of markets.

Threatened Species Mapping

We used proportional symbols to map locations of bushmeat markets according to the number of threatened species sold in each. We extracted range data for those threatened species appearing in markets from the 2012 Red List Spatial Database for Mammals (IUCN 2012). We then used the count overlapping polygons extension (B. Smith, unpublished) in ArcView (version 3.3) GIS software (ESRI, Redlands, California) to calculate species richness for each grid square based on a series of the species’ distribution polygons.

Results

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

Forty-four mammal species were traded across all markets (Supporting Information). The mean number of carcasses traded per market (total 7594 market days) was 2410.1 (SE 342.9), and it represented a mean biomass of 16,523.0 kg (SE 2315.1) per market.

Market Groups

Similarities in the species composition of all markets indicated 8 distinct market groups (MGx) (Figs. 2, 3, & Supporting Information). The largest market group, MG2, occupied the central portion of the study area from the western perimeter of the Banyang Mbo Wildlife Sanctuary (BMWS) and Korup National Park across the border into the CRNP–Oban Division. Market group 3 also occupied a relatively large area from around the CRNP Oban sector in Nigeria extending to the south into the Calabar area. Market group 8 was in the eastern portion of the study area, close to BMWS. Market group 4 was characteristic of the lowlands north of Mount Cameroon, Market group 5 was associated with Mount Cameroon itself.

image

Figure 2. Dendrogram of species similarities among markets and market groups classified on the basis of cluster analyses.

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image

Figure 3. Map indicating market sites and market groups (lines).

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The mean proportion of species sold within each market group relative to the total number of species traded in the region ranged from 19.1% in MG6 to 76.6% in MG4. Species diversity ranged from 1.54 to 2.35 (Table 1). Threatened species appeared in all market groups, from 1 (7.1%) in MG1 to 11 (78.6%) in MG4.

Table 1. Main characteristics of bushmeat species composition in defined market groupsa within the Cross–Sanaga rivers region
MarketNumber ofTotal number of speciesNumber of threatenedHʹ (speciesHʹ/lnSDominantNumber of prevalentRepresentative
groupamarketstradedspecies tradeddiversity)(evenness)speciesspeciesspeciesb
  1. a

    Market groups were identified using cluster analyses to determine clusters of markets that traded similar species assemblages.

  2. b

    A representative species is one traded in 50–80% of markets.

MG111411.790.685.9614
MG2423391.950.567.37122
MG3152481.560.494.8674
MG41236112.140.68.7493
MG572272.080.678.06102
MG61921.540.74.659
MG712592.350.7310.4825
MG881831.550.544.9545

Threatened species accounted for an average of 23.29% (10.17) of bushmeat biomass by volume (minimum 1192.8 kg/year in MG1; maximum 87,902.6 kg/year in MG2) (Table 2). The mean proportion of total biomass traded that was from threatened species ranged from 3.2% in MG3 to 84.5% in MG6.

Table 2. Bushmeat biomass traded per annum within defined market groups in the Cross–Sanaga rivers regiona
  TotalBiomass/Biomass threatenedBiomass threatenedPercent threatened
MarketNumber ofbiomass/market/yearspecies/marketspecies/market/species of
groupbmarketsyear (kg)(kg)group/year (kg)year (kg)total biomass
  1. a

    Figures are based on 4936 market days sampled in Nigeria and 2658 market days in Cameroon.

  2. b

    Market groups were identified using cluster analyses to determine clusters of markets that traded similar species assemblages.

MG1112,912.912,912.91,192.81.192.89.2
MG242662,894.115,783.287,902.62.092.913.3
MG315399,770.024,985.612,696.6793.53.2
MG412246,324.818,948.130,406.02.338.912.3
MG5717,532.92,504.71,282.2183.27.3
MG619,873.19,873.18,345.98,345.984.5
MG7166,248.966,248.933,02.733,002.749.8
MG8854,988.66,873.63,708.4463.66.7

Mean body mass of species in all market groups was low, ranging from 5.8 kg in MG5 to 44.0 kg in MG6. Compared with the mean body mass of all mammal species traded (Fig. 4) in each market group, the actual mean body mass of the species traded in each group was significantly lower (Z = −2.521; p = 0.012). This means small-bodied species contributed significantly more to the total biomass traded within all market groups than expected from the body mass characteristic of all species appearing in the market.

image

Figure 4. Mean body mass of all carcasses of mammal species traded in each market group and the mean body mass of all species represented in each market group.

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Species by Market Groups

Only 3 species were traded exclusively in a single market group: black-footed mongooses (Bdeogale nigripes) and leopards (Panthera pardus) in MG8 and Peters’ duiker (Cephalophus callipygus) in MG7 (Supporting Information). Therefore, most market groups were characterized by the combination of species sold within them, rather than by the presence of species not shared with other markets.

Thirty-four species were dominant in all markets, of which 18 species were dominant in at least half of the markets within each market group (Supporting Information). Ten of the 34 dominant species were threatened, of which 4 were dominant in at least half of the markets in each market group (red-eared guenon [Cercopithecus erythrotis], Preuss's guenon [Allochrocebus preussi], drill [M. leucophaeus], Preuss's red colobus [Piliocolobus preussi], black colobus [Colobus satanas], collared mangabey [Cercocebus torquatus], chimpanzee [Pan troglodytes], African white-bellied pangolin [Phataginus tricuspis], black-bellied pangolin [Uromanis tetradactyla], forest elephant [Loxodonta cyclotis], and straw-colored fruit bat).

The brush-tailed porcupine (Atherurus africanus) and the greater cane rat (Thryonomys swinderianus) were prevalent in all market groups. The blue duiker (Philantomba monticola) and the bay duiker (Cephalophus dorsalis) were prevalent in 7 and 6 market groups, respectively. This means that the most frequently encountered taxa across all markets consisted of relatively small-bodied species that were not threatened. Threatened species appeared as prevalent species in only a small number of market groups.

Threatened Species Trade Hotspots

We detected trade of threatened species in 88 of the 89 (98.9%) markets. A clear zone of higher trade in threatened species extended from Douala in the southeast to Loum and Manyemen (Cameroon) and Ikom and Abragda (Nigeria) in the northwest (Fig. 5). This area of higher in threatened species followed the main roads from Douala to the town of Ikom and occurred in the overlap of distribution of up to 11 threatened species in the area from the Cross River to the Korup National Parks.

image

Figure 5. Number of carcasses of threatened species sold by market and associated overlap of the distribution ranges of those threatened species.

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Discussion

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

We used analytical tools commonly used in biogeography to determine spatial patterns of bushmeat sales in the study area. Species sold could be grouped into 8 statistically distinct market groups; some species were sold in just a single market, whereas others were sold in as many as 50% of all markets. Around 80% of the species sold were common to all market groups. Although information on the fauna directly surrounding each market was not available, our results showed that market groups were distinct with regards to species sold. The largest market group occupied the center of the study area in the midst of clearly defined western, eastern, and southern groups. In all market groups, small-bodied species such as the blue duiker and brush-tailed porcupine dominated both numbers of carcasses and biomass sold.

Threatened (and nominally protected) species were sold in a very high proportion of markets sampled. The appearance of threatened species in the markets indicated widespread hunting and trade of species that are protected by law in both countries. However, numbers and biomass of threatened species sold varied substantially among market groups. This was because market groups (MG6 that stretched along the Cross River and MG2 between Korup National Park and BMWS) that were closer to the more intact forest blocks and contained protected areas, as shown by Fa et al. (2006), were areas where threatened taxa were more abundant. Preuss's red colobus, endemic to the Cross-Sanaga, is found primarily in the Korup National Park; smaller populations are found in the CRNP–Oban Division in Nigeria and in the protected Ebo forest, north of the Sanaga River (Oates et al. 2008). This species was sold in markets closest to Korup National Park and in the Calabar market, across the border in Nigeria, confirming that roads and access points enable movement of species from the parks to relatively distant markets. Likewise, the western lowland gorilla, guereza (Colobus guereza), moustached monkey (Cercopithecus cephus), Peter's duiker, and the black colobus, which occur beyond the Sanaga River to the east and north of our study area, appeared in markets in Douala and Manyemen, up to approximately 40 km or more from their source. Results of other studies confirm that hunting occurs inside parks within our study area (Linder & Oates 2011). We found substantial evidence to support an urgent need to enforce adequate protection of a range of threatened species in protected areas (Macdonald et al. 2012a).

Monitoring and perhaps even banning bushmeat transport along the main routes in the region would be an important, although short-term, solution. Roads are easily accessed in the 2 countries and within the Cross River State in Nigeria and the Southwest Province in Cameroon, and road access remains the major problem in the control of illegal bushmeat trade. Most markets in our study were within 5 km of a road (Macdonald et al. 2012b); a condition that is also typical of approximately 40% of forests in Central Africa (Wilkie et al. 1992). Consequently, the similarity in species sold in the Calabar market and markets around Korup National Park may indicate that Korup-hunted animals can be easily transported to Calabar. The situation is likely to worsen because hunting pressure will grow as road networks expand and the area of forest accessible to hunters increases, as observed in many tropical forest regions (e.g., Peres & Lake 2003; Laurance et al. 2006).

Longer-lasting solutions to hunting of threatened species will have to rely on less draconian measures, such as community-run wildlife management areas (Thirgood et al. 2004; CBD 2013). By pinpointing hotspots of trade in threatened species, it should be possible to pinpoint where policing effort should be increased and where illegal bushmeat hunting could be decreased through financial incentives (Wright & Priston 2010; LHBI 2013) or alternative-income programs (Nkonyu & Dunn 2009). The ultimate aim may be to develop locally appropriate mitigation strategies to reduce local people's reliance on bushmeat, especially threatened species.

Similar to density mapping used to identify crime hotspots in cities (e.g., Burgess 2011), our results provide a measure of the number of illegal hunting incidents occurring within a specified area. Although our data were collected from 2002 to 2003, the areas delimited in our map as containing high numbers of threatened species are consistent with findings of recent investigations undertaken in the Cross–Sanaga region (LAGA 2012b). It is likely that even though the situation may have changed in terms of volume of bushmeat extracted, the geographical patterns of extraction of threatened species is likely to still be the same, primarily because these taxa are concentrated around specific regions, namely large national parks.

The present scale and intensity of commercial bushmeat hunting occurring in the Cross–Sanaga rivers region threatens already severely threatened species, such as primates, large ungulates, and elephants. Our results indicated that the highest volume of bushmeat traded in the region is derived from a small number of highly productive species, which is consistent with the results of Fa et al. (2007). Thus, ending the trade completely could damage the livelihoods of local people for whom it provides both an important source of income and animal protein. One possible solution is to bring trade of these highly productive species into the formal economy, with regulation and taxation as suggested by Wilkie et al. (2006).

Collecting reliable information on the trade of threatened species as bushmeat is difficult because informants may be unwilling to discuss their involvement to avoid incriminating themselves (St. John et al. 2010; Jenkins et al. 2011; Keane et al. 2011). Prohibited species can be hidden from view and offered to clients on their request. Equally, forbidden taxa may be on sale as unrecognizable meat portions. Whether more carcasses of threatened species were being sold than our figures show is difficult to ascertain. Feedback from our field assistants suggested that bushmeat sellers were open to being scrutinized and that threatened species such as chimpanzees were either already on display or shown to the assistant. All personnel employed by our project for data collection were local residents and thus were not treated with suspicion. Nonetheless, it is possible that some species sold as smoked meat were unrecognizable to our observers. In such cases, DNA barcoding offers promise as an effective tool for monitoring poaching and commercial trade of threatened species, especially when investigating semiprocessed or morphologically indistinguishable wildlife products (Eaton et al. 2010). Further research should explicitly consider incentives faced by informants to promote honesty and attempt to triangulate evidence from multiple sources where possible. Investigations that attempt to reveal whether questions may not be honestly answered would be a crucial next step.

In our study region, the prohibition of killing species protected by law is regulated in principle. In practice, however, this is rarely enforced, even in and around protected areas. The number of threatened and prohibited species appearing in markets in our study provides evidence that the regulation of illegal hunting is ineffective. Monitoring adherence to rules and agreements and punishment for infractions are essential parts of successful conservation and natural resource management (Rowcliffe et al. 2004) and need to be applied in the Cross–Sanaga region. Illegal hunting could be substantially reduced if the effort devoted to law enforcement were increased. However, with limited resources available for conservation initiatives, particularly in the developing world, enforcement at a level that produces no infractions is prohibitively expensive.

Techniques for maximizing positive engagement of communities have been proposed (Keane et al. 2008). Such approaches are likely to be more effective because laws are necessary but not sufficient if people are unaware of the conservation status of different species. A number of factors affect compliance with laws (Keane et al. 2008), and compliance is higher in communities where people are aware of the rules (Keane et al. 2011). Steps should be taken to raise awareness where it is lacking, but awareness is only the first step toward achieving compliance. Within our study region, further work is needed to understand how to efficiently raise awareness of laws protecting species and the extent to which changes in awareness translate into changes in compliance. In particular, improved understanding of the factors that affect hunters’ decisions to hunt threatened species, as well as market sellers’ decisions to sell these species, can be used to develop robust, successful, and scientifically informed policies to promote behavioral change (Waylen et al. 2010). Stakeholder involvement is a likely factor in changing human behavior, as has been highlighted in previous studies (Cochrane et al. 1998; Bunnefeld et al. 2011). Accounting for human livelihoods is also important when advancing conservation interventions. Recent work highlights the importance of livelihoods in conservation and outlines a framework for balancing multiple objectives, such as land-use planning, that aims to secure local livelihoods while conserving land potentially important for threatened species (Nackoney & Williams 2013). Although many researchers have focused on very local scales, our results confirm the importance of scaling up to larger regions. Further work should explore how data such as ours could be used to achieve a balance among multiple social, economic, and conservation objectives (Bunnefeld et al. 2011; Milner-Gulland 2011).

Acknowledgments

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

This study was funded by the U.K. Government's Darwin Initiative Fund (project 162/10/004). We are grateful to our locally recruited staff in Cameroon and Nigeria. P.J. thanks the John Ellerman Foundation for their support. Useful comments on the manuscript were received from C. Astaras.

Supporting Information

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

The list of traded species (Appendix S1), results of analyses for determining the similarity boundaries among market groups (Appendix S2), and a list of characteristic species (Appendix S3) are available online. The authors are solely responsible for the content and functionality of these materials. Queries (other than absence of the material) should be directed to the corresponding author.

Literature Cited

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information
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Supporting Information

  1. Top of page
  2. AbstractResumen
  3. Introduction
  4. Methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. Supporting Information
  9. Literature Cited
  10. Supporting Information

Disclaimer: Supplementary materials have been peer-reviewed but not copyedited.

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Appendix S1

Appendix S2

Appendix S3

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