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Article

Valorisation of Madagascar’s Wildlife Trade and Wildlife Tourism: What Are the Conservation Benefits?

by
Angus I. Carpenter
1,* and
Franco Andreone
2
1
Institute of Science and Environment, University of Cumbria, Ambleside Campus, Rydal Road, Ambleside LA22 9BB, UK 2 Museo Regionale di Scienze Naturali, Via G. Giolitti, 36, I-10123 Torino, Italy
2
Museo Regionale di Scienze Naturali, Via G. Giolitti, 36, I-10123 Torino, Italy
*
Author to whom correspondence should be addressed.
Conservation 2023, 3(4), 509-522; https://doi.org/10.3390/conservation3040033
Submission received: 11 August 2023 / Revised: 7 October 2023 / Accepted: 1 November 2023 / Published: 14 November 2023
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Abstract

:
Wildlife tourism and wildlife trade may appear juxtaposed, but are two, potentially aligning, income generators that could benefit conservation in developing countries. Utilising data sets collated from Madagascar’s Ministère du Tourisme and CITES, respectively, for the period 2007 to 2018, this study estimated levels of income from wildlife tourism and wildlife trade for Madagascar. Between 2007 and 2018, tourism reported yearly incomes ranging from a low of USD 1.4 million up to a high of USD 15.7 million. However, it was unclear what percentage of this figure flowed to benefit local communities. Alternatively, using reported networks for the live wildlife trade, the estimated economic value reaching collectors and/or intermediaries in Madagascar was USD 72,299.80 for the period 2007 to 2018. Both revenue generators operated within different geographical areas, with tourism opportunities presenting themselves to communities adjacent to national parks, while wildlife trade networks were not restricted to protected areas and operated sporadically across Madagascar. Hence, the economic benefits reached different Malagasy participants across the country. The management of both activities needs great care to ensure that environmental impacts and sustainability are core measures on any such activities. Whilst this study shines a light on economic values and novel perspectives regarding these two trade types, it also highlights knowledge gaps, thus indicating where much greater research attentions are required to allow a better understanding of the specific benefits and risks from engaging with both trade types for local Malagasy people and their environments.

1. Introduction

1.1. Socioeconomic Aspects of Wildlife Valorisation in Madagascar

A long-standing ambition in many societies has been to seek the alignment of conservation requirements and poverty alleviation to engender mutual benefits [1,2,3,4]. The paucity of reported successful case studies highlights the complexities, juxtapositions and contested notions of justice that surround such projects [5], especially regarding efforts to improve distributive justice concerned with benefits and burden sharing [6]. One of the most persistent issues is that lower income groups pay disproportionately higher costs for conservation, whereas the rich secure most of the benefits [7,8,9].
To varying degrees, conservation benefits have been derived globally from the sustainable exploitation of wildlife resources [3,9,10,11]. Conversely, it has also been stated that wildlife traded unsustainably was a major driver causing the decline in species globally [11,12]. However, in Madagascar, the impacts from harvesting wild flora and fauna were relatively poorly known, with both illegal [9,13,14] and unsustainable harvesting having been reported within and outside of protected areas [15]. A situation that was further compounded by the high numbers of new and yet to be described species, endemic to Madagascar, which were still being reported while others were to follow [16,17].
Historically, national parks (NPs) were established in Madagascar with the over-riding aim to protect its unique biodiversity [18,19]. However, local communities in Madagascar often had little or no involvement in the establishment of NPs and other protected areas [20]. Yet local communities had received varying degrees of negative impact from their creation in many cases, as local communities were stopped from utilising these areas, and the natural resources within them, for subsistence or commerce [18,20,21,22]. Since 2003, during an expansion of almost 100 additional protected areas, the selection rationale also expanded to include cultural heritage, poverty alleviation and the sustainable use of natural resources [23]. However, local communities’ knowledge on the legal processes and legislation governing protected areas and/or species protection was mostly very poor [24] and, therefore, they were unaware of the legal status and conservation protections afforded to species and habitats.

1.2. Wildlife Tourism Revenue

An alternative to extractive approaches for valorising wildlife would be to view it in-situ in applying wildlife tourism. The World Tourism Organization (UNWTO) defines ecotourism via five characteristic statements; for example, “All nature-based forms of tourism in which the main motivation of the tourists is the observation and appreciation of nature as well as the traditional cultures prevailing in natural areas”. Each statement is broad and general in its meaning and applicability (UNWTO, no date). Variations across disciplines and sectors add further inconsistencies regarding clear and concise definitions for ecotourism, wildlife tourism and, furthermore, conservation tourism. However, tourism, across its varying formats, was often viewed as a sort of panacea to resolving potential conflicts between local peoples’ needs and NP protection, by bringing tourists to see the wildlife in situ and having associated services develop around this premise [25,26]. Hence, wildlife tourism, in its broadest sense, has often been suggested as a non-extractive method for use in Madagascar [25,27,28]. However, it is evident that tourism requires careful management to ensure long-term sustainability, from broad-scale issues, such as operator responsibility (e.g., deleterious impacts from water supply demands to waste product disposal) [29], to fine-scale issues, such as negative impacts on species populations and animal welfare [30,31,32], to minimize the potential negative impacts on Madagascar’s environments.
Several studies have estimated the economic value of tourism to a few protected areas and more generally for Madagascar. For example, at Mantadia NP, the economic values generated from tourism were estimated at USD 24–65 per individual visitor or USD 0.8–2.2 million per annum [25]. At Ranomafana NP, in 2002, it was estimated that a total of USD 29–31,246 was generated per annum with USD 15,836 going to the local communities, while lemurs were stated by visitors to be the wildlife attraction [33]. Similarly, over 600 tourists visiting different NPs in Madagascar also stated lemurs to be the main attraction, with chameleons ranked second [34]. Revenues estimated to be received by local communities at Masoala NP ranged from USD 700, in 1999, to USD 500, in 2001 [27]. A national-scale estimate of income generation via tourism was stated to be between USD 26 and 29 million, with approximately 17% of tourists to Madagascar visiting national parks [34].

1.3. Flora and Fauna Trade Revenues

In addition to their apparent lack of knowledge regarding NP and species conservation legislation [24], not all local communities were keen to engage in the live trade of wildlife for international markets (typically omitting bush meat, products and other derivatives, or domestic uses, such as medicinal plants) for several reasons. For example, individuals reported being repulsed by reptiles, while payment insecurity, fear of legal repercussions and traditional barriers to harvesting certain species were other reported concerns [35,36]. However, it has been argued that Malagasy communities should have the right to trade in their local wildlife resources [37]. Certainly, the international, live wildlife trade in Madagascar appeared to be flourishing. For example, relatively high levels of trade in flora and fauna from Madagascar have been reported in studies that meet international demands [36,38,39,40,41,42,43,44].
As to the value generated from the international wildlife trade in Malagasy flora and fauna, estimates vary greatly between product types and years. For example, Waeber and Wilmé [38] reported that illegal rosewood and ebony timber stockpiles due for export were valued at a minimum of USD 600 million, while trade conducted in 2013 alone, across all CITES listed flora and fauna, was estimated at between USD 346,246 and USD 646,226 [36]. Alternatively, various estimated values have been provided for specific taxonomic groups; such as chameleons generating over USD 14.5 million [43], amphibians traded between 2000 and 2006 reportedly generating USD 906,750 [42] or just Mantella poison frogs traded between 2001 and 2003 generating up to USD 246,372 [41]. Supply chain structures in Madagascar vary [45], though the three-actor level chain was most commonly used with collector and intermediary positions filled by Malagasy people [36,41]. However, the wildlife trade comes with potential hazards to an already challenging situation of protecting Madagascar’s wildlife, such as the potential of over-harvesting, animal welfare issues, cartel formations, the possibility of introducing the amphibian disease chytridiomycosis into new locations, etc. [17,34].
This study draws together national-scale data sets on these two forms of income generation to investigate both the levels and dynamics of the income generated. Furthermore, it compares across both forms and discuss the potential benefits and costs to Madagascar for local communities. Such information greatly enhances discussions in Madagascar and internationally, which currently lack any such comparisons, regarding advancing management options and seeking the best outcomes for conservation and poverty alleviation. This paper presents: (1) numbers of tourists and levels of income generated over the period 2007–2018; (2) the numbers of ecotourists and income generated each year over the same period; (3) the CITES listed species of flora and fauna exported from Madagascar and the numbers exported in the period 2007–2018; (4) the income generated from the trade in wildlife exported from Madagascar.

2. Materials and Methods

Tourism data were obtained by request (collated October 2019) from the Ministère du Tourisme in Madagascar. The Ministry supplied data covering the period 2007–2018 that included the total number of overseas visitors (tourists) each year and estimated income from tourism for each year (Table 1). Wollenberg et al.’s [34] value of 17% (percentage of tourists who were ecotourists) was applied to the yearly tourist numbers to provide an estimate for the number of ecotourists visiting Madagascar each year (Table 1).
To estimate the income values generated from ecotourism, the yearly number of ecotourists (Table 1) was multiplied with published conversion values presented by both Wollenberg et al. [34] and Dixon and Pagiola [25], in each case the published values were adjusted for inflation in USD to 2019. Estimation 1 was calculated using Wollenberg et al.’s [34] conversion value with yearly ecotourist numbers. Estimation 2 used Dixon and Pagiola’s [25] conversion values, who provided an upper and lower value. Hence, there were two calculations performed and two sets of estimates, upper and lower values, presented.
CITES data were obtained from the CITES Trade database (https://trade.cites.org/). These data were collated on 23 December 2019 using the following criteria; export country = Madagascar, source = wild, purpose = commercial, terms = live. These criteria were applied while the ‘Search by taxon’ was left empty to collect trade data records across all CITES listed taxa groups, animals and plants, for the period 2007–2018. These data were downloaded in an Excel format for analysis and presentation.
Flora and fauna trade prices were extracted from published literature [36,41] and adjusted for inflation, in USD, for each year over the period. For plants, there were no trade structure price data available other than a single average export price [46]. The price structure reported for animals displayed a decrease in magnitude of the order of two from export to collector; hence, it has been assumed here that a similar price structure would be observed for plants. Thus, the average plant price has been reduced by two-fold to provide a general indicator of price at the collector level.

3. Results

3.1. Ecotourism Revenue Generation

The total number of tourists arriving in Madagascar for the period 2007 to 2018 was nearly 3 million people with, on average, over 240,000 people arriving each year (Table 1). Of this number of tourists, it was estimated that the number of ecotourists visiting each year was nearly 41,000 (Table 1). Over the total period 2007–2018, ecotourism generated a total income of nearly USD 189 million using Estimate 1, nearly USD 46 million using the Estimate 2 upper value and nearly USD 17 million with the Estimate 2 lower value. On average, across the period 2007–2018, a yearly income was reported ranging from a low of USD 1.4 million up to a high of USD 15.7 million (Figure 1).
The highest level of income in any one year from ecotourists was in 2008 when it generated USD 24.6 million, while the lowest was in 2010 when USD 0.1 million was generated (Figure 2). Over 2007–2018, a linear regression analysis found no increase in ecotourism growth over the period (y = 0.0741x + 15.235; R2 = 0.002) for Estimate 1. However, any long-term trend would be masked by the significant decrease in 2010. Applying a linear regression to a subset of the data, after the crash from 2011 to 2018, the income generated from ecotourism using Estimate 1 was generally increasing (y = 0.613x + 13.454; R2 = 0.4556) back towards the high recorded in 2008 (Figure 2).

3.2. Flora and Fauna Trade Revenues

Between 2007 and 2018, a total of 286,938 individual organisms were extracted from the wild and reported being exported from Madagascar with over 83% being animals and nearly 17% plants. The exported flora and fauna were from 52 known genera; 35 (67%) plant genera and 17 (33%) animal genera.
Of the 238,961 individual animals traded, over 70% was in Reptilia, over 29% in Amphibia with minor amounts in Aves (0.3%) and Mammalia (0.002%). Reviewing the trade within the animal grouping at the genus level, the top five genera, which accounted for 97% of the trade in animals, were for amphibians of the genus Mantella (29%), while for reptiles we have Phelsuma (27%), Furcifer (25%), Uroplatus (13%) and Brookesia (3%) (Figure 3). Furthermore, within each genus just a handful of species accounted for the majority of its trade (Table 2). The top five species traded accounted for over 40.5% of the total number of animals exported; Mantella betsileo (brown mantella, n = 22,737, 9.5%), Mantella baroni (Baron’s mantella, n = 21,110, 8.8%), Furcifer pardalis (panther chameleon, n = 19,029, 7.9%), Phelsuma lineata (lined day gecko, n = 17,939, 7.5%) and Furcifer lateralis (carpet chameleon, n = 15,908, 6.74%).
Of the 47,977 individual plants traded, four genera accounted for over 84% (n = 40,382) of the exported plants from Madagascar with these four genera being Pachypodium, nearly 48% (n = 22,967), Euphorbia, over 24% (n = 11,608), Operculicarya, nearly 9% (n = 4175) and Angraecum, over 3% (n = 1632) (Figure 4). Furthermore, within each genus just a handful of species accounted for most of the trade (Table 3). The top five plant species traded accounted for nearly 47% (n = 22,504) of the total number exported; Pachypodium spp. (n = 7532, 15.7%), Pachypodium densiflorum (n = 4232, 8.8%), Pachypodium brevicaule (n = 4219, 8.7%), Operculicarya pachypus (n = 3337, 6.9%) and Euphorbia primulifolia (n = 3184, 6.6%).
Consequently, using species-specific prices that were extracted from published scientific literature and adjusted for varying yearly levels of inflation, the calculation revealed an estimated total of USD 72,300 being generated from the trade between 2007 and 2018, and potentially made available to local communities (Table 4). The animal grouping contributed the majority (USD 54,728, nearly 76%) to the total value, with the plant grouping contributing USD 17,572 (over 24%). In the year 2016, both the animal and plant groupings recorded the highest levels of income (animals = USD 7944; plants = USD 4416), but both decreased rapidly post-2016. Trade remained static until 2013 (animals) and 2014 (plants), after which both groupings increased rapidly in the levels of trade (Figure 5).
Comparing the estimated levels of income generated from both ecotourism and wildlife trade in Madagascar, a much greater level of income generation was garnered from wildlife tourism (Figure 6). Wildlife tourism reported a yearly income estimated in the millions of US dollars, while estimates of income generation from the wildlife trade were recorded in thousands of US dollars (Figure 6). However, the wildlife trade displayed a positive increase in trade (y = 305.23x + 4657.4, R2 = 0.224) (excluding 2018; as it has been reported that observed drops in trade in the latest year of reporting were more likely due to an artifact of countries’ failure to meet CITES reporting timelines than a true drop in any trade—see [45]).

4. Discussion

Over the whole time period for which data exist (2007–2018), the international live trade in herpetofauna from Madagascar generated estimated revenues totalling up to USD 401,470 that were reaching local Malagasy people. Taking just the upper estimate, for the reptile- and amphibian-focused wildlife tourism, it was valued at over USD 51 million while the general figure was estimated at USD 17–46 million. However, these revenue estimates from tourism were much greater than the income estimate calculated from the wildlife trade. However, actually how much does flow to the local people was unknown. For comparison, in just 2018, Madagascar’s top income generators ranged from; firstly, coffee, tea and spices (valued at USD 1 billion; on its own, vanilla was worth USD 855.4 million and cloves USD 149 million) to tenth place, mineral fuels, including oil (valued at USD 51.5 million) [48]. The vast differences highlighted here between top income generators and the trade in wildlife potentially offer some justification for the government of Madagascar’s apparent lack of attention and focus to issues raised by this trade type. It can sometimes be forgotten by conservationists that Madagascar’s government are often dealing with perceived greater priorities and with minimal resources.
However, it should also be remembered that this study is presenting wildlife trade data only for CITES listed species. There would also be much trade in non-CITES listed species happening in parallel to these data presented here. Therefore, the monetary values presented should be viewed as minimum values. It is known that illegal trade in wildlife exists, but, obviously, due to its very nature, this is not recorded or monitored and so not represented here, despite contributing to local economies. Furthermore, whilst CITES listed species do have non-detrimental findings (NDFs—albeit NDFs remain highly questionable in terms of the population data used and the robustness of outputs) that allow quotas to be assigned to a species limiting the number of individuals they are traded in, this is not the case for non-CITES listed species. Thus, questions over the sustainability of trade in all species of flora and fauna remain. However, presenting both flora and fauna data together within this study does allow for a more complete ‘picture’ of the wildlife trade in Madagascar, whilst highlighting that many questions remain unanswered over the sustainability and management of its wildlife.
The wildlife trade appears to exhibit greater resilience to extreme political unrest, such as that witnessed in Madagascar in 2009 when political unrest ended in a coup d’état. Conversely, the tourism sector was greatly impacted by this period of unrest, as observed in Figure 2 and Figure 6 when tourism income records extreme lows in 2010. During the period of unrest, the incumbent president’s position was challenged through national, unofficial strikes, public protest marches, which led to many confrontational flash points (such as the public clashing with the army and civilians being shot, some dying) and industries shutting down, which included travel, civil servant positions, etc.
Regarding tourism with a herpetological focus, whilst over two magnitudes of difference higher than income levels generated from the international live trade, this income and any benefits were orientated towards local communities located adjacent to the NPs. Conversely, the live trade was more likely to involve individuals who were geographically dispersed and not associated to any national park. Therefore, the two alternative sources of revenue generation are possibly complementary to each other in that they could potentially engage with different sets of local people. Therefore, they should not be viewed as single, exclusive forms of income generation, but rather sources that can operate side by side, as long as it is sustainably conducted. Thus, both avenues to the valorisation of wildlife raise not only the levels of revenue generated but also the opportunities to engage in revenue generation for a wide spectrum of local communities. However, one has to be careful of the wider dynamics involved. For example, one hotel northeast of Mahajunga, Anjajavy, attempted to train individuals from the adjacent, remote, village to work in the hotel (author, pers obs.). However, due to the multiple juxtapositions between the individuals and the western-facing hotel, the training of local people to work within the hotel and, thus, provide local benefits had very mixed results. This resulted in the hotel ceasing to try to utilize staff from the local village due to several reasons, but instead recruiting individuals with more western ‘standards’ exposure from major towns and importing them to work at the hotel but living in the local village. These new recruits were from different tribes with very different social/behavioural mannerisms, outlooks and more western experiences. Yet they were expected to be both located within the local village and welcomed by those living there. The impacts were extremely wide-ranging and both negative and positive.
Despite the short-term economic benefits, the long-term conservation impacts resulting from the existing scope and scale of the consumptive use of wildlife was increasingly being questioned [1,11]. However, the potential negative impacts following unsustainable exploitation were not limited to extractive use of Madagascar’s flora and fauna. For example, broad themed issues arising from ecotourism operators’ environmental responsibility such as the demand for water supplies or waste product disposal can have large scale, deleterious impacts on the environment [29]. Alternatively, irresponsible ecotourism can result in smaller-scale negative impacts on both the conservation and welfare of wild animals, including reptiles [31,32]. For example, tourists being brought into regular and close proximity of free-ranging wildlife can negatively impact a range of species-specific behaviours, such as breeding [49] or foraging [50]. Furthermore, the direct physical contact with wildlife taken from the wild and being brought into captivity to show off to tourists can also result in the unintentional transfer of zoonotic diseases [34] and the potential death of individual animals or affect species’ populations, including potentially threatened species. These types of negative impacts are often difficult to detect [31], while the cultural backgrounds of tourists and local Malagasy will have different attitudes and societal expectations that further complicate such decision-making [32].
Both trade types reported here, whilst generating income, raise questions over their sustainability, both from direct and indirect effects. However, it is imperative that Madagascar’s authorities seek to implement much more robust and detailed reporting of the structures operating within both trade types. For example, taxes are collected from both trade types and there are potential benefits to government, local communities and conservation from implementing better monitoring. However, presently, there is a lack of knowledge and openness as to both the supply chain networks and financial flows operating within the country. Hence, to allow both fuller evaluation and greater management of these income-generation types, much greater effort needs to be focused on reporting on and managing both supply chain networks and financial flows. This would permit adjustment of higher financial flows away from wildlife exporters/foreign businesses and more towards government and local communities; importantly raising the benefits gained by local communities from maintaining local wildlife and habitats. Considering local communities are a conservation concern in places, this could be managed to benefit both local people and conservation.
No previous study has sought to estimate and compare such complex scenarios, especially for a country that has such a high conservation profile and in need of such evidence upon which to make more robust and sustainable management decisions for the national good. Ultimately, there are positives and negatives associated with both the live trade in wildlife and ecotourism. However, it will be the long-term sustainability with minimum environmental impacts that follow both activities that managers will need to ensure going forward. These will be multi-dimensional, ranging across species and ecosystems to human dimensions, and spanning both temporal and spatial scales. Hence, balancing social demands with environmental capacity to minimise impacts and maintain sustainability should be the goal of government and managers alike.

5. Conclusions

There have been no comprehensive reviews undertaken previously on the value of these two sectors for the potential conservation benefits they offer. This study was the first that sought to contrast and compare the extent of each trade type in Madagascar. It provides a comprehensive baseline from which to further investigate these areas, but also highlights the vast differences in income generated from both. However, it also highlights the need to better understand the flow of these revenue streams to better improve their benefits to both poverty alleviation and conservation. Certainly, without a much improved understanding of the flow and divisions of income, from the country level down to the local family, studies such as this one lack the detail and nuances to best advise on the changes required. This study has highlighted the levels of incomes involved, detailed the trade networks involved, highlighted the wild flora and fauna being traded and highlighted broadscale issues. It is now incumbent on others to take the fundamentals reported in this study and add the detail to allow sensitive, adaptive management proposals that benefit both poverty alleviation and conservation equally.

Author Contributions

Conceptualization, A.I.C.; methodology, A.I.C.; formal analysis, A.I.C.; investigation, A.I.C.; data curation, A.I.C.; writing—original draft preparation, A.I.C.; writing—review and editing, A.I.C. and F.A.; visualization, A.I.C. and F.A.; project administration, A.I.C. and F.A. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

CITES species trade data were openly and freely available from the CITES Trade Database.

Acknowledgments

AIC thanks the University of Cumbria for administrative, technical support and the donations in kind towards producing this study.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. The average yearly level of income (+/− Std. Dev.) generated using the published conversion values of Wollenberg et al. [34] (Estimate 1) and Dixon and Pagiola, [25] (Estimate 2 upper and lower values) to estimate ecotourism income, based on the original source tourist data from the Ministère du Tourisme, Madagascar. All values are in USD at 2019 rates.
Figure 1. The average yearly level of income (+/− Std. Dev.) generated using the published conversion values of Wollenberg et al. [34] (Estimate 1) and Dixon and Pagiola, [25] (Estimate 2 upper and lower values) to estimate ecotourism income, based on the original source tourist data from the Ministère du Tourisme, Madagascar. All values are in USD at 2019 rates.
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Figure 2. The trends in yearly estimated values (in USD) from ecotourism in Madagascar using the published conversion values of Wollenberg et al. [34] (Estimate 1) and Dixon and Pagiola, [25] (Estimate 2 upper and lower values). All values are in USD at 2019 rates.
Figure 2. The trends in yearly estimated values (in USD) from ecotourism in Madagascar using the published conversion values of Wollenberg et al. [34] (Estimate 1) and Dixon and Pagiola, [25] (Estimate 2 upper and lower values). All values are in USD at 2019 rates.
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Figure 3. Each of the animal genera with species and numbers reported within the import data (two genera, Eupleres and Fossa, were reported in the import data set but with no data reported) exported from Madagascar between 2007 and 2018. It should be noted that Chamaeleo are not found in Madagascar and the reporting here is an artifact of data reporting within the CITES data set (Reprinted by permission of Princeton University Press).
Figure 3. Each of the animal genera with species and numbers reported within the import data (two genera, Eupleres and Fossa, were reported in the import data set but with no data reported) exported from Madagascar between 2007 and 2018. It should be noted that Chamaeleo are not found in Madagascar and the reporting here is an artifact of data reporting within the CITES data set (Reprinted by permission of Princeton University Press).
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Figure 4. Each of the plant genera with species and numbers reported within the import data (one genera, Alluaudia, was reported in the import data set but with no data reported) exported from Madagascar between 2007 and 2018 (Reprinted by permission of Princeton University Press).
Figure 4. Each of the plant genera with species and numbers reported within the import data (one genera, Alluaudia, was reported in the import data set but with no data reported) exported from Madagascar between 2007 and 2018 (Reprinted by permission of Princeton University Press).
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Figure 5. Yearly income estimates from the live trade in CITES listed animals and plants exported from Madagascar between 2007 and 2018 (Source: CITES Database).
Figure 5. Yearly income estimates from the live trade in CITES listed animals and plants exported from Madagascar between 2007 and 2018 (Source: CITES Database).
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Figure 6. Yearly income estimates from both the combined live trade in CITES listed animals and plants exported from Madagascar and the mean estimated income from ecotourism to Madagascar between 2007 and 2018.
Figure 6. Yearly income estimates from both the combined live trade in CITES listed animals and plants exported from Madagascar and the mean estimated income from ecotourism to Madagascar between 2007 and 2018.
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Table 1. The yearly number of tourists visiting Madagascar between 2007 and 2018 and the levels of income generated from those tourists, in USD as reported, in 2019, by Madagascar’s Ministère du Tourisme.
Table 1. The yearly number of tourists visiting Madagascar between 2007 and 2018 and the levels of income generated from those tourists, in USD as reported, in 2019, by Madagascar’s Ministère du Tourisme.
200720082009201020112012201320142015201620172018
Number of tourists arriving on Madagascar * 344,348375,010162,68719,052225,055255,942196,375222,374244,321293,185255,460291,299
Tourist income generation (USD millions)31345,9651785211126,24927,98139,04264,96258,538748,297668,262
Number of ecotourists (17%; Wollenberg et al., 2011 [34])58,53963,75227,657323938,25943,51033,38437,80441,53549,84143,42849,521
* denotes data source Ministère du Tourisme/PAF/ADEMA/RAVINALA AIR-PORTS/APMF (collated October 2019).
Table 2. The top five traded genera within the animal groupings exported from Madagascar over the period 2007–2018, showing the total number traded within a genus and the four highest traded species within that genus and the percentage that species accounts for within the genus in trade. (Source: CITES).
Table 2. The top five traded genera within the animal groupings exported from Madagascar over the period 2007–2018, showing the total number traded within a genus and the four highest traded species within that genus and the percentage that species accounts for within the genus in trade. (Source: CITES).
GenusSpeciesNo.%
AMPHIBIANS
Mantella 68,798
Mantella betsileo22,73733.0
Mantella baroni21,11030.7
Mantella nigricans730610.6
Mantella pulchra59698.7
REPTILES
Phelsuma 65,329
Phelsuma lineata17,93927.5
Phelsuma quadriocellata15,53423.8
Phelsuma laticauda14,12421.6
Phelsuma madagascariensis10,56316.2
Uroplatus 30,335
Uroplatus sikorae10,05933.2
Uroplatus fimbriatus617020.3
Uroplatus phantasticus500216.5
Uroplatus ebenaui420213.9
Brookesia 6686
Brookesia superciliaris192728.8
Brookesia stumpffi165724.8
Brookesia thieli132619.8
Brookesia therezieni116917.5
Furcifer 59,722
Furcifer pardalis19,02931.9
Furcifer lateralis15,90826.6
Furcifer oustaleti11,26818.9
Furcifer verrucosus11,31218.9
Table 3. The top four traded genera within the plant groupings exported from Madagascar over the period 2007–2018, showing the total number traded within a genus and the four highest traded species within that genus and the percentage that species accounts for in trade within the genus. (Source: CITES).
Table 3. The top four traded genera within the plant groupings exported from Madagascar over the period 2007–2018, showing the total number traded within a genus and the four highest traded species within that genus and the percentage that species accounts for in trade within the genus. (Source: CITES).
GenusSpeciesNo.%
Pachypodium 22,967
Pachypodium spp.753232.8
Pachypodium brevicaule421918.4
Pachypodium densiflorum423218.4
Pachypodium eburneum235210.2
Euphorbia 11,608
Euphorbia primulifolia318427.4
Euphorbia spp.122210.5
Euphorbia itremensis10889.4
Euphorbia guillauminiana10298.9
Operculicarya 4175
Operculicarya pachypus333779.9
Operculicarya decaryi43010.3
Operculicarya hyphaenoides4089.8
Angraecum 1632
Angraecum urschianum1136.9
Angraecum breve955.8
Angraecum germinyanum955.8
Angraecum teretifolium895.5
Table 4. The economic values (USD in 2019) across the three actor levels (Coll. = collector, Inter. = intermediary, Export. = exporter) generated from the reptile and amphibian wildlife trade in Madagascar for the period between 2007 to 2018.
Table 4. The economic values (USD in 2019) across the three actor levels (Coll. = collector, Inter. = intermediary, Export. = exporter) generated from the reptile and amphibian wildlife trade in Madagascar for the period between 2007 to 2018.
Animals 2007PriceValue2008PriceValue2009PriceValue2010PriceValue2011PriceValue2012PriceValue2013PriceValue2014PriceValue2015PriceValue2016PriceValue2017PriceValue2018PriceValueGrand Total
Anura 7772 7348 8076 8000 6194 6191 6815 6395 3346 6070 4140 703 71,050
Dyscophus 0.250 0.260 0.260 0.260 0.270 0.280 0.280 0.280 0.280 0.2902320.2967.281100.333342
Mantella *73070.11803.7771770.11789.4776990.11846.8976980.11846.7860030.12720.3660280.12723.3666440.12797.2863470.12761.6433460.12401.5260700.12728.438860.13505.185930.1377.0968,798
Scaphiophryne4650.25116.251710.2644.463770.2698.023020.2678.521910.2751.571630.2845.641710.2847.88480.2813.44 0.280 0.290220.296.38 0.301910
Carnivora 0 4 4
Cryptoprocta 0 0 0 0 0 0 0 0 04 0 04
Psittaciformes 0 250 300 100 650
Agapornis ^ 0.30 0.310 0.310 0.310 0.320 0.3302500.3382.53000.34102 0.340 0.340 0.3501000.3636650
Sauria 12,991 014,995 14,030 13,253 16,697 14,812 8937 11,677 14,923 24,873 17,351 2592 167,131
Brookesia2670.2566.752670.2669.423960.26102.963480.2690.485640.27152.283860.28108.082980.2883.442120.2859.369220.28258.1617810.29516.4910100.29292.92350.370.56686
Calumma 0.250 0.260 0.260 0.260 0.270 0.280 0.2802620.2873.3613260.28371.2821030.29609.8711520.29334.08280.38.44871
Chamaeleo Ϯ 0.250 0.260 0.260 0.260 0.270 0.280 0.280 0.280 0.280100.292.9 0.290 0.3010
Furcifer40790.251019.7547940.261246.4440460.261051.9645490.261182.7461160.271651.3266380.281858.6442590.281192.5254100.281514.849970.281399.1683640.292425.5655120.291598.489580.3287.459,722
Palleon 0.250 0.260 0.260 0.260 0.270 0.280 0.280 0.28060.281.68150.294.35110.293.19 0.3032
Phelsuma42730.251068.2548300.261255.855770.261450.0252030.261352.7877760.272099.5263830.281787.2435560.28995.6845390.281270.9256170.281572.7689420.292593.1873280.292125.1213050.3391.565,329
Uroplatus42970.251074.2551040.261327.0439900.261037.431530.26819.7822410.27605.0714050.28393.48240.28230.7212540.28351.1220550.28575.436330.291053.5723380.29678.02410.312.330,335
Zonosaurus750.2518.75 0.260210.265.46 0.260 0.270 0.280 0.280 0.280 0.280250.297.25 0.290250.37.5146
Serpentes 05 16 21
Leioheterodon 0.25050.261.3 0.260160.264.16 0.270 0.280 0.280 0.280 0.280 0.290 0.290 0.3021
Testudines14 03 10 2 16 8 15 16 10 11 105
Erymnochelys140.253.530.260.78100.262.620.260.52 0.270160.284.4880.282.24150.284.2160.284.48100.292.9110.293.19 0.30105
Animal total 20,777 4171.2722,351 4734.7122,116 4595.3121,271 4375.7622,891 5280.1221,019 4920.8416,010 3432.2618,387 4150.8418,285 4584.4430,953 7944.4721,506 5613.823395 923.69238,961
Plants 2007PriceValue2008PriceValue2009PriceValue2010PriceValue2011PriceValue2012PriceValue2013PriceValue2014PriceValue2015Pricevalue2016PriceValue2017PriceValue
Arecales 32.93 34.2 34.07 34.63 35.73 36.47 37 37.6 37.64 38.12 38.93
Dypsis30.330.99 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390 3
Caryophyllales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Alluaudia 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Didierea 0.330 0.340 0.340500.3517.5 0.360 0.370 0.37030.381.14 0.380200.387.6 0.390 73
Cyatheales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Alsophila200.336.6 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390 20
Euphorbiales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Euphorbia13810.33455.7310330.34351.226200.34210.83700.35129.58950.36322.216000.375927100.37262.711040.38419.5214110.38536.1819740.38750.125100.39198.9 11,608
Fabales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Senna 0.330 0.340 0.340 0.350 0.360 0.370 0.370550.3820.95020.38190.763500.38133 0.390 907
Gentianales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Pachypodium27980.33923.3424340.34827.565300.34180.29450.35330.7518760.36675.3625980.37961.2614250.37527.2511560.38439.2831750.381206.554700.382078.65600.39218.4 22,967
Liliales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Aloe3900.33128.71300.3444.2 0.340 0.3501000.3636500.3718.5 0.370 0.380 0.380 0.380 0.390 670
Orchidales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Aerangis750.3324.75350.3411.9200.346.8 0.350 0.360 0.370300.3711.1 0.3801380.3852.441430.3854.341000.3939 541
Aeranthes300.339.9550.3418.7 0.340 0.350 0.360 0.370200.377.4 0.380510.3819.38300.3811.4380.3914.82 224
Angraecum930.3330.691850.3462.9 0.340 0.350 0.360 0.370800.3729.6 0.3804600.38174.85580.38212.042560.3999.84 1632
Beclardia130.334.29 0.340 0.340 0.350 0.360 0.370100.373.7 0.380220.388.36180.386.8470.392.73 70
Bulbophyllum100.333.3400.3413.6 0.340 0.350 0.360 0.370300.3711.1 0.380730.3827.741430.3854.34880.3934.32 384
Calanthe 0.330200.346.8 0.340 0.350 0.360 0.370100.373.7 0.380150.385.7180.386.84 0.390 63
Cryptopus 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.38030.381.14 0.390 3
Cymbidiella110.333.63150.345.1 0.340 0.350 0.360 0.37050.371.85 0.38040.381.52120.384.5610.390.39 48
Cynorkis90.332.97450.3415.3 0.340 0.350 0.360 0.370600.3722.2 0.380400.3815.2940.3835.7290.393.51 257
Erasanthe330.3310.89300.3410.2 0.340 0.350 0.360 0.370 0.370 0.380160.386.08230.388.74120.394.68 114
Eulophiella30.330.99 0.340 0.340 0.350 0.360 0.37050.371.85 0.38030.381.14350.3813.3130.395.07 59
Gastrorchis20.330.66 0.340 0.340 0.350 0.360 0.370250.379.25 0.380240.389.12360.3813.68250.399.75 112
Grammangis90.332.97 0.340 0.340 0.350 0.360 0.370 0.370 0.38020.380.7660.382.2810.390.39 18
Graphorkis20.330.66 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390 2
Jumellea30.330.99300.3410.2 0.340 0.350 0.360 0.370350.3712.95 0.380450.3817.1660.3825.08500.3919.5 229
Microcoelia 0.330200.346.8 0.340 0.350 0.360 0.370600.3722.2 0.380400.3815.2600.3822.8450.3917.55 225
Neobathiea20.330.66 0.340 0.340 0.350 0.360 0.370 0.370 0.380360.3813.68160.386.08110.394.29 65
Oeceoclades1500.3349.5 0.340 0.340300.3510.5 0.360 0.370 0.370 0.38030.381.14230.388.7440.391.56 210
Oeonia30.330.99 0.340 0.340 0.350 0.360 0.370 0.370 0.380330.3812.54170.386.4630.391.17 56
Oeoniella60.331.98 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.38010.380.38 0.390 7
Phaius 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.38030.381.1430.381.1410.390.39 7
Sobennikoffia400.3313.2 0.340150.345.1 0.350 0.360 0.370 0.370 0.380 0.380120.384.5620.390.78 69
(blank)2300.3375.91030.3435.021240.3442.162040.3571.42390.3686.04 0.3703050.37112.85 0.3806410.38243.58 0.38020.390.78 1848
Rhamnales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Cyphostemma 0.330 0.340 0.340 0.350 0.360330.3712.211200.3744.4210.387.981550.3858.91250.3847.5100.393.9 464
Sapindales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Operculicarya 0.330 0.340 0.340500.3517.52310.3683.165110.37189.07840.3731.082290.3887.025450.38207.120310.38771.784940.39192.66 4175
Scrophulariales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Uncarina 0.330 0.340 0.340 0.350 0.360 0.370 0.37010.380.38800.3830.4 0.380 0.390 81
Violales 0.330 0.340 0.340 0.350 0.360 0.370 0.370 0.380 0.380 0.380 0.390
Adenia 0.330 0.340 0.340 0.350 0.360 0.370 0.37010.380.38 0.380700.3826.6 0.390 71
Zygosicyos 0.330 0.340 0.340 0.35050.361.8200.377.41790.3766.23450.3817.11630.3861.942630.3899.94200.397.8 695
Plant total 5316 1754.284175 1419.51309 445.061649 577.153346 1204.564812 1780.443193 1181.412615 993.77680 2918.411,620 4415.62262 882.18 47,977
Ϯ denotes dedicated chameleon prices extracted from Carpenter et al. [45] adjusted for inflation in USD; * denotes dedicated Mantella prices extracted from Rabemananjara et al. [41] adjusted for inflation in Malagasy Ariary value before conversion to USD. ^ denotes Agapornis prices from Reuter et al. [47]. All remaining prices were extracted from Robinson et al. [36] adjusted for yearly inflation levels in USD.
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Carpenter, A.I.; Andreone, F. Valorisation of Madagascar’s Wildlife Trade and Wildlife Tourism: What Are the Conservation Benefits? Conservation 2023, 3, 509-522. https://doi.org/10.3390/conservation3040033

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Carpenter AI, Andreone F. Valorisation of Madagascar’s Wildlife Trade and Wildlife Tourism: What Are the Conservation Benefits? Conservation. 2023; 3(4):509-522. https://doi.org/10.3390/conservation3040033

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Carpenter, Angus I., and Franco Andreone. 2023. "Valorisation of Madagascar’s Wildlife Trade and Wildlife Tourism: What Are the Conservation Benefits?" Conservation 3, no. 4: 509-522. https://doi.org/10.3390/conservation3040033

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