Trade-Offs Between Biodiversity Conservation and Economic ...

Environmental Management (2012) 50:633–644 DOI 10.1007/s00267-012-9888-4

Trade-Offs Between Biodiversity Conservation and Economic Development in Five Tropical Forest Landscapes Marieke Sandker • Manuel Ruiz-Perez Bruce M. Campbell

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Received: 28 May 2010 / Accepted: 23 May 2012 / Published online: 25 July 2012 Springer Science+Business Media, LLC 2012

Abstract This study explores how conservation and development are interlinked and quantifies their reciprocal trade-offs. It identifies interventions which hold a promise to improve both conservation and development outcomes. The study finds that development trajectories can either be at the cost of conservation or can benefit conservation, but in all cases sustained poverty negatively affects conservation in the long term. Most scenarios with better outcomes for conservation come at a cost for development and the financial benefits of payments for environmental services (PES) are not sufficient to compensate for lost opportunities to earn cash. However, implementation of strategies for reducing emissions from deforestation and forest degradation in locations with low population densities come close to overcoming opportunity costs. Environmental services and subsistence income enhance the attractiveness of conservation scenarios to local people and in situations where these benefits are obvious, PES may provide the extra cash incentive to tip the balance in favor of such a scenario. The paper stresses the importance of external factors (such as industrial investments and the development of the national economy) in determining landscape scale outcomes, and suggests a negotiating and visioning role for conservation agencies.

M. Sandker (&) M. Ruiz-Perez Autonomous University of Madrid (UAM), Ecologıá, Mo´dulo C/Despacho 208 Campus de Cantoblanco C/Darwin 2, Madrid, 28049 Madrid, Spain e-mail: [email protected] B. M. Campbell Department of Agriculture and Ecology, University of Copenhagen, Challenge Program on Climate Change, Agriculture and Food Security (CCAFS), Copenhagen, Denmark

Keywords ICDP Participatory modeling PES REDD Scenarios

Introduction Conservation and development are strongly linked in tropical forest landscapes. For several decades, integrated conservation and development projects (ICDPs) have attempted to improve conservation and development outcomes simultaneously but their results have not met expectations: they often achieved little for development while biodiversity wasn’t effectively preserved either (Kremen and others 1994; Wells and others 1999; McShane and Wells 2004). Arguments about their failure have tended to be polarized—conservation biologists claim that development is inherently achieved at the cost of conservation and that ICDPs are a contradiction in terms (Oates 1999; Terborgh 1999). Meanwhile, social scientists blame a top-down approach driven by a conservation agenda with inequitable outcomes for local people for the failure of ICDPs to deliver results (Chapin 2004; Christensen 2004). Less one-sided arguments for the apparent difficulties to effectively reconcile conservation and development are given by Salafsky and Wollenberg (2000), and Malleson (2002). They argue ICDP implementers need to have a better understanding of dynamics and relationships in complex landscapes and they need to recognize that tradeoffs occur between conservation and development outcomes. Agrawal and Redford (2006) analyzed 37 peerreviewed writings on the poverty–biodiversity link and find that 34 of the 37 studies ‘‘focused on processes and outcomes in a single case and single time period without taking into account the relations between outcomes and contextual features of programmatic interventions.’’ These

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arguments suggest that we need to take a systems view of landscapes where ICDPs are being implemented, in order to understand the context, reciprocal relationships between conservation and development, and external drivers influencing projects’ outcomes. Direct payments for environmental services (PES) have been proposed as a means of complementing or improving ICDP strategies (Wunder 2005). PES are payments made to land users or owners as an incentive for them to manage ecosystems to provide certain environmental services, such as maintenance of water quality and quantity, carbon storage or wildlife conservation. PES made to poor people living in or near the forest may help lift them out of poverty while simultaneously conserving their resources and the environmental services they provide. Strategies that aim at reducing emissions from deforestation and forest degradation (REDD) are a form of PES. Payments are made to governments, regional authorities or local people as an incentive to manage forests responsibly and ensure that carbon stored in forests is not released to the atmosphere through deforestation and forest degradation. In this study we took a system view of five tropical forest landscapes where ICDPs are active. Together with ICDP staff and others working in the landscapes, models were built to represent the most important socio-economic and ecological aspects, and to simulate their dynamics and the effect of the ICDP. Potential future pathways were explored and possible trajectories of conservation and development outcomes over the next 20 years were visualized. Trade-offs between conservation and development outcomes were quantified, and the extent to which PES can overcome these trade-offs explored. Finally, we attempted to identify interventions with potential to improve both conservation and development outcomes.

Methods The Study Locations Five landscapes were included in this study (Table 1). Two landscapes were located in south-east Asia and three in west and central Africa:

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Malinau District, east Kalimantan, central Indonesia; Kaimana District, Papua, east Indonesia; Wasa Amenfi District, south-west Ghana; The South East Technical Operational Unit, south-east Cameroon; Dzanga-Sangha landscape, south-west Central African Republic (CAR).

Selected landscapes all include high biodiversity forest areas, of which a part is protected in national parks or forest reserves, and all are home to people living in poverty. In all landscapes, projects or the government are attempting to deliver both conservation and development objectives. System Dynamics Modeling System dynamics modeling was used to conceptualize the landscapes in which ICDPs operate and to simulate the complex interactions taking place over time. The system dynamics software STELLA—a so-called stock and flow modeling language—was used as modeling platform. Stocks are studied parameters such as primary forest, wildlife or human population. Flows add dynamics to the stocks, for example, deforestation, hunting and immigration. The models were created by stakeholders working in the landscape assisted by a model expert facilitator. Stakeholders included staff from conservation and development organizations and ICDPs, government officials, researchers, and in the case of Ghana, farmers and logging company personnel. The models each included between 180–590 variables. Best available data were used much of which were unpublished but equal to or exceeding the quality of information on which decisions are currently made. Data were obtained from project inventories and reports, household surveys, government statistics, literature, satellite images and expert approximations. Table 2 provides an overview of the sectors included in each model, a summary of their contents and data sources. Following the model construction, one or more parameters (which indicate the conservation and development status) are selected from the model and plotted on graphs. As such, when running a simulation the graphs display how the parameter values change over time enabling us to

Table 1 Characteristics of the five landscapes studied Total population 2

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Kalimantan

Papua

Ghana

Cameroon

CAR

65,200

42,600

161,800

140,650

7,350

Total area (km )

42,621

17,298

3,465

36,066

4,672

People/km2

1.5

2.5

46.7

3.9

1.6

Forest cover (%)

99

95

25

97

99

Primary forest cover (including primary forest after reduced impact logging) (%)

96

95

16

90

99

Ghana More information in Sandker and others 2010a

Papua More information in Sandker and others 2010b

Kalimantan More detailed information on data sources and model structure in Sandker and others 2007

Cash and subsistence income from various activities (forest products, agriculture, fisheries, salaries, fees and other) Carbon stock in land-uses, total landscape carbon REDD payment (based on international CO2 price, calculated carbon prevented from emission) and payment contract

Household income

REDD payments

Data from technoserve extension office, expert estimation, World Bank 2009a, b

Cocoa profit calculation (income [90 % from cocoa) Carbon stock in land-uses, total landscape carbon REDD payment (based on international CO2 price, calculated carbon prevented from emission) and payment contract

Household income Carbon REDD payments

Capoor and Ambrosi 2008, Butler and others 2009, CarbonPositive 2009, expert assumption

Mediated from literature (De Bruijn 2005, Swallow and others 2007, Wauters and others 2008)

District report 2005, expert estimates

Rural population, natural population growth (in- and out-migration expected to be minor and therefore not included)

Human population

Aster 2007 and Landsat 2000 images, District report 2005

Main land-uses and their dynamics

Approximation from CarbonPositive 2009, expert assumption

Approximations from De Bruijn 2005 and IPCC 2000

Shepherd and others 2009, approximations based on practices in North Sumatera and Jambi

Kaimana Statistics Centre 2008, expert estimation

District Forestry Service 2008, expert estimation

Andrianto 2006, expert estimation

Approximation from Levang and others 2005 and Barr and others 2001, expert estimation

Land use

Carbon

Urban and rural population size, growth, district migration (mainly driven by jobs in plantations), urban-rural migration

REDD payment (based on international CO2 price, calculated carbon prevented from emission) and payment contract

REDD payments

Human population

Carbon stock in land-uses, total landscape carbon

Carbon

Administrative land-use categories, secondary and primary forest cover, logging and deforestation

Approximation from CarbonPositive 2009, expert assumption

District budget and civil servant salaries

District government

Land use

Approximations from De Bruijn 2005 and IPCC 2000

Cash and subsistence income from various activities (forest products, agriculture, fisheries, salaries, fees and other)

Household income

Malinau Statistics Centre 2006 adjusted with expert estimation

Urban and rural population size, growth, district migration (mainly driven by jobs in plantations), urban-rural migration

Human population

District Forestry and Estate Crops Service 2006

Data sources

Administrative land-use categories, secondary and primary forest cover, logging and deforestation

Summary contents

Land use

Model sectors

Table 2 Overview of the models’ contents and data sources

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CAR More information in Sandker and others 2011

Cameroon More information in Sandker and others 2009

Table 2 continued

Natural population growth Bantu and BaAka populations, in- and out-migration (driven by employment, loss of jobs and bad socio-economic situation in CAR) Cash and subsistence income from various activities for BaAka pygmies and Bantu (agriculture, hunting, fishing, NTFP collection, commerce, salaries) Log production, salaried jobs and timber royalties (both determined by log production) Logistic equations of duiker and elephant populations, extraction by hunting Ecotourism employment A function of number of hunters (percentage of unemployed males), animal densities, number of guns, roads and anti-poaching measures Anti-poaching (various methods), certification, ecotourism

Human population

Household income

Logging concession Wildlife populations Ecotourism Hunting

ICDP Interventions

Anti-poaching, awareness creation, better governance, eco-monitoring, development investment, certification

ICDP interventions

Administrative land-use categories

Management of development budget (from royalties)

Governance

Land use

Wildlife royalties and safari employment

Gun and snare hunting (determined by animal density, anti-poaching activities, loss of income)

Hunting

Timber royalties, timber extraction, employment in concessions

Logistic equations of duiker and elephant populations, extraction by hunting

Wildlife populations

Safari hunting

Cash and subsistence income for Baka pygmies and Bantu from various activities (agriculture, hunting, fishing, NTFP collection, livestock, commerce, salaries)

Household income

Logging concessions

Administrative land-use categories and deforestation Natural population growth Bantu and Baka populations, in-and out-migration (driven by employment and loss of income)

Land use

Summary contents

Human population

Model sectors

Project information, expert assumption

Literature (Noss 1998), household surveys in 2006, observations, expert estimation

Project registration of 2008, expert estimation

Literature (Blake 2005, Noss 1998), project report (Turkalo 2005), expert estimation

Literature (Czesnik 2007), logging company management plan (CIB 2006), expert estimation

Household surveys in 2006, project report (Kamiss 2006), literature (Garreau 1994), expert estimation

Project census (2005, 2007), literature (UN 2009), expert estimation

GIS measurements project (2008)

Project logbook, expert information and assumption

Expert estimation

Government report (MINEFI), literature (GFW 2005)

Safari director interview, literature (GFW 2005)

Project inventories (Nzooh 2003, Nzooh and others 2005), literature (Ekobo 1998, Cowlishaw and others 2004) Household surveys (2006), expert estimation

Household surveys in 2006, project report (CEFAID 2005)

Project census (GTZ 2001), literature (UN 2006, UNFPA 2007)

Landsat images (2003), literature (GFW 2005)

Data sources

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quantify conservation-development trade-offs. ICDP activities were included in the models to visualize and quantify their impact on the selected parameters. A range of possible scenarios constructed by the stakeholders involved in the modeling were explored, rather than focusing on a single expected pathway. Stakeholders working in each landscape thus created and defined both the model representing the complex interactions in the system, and the scenarios to be explored. Indicators of Conservation and Development Indicators of both conservation and development were selected in order to quantify the trade-offs between them. Average per capita cash income was used as a proxy for economic development. Discussions were held with stakeholders concerning the roughness of this proxy in locations where subsistence income is highly important. However, the stakeholders believed it was the best available indicator for development and it was therefore retained. Different indicators of conservation status were selected in different locations. Some conservationists see wildlife hunting for food as a more immediate threat to biodiversity conservation than deforestation (Wilkie and others 2005). Stakeholders working in central Africa saw hunting as the most pressing concern, but it was not the major concern for stakeholders in Indonesia, where forests in neighboring locations are being replaced by large-scale plantations. Stakeholders in Cameroon and CAR therefore selected wildlife populations [forest elephant (Loxodonta cyclotis) and duiker (Cephalophus sp.)] as indicators of conservation status, while stakeholders in Indonesia and Ghana selected forest cover (as an indicator of forest quantity) and primary forest cover (as an indicator of forest quality) to approximate conservation outcomes.

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or development. In the Indonesian and Ghanaian landscapes modeling explored the effect of implementing REDD strategies, but in this scenario, REDD payments were entirely consumed at central and district government levels. In the central African landscapes, deforestation rates are currently low, so better governance (Sandker and others 2009) and forest certification (Sandker and others 2011) were selected as alternative scenarios. A third scenario was then selected (Scenario 3), which assumed the same approaches to conservation and development as in the second scenario, but in addition assumed that local people received a share of PES (or REDD) payments generated by better management of their resources. This aimed to identify whether PES paid to local communities could overcome the trade-offs between conservation and development outcomes. For Ghana this share was assumed to be slightly higher (25 % captured by the local population) than for the Indonesian landscapes (20 %) since Ghanaian farmers tend to have stronger ownership of their forest resources. In the central African landscapes a wildlife PES was included in the third scenario. Population baselines were constructed for elephant and duiker populations based on predictions under the BAU scenario. If poaching decreased, payments would be made according to the population size compared to the baseline; payment size was established using the Cameroonian safari hunting fees per animal. Some assumptions in the original models were altered for the purpose of this paper to obtain more coherence when comparing the different landscapes. For example, for REDD calculations the carbon price paid on the international market was set equally for all locations and the duiker density used in the CAR model was altered to have a density obtained with a similar method to the Cameroon model.

Scenario Exploration

Results

For each location a range of scenarios was explored, based on different management approaches in an attempt to identify the strategy most likely to result in best outcomes for conservation and development. Three of these scenarios were selected and reported on in this paper (Table 3). First, a business as usual (BAU) scenario (Scenario 1) was defined as the most likely series of events to occur in the absence of new conservation or ICDP approaches. The BAU scenarios were not necessarily projections of historical trends but, according to stakeholders, were the most likely to occur, considering changes already seen and those anticipated for the region. Second, an alternative scenario was selected (Scenario 2), which introduced new approaches to conservation and/

Trade-Offs and PES Figure 1 demonstrates that trade-offs occurred between conservation and development; improved conservation outcomes under Scenarios 2 and 3 came at a cost to local incomes, which were lower than under the BAU scenario (Scenario 1). The central African landscapes were an exception to this. In none of the simulations PES were able to overcome these trade-offs in cash terms in the long term, although for the Indonesian landscapes they did improve incomes substantially. Furthermore, the average per capita cash income projections for the Indonesian landscapes hide the large range of negative consequences of large scale plantation investments, such as income

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Table 3 Scenario description with main assumptions for the different landscapes Landscape

Scenario

Assumptions

Kalimantan

1. BAU

500,000 ha of forest converted to plantation over 20 years annual timber and plantation salaries are 10 and 12 mln Rp respectively oil palm requires 0.2 worker/ha, for more assumptions see Sandker and others (2007).

2. Alternative scenario

A REDD strategy is implemented resulting in plantation development restricted to 100,000 ha over 20 years; local people do not receive a share of the REDD payment.

3. Alternative scenario with PES

REDD strategy as under Scenario 2 but now local people receive 20 % of REDD payment. BAU scenario is used to calculate total amount of avoided carbon emissions; carbon price = US$10/ton CO2; 20 year REDD contract with equal annual payments.

BAU

600,000 ha of forest converted to plantation over 20 years Annual timber and plantation salaries are 10 and 12 mln Rp respectively oil palm requires 0.2 worker/ha, for more assumptions see Sandker and others (2010b). A REDD strategy is implemented resulting in plantation development restricted to 108,000 ha over 20 years; local people do not receive a share of the REDD payment.

Papua

Alternative scenario

Ghana

Cameroon

Alternative scenario with PES


BAU Alternative scenario

Prolongation of current trend; cocoa expansion at the cost of forest, see Sandker and others (2010a). A REDD strategy is implemented resulting in no more forest converted to cocoa.



BAU

Prolongation of current trend: poor governance and high levels of poaching, ICDP invests in antipoaching only, see Sandker and others (2009). Better governance: ICDP invests in improved redistribution and management of timber and wildlife royalties, see Sandker and others (2009). The scenario assumes misappropriation of decentralized royalties to reduce with 40 %.


CAR


BAU scenario without ICDP is used to calculate total number of elephants and duikers saved over 20 years; prices per animal are derived from safari hunting fees set by the Cameroonian government (US$185/elephant and US$37/duiker); duiker price is approximated as it covers several species; 20 year PES contract with equal annual payments; local people receive 100 % of PES in the form of an anti-poaching salary.

BAU

Prolongation of current trend; re-opening of the sawmill managed by a company showing low social responsibility and no long-term management plan, see Sandker and others (2011). We use minimum duiker density estimations and maximum reproduction rate approximation (adopted from Noss 1998).


Re-opening of the (currently closed) sawmill by a company obtaining Forest Stewardship Council certification, showing high social responsibility, see Sandker and others (2011).


BAU scenario (complete extinction elephant and duiker) is used to calculate total number of elephants and duikers saved over 20 years; prices per animal are derived from safari hunting fees set by the Cameroonian government, (US$185/elephant and US$37/duiker); duiker price is approximated as it covers several species; 20 year PES contract with equal annual payments; local people receive 100 % of PES in the form of an anti-poaching salary.

disparity, pollution and perhaps even conflict (Sandker and others 2007; Sandker and others 2010b). Concerns about these negative impacts, plus the fear of a ‘boom and bust’ scenario (like Rodrigues and others 2009), in which natural capital is consumed in order to provide a one-off, not sustained inflow of money, might result in local people being more attracted to the second scenario. In such a situation PES could tip the balance and provide incentives for local people to support a scenario which they already prefer.

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Figure 1 shows that an improved income situation either coincided with best conservation outcomes (see Cameroon and CAR), or with worst conservation outcomes (see Papua and Kalimantan). However, the Cameroonian and CAR cases suggest that situations of increasing or sustained poverty entail long-term negative impacts on conservation outcomes. BAU (Scenario 1) in Indonesia means economic development at the cost of natural resources. BAU in central Africa means some wildlife species would go practically extinct, while people remain (extremely) poor.


Although the central African scenarios seem the most pessimistic, they at the same time hold the largest potential for synergies between conservation and development through initiatives such as improved governance and timber certification. However, governance is a difficult issue to resolve and even under the scenarios assuming governance will improve (Scenario 2 and 3) wildlife losses are substantial. Potentially better development and conservation outcomes would result from a boost to the national economy. Sandker and others (2011) discuss such a development and find that if this would result in a 2 % outmigration rate, with people moving to cities for salaried jobs, the elephant population could be maintained at its current size. Kalimantan and Papua The most marked changes in the five studied landscapes were expected in Papua where average per capita income was more than quadrupled over 20 years. In Malinau District, east Kalimantan, the local economy already boosted over the past decade. Decentralization has resulted in an enormous cash inflow to the sparsely populated district from mining and logging royalties resulting in a boom effect on the previously small capital town (Moeliono and others 2008). This boom effect is expected to be even more extreme in the future with per capita income at least doubling. Economic development was projected to be more substantial in the Papua landscape than in Kalimantan because of its greater suitability for plantations. In both Malinau and Papua the simulations showed the larger the plantation investment, the higher the per capita cash income. When a share of the REDD payments was captured by the local population (Scenario 3), income was improved substantially compared to the alternative scenario without REDD payments (Scenario 2) but still didn’t outcompete large scale plantation investment (Scenario 1) in economic terms. Although the inflow of cash into the local economy would be much higher under Scenario 1 with the establishment of large scale plantations, than under Scenario 2, the final effect on per capita cash income is buffered by the greater inflow of migrants under Scenario 1, resulting in the economic benefits (mainly salaries) being shared among more people. These average figures hide vast income disparities which would be likely to occur with the arrival of large scale plantations. Salaries would only be captured by a few people, while many more would suffer negative impacts on their incomes from natural resources as a result of pollution and large scale deforestation. Both Malinau and Papua concern large forest areas with relatively small populations. In combination with the vast carbon sink formed by its mostly primary forest cover and the elevated Indonesian

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deforestation rates, under Scenario 3 this would result in very high per capita REDD payments. However, it is quite possible that if large REDD payments were made through government channels, large scale corruption would result; or when payments were distributed among the local population, migrants would be attracted to the district to capture a share. The per capita cash income under Scenario 3 might in reality be much lower when shared among many more people. Ghana For the Ghanaian landscape, future cash income was unlikely to decrease as much as shown in Fig. 1 under any of the scenarios. The future economy is likely to depend less on natural resources, and more on off-farm employment and urbanization (which were not included in the Ghana model). A REDD strategy in this landscape (Scenario 2 and 3) was unlikely to be effective in the long term because REDD payments would not be high enough to outweigh the opportunity costs of foregone cocoa production. Large upfront REDD payments might result in many farmers signing up for such a scheme, but breaking the contract some years later. In the long term this would not result in reduced carbon emissions. Cameroon and CAR In the two central African landscapes, stakeholders were pessimistic of both future conservation and development outcomes. They foresaw dramatic losses in wildlife, especially in CAR, while people remained in (extreme) poverty (Fig. 1). Although under Scenarios 2 and 3 local people’s economic conditions improved, this progress was minor, especially compared with projected development in the Asian landscapes. In CAR, the most optimistic scenario still resulted in a wildlife population loss of over 50 % (Fig. 1). For both central African landscapes, the wildlife PES scheme envisaged under Scenario 3 resulted in a per capita payment which would have little effect on people’s income. However, poor people might be incentivized even with a small amount of extra cash, especially since these scenarios already come with benefits for local people.

Discussion Income and Deforestation With the exception of Ghana, small scale agriculture is not the main driver of deforestation and forest degradation in the landscapes studied. Rather, as also noted by Ickowitz (2006), these processes are driven by commercial

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Environmental Management (2012) 50:633–644 Papua

Malinau

Ghana

Central African Republic

Cameroon

Developmentb

Conservationa

Developmentb

Conservationa

Developmentb

Conservationa

Developmentb

Conservationa

Developmentb

Conservationa

Scenario 1: -39% 7 -24% 362% -3% -95% -13% 191% -37% -22% 'Business as usual' 99% -8% -37% -21% 24% -59% 18 Scenario 2: -4% 314% 7 'Alternative scenario'c 140% -8% -36% -21% 24% -59% 18 Scenario 3: 329% 7 -4% 'Alternative scenario with d PES' a. In case of Malinau, Papua and Ghana the conservation indicator value is obtained taking the average of total forest cover and primary forest cover; in case of Cameroon and Central African Republic the conservation indicator value is obtained taking the average of percentage change in elephant and duiker population over year 2009 b. Percentage change in per capita cash income over year 2009 c. Scenario 2 assumes REDD implementation without payments captured by the local population for Malinau, Papua and Ghana; assumes better governance of wildlife and timber royalties for Cameroon; assumes certified logging for Central African Republic d. Scenario 3 has same assumptions as scenario 2 with the only difference that a share of REDD payments reached local population (Malinau, Papua, Ghana) or that it includes a wildlife payment to local population (Cameroon, Central African Republic)

Fig. 1 Simulated conservation and development indicator value change in 2029 over base year (best scores with white background, worsening with darker grey shading—similar shading tone means no relevant difference)

plantation and logging companies. In such situations ICDPs need to work, not only with local communities, but also with plantation and logging companies, and government, who should be well informed before distributing permits for such operations. As small scale agriculture is not the primary driver of deforestation, the relationship between deforestation and poverty is not necessarily direct. Investments in the landscape that coincide with forest deterioration or loss may influence local people’s incomes positively, through an inflow of cash in royalties and salaried jobs; negatively, through increased pollution and depletion of wildlife and forest products; or, in most cases, in ambiguous ways. Results from our landscape studies were similar to findings from national level studies on this relationship. Several studies (Kaimowitz and Angelsen 1998; Koop and Tole 1999; Thomas and others 2000) have tested the hypothesis of a Kuznets curve relation between poverty alleviation and deforestation. The environmental Kuznets curve relation assumes an inverse U-curve, where moving out of absolute poverty first comes with degradation and only after a substantial increase in wealth, this degradation is halted and turned into restoration. Although in some cases this correlation is found to be positive (Kaimowitz and Angelsen 1998; Thomas and others 2000), in all cases it is statistically insignificant, providing weak empirical evidence for a causal relationship at the national level. There seems to be no one-size-fits-all explanation for conservation and development interactions. Wunder (2001) explains this by noting that poverty is extremely complex and multidimensional, and in many cases its links with deforestation are indirect. Our findings concurred with this: for example, in the Indonesian landscapes, poverty (when measured in average per capita cash income) seemed to diminish most under the scenario with the highest

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deforestation, while many poor households that depend on natural resources for their income became poorer under the same scenario.

Income and Bushmeat Consumption The relationship between bushmeat consumption and wealth does not seem to be explained by the Kuznets curve either. Studies among poor populations have found that an increase in wealth in some cases is negatively related to bushmeat consumption ((Albrechtsen and others 2006), and in others it is positively related (Wilkie and others 2005). Apaza and others (2002) find that earnings bear no relation to wildlife consumption. Godoy and others (2006) explain these different responses by categorizing bushmeat in the different locations of these studies as an inferior, normal or luxury good. In the central African landscapes bushmeat is preferred over other meat sources (Wilkie and Carpenter 1999) so one would expect an increase in income to result in increased bushmeat consumption, causing a decline in wildlife populations. However, our scenarios suggested the contrary; in the Cameroonian and CAR landscapes, the scenarios resulting in the highest income also offered the best conservation outcomes for wildlife populations. This can be explained by the assumption in Scenarios 2 and 3 that local people will protect their natural resources if incentives are structured to provide them with extra income. Local people received benefits related to their natural resources through improved governance of wildlife and timber royalties (Cameroon) or through the implementation of FSC certification standards (CAR). A continuation of the status quo, where people remain poor, is unlikely to maintain viable wildlife populations since


current hunting levels are thought to be unsustainable (Noss 1998). National Economic Development and Conservation Macroeconomic development of the national economy strongly influences conservation and rural development. In some cases, external factors even determine conservation outcomes, rendering local management institutions obsolete (Fisher and others 2010). All scenarios for the CAR landscape resulted in substantial wildlife losses (Sandker and others 2011), due to a lack of alternative incomegenerating opportunities for the local population other than bushmeat hunting. Increased opportunities outside the forest and urbanization trends can reduce the pressure on forest resources. However, the stagnant CAR economy together with a turbulent socio-political situation, has led to a lack of income-generating opportunities outside the forest. The result is low migration out of forest landscapes— currently only 38 % of the CAR population is urban, while in neighboring Cameroon it is 55 % (UN 2006). In addition, the forest acts as a livelihood safety net, which might attract people fleeing other parts of the country. According to Brandon (2001) ‘‘getting the politics right’’ is the swiftest and most direct way to influence the links between poverty, land use and biodiversity loss. In Cameroon for example, conservation outcomes will not be sustainable in the absence of improvements in governance (Sandker and others 2009). Culas (2007) and Shiferaw and others (2009) confirm the important role of the overall policy framework. They highlight environmental policies and institutions that empower local people have a critical impact on the sustainability of natural resource use. Shiferaw and others (2009) also find that ‘‘policy and institutional failures exacerbate market failures, locking smallholder resource users into a low level equilibrium that perpetuates poverty and land degradation.’’ PES Tropical forests are often regarded as invaluable for humanity or, when assessed in monetary terms, are highly valued (e.g., Costanza and others 1997). Despite this, our findings concurred with those of Karsenty (2007) who finds that conservation payments rarely come close to the real opportunity costs of conservation. At current payment levels, PES are unlikely to reverse the economic drivers of deforestation or degradation, as the Ghanaian landscape scenarios demonstrated. Furthermore as Karsenty (2007) argues, in a situation with high opportunity costs, ‘low-cost conservation’ is a potential threat to the development wishes of poor people. According to our findings, a population that remains in poverty exerts an unsustainable

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pressure on natural resources, and in the long term such ‘low-cost conservation’ could be counterproductive. Frost and others (2007) claim that wide ranging investments and large infusions of capital are needed to significantly reduce poverty, and that ‘‘without significant external changes, not much can be done to improve on what local people are already doing for themselves.’’ Some PES ‘hand-outs’ for conservation will thus not alleviate poverty, and a status quo in development will not reduce pressure on natural resources. Our results suggest that PES will only be effective if they reinforce people’s intrinsic motivations. In this way they enhance the attractiveness of a scenario which is already much appreciated by local people, and are effective only where the local people themselves value the ecological services and prefer to preserve them. For example, in Kalimantan, local people indicated they would settle for much less than the opportunity costs for preserving their community forest (Wunder and others 2008). Decision-Making Processes Unfortunately, decisions are often not made on the basis of best outcomes for local people, even when decisionmaking power has been decentralized. An obvious example occurred in the Cameroonian landscape where local leaders showed little concern about improving the situation for the poorest people in their administrative unit. The previous mayor had siphoned off most of the timber royalties destined to finance development projects. Likewise, the decision on whether to attract oil palm investments or apply a REDD strategy in the Indonesian landscapes could be determined by the best deal for the district government (and its officials) rather than concerns about outcomes for local people. In such a situation there is a risk that ‘lowcost conservation’ provides local leaders with cash, and encourages them to choose a conservation scenario which deprives local people of opportunities to improve their own incomes. In our Indonesian landscapes though it could encourage local leaders to opt for a conservation scenario that ‘protects’ local people from the negative effects associated with the BAU scenario, such as large scale forest loss and pollution from oil palm plantations. Conservationists must weigh up the different scenarios and their trade-offs to ensure they do not create an unethical situation which further disadvantages the poor.

Conclusion In our attempt to understand the relationship between conservation and development, we found that an increase in the well-being of local people could either occur at the

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expense of natural resources or could be coherent with conservation. However, in all cases, a population that remained in poverty negatively affected conservation outcomes in the long term. This suggests that lifting people out of poverty could ultimately alter the pressures on natural resources, but whether the pressure is reduced or increased depends on the development pathway chosen. The choice of pathway can be influenced by PES, but such schemes have limited potential and alone are unlikely to lift people out of poverty. PES schemes are likely to promote environmentally less destructive options only if these bring substantial non-monetary benefits for local people. The BAU scenarios resulted in the worst outcomes for conservation in all five landscapes, and in some cases for development as well. This finding urges for a change in current conservation approaches and highlights the need to explore alternative conservation and development pathways. In some landscapes, such as that in Ghana, no conservation alternative is likely to compete with economic drivers. A REDD scheme limiting forest conversion will not be successful, but alternative investments such as enrichment of cocoa plantations with timber species should be explored. In landscapes like the Indonesian ones, where forests are being lost rapidly and on a large scale yet locally there is interest in alternative options, REDD negotiations should be accelerated for a rapid implementation. As the CAR landscape showed, when defining a conservation and development strategy, external factors like investments in the local economy and development of the national economy must be considered. In some cases this may mean that conservation and development organizations working at the local level can have more impact by engaging in negotiations, influencing policy formulation and local government decisions. Conservationists may find themselves advocating better governance, or supporting government in negotiations to allocate forest management rights to logging companies that commit to FSC certification. These tasks may seem far removed from wildlife conservation but in reality could have a major impact on conservation and development outcomes. Culas (2007) suggests that in order to effectively reduce pressure on natural forests, environmental policies and institutions should be improved, rather than limiting economic or population growth. Our findings support this conclusion, as limiting economic growth also creates unsustainable pressures on natural resources. We suggest that conservation and development scenarios should be more thoroughly explored, to identify situations where investment in a conservation strategy is a waste of resources, and where such an investment can realistically promote the desired conservation and development outcomes.

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Environmental Management (2012) 50:633–644 Acknowledgments The authors acknowledge the Livelihoods and Landscapes Initiative (LLS) from the International Union for Conservation of Nature (IUCN) for their financial support for the research done in several of the study locations.

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