Safeguarding ecosystem services and livelihoods: Understanding the impact of conservation strategies on benefit flows to society

Ecosystem Services 4 (2013) 95–103

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Ecosystem Services journal homepage: www.elsevier.com/locate/ecoser

Safeguarding ecosystem services and livelihoods: Understanding the impact of conservation strategies on benefit flows to society Louise Willemen n, Evangelia G. Drakou, Martha B. Dunbar, Philippe Mayaux, Benis N. Egoh Institute for Environment and Sustainability, Joint Research Centre—European Commission, Via E. Fermi 2749, 21027 Ispra, Italy

a r t i c l e i n f o

abstract

Article history: Received 21 May 2012 Received in revised form 24 January 2013 Accepted 13 February 2013 Available online 19 March 2013

Society has always benefited from ecosystems through the provision of ecosystem services. To ensure a continuous flow of these benefits, different strategies aimed at safeguarding ecosystem services are proposed. In this paper we explore how biodiversity conservation measures, particularly protected areas, influence the flow of ecosystem services to different members of society. We highlight the impact of these measures on the poorer members of society because of their strong dependence on ecosystem services to sustain their livelihood. For the Democratic Republic of Congo we mapped five ecosystem services (food production, tourism, carbon, timber and fuel wood production) using spatial landscape indicators, within and outside protected areas, and identified their direct beneficiaries. This illustration was used to feed a round-table discussion on the impact of different conservation strategies on society, held with ecosystem services professionals during the 4th Ecosystem Service Partnership Conference in the Netherlands. The discussion highlighted the need for spatial methods to assess ecosystem service trade-offs, as well as the main challenges for conservation measures to contribute to both livelihood improvement and conservation gains. We argue that, ecosystem services maps can play a crucial role in understanding and managing the trade-offs in ecosystem service flows resulting from conservation strategies. & 2013 Elsevier B.V. All rights reserved.

Keywords: Protected area Democratic Republic of Congo GIS Ecosystem Service Partnership

1. Introduction Ecosystem services contribute to human well-being worldwide. The Millennium Ecosystem Assessment, among others, highlighted the importance of ecosystem services (ES), in particular for the poorer members of society, as this group often shows a strong dependence on ES to sustain their livelihoods (MA, 2003; Tallis et al., 2008; TEEB, 2008). This dependency is linked to reliance on accessible natural resources, limited adaptive capacity, and vulnerability to natural hazards. Degradation and unsustainable use of ecosystems and their services worldwide now threatens the livelihoods of many poor people. ES provide direct benefits that can also generate monetary benefits when they are paid for (Swallow et al., 2009; Milder et al., 2010; Kinzig et al., 2011). Over the past 50 years humans have changed ecosystems rapidly and extensively leading to a global loss of biodiversity and ES (MA, 2005). There is an urgent need for a change in behaviour in order to avert the negative consequences of human activities on biodiversity and ES. To ensure a continuous

n Corresponding author. Current address: Ecoagriculture Working Group, Department of Natural Resources, Cornell University, Ithaca NY, 14853, USA. E-mail address: [email protected] (L. Willemen).

2212-0416/$ - see front matter & 2013 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.ecoser.2013.02.004

flow of benefits to society different strategies are developed to safeguard ES. Such strategies include, among others, coupling of ES with biodiversity conservation policies or creating market incentives for ecosystem protection. These strategies envision win–win situations where biodiversity is conserved because people understand its value, while ecosystem services are used as an argument to justify biodiversity conservation (Turner et al., 2007; Naidoo et al., 2008). At present several biodiversity conservation policies and strategies include the explicit objective of safeguarding ES (e.g. CBD, 2010; EC, 2010). Establishing protected areas (PAs) is a common conservation strategy which has been pursued for biodiversity conservation and is also seen as an important opportunity to safeguard ecosystem services (Chan et al., 2006; Turner et al., 2007; Nelson et al., 2008; Egoh et al., 2009; Pettorelli et al., 2012). A well-connected and robust network of PAs could provide numerous ES benefits to people, especially to the surrounding local population (Figueroa and Aronson, 2006). Protected areas restrict and control human activities and use, and consequently protect the functioning of natural ecosystems (Dudley, 2008). However, the value of ES as a contribution to human well-being lies in their use which presents a potential conflict when maintaining areas in natural conditions. Biodiversity conservation strategies proposed for ecosystem services

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remain untested and little is known about the potential challenges encountered by the different stakeholder groups when implementing these strategies. According to the common definition, ES support the well-being of ‘society’. To explore the contribution of ES to local livelihoods insight is needed into which part of society is profiting from which specific ES. ES operate at different spatial scales, thus presenting a complex situation of benefit flows. The beneficiaries are not always located at the site of ES supply (Hein et al., 2006; Kinzig et al., 2011) or encounter access barriers to benefit from them (Daw et al., 2011). Therefore, in order to assess the contribution of ES to local livelihoods and the trade-offs between beneficiary groups, flows of services must be understood. In this paper we explore how biodiversity conservation measures, particularly protected areas, could influence the flow of ES benefits to society, Based on an illustration for the Democratic Republic of Congo, we show how ES indicators and maps, can contribute to a better understanding of trade-offs in ES benefit flows as a result of conservation strategies. Subsequently, we present the outcomes of a round-table discussion among ES professionals on the role of conservation strategies in contributing to both livelihood improvement and conservation gains. The discussion was held during the 4th Ecosystem Service Partnership conference in Wageningen, the Netherlands, in 2011.

2. Ecosystem services and beneficiaries An ES is a characteristic of an ecosystem that is considered useful to humans. For example, the presence of fish could benefit society through the provisioning of food, or through recreational fishing as a leisure activity. However, whether something is regarded a service or not depends on the location, time, and perception of (groups within) society (Haines-Young and Potschin, 2010). People will adapt, use, or protect ecosystems based on their own preferences, needs, and values. According to Swallow (2009) stakeholders can have three different roles in their interaction with ES. The first group are the beneficiaries, i.e. people who benefit from the ES. The second group are the stewards, i.e. people whose actions modify the flows of ES. And the third group are the intermediaries, i.e. people who govern interactions among stewards, beneficiaries, and the ecosystem. Decisions that change the ecosystem commonly lead to trade-offs in ES supply, resulting in a variety of winning and losing beneficiaries (Raudsepp-Hearne et al., 2010; Willemen et al., 2012). Well-managed set aside protected areas enhance ES linked to natural areas, such as soil, climate and water regulation, but do not directly improve those ES associated with human-transformed areas, such as crop production. In the context of ES and their role in sustaining livelihoods, Daw et al. (2011) identified besides trade-offs among ES, three other important aspects that should be taken into account: stakeholder access to ES, stakeholders in ES market mechanisms, and the level of dependency on ES. Access to ES is described by the authors as the social relationships, institutions, capabilities, rights, and capital that allow people to benefit from them. A clear example in relation to protected areas is the institutionalized access limitation. Subsequently, the authors emphasise the contribution to well-being through income generation, trade, and employment opportunities. In the case of protected areas this could, for example, be the spin-offs of the international tourism industry. With regard to the last issue the level of dependency reflects on the contribution of an ES to the overall well-being, which is defined by the beneficiary’s context and situation (Daw et al., 2011). The World Commission on Protected Areas (WCPA) has defined six types of management categories for protected areas,

which could each have a different impact on the ecosystem services and potential beneficiaries. These management levels vary from strictly setting aside natural areas, thus prohibiting any human interventions, to cultural landscapes with permanent human activities (Dudley, 2008). PAs that are classified as category I or II by the IUCN are areas in which biodiversity, along with its underlying ecological structure and processes, are kept as ‘natural’ as possible, and include strict nature reserves, wilderness areas, and national parks. Here, human intervention is minimal. In the following section we focus explicitly on the impact of the IUCN I and II categories on ES benefit flows to society.

3. Protected areas and benefit flows in the Democratic Republic of Congo The Democratic Republic of Congo (DRC) is a country with strong development and livelihood improvement needs (Von Grebmer et al., 2011). According to World Bank data, approximately 70% of the people currently live below the poverty line. A large part of the population relies on direct access to natural resources for their subsistence. The country has an extremely rich, albeit threatened, flora and fauna. In fact, the DRC has the highest level of biological diversity in Africa (UNEP, 2011). Of its 2.3 million square kilometres, the size of Western Europe, ca. 67% of the country is covered with forest (Fig. 1) and roughly 10% of the land is currently situated in a protected area (Eba’a Atyi and Bayol, 2009). In line with Target 11 of the global Strategic Plan of the Convention on Biological Diversity (CBD, 2010), the DRC plans to expand its protected area to approximately 17%. 3.1. Spatial distribution of ES To assess the relation between PAs and their contribution of ES flows to society we mapped and quantified the provision of ES in the DRC, identified the direct beneficiary groups, and subsequently assessed the impact of PAs on the ES flows. We used a set of spatial indicators to assess and map five selected ES in the DRC, i.e. food production from agricultural fields, fuel wood provision, timber production, carbon stocks for climate regulation, and tourism. This selection of services is limited to ES that have a direct human use and/or finance mechanisms (commodity goods, future REDD þ). Additionally the selected ES provide benefits on different spatial levels, allowing for illustrating trade-offs between beneficiaries across spatial levels. The suitability for food production and underlying spatial explanatory variables are assessed for the DRC using the Africover land cover map (FAO, 2003). As actual production figures are not available, the probability of finding agricultural fields is used to quantify the food production service. The land cover classes of the Africover map are based on the Land Cover Classification System which was visually applied to digitally enhanced LANDSAT TM images acquired during 2000 and 2001. Agricultural classes were extracted from the Africover map and comprised all classes that include crop and agricultural cover (Fig. 1). Based on 5000 randomly sampled points, all locations classified with or without agriculture were regressed against a set of spatial indicators (Table 1). To minimise the uncertainty in the input data in the regression, we only include points that were also classified as agriculture on another DRC land cover map for the same year by Vancutsem et al. (2006). Using a forward step-wise regression, based on Akaike’s information criterion scores, the predictive variables were selected. Additionally we omitted all variables with a p-value40.10 and a high collinearity (i.e. a Variance Inflation Factor VIF4 10). The final set of variables to explain

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Fig. 1. Land use and cover in Democratic Republic of Congo, based on the Africover map, and the location of the ten protected areas (IUCN category I and II). In green the forested areas, in light brown the savannah regions. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

Table 1 Spatial indicators and methods used for mapping ecosystem services in the Democratic Republic of Congo. Ecosystem service

Method

Spatial indicator

Mapped unit

Food production

Logistic regression

Probability of finding agricultural fields (index)

Carbon stock

Land cover proxy

Timber production

Land cover proxy

Fuel wood

Multi-criteria assessment

Tourism

Multi-criteria assessment

Location agricultural field Soil type Proximity to roads Moderate precipitation Proximity to populated places Vegetation type Biomass constant/ vegetation type Carbon constant/ vegetation type Woody vegetation Carbon stock Biomass/timber constants Timber concessions Woody vegetation Biomass Populated places Fuel wood needs Protected area location Presence of key species Distribution of key species

the location of agricultural fields showed an area under the Receiver Operating Characteristic curve (AUC) of 0.80, a statistical measure that indicates a very good fit (Hair et al., 1998). Carbon stock for climate regulation stored in aboveground biomass is estimated for each Africover land cover class containing woody vegetation. In Table 2 carbon values in Mg per hectare are assigned to each matching Africover land cover class based on carbon estimates from the literature and expert knowledge (Saenger and Snedaker, 1993; IPCC, 2003; Gibbs, 2006; Nasi et al., 2009). The timber production assessment is limited to locations inside the official logging-concessions in the DRC, therefore excludes all small-scale logging activities outside the concessions. The 65 official concessions are mainly run by international timber companies (de Wasseige et al., 2009). We used a generic formula (Brown, 1997) to calculate the timber volumes for trees with a minimum diameter of 10 cm based on biomass and wood density VOBðm3 =haÞ ¼ AGBðMg=haÞ =ðWDðMg=m3 Þ BEF

Above ground C-stock (Mg/ha)

Timber harvest (m3/ha/yr)

Accessible biomass (m3/yr)

Attractiveness index of PA (index)

tree, in volume per hectare, AGB is the total aboveground forest biomass per hectare, WD is the volume-weighted average wood density of oven dry biomass per tree volume, and BEF is the biomass expansion factor, indicating the ratio of aboveground oven-dry biomass of trees to oven-dry biomass of the merchantable volume. The AGB is calculated by converting the land cover-based carbon stock to biomass values, using the carbon-fraction conversion factor of 0.47 (IPCC, 2003). As more specific data were lacking the wood density (WD) is set to the mean density of 282 tropical African tree species, 0.58 Mg per m3 (Brown, 1997). This number is in line with Henry et al. (2010), who measured an average wood density of 0.59 Mg per m3 in a wet evergreen forest in Ghana. The biomass expansion factor (BEF) is assumed to be 1.74, the general estimation of mature tropical forests (Brown, 1997). So, WD ðMg=m3 ÞnBEF ¼ 0:58n1:74

ð1Þ

where, VOB is the volume over bark, the merchantable part of a

¼ 1ðMg=m3 Þ

ð2Þ

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Table 2 Africover land cover classes with their assigned carbon stock values per hectare, and the derived biomass and timber stock estimates. Carbon stock (Mg/ha)

AFRICOVER class

Aquatic agriculture 9 Aquatic closed to open grass incl. Sparse trees and shrubs (fresh water, permanently and temporarily flooded) 9 Aquatic closed to open trees, shrubs and woody vegetation (brackish water) (mangroves) 80 Aquatic closed to open trees, shrubs and woody vegetation (fresh water, permanently or temporarily flooded) 85 Aquatic floating forbs (fresh water, permanently and temporarily flooded) and closed to open herbaceous 9 (brackish water) Bare rock, bare rock with shallow sand and tidal areas, salt flats, very stony and stony soil 0 Closed to open shrubs and woody vegetation 33 Closed trees lowland (o 900 m)e 126 Closed trees highland (4 900 m)e 68 Irrigated and postflooding herbaceous crops 9 Irrigated and postflooding shrub crops, irrigated tree crops, irrigated forest plantations 9 Loose and shifting sands, bare soil, dunes, sand banks and beaches 0 Open to closed grassland 9 Open to very open trees 56 Rainfed herbaceous crops (large to medium, continuous fields) 8 Rainfed herbaceous crops (small, continuous fields and clustered and isolated fields) 8 Rainfed shrub crops, tree crops, forest plantations 54 Sparse vegetation 5 Tree and shrub savannah 14 Urban areas 0 Water (natural and artificial) 0

Lit. source

Biomass (Mg/ha)

Timber stock (m3/ha)

a

19 19 170 180 19

NA NA 170 180 NA

0 70 268 145 19 19 0 19 119 17 17 115 11 30 0 0

NA 70 268 145 NA NA NA NA 119 – – 115 NA 30 NA NA

a b c a

– d c c a a – a 4 a a c c c – –

NA. Not Applicable, no forest or wooded land. a Gibbs, H. K. 2006. Olson’s Major World Ecosystems Ranked by Carbon in Live Vegetation: An Updated Database Using the GLC2000 Land Cover Product, NDP-017b. Available from /http://cdiac.ornl.gov/epubs/ndp/ndp017/ndp017b.htmlS the Carbon Dioxide Information Analysis Center, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. b Saenger, P., Snedaker, S., 1993. Pantropical trends in mangrove above-ground biomass and annual litterfall. Oecologia 96, pp. 293–299. c Nasi, R., Mayaux, P., Devers, D., Bayol, N., Eba’a Atyi, R., Mugnier, A., Cassagne, B., Billand, A., Sonwa, D., 2009. A first look at carbon stocks and their variation in Congo Basin forests. In: de Wasseige, C., Devers, D., de Marcken, R., Eba’a Atyi, R., Nasi, R., Mayaux, P., (Eds.), The forests of the Congo basin: state of the forest 2008 Publications Office of the European Union, Luxembourg, p. 426. d IPCC, 2003. Good practice guidance for land use, land-use change and forestry. Intergovernmental Panel on Climate Change (IPCC), Hayama, Japan. e The land cover class Closed trees was split into highland and lowland forest based on elevation data.

Therefore, VOBðm3 =haÞ ¼ AGBðMg=haÞ=1ðMg=m3 Þ

ð3Þ

For all forest and wooded land cover in concessions, the timber stock is calculated (using Eq. (3)). We assume that a 25 year logging-scheme is applied in each concession; therefore 4% of the total area is logged per year. To estimate fuel wood production, the biomass of assumed collection sites is mapped. All sites with woody biomass, based on land cover classes of the Africover map, within 5 km of a road, river, or village are considered collection locations (Drigo, 2005; Sims et al., 2006). Approximately 1 m3 biomass per capita per year is used as fuel wood (Schure et al., 2011), which is 580 kg per year with an average wood density of 0.58 Mg per m3 (Brown, 1997). Based on the population per district (Tatem et al., 2007) we mapped all accessible biomass that is assumed to be consumed as fuel wood per year. The attractiveness for international tourism is estimated for national parks only (PAs), as international tourists visiting the DRC are mostly attracted by its wildlife (UNEP, 2011). Based on IUCN species distribution data (IUCN, 2010) all PAs were ranked according to the presence of key species for tourism. In the DRC attractive species for tourism include the gorilla, bonobo, chimpanzee, okapi, giraffe, striped hyena, hippopotamus, cheetah, lion and common eland. We corrected the scores of a park with the inverted count of number of other PAs in Africa where these species can be found too. This resulted in an increased attractiveness of the parks with endemic species. The resulting ES maps are presented in Fig. 2 on a 1 km  1 km resolution. Areas high in food production and fuel wood are

mostly located in the more densely populated eastern and southern parts of the country, whereas areas high in carbon and timber are located in the densely forested central and northern parts of the country. The beneficiaries of the provided services are identified at different spatial levels, ranging from local (food) to global level (climate regulation). In Fig. 2 we indicate the ES flows to the different beneficiary groups. The beneficiaries are defined in general terms after expert consultation during a one week workshop in Kinshasa with governmental organisations, scientists and NGOs. In the DRC most agricultural products and fuel wood are consumed locally or in the cities. Timber from concession areas is typically traded to end-users in the cities and consumers abroad. Most tourists in the DRC come from abroad; therefore the beneficiaries of the tourism service are defined as the international travellers. The complete global population benefits from the global climate regulation service, and therefore encompasses all beneficiary groups. Note that in Fig. 2 only the direct beneficiaries (i.e. the end-users of the service) of ES flows are defined. We therefore exclude the different actors in the market chain of commodity goods or commercial services, like in the sales of products, entry fees or tour guiding. 3.2. Impact of protected areas on ES beneficiaries To illustrate how a protected area could influence the flow of ES benefits to the different beneficiary groups in society, we use the spatial indicators for ES in the DRC as a basis (Table 1). With the establishment of a PA, the spatial characteristics of the landscape changes, thus resulting in a change in ES supply. In Table 3 we show the complex interactions among spatial indicators, the corresponding ES, the impact of a PA on these ES, as well as on the benefit flows to

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Fig. 2. Spatial distribution of ES in the Democratic Republic of Congo and the ES flows to the groups on different spatial levels.

Fig. 3. ES supply and the ten strict protected areas (IUCN category I and II) in the Democratic Republic of Congo.

the different beneficiary groups. The contribution of a spatial indicator to an ES is indicated with plus (þ) and minus ( ) signs. For example, good accessibility improves the food supply services, while

the presence of crop land decreases the fuel wood collection options. The estimated impact of a PA on the spatial indicators is shown by the arrows; for example the presence of a PA results in a reduced

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Spatial scale

Table 3 Impact of protected areas on spatial indicators, ES and the flows to beneficiary groups. In red the expected negative impacts, in green the positive impacts and in yellow the negative impact depending on the distance to the protected area.

accessibility while most likely increasing woody vegetation. The colour scheme red (negative), yellow (gradient), green (positive) shows the estimated impact of a PA on the ES and their beneficiaries. The most obvious difference is between the food and carbon ES and beneficiary groups; i.e. a PA is expected to increase the carbon stock and the benefit flow to all spatial levels of the global population. In contrast, a PA leads to less favourable conditions in terms of crop production and the flows of benefits to local villagers and urban populations in the DRC. Timber and fuel wood resources are expected to increase; however, the access limitations will decrease causing a barrier to the benefit flow to humans. Overlaying the ES maps with current PA boundaries illustrates where conflicts between biodiversity conservation strategies and ES use could be expected due to access and use restrictions (Fig. 3). Some strict PAs are real hotspots of ES. For example, the Virunga National Park on the eastern border of the country scores high in all mapped ES. The National Park also has an exceptional biodiversity and is home to the endangered mountain gorilla, among others, making it an important spot for biodiversity conservation (IUCN, 2010). This National Park, being an IUCN category II, is set aside to protect ecological processes from human interventions. Therefore, the conservation status of the park has implications for food, fuel wood, and tourism uses, since these are restricted. As these ES are present, in principle, the flow of ES is limited through governance access barriers. This access restriction could lead to conflicts with society, especially when the ES beneficiaries are collocated with the ES supply site; e.g. through food production and fuel wood. Regulations on ES use, however, can also avoid conflicts as can be seen from the timber production locations which are regulated and do not overlap with PA. Strictly PAs should ideally be established away from areas high in ecosystem services that are not delivered by a completely natural environment. For example, the location of areas high in food production and fuel wood in highly populated areas in the eastern and southern parts of the country, present a potential area of conflict if a strict PA is established in these regions. These areas are suitable for the establishment of protected areas which allows some level of access (e.g. conservancies). Otherwise strict PAs should be established in the centre of the country where carbon stocks are high and could also benefit other ecosystem services such as water regulation.

and Practice’’. With ca. 50 conference participants we discussed the opportunities and constraints of conservation strategies for safeguarding ES and local livelihoods. We did not solely discuss protected areas but also market-based conservation strategies such as PES. PES schemes exist worldwide and could constitute an important livelihood benefit, especially in low-income countries (Swallow et al., 2009; Milder et al., 2010). In a PES scheme, the beneficiaries of ES pay the people who are responsible for maintaining sustainable land uses that deliver these ES. PES schemes are perceived to be a successful strategy for biodiversity conservation ¨ (Daily and Matson, 2008; Wunscher et al., 2008). During the conference session we conducted a short survey among the audience. We asked them to score, based on the percentage of agreement, four statements related to the session theme. In general, participants considered the ‘‘establishment of a PA an adequate strategy to safeguard ES’’ (mean level of agreement 75%) and perceived ‘‘PES schemes as contributors to local livelihoods’’ (mean level of agreement 64%). While the participants indicated that ‘‘PAs play a role in delivering benefits to people at multiple spatial scales’’, they acknowledged that the ‘‘establishment of PAs can generate local conflicts for land’’ (mean level of agreement 59%).

4. Discussion and implications In this paper we explore how biodiversity conservation measures influence the flow of ecosystem service benefits to different members of society. The presented DRC case illustrates the potential impact of the establishment of PAs as a conservation strategy. However, there are different conservation paradigms focusing on safeguarding ES, such as PES schemes including the REDDþ initiative. Following the subjects of the round-table discussion we here discuss the role of spatial methods to assess ecosystem service trade-offs to support conservation planning and governance, as well as the main obstacles for conservation measures to contribute to both livelihood improvement and conservation gains.

3.3. Round-table discussion with ES professionals

4.1. Importance of ES maps in conservation planning and governance

The DRC case was used to feed a round-table discussion with ecosystem services professionals during a special session organised at the 4th ESP conference ‘‘Ecosystem services: integrating Science

Spatial information on ES supply is considered to be of indisputable value in understanding the contribution of ES benefits in supporting local livelihoods. The DRC illustration shows how

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spatial information is used to assess the changes in flow of ES benefits to different beneficiary groups in society. In the context of safeguarding the flow of ES to the different beneficiaries, sound governance plays an important role (Biermann, 2007; Daily and Matson, 2008). According to Cowling et al. (2008) three phases are required to ensure good governance of service supply in a dynamic but resilient social-ecological system. These phases include (i) assessment, (ii) planning, and (iii) management of the landscape. Mapping ES and identifying their beneficiaries are part of the first phase of assessing the landscape systems. This information is crucial for the subsequent planning and governance phases. When carefully planned, PAs can be a good strategy for safeguarding ES while simultaneously conserving biodiversity. ES maps combined with spatial information on biodiversity can contribute to the prioritisation of conservation areas (Egoh et al., 2010). Strict protected areas are mostly beneficial for regulating and cultural services (Dudley et al., 2011) but do not directly benefit provisioning ES because of use restrictions. However, with suitable landscape management strategies and involvement of land holders, conflicts between conservation and development objectives could be minimised (Schroth and McNeely 2011; Cortina-Villar et al., 2012). In our assessment for DRC only a limited number of ES were included. The illustration therefore does not give a comprehensive overview of all benefit flows but it shows that spatial information when linked to beneficiary groups could support PA management plans as they reveal where conflicts or synergies can be expected and who is affected. The spatial methods, as described in the DRC example, miss spatial-temporal dynamics of the ecological, social, and economic systems. Therefore, they fail to take into account temporal ES benefits (immediate and long-term), financial benefits, and (global) market mechanisms. Currently, ES mapping methods still face challenges concerning data availability, uncertainty and error propagation (Troy and Wilson, 2006; Eigenbrod et al., 2010; Schulp and Alkemade, 2011). Additionally, inconsistency in methods to quantify and map ecosystem services challenges the development of robust values of ecosystem services for policy and natural resource management decision-making (Crossman et al., 2013). Because of the current limitations, ES maps are still of limited use in detailed decision making. Mapping methods, as presented in the example for the DRC, however typically link landscape indicators to ecosystem service provision which supports decision makers with an increased understanding of the human-environment system. Good governance of ES is challenging because of the frequent mismatches between human and environmental boundaries (Cash et al., 2006). Appropriate management of landscape systems should therefore be at a scale consistent with all relevant biophysical and social processes involved (Perrings et al., 2011). For example, PAs do not always have a physical barrier; people can go in and wildlife can go out. Taking this permeability into account in governance strategies could help decrease conflicts inside (allow people to enter) and outside (livestock kill by wildlife) the PA boundaries. Management strategies, including sustainable use of ES, may vary according to the ES. When choosing a suitable management strategy important considerations are: whether a ES is a public good, the ES are provided and benefited from at the same location and, if there is a benefit now or in the future (Kinzig et al., 2011). In order to sustain livelihoods a balance in the supply of different types of ES (provisioning, regulating, cultural) must be maintained (Lovell et al., 2010). 4.2. Development goals in conservation strategies ES contribute largely to different aspects of human well-being at local level (van Jaarsveld et al., 2005; Reyers et al., 2009). Apart

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from direct ecosystem benefits, conservation strategies can also contribute to livelihood improvement through linked financial assets (Swallow et al., 2009; Milder et al., 2010). The presented illustration on the DRC omitted the ES benefits for all different actors in the market chain (trade of natural resources, PES rewards) or commercial services (like tourism spin-offs), which obviously contribute strongly local livelihoods. PES has rapidly gained popularity with its focus on market-based mechanisms for enhancing ES supply (Pagiola et al., 2005; Van Noordwijk and Leimona, 2010). We here specifically address the role of PES schemes as part of development pathways, as this subject was strongly emphasised during the round-table discussion by the ES professionals. In this section three following issues are highlighted: (i) practical applications of the benefit flows; (ii) valuation and financing; and (iii) contribution of PES to poverty alleviation. A successful application of PES schemes requires a clear identification of the direct and indirect beneficiaries for the generated services along with the quantification of the impact of conservation actions on ES supply. Most people in the world are not land owners but land stewards. This land property issue makes the distribution of payment flows challenging. For instance, as mentioned during the round-table discussion, ‘‘in Kenya, people pay increased fees for compensation to the water company, but there are no guidelines that connect these directly to ES suppliers’’. In contrast, a successful example was the application of the Water Framework Directive (2000/60/EC) regulations in the UK. The water companies, in agreement with the farmers, raised the water bill in order to compensate farmers for the restrictions imposed in the use of water for agriculture. Also in the context of REDDþ , the trend is to implement the payment mechanisms at national level. However in order to achieve the real objective, i.e. the reduction of deforestation, the payment should be redistributed to the local level, where people traditionally use the land, even if they are not the owners from a legal perspective. The heterogeneity of PES paradigms shows the emergent need for clear guidelines in PES implementation, monitoring as well as adopted methods of benefit sharing. PES implementations link to the need to value ecosystems. The CBD (2011) clearly stresses the need to raise public awareness about the economic value of ecosystems and biodiversity and the fair and equitable sharing of this economic value. However, there are unclear links between PES schemes and current ES valuation (Go´mez-Baggethun and Ruiz-Pe´rez, 2011). Additionally, depending on the nature of the ES, appropriate financing mechanisms must be designed (Arriagada and Perrings, 2011; Kinzig et al., 2011). Participants of the conference round-table discussion raised the question whether PES provides the correct framework to address poverty issues. There are doubts whether PES schemes and ES markets can contribute to both development and conservation gains (Go´mez-Baggethun and Ruiz-Pe´rez, 2011; Kinzig et al., 2011; McAfee, 2012). Some session participants stressed the danger of ‘‘countries shifting money from environment to development budgets, in order to link them to PES schemes for poverty alleviation, with the risk of PES getting expensivey while the poor members of society are not reached’’. Therefore, some argue that PES schemes should primarily focus on environment benefits, not on poverty alleviation (Wunder, 2008). In order to account for the many remaining challenges, conservation strategies must adopt an integrated approach taking into account the complexity of the socio-ecological system as well as its spatial-temporal dynamics across the different scales. This will require close integration of trans-disciplinary research, monitoring, assessment, and sound policy development on different spatial levels (Roe et al., 2009; Perrings et al., 2011; Potschin and Haines-Young 2011).

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Acknowledgements The authors would like to thank all presenters and participants of the Special Session on ‘Safeguarding ecosystem services and local livelihood: opportunities and constraints of conservation strategies’, organised during the 4th ESP Conference ‘Ecosystem services: integrating Science and Practice’ in Wageningen, the Netherlands, October 2011. References Arriagada, R., Perrings, C., 2011. Paying for International Environmental Public Goods. AMBIO: A Journal of the Human Environment 40, 798–806. Biermann, F., 2007. Earth system governance’ as a crosscutting theme of global change research. Global Environmental Change 17, 326–337. Brown, S. 1997. Estimating biomass and biomass changes of tropical forests: A primer. Rome, Italy. Cash, D.W., Adger, W., Berkes, F., Garden, P., Lebel, L., Olsson, P., Pritchard, L., Young, O., 2006. Scale and cross-scale dynamics: governance and information in a multilevel world. Ecology and Society 11, 8. CBD, 2010. The Convention on Biological Diversity, In: Proceedings of the 10th meeting of the Conference of Parties (COP 10): Decision X/2 on Strategic Plan for Biodiversity 2011–2020. Online: /http://www.cbd.int/decision/cop/ ?id=12268S. CBD, 2011. Nagoya protocol on access to genetic resources and the fair and equitable sharing of benefits arising from their utilization to the convention on biological diversity: Text and annex. Secretariat of the Convention on Biological Diversity, Montreal, Canada. Chan, K.M.A., Shaw, M.R., Cameron, D.R., Underwood, E.C., Daily, G.C., 2006. Conservation Planning for Ecosystem Services. PLoS biology 4, e379. Cortina-Villar, S., Plascencia-Vargas, H., Vaca, R., Schroth, G., Zepeda, Y., Soto-Pinto, L., Nahed-Toral, J., 2012. Resolving the conflict between ecosystem protection and land use in protected areas of the sierra madre de chiapas, Mexico. Environmental Management 49, 649–662. Cowling, R.M., Egoh, B., Knight, A.T., O’Farrell, P.J., Reyers, B., Rouget, M., Roux, D.J., Welz, A., Wilhelm-Rechman, A.. 2008. An operational model for mainstreaming ecosystem services for implementation. In: Proceedings of the National Academy of Sciences 105, pp. 9483–9488. Crossman, N.D., Burkhard, B., Nedkov, S., Willemen, L., Petz, K., Palomo, I., Drakou, E.G., Martı´n-Lopez, B., McPhearson, T., Boyanova, K., Alkemade, R., Egoh, B., Dunbar, M.B, Maes, J., 2013. A blueprint for mapping and modelling ecosystem services 4, 4–14. Daily, G.C., Matson, P.A., 2008. Ecosystem services: From theory to implementation. In: Proceedings of the National Academy of Sciences 105, pp. 9455–9456. Daw, T., Brown, K., Rosendo, S., Pomeroy, R., 2011. Applying the ecosystem services concept to poverty alleviation: The need to disaggregate human well-being. Environmental Conservation 38, 370–379. de Wasseige, C., Devers, D., de Marcken, P., Eba’a Atyi, R., Nasi, R., M. P. (Eds.), 2009. The Forests of the Congo Basin - State of the Forest. Publications Office of the European Union, Luxembourg 2008. Drigo, R. 2005. WISDOM—East Africa. Woodfuel Integrated Supply/Demand Overview Mapping (WISDOM) Methodology. Spatial woodfuel production and consumption analysis of selected African countries. FAO Forestry Department Wood Energy, Rome, Italy. Dudley, N. (Ed.), 2008. Guidelines for Applying Protected Area Management Categories. IUCN, Gland, Switzerland. Dudley, N., Higgins-Zogib, L., Hockings, M., MacKinnon, K., Sandwith, T., Stolton, S., 2011. National Parks with Benefits. How Protecting the Planet’s Biodiversity Also Provides Ecosystem Services Solutions 2, 87–95. Eba’a Atyi, R., Bayol, N., 2009. The Forests of the Democratic Republic of Congo in 2008. In: C. de Wasseige, D.D., d., M.P., Eba’a Atyi, R., N.R., M.P. (Eds.), The Forests of the Congo Basin—State of the Forest 2008. Publications Office of the European Union, Luxembourg. EC, 2010. Council conclusions on biodiversity post-2010—EU and global vision and international access and burden sharing regime. 15/03/2010. Council of European Union, Brussels. Egoh, B., Reyers, B., Rouget, M., Bode, M., Richardson, D.M., 2009. Spatial congruence between biodiversity and ecosystem services in South Africa. Biological Conservation 142, 553–562. Egoh, B.N., Reyers, B., Carwardine, J., Bode, M., O’Farrell, P.J., Wilson, K.A., Possingham, H.P., Rouget, M., De Lange, W., Richardson, D.M., Cowling, R.M., 2010. Safeguarding biodiversity and ecosystem services in the Little Karoo, South Africa. Conservation Biology 24, 1021–1030. Eigenbrod, F., Armsworth, P.R., Anderson, B.J., Heinemeyer, A., Gillings, S., Roy, D.B., Thomas, C.D., Gaston, K.J., 2010. Error propagation associated with benefits transfer-based mapping of ecosystem services. Biological Conservation 143, 2487–2493. FAO, 2003. Africover: Multipurpose Landcover database /http://www.africover.orgS. Figueroa, E.B., Aronson, J., 2006. New linkages for protected areas: Making them worth conserving and restoring. Journal for Nature Conservation 14, 225–232. Gibbs, H.K. 2006. Olson’s major world ecosystems ranked by carbon in live vegetation: An updated database using the GLC2000 land cover product,

NDP-017b. Available from /http://cdiac.ornl.gov/epubs/ndp/ndp017/ ndp017b.htmlS from the Carbon Dioxide Information Analysis Centre, Oak Ridge National Laboratory, Oak Ridge, Tennessee, U.S.A. Go´mez-Baggethun, E., Ruiz-Pe´rez, M., 2011. Economic valuation and the commodification of ecosystem services. Progress in Physical Geography 35, 613–628. Haines-Young, R., Potschin, M., 2010. The links between biodiversity, ecosystem services and human well-being. In: Raffaelli, D.G., Frid, C.L.J. (Eds.), Ecosystem Ecology: A New Synthesis. Cambridge University Press, Cambridge, pp. 110–139. Hair, J.F.J., Anderson, R.E., Tatham, R.L., Black, W.C., 1998. Multivariate data analysis Prentice-Hall, Upper Saddle River, New Jersey. Hein, L., van Koppen, K., De Groot, R.S., Van Ierland, E.C., 2006. Spatial scales, stakeholders and the valuation of ecosystem services. Ecological Economics 57, 209–228. Henry, M., Besnard, A., Asante, W.A., Eshun, J., Adu-Bredu, S., Valentini, R., Bernoux, M., Saint-Andre´, L., 2010. Wood density, phytomass variations within and among trees, and allometric equations in a tropical rainforest of Africa. Forest Ecology and Management 260, 1375–1388. IPCC, 2003. Good practice guidance for land use, land-use change and forestry. Intergovernmental Panel on Climate Change (IPCC), Hayama, Japan. IUCN, 2010. IUCN red list of threatened species. Version 2010.4 /http://www. iucnredlist.orgS. Kinzig, A.P., Perrings, C., Chapin, F.S., Polasky, S., Smith, V.K., Tilman, D., Turner, B.L., 2011. Paying for ecosystem services—promise and peril. Science 334, 603–604. Lovell, S.T., DeSantis, S. r., Nathan, C.A., Olson, M.B., Ernesto Me´ndez, V., Kominami, H.C., Erickson, D.L., Morris, K.S., Morris, W.B., 2010. Integrating agroecology and landscape multifunctionality in Vermont: An evolving framework to evaluate the design of agroecosystems. Agricultural Systems 103, 327–341. MA, 2003. Millennium ecosystem assessment, ecosystems and human well-being: a framework for assessment. Island Press, Washington. MA, 2005. Ecosystems and Human Well-being: Synthesis. Island Press, Washington, DC. McAfee, K., 2012. The contradictory logic of global ecosystem services markets. Development and Change 43, 105–131. Milder, J.C., Scherr, S.J., Bracer, C., 2010. Trends and future potential of payment for ecosystem services to alleviate rural poverty in developing countries. Ecology and Society 15, 6. Naidoo, R., Balmford, A., Costanza, R., Fisher, B., Green, R.E., Lehner, B., Malcolm, T. R., Ricketts, T.H. 2008. Global mapping of ecosystem services and conservation priorities. In: Proceedings of the National Academy of Sciences 105, pp. 9495–9500. Nasi, R., Mayaux, P., Devers, D., Bayol, N., Eba’a Atyi, R., Mugnier, A., Cassagne, B., Billand, A., Sonwa, D., 2009. A first look at carbon stocks and their variation in Congo Basin forests. In: de Wasseige, C., Devers, D., de Marcken, R., Eba’a Atyi, R., Nasi, R., Mayaux, P. (Eds.), The forests of the Congo basin: state of the forest 2008. Publications Office of the European Union, Luxembourg, pp. 426. Nelson, E., Polasky, S., Lewis, D.J., Plantinga, A.J., Lonsdorf, E., White, D., Bael, D., Lawler, J.J., 2008. Efficiency of incentives to jointly increase carbon sequestration and species conservation on a landscape. In: Proceedings of the National Academy of Sciences 105, pp. 9471–9476. Pagiola, S., Arcenas, A., Platais, G., 2005. Can payments for environmental services help reduce poverty? An exploration of the issues and the evidence to date from Latin America. World Development 33, 237–253. Perrings, C., Duraiappah, A., Larigauderie, A., Mooney, H., 2011. The biodiversity and ecosystem services science-policy interface. Science 331, 1139–1140. Pettorelli, N., Chauvenet, A.L.M., Duffy, J.P., Cornforth, W.A., Meillere, A., Baillie, J.E.M., 2012. Tracking the effect of climate change on ecosystem functioning using protected areas: Africa as a case study. Ecological Indicators 20, 269–276. Potschin, M.B., Haines-Young, R.H., 2011. Ecosystem services - Exploring a geographical perspective. Progress in Physical Geography 35, 575–594. Raudsepp-Hearne, C., Peterson, G.D., Bennett, E.M. 2010. Ecosystem service bundles for analyzing tradeoffs in diverse landscapes. In: Proceedings of the National Academy of Sciences 107, pp. 5242–5247. Reyers, B., O’Farrell, P.J., Cowling, R.M., Egoh, B.N., Le Maitre, D.C., Vlok, J.H.J., 2009. Ecosystem services, land-cover change, and stakeholders: finding a sustainable foothold for a semiarid biodiversity hotspot. Ecology and Society 14, 38. Roe, D., Nelson, F., Sandbrook, C. (Eds.), 2009. Community management of natural resources in Africa: Impacts, experiences and future directions. International Institute for Environment and Development, London, UK. Saenger, P., Snedaker, S., 1993. Pantropical trends in mangrove above-ground biomass and annual litterfall. Oecologia 96, 293–299. Schroth, G., McNeely, J.A., 2011. Biodiversity conservation, ecosystem services and livelihoods in tropical landscapes: Towards a common agenda. Environmental Management 48, 229–236. Schulp, C.J.E., Alkemade, R., 2011. Consequences of uncertainty in global-scale land cover maps for mapping ecosystem functions: An analysis of pollination efficiency. Remote Sensing 3, 2057–2075. Schure, J., Ingram, V., Akalakou-Mayima, C., 2011. Bois e´nergie en RDC: Analyse de la filie re des villes de Kinshasa et de Kisangani. Projet Makala/CIFOR, Kinshasa, RD Congo and Yaounde´, Cameroun. Sims, R.E.H., Hastings, A., Schlamadinger, B., Taylor, G., Smith, P., 2006. Energy crops: current status and future prospects. Global Change Biology 12, 2054–2076.

L. Willemen et al. / Ecosystem Services 4 (2013) 95–103

Swallow, B.M., Kallesoe, M.F., Iftikhar, U.A., van Noordwijk, M., Bracer, C., Scherr, S.J., Raju, K.V., Poats, S.V., Kumar Duraiappah, A., Ochieng, B.O., Mallee, H., Rumley, R., 2009. Compensation and rewards for environmental services in the developing world: framing pan-tropical analysis and comparison. Ecology and Society 14, 26. Tallis, H., Kareiva, P., Marvier, M., Chang, A. 2008. An ecosystem services framework to support both practical conservation and economic development. In: Proceedings of the National Academy of Sciences 105, pp. 9457–9464. Tatem, A.J., Noor, A.M., von Hagen, C., Di Gregorio, A., Hay, S.I., 2007. High Resolution Population Maps for Low Income Nations: Combining Land Cover and Census in East Africa. PLoS ONE 2, e1298. TEEB. 2008. The Economics of Ecosystems and Biodiversity: An interim report. European Communities. Troy, A., Wilson, M.A., 2006. Mapping ecosystem services: Practical challenges and opportunities in linking GIS and value transfer. Ecological Economics 60, 435–449. Turner, W.R., Brandon, K., Brooks, T.M., Costanza, R., da Fonseca, G.A.B., Portela, R., 2007. Global Conservation of Biodiversity and Ecosystem Services. BioScience 57, 868–873. UNEP, 2011. The Democratic Republic of the Congo: Post-Conflict Environmental Assessment Synthesis for Policy Makers. United Nations Environment Programme. van Jaarsveld, A.S., Biggs, R., Scholes, R.J., Bohensky, E., Reyers, B., Lynam, T., Musvoto, C., Fabricius, C., 2005. Measuring conditions and trends in ecosystem

103

services at multiple scales: the Southern African Millennium Ecosystem Assessment (SAfMA) experience. Philosophical Transactions of the Royal Society B: Biological Sciences 360, 425–441. Van Noordwijk, M., Leimona, B., 2010. Principles for fairness and efficiency in enhancing environmental services in Asia: payments, compensation, or co-investment? Ecology and Society 15, 17. Vancutsem, C., Pekel, J.-F., Evrard, C., Malaisse, F., Lubamba, J.-P.K., Blaes, X., de Wasseige, C., Defourny, P., 2006. The land cover map of the Democratic Republic of Congo. In: UCL-Geomatics, (Ed.). Presses universitaires de Louvain Louvain-la-Neuve, Belgium. Von Grebmer, K., Torero, M., Olofinbiyi, T., Fritschel, H., Wiesmann, D., Yohannes, Y., Schofield, L., Von Oppeln, C., 2011. 2011 Global Hunger Index. The Challenge of Hunger: Taming Price Spikes and Excessive Food Price Volatility. IFPRI, Welthungerhilfe, and Concern Worldwide, Bonn, Washington, DC, Dublin. Willemen, L., Veldkamp, A., Verburg, P.H., Hein, L., Leemans, R., 2012. A multi-scale modelling approach for analysing landscape service dynamics. Journal of Environmental Management 100, 86–95. Wunder, S., 2008. Payments for environmental services and the poor: concepts and preliminary evidence. Environment and Development Economics 13, 279–297. ¨ Wunscher, T., Engel, S., Wunder, S., 2008. Spatial targeting of payments for environmental services: A tool for boosting conservation benefits. Ecological Economics 65, 822–833.