Year : 2016 | Volume
| Issue : 3 | Page : 163-182
Modelling Local Attitudes to Protected Areas in Developing Countries
Chiara Bragagnolo1, Ana C.M. Malhado1, Paul Jepson2, Richard J Ladle3
1 Institute of Biological and Health Sciences, Federal University of Alagoas, Maceió, Brazil
2 School of Geography and the Environment, University of Oxford, Oxford, UK
3 Institute of Biological and Health Sciences, Federal University of Alagoas, Maceió, Brazil; School of Geography and the Environment, University of Oxford, Oxford, UK
Institute of Biological and Health Sciences, Federal University of Alagoas, Maceió
Source of Support: None, Conflict of Interest: None
|Date of Web Publication||27-Sep-2016|
| Abstract|| |
During a time of intensifying competition for land, Protected Areas (PAs) are coming under increasing pressure to justify their status. Positive local attitudes to a PA are a potentially important component of any such justification, especially in the developing world where human pressure on natural resources is often high. However, despite numerous studies our understanding of what drives positive attitudes to PAs is still exceedingly limited. Here, we review the literature on local attitudes towards PAs in developing countries. Our survey reveals a highly fragmented research area where studies typically lack an explicit conceptual basis, and where there is wide variation in choice of statistical approach, explanatory and response variables, and incorporation of contextual information. Nevertheless, there is a relatively high degree of concordance between studies, with certain variables showing strong associations with attitudes. We recommend that PA attitude researchers in developing countries adopt a more rigorous model building approach based on a clear conceptual framework and drawing on the extensive empirical literature. Such an approach would improve the quality of research, increase comparability, and provide a stronger basis to support conservation decision-making.
Keywords: people-park interactions, decision support tools, attitude theory, epistemology, model building, multivariate analysis, national parks
|How to cite this article:|
Bragagnolo C, Malhado AC, Jepson P, Ladle RJ. Modelling Local Attitudes to Protected Areas in Developing Countries. Conservat Soc 2016;14:163-82
| Introduction|| |
One the eve of the 2014 World Parks Congress, the Director General of the International Union for Conservation of Nature (IUCN) identified the “delicate balancing act between conservation and development needs” as the key to ensuring the long-term sustainability of the world's protected areas (Marton-Lefeèvre 2014: 525). The difficulty of finding such a balance is perhaps most clearly exemplified in the often fraught interactions between parks and the human populations that live in and around them. If society as a whole is unenthusiastic or even antagonistic towards gazetting land for conservation purposes, the politicians who represent them can justifiably question the social value of PAs, paving the way for downgrading, downsizing, de-gazetting or reclassifying parks (Mascia and Pailler 2011). At a local scale, a lack of community support can lead to negative attitudes towards PA regulations leading to behaviours such as illegal occupation (Singh 1999), unsustainable exploitation of wildlife (Loibooki et al. 2002), and grazing of livestock within PA boundaries (Nyahongo et al. 2005). These problems are particularly acute in the developing world where local communities can exert a strong and direct influence on the conservation effectiveness of nearby PAs, most notably through their natural resource extraction activities (Balmford and Whitten 2003).
Ever increasing competition for land (reviewed in Smith et al. 2010) is putting enormous pressure on PAs to justify their existence. Conservation actors are responding by refocusing their efforts to show how “protected areas yield substantial benefits for people” (Marton-Lefeèvre 2014: 525). Consequently, PAs are increasingly being called upon to do more than simply conserve biodiversity (Watson et al. 2014), incorporating diverse management objectives such as sequestering carbon, protecting/regulating water resources, increasing human well-being (Pullin et al. 2013) or even promoting human rights (Corsonet al. 2014). This change in focus can be clearly observed in the move of PA governance from a “fences and fines” approach to more community-focused approaches. One of the main consequences of this paradigm shift is that local communities have become much more active participants in PA conservation initiatives and decision-making processes (Adam and Hulme 2001). A lack of social support is therefore now considered as a key indicator of PA effectiveness (Hockings and Phillips 1999) and attitudinal studies are a key tool to evaluate public understanding and acceptance of conservation initiatives (Struhsaker et al. 2005; Kideghesho et al. 2007).
The academic community has an important role during this uncertain and transitional period for the world's PAs, filling knowledge gaps and producing policy relevant studies. One such knowledge gap is our lack of understanding about what drives local attitudes to PAs. According to Gifford and Sussman (2012), the most important drivers forming attitudes and shaping individual behaviours are values. In theory, since people endorsing biocentric values are expected to be more engaged in pro-conservation and environmental behaviours, their attitudes towards parks are assumed to be more positive. Operationally, studying attitudes is generally agreed as one of the best ways to proxy individual behaviours - which are far harder to observe and quantify (Fishbein and Ajzen 2010).
Since the early 1990s there have been an increasing number of academic studies of local attitudes to PAs, the results of which often aim to evaluate the impact of conservation initiatives and inform the development of new management strategies (Anthony 2007). Nevertheless, very little progress has been made in uncovering general principles – possibly because of the lack of consistent methodological approaches, the absence of over-arching conceptual frameworks and inadequate statistical analyses. This has led to diverse studies scattered across disciplinary journals, adopting radically different approaches and drawing on distinct philosophical and epistemological frameworks (Pullin et al. 2013). As a consequence, there are no strong grounds to explain how attitudes to PAs vary greatly among cultures, social groups and individual attributes, as well as among different management approaches (e.g. exclusive vs. participatory) and external global factors (i.e. economic crisis, climate change, etc.).
The most statistically robust approach to quantify and understand the drivers of attitudes to PAs is through multivariate models (e.g. multiple regression, logistic regression, general linear model, multi-model inference). This is not to down-play the important role of descriptive, in-depth qualitative studies. Such descriptive approaches are essential to provide contextual information and more nuanced insights into a broad range of related issues. Moreover, qualitative studies can significantly contribute to the interpretation of quantitative models. In contrast, quantitative approaches are better for generating evidence-based outcomes which can support conservation policy and decision-making. A good example is Jepson and Ladle's (2005, 2009) large scale study of wild-bird keeping in Indonesia which surveyed 1,781 households in the six largest cities in Java and Bali. Their results, which could be robustly scaled up to the entire urban population, powerfully demonstrated the strong cultural attachment of bird-keeping, providing support for a move towards softer policy instruments (e.g. market-based and voluntary mechanisms) that would engage a wider range of people and organisations.
There are three general challenges to quantitative research on attitudes. The first challenge is to identify appropriate response variables (the metric/s of attitude to the PA) that allow different studies to be compared. The second and third challenges both involve the selection of appropriate explanatory variables – the characteristics of the study participants that explain their attitudes (positive or negative). These challenges arise because poor choice of explanatory variables in multivariate models can significantly bias the results leading to faulty inferences about causation (Grafen and Hails 2002). Ideally, explanatory variables should be chosen on the basis of theoretical relevance rather than simple availability (Cox and Snell 1974; Grafen and Hails 2002; Miller and Salkind 2002). This avoids the inclusion of “junk data”: arbitrary variables that decrease the degrees of freedom and reduce the precision of all the estimates of valid explanatory variables.
Theoretical relevance could be based on theories of human sentiment and behaviour such as the Theory of Reasoned Action (TRA) and the Theory of Planned Behaviour (TPB) (Fishbein and Ajzen 1975; Fishbein 1979). Alternatively, variables could be chosen on the basis of contemporary understandings of people-park interactions (e.g. Agrawal and Redford 2006; Upton et al. 2008) or the vast literature on social consequences of PA designation (West et al. 2006; Brockington et al. 2008). And finally, selection of covariates should be based on factors that influence the outcome or the potential relationship between the predictor of choice and the outcome. A separate, but related, challenge of choosing explanatory variables for multivariate models is dealing with omitted variable bias (Cox and Snell 1974): the failure to identify and include significant variables in the model. This bias cannot be completely avoided (Clarke 2005), but can be limited by carefully deriving explanatory variables from a combination of theory and robust empirical studies (Hanushek and Jackson 1977).
The aim of our review is to outline a general methodological approach to studying attitudes of local peoples to surrounding protected areas in developing countries, providing the necessary information and context for researchers to develop robust and comparable multivariate models. To achieve this goal, we review the literature on local attitudes towards PAs in developing countries with the aim of identifying: 1) the normative theoretical lens/approach adopted; 2) common metrics of attitude used as response/explanatory variables, and; 3) statistically significant relationships between explanatory variables and attitudes. These three characteristics are fundamental for the development of theoretically and statistically robust models of attitudes to PAs. Moreover, such a review will provide an invaluable aid to researchers in developing countries and will potentially improve the quality and comparability of studies in this region.
| Materials and Methods|| |
We followed Pullin et al.'s (2013) bibliometric approach which conducted a priori searches and separated qualitative from quantitative studies in order to systematically review impacts of terrestrial protected areas on human well-being. Specifically, we initially retrieved 400 articles selected from two research databases (ISI Web of Science and Scopus) on the 10 February 2014 using the following search strings: (“Protected Areas” AND attitude*) or (”National Parks” AND attitude*). We searched in the title, abstract and keywords with no restrictions (i.e. year of publication, languages, etc.). Then, we applied filters to select relevant articles (as recommended by Pullin and Stewart 2006). Based on a review of the full text, we excluded articles that: 1) presented case studies in developed countries; 2) were primarily focused on attitudes to Marine Protected Areas (MPAs), and; 3) surveyed only tourists' attitudes.
We focused on research in developing countries because they are often characterised by large rural populations with high dependency on natural resources (Cardozo 2011). Many empirical studies showed that residents in such countries often have difficulty in perceiving the intrinsic conservation values associated with nearby PAs (Müller-Böker and Kollmair 2000; Balmford and Whitten 2003), and have a general expectation that PAs should contribute to the social and economic well-being of local people (Ezebilo 2012; Pullin et al. 2013). We excluded attitude studies of MPAs because: 1) many marine parks are situated a considerable distance from human populations and settlements (e.g. Exclusive Economic Zones and high seas) (UN 2013); 2) the focus of MPA research is typically restricted to the economics of resource extraction (Pita et al. 2011) and; 3) data from these studies often refers to a single user group (fishers) rather than the entire community (e.g. Stump and Kriwoken 2006; Sutton and Tobin 2009). Articles about tourist attitudes to PAs were excluded because tourists do not represent local communities.
After filtering, we were left with a final list of 123 journal article with a focus on local attitudes to terrestrial PAs in developing countries. The full list is included in Appendix A [Additional file 1] [Additional file 2].
In order to better identify the normative theoretical lens/approach adopted by PA attitude studies, we calculated and plotted the co-citation network for the articles in our sample. We included in our network all references that were cited in 15 or more of our 123 selected references. The underlying rationale for this approach is that core conceptual references will be cited in multiple articles and that references cited in the same paper (co-citations) are likely to be conceptually related. Network analysis of co-cited references should also be able to identify multiple conceptual frameworks (e.g. attitude theory, social consequences of PA designation, etc.), if these are being used. The co-citation network was created in Bibexcel (Perssonet al. 2009), plotted with Pajek (Batagelj and Mrvar 1998) and redrawn with Inkscape (Bah 2009).
To review the papers and to better provide empirical support for future model building, we clustered and ranked significant variables associated or correlated with positive/negative attitudes to PAs. Firstly, we assigned an ID code to each paper. We then clustered them into two broad categories based on whether they applied qualitative or quantitative approaches. Those applying quantitative approaches (66% of the total sample) were used to identify statistically significant associations between dependent and explanatory variables (see following sections) which were ranked based on the frequency of their statistical significance. The remaining papers (those eschewing model testing in favour of exploratory and descriptive statistics) were used to provide context and support observed quantitative associations and correlations.
| Results|| |
More than 90% of the studies were published after the year 2000. Asia was the most represented continent (49.6% of studies), followed by Africa (41.5%), and Central and South America (8.9%). Nepal, India, Tanzania, Uganda and China were the most studied countries. The majority of studies were published in biology and environment conservation journals (43.9%), human ecology and sustainable development journals (20%) and environmental management journals (17%). Most of the articles used a single PA as a case study (78%) with National Parks the most frequent designation (53.7% of studies).
All the studies applied social science techniques, mainly semi-structured interviews based on questionnaires including open- and closed-ended questions, to survey the attitudes of local people towards PAs.
One of the most striking features of our sample of articles about attitudes to PAs in the developing world is the general absence of a theoretical framework – a critical component for model building approaches (Grafen and Hails 2002). Within our sample, about 65% (80 out of 123 articles) were exclusively based on empirical studies and can be interpreted as being indirectly influenced by socio-psychological theories such as the Theory of Reasoned Action (TRA) and the Theory of Planned Behaviour (TPB) (Fishbein and Ajzen 1975; Fishbein 1979). The stated conceptual basis in remaining articles (about 35%) were based on diverse sources, including social anthropology (linking negative attitudes towards PAs to social conflicts and historical grievances) (e.g. Hartter and Goldman 2010); economic and market theories that assume that PA-related activities and initiatives that generate net benefits will tend to positively influence perceptions (e.g. Guthiga et al. 2008); and the biophilia hypothesis and wildlife value orientation theory, using the general assumption that humans have intrinsic emotional connections with wildlife that drives positive attitudes to conservation and pro-conservation behaviours (e.g. Bauer 2003; Anthony 2007).
The lack of conceptual framing was further supported by our co-citation network analysis ([Figure 1]), which clearly shows that the majority of the most highly cited articles were other empirical attitude studies from (almost exclusively) natural science journals (e.g. Infield 1988; Newmark et al. 1993; Fiallo and Jacobson 1995). This implies that the majority of studies are re-working or replicating existing empirically-grounded methodologies. This pattern of citations indicates that there have been very few attempts to draw on the rich social science literature that seeks to understand how attitudes form and how they interact with knowledge and behaviours (see discussion).
|Figure 1 Co-citation analysis based on cited references that appear in the 123 surveyed articles. Circle size represents the number of times the paper has been cited and line weight represents the number of co-citations (cited in the same article) with a threshold of 8 co-citations to enhance clarity. Centrality (betweeness) is determined by the fraction of all directed paths between any two vertices that pass through a node; closeness (distance of one vertex to others) depends on inverse distance to other vertices. Full citations are provided in Appendix B|
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Although the choice of response variables in observation studies is typically more clear-cut than that of explanatory variables (Cox and Snell 1974), depending on the hypothesis it is often desirable to use one or more measures (Cox and Wermuth 1996). On the other hand, a wide range of response variables and differences in how they are measured cause a low level of replication, making direct comparison of studies problematic (Pullin et al. 2013). Indeed, in our review we observed a wide range of response variables ([Table 1]). Many were framed in terms of whether local people like/dislike the park or agree/disagree with de-gazzeting according to the main objective of the paper (e.g. Allendorf 2007). However, some studies sought to explain attitudes to specific aspects of people-park interactions based on management imperatives or other perceptions and beliefs, such as: perceived PA-related benefits (i.e. employment, infrastructures and services, etc.) and costs (i.e. wildlife damages, eviction, harassments, etc.) (Sarker and Røskaft 2011; Karanth and Nepal 2012); relationships with PA staff (Newmarket al. 1993); interaction with management approaches and effectiveness of management programmes (Archabald and Naughton-Treves 2001; Mehta and Heinen 2001; Guthigaet al. 2008); and ecotourism development (Walpole and Goodwin 2001).
As an added complication, response variables used in one study are frequently used as explanatory variables in other studies, depending on the focus of the study – this is especially the case for nested and covariate factors influencing attitudes (e.g. knowledge, behaviours, perceptions and beliefs) as well as for attitudes relating to specific aspects of people-park interactions (see [Table 1]). Moreover, the choice and measurement of response variables strongly influences the type and power of the statistical analysis (techniques span from simple chi-square tests to multivariate analysis and models).
As outlined previously, the choice of explanatory variables is critical to model building, though it is rarely straightforward. In general, variable choice should be based on a combination of theoretical relevance and the results of high quality empirical studies (Cox and Wermuth 1996; Grafen and Hails 2002). Moreover, the number of variables entering the model should be kept to the absolute minimum needed to address the question of interest (Grafen and Hails 2002). Where theory is poorly developed (see Conceptual Approaches above) and empirical findings are partial or contradictory; decisions about choice/number of explanatory variables are often arbitrary leading to problems associated with the inclusion of junk data or the omission of potentially significant factors.
Explanatory variables in our reviewed studies ([Table 2]) included a broad range of demographic and socio-economic factors that together with spatial variables, measures of knowledge, behaviours, perceptions and beliefs (i.e. perceived PA-related benefits and costs) are frequently associated or correlated with positive or negative attitudes of local people to PAs. Some of these variables influenced attitudes both positively and negatively, depending on the study (Mehta and Heinen 2001; Htunet al. 2012). For example, key demographic variables such as age and gender may be associated with both positive and negative attitudes to PAs depending on the cultural/historical context (e.g. past evictions). They may also co-vary with other factors (e.g. knowledge) that have complex, culturally specific associations with attitudes to the PA. This is well illustrated by two contrasting case studies: 1) younger people living near the Kruger National Park in South Africa have more favourable attitudes towards the park due to a lack of exposure to historical injustices and abundant opportunities for local children to participate in educational excursions organised by the Park (Anthony 2007); 2) elders in rural areas surrounding four PAs in Ethiopia held more positive attitudes of the parks than younger residents, possibly because their personal experience of the impacts of environmental degradation allowed them to better recognise the important role of the parks in wildlife conservation (Tessemaet al. 2010).
|Table 2 Explanatory variables – number of times the explanatory variable is found statistically significant in explaining response variables and total number that variable is taken into consideration by articles using quantitative metrics to test the association/correlation|
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In the following sections we provide a detailed analysis of different categories of explanatory and/or response variables.
Socio-demographic variables, including population parameters such as age and gender, are considered as key factors for explaining environmental attitudes (Gifford and Sussman 2012). In our sample, gender is the most important demographic variable explaining attitudes to PA ([Table 2]). Nevertheless, such trends are by no means universal and are highly dependent on economic, cultural and ethnic contexts. Although gender is built upon sexual characteristics, it refers to how roles, rights and responsibilities for men and women are defined in a given society. In Asian countries, for example, women are less likely to express their opinions on the problems and benefits associated with PAs (e.g. Arjunanet al. 2006; Allendorf and Allendorf 2012). This reluctance (sometimes termed the invisibility of gendered vulnerabilities) has been associated with gender norms, space, work status, and identity factors (Ogra 2008).
Several studies also observed that women were less informed about local wildlife and PA management (Xuet al. 2006; Olomí-Solàet al. 2012), and had poorer knowledge about wildlife and ecological issues (Nyhus and Tilson 2003; Bitanyiet al. 2012). As gender inequalities may exist in many countries in terms of access to opportunities for education and participation in decisions involving conservation, use and management of natural resources, the observed associations between attitudes and gender may reflect the interaction between gender and knowledge (e.g. experiential knowledge of wild animals) rather than the direct effect of gender on attitudes (Xuet al. 2006). The generality of such relationships is, however, difficult to assess given the low frequency of PA studies that explicitly address gender equality (Pullin et al. 2013).
Gender may also be associated with how costs and benefits of wildlife are perceived and experienced (Mehta and Kellert 1998; Sah and Heinen 2001; Sarker and Røskaft 2011). Women generally attach more individual and tangible values to resources, hunting and ecosystem services provided by PAs (Ogra 2009; Allendorf and Allendorf 2013). Moreover, women are often more exposed to the negative socioeconomic costs of wildlife (e.g. crop raiding, risks to livelihood, etc.) which, in turn, is reflected in more negative attitudes towards conservation (Allendorfet al. 2006).
There is also a complex relationship between gender and species preferences, with a clear distinction between cognitive (belief, symbolic meaning) and emotional aspects (fear, like, dislike). The former is well portrayed in a study exploring the animal preferences and acceptability of wildlife management actions around Serengeti National Park in Tanzania: Kaltenborn et al. (2006) found that men expressed stronger preferences for all animals – possibly reflecting the traditional role of hunting for males in that culture. Gender differences in attitudes towards certain animal species have been also been related to safety needs (i.e. spread of disease, competition for resources with livestock and wildlife damages) (Groom and Harris 2008). Women have also been recorded as more likely to recognise the negative correlation between human behaviour and habitat degradation (Baral and Heinen 2007), accept a ban on fishing or hunting inside a PA (Martino 2008), and make behavioural changes to conserve the environment (Allendorf and Allendorf 2012).
Age effects are also difficult to interpret due to covariance with many other socio-demographic characteristics, its explanatory power being frequently associated with educational status or the length of residence, as well as with knowledge, perceptions and beliefs (see Waylenet al. 2009).
Region of origin and time of residence are also important explanatory variables in many studies ([Table 2]). Interestingly, while indigenous or long-term residents generally have more positive attitudes to the Park and its conservation (Ferreira and Freire 2009; Leeet al. 2009; Vodouhêet al. 2010), they often possess more negative attitudes to PA staff or departments (Newmarket al. 1993; Arjunanet al. 2006). Conflicts with PA managers and rangers mainly arise because residents associate staff with bans on natural resources extraction and livestock keeping (Heinen and Shrivastava 2009), harassment when rules are being transgressed (Infield and Namara 2001) and fear of resettlement (Allendorf et al. 2007).
Finally, ethnicity can be a powerful predictor of attitudes towards wildlife and resource use (Mehta and Heinen 2001; Holmes 2003a; Baral and Heinen 2007). This is unsurprising given the importance of social norms and traditional resource management systems in shaping and controlling resource use (St Johnet al. 2010).
The importance of socio-economic variables rests on the assumption that evaluative judgments shaping attitudes may be influenced by cognitive, affective and conative (e.g. impulse, desire, volition) aspects (Gifford and Sussman 2012). Thus, education (both formal and informal) is considered among the most important factors driving knowledge and learning processes, and thereby, influencing the direction of the attitude toward an object (here PA). By contrast, wealth-related variables such as occupation and income can strongly affect human needs and whose effect on attitudes can be directly related to Maslow's needs framework (see Discussion).
In our sample, education was the most significant socioeconomic predictor of positive attitudes towards PAs and, to some extent, to perceptions of PA-related benefits and costs ([Table 2]). Many studies demonstrated that education programmes can lead to more positive attitudes towards PA. However, the effects of education are frequently confounded by other socio-demographic variables such as age and gender. This covariate effect will often depend upon the homogeneity of community. For example, in the developing world, older inhabitants are often both less educated and less likely to support PAs (Fiallo and Jacobson 1995; Anthony 2007), especially use-restrictions imposed by park regulations.
Education has been also suggested as a key driver of better employment opportunities and as a means to generate alternative livelihood strategies, diminishing direct dependency on natural resources (Stemet al. 2003; Kidegheshoet al. 2007). Formal education has also been associated with participation in pro-conservation activities such as anti-poaching patrols, ecotourism, and sustainable use of resources (Vodouhêet al. 2010). Nevertheless, education level is not always positively associated with favourable attitudes. In comparing the levels of community satisfaction with three distinct forest management approaches of Kakamega Forest in Kenya, Guthiga et al. (2008) found that educated households were more dissatisfied with the protectionist approach despite its ecological effectiveness.
Measures of wealth variables (i.e. income, occupation, landholding, and receipt of incentives) were the second most important category of socioeconomic variables in predicting attitudes ([Table 2]) and are frequently used as proxies of human well-being (Pullin et al. 2013). Being a PA employee, having a PA-related employment (e.g. ecotourism) or having a family member employed in a PA-related job was generally a predictor of positive attitudes towards the PA, its management and associated ecotourism development (Walpole and Goodwin 2001; Anthony 2007; Snyman 2012). Individuals from poor households or those highly dependent on natural resources are, in most cases, associated with negative attitudes towards PAs (Doliscaet al. 2006; Ferreira and Freire 2009) and acutely perceive wildlife costs such as crop damages, livestock losses and reduced access to natural resources (Spiteri and Nepal 2006; Shibia 2010). Thus, non-farmers and households with higher incomes are usually likely to hold a more favourable attitude towards conservation. Increasing technical skills and enlarging income opportunities for poor people has therefore often been suggested as a way to increase positive attitudes. In a case study from the Forêt des Pins Reserve in Haiti, the most important factor in stimulating environmental participation was the provision of opportunities to increase incomes (Doliscaet al. 2006).
Finally, being a member of social groups (traditional authority, natural resource management user group, etc.) has been associated with positive attitudes to PAs (Anthony 2007), PA management (Doliscaet al. 2006) and knowledge (Xuet al. 2006). Such social membership generally drives a more positive attitude to PA and a stronger motivation to participate in PA management (Sirivongs and Tsuchiya 2012) since it reflects higher levels of integration of individuals into their respective communities, which in turn facilitates a better exchange of information, adherence to norms and sanctions, and contributes to a higher trust in authorities (including PA staff) (Bauer 2003). By assessing which factors influence conservation attitudes of local people towards Cat Tien National Park in South Vietnam, Thuy et al. (2011) found a strong correlation between positive attitudes and social capital. Here, social capital is defined as features of social organisation, including trust, norms and networks that can facilitate coordinated actions and active participation, improving the collaborative management of natural resources (Pretty 2003).
Spatial variables may also be strongly associated with attitudes to PAs. For example, residents that live closer to the park boundary (where conflicts are more likely) often have more negative attitudes than those in more distant settlements (Jim and Xu 2002; Spiteri and Nepal 2008). Spatial variables are important for two main reasons. Firstly, there may be cognitive, affective and conative relationships between humans and places, often identified as Sense of Place (Jorgensen and Stedman 2001). Secondly, the way people perceive an environmental problem is often affected by spatial distance (e.g. NIMBY – Not In My BackYard – syndrome) and the sense of environmental responsibility may therefore often be scale dependent (Uzzell 2000).
Perhaps the main driver of spatial variation in support for PAs is an unequal distribution of costs and benefits. Positive attitudes to PAs are often driven by benefits arising from conservation activities (Mehta and Heinen 2001) and ecotourism development (Heet al. 2008), whereas more negative attitudes are often driven by higher frequencies or intensities of human-wildlife conflicts (Hartter 2009; Sarker and Røskaft 2011) experienced by residents living closer to PAs. Such residents frequently perceiving wildlife damage as a threat to their food security, income and personal safety (Shrestha and Alavalapati 2006).
Roth (2008) has argued that conservation spaces are generally established through top-down approaches and may therefore conflict with the complex local livelihood spatiality and availability of natural resources. This can lead to restricted access of certain social groups to previously shared resources that frequently bear the greatest costs of PAs (e.g. women, poor, etc.) (Spiteri and Nepal 2008). For example, the majority of buffer zone residents of the Allpahuayo-Mishana National Reserve in the Peruvian Amazon had a negative attitude to PA primarily because of the perceived loss of resource use rights (Cardozo 2011) – a type of 'economic displacement'.
This could have the effect of increasing negative attitudes and social injustice among these groups. New livelihood opportunities such as ecotourism may also be perceived as unequally distributed or unable to replicate income generation from traditional activities. For example, new tourism revenues from the Cross River National Park in Nigeria did not effectively compensate for the loss of traditional timber extraction and collection of non-timber forest products (NTFPs) – activities to which people also attached considerable cultural value (Ezebilo and Mattsson 2010).
The expectations of individuals with respect to benefits from the PA may also have a spatial component. Specifically, residents living closer to a PA boundary might expect greater benefits from the PAs in terms of income generation, compensation or right to exploit certain natural resources (Spiteri and Nepal 2006). The potential consequences of these expectations not being met are an increase in 'social frustration' (Jim and Xu 2002) and, as a result decreased support for the Park (Simelaneet al. 2006).
Knowledge, Perceptions and Beliefs
Behavioural, normative and control beliefs, as well as affective and cognitive processes (the way in which knowledge is acquired) play a key role in the formation of attitudes (Ajzen 2001). In our sample, knowledge metrics are mostly restricted to environmental and general ecological issues and PA characteristics (name, boundaries, goals, regulations and rights). Studies found a significant association between knowledge and positive attitudes towards a number of response variables including forests and PA management (Macuraet al. 2011) and perceptions of benefits and ecosystem services (Allendorf and Yang 2013). Knowledge is often positively associated with the level of both education and participation in PA or forest management (Vodouhê et al. 2010; Olomí-Solà et al. 2012), both of which influence access to information, and individual and social learning processes.
More generally, the power of knowledge for predicting attitudes was typically low in our sample ([Table 2]), with no studies going on to investigate the potential influence of knowledge on behaviour. Moreover, the effect of other types of knowledge (i.e. traditional or local knowledge) which play a crucial role in rural and indigenous communities (e.g. traditional tools and techniques for hunting or fishing, use of medicinal plants, etc.) was only marginally considered.
Measurements of perceptions and beliefs mainly relied on costs and benefits associated with PA, and particularly on the trade-off between wildlife conservation and local subsistence. For example, damage by wildlife has been identified as the primary source of PA-people conflicts and the most difficult to off-set (Weladji and Tchamba 2003), despite some evidence of over-reporting (Gillingham and Lee 2003). In the absence of compensation mechanisms, wildlife damage could lead to an increase in negative attitudes to PA and PA management (lack of support), illegal behaviours (e.g. poaching) and social conflicts (Infield and Namara 2001). Some of these negative effects can be ameliorated through co-management, giving more authority to local communities to protect their crops/livestock (Bajracharyaet al. 2006) and increasing the sense of ownership of natural resources within the PA (Gillingham and Lee 2003). However, even where co-management approaches are in place, behavioural changes have not necessarily followed (Holmes 2003b; Arjunanet al. 2006).
Non-instrumental values such as spiritual significance, ecological value, aesthetic characteristics and safety are also frequently associated with positive attitudes to PAs (e.g. Allendorf 2007; Sirivongs and Tsuchiya 2012). However, such values are rarely assessed and, if they are studied are difficult to interpret or compare. For example, Allendorf et al. (2007) found that residents simultaneously considered the illegal extraction of resources to be both a benefit and a problem in the Royal Bardia National Park in western Nepal. This suggests that while bio-centric values may drive positive views of PAs (as places for conserving nature and natural resources), more ego-centric values may go to the opposite direction, negatively influencing how people view a PA (a place of “bans”) and associated PA staff (those with the power to punish). This attitudinal ambivalence has been frequently observed by psychologists and is interpreted as the result of a conflict between cognition and affect or conflicting beliefs driven by knowledge (Ajzen 2001).
The relationship between attitudes and behaviour is at the core of socio-psychological theories and models of social change (Ajzen 2001). In the context of PAs, understanding the factors that motivate human behaviours is crucial. Nevertheless, studies of PA-related behaviours are rare and frequently problematic (Holmes 2003b), particularly when the focus is on sensitive or illegal behaviours (e.g. poaching) that are often most important for implementing effective biodiversity conservation programmes in PAs and buffer zones (e.g. Gama et al. 2016). One of the reasons that behavioural studies are so sorely needed is also one of the fundamental weaknesses of studies that focus on attitudes, namely, that pro-conservation attitudes do not necessarily translate into pro-conservation behaviours (reviewed in St Johnet al. 2010). Even when programmes aiming at changing negative attitudes are in place (e.g. incentive-based, community-based conservation, etc.), they may only change attitudes while leaving environmentally destructive behaviours intact. This was observed in communities around Lake Mburo National Park in Uganda, where awareness raising activities led to more positive attitudes of participating communities towards the park, but failed to decrease poaching and illegal grazing (Infield and Namara 2001).
| Discussion|| |
Our review of 123 studies revealed that a prominent feature of PA attitude research in the developing world is that it typically has been descriptive and exploratory, with an associated lack of conceptual underpinning. There are several potential reasons for this, including: 1) the academic background of the research team may be exclusively from the natural sciences, part of a more general absence of inter-disciplinarity in much conservation research (Balmford and Cowling 2006; Ladle and Jepson 2008); 2) in contrast to areas such as biodiversity assessment, methods and approaches to designing attitude studies of protected areas have not been standardised and there appears to be a general absence of accessible and context methodologies/handbooks. This is clearly apparent in the co-citation analysis of the most cited articles ([Figure 1]), the vast majority of which are other empirical studies.
It should be noted that there are a number of well-developed theories and conceptual models that are commonly used in attitude research in other disciplinary areas, particularly social psychology. Specifically, the two most widely used conceptual models of the relationship between attitudes, knowledge and behaviour are the Theory of Reasoned Action (TRA) and the Theory of Planned Behaviour (TPB) (Fishbein and Ajzen 1975; Fishbein 1979). The TPB and TRA both suggest that individual behavioural intentions depend on the person's attitude about the behaviour and subjective norms (or perceived social pressure to engage or not in a behaviour). The main difference between the models is that the TPB incorporates perceived behavioural control, the belief that an individual holds about how easy or difficult it will be to perform a specific behaviour. Here, attitude is defined as a tendency expressed by evaluating a particular entity with some degree of favour or disfavour (Eagly and Chaiken 1993). A closely related framework is the Value-Attitude-Behaviour (VAB) model, which emphasises the causal link between values, attitudes and behaviours, and which assumes that values are underlying dispositions for individual beliefs/attitudes and that behaviors are the product of evaluating options oriented by values (Rokeach 1973; Schwartz 1992). Manfredo and colleagues (Manfredo et al. 2004; Manfredo et al. 2009; Vaske and Manfredo 2012) have used these insights to develop a “Cognitive Hierarchy Framework”, a hierarchical VAB model for studying human thoughts and behaviours towards wildlife. However, although there have been a few direct applications of these models to conservation attitudes, there is some evidence that these theories are nonetheless indirectly influencing research designs (see Conceptual Approaches above). Specifically, many PA attitude studies are clear extensions of the underlying logic of the TRA, TPB and VAB models in that they seek simple deterministic relationships (and explanations) between socio-cultural variables and conservation attitudes/behaviours.
An alternative (and currently unused in PA attitude research) psychological framework for understanding behaviours is Maslow's Theory of Human Motivation (Maslow 1943). This theory stresses on the motivating factors driving human behaviour, classifying human needs in a hierarchy (from survival to self-actualisation) and suggesting that individuals tend to move up the hierarchy when their needs at a lower level are being met. Many PAs have the potential (if not the mission) to meet various individual, social group, or societal or community needs. By extension, people can be motivated to behave (or not) in ways favourable to conservation based on the degree to which the PA is perceived as meeting these needs (Rishiet al. 2008).
The hierarchy of needs could be broadly mapped onto PAs as follows: 1) survival needs mainly rely on access to essential natural resources (food, water, etc.); 2) security needs reflect shelter, fear and threats (e.g. dangerous animals, pests, etc.), livelihood and contingency security (e.g. fire, extreme climate events, etc.), natural impacts and costs (wildlife crop damages, etc.); 3) belongingness needs may relate to formal or informal associations with the PA and its staff; 4) self-esteem reflects feelings of pride about PA (e.g. its association with local or national identity), or membership of social groups (Traditional Authority, natural resource management user groups, etc.), and; 5) self-actualisation could be associated with personal growth and fulfilment activities such as experiencing nature or feelings of spiritual renewal. Accordingly, if survival needs are not satisfied, people are unlikely to be motivated to participate in conservation related activities. Moreover, attitudes (positive or negative) to the PA may vary in relation to the relative position of a person on the hierarchy of needs and the degree to which the park is perceived as meeting them.
Both attitude theories and Maslow's hierarchy implicitly assume that values strongly influence beliefs, attitudes, norms, motivations, and ultimately, behaviours. Nevertheless, preferences, choices or behaviours may differ between individuals with a similar suite of values as the result of a different priority given to those values reflecting a broad range of motivations (e.g. egoistic, altruistic, etc.). When conflicts between values occur, people tend to act based on their own priorities. For example, pro-conservation attitudes and behaviours are often superseded by short-term local needs. Thus, both the TRA and TPB are widely acknowledged to be incomplete, behavioural changes being particularly sensitive to additional factors such as past behaviours/habits, belief salience (Cronen and Conville 1973), perceived behavioural control (Ajzen and Madden 1986), moral norms (Manstead 2000), self-identity (Sparks and Guthrie 1998) and affective beliefs (Frenchet al. 2005). Moreover, such an approach sustains traditional governance approaches and interventions (e.g. targeted awareness-raising) while largely ignoring that social transformations typically involve concurrent changes in technology, markets, user practices, regulations, infrastructures and cultural meanings (Elzenet al. 2004; Shove 2010). These wider contextual changes may align with targeted interventions or may mitigate against the success of simple communications-based strategies aimed at improving attitudes. In this respect PA attitude researchers need to have a clear understanding of historical grievances and social stratification in the population they are studying, for example, whether PAs are supported by the urban majority and viewed negatively by the rural minority who interact with them (Triguero-Maset al. 2009). Likewise, it is also important to have an understanding of whether PAs are championed by the ruling elite (who may view them as valuable symbols of international/regional prestige) while seen as costly and inconvenient impositions by local communities (Allendorfet al . 2007).
Growth of the global PA network has been partly driven by predominantly western desires to protect wilderness from human encroachment (Jepson et al. 2011). This Manichean separation of nature from culture has often led to resistance of local people to designations and long standing historical grievances against PAs, especially in non-industrial societies and developing countries where values associated with nature are different and social norms have contributed to traditional systems of natural resources management (St John et al. 2010). Moreover, neoliberal economics and recent globalisation have established different conditions of governance, introducing new global actors (e.g. international conservation NGOs, World Bank, etc.), demarking new forms of control of people and resources (e.g. private PAs, community-based conservation schemes) and shaping new types of powers (e.g. devolution, corporations, etc.). In this context, conservation initiatives such as the establishment of new PAs can locally alter social norms and traditional governance systems, some of which may have provided positive management practices (Jones et al. 2008).
Some of these issues have been comprehensively addressed in social anthropology research. The most cited (and controversial) social impacts of PAs include displacement of people from PAs (Rangarajan and Shahabuddin 2006), changes in land-use rights and access to natural resources (Dahlberget al. 2010), and social justice (unequal distribution of PA-related benefits, poverty, etc.) (Brechinet al . 2003; Brockington and Wilkie 2015). Integrated and cooperative conservation strategies such as Integrated Conservation and Development Projects (ICDPs), Community-Based Conservation (CBC), pro-poor conservation programmes and ecotourism development projects have been among the most cited initiatives to offset these negative impacts of PAs on local communities and to promote positive attitudes and pro-park behaviours. However, many conservationists remain critical, arguing that: 1) multiple objectives are rarely achieved in community-based approaches (Agrawal and Gibson 1999; Adam and Hulme 2001; Musumaliet al. 2007); 2) perceptions and interactions between conservation protagonists may change, keeping local conflicts unresolved, interests unmoved and sustaining people's behaviours (Infield and Namara, 2001); 3) PA-related benefits and costs may be distributed unevenly increasing social differences and poverty (Gibbes and Keys 2010); 4) local people's behaviours may be influenced by corporate interests (e.g. international agencies, international environmental NGOs, etc.), and; 4) cooperation among different groups and co-management may depend upon the characteristics and powers of individuals which form the groups as well as the social, institutional and political circumstances in which groups are cooperating and taking decisions (Pomeroyet al. 2001).
The application of quantitative and model-based approaches and the standardisation of response and explanatory variables should be encouraged to provide robust and scaleable information for researchers and to make attitude studies comparable among different contexts and cultures. Of course, choice of statistical methods depends upon the specific research question and hypotheses that researchers wish to test (Newing 2011). Generally speaking, General Linear Models (continuous response variable) or Binary Logistic Regressions (dichotomous response variable) are the most appropriate statistical approaches for predicting attitudes. Both these approaches are sufficiently flexible to allow for a wide range of explanatory variables (e.g. nominal, ordinal or continuous data) and are particularly useful to test a priori hypotheses. Nevertheless, since explanatory variables may be numerous and highly correlated, stepwise selection is often applied in order to reduce model complexity. This traditional analytical approach has been often criticised for producing significant bias (Whittingham et al. 2006), excluding multiple working hypotheses and limiting critical thinking (Burnham and Anderson, 2002). Thus, innovative techniques for model selection based on more than one model (e.g. multi-model inference) may be more effective for deriving plausible conclusions from empirical data (Burnham and Anderson, 2002). Such approaches are mainly based on information-theoretic criteria and model averaging, generating a number of plausible models and selecting the best one according to some criteria (e.g., AIC, AICc, QAIC, or TIC). Model averaging may have the added advantage of encouraging harder thinking about the system under study and the data collected, allowing the relative importance of each variable to be assessed across all models through statistical scores (e.g. sum of the Akaike weights).
Examining alternative models is generally considered a better way to deal with complex systems and correlated effects of variables. Multi-model approaches are consequently being increasingly applied by environmental scientists, particularly for ecological modelling and behavioural studies (e.g. Austin 2007; Burnham et al. 2011). Innovative approaches for selecting models and variables have also been recently applied by environmental economists to study the outcomes and trade-offs of PAs, providing a more robust evaluation of conservation programmes and policies (Baylis et al. 2016). Likewise, 'random forests' (an algorithm to select key variables to use in regression and classification analyses) has been combined with model averaging to globally assess the social and conservation outcomes of PAs (Oldekop et al. 2016). Similarly, matching-based statistical approaches have been applied to identify and quantify the effects of PAs on social and environmental outcomes (Andam et al. 2010), and appears to be a powerful analytical method to deal with environmental causal effects (Agrawal 2014).
Although the choice to include (or remove) an explanatory variable within a model ultimately depends on the experimental context and its ability to provide meaning to the data (condicio sine qua non), these new statistical approaches can be easily applied to model social and attitudinal data, given the complex relationship between explanatory and response variables and the uncertainty characterising hypotheses.
An alternative approach to deal with correlated variables is through Principal Component Analysis (PCA) which transforms a number of correlated variables into a set of uncorrelated variables, ranking them in a decreasing order of importance. The first Principal Component (PC) is usually an index of the overall “size” of the data, allowing the number of variables to be reduced. Although this method is extremely useful for exploring data, revealing preliminary patterns, and building a posteriori hypotheses, it is generally poorly applied. Such important contextual insights are rarely integrated into attitude studies, quantitative social surveys or the interventions that are based on them.
| Recommendations and Conclusions|| |
Synthesising the results of attitude studies of PAs in the developing world is inherently difficult due to the wide range of response and explanatory variables and the lack of a robust and widely accepted conceptual framework that could inform model development. Arguably, these weaknesses have led to PA attitude studies that are scattered across the academic literature, poorly cited and increasingly absent from mainstream conservation journals. There are three main reasons that these trends should be of concern to conservationists: 1) as competition between land-uses increases over the following century, PAs will be increasingly asked to justify the continued investment of public and private organisations (Ladleet al. 2011). Explicitly demonstrating the support of local communities will be an essential aspect of such justifications, as will measures of the services (tangible and intangible) that the PA provides for nearby residents and wider society; 2) effective PA governance requires a detailed knowledge of the perceptions and behaviours of local residents. Since many of the management problems associated with PAs come from individual behaviours and small-scale activities (e.g. deforestation, hunting, etc.) (Bonaiutoet al. 2002), well designed social surveys have the potential to provide this knowledge, generating insights into what sort of interventions may most effectively mitigate conflicts and promote positive attitudes, providing a useful and evidence-based method to assessing and monitoring the social impacts of conservation interventions, and; 3) since negative attitudes typically occur when there is a mismatch between values, to understand (and potentially change) attitudes to PAs it is also necessary to understand what values they represent (see Ladleet al. 2011 for a detailed discussion), how these values are perceived by the social group of interest (local community, society, etc.), and how the values of the PA differ from those held by this group.
One way to face these challenges could be to more closely align the values of the park with the values of the target social group. Such alignment could potentially be achieved through redefining or re-stating the social purpose of the park to better align with the values of the target group. If this is unacceptable from a conservation perspective, policy makers could try to influence the attitudes/behaviour of the target social group. Either approach should be carefully informed by quantitative social research – ideally based upon robust concepts and methodologies.
Based on our review we have four general recommendations for improving PA attitude studies. First, the conceptual basis of studies (see Discussion) should be explicitly acknowledged and used to define research questions, guide choice of study variables and interpret results. Second, response and explanatory variables should be chosen on the basis of theory and empirical studies (See [Table 1] and [Table 2]) and modified in response to local context. Although complete standardisation is unrealistic, comparison of studies would be greatly enhanced by reducing variation in the measurement of key demographic and socioeconomic variables – our survey provides a first step to guide this selection. Third, studies should strive to go beyond purely descriptive approaches (although these undoubtedly have considerable value) and embrace model-testing, adopting robust statistical practices that provide predictive insights into the key factors driving attitudes. Finally, results should be carefully filtered through the lens of theory and interpreted in the context of local circumstances and history.
Adopting these measures should improve the quality of research and comparability of future studies, allowing us to tease out macro geographic patterns that are not currently apparent. Nevertheless, without a more systematic and unified approach to assessing PA attitudes there is little prospect of using attitude metrics as part of a wider system of assessment of the cultural and social value of PAs. In this context, an important aim for conservation should be the development of standard, validated social surveys for local communities that live near PAs that can be administered in isolation or as part of a geographically wider coordinated assessment. More generally, our findings are broadly concordant with those of Pullin and his colleagues, who concluded their recent review of the effects of protected areas on human well-being by observing that the current evidence base provides very little support for improved decision making (Pullin et al. 2013). Social surveys are a vital source of evidence about people-park interactions, but are capable of generating more smoke than light if poorly designed and implemented.
| Acknowledgements|| |
CB is funded by the Brazilian Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq) grant 501168/2012-5&168258/2014-5. RJL is supported by CNPQ 311412/2011-4 and PJ is supported by CNPQ 400325/2014-4. We are very grateful to Dr. Ricardo Correia for re-analysing the co-citation network ([Figure 1]).
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[Table 1], [Table 2]