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Network analysis to support environmental resources management. A case study in the Cerrado, Brazil
Land Use Policy 59 (2016) 217–226
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Land Use Policy journal homepage: www.elsevier.com/locate/landusepol
Network analysis to support environmental resources management. A case study in the Cerrado, Brazil Giovanni Santopuoli b,∗ , Jader Nunes Cachoeira a , Marco Marchetti b , Marcelo Ribeiro Viola c , Marcos Giongo a a
Forest Engineering, Universidade Federal do Tocantins, Campus of Gurupi (TO), Brazil Laboratory of Natural Resources and Environmental Planning, Department of Biosciences and Territory, University of Molise, Cda Fonte Lappone, snc, 86090 Pesche (IS), Italy c Forest Engineering, Universidade Federal de Lavras, Soil and Water Engineering Group, Lavras, Brazil b
a r t i c l e
i n f o
Article history: Received 29 April 2016 Received in revised form 5 July 2016 Accepted 5 September 2016 Keywords: Network analysis Cognitive map Bushfire Cerrado Brazil
a b s t r a c t The study examines citizens’ opinions about one crucial factor: the fire that affects the Brazilian savannah “Cerrado”. The paper aims at introducing a new tool that facilitates the assessment of people’s behaviour in order to support practitioners and decision makers to develop management strategies that fostering the environmental conservation, economic growth and human wellbeing. The study applies the network analysis in order to analyse the citizens’ opinions about causes of fire ignition and suppression activities for firefighting evoked by local inhabitants during the face-to-face interviews. The main finding carried out in this work is the usefulness of a cognitive map for synthesising a variety of people’s beliefs. Furthermore, the study reveals the general lack of awareness among people concerning fire use and management and the careless use of fire in rural activities. The chi-square test reveals that natural and physical dimensions affect society’s beliefs with statistical significance p < 0.001. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Environmental resources management planning is one of the most important tools for assuring the sustainable use of natural resources and promoting sustainable development (Grunewald and Bastian, 2015). However, managing environmental problems becomes more complicated when humans are involved (Özesmi and Özesmi, 2004) for two main reasons. Firstly, the numerous goods and services that natural ecosystems provide attract many categories of stakeholders (Daily et al., 2009; van Wensem, 2013). Secondly, landowners and local laborers are the main managers of rural environments and their legitimation is crucial for the implementation of a management plan (Nuno et al., 2014; Khew et al., 2014). For these reasons, inhabitants’ behavior and opinions are very important for decision makers in terms of the development and the implementation of a management plan (Appelstrand, 2002;
∗ Corresponding author at: Laboratory of Natural Resources and Environmental Planning, Department of Biosciences and Territory, University of Molise, Cda Fonte Lappone, snc, 86090 Pesche (IS), Italy. E-mail addresses: [email protected], [email protected] (G. Santopuoli). http://dx.doi.org/10.1016/j.landusepol.2016.09.002 0264-8377/© 2016 Elsevier Ltd. All rights reserved.
Janse and Konijnendijk, 2007), such as a forest management plan or a fire prevention and control plan. In such cases, the knowledge of the local traditional background supplies very significant insights for managing environmental resources (Mistry, 1998). Otherwise, their opinions would be very misconceived and limited (Jones et al., 2011) requiring greater efforts in order to share and implement management strategies. Nevertheless, assessing citizens’ opinions is not only a crucial aspect for local technicians and policy makers (Khew et al., 2014), but also represents an important learning phase that permits the concept of management to be shared with local inhabitants (Morse 2008; Bodin et al., 2006). Lindell et al. (2009) consider their perceptions as the social representations of such topics, since they determine people’s behavior and practices. Similarly, Buergelt and Paton (2014) stated that people’s experience and beliefs affect their behavior and their capacity building in risk management. Other authors, such as Jones et al. (2011) compared inhabitants’ perceptions to the “mental model” and stated that it partially describes the personal and internal representations of the external reality that citizens use to interact with the environment around them. Over the years, several methodologies for evaluating people’s opinions have been developed and one of these is network analysis through the cognitive maps. Although cognitive maps are frequently used in the sociology field (Ferreira et al., 2006;
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Morandin and Bergami, 2014; Dempwolf and Lyles, 2012), their use also becomes common in other field of study such as ecology and forestry (Santopuoli et al., 2012; Mendoza and Prabhu, 2003; Bodin et al., 2006). Cognitive maps allow the representation of people’s behavior and opinions (Jones et al., 2011), enabling decision makers to use this representation in decision-making activities beyond the scientific experience (Janse and Konijnendijk, 2007). Assessing local perceptions not only allows to identify how citizens consider a specific topic, but also allows to communicate with local inhabitants and practitioners, increasing the awareness of environmental problems management among them (Renn, 2006; Reed et al., 2008; Robertson et al., 2012; Toikkanen and Lipponen 2011). In this study, we adopt the cognitive map in order to explore citizens’ opinions about the fire in the “Cerrado” environment, also known as the Brazilian savannah, in the state of Tocantins, Brazil. In this area, fire represents one of the most important ecological factors, affecting the biodiversity conservation and the management of environmental resources. Apart from its origin, either naturally ignited or induced by humans, fire occurs very frequently – around two/three years – (Pereira et al., 2014) affecting forest areas, which are characterized as highly flammable vegetation (Klink and Machado, 2005; Hoffmann et al., 2009). Residents and local inhabitants consider fire very helpful for the majority of rural activities (Pivello, 2011). They use fire for several activities such as clearing trails or pathways and other open spaces around the houses in order to facilitate walking; stimulating grass regrowth, flowering and fruiting of some plants; removing crop residuals and waste; attracting game for collecting honey as well as driving and attracting game during hunting. Furthermore, the majority of indigenous populations use fire for religious and spiritual rituals, as well as for signals and traditional folklore (Mistry et al., 2005). Numerous efforts were carried out in order to assess the role and the effect of fire on the vegetation (Simon and Pennington, 2012; Pivello, 2011), but few studies focused on the relationship between local inhabitants and fire. Due to the fact that the majority of fires are human induced (Coughlan and Petty, 2012), being aware of people’s opinions can help to understand how to reduce bushfire risk. Traditional culture in the State of Tocantins fosters the daily use of fire, often with negligence (Mistry, 1998). This increases bushfire risk and often culminates with enormous areas of burned forest. One recent study (Cachoeira, 2015) highlights that in the state of Tocantins the average annual burned area is 3,200,000 ha. The poor surveillance services and the scarce presence of civil fire brigades allow the very rapid development of fire with severe damage to vegetation, animals and human infrastructures. The aim of this study is to explore the citizens’ vision about fire use and management, identifying the core causes of fire ignitions and the actions useful for firefighting and control according the inhabitants’ point of view, answering the research questions: which are the causes of fire ignition and how do people interact with bushfire? Furthermore, we test whether or not the social structure of the population affects the core opinions identified, answering the research question: does the social structure of the population affect inhabitants’ perceptions about fire ignition and fire risk reduction? In the next section, we present the conceptual framework of the study, followed by the materials and methods within which there will be the description of the study area, the data collection approach and the data analysis methodology. Section 4 shows the results obtained and finally Sections 5 and 6 report discussion and conclusion respectively.
2. Conceptual framework The study explores the citizens’ opinions about fire use and fire management in order to assess people’s view of fire within the Cer-
rado environment, as well as to support local policy and decision makers. To reach this goal, after the collection of information, the authors describe people’s beliefs through the use of network analysis. Two clarifications about people’s beliefs and network analysis are needed. Firstly, their beliefs represent, on one hand, the probable causes that citizens highlighted as responsible for fire ignition, and, on the other hand, the actions that people consider useful for preventing, fighting and controlling fire, or in other words, the actions that allow the reduction of fire impact on natural resources and human infrastructures. In this context, we use the term “cause” to indicate the source of bushfire ignition according to citizens’ opinions and the term “solution” to indicate a personal opinion about necessary actions to reduce bushfire. Secondly, the network analysis allows the causal relationship between causes and solutions, highlighting the citizens’ opinions about fire issues in the study area. Since we consider citizens’ opinions as the summary representation of individual experience, beliefs and behavior, we consider age, class, gender, residence and educational qualification as the parameters of social structure that can affect their opinions. Although race could be a proxy since the indigenous people use fire for several traditional rituals, this factor was not considered in the analysis of this study because the number of indigenous people interviewed was very low and therefor resulted statistically insignificant. The network was constructed using the causes and the solutions that each interviewed party listed during the collection phase. Each citizen mentioned such causes and such solutions that indirectly constitute one relationship. The authors used these relationships in order to construct the network. The connection between causes and solutions represents the view of citizens regarding fire issues, summarizing their awareness and preparedness. The final network, within which all the causes and solutions were connected, was graphically displayed by the cognitive map. According to Jones et al. (2011), a cognitive map is a tool that permits people’s spatial mental model to be displayed. For our purposes, the cognitive map not only represents a tool for displaying social opinions, but also investigates the preparedness of some citizens (Buergelt and Paton, 2014) concerning the core causes of fire ignition and the most common solutions useful to reduce fire risk and its impact on the environment. In the cognitive map, the causes and the solutions that the interviewees mentioned represent the nodes of the network, while the ties between them represent the associations that the interviewees made between causes and solutions. The number of nodes, their position within the network and their interconnections allow us to assess the variability of people’s opinions, while density and centrality measures foster the identification of gaps in fire management according to people’s opinions.
3. Material and methods 3.1. Study area The study area selected for this work includes three municipalities in the state of Tocantins (Brazil): Dueré, Formoso do Araguaia and Lagoa da Confusão (Fig. 1). The amount of population in 2014 was of 4720 in Dueré, 18,773 in Formoso do Araguaia and 11,859 in Lagoa da Confusão (http://www.ibge.gov.br). This area was selected because fire represents an important aspect both for local landowners and decision makers, as well as for the citizens living there. In this area, the forest vegetation is the Cerrado, also known as “Brazilian savannah” (Forzza et al., 2012; Simon and Pennington, 2012). According to Pereira Jr et al. (2014), the Cerrado is the world’s most biologically rich tropical savannah, but the current land use and agricultural practices have been changing fire regime, affecting the biodiversity conservation. The vegetation ranges from grasslands
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Fig. 1. Area of study. The study excluded the indigenous area denominated “Bananal Island”, located within the three municipalities.
(campo limpo) through several savannah formations (campo sujo, campo cerrado, cerrado sensu stricto) to sclerophylous woodland (cerradão), according to increasing tree density (Pereira Jr. et al. 2014). Pivello (2011) reported that the Cerrado is a fire-dependent environment, and the landowners use fire very frequently for their agriculture, forest and breeding activities as well as for their domestic activities. The National Institute for Space Research (INPE – Instituto Nacional de Pesquisas Espaciais) reports that for the period 1999 to 2015 the annual average number of bushfires in the state of Tocantins is 11,902, showing that most of them occur during the dry season, especially in September (5,039).
3.2. Data collection The data was collected through face-to-face interviews based on a questionnaire aimed at investigating the causes of fire ignitions and the actions necessary to reduce them. In particular, the authors
asked people to list possible causes of fire ignition in the Cerrado environment. In the same way, people were asked to list possible actions in order to reduce bushfire development. The interviews took approximately 20–30 min and consisted in the introduction of the study in order to explain the objective of the work and its importance for this area, due to the fact that fire frequency is very high, as well as to assess the citizens’ availability to take part in the interview. Subsequently, six main questions were formulated for the interviewees, including personal information (such as name, age, gender, residence, educational qualification) and questions aimed to discover the causes and the solutions about fire issues, asking to provide some examples of personal experiences. Furthermore, other questions were provided in order to explore the personal use and preparedness about firefighting (such as if someone took part in the training course about fire control and prevention) although this information was used to enrich the discussion section rather than being analyzed in order to assess their preparedness. The
nodes
(1)
• Network density (Nd), which corresponds to the proportion of existing ties when compared to all the possible ties (Eq. (2)). Higher values of Nd reflect the complexity of the network and, in this context, of social opinions.
Nd =
(ties) % Rows *Colums
(2)
• The centrality parameters, such as the Degree, which reflects the number of relations for each node. Higher values of Degree
Short-circuit
2 13 4 9 6 8 4 6 1 53 0 3 0 1 0 1 0 0 0 3 0 3 0 1 0 1 0 0 0 3
Indigenous Do not know
0 3 0 1 1 0 0 1 1 5 0 1 0 0 0 0 0 0 0 1
Breeding Glass fragments
0 5 1 2 1 0 0 1 0 5 0 1 0 1 0 0 0 0 0 2
bonfire Beekeeping
0 2 0 0 0 1 0 0 0 2 0 5 0 0 0 0 1 0 0 2
Hunting/Fishing Climate
0 2 2 3 0 1 0 0 0 4 1 15 0 3 5 5 1 2 0 7
Slash and Burn Intentionally
0 14 1 6 3 7 0 1 0 6 0 25 2 6 7 5 4 4 0 7
Ns =
Cigarettes
• Network size (Ns), which corresponds to the number of nodes forming the network (Eq. (1)). In this context, higher values of Ns display high variability of causes and solutions mentioned by the interviewees.
1 21 0 0 6 3 3 1 0 6
The analysis of data starts with the description of the population structure, considering age, gender and educational qualification. Subsequently, we proceed to the statistical analysis including two types of analysis: network analysis and chi-square analysis. The network analysis is carried out through the UCINET software, which allows us to draw the network of citizens’ opinions. In particular, we adopt the two-mode network due to the rows and columns reported two different sets of entities (Hanneman and Riddle, 2005) such as causes and solutions. The nodes of the network represent people’s opinions, concerning both causes and solutions, while the ties represent the linkage between solutions and causes that the authors made according to the citizens’ opinions. Within the network the dimension, the colors, the shape and the position of the nodes display the network structure reflecting citizens’ opinions. In the two-mode network, the ties are unidirectional from solutions to causes and there are no connections among nodes of the same entities, such as among causes or among solutions, but only the linkage between nodes of different entities is possible. The thickness of the ties reflects how strong the connections between solutions and causes are, according to the interviewees’ opinions. In detail, the ties, which link solutions and causes mentioned by many people, are bigger than ties, which connect solutions and causes mentioned few times. The main parameters observed from the network analysis are:
Accidentally
3.3. Data analysis
Cooperation Conciousness Monitoring Reduce use Prevention Surveillance Training Do not know No solution Indegree
interviewees answered the open questions freely, without being influenced, since the questions were simple and explicit, so that citizens did not feel penalized for sharing their opinions. In order to collect the greatest variety of opinions as possible, the explorative study adopted the theoretical sampling strategy (López-Santiago et al., 2014) involving 116 people from the three municipalities. The theoretical sampling strategy allows the collection of the greatest variety of information, reflecting individual acquaintance and practical experiences, rather than that most representative within a population (Patton, 1990; Strauss and Corbin, 1998). In fact, the interviewees were encountered in public places such as offices, restaurants or shops, as well as along the road and in the farms. Considering the total amount of population of the study area, the estimated sampling error is ±9.1 with 95% of confidence level. People were free to list as many causes as possible, even though we verified that the same person mentioned no more than three causes and three solutions. The data obtained was used to implement a contingency matrix (Table 1), where the columns represent the causes and the rows represent the solutions that people mentioned during said interviews.
Outdegree
G. Santopuoli et al. / Land Use Policy 59 (2016) 217–226 Table 1 Causes and solutions matrix. The matrix represents the connection between causes (columns) and solutions (rows) that citizens mentioned during the interviews. The last column reports the Outdegree value, and the last row, the Indegree value. These are centrality parameters which reflect how many times one solution was linked to the causes (Outdegree) and how many solutions were mentioned for the same cause (Indegree).
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221
Fig. 2. Social structure of the population according to gender, age, class and race.
indicate the central position of the node within the network, reflecting the consideration given by people to this node. The Degree is the sum of Indegree and Outdegree values, even if in the two-mode network the Degree is equal to the Outdegree or to the Indegree for solutions and causes, respectively. The Indegree is the number of ties that one node receives (causes), reflecting how many times the interviewees mentioned one specific cause, while the Outdegree is the number of ties that one node sends (solutions) to other nodes. In this context, the Outdegree represents how many times the interviewees associated the solutions with the causes. Centrality reflects how a node is central or prevailing within the network. • The K-core, which consists in the identification of particular subsets of the network, based on some number (k) of connections that the nodes have within the network (Hanneman and Riddle, 2005).
Finally, we test the existence of correlations between the variability of citizens’ opinions and the social structure through the chi-square analysis, statistical significance p < 0.001, using the SPSS software.
4. Results The total number of people contacted was 116, ranging from 16 to 87 years old (Fig. 2. Concerning the race of the interviewees, most of them are brown, 56%, while white and black people represent 22% and 18% of the interviewees, respectively, and 2% are indigenous. As to gender, male represents 75%, while female represents 25% of the interviewees. A small percentage of people (16%) completed elementary school, while 34% of the interviewees completed middle school, and only 12% declared they had completed high school. Almost 40% of the interviewees are illiterate, or did not complete elementary school (Fig. 3). The interviewees mentioned 13 different causes and 9 different solutions, representing the 22 nodes (Ns = 22) of the network (Fig. 4), with an average equal to 3.75, standard deviation equal to 4.8 and variance equal to 23.05. Statistical findings for each node are displayed in the Table 2. In the network, the shape of the nodes reflects the kinds of entities such as causes (square) and solutions (circle). In relation to the size of the nodes, bigger nodes represent
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Table 2 List of nodes’ names and types, with the centrality parameters: Degree and k-core values. The last three columns show the average, the standard deviation and the variance for each node. Node name
Node type
Degree
K-core
Average
Standard Deviation
Variance
Consciousness Reduce use Surveillance Cigarettes S&B Accidentally Intentionally Prevention Do not know Glass Do not know Climate Monitoring Training Indigenous Short-circuit Hunting/fishing Beekeeping Bonfire Cooperation Breeding No solution
solutions solutions solutions cause cause cause cause solutions solutions cause cause cause solutions solutions cause cause cause cause cause solutions cause solutions
13 9 8 7 7 6 6 6 6 5 5 4 4 4 3 3 2 2 2 2 1 1
4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 2 2 2 2 1 1
7.69 2.67 3.00 7.57 4.57 5.83 5.33 3.83 1.67 2.00 1.40 2.00 1.50 2.25 1.67 1.67 3.00 1.50 1.00 1.00 1.00 1.00
7.87 1.94 2.24 7.27 4.53 6.99 4.50 2.34 1.11 1.55 0.80 0.71 0.50 1.30 0.94 0.94 2.00 0.50 0.00 0.00 0.00 1.00
61.91 3.78 5.00 52.82 20.53 48.81 20.22 5.47 1.22 2.40 0.64 0.50 0.25 1.69 0.89 0.89 4.00 0.25 0.00 0.00 0.00 0.00
Fig. 3. Educational qualification of the interviewees.
high values of Degree while smaller nodes represent low values of Degree (Table 2). Thus, the causes that reach the biggest value of Degree are cigarettes (CIG) and agricultural practices, such as slash and burn (S&B), which score a value equal to seven, followed by the accidentally causes (ACC) and intentional causes (INT) reaching scores equal to six. Furthermore, ten interviewees declared that glass fragments (GLASS) are the cause of forest fire ignition and other seven declared that they do not know the causes. These last two categories reach five as a value of Degree in the network, followed by climatic conditions (CLIMATE), such as high temperatures, season, and wind direction, which present Degree equal to four. Causes such as indigenous activities and short-circuit score lower values of the Degree, equal to three. Finally, hunting and fishing (CATCH) activities, beekeeping and bonfires, with Degree equal to two, and breeding activities with Degree equal to one, are the causes that present the lowest values of Degree in this context. Concerning the solutions mentioned by the interviewees, consciousness scores the highest value of Degree, in absolute, equal to 13, followed by reducing use, which scores nine, and improving surveillance, which scores eight. These represent the three main solutions that people mentioned as helpful to reduce the bushfire and its impact on the environment. Prevention activities repre-
sent the solution that scores six as value of Degree as well as do not know, as declared by ten different interviewees. Further solutions identified are the monitoring activities and the training course about forest firefighting and fire control, reaching a value of Degree equal to four. In addition, another action was identified as a possible solution in order to reduce fire impact, which is the cooperation among citizens, including landowners, farmers and general population. Finally, one interviewee declared that there is no solution to reduce fire risk, highlighting indifference or resigned behavior towards forest fire. The total number of connection among causes and solution are 199, even if only 53 out of 117 all possible combinations have been identified, with the Nd equal to 45% (Table 1). The connection that reaches the greatest value is related to consciousness with CIG (25), followed by consciousness with ACC (21), consciousness with S&B (15) and consciousness with INT (14). All the other ties reach values lower than 10. According to the k-core, it is possible to distinguish four sub-groups of nodes within the network, highlighting the variety of people’s considerations. Important insights can be found within the k-core. In relation to the causes, 7 out of 13 represent the most common causes mentioned by people. Most of them confirm that the forest fire are human induced through “cigarettes”, “agricultural activities”, “negligent” and “intentional” use of fire, which stress the importance of monitoring and surveillance activities. Although they occupy peripheral position within this group, “climatic conditions”, “glass fragments” and “do not know” are considered the main causes of fire ignition, highlighting the lack of awareness of fire issues among citizens. Other causes occupy marginal positions within the network, forming three different sub-groups. The marginal position in the network reflects the scarce consideration that citizens have of them. In fact, these three causes were never mentioned as the first cause by the interviewees. Concerning the solutions, six out nine represent the main sub-group of network. This sub-group includes “consciousness”, “reducing use” and “surveillance”, which occupy the central position, and “prevention”, “monitoring” and “do not know”, which occupy a peripheral position within the sub-group. “Training activities”, “cooperation” and “no solutions” occupy a peripheral position within the network, mirroring the lesser consideration people have expressed in relation to them. On one hand, there is strong awareness that consciousness is necessary in order to improve the knowledge of fire issues among people. On the other hand, great
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Fig. 4. Cognitive map. In the network, the shape of the nodes reflects the causes (square) and solutions (circle) mentioned by the interviewees. The size of the node represents the Degree value, while the colors reflect the k-core. The direction of the ties reflects the connections between causes and mentioned solutions, while the thickness of the ties represents the strength of the connections, demonstrating how many times people mentioned the same connection.
Table 3 Chi-square values for causes and solutions, according to four variables. Cause
Educational qualification Age Gender Residence
izens mentioned “climate” as a cause of bushfire, while it was not mentioned in Lagoa da Confusão.
Solutions
Chi-square
sig
Chi-square
sig
62.32 47.97 8.36 56.42
0.785 0.474 0.756 0.000
46.77 18.91 5.41 11.42
0.523 0.968 0.713 0.783
efforts are needed in order to involve people in training activities related to fire management and for the implementation of prevention activities. The cognitive map summarizes the social opinion variability about fire ignition and fire control among citizens of the three municipalities. Overall, the local opinion does not depend on the social structure parameters, such as age, gender and educational qualification, but there is one statistically significant correlation between the causes and the citizens’ residence (Table 3), with a X2 = 56.42 and p = 0.000. The first difference is the number of causes mentioned by citizens within their municipalities (Fig. 5. In Dueré and Formoso do Araguaia citizens mentioned 8 out of 13 different causes, while in Lagoa da Confusão the causes mentioned amount to 11. Only 4 out 13 causes, namely: “accidentally”, “cigarettes”, “slash and burn” and “intentionally”, are common to all the three municipalities and occupy the most central position in the network of Fig. 4. On the other hand, there are two causes mentioned only by citizens from Lagoa da Confusão. These are “breeding” and “beekeeping”. Similarly, only in Formoso do Araguaia one citizen mentioned the “bonfire” as a possible cause of bushfire. Furthermore, “do not know” reaches a higher score in Formoso do Araguaia compared to Lagoa da Confusão and it is totally absent in Dueré. Similarly, “indigenous” people are mentioned more in Lagoa da Confusão than in Formoso do Araguaia, and there is no mention of them in the Dueré. On the contrary, in Formoso do Araguaia and in Dueré cit-
5. Discussion Overall, the interviewees mentioned 13 different causes of fire ignition and 9 different solutions to reduce bushfire risk. Nevertheless, they individually mentioned no more than three causes and three solutions. We demonstrated that a cognitive map is a very useful tool for identifying people’s opinions about environmental problems such as bushfire. The cognitive map highlights citizens’ opinions, helping decision makers to assess the human cognition and preparedness in relation to fire issues (Robertson et al., 2012; Toikkanen and Lipponen, 2011). In the network of this study, the interviewees mentioned 13 different causes of fire ignition, giving prominence to two main insights, careless fire use and the general lack of awareness of fire issues among citizens. This study highlights how citizens strongly consider “cigarettes” as the cause of fire ignition, even if it is demonstrated that this risk is very low (Xanthopoulos et al., 2006). Similarly, they also strongly recognize that fire ignition depends on the mismanagement of agricultural practices, as reported in other studies (Pivello, 2011). These two aforementioned causes highlight the existence of a gap concerning fire behavior among citizens and land managers. This is even more evident if we consider the following causes mentioned by citizens as “accidental” and “intentional”. Citizens refer to the accidental causes, stressing the negligent use of fire in daily activities, such as burning domestic waste or agricultural residues (Bernardes and Günther, 2014). However, they also stress that humans intentionally ignite bushfire. People recognize the careless use of fire in their activities, identifying people’s consciousness as the most important action to be taken in order to reduce bushfire risk. This is demonstrated by the thickness of ties between consciousness and the four causes mentioned previously. For this reason, training activities related to fire behavior, fire management,
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Fig. 5. Frequency of the mentioned causes among the three municipalities.
firefighting, should be promoted in order to foster human learning and consciousness of the use of fire in agricultural practices and in environmental management. Further causes, which score high importance among citizens’ opinions, are “climatic conditions”, “glass fragments” and “do not know”, which are part of the main k-core sub-group. If, on one hand, these causes show the higher variety of elements that affect fire ignitions, although the probability is scarce, particularly for glass fragments (Wittich and Müller, 2009), on the other hand, they highlight the lesser degree of preparedness of citizens in relation to fire issues. This is demonstrated by the fact that the interviewees are not able to mention any causes of fire ignition, as well as by the fact that they prefer to reduce the use of fire, without considering that the Cerrado is a fire dependent ecosystem (Pivello, 2011; Simon and Pennington, 2012), rather than implementing preventive or monitoring activities. As Geiger et al. (2011) stated, repetitive actions of fire suppression within the Cerrado allow the expansion of forest to the detriment of the vegetation of the Cerrado biome. Nevertheless, although prevention and monitoring are within the main k-core sub-group, they occupy a more peripheral position than reducing use and surveillance. The “do not know” solution mentioned by the interviewees supports our findings about the lack of awareness and preparedness. General careless use of fire and lack of awareness of fire issues are the main findings that the cognitive map allowed to identify in the main k-core sub-group. Furthermore, the interviewees believe more in surveillance activities than in monitoring and preventive activities. This aspect allows us to consider that people prefer top-down management implementation rather than bottom-up actions. However, this approach does not encourage people to improve in terms of their risk management skills (Lindell et al., 2009). Furthermore, the cognitive map shows additional causes and solutions that occupy a peripheral position within the network,
forming other three k-core sub-groups. The cognitive map shows that the interviewees mentioned “short-circuit” and “indigenous” activities as possible causes of fire ignition, suggesting “surveillance”, “reducing use” and “consciousness” as possible solutions. In this case, the relationship between causes and solutions appears to be contrasting and confusing, particularly between “short-circuit” and “reducing use”. The explanation is that the interviewees considered “short-circuit” as the consequence of rural activities such as fence servicing, or of animals touching the electricity transmission towers. On the other hand, with the term “reducing use” we indicate the rational use of fire by residents and native people, as well as the responsible implementation of farming practices. Some interviewees also mentioned causes such as “bonfire”, “hunting/fishing” and “beekeeping” activities, associating them to possible solutions such as “surveillance”, “training” activities, “reducing use” and “consciousness”. It is interesting to note how the interviewees identified recreation activities as possible causes of bushfire, even though they occupy a peripheral position in this network. This highlights the importance of the environment as a source of goods and services for society, and, at the same time, it stresses the challenge that environmental managers have to face in order to improve the provision of these ecosystem services. Finally, the interviewees declared that the use of fire in “breeding” practices, such as pasture regrowth (Mistry, 1998), can represent a further cause of fire ignition, highlighting the importance given to the need to improve the consciousness of fire use. Concerning the solutions that occupy the peripheral positions in the network, the interviewees mentioned training as an activity that would be useful in order to improve agricultural, hunting and fishing management practices, as well as in order to reduce fire ignition due to accidental causes and cigarettes. Although it is poorly considered, training activity represents one of the most important actions in order to improve people’s capacity building in the management of fire risk (Buergelt and Paton, 2014). This
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insight represents an important challenge for decision makers who firstly have to understand why the training course is little considered among the inhabitants and, subsequently, implement a more stimulating course in order to increase the number of participants, altering citizens’ opinions and fostering a better management of fire among inhabitants. The interviewees also mentioned “cooperation” among citizens in order to reduce forest fire risk, particularly connected with causes such as “slash and burn” and “accidentally”. The cooperation across community allows the sharing of actions and aims among citizens (Paton, 2008), reducing bushfire risk and also reducing costs for fire prevention and management. Contrary to the central k-core sub-group, this finding compels us to state that some interviewees prefer bottom-up management rather than top-down management actions. Finally, there is one case in which the interviewee declared that there is no solution to reduce fire in the Cerrado, even though he was not able to identify any causes of fire ignition. The lack of preparedness concerning fire management has also emerged in this case, compelling us to consider that fire risk represents a strong threat not only for the environment but also for residents. Studies on the preparedness and capacity building have demonstrated that the holistic system and a multidisciplinary approach are required for a better understanding of how people act, particularly for management of environmental resources (Buergelt and Paton, 2014; Paton et al., 2006; Coughlan and Petty, 2012). Nevertheless, the cognitive map strongly supports decision makers in order to identify challenges and gaps that hinder people from managing fire correctly, altering the environment. The findings that are derived from the peripheral causes displayed in this network, on one hand, confirm the general careless use of fire, and on the other hand, a lack of knowledge, not only of fire management but also of rural practices such as agriculture, breeding, hunting, fishing and beekeeping. These challenges call for integrated educational activities not only in fire management but also in environmental resources management, considering the numerous benefits that humans obtain from the ecosystems. The added value of the cognitive map for decision makers in the development of a management plan of the natural resources brings to light information in order to identify weaknesses that need to be solved. In this manner, through management plan, natural resource managers can suggest how to use funding in order to improve both efficiency in fire management and the conservation of natural resources. Finally, we demonstrated that the social structure of the surveyed population, such as gender, age and educational qualification, does not present alterations of the answers to the questionnaire and in citizens’ opinions in relation to fire issues. However, there is a significant statistical correlation between municipality residence and causes mentioned, as demonstrated by the chi-square analysis. People from the same municipality mentioned the same opinions. As Buergelt and Paton (2014) highlighted, the natural and the physical dimensions not only affect citizens’ behavior, but also foster the communication and the sharing of experience and beliefs. We can confirm that people sharing personal experience and beliefs beyond scientific knowledge affect society’s opinion. Nevertheless, citizens from Dueré showed the most homogeneity of causes with most of them being amongst the core causes of the network. Citizens from Formoso do Araguaia showed less homogeneity in the answers, highlighting a moderate rate of uncertainty among interviewed parties which stressed “do not know” as cause of fire ignition. Finally, citizens from Lagoa da Confusão showed the most variability of causes and high heterogeneity among them. Because the fire represents a real threat in this area, we suggest the inclusion of fire lessons within the educational program in schools in order to improve the awareness about fire risk and damage as well as fire management, prevention and
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control. Strong efforts are needed in order to improve the awareness among citizens in order to promote the conservation of natural resources and the use of them in a sustainable manner. 6. Conclusions Due to the personal benefits obtained, humans manage the environmental resources based on their personal experience and beliefs. For this reason, responsible management of the environmental resources represents the path towards sustainable development. This is possible only if decision makers are able to transfer scientific knowledge to local landowners, practitioners and citizens. Management plans represent useful tools for sharing knowledge and management strategies; thus, it is fundamental to assess their actual implementation by local people, since said implementation may be lacking due to conflicting interests. For this reason, it is important to involve people in management activities in order to understand their opinions and to develop management strategies that meet societal benefit, ecological conservation and economic development. In this study, we applied the cognitive map for ecological problems, such as fire, highlighting the usefulness of this tool in the identification of the human cognition about causes and solutions to bushfire. In particular, we can conclude that the cognitive map is a useful tool for synthesizing a variety of people’s perceptions, fostering the assessment of people’s behavior about such relevant topics of environmental resources. The cognitive map strongly supports decision makers, allowing the identification of challenges and providing awareness of gaps that hinder environmental conservation. In this case, two main findings are carried out from the cognitive map; firstly, there is a general lack of awareness of bushfire ignition among people and, secondly, people highlight a careless use of fire, which results abundant and not rational, with a trend regarding mismanagement in farmer activities. People strongly consider human consciousness as possible solution to reduce bushfire, and they also believe in surveillance activities, while there is poorly consideration of training activities. We recommend a strong revision of the current training course in order to develop more attractive educational courses, improving citizens’ participation and encouraging a shift from local beliefs to scientific assumptions. Acknowledgements We gratefully acknowledge financial support from CAPES Foundation, the Ministry of Education of Brazil, project 88881.062168/2014-01. We are also grateful to the voluntary interviewees of the municipalities of the Dueré, Formoso do Araguaia and Lagoa da Confusão. References Özesmi, U., Özesmi, S.L., 2004. Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecol. Modell. 176 (1–2), 43–64, http://dx.doi.org/10.1016/j.ecolmodel.2003.10.027. Appelstrand, Marie, 2002. Participation and societal values: the challenge for lawmakers and policy practitioners. For. Policy Econ. 4 (4), 281–290, http://dx. doi.org/10.1016/s1389-9341(02)00070-9. Bernardes, C., Günther, W.M.R., 2014. Generation of domestic solid waste in rural areas: case study of remote communities in the brazilian amazon. Hum. Ecol. 42 (4), 617–623. Bodin, Ö., Crona, B., Ernstson, H., 2006. Social networks in natural resource management: what is there to learn from a structural perspective? Ecol. Soc. 11 (2). Buergelt, P.T., Paton, D., 2014. An ecological risk management and capacity building model. Hum. Ecol. 42 (4), 591–603. Cachoeira, N.J., 2015. Caracterizac¸ão das Queimadas e Incêndios Florestais no Estado do Tocantins no Período de 2003 a 2011. In: Dissertac¸ão Thesis. Universidade Federal do Tocantins. Coughlan, M.R., Petty, A.M., 2012. Linking humans and fire: a proposal for a transdisciplinary fire ecology. Int. J. Wildland Fire 21 (5), 477–487.
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Land Use Policy journal homepage: www.elsevier.com/locate/landusepol
Network analysis to support environmental resources management. A case study in the Cerrado, Brazil Giovanni Santopuoli b,∗ , Jader Nunes Cachoeira a , Marco Marchetti b , Marcelo Ribeiro Viola c , Marcos Giongo a a
Forest Engineering, Universidade Federal do Tocantins, Campus of Gurupi (TO), Brazil Laboratory of Natural Resources and Environmental Planning, Department of Biosciences and Territory, University of Molise, Cda Fonte Lappone, snc, 86090 Pesche (IS), Italy c Forest Engineering, Universidade Federal de Lavras, Soil and Water Engineering Group, Lavras, Brazil b
a r t i c l e
i n f o
Article history: Received 29 April 2016 Received in revised form 5 July 2016 Accepted 5 September 2016 Keywords: Network analysis Cognitive map Bushfire Cerrado Brazil
a b s t r a c t The study examines citizens’ opinions about one crucial factor: the fire that affects the Brazilian savannah “Cerrado”. The paper aims at introducing a new tool that facilitates the assessment of people’s behaviour in order to support practitioners and decision makers to develop management strategies that fostering the environmental conservation, economic growth and human wellbeing. The study applies the network analysis in order to analyse the citizens’ opinions about causes of fire ignition and suppression activities for firefighting evoked by local inhabitants during the face-to-face interviews. The main finding carried out in this work is the usefulness of a cognitive map for synthesising a variety of people’s beliefs. Furthermore, the study reveals the general lack of awareness among people concerning fire use and management and the careless use of fire in rural activities. The chi-square test reveals that natural and physical dimensions affect society’s beliefs with statistical significance p < 0.001. © 2016 Elsevier Ltd. All rights reserved.
1. Introduction Environmental resources management planning is one of the most important tools for assuring the sustainable use of natural resources and promoting sustainable development (Grunewald and Bastian, 2015). However, managing environmental problems becomes more complicated when humans are involved (Özesmi and Özesmi, 2004) for two main reasons. Firstly, the numerous goods and services that natural ecosystems provide attract many categories of stakeholders (Daily et al., 2009; van Wensem, 2013). Secondly, landowners and local laborers are the main managers of rural environments and their legitimation is crucial for the implementation of a management plan (Nuno et al., 2014; Khew et al., 2014). For these reasons, inhabitants’ behavior and opinions are very important for decision makers in terms of the development and the implementation of a management plan (Appelstrand, 2002;
∗ Corresponding author at: Laboratory of Natural Resources and Environmental Planning, Department of Biosciences and Territory, University of Molise, Cda Fonte Lappone, snc, 86090 Pesche (IS), Italy. E-mail addresses: [email protected], [email protected] (G. Santopuoli). http://dx.doi.org/10.1016/j.landusepol.2016.09.002 0264-8377/© 2016 Elsevier Ltd. All rights reserved.
Janse and Konijnendijk, 2007), such as a forest management plan or a fire prevention and control plan. In such cases, the knowledge of the local traditional background supplies very significant insights for managing environmental resources (Mistry, 1998). Otherwise, their opinions would be very misconceived and limited (Jones et al., 2011) requiring greater efforts in order to share and implement management strategies. Nevertheless, assessing citizens’ opinions is not only a crucial aspect for local technicians and policy makers (Khew et al., 2014), but also represents an important learning phase that permits the concept of management to be shared with local inhabitants (Morse 2008; Bodin et al., 2006). Lindell et al. (2009) consider their perceptions as the social representations of such topics, since they determine people’s behavior and practices. Similarly, Buergelt and Paton (2014) stated that people’s experience and beliefs affect their behavior and their capacity building in risk management. Other authors, such as Jones et al. (2011) compared inhabitants’ perceptions to the “mental model” and stated that it partially describes the personal and internal representations of the external reality that citizens use to interact with the environment around them. Over the years, several methodologies for evaluating people’s opinions have been developed and one of these is network analysis through the cognitive maps. Although cognitive maps are frequently used in the sociology field (Ferreira et al., 2006;
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Morandin and Bergami, 2014; Dempwolf and Lyles, 2012), their use also becomes common in other field of study such as ecology and forestry (Santopuoli et al., 2012; Mendoza and Prabhu, 2003; Bodin et al., 2006). Cognitive maps allow the representation of people’s behavior and opinions (Jones et al., 2011), enabling decision makers to use this representation in decision-making activities beyond the scientific experience (Janse and Konijnendijk, 2007). Assessing local perceptions not only allows to identify how citizens consider a specific topic, but also allows to communicate with local inhabitants and practitioners, increasing the awareness of environmental problems management among them (Renn, 2006; Reed et al., 2008; Robertson et al., 2012; Toikkanen and Lipponen 2011). In this study, we adopt the cognitive map in order to explore citizens’ opinions about the fire in the “Cerrado” environment, also known as the Brazilian savannah, in the state of Tocantins, Brazil. In this area, fire represents one of the most important ecological factors, affecting the biodiversity conservation and the management of environmental resources. Apart from its origin, either naturally ignited or induced by humans, fire occurs very frequently – around two/three years – (Pereira et al., 2014) affecting forest areas, which are characterized as highly flammable vegetation (Klink and Machado, 2005; Hoffmann et al., 2009). Residents and local inhabitants consider fire very helpful for the majority of rural activities (Pivello, 2011). They use fire for several activities such as clearing trails or pathways and other open spaces around the houses in order to facilitate walking; stimulating grass regrowth, flowering and fruiting of some plants; removing crop residuals and waste; attracting game for collecting honey as well as driving and attracting game during hunting. Furthermore, the majority of indigenous populations use fire for religious and spiritual rituals, as well as for signals and traditional folklore (Mistry et al., 2005). Numerous efforts were carried out in order to assess the role and the effect of fire on the vegetation (Simon and Pennington, 2012; Pivello, 2011), but few studies focused on the relationship between local inhabitants and fire. Due to the fact that the majority of fires are human induced (Coughlan and Petty, 2012), being aware of people’s opinions can help to understand how to reduce bushfire risk. Traditional culture in the State of Tocantins fosters the daily use of fire, often with negligence (Mistry, 1998). This increases bushfire risk and often culminates with enormous areas of burned forest. One recent study (Cachoeira, 2015) highlights that in the state of Tocantins the average annual burned area is 3,200,000 ha. The poor surveillance services and the scarce presence of civil fire brigades allow the very rapid development of fire with severe damage to vegetation, animals and human infrastructures. The aim of this study is to explore the citizens’ vision about fire use and management, identifying the core causes of fire ignitions and the actions useful for firefighting and control according the inhabitants’ point of view, answering the research questions: which are the causes of fire ignition and how do people interact with bushfire? Furthermore, we test whether or not the social structure of the population affects the core opinions identified, answering the research question: does the social structure of the population affect inhabitants’ perceptions about fire ignition and fire risk reduction? In the next section, we present the conceptual framework of the study, followed by the materials and methods within which there will be the description of the study area, the data collection approach and the data analysis methodology. Section 4 shows the results obtained and finally Sections 5 and 6 report discussion and conclusion respectively.
2. Conceptual framework The study explores the citizens’ opinions about fire use and fire management in order to assess people’s view of fire within the Cer-
rado environment, as well as to support local policy and decision makers. To reach this goal, after the collection of information, the authors describe people’s beliefs through the use of network analysis. Two clarifications about people’s beliefs and network analysis are needed. Firstly, their beliefs represent, on one hand, the probable causes that citizens highlighted as responsible for fire ignition, and, on the other hand, the actions that people consider useful for preventing, fighting and controlling fire, or in other words, the actions that allow the reduction of fire impact on natural resources and human infrastructures. In this context, we use the term “cause” to indicate the source of bushfire ignition according to citizens’ opinions and the term “solution” to indicate a personal opinion about necessary actions to reduce bushfire. Secondly, the network analysis allows the causal relationship between causes and solutions, highlighting the citizens’ opinions about fire issues in the study area. Since we consider citizens’ opinions as the summary representation of individual experience, beliefs and behavior, we consider age, class, gender, residence and educational qualification as the parameters of social structure that can affect their opinions. Although race could be a proxy since the indigenous people use fire for several traditional rituals, this factor was not considered in the analysis of this study because the number of indigenous people interviewed was very low and therefor resulted statistically insignificant. The network was constructed using the causes and the solutions that each interviewed party listed during the collection phase. Each citizen mentioned such causes and such solutions that indirectly constitute one relationship. The authors used these relationships in order to construct the network. The connection between causes and solutions represents the view of citizens regarding fire issues, summarizing their awareness and preparedness. The final network, within which all the causes and solutions were connected, was graphically displayed by the cognitive map. According to Jones et al. (2011), a cognitive map is a tool that permits people’s spatial mental model to be displayed. For our purposes, the cognitive map not only represents a tool for displaying social opinions, but also investigates the preparedness of some citizens (Buergelt and Paton, 2014) concerning the core causes of fire ignition and the most common solutions useful to reduce fire risk and its impact on the environment. In the cognitive map, the causes and the solutions that the interviewees mentioned represent the nodes of the network, while the ties between them represent the associations that the interviewees made between causes and solutions. The number of nodes, their position within the network and their interconnections allow us to assess the variability of people’s opinions, while density and centrality measures foster the identification of gaps in fire management according to people’s opinions.
3. Material and methods 3.1. Study area The study area selected for this work includes three municipalities in the state of Tocantins (Brazil): Dueré, Formoso do Araguaia and Lagoa da Confusão (Fig. 1). The amount of population in 2014 was of 4720 in Dueré, 18,773 in Formoso do Araguaia and 11,859 in Lagoa da Confusão (http://www.ibge.gov.br). This area was selected because fire represents an important aspect both for local landowners and decision makers, as well as for the citizens living there. In this area, the forest vegetation is the Cerrado, also known as “Brazilian savannah” (Forzza et al., 2012; Simon and Pennington, 2012). According to Pereira Jr et al. (2014), the Cerrado is the world’s most biologically rich tropical savannah, but the current land use and agricultural practices have been changing fire regime, affecting the biodiversity conservation. The vegetation ranges from grasslands
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Fig. 1. Area of study. The study excluded the indigenous area denominated “Bananal Island”, located within the three municipalities.
(campo limpo) through several savannah formations (campo sujo, campo cerrado, cerrado sensu stricto) to sclerophylous woodland (cerradão), according to increasing tree density (Pereira Jr. et al. 2014). Pivello (2011) reported that the Cerrado is a fire-dependent environment, and the landowners use fire very frequently for their agriculture, forest and breeding activities as well as for their domestic activities. The National Institute for Space Research (INPE – Instituto Nacional de Pesquisas Espaciais) reports that for the period 1999 to 2015 the annual average number of bushfires in the state of Tocantins is 11,902, showing that most of them occur during the dry season, especially in September (5,039).
3.2. Data collection The data was collected through face-to-face interviews based on a questionnaire aimed at investigating the causes of fire ignitions and the actions necessary to reduce them. In particular, the authors
asked people to list possible causes of fire ignition in the Cerrado environment. In the same way, people were asked to list possible actions in order to reduce bushfire development. The interviews took approximately 20–30 min and consisted in the introduction of the study in order to explain the objective of the work and its importance for this area, due to the fact that fire frequency is very high, as well as to assess the citizens’ availability to take part in the interview. Subsequently, six main questions were formulated for the interviewees, including personal information (such as name, age, gender, residence, educational qualification) and questions aimed to discover the causes and the solutions about fire issues, asking to provide some examples of personal experiences. Furthermore, other questions were provided in order to explore the personal use and preparedness about firefighting (such as if someone took part in the training course about fire control and prevention) although this information was used to enrich the discussion section rather than being analyzed in order to assess their preparedness. The
nodes
(1)
• Network density (Nd), which corresponds to the proportion of existing ties when compared to all the possible ties (Eq. (2)). Higher values of Nd reflect the complexity of the network and, in this context, of social opinions.
Nd =
(ties) % Rows *Colums
(2)
• The centrality parameters, such as the Degree, which reflects the number of relations for each node. Higher values of Degree
Short-circuit
2 13 4 9 6 8 4 6 1 53 0 3 0 1 0 1 0 0 0 3 0 3 0 1 0 1 0 0 0 3
Indigenous Do not know
0 3 0 1 1 0 0 1 1 5 0 1 0 0 0 0 0 0 0 1
Breeding Glass fragments
0 5 1 2 1 0 0 1 0 5 0 1 0 1 0 0 0 0 0 2
bonfire Beekeeping
0 2 0 0 0 1 0 0 0 2 0 5 0 0 0 0 1 0 0 2
Hunting/Fishing Climate
0 2 2 3 0 1 0 0 0 4 1 15 0 3 5 5 1 2 0 7
Slash and Burn Intentionally
0 14 1 6 3 7 0 1 0 6 0 25 2 6 7 5 4 4 0 7
Ns =
Cigarettes
• Network size (Ns), which corresponds to the number of nodes forming the network (Eq. (1)). In this context, higher values of Ns display high variability of causes and solutions mentioned by the interviewees.
1 21 0 0 6 3 3 1 0 6
The analysis of data starts with the description of the population structure, considering age, gender and educational qualification. Subsequently, we proceed to the statistical analysis including two types of analysis: network analysis and chi-square analysis. The network analysis is carried out through the UCINET software, which allows us to draw the network of citizens’ opinions. In particular, we adopt the two-mode network due to the rows and columns reported two different sets of entities (Hanneman and Riddle, 2005) such as causes and solutions. The nodes of the network represent people’s opinions, concerning both causes and solutions, while the ties represent the linkage between solutions and causes that the authors made according to the citizens’ opinions. Within the network the dimension, the colors, the shape and the position of the nodes display the network structure reflecting citizens’ opinions. In the two-mode network, the ties are unidirectional from solutions to causes and there are no connections among nodes of the same entities, such as among causes or among solutions, but only the linkage between nodes of different entities is possible. The thickness of the ties reflects how strong the connections between solutions and causes are, according to the interviewees’ opinions. In detail, the ties, which link solutions and causes mentioned by many people, are bigger than ties, which connect solutions and causes mentioned few times. The main parameters observed from the network analysis are:
Accidentally
3.3. Data analysis
Cooperation Conciousness Monitoring Reduce use Prevention Surveillance Training Do not know No solution Indegree
interviewees answered the open questions freely, without being influenced, since the questions were simple and explicit, so that citizens did not feel penalized for sharing their opinions. In order to collect the greatest variety of opinions as possible, the explorative study adopted the theoretical sampling strategy (López-Santiago et al., 2014) involving 116 people from the three municipalities. The theoretical sampling strategy allows the collection of the greatest variety of information, reflecting individual acquaintance and practical experiences, rather than that most representative within a population (Patton, 1990; Strauss and Corbin, 1998). In fact, the interviewees were encountered in public places such as offices, restaurants or shops, as well as along the road and in the farms. Considering the total amount of population of the study area, the estimated sampling error is ±9.1 with 95% of confidence level. People were free to list as many causes as possible, even though we verified that the same person mentioned no more than three causes and three solutions. The data obtained was used to implement a contingency matrix (Table 1), where the columns represent the causes and the rows represent the solutions that people mentioned during said interviews.
Outdegree
G. Santopuoli et al. / Land Use Policy 59 (2016) 217–226 Table 1 Causes and solutions matrix. The matrix represents the connection between causes (columns) and solutions (rows) that citizens mentioned during the interviews. The last column reports the Outdegree value, and the last row, the Indegree value. These are centrality parameters which reflect how many times one solution was linked to the causes (Outdegree) and how many solutions were mentioned for the same cause (Indegree).
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Fig. 2. Social structure of the population according to gender, age, class and race.
indicate the central position of the node within the network, reflecting the consideration given by people to this node. The Degree is the sum of Indegree and Outdegree values, even if in the two-mode network the Degree is equal to the Outdegree or to the Indegree for solutions and causes, respectively. The Indegree is the number of ties that one node receives (causes), reflecting how many times the interviewees mentioned one specific cause, while the Outdegree is the number of ties that one node sends (solutions) to other nodes. In this context, the Outdegree represents how many times the interviewees associated the solutions with the causes. Centrality reflects how a node is central or prevailing within the network. • The K-core, which consists in the identification of particular subsets of the network, based on some number (k) of connections that the nodes have within the network (Hanneman and Riddle, 2005).
Finally, we test the existence of correlations between the variability of citizens’ opinions and the social structure through the chi-square analysis, statistical significance p < 0.001, using the SPSS software.
4. Results The total number of people contacted was 116, ranging from 16 to 87 years old (Fig. 2. Concerning the race of the interviewees, most of them are brown, 56%, while white and black people represent 22% and 18% of the interviewees, respectively, and 2% are indigenous. As to gender, male represents 75%, while female represents 25% of the interviewees. A small percentage of people (16%) completed elementary school, while 34% of the interviewees completed middle school, and only 12% declared they had completed high school. Almost 40% of the interviewees are illiterate, or did not complete elementary school (Fig. 3). The interviewees mentioned 13 different causes and 9 different solutions, representing the 22 nodes (Ns = 22) of the network (Fig. 4), with an average equal to 3.75, standard deviation equal to 4.8 and variance equal to 23.05. Statistical findings for each node are displayed in the Table 2. In the network, the shape of the nodes reflects the kinds of entities such as causes (square) and solutions (circle). In relation to the size of the nodes, bigger nodes represent
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Table 2 List of nodes’ names and types, with the centrality parameters: Degree and k-core values. The last three columns show the average, the standard deviation and the variance for each node. Node name
Node type
Degree
K-core
Average
Standard Deviation
Variance
Consciousness Reduce use Surveillance Cigarettes S&B Accidentally Intentionally Prevention Do not know Glass Do not know Climate Monitoring Training Indigenous Short-circuit Hunting/fishing Beekeeping Bonfire Cooperation Breeding No solution
solutions solutions solutions cause cause cause cause solutions solutions cause cause cause solutions solutions cause cause cause cause cause solutions cause solutions
13 9 8 7 7 6 6 6 6 5 5 4 4 4 3 3 2 2 2 2 1 1
4 4 4 4 4 4 4 4 4 4 4 4 4 3 3 3 2 2 2 2 1 1
7.69 2.67 3.00 7.57 4.57 5.83 5.33 3.83 1.67 2.00 1.40 2.00 1.50 2.25 1.67 1.67 3.00 1.50 1.00 1.00 1.00 1.00
7.87 1.94 2.24 7.27 4.53 6.99 4.50 2.34 1.11 1.55 0.80 0.71 0.50 1.30 0.94 0.94 2.00 0.50 0.00 0.00 0.00 1.00
61.91 3.78 5.00 52.82 20.53 48.81 20.22 5.47 1.22 2.40 0.64 0.50 0.25 1.69 0.89 0.89 4.00 0.25 0.00 0.00 0.00 0.00
Fig. 3. Educational qualification of the interviewees.
high values of Degree while smaller nodes represent low values of Degree (Table 2). Thus, the causes that reach the biggest value of Degree are cigarettes (CIG) and agricultural practices, such as slash and burn (S&B), which score a value equal to seven, followed by the accidentally causes (ACC) and intentional causes (INT) reaching scores equal to six. Furthermore, ten interviewees declared that glass fragments (GLASS) are the cause of forest fire ignition and other seven declared that they do not know the causes. These last two categories reach five as a value of Degree in the network, followed by climatic conditions (CLIMATE), such as high temperatures, season, and wind direction, which present Degree equal to four. Causes such as indigenous activities and short-circuit score lower values of the Degree, equal to three. Finally, hunting and fishing (CATCH) activities, beekeeping and bonfires, with Degree equal to two, and breeding activities with Degree equal to one, are the causes that present the lowest values of Degree in this context. Concerning the solutions mentioned by the interviewees, consciousness scores the highest value of Degree, in absolute, equal to 13, followed by reducing use, which scores nine, and improving surveillance, which scores eight. These represent the three main solutions that people mentioned as helpful to reduce the bushfire and its impact on the environment. Prevention activities repre-
sent the solution that scores six as value of Degree as well as do not know, as declared by ten different interviewees. Further solutions identified are the monitoring activities and the training course about forest firefighting and fire control, reaching a value of Degree equal to four. In addition, another action was identified as a possible solution in order to reduce fire impact, which is the cooperation among citizens, including landowners, farmers and general population. Finally, one interviewee declared that there is no solution to reduce fire risk, highlighting indifference or resigned behavior towards forest fire. The total number of connection among causes and solution are 199, even if only 53 out of 117 all possible combinations have been identified, with the Nd equal to 45% (Table 1). The connection that reaches the greatest value is related to consciousness with CIG (25), followed by consciousness with ACC (21), consciousness with S&B (15) and consciousness with INT (14). All the other ties reach values lower than 10. According to the k-core, it is possible to distinguish four sub-groups of nodes within the network, highlighting the variety of people’s considerations. Important insights can be found within the k-core. In relation to the causes, 7 out of 13 represent the most common causes mentioned by people. Most of them confirm that the forest fire are human induced through “cigarettes”, “agricultural activities”, “negligent” and “intentional” use of fire, which stress the importance of monitoring and surveillance activities. Although they occupy peripheral position within this group, “climatic conditions”, “glass fragments” and “do not know” are considered the main causes of fire ignition, highlighting the lack of awareness of fire issues among citizens. Other causes occupy marginal positions within the network, forming three different sub-groups. The marginal position in the network reflects the scarce consideration that citizens have of them. In fact, these three causes were never mentioned as the first cause by the interviewees. Concerning the solutions, six out nine represent the main sub-group of network. This sub-group includes “consciousness”, “reducing use” and “surveillance”, which occupy the central position, and “prevention”, “monitoring” and “do not know”, which occupy a peripheral position within the sub-group. “Training activities”, “cooperation” and “no solutions” occupy a peripheral position within the network, mirroring the lesser consideration people have expressed in relation to them. On one hand, there is strong awareness that consciousness is necessary in order to improve the knowledge of fire issues among people. On the other hand, great
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Fig. 4. Cognitive map. In the network, the shape of the nodes reflects the causes (square) and solutions (circle) mentioned by the interviewees. The size of the node represents the Degree value, while the colors reflect the k-core. The direction of the ties reflects the connections between causes and mentioned solutions, while the thickness of the ties represents the strength of the connections, demonstrating how many times people mentioned the same connection.
Table 3 Chi-square values for causes and solutions, according to four variables. Cause
Educational qualification Age Gender Residence
izens mentioned “climate” as a cause of bushfire, while it was not mentioned in Lagoa da Confusão.
Solutions
Chi-square
sig
Chi-square
sig
62.32 47.97 8.36 56.42
0.785 0.474 0.756 0.000
46.77 18.91 5.41 11.42
0.523 0.968 0.713 0.783
efforts are needed in order to involve people in training activities related to fire management and for the implementation of prevention activities. The cognitive map summarizes the social opinion variability about fire ignition and fire control among citizens of the three municipalities. Overall, the local opinion does not depend on the social structure parameters, such as age, gender and educational qualification, but there is one statistically significant correlation between the causes and the citizens’ residence (Table 3), with a X2 = 56.42 and p = 0.000. The first difference is the number of causes mentioned by citizens within their municipalities (Fig. 5. In Dueré and Formoso do Araguaia citizens mentioned 8 out of 13 different causes, while in Lagoa da Confusão the causes mentioned amount to 11. Only 4 out 13 causes, namely: “accidentally”, “cigarettes”, “slash and burn” and “intentionally”, are common to all the three municipalities and occupy the most central position in the network of Fig. 4. On the other hand, there are two causes mentioned only by citizens from Lagoa da Confusão. These are “breeding” and “beekeeping”. Similarly, only in Formoso do Araguaia one citizen mentioned the “bonfire” as a possible cause of bushfire. Furthermore, “do not know” reaches a higher score in Formoso do Araguaia compared to Lagoa da Confusão and it is totally absent in Dueré. Similarly, “indigenous” people are mentioned more in Lagoa da Confusão than in Formoso do Araguaia, and there is no mention of them in the Dueré. On the contrary, in Formoso do Araguaia and in Dueré cit-
5. Discussion Overall, the interviewees mentioned 13 different causes of fire ignition and 9 different solutions to reduce bushfire risk. Nevertheless, they individually mentioned no more than three causes and three solutions. We demonstrated that a cognitive map is a very useful tool for identifying people’s opinions about environmental problems such as bushfire. The cognitive map highlights citizens’ opinions, helping decision makers to assess the human cognition and preparedness in relation to fire issues (Robertson et al., 2012; Toikkanen and Lipponen, 2011). In the network of this study, the interviewees mentioned 13 different causes of fire ignition, giving prominence to two main insights, careless fire use and the general lack of awareness of fire issues among citizens. This study highlights how citizens strongly consider “cigarettes” as the cause of fire ignition, even if it is demonstrated that this risk is very low (Xanthopoulos et al., 2006). Similarly, they also strongly recognize that fire ignition depends on the mismanagement of agricultural practices, as reported in other studies (Pivello, 2011). These two aforementioned causes highlight the existence of a gap concerning fire behavior among citizens and land managers. This is even more evident if we consider the following causes mentioned by citizens as “accidental” and “intentional”. Citizens refer to the accidental causes, stressing the negligent use of fire in daily activities, such as burning domestic waste or agricultural residues (Bernardes and Günther, 2014). However, they also stress that humans intentionally ignite bushfire. People recognize the careless use of fire in their activities, identifying people’s consciousness as the most important action to be taken in order to reduce bushfire risk. This is demonstrated by the thickness of ties between consciousness and the four causes mentioned previously. For this reason, training activities related to fire behavior, fire management,
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Fig. 5. Frequency of the mentioned causes among the three municipalities.
firefighting, should be promoted in order to foster human learning and consciousness of the use of fire in agricultural practices and in environmental management. Further causes, which score high importance among citizens’ opinions, are “climatic conditions”, “glass fragments” and “do not know”, which are part of the main k-core sub-group. If, on one hand, these causes show the higher variety of elements that affect fire ignitions, although the probability is scarce, particularly for glass fragments (Wittich and Müller, 2009), on the other hand, they highlight the lesser degree of preparedness of citizens in relation to fire issues. This is demonstrated by the fact that the interviewees are not able to mention any causes of fire ignition, as well as by the fact that they prefer to reduce the use of fire, without considering that the Cerrado is a fire dependent ecosystem (Pivello, 2011; Simon and Pennington, 2012), rather than implementing preventive or monitoring activities. As Geiger et al. (2011) stated, repetitive actions of fire suppression within the Cerrado allow the expansion of forest to the detriment of the vegetation of the Cerrado biome. Nevertheless, although prevention and monitoring are within the main k-core sub-group, they occupy a more peripheral position than reducing use and surveillance. The “do not know” solution mentioned by the interviewees supports our findings about the lack of awareness and preparedness. General careless use of fire and lack of awareness of fire issues are the main findings that the cognitive map allowed to identify in the main k-core sub-group. Furthermore, the interviewees believe more in surveillance activities than in monitoring and preventive activities. This aspect allows us to consider that people prefer top-down management implementation rather than bottom-up actions. However, this approach does not encourage people to improve in terms of their risk management skills (Lindell et al., 2009). Furthermore, the cognitive map shows additional causes and solutions that occupy a peripheral position within the network,
forming other three k-core sub-groups. The cognitive map shows that the interviewees mentioned “short-circuit” and “indigenous” activities as possible causes of fire ignition, suggesting “surveillance”, “reducing use” and “consciousness” as possible solutions. In this case, the relationship between causes and solutions appears to be contrasting and confusing, particularly between “short-circuit” and “reducing use”. The explanation is that the interviewees considered “short-circuit” as the consequence of rural activities such as fence servicing, or of animals touching the electricity transmission towers. On the other hand, with the term “reducing use” we indicate the rational use of fire by residents and native people, as well as the responsible implementation of farming practices. Some interviewees also mentioned causes such as “bonfire”, “hunting/fishing” and “beekeeping” activities, associating them to possible solutions such as “surveillance”, “training” activities, “reducing use” and “consciousness”. It is interesting to note how the interviewees identified recreation activities as possible causes of bushfire, even though they occupy a peripheral position in this network. This highlights the importance of the environment as a source of goods and services for society, and, at the same time, it stresses the challenge that environmental managers have to face in order to improve the provision of these ecosystem services. Finally, the interviewees declared that the use of fire in “breeding” practices, such as pasture regrowth (Mistry, 1998), can represent a further cause of fire ignition, highlighting the importance given to the need to improve the consciousness of fire use. Concerning the solutions that occupy the peripheral positions in the network, the interviewees mentioned training as an activity that would be useful in order to improve agricultural, hunting and fishing management practices, as well as in order to reduce fire ignition due to accidental causes and cigarettes. Although it is poorly considered, training activity represents one of the most important actions in order to improve people’s capacity building in the management of fire risk (Buergelt and Paton, 2014). This
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insight represents an important challenge for decision makers who firstly have to understand why the training course is little considered among the inhabitants and, subsequently, implement a more stimulating course in order to increase the number of participants, altering citizens’ opinions and fostering a better management of fire among inhabitants. The interviewees also mentioned “cooperation” among citizens in order to reduce forest fire risk, particularly connected with causes such as “slash and burn” and “accidentally”. The cooperation across community allows the sharing of actions and aims among citizens (Paton, 2008), reducing bushfire risk and also reducing costs for fire prevention and management. Contrary to the central k-core sub-group, this finding compels us to state that some interviewees prefer bottom-up management rather than top-down management actions. Finally, there is one case in which the interviewee declared that there is no solution to reduce fire in the Cerrado, even though he was not able to identify any causes of fire ignition. The lack of preparedness concerning fire management has also emerged in this case, compelling us to consider that fire risk represents a strong threat not only for the environment but also for residents. Studies on the preparedness and capacity building have demonstrated that the holistic system and a multidisciplinary approach are required for a better understanding of how people act, particularly for management of environmental resources (Buergelt and Paton, 2014; Paton et al., 2006; Coughlan and Petty, 2012). Nevertheless, the cognitive map strongly supports decision makers in order to identify challenges and gaps that hinder people from managing fire correctly, altering the environment. The findings that are derived from the peripheral causes displayed in this network, on one hand, confirm the general careless use of fire, and on the other hand, a lack of knowledge, not only of fire management but also of rural practices such as agriculture, breeding, hunting, fishing and beekeeping. These challenges call for integrated educational activities not only in fire management but also in environmental resources management, considering the numerous benefits that humans obtain from the ecosystems. The added value of the cognitive map for decision makers in the development of a management plan of the natural resources brings to light information in order to identify weaknesses that need to be solved. In this manner, through management plan, natural resource managers can suggest how to use funding in order to improve both efficiency in fire management and the conservation of natural resources. Finally, we demonstrated that the social structure of the surveyed population, such as gender, age and educational qualification, does not present alterations of the answers to the questionnaire and in citizens’ opinions in relation to fire issues. However, there is a significant statistical correlation between municipality residence and causes mentioned, as demonstrated by the chi-square analysis. People from the same municipality mentioned the same opinions. As Buergelt and Paton (2014) highlighted, the natural and the physical dimensions not only affect citizens’ behavior, but also foster the communication and the sharing of experience and beliefs. We can confirm that people sharing personal experience and beliefs beyond scientific knowledge affect society’s opinion. Nevertheless, citizens from Dueré showed the most homogeneity of causes with most of them being amongst the core causes of the network. Citizens from Formoso do Araguaia showed less homogeneity in the answers, highlighting a moderate rate of uncertainty among interviewed parties which stressed “do not know” as cause of fire ignition. Finally, citizens from Lagoa da Confusão showed the most variability of causes and high heterogeneity among them. Because the fire represents a real threat in this area, we suggest the inclusion of fire lessons within the educational program in schools in order to improve the awareness about fire risk and damage as well as fire management, prevention and
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control. Strong efforts are needed in order to improve the awareness among citizens in order to promote the conservation of natural resources and the use of them in a sustainable manner. 6. Conclusions Due to the personal benefits obtained, humans manage the environmental resources based on their personal experience and beliefs. For this reason, responsible management of the environmental resources represents the path towards sustainable development. This is possible only if decision makers are able to transfer scientific knowledge to local landowners, practitioners and citizens. Management plans represent useful tools for sharing knowledge and management strategies; thus, it is fundamental to assess their actual implementation by local people, since said implementation may be lacking due to conflicting interests. For this reason, it is important to involve people in management activities in order to understand their opinions and to develop management strategies that meet societal benefit, ecological conservation and economic development. In this study, we applied the cognitive map for ecological problems, such as fire, highlighting the usefulness of this tool in the identification of the human cognition about causes and solutions to bushfire. In particular, we can conclude that the cognitive map is a useful tool for synthesizing a variety of people’s perceptions, fostering the assessment of people’s behavior about such relevant topics of environmental resources. The cognitive map strongly supports decision makers, allowing the identification of challenges and providing awareness of gaps that hinder environmental conservation. In this case, two main findings are carried out from the cognitive map; firstly, there is a general lack of awareness of bushfire ignition among people and, secondly, people highlight a careless use of fire, which results abundant and not rational, with a trend regarding mismanagement in farmer activities. People strongly consider human consciousness as possible solution to reduce bushfire, and they also believe in surveillance activities, while there is poorly consideration of training activities. We recommend a strong revision of the current training course in order to develop more attractive educational courses, improving citizens’ participation and encouraging a shift from local beliefs to scientific assumptions. Acknowledgements We gratefully acknowledge financial support from CAPES Foundation, the Ministry of Education of Brazil, project 88881.062168/2014-01. We are also grateful to the voluntary interviewees of the municipalities of the Dueré, Formoso do Araguaia and Lagoa da Confusão. References Özesmi, U., Özesmi, S.L., 2004. Ecological models based on people’s knowledge: a multi-step fuzzy cognitive mapping approach. Ecol. Modell. 176 (1–2), 43–64, http://dx.doi.org/10.1016/j.ecolmodel.2003.10.027. Appelstrand, Marie, 2002. Participation and societal values: the challenge for lawmakers and policy practitioners. For. Policy Econ. 4 (4), 281–290, http://dx. doi.org/10.1016/s1389-9341(02)00070-9. Bernardes, C., Günther, W.M.R., 2014. Generation of domestic solid waste in rural areas: case study of remote communities in the brazilian amazon. Hum. Ecol. 42 (4), 617–623. Bodin, Ö., Crona, B., Ernstson, H., 2006. Social networks in natural resource management: what is there to learn from a structural perspective? Ecol. Soc. 11 (2). Buergelt, P.T., Paton, D., 2014. An ecological risk management and capacity building model. Hum. Ecol. 42 (4), 591–603. Cachoeira, N.J., 2015. Caracterizac¸ão das Queimadas e Incêndios Florestais no Estado do Tocantins no Período de 2003 a 2011. In: Dissertac¸ão Thesis. Universidade Federal do Tocantins. Coughlan, M.R., Petty, A.M., 2012. Linking humans and fire: a proposal for a transdisciplinary fire ecology. Int. J. Wildland Fire 21 (5), 477–487.
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