Modeling landscape sustainability in the oil producing Niger delta area of Nigeria

Energy Policy 133 (2019) 110893

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Modeling landscape sustainability in the oil producing Niger delta area of Nigeria

T

Christian N. Madua,b,*, Chu-hua Kueib a b

Shell Center for Environmental Management & Control (CEMAC), University of Nigeria, Enugu Campus, Enugu, Nigeria Department of Management and Management Science, Lubin School of Business Pace University, 1 Pace Plaza, New York, N.Y, 10038, United States

A R T I C LE I N FO

A B S T R A C T

Keywords: Landscape sustainability Text mining System dynamics Oil spillages Ecosystem services Sentiment analysis

This paper models landscape sustainability in the oil-producing Niger Delta area of Nigeria. Simon decision making cycle (intelligence-design-choice) was used to examine landscape sustainability planning issues. This approach involves three levels of application namely intelligence, design, and choice. Probability topic model was used in R software to identify the key problems in the Niger Delta area as (1) oil spillage impacts on water/ land use (landscape capital) and (2) militancy (vandalism) and leadership (planning). These problems significantly, affect the landscape capital in the Niger Delta area. System dynamic simulation was applied to evaluate landscape capital under different scenarios of vandalism and different levels of revenue allocation. The study found that the greatest landscape capital can be achieved in 18.25 years if the revenue allocation to the Niger Delta oil producing states is increased from the current level of 13 percent to 21 percent. These results are consistent with UNEP's report that highlights oil spillages in the Niger Delta area as affecting landscape sustainability in the area.

1. Introduction Potschin and Haines-Young (2006, p.156) asked can landscapes be sustainable? They note that “in planning for sustainability, we need to find ways of identifying the set of possible landscapes that can maintain the outputs of goods and services that people value, rather than developing optimal design solutions (Potschin and Haines-Young, p.160)." This view is shared by Wu (2013, 2012), Selman (2012), Ramos (2011), and Jones and Stenseke (2011). A landscape is a nexus of social, economic, and ecological components in a place offering desired or appropriate levels of ecosystem services such as water supply, hazard/ disease regulation, food festivals, and nutrient cycling (Suich et al., 2015; Fisher et al., 2014; Ernstson, 2013; Braat and de Groot, 2012). The issue of landscape sustainability is very important in the Niger Delta area of Nigeria due to several years of neglect of the crude oil pollution in the area. This has subsequently impacted on the soil, water and the mainstream economy of the Niger Delta. Wu (2013, 2012) describes landscape sustainability to include a complex social system, a spatial entity, a temporal dimension, a nexus of nature and culture, and a mental entity. Landscape sustainability allows policy makers to incorporate normative activities (e.g. policy, design, planning and implementation, and management/maintenance/ land care) into organizations and institutions at all levels to increase

*

landscape capitals such as acres of clean and green land Sovacool and Geels (2016), Espinosa (2015), Marseglia et al. (2018). Thus, actionable solutions can be produced to achieve the triple bottom line of economic development, environmental performance, and social equity. Similarly, ecosystem services aim to achieve the triple bottom line through regulating, cultural, and habitat/provisional services in a given landscape [Hamel and Bryant (2017), Zhang et al. (2016), Braat and de Groot (2012), and Muller and Burkhard (2012)]. However, landscape sustainability can be distinguished from ecosystem services. They seem to differ in terms of purpose, functions, forms, and common grounds. These differences are presented in Appendix 1. While there are subtle differences between landscape sustainability and ecosystem services, there is often the tendency to view their functions as alike. This is often more prominent in the case of provisional services (du Toit et al., 2018). The content variables of landscape sustainability can be viewed from Simon's three decision making cycles: intelligence, design, and choice (Simon, 1960). Snowden and Boone (2007) and Alberti and Susskind (1996) applied Simon's concept to describe a complex system landscape sustainability and note as follows: ⁃ Intelligence: searching the managerial, technological, organizational, economic, environmental, and social development conditions

Corresponding author. Shell Center for Environmental Management & Control (CEMAC), University of Nigeria, Enugu Campus, Enugu, Nigeria. E-mail address: [email protected] (C.N. Madu).

https://doi.org/10.1016/j.enpol.2019.110893 Received 5 February 2019; Received in revised form 28 June 2019; Accepted 20 July 2019 0301-4215/ © 2019 Elsevier Ltd. All rights reserved.

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Niger Delta area. ⁃ Social Equity: “Despite the significant revenue generation from the Niger Delta area, there is acute poverty that the Niger Delta is often used as an example of resource curse in the world (Madu et al., 2017, p.23)." ⁃ Action Profiles: Nwankwo (2015, p.387) notes that three action profiles are adopted by the Nigerian government, namely, “the derivation principle [revenue allocation], the establishment of developmental bodies, and the militarization of the region.” The federal government controls the oil revenue and currently, allocates 13% of the oil revenue to the Niger Delta area [Nwankwo (2015, p.387)]. ⁃ Awareness and perceptions of ecosystem services (ES): Zhang et al. (2016, p.154), note that villagers in Nigeria are more aware of provisional ES than cultural and regulating and support services. Provisional ES include acres of clean and green land and are associated with crops, foods, fish, livestock, fuel, and medicine in Nigeria. The UNDP’s 2006 report concludes that the Niger Delta “is a region suffering from administrative neglect, crumbling social infrastructure and services, high unemployment, social deprivation, abject poverty, filth and squalor, and endemic conflict [UNDP (2006, p.25)]." This paper also addresses some of the 17 Sustainable Development Goals as articulated in the United Nations document. Specifically, it has implications to issues of poverty and hunger, clean energy and clean water, and sustainable cities and communities. It is therefore imperative that policy makers in Nigeria understand key trends or current states of landscape sustainability in the Niger Delta since the crude oil generated from the area is the mainstream of the Nigerian economy. They also need to pay attention to the list of emerging conflicts in the area and perhaps, develop a long-term sustainable development vision. This paper aims to address policy issues by focusing on two areas:

Fig. 1. Niger Delta states.

calling for decisions ⁃ Design: seeking and exploring alternatives to interventions resulting in positive impacts on stakeholders' attitude, sustainable practices, and economic wellbeing ⁃ Choice: finding answers in the form of action and risk profiles, building institutional capacities, and measuring success Simon's concept provides a comprehensive way of evaluating a problem situation. It is therefore adopted in this paper to study landscape capitals (e.g. acres of clean and green land) due to oil spillages in the Niger Delta area of Nigeria (see Fig. 1). Oil spillages constitute a major ecological disaster and create enormous environmental, economic, and social problems (Madu et al., 2018; Madu et al., 2017; Nwankwo, 2015; UNEP, 2011; UNDP, 2006; Wurthmann, 2006; Nwilo and Badejo, 2005; Mansour and Haddad, 2017). The problem of oil spillages can be classified as the worst landscape sustainability scenario (Wu, 2012; Selman, 2012; Jones and Stenseke, 2011; Ramos, 2011; Tress and Tress, 2001). We use seven aspects of landscape sustainability to explore the problems of oil spillages in the Niger Delta area of Nigeria. These aspects are identified as follows:

⁃ Revenue allocation by the federal government of Nigeria to the Niger Delta area, and ⁃ Potential breakdown on landscape capitals due to oil pipeline vandalism in the region and natural degradation. The outline of the model approach adopted in this paper is presented in Fig. 2. Specifically, Simon's decision making cycle concept was applied and models are integrated at each stage of the cycle to be able to address the problems already identified. The goal is to identify burning issues in the Niger Delta area, review the current revenue allocation policy in terms of both landscape sustainability and oil pipeline vandalism, and evaluate the role of leadership in achieving long term landscape sustainability goals. The outcome of this research could offer policy guidelines to restore landscape sustainability and ecosystem services in the Niger Delta area of Nigeria. We may also be able to identify the barriers to landscape sustainability in Niger Delta and find the drivers and enablers of change to achieve landscape sustainability. The paper is broken down into sections as follows: Section 1: Introduction; 2: Research Background; 3: Landscape Sustainability Planning; 4: Empirical Assessment – Model Generation and Analysis; 5: Practical Significance/Implications and Limitations; and 6: Conclusions and Policy Implications.

⁃ Place: the Niger Delta zone consists of the nine oil producing states out of the thirty-six states of Nigeria (see Fig. 1). ⁃ Normative Activities: The United Nations Development Programme (UNDP) report of 2006 notes that “for both state and local governments, accountability, transparency and integrity have not necessarily kept up with the increased flow of resources in the delta—politicians and local officials flaunting ill-gotten gains in fact help to fuel conflicts (UNDP, 2006, p.18)." Lehmann (2012) uses a policy mix to analyze pollution problems. This helps to correct for multiple reinforcing failures that are associated with pollution externalities and technology spillovers. Other studies have followed similar path where a policy mix is followed to evaluate energy strategies (Shayegh et al., 2017; Marseglia et al., 2018). ⁃ Economic Development: Wurthmann (2006) estimated that over 600 billion US dollars have been generated from Nigeria's crude oil sales since 1960. ⁃ Environmental Performance: Madu et al. (2017, p.24) indicate that the Ogoni Oil Spills and the cleanup program in the area emphasizes the need for multinational oil firms to engage in corporate social responsibility programs that will benefit the communities. The emphasis here is more on acres of clean and green land. Ogoni is in the

2. Research Background 2.1. Landscape sustainability Landscape sustainability can be enhanced by combining exploratory landscape scenarios and normative activities (Festus 2014; Selman 2012; Ramos 2011; Jones and Stenseke 2011; Wu (2012, 2013)). Ramos (2011, p.205), discusses exploratory landscape scenarios involving “the formulation of plausible scenarios that are subsequently assessed by 2

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Fig. 2. Landscape Sustainability Planning using Simon's Decision-Making Cycle.

stakeholders,” and “bringing out major concerns and desires regarding the future of their [stakeholders'] landscape.” Selman (2012) reports that three factors, namely, landscape setting and context for development, flooding and water resource management, and habitat provision, are associated with environmental landscape modification and creation. The inputs or normative activities of environmental landscape modification and creation process include (1) urban, rural, urban fringe and coastal policy, (2) planning and implementation, (3) design (systematic, ethical, and regenerative), and (4) management, maintenance and land care. These factors are associated to the three elements of ecosystem services (i.e. cultural services/sense of landscapes, regulating services/ flood mitigation, and provisional services/food and wood) identified by Wu (2013). The ultimate aim of landscape sustainability is to enhance social-ecological resilience and offer more space to nature and people. Selman (2012, p.124) further notes that “whilst all participatory processes raise significant practical and ethical issues, the incorporation of public preferences into landscape decisions faces a particular difficulty – namely, there is often no obviously preferable future direction for a given landscape.” Festus (2014) identifies the negative and positive impacts from landscape planning perspectives and also notes that “unsustainable use of landscape elements leads to environmental problems like biodiversity loss, climate change, global warming, soil and coastal erosion, and pollution (Festus, 2014, p.143)." This view is consistent with that of UNDP report (UNDP, 2006). It is difficult to achieve energy conversion with low environmental impact and high performances (Manni et al., 2018; Mendecka and Lombardi, 2018; Marseglia et al., 2018). Jones and Stenseke (2011) emphasize that landscape policy should protect outstanding landscape features and should also enhance the quality of life. They use three concepts to describe landscape: polity (i.e. conditions of a land noted by civil governments), scenery (i.e. the visual content of an area of interest perceived by the general public), and morphology (i.e. material forms of physical surroundings normally studied by scientists).

report opines that the local people have been denied the right to benefit from the resources on the land they live in due to the central control of petroleum resources. This lack of control by the locals, has been attributed as a major cause of civil unrest in the area. The main oil producing area is predominantly habited by the Ogoni people and the area is popularly referred to as Ogoniland. The people of Ogoniland view the central control of these resources as injustice and frequently challenge the revenue allocation formula. This has led to tensions and even agitations for independent states to break away from the government control of their natural resources. Hence the agitation for the emancipation of the Niger Delta. The Niger Deltans demand 50% of the oil revenue while the government gives them 13%. Many attribute the rise in militancy and vandalism of oil pipelines to be as a result of their disagreement with the current revenue allocation percentage. In this paper, we investigate the impact on landscape scenarios by using the current 13% revenue allocation to the Niger Delta states and conduct a “what if” analysis by marginally increasing this value to say 15%. For example, will a marginal increase in the revenue allocation have any effect on oil pipeline vandalism or militancy in the area? Or, will the government need a much higher increase such as 25%, 30%, 35%, etc., to observe a significant change in attitude and landscape capitals of Niger Delta states? These “what if” questions are addressed using system dynamics simulation models. Thus, the different landscape scenarios, leverage points, and/or vandalism activities are evaluated in this paper. In Appendix 1, we try to establish an inter-link between landscape sustainability and ecosystem services and use that to show relationship to revenue allocation. There is need to prioritize the ecosystem services in other to achieve the desired state of ecosystem services. Four categories of ecosystem services are identified (Braat and de Groot, 2012; Costanza, 2012; Ernstson, 2013; Suich et al., 2015; Cerra, 2017): ⁃ provisional services (e.g. land use, foods and water obtained from ecosystems), ⁃ regulating services (e.g. water filtration, regulation of floods and disease), ⁃ cultural services (e.g. cognitive development and nonmaterial benefits), and ⁃ habitat/supporting services (e.g. nutrient for maintenance of ecosystems and soil formation).

2.2. Revenue allocation mechanisms, vandalism activities in Nigeria, and provisional services The issues of resource control and revenue allocation formula used by the federal government of Nigeria in distributing oil revenues to the states are often mentioned as one of the major socio-political factors associated with pipeline vandalism in the Niger Delta area of Nigeria (Nwankwo, 2015; Oteh and Eze, 2012; Barry, 2010; Ojakorotu, 2009; UNDP, 2006). Oteh and Eze (2012, p.17) note that “between 1976 and 1990 about 3,000 oil spill incidents were reported.” UNDP (2006, p.35)

To enhance sustainability landscapes it is imperative to investigate issues of oil spillages in the area and mostly as a result of oil pipeline vandalism. Landscape sustainability models and frameworks are often influenced by ecosystem services. As presented in Appendix 1, it is 3

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Blei (2012) provides a text mining method known as probabilistic topic modeling (PTM) to find “K" (e.g. five) hidden topics in a selected corpus (e.g. 49 text document files on landscape sustainability and oil spillages). This method uses the Latent Dirichelet Allocation (LDA) algorithms unsupervised in R (i.e. the “topicmodels” package) to find “K" (e.g. five) hidden topics and generate the relationship between five hidden topics and “N" text document files on any topic of interest. In our case, we are interested in landscape sustainability and oil spillages. The R software that is used for this application has strong graphic capabilities and can generate image files to show the relationship between landscape sustainability and oil spillages. Madu et al. (2018) use unsupervised LDA to explore policy resistance on oil spillages in the Niger Delta area. Carrera and Jung (2018) also applied probability topic modeling and sentiment analysis to study information diffusion in online social networks. Serna et al. (2017) used sentiment analysis techniques to extract information from social media on sustainable urban mobility conflicts. They categorized attitudes expressed in text documents as either positive, negative, or neutral. Silge and Robinson (2018) present algorithms for -PTM and sentiment analysis. These algorithms are developed in R packages and are namely, “topicmodels”, “tidytext”, and “tidyverse." System dynamic models with R library (“deSolve”) are also useful in providing intelligible explanations to policy makers. They are often presented in the form of causal loop diagrams and with stocks and flows (Abdelkafi and Tauscher, 2016; Banson et al., 2016; Duggan 2008, 2016; Olaya, 2015; Größler and Strohhecker, 2012; Sterman, 2012; Ford, 2010; Harich, 2010; Olabisi, 2010; Forrester, 2003; Vennix, 1996; Kim and Senge, 1994). Olabisi (2010), for example, develops causal loop diagrams depicting forest cover decline in Negros Island. Team and opportunistic learning can both be enhanced by developing causal loop diagrams (Vennix, 1996; Kim and Senge, 1994). Duggan (2016) used the R software to build system dynamics simulation models. The simulation model consists of two model vectors: (1) stocks, and (2) auxiliary variables. The former defines the model stock (e.g. landscape capital of Niger Delta states) and its initial value, while the latter defines the exogenous parameters (e.g. revenue allocation, degradation rate of the landscape). Welbers et al. (2017) use the “quanteda” library in R to generate a comparison report between two text documents to learn the tacit secrets of interest. The chi-square test statistic is used to compare the two text documents. The focal points of one group of observable text data (i.e. the words in the documents) can be thus collaborated by the text evidence from another group. At the conclusion of this part of text mining, tacit knowledge, a concept described by Nonaka (2007) may be realized. R packages provide effective ways to implement these innovative ideas.

provisional services. For the purpose of this study, six content variables of landscape sustainability (provisional services) are considered: (1) key trends or current states of landscape sustainability (provisional services), (2) sentiment scores of landscape sustainability's topical issues (3) landscape capitals (e.g. acres of clean and green land), in the Niger Delta area of Nigeria, (4) stock-and-flow modeling of revenue allocation and vandalism, (5) landscape capitals with planning scenarios (revenue allocation) and vandalism scenarios, and (6)“tacit knowledge” of leadership (landscape sustainability planning). This is depicted in Fig. 2. Note also that landscape capitals (e.g. acres of clean and green land) appear to reflect one of the major features of provisional services in the Niger Delta area of Nigeria based on previous studies (UNEP, 2011; UNDP, 2006). As also shown in Fig. 2, applying Simon's decision-making cycle (intelligence-design-choice) to landscape sustainability would require a systematic process of adopting emerging new data analytics tools to identify planning issues and proffer solutions, and ultimately designing further experiments to find opportunities for continuous improvement. Text mining and systems dynamics modeling with R packages are applied in this context. At the intelligence level, as shown in Fig. 2, the R “topicmodels” routine based on Latent Dirichelet Allocation (LDA) algorithm (see section 2.3) is used. This routine enables scrutiny of text documents files and building topic models. Key trends or current states of landscape sustainability (provisional services) can thus be presented in a graphical form. To build such a model, top-ranked texts are aggregated into topical issues (or topics). They are called hidden topics (or underlying topical issues) in this part of the study since they are derived from mining unstructured text document files. With sentiment analysis in R, using “tidytext” and “tidyverse” libraries, sentiment profiles with sentiment or response scores are subsequently generated and are based on text documents associated with each hidden topic. At the design level, as shown in Fig. 2, we explore the nonlinear behavior of complex provisional services (see Appendix 1) by building causal loop diagrams. System dynamics simulation models with R's “deSolve” library (Duggan, 2016) are then used to explore the different landscape scenarios (e.g. most likely case of vandalism in the Niger Delta area of Nigeria) and their impacts on landscape capitals (e.g. acres of clean and green land). Finally, at the choice level, sensitivity analysis or “what if” is conducted to test the different leverage points (e.g. revenue allocation percentage) to maximize landscape capitals and the overall wellbeing of the people of Niger Delta (e.g. natural and social capital assets discussed by Costanza, 2012). Tacit knowledge-based action profiles are generated after this review. To assure the efficiency of the computation, “quanteda” library in R as suggested by Welbers et al. (2017) is used. The tacit knowledge model derived from the R packages and the two texts from sentiment profiles are associated with the concerns of specific trends of landscape sustainability. They offer another layer of opportunistic learning for continuous improvement. Discrepancies between action profiles and the goals or trends of landscape sustainability may suggest need for landscape planning modifications or landscape sustainability (re)creation initiatives. Thus, the modeling approach followed here may be helpful in improving policy making in the Niger Delta area.

3. Landscape sustainability planning

4. Empirical Assessment – Model Generation and Analysis

A modeling approach that looks at the several interacting and complex social, economic and environmental variables or content variables of landscape sustainability in the Niger Delta is often lacking and thus, the policies made may not be well informed and may in fact, create more problems in the area. To overcome this drawback, we employ innovative modeling approaches to understand landscape sustainability planning issues. Our focus is to achieve one dimension of landscape sustainability, that is,

There are few studies that examine landscape sustainability planning issues. The Niger Delta area of Nigeria is a typical landscape or place that is intriguing to study because of some of its unique characteristics (e.g. a complex social system, a spatial entity, a temporal dimension, a nexus of nature and culture, and a mental entity). Even in the mist of huge revenue generation, the area continues to suffer from severe economic hardship and serious ecological disasters. There is an urgent need to find solutions on how to better enhance its landscape

observed that the categories of ecosystem services such as provisional services are embedded in the process of landscape sustainability (Wu, 2013). Thus, we study landscape sustainability by focusing on provisional services (Wu, 2013; Selman, 2012). We model the direct relationship between revenue allocation formula and exploratory landscape scenarios in the Niger Delta area of Nigeria. 2.3. Modeling the environment with R

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Fig. 3. Topic model (current states of landscape sustainability): Relationships between topics and documents (probability ≥ 0.45, N = 49).

Fig. 3 shows the relationship between five hidden topics (or underlying topical issues) and “49″ text document files on landscape sustainability and oil spillages that were investigated. These text documents were derived from newsprints, academic publications, and the Website of Shell Petroleum Development Corporation. The five hidden topics are selected based on their relative frequencies in the text documents. Hidden topic generated via R (topicmodel) is defined here as the key trends or the current states of landscape sustainability (see Fig. 2). For generating such an image, we increment the starting probability such as 30%, by 5% until good data visualization is produced. Consequently, we set the probability of relationship between topic and text document files to be at least 0.45. This visual aid highlights the importance of the key planning issues that need to be addressed to achieve landscape sustainability in the Niger Delta area. Five hidden topics identified by using the Latent Dirichelet Allocation (LDA) algorithms unsupervised in R are: Ogoniland People (topic 1), Niger Delta communities (topic 2), oil spills and cleanup (topic 3), militancy (vandalism) and President (planning/president Buhari) (topic 4), and oil spillage impact on water and land – landscape capital (topic 5). Fig. 3 can be further examined from key aspects of landscape sustainability discussed in section 1:

⁃ Social Equity: through coordinated efforts by the multinational oil companies such as Shell and the local communities, there may be an improved chance to resolve the conflicts in the Niger Delta (see Fig. 3, topic 2). ⁃ Normative Activities: the cleanup program in the Niger Delta area further emphasizes the importance of data on oil spills in the Niger Delta area and the role of government agencies (see Fig. 3, topic 3). This conclusion is consistent with that of UNEP report of the Oil Spills in Ogoni (UNEP, 2011). According to UNEP, its field observations and scientific investigations found that oil contamination in Ogoniland is widespread and severely impacting many components of the environment. The assessment notes that “overlapping authorities and responsibilities between ministries and a lack of resources within key agencies has serious implications for environmental management on the-ground, including enforcement (UNEP, 2011, p.9)." ⁃ Action Profiles and Economic Development: some acts of militancy (vandalism) are not for profit-making but to halt economic activities in Nigeria. The role of President (Buhari) is also noted (see Fig. 3, topic 4). Oil sabotage/theft accounts for about 28% of total spills in the area (Nwilo and Badejo, 2005). Nwilo and Badejo (2005) further note that Nigeria lost about N7.7 billion (naira) in the year 2002 due to vandalism of oil pipelines. ⁃ Environmental Performance: Water and land use, one of the focal functions of ecosystem services (i.e. provisional services), are noted as major concerns according to our text mining analysis. No design of landscape sustainability is complete without dealing with these core issues (see Fig. 3, topic 5). This finding is also echoed in the report prepared by UNEP (2011). This report points out four areas of landscape sustainability concerns as: contaminated soil and groundwater, vegetation, aquatic, and public health.

⁃ Place: in spite of the vast oil and gas resources in the Niger Delta, the quality of life in the area is considerably very poor (see Fig. 3, topic 1).

It is also observed from Fig. 3 that opportunities exist to enhance the landscape capitals of Niger Delta states such as natural capital (e.g. water and land use), human capital (e.g. skills), physical capital (e.g.

capitals (e.g. acres of clean and green land). Currently, there is an ongoing cleanup exercise that will take several years to rebuild the area from decades of oil pollution. Fig. 2 shows a conceptual framework of the approach followed in this paper to understand the landscape capital and the overall wellbeing of the people of Niger Delta. We shall present our empirical findings below. 4.1. Intelligence activities - topic model

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secrets of knowledge in that file. This further inquiry will be presented in section 4.6.

infrastructures), social capital (e.g. trust), and financial capital (UNDP, 2006, p.373). As shown in Fig. 3, even with probability ≥0.45, water and land use appear to be the number one issue of concern. In subsequent sections, we shall explore clean and green land under different revenue allocation formula and conditions.

4.3. Design activities – causal loop diagram of landscape sustainability Economic growth and environmental justice can be jointly achieved if a proper level of revenue allocation is in effect in the Niger Delta. This can help to reduce the tension in the area, improve the quality of the environment, and provide ecosystem services. We construct a causal loop diagram to focus on landscape capitals and the functions of ecosystem services (see Fig. 4):

4.2. Intelligence activities – sentiment profile model We explore the use of sentiment analysis in R to understand the attitudes and opinions expressed in the avalanche of unstructured text document files. Sentiment analysis generates sentiment or response scores on three types of response, namely, positive (or +), neutral (or 0), and negative (or -). Policy makers can therefore quickly identify the area with higher conflict of opinions. Five sentiment profiles were built with sentiment or response scores based on text document files on five hidden topics (or underlying topical issues). For each sentiment profile, text document file ID (or text ID) is identified by reviewing the corresponding image shown in Fig. 2. For example, referring to Fig. 2, text ID “35" is connected to topic 1. The sentiment or response scores of the five key trends are presented in the last column of Table 1. As shown in Table 1, oil spillage impacts on water/land use landscape capital, and (2) militancy (vandalism) and leadership (planning) have the largest number of text document files. They are also areas of high conflicts. For example, for the case of militancy (vandalism) and leadership (planning) trend, three text document files have positive response (sentiment) scores while four text document files have negative response scores. Developing sentiment profiles with response scores enables the policy maker to identify areas of potential high conflicts so greater attention can be focused there. After a thorough review of Table 1, text ID 32 with a score of −19 is the most pressing since it is connected to Nigeria's President. Specific planning issues regarding landscape sustainability improvement opportunities may be hidden in that text document file. Thus, it is important to dig deeper and present the tacit

⁃ landscape capitals of Niger Delta and revenue allocation in the Niger Delta (see section 2.2), and ⁃ functions of ecosystem services (as discussed in section 2.2) in Nigeria. Signs such as "+" and "-" are used to show the directions of influence between content variables. The former shows that two content variables connected by an arrow move in the same direction, while the latter means they move in opposite directions. As shown in Fig. 4, for the first focal area, the state of landscape capitals of Niger Delta, revenue allocation mechanisms, and UNEP implementation plans and coordinated actions on the four dimensions of local environmental services adopted by oil firms could contribute significantly in increasing profit. Relying on the concept of exploratory landscape scenarios and normative activities, we shall elaborate further on revenue allocation mechanisms in section 4.2 (Selman, 2012; Ramos, 2011; Jones and Stenseke, 2011). The top-right corner of Fig. 4 shows the second focal area. We hypothesize that the seven-point development agenda proposed by UNDP (2006, pp.10–11) may be effective in resolving conflicts and solving environmental services concerns in the non-oil producing states of Nigeria. The seven-point development agenda consists of: ⁃ Promoting peace as the foundation for development, ⁃ Making local governance effective and responsive to the needs of the people, ⁃ Improving and diversifying the economy, ⁃ Promoting social inclusion and improved access to social services, ⁃ Promoting environmental sustainability to preserve the means of people's sustainable livelihoods, ⁃ Taking an integrated approach to HIV&AIDS, and ⁃ Building sustainable partnership for the advancement of human development.

Table 1 Sentiment scores of landscape Sustainability's five underlying topical issues. Topic

Underlying Topical Issues

Text ID

Score

1

Ogoniland People

35

−267

2

Niger Delta Communities

2 3 20 1 24

−14 −17 −17 −37 −86

3

Oil Spills and Cleanup

18 11 12 34

5 0 −14 −18

4

Militancy* (Vandalism) and President** (Buhari)

33** 29 28 23* 32** 22* 31*

23 15 21 −15 −19 −38 −39

48 37 44 49 46 42 47 15

14 12 11 7 −3 −8 −9 −38

5

Oil Spillage Impacts on Water and Land Use

Fig. 4 suggests that ecosystem services can be delivered in Nigeria through such a comprehensive plan. The issue of quality of life is also highlighted in Fig. 4. There are more questions than answers when constructing the causal loop diagram of landscape sustainability shown in Fig. 4. If the revenue allocation in the Niger Delta is increased, there may be more problems. So, some of these anticipated problems should be addressed. Some of the questions that may need be addressed are: ⁃ Will there be a civil war in the Niger Delta states by the residents to fight for control of these additional revenues? What other socioeconomic problems may result from this change? ⁃ Will this change affect the stability of the country? How will the non-Niger Delta states react as their own revenues may either be reduced or remain stagnant? ⁃ Will there be overpopulation in the Niger Delta area as people move to where there are more resources to seek for employment and what happens with the quality of life, crime rate, inflation etc. ⁃ Will the federal government be handicapped with the reduced revenue that it may no longer be able to provide some of the social services? 6

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Fig. 4. Causal loop diagram of landscape sustainability.

⁃ Will the change spur development in the non-Niger Delta states by them looking for other avenues to increase revenue generation? Or, will they seek to increase taxes thereby hurting businesses in their states. ⁃ What effect will change in the revenue allocation for oil producing states have on the allocation to non-oil producing states that have solid minerals such as coal, tin, bauxite, etc., that are tapped and also controlled by the federal government because of the land use laws? ⁃ What effect will change in revenue allocation have on the activities of the oil pipeline vandals?

central concern to achieve the purpose of landscape sustainability. The rationale behind this stock-and-flow system design is presented as follows: The level of land use in a region is, associated to provisional services (Zhang et al., 2016). Suich et al. (2015) provide empirical evidence linking ecosystem services (e.g. provisioning services and regulating services) to poverty alleviation. Based on extensive literature review, Suich et al. (2015) note that provisional services are the main determinants of poverty alleviation. Nwankwo (2015) emphasizes the use of revenue allocation mechanisms to increase landscape capitals (e.g. acres of clean and green land) in the Niger Delta area of Nigeria. The present study develops a stock-and-flow (operational) model with four feedback loops (Duggan, 2016; Sterman, 2012): revenue allocation, degradation, revenue generation, and vandalism. Landscape capitals are treated as the same as ecosystem provisional services in this study (see Appendix 1). The Niger Delta area of Nigeria needs to first concentrate on increasing acres of clean and green land (see Fig. 5). The focus here is on two major loops: revenue allocation and natural degradation. The former mechanisms (13%, 15%, 17%, 19%, or 21%), as shown in Fig. 5, provide major opportunities to increase and/or maintain landscape capitals such as acres of clean and green land, while the latter represent the natural forces at work in limiting the growth (Degradation = 0.05 in this preliminary model). The oil sector in the Niger Delta area of Nigeria, as a main stock in the revenue generation loop, holds the key to revenue generation (Wurthmann, 2006). In this preliminary study (Fig. 5), we also model levels of vandalism in the Niger Delta area. We note in particular that our first-tier system dynamics simulation model is in line with Duggan's two-stock model (Duggan, 2016). The R model presented by Duggan (2016) is thus adapted in this study (see Fig. 5). The technical details are presented in Appendix II.

4.4. Design activities – system dynamics model We start our causal loop diagram at the choice level. It is important at this stage, to have appropriate number of feedback loops (e.g. landscape capitals as discussed in section 3). Once this first-tier model is well developed and tested, the next level of complexity can be built (e.g. functions of ecosystem services as discussed in Appendix 1). The ultimate aim here is to reflect on all the content variables and their relationships as shown in Fig. 4. We therefore, use system dynamics simulation model to examine the impacts of different levels of revenue allocation on landscape capitals (e.g. acres of clean and green land) under three oil pipeline vandalism case scenarios. This is done since the landscape capitals of the Niger Delta are hypothesized to be associated to revenue allocation mechanisms and pipeline vandalism activities. As mentioned in section 2.2, the issues of resource control and revenue allocation formula used by the federal government in distributing oil revenues to the states are often mentioned as a contributory factor to oil pipeline vandalism and militancy in the area. For example, UNDP (2006, p.38) indicates that “only an equitable revenue allocation formula will ease the tension, agitations and perceptions of unfairness” in the Niger Delta area of Nigeria. Landscape capitals (e.g. acres of clean and green land) are objects of 7

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Fig. 5. System dynamics model (Stock-and-Flow modeling of Revenue Allocation and Vandalism).

4.5. Choice activities – simulated states of landscape capitals

years with 21% revenue allocation level under the most likely oil pipeline vandalism case scenario (see Table 2). Fig. 5 also shows the image for each level of revenue allocation under the most likely vandalism case scenario. The possible phenomenon of limits to growth is also noted. What will be the expected performance such as “average provisional

Table 2 presents simulation results with five different revenue allocation levels (i.e. 13%, 15%, 17%, 19%, and 21%) 15 years and 25 years later. It is also observed that the highest landscape capital, 214.60 simulated acres of clean and green land, can be reached after 18.25

Fig. 6. Simulated states of landscape capitals with five planning scenarios (revenue allocation percentages) and three vandalism scenarios. 8

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knowledge (Welbers et al., 2017). Fig. 7a, for example, depicts our summary findings with respect to two text document files shown in Table 1. From Table 1 for example, we compare text ID 33's text entry to text ID 32's text entry to identify tacit secrets of leadership (planning) trend. The former has positive sentiment or response score (i.e. 23) while the latter has negative sentiment or response score (i.e. −19). Clearly, as shown in Fig. 7a, the target file is text ID 33 and the reference file is text ID 32. “quanteda” in R helps us to learn diverse tacit secrets of leadership by comparing the word frequencies of two text entries in the same category of trends of landscape sustainability such as leadership. To get positive sentiment or responses in the long run, UNEP report of the Oil Spills in Ogoni seems to be singled out as the main planning reference on provisional services of landscape sustainability. This focal point is further confirmed by reviewing the world cloud shown in Fig. 7b. Original messages entered by stakeholder in the Niger Delta area of Nigeria can be presented at the conclusion of our inquiry (see Fig. 2). From there, policy makers need to design a series of strategies and activities around tacit knowledge, convert tacit knowledge to explicit knowledge, and engage stakeholders as suggested by Nonaka (2007). We shall in section 5, discuss the practical significance, implications and limitations of the study. The section will also discuss the different strategies followed in the study.

Table 2 Simulated Landscape Capitals (i.e. acres of clean and green land). Revenue Allocation

13% 15% 17% 19% 21%

15 years later

25 Years Later

Best Casea

Most Likelya

Worst Casea

Best Casea

Most Likelya

Worst Casea

38.26 57.72 86.32 126.85 180.37

37.67 56.66 84.22 122.3 169.98

34.43 50.03 71.27 98.6 132.7

112.91 140.83 148.53 151.91 154.81

104.78 134.65 148.26 154.25 157.92

80.08 111.40 134.06 148.84 159.32

Best Casea 225.9 (17.75year)

Most Likelya 214.60 (18.25year)

Worst Casea 183 (20year)

The highest capital value - (year)

a

Vandalism.

Table 3 Expected level of impact under different revenue allocation percentages. Average Provisional Service Base (e.g. acres of land use) Revenue Allocation 13% 21% Performance Changeb: Average Performance Changeb:

13% 21% Performance Changeb: Average Performance Changeb: a b

Best Casea 33.63 39.60 17.75% 31.15%

Most Likelya 31.55 39.52 25.26%

Worst Casea 24.81 37.32 50.46%

5. Practical Significance/Implications and Limitations 5.1. Intelligence - exploiting provisional services first

15 years later Provisional Service Base (e.g. acres of land use) 37.57 36.64 30.21 131.27 114.25 82.34 249.40% 211.82% 172.56% 211.26%

Selman (2012, p.124) notes that “whilst all participatory processes raise significant practical and ethical issues, the incorporation of public preferences into landscape decisions faces a particular difficulty – namely, there is often no obviously preferable future direction for a given landscape.” To overcome this, this study presents new ways for collecting and presenting intelligence. On one hand, as suggested in Fig. 2, one needs to hear the voices of the stakeholders in a given landscape. Probabilistic topic modeling (PTM) which is based on the Latent Dirichelet Allocation (LDA) algorithms is used in this study to identify issues of importance to the stakeholders. We found that (1) oil spillage impacts on water/land use (landscape capital) and (2) militancy (vandalism) and leadership (planning) are the top issues of concern. These results are shown in Fig. 3. These findings are consistent with the UNDP 2006 report on Niger Delta. This report notes that by 2015, about half of the population of people living in the area will not have sustainable access to safe drinking water and sanitation (UNDP, 2006, p.118). Our findings are also supported by sentiment analysis since these two are major causes of conflicts in the Niger Delta area. Landscape capital centering on acres of clean and green land, a measurement of provisioning services, thus seems to be the first stepping stone for opportunistic learning and continuous improvement to a more sustainable future (see Table 1). In recent times, enormous amounts of useful information are stored as text. Obtaining intelligence from unstructured text datasets is the current trend and challenge in text analytics. Policy makers need to respond effectively to such a challenge, be able to frame the issues, understand the role of culture and worldviews, gain insights into the attitudes and opinions expressed within real time text archives and/or text document files, and know the interacting variables that affect landscape sustainability.

Vandalism. (21% Performance - 13% Performance)/13% Performance.

service base or the provisional service base 15-years later” of our stockand-flow simulation system (see Fig. 5) if revenue is increased from 13% to 21%? Fig. 5 also shows that more landscape capital and less vandalism may lead to more extraction or oil revenue generation activities and oil firms will face a greener and more sustainable environment. Extraction is defined here as provisional service base (e.g. acres of land use) used to generate oil revenue if oil firms are in harmony with local communities and nature. Table 3 presents two groups of simulation results with only two different revenue allocation levels (i.e. 13% and 21%): (1) average provisional service base over 25 years, and (2) provisional service base 15 years later. It turns out that, for example, predicted performance (i.e. provisional service base) of our system dynamics model based on 21% revenue allocation 15 years later is on average 211 percent higher than predicted performance based on 13% revenue allocation. 4.6. Choice activities – tacit knowledge model The text mining tool using “quanteda” library in R uses the chisquare test statistic to compare keywords in two text entries [Welbers et al. (2017)]. We use the chi-square test here to identify tacit knowledge that may be of interest to stakeholders. This can posit areas of focus especially for resolving conflicts and achieving continuous improvement over time. Tacit knowledge may be difficult to quantify or pass on from one party to another. However, they may be deeply rooted in individual text document files and can be extracted using “quanteda” library in R. Using “quanteda” and image generation tools in R, we can navigate through text visualization diagrams to learn more about such tacit

5.2. Design – understanding a complete chain of cause and effect It is important to know the mutual interactions between the main content variables of landscape sustainability. As shown in Fig. 4, nine main elements are identified from the literature review (see, for 9

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Fig. 7a. Tacit knowledge model (Leadership – Tacit secrets of interest derived from Text 33 (blue color) and Text 32). (For interpretation of the references to color in this figure legend, the reader is referred to the Web version of this article.)

As also observed from Table 2, under the different revenue allocations, the simulated landscape capitals (i.e. acres of clean and green land) in the Niger Delta area of Nigeria change dramatically 15-year later regardless of vandalism scenarios. However, due to the impacts of other feedback loops such as (natural) degradation, the simulated landscape capitals seem to slow down and show a steady state behavior. Furthermore, we notice as shown in the last row of Table 2, the stockand-flow system achieves its peak 17.75-year later under the best-case scenario of vandalism (i.e. 225.9 simulated acres of clean and green land). For the worst case scenario, it will happen 20 years later with only 183 acres of clean and green land. Jones and Stenseke (2011, p.3) note that the emphasis of landscape sustainability policy is on “protecting outstanding landscape features” and enhancing “quality of all living surroundings, whether outstanding, every day or degraded.” In this study, we contend that Nigerian government recognizes the importance of landscape sustainability policies and develop strategies to exploit provisional services as described in Appendix 1. To form such a policy, as shown in Fig. 5, policy makers can build stock-and-flow (operational) models to examine leverage points with different situational factors under different scenarios and assumptions. We focus here on operational modeling of revenue allocation and vandalism. The image presented in Fig. 5 shows how two stocks, namely, landscape capital (i.e. acres of clean and green land) and oil spill incidents, can be linked together. Such a linkage is again supported by the UNDP 2006 report. The UNDP report notes that oil spills and gas flaring have contributed immensely to pollution in the delta and this has affected air, water, soil, vegetation and even physical structures. As we have mentioned previously, these problems have also affected access to safe drinking water. The incidence of oil spills is also on the rise as a result of the expansion of oil production in the region. In future studies, we shall find answers to other trends posed in section 4.1 by referring to the bigger picture shown in Fig. 4.

Fig. 7b. Tacit knowledge model (Leadership – World Cloud derived from Text 33 and Text 32).

example, Appendix 1) and the results of text mining (see Fig. 3). Vandalism is considered one of the key elements in the loss of landscape capitals (i.e. environmental resources, economic activities, and social conditions) in the Niger Delta area. Causal loop diagram (Fig. 4) thus helps to explain the cause-and-effect of a landscape sustainability with a particular focus on landscape capital such as acres of clean and green land. The graphics of stock-and-flow model, as shown in Fig. 5, is used to reflect the focal point (i.e. landscape capitals of Niger Delta) shown in the causal loop diagram (see Fig. 4). This approach stimulates the interest of the stakeholders in the region as well as policy makers at all levels of government. Armed with such a stock-and-flow image and simulated results (see Table 2), they can see how the simulated landscape capitals (i.e. acres of clean and green land) in the Niger Delta area of Nigeria 15 years and 25 years later will differ remarkably under three different vandalism scenarios. It clearly appears that oil pipeline vandalism activities play a vital role in landscape sustainability (see Tables 2 and 3). This further confirms the causal linkages presented in Fig. 4.

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5.3. Choice – taking issue with both simulation results and tacit secrets of interest

the key actors in Niger Delta to increase the revenue allocation. Although our model is suggesting perhaps an “optimal” level for landscape sustainability, we must note that the 17% revenue allocation recommended by the UNEP report will significantly improve the situation in Niger Delta. One thing that is clear now is that keeping the current level of 13% will not ease tension and will diminish landscape sustainability in the Niger Delta. Enhancing landscape sustainability is an ongoing process. In this study, to replicate the problems along all dimensions of landscape sustainability shown in Appendix 1, we only investigate one major aspect of landscape sustainability, that is, provisional services, in the form of stock-and-flow. If we consider all overlapping functions presented in Appendix 1, the type of stock-and-flow models that may be of interest will be the regulating service, cultural services as described by Wu (2013), Selman (2012), and Braat and de Groot (2012). Thus, there may be a need for more composite definition of landscape sustainability. In future studies, landscape capitals can be represented as a composite score (Shen et al., 2016) or extended to include other aspects of landscape sustainability (and/or ecosystem services). In the long run, enhancing or improving on landscape sustainability as a whole may result in poverty alleviation in the Niger Delta area of Nigeria.

Wu (2013) points out that the outcomes of choice in a landscape setting are on human well-being, social conditions, biodiversity, and ecological processes. Landscape sustainability should be viewed as a leadership process with emphasis on understanding multiple perspectives and tacit knowledge. We have used Figs. 4 and 5 to show the causal relationships that may be observed. Such information is obtained by listening to the voices of the stakeholders. These multiple perspectives are integrated in Fig. 2. The learning obtained from these multiple views are applied in systems dynamics modeling to understand the role of revenue allocation and also oil pipeline vandalism in achieving landscape sustainability. System dynamics simulation models are used here to investigate landscape sustainability under different cases/scenarios of oil pipeline vandalism. Our aim here is therefore, to find effective interventions, seek solutions and action consequences, and identify important issues for discussions by stakeholders in the Niger Delta to be able to address how oil pipeline vandalism is associated to revenue allocation and the influence on landscape sustainability. Simulation results are presented in Tables 2 and 3 It is apparent that revenue allocation is an overriding factor in improving landscape sustainability. We observe that a revenue allocation of 21% will be a good leverage point and will greatly enhance landscape sustainability overtime while significantly reducing oil pipeline vandalism. Its impact will also be felt on other provisional services. In fact, the UNDP report recommends revising the current allocation plan from 13% to 17% although the residents of Niger Delta are demanding a minimum of 25% with a phased review to 50% (UNDP, 2006). Our simulation model recommends that the revenue allocation be increased to 21% (see Fig. 6). Fig. 6 is the visual display of our simulation results shown in the first four columns of Table 2. It shows the simulated landscape capitals with five revenue allocation percentages (i.e. 13%, 15%, 17%, 19%, and 21%) and three pipeline vandalism activities (i.e. base case, most likely case, and worst case). This figure provides a summary of answers to the main questions posed in this study (e.g. what effects will the percentage of revenue allocation and incidences of vandalism activities have on landscape capitals?). The visual form presented in this figure allows policy makers to effectively assess their action consequences. As shown in Fig. 6, for example, even with the worst vandalism scenario, 21% revenue allocation will lead to the best level of simulated landscape capitals (i.e. 132.7). It should also be noted that, for a revenue allocation of 21%, a gain of 28% (i.e. (169.98–132.7)/132.7 = 28%) is achieved when the most likely case is compared against the worst case of vandalism scenario with regards to simulated landscape capitals. This is the best gain when inspecting the performance changes shown in Fig. 6. The most likely scenario is also more representative of reality and shows that we can improve on the landscape in the Niger Delta and reduce oil pipeline vandalism if the revenue allocation is kept at 21%. Further, as illustrated in Fig. 7a and b, concerns on tacit knowledge and strategy/action profiles of leaders in the region should be investigated along the intelligence-design-choice cycle as shown in Fig. 2. As noted by Madu (1996, p.121), “productive conflict helps purposeful organizations because, through conflict analysis, the limitations of the organization as well as the environment could be well explained and understood.” To support such additional analyses, our study offers effective ways of inquiry and analytics methods using “quanteda” library in R.

6. Conclusion and Policy Implications In this paper, we have compared the concepts of ecosystem services and landscape sustainability. We note that the functions of ecosystem services are often viewed as similar to that of landscape sustainability. It is difficult to measure some of those functions such as provisional services and regulating services as well as their impacts on human well-being, social conditions, biodiversity, and ecological processes. We however identify two aspects of landscape sustainability: exploratory landscape scenarios and normative activities. We further note the usefulness of the Simon's decision making cycle to understand key trends or current states of landscape sustainability. Adoption of such an approach helps in identifying the negative and positive impacts from landscape planning. It helps us in understanding natural degradation, examining landscape capitals under different scenarios (i.e., revenue allocation scenarios and vandalism scenarios), and in understanding the implications of the tacit knowledge that may be embedded in a text document. The ultimate goal here is to be able to reverse the loss of environmental resources, and restore the pride and functions of landscape sustainability and/or ecosystem services in the Niger Delta area of Nigeria. A better function of provisioning services may lead to economic benefits, poverty reduction and/or poverty alleviation. By adopting multiple perspectives, policy makers can pay attention to conflict of opinion, and listen to the voices of the stakeholders. We also suggest that goals, interventions, and priorities of landscape sustainability must be supported by stakeholders and active landscape participants. Policy analysis tools with strong graphic capabilities are of utmost importance. Developing topic models and sentiment profiles with response scores enables greater attention to be paid to the list of conflict of opinions shown in the profiles in the oil-producing Niger Delta states. Causal loop diagrams can also be developed to identify circular causality. System dynamics models in the form of stock-and-flow can be established to examine leverage points such as revenue allocation. Overall, appropriate text mining tools can help guide stakeholders and policy makers to optimize intelligence-design-choice performances to achieve landscape sustainability. Some of the key findings of the research can be summarized as follows:

5.4. UNEP report and beyond – enhancing landscape sustainability The UNEP report identified five top issues facing the Niger Delta as: poor infrastructure (37.8%), unemployment (13.3%), pollution (12.2%), corruption (11.1%), and no rule of law, equity and justice (7.8%) (UNEP 2006, p.396). These problems can be significantly improved on if an agreement can be reached with the government and all

1. As the percentage of revenue allocation is increased, better landscape capital is achieved. Thus, there is a direct association between the percentage of revenue allocation and landscape capital. The percentage of revenue allocation to the Niger Delta area therefore 11

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well structured, it will attract the attention of public policy makers who have the discretion to decide on whether to implement it wholly, amend it, or adjust it to suit their unique needs. Increasing revenue allocation to Niger Delta is not a singular factor to solve all the problems of intentional oil spillages in the area. The enabling conditions must also be present to ensure that the increased allocation is dedicated to providing social services. Also, the people should be carried along and they should begin to see themselves as stakeholders in protecting the pipelines. Thus, the increased allocation would require good governance to be able to address the problems of marginalization. The federal government of Nigeria has in the past, instituted many programs including an Amnesty Program for the Niger Delta militants in 2009 with the hope of addressing the issue of marginalization and reducing pipeline vandalism. These programs have not yielded the desired outcome as the region continues to insist on equitable revenue allocation (Okpo and Eze, 2012). Several studies have shown significant negative association between marginalization and vandalism (Fathi et al., 2012; Umar and Othman, 2017). According to Okpo and Eze (2012), the Niger Delta agitators generally believe that oil pipeline vandalism will induce the government to increase the revenue allocation to the area. Thus, it is important the issue of revenue allocation and its association to oil pipeline vandalism is taken seriously. Although the focus of this study is on landscape sustainability planning (i.e., provisioning services), the methodology adopted here could be applied to other functions of ecosystem services. Our study thus has contributions in terms of both the methodology and the research findings. Specifically, the study found that the highest landscape capital value, for the most likely case, will be achieved in 18.25 years and would lead to recovery of 214.60 acres of clean and green land if the revenue allocation to Niger Delta is increased to 21%. This would also lead to a significant reduction in oil pipeline vandalism. We have posed a lot of questions in this paper. Some of them cannot be answered directly by our model. However, it is expected that there will be a ripple effect if the outcomes of the research are implemented. For example, if we are able to increase the revenue allocation as recommended and the resources are managed judiciously, we expect that landscape sustainability will improve significantly and poverty alleviation may be achieved. Further, UNEP report of the Oil Spills in Ogoni seems to play a role in this regard based on our study. The implementation of the results found here requires an enabling environment and the support and involvement of the leadership and other stakeholders.

contributes to the level of environmental degradation in the area. This result is shown in Fig. 6. 2. Oil pipeline vandalism contributes significantly to the environmental degradation in the Niger Delta area and there is an association between oil pipeline vandalism and the percentage of revenue allocation. The stock-and-flow model presented in Table 2 shows that under the best-case scenario for oil pipeline vandalism, it will take 17.75 years to achieve 225.9 acres of clean and green land. However, under the worst-case scenario for oil pipeline vandalism, it will take 20 years to recover 183 acres of clean and green land. It is therefore clear that the worst-case oil pipeline vandalism will generally lead to low landscape capital in the long run. It is equally imperative that public policies must articulate the nexus between oil pipeline vandalism and landscape capital. This would help to avoid the huge cost of oil cleanup later. 3. The study found that the greatest landscape capital can be achieved in 18.25 years if the revenue allocation to the Niger Delta oil producing states is increased from the current level of 13 percent to 21 percent. This is based on the most probable case of oil pipeline vandalism. Currently, there is a massive cleanup going on in Ogoniland – a major oil producing area in Niger Delta. The United Nations Environmental Program in its Environmental Assessment of Ogoniland in 2011, estimates that to cleanup Ogoniland and decontaminate the area for sustainable recovery could cost $1 billion and take 30 years to complete. This report also calls for cessation of all sources of ongoing contamination before the cleanup can commence. With this huge cost of cleanup, action must be taken to remedy the situation and avoid a repeat. There is also increasing public agitation against pollution in the area and the loss of farmlands and livestock. The government is becoming more responsive to the needs of these communities. One can also infer that if the residents of Niger Delta receive an equitable revenue allocation, they will also become stakeholders in protecting the oil pipelines thereby reducing some of the intentional human activities since their revenue allocation depends on the viability of the crude oil business. Many international agencies including the UN have alluded to the need for an upward change in the revenue allocation. To the best of our knowledge, our model is novel in proposing a revenue allocation that will lead to greatest landscape capital (recovery of clean and green land) over time. Of course, this model is not a panacea to all the problems of intentional human activities that may lead to oil spillages in the Niger Delta area. However, it offers a starting point to addressing a major problem that is affecting the country economically and otherwise. UNEP's report also noted the fact that oil spillages affect landscape sustainability in the Niger Delta area and subsequently, recommends a change of the oil revenue allocation to 17% as a way of addressing this problem. We believe that since the present research is objective and

Acknowledgement We acknowledge the helpful comments of the anonymous reviewers. These comments have significantly improved the quality of the paper.

Appendix J. Supplementary data Supplementary data to this article can be found online at https://doi.org/10.1016/j.enpol.2019.110893. Appendix 1. A Contrast of Landscape Sustainability to Ecosystem Services

Purpose

Function 1 Function 2 Function 3

Landscape Sustainability

Ecosystem Services

Combining exploratory landscape scenarios and normative activities to produce locally actionable solutions, restore the pride of the places in question, and increase landscape capitals (e.g. acres of clean and green land); More elaborated versions of landscape capital are called functions of landscape sustainability flood and water resource management (Selman, 2012) - regulating services/ ecosystem services (Wu, 2013, p.1008, p.1008) landscape setting and context for development (Selman, 2012) - cultural services/ecosystem services (Wu, 2013, p.1008, p.1008) habitat provision (Selman, 2012) - provisioning services/ecosystem services (Wu, 2013, p.1008, p.1008)

Moving between a domain of ecosystems' main functions (e.g. provisional services) and socio-economic systems via a cycle of reflection (intelligence and design) and action (choice) to enhance present and future states of biodiversity and (re)design resilient, sustainable socio-economic systems regulating services (e.g. water filtration, regulation of floods and disease)

12

cultural services (e.g. cognitive development and nonmaterial benefits) provisional services (e.g. foods and water obtained from ecosystems)

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N/A (Wu, 2013, p.1008, p.1008)

habitat/supporting services (e.g. nutrient for maintenance of ecosystems and soil formation) Form (Context) a complex social system, a spatial entity, a temporal dimension, a nexus of ecosystems' main functions (e.g. provisional services) interacting with socionature and culture, and a mental entity (Wu, 2012) economic systems and forming a larger feedback process Form (Interventio- four strategies such as Conservation, Restoration, (Re)creation, Reinforcement* a dual approach with a focus on the conditions of ecosystems' main functions n) (e.g. provisional services) and socio-economic systems' policy, capital inputs, and collective behavior Form (Mechanism) a landscape modification and creation process including (1) urban, rural, urban water provisional service: water supply (e.g. surface water); water demand fringe and coastal policy, (2) planning and implementation, (3) design (e.g. public/agricultural/energy/industrial water use); valuation (public/ (systematic, ethical, and regenerative), and (4) management, maintenance and agricultural/energy/industrial monetary map); water availability; water land care (Selman, 2012) scarcity indicators (Karabulut et al., 2016, p.281, p.281) unconditional quality of ecosystem services and sustainable consumption; Form (Outcome) environmental justice; human well-being/social conditions; biodiversity and ecological processes (Wu, 2013); polity, scenery, and morphology (Jones and human wellbeing (security, basic material for good life, health, and good social relations (Fisher et al., 2014) Stenseke, 2011) Common Ground 1 Simon's Intelligence – Design – Choice model Common Ground 2 Analytics (shown in Fig. 2) Common Ground 3 Disaster Risk Reduction and Climate Change Adaptation (e.g. silent networks)

Appendix II. Technical Details on the R Model The R model presented by Duggan (2016) is adapted in this paper. Specifically, we run the following stock-and-flow model (e.g. Revenue Allocation = 0.13%; most likely scenario of oil pipeline vandalism) directly in R studio: (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)

R Library used: deSolve and gglopt2 Simulation time used: 25 years Stock 1 defined: Landscape Capital of Niger Delta States (initial value = 5 acres of clean and green land) Stock 2 defined: Resource - The Oil Sector in the Niger Delta area of Nigeria (initial value = 1000) Auxiliary variables defined: Degradation = 0.05, Cost. Per.Investment = 2, Fraction. RevenueAllocation = 0.13, Revenue. Per.Unit = 3 Most likely scenario of vandalism defined as a relationship between resource (stock 2) level and a set of extraction efficiency values (i.e. 0,0.25,0.45,0.63,0.75,0.85,0.92,0.96,0.98,0.99,1) Model defined: function (simulation time, stocks, auxiliary variables) Equation defined: for example, dS1_dt = Investment-Degradation (note: S1 = stock 1) Return (i.e. output) values defined: capital, resource, investment, degradation, extraction A range of scenarios examined: 13%, 15%, 17%, 19%, or 21% Graph generated: Fig. 6 (see also section 6.2)

The above model is ran for the best-case and the worst-case scenarios. Such a scenario is defined as the relationship between resource (stock 2 The Oil Sector in the Niger Delta area of Nigeria) level and a set of extraction efficiency values. Two more scenarios are considered in this preliminary model: - Best scenario of vandalism's date sets = 0,0.35,0.55,0.73,0.85,0.90,0.95,0.97,0.99,0.999,1, - Worst scenario of vandalism's date sets = 0,0.1,0.25,0.43,0.55,0.65,0.72,0.82,0.89,0.95,1.

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