Wars Without Beginning or End: Violent Political Organizations and Irregular Warfare in the Sahel-Sahara
11 Wars Without Beginning or End: Violent Political Organizations and Irregular Warfare in the Sahel-Sahara
Olivier J. Walther
University of Southern Denmark, [email protected] Christian Leuprecht
Royal Military College of Canada
David Skillicorn
Queen’s University
Abstract
This article examines the structure and spatial patterns of violent political organizations in the Sahel-Sahara, a region characterized by growing political instability over the last 20 years. Drawing on a public collection of disaggregated data, the article uses network science to represent alliances and conflicts of 179 organizations that were involved in violent events between 1997 and 2014. To this end, we combine two spectral embedding techniques that have previously been considered separately: one for directed graphs (relationships are asymmetric), and one for signed graphs (relationships are positive or negative). Our result show that groups that are net attackers are indistinguishable at the level of their individual behavior, but clearly separate into pro- and anti-political violence based on the groups to which they are close. The second part of the article maps a series of 389 events related to nine Trans-Saharan Islamist groups between 2004 and 2014. Spatial analysis suggests that cross-border movement has intensified following the establishment of military bases by AQIM in Mali but reveals no evidence of a border ‘sanctuary’. Owing to the transnational nature of conflict, the article shows that national management strategies and foreign military interventions have profoundly affected the movement of Islamist groups.
Acknowledgments
We are grateful to Larry Brooks, Dimitris Christopoulos, Alistair Edgar, Colin Flint, and Clionadh Raleigh. Alexandra Green and Marie Hugo-Persson provided valuable technical assistance. An earlier version of this paper was presented at the Balsillie School of International Affairs, Waterloo, on 19-20 March 2015, and at the Workshop on Subnational Governance and Conflict at the University of Sussex on 22 May 2015.
1. Introduction
Inter-state conflicts usually start with a declaration of war and end with surrender, negotiation or an armistice between the belligerents. By contrast, many modern conflicts are seemingly intractable. This trend is particularly evident in the Sahel-Sahara region in North and West Africa, a battleground for Islamists seeking to impose sharia , rebels seeking independence, transnational traffickers, and former colonial powers looking to project influence. While many Sahel-Saharan countries oscillate between periods of rebellion and political unrest, and periods of peace and reconciliation, the actual location and onset of violence defy prediction. Long considered a poster-child of political stability, Mali, for example, faced a military coup, a rebellion, a Western military intervention, and several major terrorist attacks – all in less than 2 years. By contrast, Chad, plagued by civil war and rebellion until the end of the 2000s, has been experiencing an unexpected period of stability – it is among the very few destinations in the Sahara that is still considered safe for tourists (OECD 2014). Against this background, this article examines the relationships between alliances and conflicts as a putative explanation for the apparent unpredictability of many modern wars in the Sahel-Sahara. Social scientists have long been preoccupied with the logic of violence, explaining the presence and absence of violent conflict, and the onset and diffusion of internecine violence. Ostensibly, these are important questions to answer if we hope to prevent and forestall violent conflict. However, in the Sahara-Sahel these models seem to have little explanatory traction: although they vary, the preconditions for violent conflict are omnipresent, yet violence itself seemingly eludes prediction while actual patterns of violence are volatile. Recent research on the social determinants of conflicts in political geography has shown that political allegiances in the Sahel-Sahara were fluid and largely not ideologically motivated (Hagen 2014). Armed groups split and coalesce unpredictably, change names as new opportunities arise, and morph as ephemeral coalitions between tribal and ethnic groups. A similar volatility characterizes commanders and rank-and-file fighters who frequently shift allegiances among regular forces, rebel movements, and violent political organizations (VPOs), depending on local circumstances (Author, 2013). The initial objective of this article posits a relational approach to the study of the structure of relationships among state and non-state actors. In doing so, it harnesses network theory for which social phenomena such as political violence are necessarily mediated by social interactions (Burt 1992). Drawing on a public collection of data on political violence, the article uses network science to represent alliances and conflicts between 179 organizations involved in violent events between 1997 and 2014. Owing to the fundamentally relational nature of internecine violence, we are particularly interested in the way the structural positions of conflicting parties affect their ability to resort to political violence. To this end, we combine two spectral embedding techniques that have previously been considered separately: one for directed graphs that takes into account the direction of relationships between belligerents, and one for signed graphs that takes into consideration whether relationships are positive or negative between groups. Our second objective is to analyze the spatial patterns of violence across the region by localizing violent events and studying the geographic scales of regional dynamics. The literature presumes that borders matter because they circumscribe sovereign territories that impose transaction costs on those who cross. But do borders matter to Islamist groups in the Sahel-Sahara region? If so, what are their effects? And what transaction costs, countervailing or otherwise, do they impose on the movement of Islamist groups? In a geographical environment where populations remain poor and sparse, recent research on the spatiality of conflict in the region has established that cross-border mobility was an important component of military strategy (Zenn, 2014). Armed groups such as Al Qaeda in the Islamic Maghreb (AQIM) capitalize on marital, political, and financial ties throughout the region to attack targets, take hostages, and evade security forces (Guidère 2011, Wilkinson, 2012, Lebovich 2013, Bøås 2014). These general principles of desert insurgency based on mobility, speed and range challenge the Clausewitzian conception of warfare: hold territory and attack the enemy’s strongest point (Keegan 1993). While the desert is seen by many as a hostile environment that “distances and isolates [VPOs] from major population centers and force them to disperse rather than concentrate their forces” (USAID 2014: 16), it can also provide a resource to strike anywhere, anytime, and without apparent logic. Focusing on 389 violent events in which nine Al-Qaeda-affiliated groups have been involved, we highlight specific spatial patterns that emerge from a longitudinal analysis of events over a ten-year period starting in 2004. Due to the transnational nature of conflict, we ascertain the countervailing transaction costs that borders represent, notably by testing whether national borders limit the displacement of Islamist groups or serve as sanctuaries whence attacks are launched. The article proceeds as follows. The second section reviews the literature on the social and spatial organization of state and non-state organizations in West Africa, paying particular attention to the role of networks and national borders. The third section presents the data and explains how, using network analysis and geographical information systems, we structured them into networks and chronological events. The fourth section models the structural position of actors in conflict. The fifth section addresses the spatial patterns of Islamist groups and implications of the findings for theory, method, and practice.
2. Previous research
3. Research design , but neighbors of neighbors and, in fact, the structure of the entire graph. It is this integration that makes the process challenging: positive relationships are naturally transitive (“the ally of my ally could plausibly become my ally”) but negative relationships are not (the proverbial “enemy of my enemy is my friend” does not obtain). Technically, the adjacency matrices that describe positive and negative ties are combined into a matrix, called a Laplacian, that combines both kinds of ties and normalizes the representation so that well-connected nodes are central and poorly connected nodes peripheral (see representation Zheng and Skillicorn 2015, Zheng et al. 2015 for more details). This Laplacian matrix is transformed to discover the directions in which the graph varies the most and these are used as axes for creating an embedded graph. In this representation, position and distance are meaningful. Sets of ‘bad actors’ such as VPOs and (supposedly) ‘good actors’ such as governmental forces and civil society tend to form polar opposites in some dimension(s) of the representation. Since proximity represents similarity – commonly known as an alliance – distance tends to represent opposition. In the networks considered, “neighbors” refer to actors who cooperate or fight each other, and do not necessarily refer to locational space.
4. A social network analysis of political violence
Rank Degree centrality Eigenvector centrality
1 AQIM (0.264) AQIM (0.743) 2 Boko Haram (0.200) MUJAO (0.421) 3 MUJAO (0.136) Military Forces of Algeria (0.289) 4 Ansar al-Sharia (0.120) GSPC (0.257) 5 Ansar Dine (0.096) Ansar Dine (0.229) Mean 0.024 0.071 Std. Dev. 0.035 0.095
Note: Scores are indicated between brackets. The structure of the network of enemies contrasts strongly with the one showing how organizations involved in violent events have collaborated across the region. As depicted in Figure 2, the positive-tie network is divided into three main unconnected groups of allies, one triad connecting an unidentified armed group to Boko Haram and Ansaru, and three dyads. The main cluster on the left is structured around North and West African military and police forces and their civilian allies, which are represented in red and yellow respectively. This cluster is indirectly connected to some of the main Islamist groups in the region, which are represented in green, through the secessionist movement MNLA. MNLA was allied with Ansar Dine in the first weeks of the Malian conflict before switching sides and fighting alongside the French-led military forces in 2013. The two other clusters are related to the Libyan conflict. One is structured around the armed forces of Libya and their pro-government brigades and battalions, 1 the other around Islamist groups and ethnic and communal militias. Each cluster has a chain-like structure in which organizations are rather distant from one another. The Algerian Private Security Forces, for example, are eight steps away from Al Mourabitoune. The long path-length distance, low density (0.034) and low clustering coefficient (0.104) of the network are typical of a structure that is not organized around groups of tightly connected actors. This suggests that most governmental forces and VPOs tend to build bilateral or trilateral alliances rather than broad coalitions across the region. The graph also highlights the lack of regional cooperation between government forces that face similar threats: there is no reported tie between the military forces of Libya and Algeria, or between the military forces of Cameroon and Nigeria. Figure 2: Positive ties between organizations involved in violent events, 1997-2014 Notes: green nodes refer to Islamist groups, red to government forces, yellow to civilians, and blue to other actors. Military and police forces have the highest eigenvector and betweenness centrality, followed by Ansar al-Sharia and the Shura Council of Benghazi Revolutionaries (BSCR), both of which hail from Libya (Table 2). Generally speaking, betweenness centrality scores – that refer to the propensity to bridge clusters – are very low, even for top-scoring nodes, which suggests that the networks contain few exceptional brokers. Only the French military forces play a role in bridging several African armed forces that would otherwise not be connected, hence their high 2 betweenness centrality. Once again, the isolation of Boko Haram in Nigeria contrasts sharply with the network of alliances among other Sahelo-Saharan and Libyan groups. Table 2: Top-scoring nodes for selected centrality measures – positive ties
Rank Eigenvector centrality Betweenness centrality
1 Military Forces of Nigeria (0.400) Military Forces of France (0.111) 2 Police Forces of Nigeria (0.379) Military Forces of Algeria (0.071) 3 Ansar al-Sharia (0.223) Military Forces of Mali (0.070) 4 Shura Council of Benghazi Revolutionaries (0.260) Military Forces of Nigeria (0.062) 5 Military Forces of Libya (0.193) MNLA (0.052) Mean 0.039 0.012 St. Dev. 0.082 0.022
Note: Scores are indicated between brackets. 4.2. Spectral embedding Now, we compute the spectral embedding of the social networks derived from the ACLED data. Initially, for the sake of simplicity, we disregard the direction of the ties. The embeddings are shown in Figure 3. Negative ties resulting from recorded attacks are shown in red and positive ties resulting from alliances, or at least common purpose, are shown in green. The general structure is of a group of opposing poles representing groups whose primary relationship is that they attack or are attacked by groups at the other pole. The graph clearly shows how ‘bad’ actors such as Islamist and Jihadist groups are grouped opposite ‘good’ actors, both violent and non-violent. The contrast is particularly evident for Boko Haram, and its opposition to governmental forces and civilians from Nigeria and Cameroon, as well as for GIA-GSPC-AQIM, and its opposition to Algerian armed forces and civilians. The graph also shows that the attack patterns of GIA, GSPC and AQMI differ significantly from those of Ansar Dine, MUJAO and Al Mourabitoune, which are located much closer to the center of Figure 3. 3 Figure 3: Spectral embedding showing positive and negative ties Any measure that considers a group in isolation is unable to distinguish VPOs from military or police organizations because both have similar patterns of interaction. We, therefore, compute measures of outward and inward aggression based not on the number of such incidents but on the length of the relevant ties in the embeddings. A group’s position in the embedding reflects its relationships with all of the groups with which it interacts, and, therefore, the length of the embedded ties is more revealing than simply the number of attacks. For example, the distance of a group from the center of the embedding reflects not only how many other groups attack it (or are attacked by it) but also the extent to which its enemies are similar to one another (close in the embedding). Thus a long red tie measures not only the existence and frequency of attacks, but also their strategic intensity. On Figure 4, groups are plotted at the same positions as in the spectral embedding presented in Figure 3 to denote “levels of aggression”. They measure the outgoing aggression of each group and the incoming aggression to which it is subjected. They are color-coded: red means a group generates more aggression than it receives; orange means that the group generates some outgoing aggression; and green means that there is no outgoing aggression (individual scores are presented in Appendix 1). 4 Figure 4: Spectral embedding showing levels of aggression The vicinity of groups presented in Figure 4 allows us to distinguish VPOs (almost all groups are red) from national defense forces (many are also red but adjoined by orange or green). In other words, most of the polar opposites consist of ‘bad actors’ on one side and ‘good actors’ on the other, and they are structurally distinct. ‘Bad’ aggressive actors such as AQIM or Boko Haram tend to be in clusters of net aggressors, or isolated; ‘good’ aggressive actors such as militaries tend to be in clusters with orange and green groups. Neutral actors such as the International Committee of the Red Cross (ICRC) tend to fall in the middle and green. Victims are also green but tend to be located near their champions. Northern Nigeria and Libya are particularly interesting as they involve many VPOs with strong structural constraints. From the literature we would expect Northern Nigeria, where Boko Haram is particularly dominant, to have more of a dual structure than Libya, where myriad of violent groups compete for the control of the state and oil resources (Gow et al. 2013). We find that our intuition was correct as Figures 5 and 6 show. Spectral embedding showing conflicts and cooperation for 37 organizations in Northern Nigeria clearly confirms that Boko Haram is in conflict with virtually everyone, a situation comparable to that of ISIS in the Middle East, which opposes all governments and non-state actors – including Al Qaeda – in the region. 5 Figure 5: Spectral embedding showing positive Figure 6: Spectral embedding showing and negative ties for 37 organization in positive and negative ties for 30 Northern Nigeria organizations in Libya Note: for the sake of clarity, Ansaru is not shown. In Libya, spectral embedding conducted on 30 organizations highlights the ongoing conflict between pro-Islamist groups and pro-government forces (Figure 6). Islamist groups, on the left of the graph, are composed of Islamist militias such as Libya Dawn and Libya Shield, and of Jihadist groups close to Al Qaeda such as the Revolutionaries Shura Council (BRSC), a coalition that includes Ansar al-Sharia, the 17 February Brigade, and the Rafallah Sehati Brigade. These groups, based in Tripoli and in Benghazi, all oppose the Libyan army, as indicated by several long red ties. Among pro-government forces, on the right, are anti-Islamist militias such as the Zintan Militia, the Al-Sawaiq Battalion and the Al Qaqa Brigade. Civilians and journalists are located near the internationally recognized authorities of Libya.
5. Spatial analysis of mobility patterns
This section examines the spatiality of select Islamist groups that have developed attack patterns across the Sahel-Sahara region. For strategic and policy purposes, we are particularly interested in whether state border strategies and multinational military missions have had a measurable effect on the transborder movement of Islamist groups. 5.1. Changing mobility patterns The analysis that follows reveals no evidence of a ‘sanctuary’ pattern in which Islamist groups make systematic use of a particular border area. However, Table 3 reveals that the movement of Islamist groups changed completely between 2004 and 2014: while the first seven years were marked by an apparent unpredictability of events across time and space, the last three years were characterized by a concentration of events, due to the outbreak of the Malian conflict and the strategies adopted by some states to control their borders. This shift occurred in a political environment where the number of violent incidents and victims related to Islamist groups in Sub-6 Saharan Africa has been on the rise (Dowd 2013, 2015, Dowd and Raleigh 2013). While only 30 events totaling 201 victims were reported between 2004 and 2008, there were 359 events and 1233 victims between 2009 and 2014. The intensification of attacks significantly reduced the average frequency between violent incidents, from an average of 44.8 days in 2008 to 7.5 days in 2014. Table 3: Key metrics
Year Number of events Cross-border movements (%) Number of victims Average distance between events (km) Average distance to borders (km) Average time between events (days)
The region has always been characterized by a high level of transborder activity. Figure 7 confirms that, until 2011, Islamist groups travelled extensively across borders and, in many regions of Mali, Mauritania, Algeria and Niger, without much risk of being apprehended. After Algeria expelled them, they were tolerated by the Malian government of President Amadou Toumani Touré (2002-2012), which sought to capitalize on divisions within Tuareg society and on a withdrawal of the state to administer the northern part of the country. Successive events repeatedly occurred hundreds or thousands of kilometers apart, in different countries, and irregularly, from Algeria to Mauritania, the Mauritanian-Malian border, and Niger. In 2005 and 2006, the average distance between two events exceeded 500 km, which is impressive given the harsh terrain and lack of road infrastructure, in particular in the Sahara. One of the best known movements of this period is also the one that marked the beginning of the Saharan expansion of what would become AQIM. Between 21 February and 11 April 2003, 32 European tourists were kidnapped in the region between Illizi and Amguid in Algeria by Abderazak el-Para (born Amar Saïfi) and Abdelhamid Abu Zeid (born Mohamed Ghadir), two militants of GSPC. As Algerian security forces gave chase, the terrorists and hostages initially journeyed of over 3000 km to northern Mali. After having spent several months establishing alliances with leaders of local nomadic tribes, they moved to Niger through the plains of Azawagh, Aïr Mountains and the Ténéré desert, and ended up in the mountainous area of Tibesti in Chad where they were killed or captured, a second journey of over 2500 km through some of the most inhospitable environment on the planet (Author 2010). In 2011, Mauritania and Algeria undertook a series of joint counter-terrorism operations aimed at AQIM’s military bases. Such an attack took place in the Wagadu forest on the border between 7 Mauritania and Mali in June. The central intelligence cell created to facilitate co-ordination between Saharan and Sahelian countries, known as the Combined Operational General Staff Committee (CEMOC), first met in Bamako in April 2011. Nonetheless, the level of regional cooperation remained low because Mali was not trusted by its neighbors, which accused it of colluding with Islamist groups. Henceforth, Mauritania and Algeria would conduct military operations in Mali when they deemed their interests to be threatened by the activities of transnational groups. The chronological succession of attacks by AQIM in 2011 shows a high intensity and percentage of cross-border movements. For example, AQIM claimed responsibility for a bomb attack in Bamako, the capital of Mali, on 5 January, followed by a hostage taking in Niamey, Niger three days later. On February 1, these attacks were followed by an AQIM car bomb in the Mauritanian town of Adel Bagrou, the abduction of an Italian tourist in Djanet, Algeria, a day later, and the killing of a Mauritanian policeman by two members of AQIM in the region of Legsseiba near the north bank of the River Senegal on February 3. The year 2012 contrasts sharply with the period 2004-2011 because most events transpired in Mali, and, to a lesser extent, Algeria. Following the fall of Col. Muammar Gaddafi in Libya (2011) and President Amadou Toumani Touré (2012) a provisional alliance between Al Qaeda-affiliated groups and secessionists rebels of the MNLA launched a wide-ranging military offensive against the Malian army. Over a matter of weeks, all major cities of Northern Mali were seized, including Tessalit and Kidal in the Adrar des Ifoghas, where the offensive started, as well as Menaka, Timbuktu and Gao. New groups such as MUJOA and Ansar Dine were particularly active during this period and started to clash with their former Tuareg allies over the cities of the north of the country and main lines of communication. Our analysis shows that during this period the distance between violent events and borders is the more stable (approximately 150 km) than the preceding period during which average distances to borders varied from 39 to 334 km. In 2013, the French-led Opération Serval reasserted control over Northern Mali. As French and Chadian troops progressed north, Islamist groups were driven from Kona, Douentza, Gao, Timbuktu, and were chased out of their stronghold of the Adrar of the Ifoghas. Operation Panthère, launched around Tessalit on 18 February 2013, successfully defeated them, possibly because the French and their allies adopted some of the principles of warfare that had made Islamists and rebels so successful in the region. Operation Panthère relied on a combination of airstrikes, artillery and ground combat operations conducted by the French, knowledge of the country provided by Tuareg guides, and Chadian desert warfare. Chadian troops and their highly mobile light trucks proved as effective in Mali as they have in the past 30 years in their own country. 8 Figure 7: Events connected chronologically, 2004-2014 Note: the color of the lines refers to the year(s). As in 2012, most events in 2013 took place in Mali and Algeria, along a south-west–north-east axis extending from Bamako in Mali to Tamanrasset in Algeria. While the French and their allies pushed north, the rebels of the MNLA seized Kidal and Tin Zaouaten from Islamist groups, and clashed with AQIM and MUJAO. The Algerian army also clashed with Islamist groups fleeing Mali towards Libya. The most brazen terrorist attack was launched in January 2013 against the 9 gas facility of In Amenas in Algeria where MUJAO and Al Moulathamoun coordinated their activities, resulting in at least 67 deaths. A decade after being expelled from Algeria, Al Qaeda-affiliated groups were back in the country. Later that year, a camp of Niger’s military was hit by MUJAO in Agades in May, military barracks were attacked in Niamey in June by Those Who Sign in Blood, and two French journalists were killed by AQIM in Bamako in November 2013. The spatial patterns of attacks in 2014 are similar: principally concentrated in Northern Mali and, to a lesser extent, in Southern Algeria, localized events resulted from the French offensive in the Tighaghar Mountains that killed many Islamist leaders, and from MNLA rebels clashing with MUJAO. Roadside bombs and suicide car bombings organized by Al Mourabitoune targeted the United Nations Multidimensional Integrated Stabilization Mission in Mali (MINUSMA). The French-led anti-terrorist Opération Barkhane replaced Opération Serval in August 2014, and relies on highly mobile forces. Contrary to previous military engagements that targeted “one country, one crisis, and one theatre of operations”, Opération Barkhane explicitly addresses the regional and cross-border dimension of terrorist activity throughout the region. The Operation relies on three ports in the Gulf of Guinea, two main airports in the Sahel, and a series of Saharan outposts located at the extreme periphery of Chad, Mali and Niger to disrupt cross-border trafficking routes and terrorist networks. Considering that Algeria and Libya are beyond the reach of any foreign armed forces and that the French military is stretched to the limit (de Galbert 2015), for the time being Opération Barkhane is the most ambitious military initiative at the regional level. 5.2. State border strategies Do borders not matter if they cannot offer sanctuary? On the contrary, our analysis suggests that borders do matter because countries have put in place management strategies that affect the spatial patterns of Islamist groups. Building on Arsenault and Bacon’s (2015) distinction between government will and capability to fight foreign terrorist groups, four situations can be distinguished (Table 4). States may have the military capacity to challenge transnational groups and choose to do so. In the region, Mauritania is probably the country most similar to this situation. Despite the small size of its armed forces, Mauritania took a number of strong military measures to control the flows of Islamist groups across its borders: develop mobile patrols, attack intruders systematically and establish partnerships with local tribes. As our analysis revealed, this firm attitude, combined with a national strategy for deradicalization (Ould Ahmed Salem 2013), has occasioned a significant decrease of violent events since 2012. Table 4: Government will and capacity to fight transnational groups
Will
Strong Weak
Capacity
Strong e.g. Mauritania Algeria Weak e.g. Niger e.g. Mali Some states may also be in a position to deny foreign fighters access to their territory but choose not to do so, for strategic reasons. Whether Algeria would have adopted this strategy is a matter of debate. On the one hand, having suffered from decades of political violence, Algeria is strongly committed to combating terrorism in the region and plays a major role in peace 0 negotiations in Mali. During the Malian conflict, Algeria deployed tens of thousands of troops to secure its borders, which are probably the most heavily guarded in the region. On the other hand, Islamist groups would have been unlikely to emerge in Northern Mali if Algeria’s borders had been hermetically sealed. Many of the aforementioned groups originally hail from Algeria or are affiliated with organizations based there, and there is strong evidence that Algerian borders are easily crossed by Islamist groups to get food and oil supplies through informal arrangements with state representatives (CSIS 2014). The third situation, where states may want to disrupt transnational groups without being able to project military power into borderlands, characterizes Niger. The 5,700 km border of Niger has long been poorly guarded due to lack of men and material. AQIM and other groups have capitalized on the situation either to take hostages in the region or to move to the south of Libya, where numerous Islamist groups have found favorable conditions (CSIS 2014). Finally, Mali exemplifies a lack of political will and ability to fight foreign Islamist groups. The gradual withdrawal of the state from the North of the country in the 2000s left Mali’s borders unguarded and frequented by traffickers and militant groups.
6. Conclusion
The article examines the structure and spatial patterns of VPOs in the Sahel-Sahara, a region characterized by growing political instability over the last 20 years. Based on a novel approach that combines signed and directed graphs, our methodological contribution has been to highlight opposed groups and distinguish among several kinds of aggressors depending on their conflict patterns. In settings where groups form shifting alliances and oppositions, an approach that takes into account not only the local, pairwise relationships, but also the global patterns that emerge, is needed for situational awareness. Conventional social network analysis can represent positive ties, but not ties where direction matters, or where ties represent a negative association. Furthermore, these are not independent properties of a social network and so must be represented together. This article has illustrated the effectiveness of extending social network analysis to such settings. Conventional social network measures fail in these settings. For example, measures such as betweenness are inappropriate because negativity does ‘flow’ in the way that positivity is conceived, and centrality is not a crucial property when negativity separates nodes far from the center. From a theoretical perspective, the paper advances theory on the spatiality of Islamist groups by showing that sanctuary is immaterial to Saharan borders because many Islamist groups seek to control the movement of people and (often illicit) goods (Bøås 2015). The inability to garrison a sparsely populated region such as the Sahel-Sahara – which is the size of the United States – makes it difficult to hold territory. This situation is similar to the one adopted by Daesh between Syria and Iraq, and radically different from the territorial objective of such groups as Boko Haram in Africa, or the Taliban on the Afghanistan-Pakistan border, for which the defense of a delineated territory is paramount. Building on publicly available data, we started by mapping how 179 organizations involved in political violence were structurally connected through conflict and alliances. Our results show that the network that connects actors in conflict has a low density, a low level of transitivity, and 1 contains few central actors, three typical features of negative-tie networks. AQIM is unequivocally the most connected organization, both in terms of the overall number of actors with which the group is in conflict, and the respective centrality of its enemies. In network terms, this is a liability. Divided into several clusters, the positive-tie network has a long path-length distance, low density and low clustering coefficient, a structure that suggests that most organizations tend to build limited alliances rather than broad coalitions across the region. We then combined the two networks and modeled the effect of having friends and foes simultaneously. Using the attack relationships, we also measured the level of outgoing and incoming aggression of each group. From this approach, five categories emerge. The first category includes neutral actors, represented in the middle of our graphs. The following categories include three kinds of groups that cluster together: victims, groups that are attacked more than they themselves attack, and groups that counter violence and thus attack more than they are attacked (e.g. militaries). The fifth category includes violent extremist groups that attack more than they are attacked, such as VPOs. Groups that are net attackers are indistinguishable at the level of individual behavior, but clearly separate into pro- and anti-violent extremism based on the groups to which they are close. This conclusion is in line with our original assumption that the propensity to use political violence concur with a group’s position in the social network. The second part of the article mapped a series of 389 events related to nine major Islamist groups in the region. Spatial analysis suggests that violent events involving Islamist groups have followed different patterns depending on the period under consideration but reveals no evidence of a border ‘sanctuary’. While violence was concentrated almost exclusively within Algeria until 2004, cross-border movement has since intensified, following the establishment of military bases by AQIM in Mali. This suggests a ‘mobility’ scenario similar to the Arab revolt of the 20 th century during which a highly mobile irregular force defeated the immobile and defensive Ottoman Turkish army. Our analysis suggests that until the French-led military offensive of 2013, military operations of trans-Saharan Islamist groups were “more like naval warfare than ordinary land operations, in their mobility, their ubiquity, their independence of bases and communications, their lack of ground features, of fixed directions, of fixed points” (Lawrence 1920). More recently, Islamist groups have concentrated their operations in Northern Mali as well as Southern Algeria, leaving Mauritania, Niger and Chad relatively unscathed. Owing to the Malian conflict and to a series of state and international military initiatives, cross-border movement has been on the wane in some countries, which seems to validate our original assumption that Islamist groups concentrate on border segments that are less heavily guarded and/or where informal arrangements with border officials are possible. Our results have policy implications for governments and external forces involved in deterring politically violent organizations. First, unlike their adversaries, VPOs are socially and spatially connected across the regions; so, there is a need for collective security institutions that can help countries coordinate, build trust, and go beyond ad hoc engagements. In recent years, several ‘Sahel’ strategies have been initiated by organizations as diverse as the European Union (2011), the United Nations (2013), the Economic Community of West African States (2014), the African Union (2014), and the regional coordination framework G5 Sahel, to address governance, security and development in the region. Building institutional capacity around common interests is likely to pay off in a region that is largely devoid of collective security institutions. Precedent 2 also suggests that states outside the region will continue to play a supporting rather than a lead role. In addition to supporting capacity-building efforts already underway, Western governments should be prepared to mount a comprehensive Whole-of-Government effort in support of local authorities that will minimize their local footprint while optimizing outcomes. From a military perspective, the fluidity of personal allegiances and mobility of actors across borders in the region calls for a mobile and flexible military response. Regional volatility notwithstanding, operations Serval and Barkhane suggest that desert insurgents are not impervious to external attack. As Western armies and their African allies become more mobile and flexible in their regional responses to political violence, desert insurgency proves to be a double-edged sword that can also work against those who know the terrain best. References
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40: 103−122. 7 Appendix 1. Violent political organizations, 1997-2014 Abu Obeida Brigade Abu Salim Martyrs’ Brigade Al Qaeda Al Qaqa Brigade Al-Burayqah Martyr’s Brigade Al-Salafiya Al Jihadia Ansar al-Sharia Ansar Dine Ansaru AQIM: Al Qaeda in the Islamic Maghreb Boko Haram Brega Martyrs Brigade El-Farouk Brigade Falcons for the Liberation of Africa February 17 Martyrs Brigade Fighters of The Martyrs Brigade FIS: Islamic Salvation Front GIA: Armed Islamic Group GMA: Mourabitounes Group of Azawad GSL: Free Salafist Group GSPC: Salafist Group for Call and Combat Islamic Emirate of Barqa Islamic State of Tripoli Knights of Change Libya Shield Brigade LIDD: The Islamic League for Preaching and Holy Struggle Martyrs’ Brigade MUJAO: Movement for Unity and Jihad in West Africa Muslim Brotherhood Nawasi Brigade Nusur al-Sahel Brigade Rafallah Sehati Brigade Soldiers of the Caliphate in Algeria Those Who Signed in Blood Timizart Brigade 8 Appendix 2. Aggression levels for all groups that have more than one enemy
Group aggression outaggression inaggression
Rioters (Libya) 1.32 1.32 0.00 Military Forces of Libya 0.43 0.50 0.07 MUJAO 0.32 0.84 0.53 Military Forces of Algeria 0.28 0.50 0.21 Protesters (Mali) 0.21 0.21 0.00 Protesters (Libya) 0.19 0.19 0.00 GIA 0.14 0.31 0.17 Military Forces of Tunisia 0.14 0.14 0.00 Police Forces of Tunisia 0.13 0.13 0.00 Unidentified Armed Group (Algeria) 0.11 0.11 0.00 Civilians (France) 0.11 0.26 0.15 GMA 0.10 0.16 0.06 Libya Shield Brigade 0.09 0.54 0.45 Military Forces of Chad 0.09 0.12 0.04 Military Forces of Libya Special Forces 0.06 0.13 0.06 Libyan Rebel Forces 0.06 0.27 0.20 LIDD 0.06 0.09 0.03 GSPC 0.05 0.31 0.26 AQIM 0.05 0.76 0.71 Military Forces of Nigeria 0.04 0.09 0.05 Wershefana Communal Militia (Libya) 0.03 0.14 0.10 GLD 0.01 0.04 0.04 Boko Haram 0.01 0.19 0.18 Ansar Dine 0.00 0.42 0.42 El-Farouk Brigade 0.00 0.06 0.06 Military Forces of Mali 0.00 0.22 0.22 MNLA 0.00 0.23 0.23 Military Forces of France 0.00 0.25 0.25 Those Who Signed in Blood -0.01 0.09 0.09 Martyrs Brigade -0.02 0.04 0.06 February 17 Martyrs Brigade -0.02 0.16 0.18 Patriot Militia of Algerian Government -0.03 0.12 0.15 Abu Salim Martyrs Brigade -0.04 0.00 0.04 Civilians (Nigeria) -0.04 0.05 0.09 Military Forces of Mauritania -0.05 0.05 0.10 Military Forces of Niger -0.07 0.10 0.17 Al Qaqa Brigade -0.07 0.00 0.07 Ansaru -0.08 0.04 0.12 9 Police Forces of Algeria -0.08 0.13 0.21 FIS -0.08 0.00 0.08 Al Qaeda -0.10 0.21 0.31 Unidentified Armed Group (Libya) -0.10 0.37 0.48 Civilians (Libya) -0.12 0.09 0.21 Police Forces of Morocco -0.12 0.00 0.12 Civilians (Niger) -0.12 0.00 0.12 Civilians (Algeria) -0.12 0.08 0.21 Rafallah Sehati Brigade -0.13 0.00 0.13 UN -0.14 0.07 0.21 Zawia Ethnic Militia (Libya) -0.16 0.00 0.16 Civilians (Morocco) -0.16 0.00 0.16 Civilians (International) -0.20 0.04 0.24 Soldiers of the Caliphate in Algeria -0.21 0.00 0.21 Civilians (Mali) -0.36 0.00 0.36 Ansar al-Sharia -0.52 0.53 1.05 Muslim Brotherhood -0.91 0.00 0.91 Note: For each group, the outaggression is the average length of outgoing attack ties in the embedded graph, inaggression is the average length of incoming attack ties, and net aggression is the difference of the two. 0 Appendix 3. Aggression levels for Libyan organizations
Group aggression outaggression inaggression
Protesters 1.24 1.24 0.00 Military Forces 0.77 0.83 0.07 Libyan Rebel Forces 0.41 0.68 0.28 Libya Shield Brigade 0.36 1.13 0.77 Wershefana Communal Militia 0.20 0.51 0.31 Misratah Communal Militia 0.00 0.32 0.32 Abu Salim Martyrs Brigade 0.00 0.06 0.06 Ansar al-Sharia -0.04 0.70 0.74 Islamist Militia -0.06 0.00 0.06 Brega Martyrs Brigade -0.06 0.00 0.06 Vigilante Militia -0.07 0.00 0.07 Al Qaeda -0.09 0.00 0.09 Al Qaqa Brigade -0.11 0.85 0.96 Zintan Ethnic Militia -0.22 0.00 0.22 Operation Libya Dawn -0.23 0.00 0.23 Zawia Ethnic Militia -0.25 0.00 0.25 Civilians -0.26 0.22 0.48 Gharyan Communal Militia -0.30 0.00 0.30 February 17 Martyrs Brigade -0.47 0.06 0.53 Rafallah Sehati Brigade -0.81 0.00 0.81 Source: ACLED. Calculations: authors. Note: the following organizations with entirely zero rows have been removed from the table: El-Farouk Brigade, Al-Sawaiq Battalion, BSRC, Journalists, Police Forces, Salafist Group, Mutiny of Military Forces, Janzur Communal Militia, Awlad Suleiman Ethnic Militia, Shura Council of Benghazi Revolutionaries. 1 Appendix 4. Aggression levels for Nigerian organizations