Ecology is the study of the relationships between organisms and the biological and non-biological components of their natural environments. Ecologists consider natural systems to be organized in a nested structure. In a given locale, there are individual organisms, groups of organisms of the same species (populations), antagonistic or cooperative interactions among groups of species (communities), and interactions among communities and the non-biological environment (e.g., air, water, and sunlight). We refer to these latter units as biological ecosystems to distinguish them from human organizational structures, networks, and systems, which we refer to as organizational ecosystems. In biological ecosystems, nodes are different species (i.e., each node is a collective of individuals of the same species). Biological ecosystems can contain hundreds or even thousands of species, but certain species—keystone species—play outsized roles in structuring them. Generally speaking, keystone species are those whose removal can be expected to have exceptionally strong effects on other members of the community, and hence on the functioning of the ecosystem as a whole. Organizations increasingly belong to complex networks that enable them to work together in support of shared and complementary goals. To understand this trend, scholars, policy makers, and leaders regularly seek new viewpoints from which to explore the conditions and complexities associated with human networks and organizational systems. Sociologists have developed a range of analytical models for identifying actors and organizations within formal and informal systems, and for explaining the various relational ties that link these organizations together Social network analysis (SNA) has been used to describe the formation of and communication patterns within and between terrorist cells, as well as to predict the outcomes of particular cell activities. Many questions remain, however. Organizational scientists have begun to recognize the power of biological concepts to explain the dynamics that foster and sustain linkages between actors and organizations Here, we look to the field of ecosystem ecology for insights into the conditions, relational dynamics, and complexities that underpin and sustain violent non-state actor (VNSA) networks.
There are many potential applications of ecosystem models, but we are particularly excited about the potential for applying principles discovered by ecologists studying the effects of species extinction to develop testable hypotheses about the effects of eliminating particular militant groups within the VNSA organizational ecosystem. There are a number of crucial questions that could be explored using this framework. In the context of a region with multiple militant groups (pursuing a variety of goals, sometimes competing and sometimes cooperating, some more directly threatening to the United States than others, some using more brutal tactics than others), what traits identify groups that play a keystone role within the broader violent conflict ecosystem? How would eliminating a particular group affect the intensity of violence within the system as a whole? What are the effects—both beneficial and detrimental—on other VNSA nodes within the system and on the system as a whole? What other qualities of the broader environment condition the consequences of eliminating an actor within the system? There has been a tendency in both academic and policy circles to focus on the effectiveness of strategies designed to disrupt and destroy militant organizations while ignoring the wider system-level effects of eliminating any particular actor within the system. But counterterrorism strategists should be concerned with the potential unintended consequences of eliminating militant groups, as removing one node from a system clearly can have a wide range of effects…
Dark networks (such as those involving terrorists and criminal narcotics traffickers) are hidden from nonparticipants yet could have a devastating effect on our social order and economy. Understanding their topology yields greater insight into the nature of clandestine organizations and could help develop effective disruptive strategies. However, obtaining reliable data about dark networks is extremely difficult, so our understanding of them remains largely hypothetical. To the best of our knowledge, the data sets we explore here, though subject to limitations, are the rst to allow for statistical analysis of the topologies of dark networks.
We found that the covert networks we studied share many common topological properties with other types of networks. Their ef ciency in terms of communication and information ow and commands can be tied to their small-world structures, which are characterized by short average path length and a high clustering coefficient. In addition, we found that due to their small-world properties, dark networks are more vulnerable to attack on their bridges that connect different communities within them than to attacks on their hubs. This nding may give authorities insight for intelligence and security purposes.
Another interesting nding about the three elicited human networks we studied is that their substantially high clustering coefficients (not always present in other empirical networks) are dif cult to regenerate based on only known network effects (such as preferential attachment and small-world effects). Other mechanisms (such as recruitment) may also play an important role in network evolution. Other research has found that alter- native mechanisms (such as highly optimized tolerance) may govern the evolution of many complex systems in environments characterized by high risk and uncertainty……topology-of-dark-networks-xu-2007