Assortative mixing in networks

A network is said to show assortative mixing if the nodes in the network that have many connections tend to be connected to other nodes with many connections. We define a measure of assortative mixing for networks and use it to show that social networks are often assortatively mixed, but that technological and biological networks tend to be disassortative. We propose a model of an assortative network, which we study both analytically and numerically. Within the framework of this model we find that assortative networks tend to percolate more easily than their disassortative counterparts and that they are also more robust to vertex removal.Comment: 5 pages, 1 table, 1 figur

Ambiguity, complexity and dynamics in the membership of collaboration

This paper is concerned with the role that membership structures of inter-organizational collaborations have on the achievement of collaborative advantage in the context of tackling social issues. Based on action research involving participants in a wide variety of collaborative situations, the paper aims to explore the nature of the membership of collaborations in practice. A picture of membership is built up from two perspectives. The first considers the structure of collaboration, and argues that ambiguity and complexity in structure may be demonstrated over many dimensions. The second adds another layer of complication through exploring the dynamics of the way in which membership structures change over time. The paper concludes by examining the implications for practitioners and policy makers of this picture in terms of its effect on the design of collaborations and on the factors which tend to lead to collaborative inertia instead of collaborative advantage

Propagating uncertainty to estimates of above-ground biomass for Kenyan mangroves: a scaling procedure from tree to landscape level

Mangroves are globally important carbon stores and as such have potential for inclusion in future forest-based climate change mitigation strategies such as Reduced Emissions from Deforestation and Degradation (REDD+). Participation in REDD+ will require developing countries to produce robust estimates of forest above-ground biomass (AGB) accompanied by an appropriate measure of uncertainty. Final estimates of AGB should account for known sources of uncertainty (measurement and predictive) particularly when estimating AGB at large spatial scales. In this study, mixed-effects models were used to account for variability in the allometric relationship of Kenyan mangroves due to species and site effects. A generic biomass equation for Kenyan mangroves was produced in addition to a set of species-site specific equations. The generic equation has potential for broad application as it can be used to predict the AGB of new trees where there is no pre-existing knowledge of the specific species-site allometric relationship: the most commonly encountered scenario in practical biomass studies. Predictions of AGB using the mixed-effects model showed good correspondence with the original observed values of AGB although displayed a poorer fit at higher AGB values, suggesting caution in extrapolation. A strong relationship was found between the observed and predicted values of AGB using an independent validation dataset from the Zambezi Delta, Mozambique (R2 = 0.96, p = < 0.001). The simulation based approach to uncertainty propagation employed in the current study produced estimates of AGB at different spatial scales (tree – landscape level) accompanied by a realistic measure of the total uncertainty. Estimates of mangrove AGB in Kenya are presented at the plot, regional and landscape level accompanied by 95% prediction intervals. The 95% prediction intervals for landscape level estimates of total AGB stocks suggest that between 5.4 and 7.2 megatonnes of AGB is currently held in Kenyan mangrove forests

Factors influencing the frames and approaches of host organizations for collaborative catchment management in England

The frames and approaches adopted for collaborative catchment management (CCM) by 22 host organizations in England were examined. Hosts framed and approached CCM according to their particular funding arrangements, management priorities, actor networks, attitudes toward knowledge and uncertainty, and willingness to share power and take risks. The findings support the theory of path dependency, and indicate that the majority of hosts created CCM groups that were much narrower in scope, direction, and structure than had been envisaged by government policymakers. To address this, a new national policy framework for catchment management in England is recommended that defines guiding principles for collaboration and balances the needs for clear direction and discretion in policy implementation

The Fish Community of an East African Mangrove: Effects of Turbidity and Distance from the Sea

Mangroves are often reported as nursery grounds for fish. Fish may enter mangroves in order to avoid predators, but may not need to do so if turbidity provides a sufficient predator refuge outside the forest. This study assessed the effects of turbidity in the field and laboratory on mangrove fish community structure and behaviour. The extent to which fish penetrate into mangroves has received little attention. This study also looked at differences in fish community structure at mangrove sites near (6m) and far (200m) from the mangrove/sea boundary. Twelve field samples were taken at approximately monthly intervals from replicate 25m2 landward and seaward plots, in a Sonneratia alba stand at Gazi Bay, Kenya. A total of 25 species of fish were caught, 15 in seaward plots and 13 in landward ones. Mean abundance for all plots and sampling times was 2.15 (equivalent to 0.09 m-2). Seaward plots had a total mean abundance more than twice that of landward plots (2.75 ± 1.9 S.D. vs. 1.23 ± 0.33 S.D. respectively). There was no relationship between abundance and turbidity. Laboratory experiments showed no significant changes in behaviour of three common species in response to turbidity. The low density of fish recorded concurs with previous work, and probably reflects conditions in Gazi Bay as a whole, rather than unusual features of the mangrove environment there

Carbon in the coastal seascape: how interactions between mangrove forests, seagrass meadows and tidal marshes influence carbon storage

Purpose of review: We use the ‘seascape’ concept to explore how interactions between mangrove forests, tidal marshes and seagrass influences the storage of carbon in these ecosystems. Mangrove forests, with the other two ‘blue carbon’ habitats, are exceptionally powerful carbon sinks. Maintaining and enhancing these sinks is an emerging priority in climate change mitigation. However managing any one ecosystem on its own risks ignoring important contextual drivers of carbon storage emerging from its place in the seascape. We consider how interactions between these coastal habitats directly or indirectly affect the amounts of carbon they can store.Recent findings: The export of carbon from seagrasses may occur over hundreds or thousands of kilometres, much further than reported for mangroves or tidal marshes. Seagrasses may buffer mangroves from wave impacts, assisting forest regeneration. Trophic cascades supported by contiguous blue carbon habitat may limit excessive herbivory and bioturbation in them but evidence is limited. Summary: Direct transfers of carbon between blue carbon habitats are common and are likely to enhance total carbon storage but our understanding of their contribution to carbon stocks at the seascape level is elementary. There is evidence for indirect enhancement of carbon storage at the seascape by close association of habitats, mostly through the creation and maintenance of propitious conditions by one ecosystem for another. Protection from waves of mangroves by seagrass and protection from excess nutrients and sediment of seagrass by mangroves and tidal marsh are key mechanisms. There is little evidence or theory suggesting negative effects on carbon storage of one blue carbon habitat on another

AI for the Public Sector: Opportunities and challenges of cross-sector collaboration

Public sector organisations are increasingly interested in using data science and artificial intelligence capabilities to deliver policy and generate efficiencies in high uncertainty environments. The long-term success of data science and AI in the public sector relies on effectively embedding it into delivery solutions for policy implementation. However, governments cannot do this integration of AI into public service delivery on their own. The UK Government Industrial Strategy is clear that delivering on the AI grand challenge requires collaboration between universities and public and private sectors. This cross-sectoral collaborative approach is the norm in applied AI centres of excellence around the world. Despite their popularity, cross-sector collaborations entail serious management challenges that hinder their success. In this article we discuss the opportunities and challenges from AI for public sector. Finally, we propose a series of strategies to successfully manage these cross-sectoral collaborations

Exploring leadership in multi-sectoral partnerships

This article explores some critical aspects of leadership in the context of multi-sectoral partnerships. It focuses on leadership in practice and asks the question, `How do managers experience and perceive leadership in such partnerships?' The study contributes to the debate on whether leadership in a multi-sectoral partnership context differs from that within a single organization. It is based on the accounts of practising managers working in complex partnerships. The article highlights a number of leadership challenges faced by those working in multi-sectoral partnerships. Partnership practitioners were clear that leadership in partnerships was more complex than in single organizations. However, it was more difficult for them to agree a consensus on the essential nature of leadership in partnership. We suggest that a first-, second- and third-person approach might be a way of better interpreting leadership in the context of partnerships

Shrimp aquaculture as a vehicle for Climate Compatible Development in Sri Lanka. The case of Puttalam Lagoon

At present, aquaculture of black tiger shrimp (Penaeus monodon) in the Puttalam district of Sri Lanka is unsustainable with more than 90% of the former shrimp ponds laying abandoned as a result of shrimp disease and improper management. Between 1992-1998, over 50% of the mangrove cover was removed in order to establish shrimp aquaculture. This severely affected the functioning of coastal ecosystems, reducing their provision of useful services and increasing coastal vulnerability to climate change. Changes in the hydrology and polluted residual matter make the soil unsuitable for other agricultural purposes without costly restoration. The root of the problem was inappropriate management and a focus on short term economic gains. Despite this previous failure, the national development plan, Mahinda Chinthana, now promotes aquaculture as an avenue for development. This will only be possible if aquaculture is regulated in a sustainable and well-managed manner, and does not increase local vulnerability to climate change effects. The current paper discusses the possible costs and benefits in applying the concept of Climate Compatible Development (CCD) to shrimp aquaculture in Puttalam, Sri Lanka. It suggests how the sector can support mitigation of Green House Gas (GHG) emissions and adaptation to climate change effects, whilst stimulating development that will also benefit rural societies. Mechanisms that could enable this change include subsidies, insurance and bank loans which will also facilitate investment by foreign private enterprises and subsequent export. The development of a specific aquaculture policy and master plan would facilitate the process further