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Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial data sets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America.

Mangroves are critical nursery habitats for fish and invertebrates, providing livelihoods for many coastal communities. Despite their importance, there is currently no estimate of the number of fishers engaged in mangrove associated fisheries, nor of the fishing intensity associated with mangroves at a global scale. We address these gaps by developing a global model of mangrove associated fisher numbers and mangrove fishing intensity. To develop the model, we undertook a three-round Delphi process with mangrove fisheries experts to identify the key drivers of mangrove fishing intensity. We then developed a conceptual model of intensity of mangrove fishing using those factors identified both as being important and for which appropriate global data could be found or developed. These factors were non-urban population, distance to market, distance to mangroves and other fishing grounds, and storm events. By projecting this conceptual model using geospatial datasets, we were able to estimate the number and distribution of mangrove associated fishers and the intensity of fishing in mangroves. We estimate there are 4.1 million mangrove associated fishers globally, with the highest number of mangrove fishers found in Indonesia, India, Bangladesh, Myanmar, and Brazil. Mangrove fishing intensity was greatest throughout Asia, and to a lesser extent West and Central Africa, and Central and South America., SCOPUS: ar.j, iiTSE, info:eu-repo/semantics/published

There are many challenges in evaluating international networks. The use of conventional tools can be difficult and often provides less than useful information. Social Network Analysis offers benefits for network evaluators by allowing for documentation and analysis of inter-relationships between individuals and organisations. This paper describes the use of this approach in the evaluation of a major international project entitled the Global Dialogues on Sexual Health and Well-being. It highlights the value of maps in enabling clear visual representations of networks, the identification of areas needing greater focus and the basis on which networks are constructed.

There are many challenges in evaluating international networks. The use of conventional tools can be difficult and often provides less than useful information. Social Network Analysis offers benefits for network evaluators by allowing for documentation and analysis of inter-relationships between individuals and organisations. This paper describes the use of this approach in the evaluation of a major international project entitled the Global Dialogues on Sexual Health and Well-being. It highlights the value of maps in enabling clear visual representations of networks, the identification of areas needing greater focus and the basis on which networks are constructed.

There are many challenges in evaluating international networks. The use of conventional tools can be difficult and often provides less than useful information. Social Network Analysis offers benefits for network evaluators by allowing for documentation and analysis of inter-relationships between individuals and organisations. This paper describes the use of this approach in the evaluation of a major international project entitled the Global Dialogues on Sexual Health and Well-being. It highlights the value of maps in enabling clear visual representations of networks, the identification of areas needing greater focus and the basis on which networks are constructed.

Context: Frontline emergency ambulance clinicians collaborated in a national quality improvement (QI) initiative to improve pre-hospital care for patients with acute myocardial infarction (AMI). Problem: The National Ambulance Clinical Performance Indicator (CPI) care bundle for AMI (consisting of aspirin, GTN, pain assessment and administration of analgesia) highlighted a consistent shortfall in patient pain assessment and inadequate provision of analgesia. Ineffective pain management in AMI has negative physiological and psychological effects that can be detrimental to patient outcomes. The aim is to increase the delivery of the entire AMI care bundle to 90% by March 2012 Assessment of problem and analysis of its causes: We explored barriers to effective pain management using process maps, cause-and-effect diagrams and thematic analysis of audio recordings from QI collaborative workshops and semi-structured interviews. We found that ergonomic factors (interaction between human and system factors), which included ineffective and inefficient pain assessment methods, ineffective feedback processes and poor access to analgesia were root causes for suboptimal pain management in AMI. Intervention: Through collaboration with frontline ambulance clinicians, solutions were found to overcome these root causes. These included: •Provider prompts (e.g. aide memoires and checklists) to prompt care bundle delivery. •Modified pain assessment tools (integrating Wong-baker faces, numerical verbal scores from 0 to 10 and descriptive intensity scales). •Individual clinical feedback by a clinical leader. •The introduction of small nitrous oxide canisters to increase availability and administration of analgesia earlier in the care pathway. Strategy for change: We used Plan-Do-Study-Act (PDSA) cycles to improve processes of care in AMI. Once improvements developed through PDSA cycles were identified, these were spread to county divisions and then trust-wide. Results were shared through

Context: We undertook a national collaborative to improve cardiovascular care by frontline clinicians in 12 English Ambulance Services. Data were collected by clinical audit staff and submitted centrally where they were collated and analysed. Problem: Cardiovascular disease is the commonest cause of death in the United Kingdom (UK). Acute Myocardial Infarction (AMI) causes 250,000 deaths per year and 1 in 3 heart attack victims die before reaching hospital. There are approximately 152,000 strokes per year causing more than 49,000 deaths. Early and effective treatment decreases death rates for AMI and stroke, improves long-term health and reduces future disability. National guidelines for ambulance clinicians are based on evidence for best clinical practice for AMI and stroke care by ambulance services as defined in the National Service Framework for CHD and National Stroke Strategy. Whilst ambulance clinicians were good at delivering specific aspects of care they were less effective at delivering whole bundles of care. Assessment of problem and analysis of its causes: The process of care delivered by English ambulance services is now assessed using National Clinical Performance Indicators (nCPIs) which include measures of complete bundles of care. The care bundle for AMI is: administration of aspirin and GTN, pain score recorded before and after treatment and administration of analgesia. The stroke care bundle consists of recording of FAST, blood glucose and blood pressure. A key project aim was to produce a sustained improvement in the national rate of care bundle delivery for AMI from 43% (range 26.2%-90.32%) to 90% and for stroke from 83.1% (range 39.4 %– 97.6%) to 90% within 2 years. Intervention: Frontline clinicians identified barriers and facilitators to delivery of care bundles and designed and tested new processes using quality improvement (QI) methods after being trained in process mapping, root cause analysis and Plan Do Study Act cycles. The effects of i