Browsing by Author "Greenhalgh S"

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    Attitudes of a farming community towards urban growth and rural fragmentation – An Auckland case study
    (Elsevier, 6/08/2016) Curran-Cournane F; Cain T; Greenhalgh S; Samarsinghe O
    As the global population continues to increase, rural areas are expected to accommodate future growth at the same time as continuing to feed growing populations. This tension is greatest on those who farm land that is earmarked for future urban growth. Yet, little is known about the attitudes and values of the affected rural farming communities or farmers’ perceptions of the challenges and opportunities that population growth presents. This paper presents the results from a survey of outdoor vegetable growers in Pukekohe, an area under increasing pressure from urban growth, located in Auckland, New Zealand’s fastest growing city. An analysis of rural fragmentation is also provided to demonstrate the extent of land use change to help contextualise growers’ responses. Survey results showed that economic discourses fail to fully capture the symbolic meaning the land has for growers; many participants were deeply connected to the land, with the desire for the farming legacy to continue, while also recognising its highly productive capability. Participating growers identified numerous challenges and opportunities as a consequence of urban growth. Key challenges included: reverse sensitivity associated with development pressures; achieving sustainable productivity and profits; and perceptions of an increasingly bureaucratic legislative environment. Key opportunities included: occupation of a unique vegetable growing environment; capitalising on the area’s close proximity to city markets; and for a minority of participants, possible financial gains through residential housing development. Geospatial analysis demonstrated a large degree of rural fragmentation that can lead to adverse cumulative effects without the intervention of policy. Future research needs to focus on determining the consequences of continuous development pressures onto versatile land in relation to a country’s, current and future, food-growing capacity. This will be imperative as the population continues to grow. It will not only inform the environmental impacts of these land use decisions but also the socio-economic consequences that will aid with fully informed planning, policy and decision-making that account for a multiplicity of needs.
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    Practitioner perspectives on informing decisions in One Health sectors with predictive models
    (Springer Nature Limited, 2025-12-01) Pepin KM; Carlisle K; Chipman RB; Cole D; Anderson DP; Baker MG; Benschop J; Bunce M; Binny RN; French N; Greenhalgh S; O’Neale DRJ; McDougall S; Morgan FJ; Muellner P; Murphy E; Plank MJ; Tompkins DM; Hayman DTS
    The continued emergence of challenges in human, animal, and environmental health (One Health sectors) requires public servants to make management and policy decisions about system-level ecological and sociological processes that are complex, poorly understood, and change over time. Relying on intuition, evidence, and experience for robust decision-making is challenging without a formal assimilation of these elements (a model), especially when the decision needs to consider potential impacts if an action is or is not taken. Models can provide assistance to this challenge, but effective development and use of model-based evidence in decision-making (‘model-to-decision workflow’) can be challenging. To address this gap, we examined conditions that maximize the value of model-based evidence in decision-making in One Health sectors by conducting 41 semi-structured interviews of researchers, science advisors, operational managers, and policy decision-makers with direct experience in model-to-decision workflows (‘Practitioners’) in One Health sectors. Broadly, our interview guide was structured to understand practitioner perspectives about the utility of models in health policy or management decision-making, challenges and risks with using models in this capacity, experience with using models, factors that affect trust in model-based evidence, and perspectives about conditions that lead to the most effective model-to-decision workflow. We used inductive qualitative analysis of the interview data with iterative coding to identify key themes for maximizing the value of model-based evidence in One Health applications. Our analysis describes practitioner perspectives for improved collaboration among modelers and decision-makers in public service, and priorities for increasing accessibility and value of model-based evidence in One Health decision-making. Two emergent priorities include establishing different standards for development of model-based evidence before or after decisions are made, or in real-time versus preparedness phases of emergency response, and investment in knowledge brokers with modeling expertise working in teams with decision-makers.
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    Steps towards operationalizing One Health approaches.
    (Elsevier B.V., 2024-04-27) Pepin KM; Carlisle K; Anderson D; Baker MG; Chipman RB; Benschop J; French NP; Greenhalgh S; McDougall S; Muellner P; Murphy E; O'Neale DRJ; Plank MJ; Hayman DTS
    One Health recognizes the health of humans, agriculture, wildlife, and the environment are interrelated. The concept has been embraced by international health and environmental authorities such as WHO, WOAH, FAO, and UNEP, but One Health approaches have been more practiced by researchers than national or international authorities. To identify priorities for operationalizing One Health beyond research contexts, we conducted 41 semi-structured interviews with professionals across One Health sectors (public health, environment, agriculture, wildlife) and institutional contexts, who focus on national-scale and international applications. We identify important challenges, solutions, and priorities for delivering the One Health agenda through government action. Participants said One Health has made progress with motivating stakeholders to attempt One Health approaches, but achieving implementation needs more guidance (action plans for how to leverage or change current government infrastructure to accommodate cross-sector policy and strategic mission planning) and facilitation (behavioral change, dedicated personnel, new training model).