Exploring the solution space for different forestry management structures in New Zealand under climate change

The concept of “solution spaces” is used to explore the potential future of forestry under climate change for different types of forestry management structures. We base the analysis in New Zealand, where forestry plays an increasingly critical role in the nation's climate policy, but the concept could be applied to any region. Understanding solution spaces and the ways in which they can be influenced at different levels of ownership is a critical step towards effective climate change adaptation. Building on the base of existing climate projections, scenarios, and economic and social science literature, we form an assessment of the capacity of each forest owner typology to influence their solution spaces into the future. Different management structures have strengths in different areas – while industrial forest managers may be able to utilise emerging technologies better than their smaller scale counterparts for example, they may be less agile and flexible. The sector as a whole may benefit from working collectively to draw on the respective strengths of each typology. Critically, planning now to expand the space into the future will be essential

Recovery of carbon stocks after wildfires in boreal forests : a synthesis

Book of abstracts Cool forests at risk? The Critical Role of Boreal and Mountain Ecosystems for People, Bioeconomy, and ClimatePeer reviewe

Modelación matemática en estudio de agro-cadenas: una revisión de literatura

The agricultural sector is the fundamental axis that moves the world economy, it allows the generation of agricultural and livestock products to supply small and large cities. In underdeveloped countries, the participation of industry and academia is necessary to strengthen production systems, this based on the injection of technology, as well as the transfer and appropriation of knowledge in the sector. An approach used to strengthen the sector is the study of agricultural supply chains (agro-chains) based on mathematical modeling, that allows data processing and facilitates strategic, tactical or operational decision-making. We conducted a review of the literature on the application of mathematical models in the study of agricultural chains during the last 20 years. The study concludes that there is a fairly great interest by the academic-scientific community to strengthen the agricultural sector in different countries such as the United States, Brazil, India and the Netherlands, among others. Stochastic simulation models are used in 36% of the consulted works, allowing complex problems involving uncertainty in data behavior to be addressed. Also, in 70% of the works consulted, heuristic models are used to solve design and distribution problems in agro-chains, and the remaining 30% require the use of metaheuristics because they require solving problems with multiple responses given the complexity of the data. Mathematical modeling has become a very useful tool for solving latent problems in agro-chains, it facilitates data processing and complex decision-making, mainly during chain design, product supply and control of costs, delivery times and environmental impacts, among other important variables.El sector agrícola es el eje fundamental que mueve la economía del mundo, permite la generación de productos agrícolas y pecuarios para el abastecimiento de pequeñas y grandes ciudades. En los países subdesarrollados es necesaria la participación de la industria y la academia para el fortalecimiento de los sistemas productivos, esto a partir de la inyección de tecnología, así como la transferencia y apropiación de conocimiento en el sector. Un enfoque usado para el fortalecimiento del sector, es el estudio de las cadenas de suministro agrícolas (agro-cadenas) a partir de la modelación matemática, la cual permite el tratamiento de datos y facilita la toma de decisiones de orden estratégico, táctico y/o operativo. En el presente trabajo se realizó una revisión de literatura sobre la aplicación de la modelación matemática en el estudio de las Agro-cadenas durante los últimos 20 años. Se concluye del estudio que, existe un interés bastante grande por la comunidad académico-científica por fortalecer el sector agrícola en diferentes países como Estados Unidos, Brasil, india y Holanda entre otros. En el 36% de los trabajos consultados se emplean modelos de simulación estocástica, permitiendo abordar problemas complejos que involucran incertidumbre en con comportamiento de los datos. Además, en el 70% de los trabajos consultados, se utilizan modelos heurísticos para resolver problemas de diseño y distribución en agrocadenas, y el 30% restante requiere el uso de meta-heurísticas porque requieren resolver problemas con múltiples respuestas dada la complejidad de los datos. La modelación matemática se ha convertido en una herramienta de gran utilidad para la solución de problemas latentes en la agro-cadenas, facilita el tratamiento de datos y la toma de decisiones complejas, principalmente durante el diseño de cadena, el abastecimiento de producto y control de costos, tiempos de entrega e impactos ambientales, entre otras variables importantes.El sector agrícola es el eje fundamental que mueve la economía del mundo, permite la generación de productos agrícolas y pecuarios para el abastecimiento de pequeñas y grandes ciudades. En los países subdesarrollados es necesaria la participación de la industria y la academia para el fortalecimiento de los sistemas productivos, esto a partir de la inyección de tecnología, así como la transferencia y apropiación de conocimiento en el sector. Un enfoque usado para el fortalecimiento del sector, es el estudio de las cadenas de suministro agrícolas (agro-cadenas) a partir de la modelación matemática, la cual permite el tratamiento de datos y facilita la toma de decisiones de orden estratégico, táctico y/o operativo. En el presente trabajo se realizó una revisión de literatura sobre la aplicación de la modelación matemática en el estudio de las Agro-cadenas durante los últimos 20 años. Se concluye del estudio que, existe un interés bastante grande por la comunidad académico-científica por fortalecer el sector agrícola en diferentes países como Estados Unidos, Brasil, india y Holanda entre otros. En el 36% de los trabajos consultados se emplean modelos de simulación estocástica, permitiendo abordar problemas complejos que involucran incertidumbre en con comportamiento de los datos. Además, en el 70% de los trabajos consultados, se utilizan modelos heurísticos para resolver problemas de diseño y distribución en agrocadenas, y el 30% restante requiere el uso de meta-heurísticas porque requieren resolver problemas con múltiples respuestas dada la complejidad de los datos. La modelación matemática se ha convertido en una herramienta de gran utilidad para la solución de problemas latentes en la agro-cadenas, facilita el tratamiento de datos y la toma de decisiones complejas, principalmente durante el diseño de cadena, el abastecimiento de producto y control de costos, tiempos de entrega e impactos ambientales, entre otras variables importantes.The agricultural sector is the fundamental axis that moves the world economy, it allows the generation of agricultural and livestock products to supply small and large cities. In underdeveloped countries, the participation of industry and academia is necessary to strengthen production systems, this based on the injection of technology, as well as the transfer and appropriation of knowledge in the sector. An approach used to strengthen the sector is the study of agricultural supply chains (agro-chains) based on mathematical modeling, that allows data processing and facilitates strategic, tactical or operational decision-making. We conducted a review of the literature on the application of mathematical models in the study of agricultural chains during the last 20 years. The study concludes that there is a fairly great interest by the academic-scientific community to strengthen the agricultural sector in different countries such as the United States, Brazil, India and the Netherlands, among others. Stochastic simulation models are used in 36% of the consulted works, allowing complex problems involving uncertainty in data behavior to be addressed. Also, in 70% of the works consulted, heuristic models are used to solve design and distribution problems in agro-chains, and the remaining 30% require the use of metaheuristics because they require solving problems with multiple responses given the complexity of the data. Mathematical modeling has become a very useful tool for solving latent problems in agro-chains, it facilitates data processing and complex decision-making, mainly during chain design, product supply and control of costs, delivery times and environmental impacts, among other important variables

Regional Tourism Organisations in New Zealand from 1980 to 2005: Process of Transition and Change

This thesis is a historical case study tracing the establishment and evolution of Regional Tourism Organisations (RTOs) in New Zealand. It describes their role, structure and functions and the political processes that have influenced how they have operated and changed from 1980 to 2005. RTOs are examined in the context of government policies, local and national politics and tourism private and public sector relationships. RTOs were central to many of the key recommendations of the New Zealand Tourism Strategy 2010 (NZTS 2010) released in 2001. The NZTS 2010 attempted to address a range of tourism policy gaps created by a policy vacuum in the 1990s whereby the public and private tourism sectors focused mainly on international marketing. This strategy shaped government policy during this decade. The research findings show that although public and private sector institutional arrangements impacting on RTOs have changed, there remains, as in the past, no uniformity in their role, structure, functions and their future financial and political viability remains insecure. The NZTS 2010 raised destination management and its alignment with destination marketing as a major policy issue that needed to be addressed in the decade leading up to 2010 with RTOs having a pivotal role. A generic regional destination management model is presented. Structures and processes incorporated into this model include: a national destination management tourism policy; support for tourism by local government at the national level; a well defined destination management team; community collaboration; and tourism being integrated into the wider planning processes of local government. The model identified requisite building blocks to support regional destination management such as: the provision of staff and financial resources for regional tourism; the building of a high tourism profile in the community; the availability of statistics and research data at the regional level; local government planners acknowledging the impacts of tourism; and the existence of a legal mandate for tourism at the regional and/or local government level. When applying this model to the New Zealand context, it was found that a number of the structures and processes required for effective regional destination management were lacking, such as regional statistics and research data, staffing and financial resources for both RTOs and local government, the ability of council planners to understand and integrate tourism into the wider planning processes and a legislative mandate for tourism. The thesis concluded that a vacuum remains in the alignment of destination marketing and management. The historical and political processes of RTO change were also examined in the context of chaos and complexity theory. Chaos and complexity theory provided a complementary and different means to view change. This thesis also presented the opportunity to reflect upon the research process which led to the adoption of a multi-paradigmatic and bricoleur research methodology. Further reflexivity and reflection towards the end of the research process articulated ontological and epistemological philosophical investigations that underlay the multi-paradigmatic approach. A model is presented emphasising that a multi-paradigmatic research approach rests on ultimate reality (metaphysics) which informs the ontology. The model then highlights that ontology precedes and directs epistemology and that both inform the multi-paradigmatic research framework

The 45th Australasian Universities Building Education Association Conference: Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment, Conference Proceedings, 23 - 25 November 2022, Western Sydney University, Kingswood Campus, Sydney, Australia

This is the proceedings of the 45th Australasian Universities Building Education Association (AUBEA) conference which will be hosted by Western Sydney University in November 2022. The conference is organised by the School of Engineering, Design, and Built Environment in collaboration with the Centre for Smart Modern Construction, Western Sydney University. This year’s conference theme is “Global Challenges in a Disrupted World: Smart, Sustainable and Resilient Approaches in the Built Environment”, and expects to publish over a hundred double-blind peer review papers under the proceedings