Spatial optimization for land use allocation: accounting for sustainability concerns

Land-use allocation has long been an important area of research in regional science. Land-use patterns are fundamental to the functions of the biosphere, creating interactions that have substantial impacts on the environment. The spatial arrangement of land uses therefore has implications for activity and travel within a region. Balancing development, economic growth, social interaction, and the protection of the natural environment is at the heart of long-term sustainability. Since land-use patterns are spatially explicit in nature, planning and management necessarily must integrate geographical information system and spatial optimization in meaningful ways if efficiency goals and objectives are to be achieved. This article reviews spatial optimization approaches that have been relied upon to support land-use planning. Characteristics of sustainable land use, particularly compactness, contiguity, and compatibility, are discussed and how spatial optimization techniques have addressed these characteristics are detailed. In particular, objectives and constraints in spatial optimization approaches are examined

Bridging adaptive management and reinforcement learning for more robust decisions

From out-competing grandmasters in chess to informing high-stakes healthcare decisions, emerging methods from artificial intelligence are increasingly capable of making complex and strategic decisions in diverse, high-dimensional, and uncertain situations. But can these methods help us devise robust strategies for managing environmental systems under great uncertainty? Here we explore how reinforcement learning, a subfield of artificial intelligence, approaches decision problems through a lens similar to adaptive environmental management: learning through experience to gradually improve decisions with updated knowledge. We review where reinforcement learning (RL) holds promise for improving evidence-informed adaptive management decisions even when classical optimization methods are intractable. For example, model-free deep RL might help identify quantitative decision strategies even when models are nonidentifiable. Finally, we discuss technical and social issues that arise when applying reinforcement learning to adaptive management problems in the environmental domain. Our synthesis suggests that environmental management and computer science can learn from one another about the practices, promises, and perils of experience-based decision-making.Comment: In press at Philosophical Transactions of the Royal Society

Florida marine biotechnology: research, development and training capabilities to advance science and commerce

The level of activity and interest in “marine biotechnology” among Florida university faculty and allied laboratory scientists is reported in this document. The information will be used to (1) promote networking and collaboration in research and education, (2) inform industry of possible academic partners, (3) identify contacts interested in potential new sources of funding, and (4) assist development of funding for a statewide marine biotechnology research, training and development program. This document is the first of its kind. Institutions of higher learning were given the opportunity to contribute both an overview of campus capabilities and individual faculty Expressions of Scientific Interest. They are listed in the table of contents. (104pp.

Reframing conservation physiology to be more inclusive, integrative, relevant and forward-looking: reflections and a horizon scan

Applying physiological tools, knowledge and concepts to understand conservation problems (i.e. conservation physiology) has become common place and confers an ability to understand mechanistic processes, develop predictive models and identify cause-and-effect relationships. Conservation physiology is making contributions to conservation solutions; the number of 'success stories' is growing, but there remain unexplored opportunities for which conservation physiology shows immense promise and has the potential to contribute to major advances in protecting and restoring biodiversity. Here, we consider howconservation physiology has evolved with a focus on reframing the discipline to be more inclusive and integrative. Using a 'horizon scan', we further exploreways in which conservation physiology can be more relevant to pressing conservation issues of today (e.g. addressing the Sustainable Development Goals; delivering science to support the UN Decade on Ecosystem Restoration), as well as more forward-looking to inform emerging issues and policies for tomorrow. Our horizon scan provides evidence that, as the discipline of conservation physiology continues to mature, it provides a wealth of opportunities to promote integration, inclusivity and forward-thinking goals that contribute to achieving conservation gains. To advance environmenta lmanagement and ecosystem restoration, we need to ensure that the underlying science (such as that generated by conservation physiology) is relevant with accompanying messaging that is straightforward and accessible to end users

Reframing conservation physiology to be more inclusive, integrative, relevant and forward-looking: Reflections and a horizon scan

Applying physiological tools, knowledge and concepts to understand conservation problems (i.e. conservation physiology) has becomecommonplace and confers an ability to understand mechanistic processes,develop predictive models and identify cause-and-effect relationships. Conservation physiology is making contributions to conservation solutions; the number of \u27success stories\u27 is growing, but there remain unexplored opportunities for which conservation physiology shows immense promise and has the potential to contribute to major advances in protecting and restoring biodiversity. Here, we consider howconservation physiology has evolved with a focus on reframing the discipline to be more inclusive and integrative.Using a \u27horizon scan\u27,we further exploreways in which conservation physiology can be more relevant to pressing conservation issues of today (e.g. addressing the Sustainable Development Goals; delivering science to support the UN Decade on Ecosystem Restoration), aswell as more forward-looking to inform emerging issues and policies for tomorrow. Our horizon scan provides evidence that, as the discipline of conservation physiology continues to mature, it provides a wealth of opportunities to promote integration, inclusivity and forward-thinking goals that contribute to achieving conservation gains. To advance environmentalmanagementand ecosystemrestoration,we need to ensure that the underlying science (such as that generated by conservation physiology) is relevant with accompanying messaging that is straightforward and accessible to end users