Managing offshore multi-use settings: Use of conceptual mapping to reduce uncertainty of co-locating seaweed aquaculture and wind farms.

The offshore Multi-use Setting (MUS) is a concept that aims to co-locate marine industrial activities, including wind farms and aquaculture. MUS is considered an innovative approach to promoting efficiency in space and resource use whilst contributing global policy priorities. However, the impacts of MUS development across social, economic, and environmental domains are uncertain, hindering the commercialisation of the concept. In this study, we initially demonstrate the potential consequences of co-locating seaweed aquaculture and a wind farm as a step towards MUS. Using a hypothetical case study and modified Delphi methodology, 14 subject matter experts predicted potential outcomes across social and environmental objectives. Five Cognitive maps and impact tables of 58 potential consequences were generated based on experts' perspective on co-locating seaweed aquaculture and a wind farm. The findings highlight the potential to exasperate pressures in the area, including those already attributed to wind farm operations, such as species mortality and stakeholder conflict. However, it may also enhance social-ecological conditions, such as resource provisioning and promoting habitat functionality in the region, through the addition of seaweed aquaculture. The cognitive maps demonstrate the complexity of managing MUS implementation, where high degree of variability and uncertainty about the outcomes is present. The findings of this study provide the vital entry point to performing further integrative assessment and modelling approaches, such as probabilistic analysis and simulations, in support of MUS decision-making. The research also strongly recommends alternative strategies in the pursuit of combining seaweed production and wind farms to avoid significant financial (among many other) trade-offs and risks. More broadly, we have found that our approach's ability to visually represent a complex situation while considering multiple objectives could be immensely valuable for other bioeconomy innovations or nature-based solutions. It helps mitigate the potential for expensive investments without a comprehensive evaluation of the associated risks and negative impacts, as necessitated by the principles of sustainability in decision-making.

Evaluating natural capital performance of urban development through system dynamics: A case study from London.

Natural capital plays a central role in urban functioning, reducing flooding, mitigating urban heat island effects, reducing air pollution, and improving urban biodiversity through provision of habitat space. There is also evidence on the role played by blue and green space in improving physical and mental health, reducing the burden on the health care service. Yet from an urban planning and development view, natural capital may be considered a nice to have, but not essential element of urban design; taking up valuable space which could otherwise be used for traditional built environment uses. While urban natural capital is largely recognised as a positive element, its benefits are difficult to measure both in space and time, making its inclusion in urban (re)development difficult to justify. Here, using a London case study and information provided by key stakeholders, we present a system dynamics (SD) modelling framework to assess the natural capital performance of development and aid design evaluation. A headline indicator: Natural Space Performance, is used to evaluate the capacity of natural space to provide ecosystem services, providing a semi-quantitative measure of system wide impacts of change within a combined natural, built and social system. We demonstrate the capacity of the model to explore how combined or individual changes in development design can affect natural capital and the provision of ecosystem services, for example, biodiversity or flood risk. By evaluating natural capital and ecosystem services over time, greater justification for their inclusion in planning and development can be derived, providing support for increased blue and green space within cities, improving urban sustainability and enhancing quality of life. Furthermore, the application of a SD approach captures key interactions between variables over time, showing system evolution while highlighting intervention opportunities.

Research Culture and Reproducibility.

There is ongoing debate regarding the robustness and credibility of published scientific research. We argue that these issues stem from two broad causal mechanisms: the cognitive biases of researchers and the incentive structures within which researchers operate. The UK Reproducibility Network (UKRN) is working with researchers, institutions, funders, publishers, and other stakeholders to address these issues.

On the use of computer-assistance to facilitate systematic mapping.

The volume of published academic research is growing rapidly and this new era of "big literature" poses new challenges to evidence synthesis, pushing traditional, manual methods of evidence synthesis to their limits. New technology developments, including machine learning, are likely to provide solutions to the problem of information overload and allow scaling of systematic maps to large and even vast literatures. In this paper, we outline how systematic maps lend themselves well to automation and computer-assistance. We believe that it is a major priority to consolidate efforts to develop and validate efficient, rigorous and robust applications of these novel technologies, ensuring the challenges of big literature do not prevent the future production of systematic maps.

A Horizon Scan of Emerging Issues for Global Conservation in 2019.

We present the results of our tenth annual horizon scan. We identified 15 emerging priority topics that may have major positive or negative effects on the future conservation of global biodiversity, but currently have low awareness within the conservation community. We hope to increase research and policy attention on these areas, improving the capacity of the community to mitigate impacts of potentially negative issues, and maximise the benefits of issues that provide opportunities. Topics include advances in crop breeding, which may affect insects and land use; manipulations of natural water flows and weather systems on the Tibetan Plateau; release of carbon and mercury from melting polar ice and thawing permafrost; new funding schemes and regulations; and land-use changes across Indo-Malaysia.

Including non-public data and studies in systematic reviews and systematic maps.

Systematic reviews and maps should be based on the best available evidence, and reviewers should make all reasonable efforts to source and include potentially relevant studies. However, reviewers may not be able to consider all existing evidence, since some data and studies may not be publicly available. Including non-public studies in reviews provides a valuable opportunity to increase systematic review/map comprehensiveness, potentially mitigating negative impacts of publication bias. Studies may be non-public for many reasons: some may still be in the process of being published (publication can take a long time); some may not be published due to author/publisher restrictions; publication bias may make it difficult to publish non-significant or negative results. Here, we consider what forms these non-public studies may take and the implications of including them in systematic reviews and maps. Reviewers should carefully consider the advantages and disadvantages of including non-public studies, weighing risks of bias against benefits of increased comprehensiveness. As with all systematic reviews and maps, reviewers must be transparent about methods used to obtain data and avoid risks of bias in their synthesis. We make tentative suggestions for reviewers in situations where non-public data may be present in an evidence base.