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Heart transplantation from donation after circulatory death (DCD) donors has the potential to substantially increase overall heart transplant activity. The aim of this report is to review the first 8 y of our clinical heart transplant program at St Vincent's Hospital Sydney, to describe how our program has evolved and to report the impact that changes to our retrieval protocols have had on posttransplant outcomes. Since 2014, we have performed 74 DCD heart transplants from DCD donors utilizing a direct procurement protocol followed by normothermic machine perfusion. Changes to our retrieval protocol have resulted in a higher retrieval rate from DCD donors and fewer rejections of DCD hearts during normothermic machine perfusion. Compared with our previously reported early experience in the first 23 transplants, we have observed a significant reduction in the incidence of severe primary graft dysfunction from 35% (8/23) to 8% (4/51) in the subsequent 51 transplant recipients ( P < 0.01). The only withdrawal time interval significantly associated with severe primary graft dysfunction was the asystolic warm ischemic time: 15 (12-17) versus 13 (11-14) min ( P < 0.05). One- and 5-y survival of DCD heart transplant recipients was 94% and 88%, comparable to that of a contemporary cohort of donation after brain death recipients: 87 and 81% ( P -value was not significant). In conclusion, heart transplantation from DCD donors has become a major contributor to our overall transplant activity accounting for almost 30% of all transplants performed by our program in the last 2 y, with similar DCD and donation after brain death outcomes.

While held to be a means for climate change adaptation and mitigation, nature-based solutions (NbS) themselves are vulnerable to climate change. To find ways of compensating for this vulnerability we combine a focused literature review on how information technology has been used to strengthen positive social–ecological–technological feedback, with the development of a prototype decision-support tool. Guided by the literature review, the tool integrates recent advances in using globally available remote sensing data to elicit information on functional diversity and ecosystem service provisioning with information on human service demand and population vulnerability. When combined, these variables can inform climate change adaptation strategies grounded in local social–ecological realities. This type of integrated monitoring and packaging information to be actionable have potential to support NbS management and local knowledge building for context-tailored solutions to societal challenges in urban environments.

Urban forests as nature-based solutions (UF-NBS) are important tools for climate change adaptation and sustainable development. However, achieving both effective and sustainable UF-NBS solutions requires diverse knowledge. This includes knowledge on UF-NBS implementation, on the assessment of their environmental impacts in diverse spatial contexts, and on their management for the long-term safeguarding of delivered benefits. A successful integration of such bodies of knowledge demands a systematic understanding of UF-NBS. To achieve such an understanding, this paper presents a conceptual UF-NBS model obtained through a semantic, trait-based modelling approach. This conceptual model is subsequently implemented as an extendible, re-usable and interoperable ontology. In so doing, a formal, trait-based vocabulary on UF-NBS is created, that allows expressing spatial, morphological, physical, functional, and institutional UF-NBS properties for their typification and a subsequent integration of further knowledge and data. Thereby, ways forward are opened for a more systematic UF-NBS impact assessment, management, and decision-making.

The most common approach to assessing natural hazard risk is investigating the willingness to pay in the presence or absence of such risk. In this work, we propose a new, machine-learning-based, indirect approach to the problem, i.e. through residential-choice modelling. Especially in urban environments, exposure and vulnerability are highly dynamic risk components, both being shaped by a complex and continuous reorganization and redistribution of assets within the urban space, including the (re-)location of urban dwellers. By modelling residential-choice behaviour in the city of Leipzig, Germany, we seek to examine how exposure and vulnerabilities are shaped by the residential-location-choice process. The proposed approach reveals hot spots and cold spots of residential choice for distinct socioeconomic groups exhibiting heterogeneous preferences. We discuss the relationship between observed patterns and disaster risk through the lens of exposure and vulnerability, as well as links to urban planning, and explore how the proposed methodology may contribute to predicting future trends in exposure, vulnerability, and risk through this analytical focus. Avenues for future research include the operational strengthening of these linkages for more effective disaster risk management.

The COVID-19 pandemic has shown that an immediate access to relevant information is key for timely interventions and forming of public opinion and discourse. In this regard, dashboards present themselves as invaluable tools for the democratization of data and for the creation of accessible evidence bases. Building on this momentum, it is proposed to integrate interactive means such as dashboards into academic literature review synthesis, in order to support the summarization, narration, and dissemination of findings, and furthermore, to increase transparency and support the transferability and comparability of findings. Exemplified for a systematic literature review on urban forests as nature-based solutions, Key functionalities, requirements and design considerations for the development of dashboards for use in academic literature reviews synthesis are identified. An application architecture that embeds dashboard development into an R workflow is presented, with emphasis on the steps needed to transform the data collected during the review process into a structured form. Technical and methodological means for the actual dashboard implementation are highlighted, considering the identified key functionalities and requirements.

Remote sensing has evolved to become a key tool for various fields of environmental analysis, thus actively informing policy across areas and domains. To evaluate the degree to which remote sensing is contributing to the science of ecologically-oriented urban planning, we carried out a systematic literature review using the SCOPUS database, searching for articles integrating knowledge in urban planning, remote sensing and ecology. We reviewed 186 articles, analysing various issues in urban environments worldwide. Key findings include that the level of integration between the three disciplines is limited, with only 12% of the papers fully integrating ecology, remote sensing and planning while 24% of the studies use specific methods from one domain only. The vast majority of studies is oriented towards contributing to the knowledge base or monitoring the impacts of existing policies. Few studies are directly policy relevant by either contributing to direct issues in planning and making specific design suggestions or evaluations. The accessibility of the scientific findings remains limited, as the majority of journal articles are not open access and proprietary software and data are frequently used. To overcome these issues, we suggest three future avenues for science as well as three potential entry points for remote sensing into applied urban planning. By doing so, remote sensing data could become a vital tool actively contributing to policies, civil engagement and concrete planning measures by providing independent and cost effective environmental analyses.

Birds respond strongly to vegetation structure and composition, yet typical species distribution models (SDMs) that incorporate Earth observation (EO) data use discrete land-use/cover data to model habitat suitability. Since this neglects factors of internal spatial composition and heterogeneity of EO data, we suggest a novel scheme deriving continuous indicators of vegetation heterogeneity from high-resolution EO data.The deployed concepts encompass vegetation fractions for determining vegetation density and spectral traits for the quantification of vegetation heterogeneity. Both indicators are derived from RapidEye data, thus featuring a continuous spatial resolution of 6.5 m. Using these indicators as predictors, we model breeding bird habitats using a random forest (RF) classifier for the city of Leipzig, Germany using a single EO image.SDMs are trained for the breeding sites of 44 urban bird species, featuring medium to very high accuracies (59–90%). Analysing similarities between the models regarding variable importance of single predictors allows species groups to be determined based on their preferences and dependencies regarding the amount of vegetation and its spatial and structural heterogeneity. When combining the SDMs, models of urban bird species richness can be derived.The combination of high-resolution EO data paired with the RF machine learning technique creates very detailed insights into the ecology of the urban avifauna, opening up opportunities of optimising greenspace management schemes or urban development in densifying cities concerning overall bird species richness or single species under threat of local extinction.

Improving Green Space Accessibility (GSA) in public spaces in cities and communities reduces disparities among people and fosters sustainable development. However, traditional mapping approaches in cities neglects green spaces in the hinterland and treats the geographical distance as a fixed quantity. This limits conclusions about spatial inequalities in Green Space Accessibility and influences the evaluation of current policies which seek to ensure a high local recreation quality for all residents irrespective of any administrative boundaries.This paper aims to detect spatial inequalities in Green Space Accessibility for urban green (UG) and non-urban green (NUG) across Europe, and reveals the role of the rural-urban interface (RUI). The approach taken here calculates Green Space Accessibility across administrative boundaries, which enables distance to be treated as a flexible variable. The results highlight major inequalities between and within regions and countries. However, unequal Green Space Accessibility for urban green is compensated in most countries by more equal one for non-urban green, which is of particular relevance in the rural-urban interface.The combined perspective on both relative and absolute Green Space Accessibility suggests a new perspective on the rural-urban interface that is critical for equitable green infrastructure planning. This paper concludes that, in order to bridge the urban-rural-divide, monitoring and planning tools that examine the arbitrary use of thresholds and existing administrative boundaries are needed.

Context Urban densification has been argued to increase the contrast between built up and open green space. This contrast may offer a starting point for assessing the extent and magnitude of the positive influences urban green infrastructure is expected to have on its surroundings. Objectives Drawing on insights from landscape ecology and urban geography, this exploratory study investigates how the combined properties of green and grey urban infrastructures determine the influence of urban green infrastructure on the overall quality of the urban landscape. Methods This article uses distance rise-or-decay functions to describe how receptive different land uses are to the influence of neighbouring green spaces, and does this based on integrated information on urban morphology, land surface temperature and habitat use by breeding birds. Results Our results show how green space has a non-linear and declining cooling influence on adjacent urban land uses, extending up to 300-400 m in densely built up areas and up to 500 m in low density areas. Further, we found a statistically significant declining impact of green space on bird species richness up to 500 m outside its boundaries. Conclusions Our focus on land use combinations and interrelations paves the way for a number of new joint landscape level assessments of direct and indirect accessibility to different ecosystem services. Our early results reinforce the challenging need to retain more green space in densely built up part of cities.

Nature-based solutions (NBS) for mitigating climate change are gaining popularity. The number of NBS is increasing, but research gaps still exist at the governance level. The objectives of this paper are (i) to give an overview of the implemented NBS for flood risk management and mitigation in Germany, (ii) to identify governance models that are applied, and (iii) to explore the differences between these models. The results of a hierarchical clustering procedure and a qualitative analysis show that while no one-size-fits-all governance model exists, polycentricism is an important commonality between the projects. The study concludes by highlighting the need for further research on traditional governance model reconversion and paradigm changes. We expect the findings to identify what has worked in the past, as well as what is important for the implementation of NBS for flood risk management in future projects.

Residential choice behaviour is a complex process underpinned by both housing market restrictions and individual preferences, which are partly conscious and partly tacit knowledge. Due to several limitations, common survey methods cannot sufficiently tap into such tacit knowledge. Thus, this paper introduces an advanced knowledge elicitation process called SilverKnETs and combines it with data mining using random forests to elicit and operationalize this type of knowledge. For the application case of the city of Leipzig, Germany, our findings indicate that rent, location and type of housing form the three predictors strongly influencing the decision making in residential choices. Other explanatory variables appear to have a much lower influence. Random forests have proven to be a promising tool for the prediction of residential choices, although the design and scope of the study govern the explanatory power of these models.

Over the 20th century, urbanization has substantially shaped the surface of Earth. With population rapidly shifting from rural locations towards the cities, urban areas have dramatically expanded on a global scale and represent crystallization points of social, cultural and economic assets and activities. This trend is estimated to persist for the next decades, and particularly the developing countries are expected to face rapid urban growth. The management of this growth will require good governance strategies and planning. By threatening the livelihoods, assets and health as foundations of human activities, another major global change contributor, climate change, became an equally important concern of stakeholders. Based on the climate trends observed over the 20th century, and a spatially explicit model of urbanization, this paper investigates the impacts of climate change in relation to different stages of development of urban areas, thus evolving a more integrated perspective on both processes. As a result, an integrative measure of climate change trends and impacts is proposed and estimated for urban areas worldwide. We show that those areas facing major urban growth are to a large extent also hotspots of climate change. Since most of these hotspots are located in the Global South, we emphasize the need for stakeholders to co-manage both drivers of global change. The presented integrative perspective is seen as a starting point to foster such co-management, and furthermore as a means to facilitate communication and knowledge exchange on climate change impacts.

A number of concepts exist regarding how urbanization can be described as a process. Understanding this process that affects billions of people and its future development in a spatial manner is imperative to address related issues such as human quality of life. In the focus of spatially explicit studies on urbanization is typically a city, a particular urban region, an agglomeration. However, gaps remain in spatially explicit global models. This paper addresses that issue by examining the spatial dynamics of urban areas over time, for a full coverage of the world. The presented model identifies past, present and potential future hotspots of urbanization as a function of an urban area's spatial variation and age, whose relation could be depicted both as a proxy and as a path of urban development.

Land-use planning is an important determinant for green space policy in cities. It defines land covers and hence the structure and function of urban ecosystems and the benefits these provide to humans, such as air purification, urban cooling, runoff mitigation, and recreation. The ecosystem service approach has helped to attract policy attention to these benefits but the concept remains poorly implemented in urban policy and governance. To address this gap, we advance a framework to bridge ecosystem services into policy processes through Multi-Criteria Decision Analysis (MCDA) as decision support tool. The paper is organized in three main parts. First, we conduct a systematic literature review to assess state-of-the-art knowledge on ecosystem service assessments through MCDA. Next, we build on insights from the literature review to develop the ‘ecosystem services policy-cycle’, a conceptual framework that merges the ‘ecosystem service cascade’ and ‘policy cycle’ models to reinforce the link between ecosystem service assessments and practical applications in urban policy and governance. Next, we illustrate the applicability of the proposed framework along an example about conflicting interests on land use and green space planning following the closure of the Airport Tempelhof in Berlin, Germany. Our results highlight the scope of MCDA as a decision support tool for integrating ecosystem service assessments in green space governance. We discuss advantages and disadvantages of different methodological choices in the use of MCDA in ecosystem service assessments and note that a key strength of this tool in informing green space policies lies in its capacity to accommodate conflicting stakeholder perspectives and to address trade-offs between ecological, social and economic values.