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1. Biodiversity loss in European agricultural landscapes is progressing rapidly despite a growing number of conservation efforts.Oneof the reasons for this is that farmers do not have enough decision-making power and do not receive adequate advice to tailor conservation measures to local conditions and regional biodiversity targets. 2. In this paper, we therefore address the potential and practical implementation of co-designing conservation measures through close collaboration between farmers and other stakeholders (e.g. other practitioners, conservation experts, agricultural advisors, scientists and policymakers). 3. Based on interviews with four researchers from ongoing European co-design - projects, one national and one European farmers’ organizations, we discuss the challenges and provide recommendations for co-design in the context of biodiversity conservation in agricultural landscapes. 4. Our aim is to reach scientists, practitioners and local decision makers working on innovative and locally adapted conservation efforts.

Discerning the relationship between urban structure and function is crucial for sustainable city planning and requires examination of how components in urban systems are organized in three-dimensional space. The Structure of Urban Landscape (STURLA) classification accounts for the compositional complexity of urban landcover structures including the built and natural environment. Building on previous research, we develop a STURLA classification for Philadelphia, PA and study the relationship between urban structure and land surface temperature. We evaluate the results in Philadelphia as compared to previous case studies in Berlin, Germany and New York City, United States. In Philadelphia, STURLA classes hosted ST that were unique and significantly different as compared to all other classes. We find a similar distribution of STURLA class composition across the three cities, though NYC and Berlin showed strong correlation with each other but not with Philadelphia. Our research highlights the use of STURLA classification to capture a physical property of the urban landscape., Peer Reviewed

Understanding the relationship between urban structure and ecological function - or environmental performance - is important for the planning of sustainable cities, and requires examination of how components in urban systems are organized. In this paper, we develop a Structure of Urban Landscape (STURLA) classification, identifying common compositions of urban components using Berlin, Germany as a case study. We compute the surface temperature corresponding to each classification grid cell, and perform within-cell and neighborhood analysis for the most common composite classes in Berlin. We found that with-class composition and neighborhood composition as well as the interaction between them drive surface temperature. Our findings suggest that the spatial organization of urban components is important in determining the surface temperature and that specific combinations, such as low-rise buildings surrounded by neighborhood trees, or mid-rise buildings surrounded by high-rise buildings, compound to create a cooling effect. These findings are important for developing an understanding of how urban planning can harness structure-function relationships and improve urban sustainability., Peer Reviewed

Die hier vorliegende Studie stellt einen neuen Stadtstrukturklassifikationsansatz vor. Hierzu werden Informationen zu Landbedeckung und Gebäudehöhe genutzt. Ziel der Studie ist es, eine internationale Vergleichbarkeit von Analysen der Beziehung zwischen Stadtstruktur und ökologischer Funktion zu erreichen und ein Bezugssystem zu entwickeln, was es ermöglicht, ökologische Prozesse und Muster als Resultat urbaner Landbedeckungsmuster zu analysieren. Wir haben die Klassifikation an zwei sehr unterschiedlichen Schauplätzen getestet: Im kontinentalen Berlin und in der Küstenstadt New York City. Als ökologischer Referenz-Indikator wurden Landsat- Oberflächentemperaturaufnahmen verwendet und für beide Städte verglichen, welcher Zusammenhang zwischen Stadtstruktur(-komposit) und Temperatur besteht. Die Ergebnisse zeigen, dass beide Städte viele Strukturklassen teilen und diese ähnliche Trends im Hinblick auf die Oberflächentemperatur beschreiben, trotz der erheblichen Unterschiede in Klima und Struktur von Berlin und New York. Es zeigt sich, dass etwa 68 % Berlins und 79 % von New York City von denselben 15 urbanen Strukturklassen beschrieben werden können. Die Ergebnisse zeigen auch, dass gemeinsame Strukturklassen ähnliche Temperaturmuster aufweisen und sich unser neues Bezugssystem der Stadtstrukturklassifikation auf sehr verschiedene Stadttypen anwenden lässt. Die Ergebnisse der neuen Klassifikation zeigen außerdem, den großen Einfluss von Gewässern auf die Temperaturregulation in Städten. Strukturklassen, welche Wasser beinhalten, weisen die niedrigsten Oberflächentemperaturen auf, was auf einen positiven Ausgleichseffekt von Wasseroberflächen zu hohen Lufttemperaturen hinweist und daher für Stadtplanung und Landmanagement äußerst wichtig ist, gerade in Zeiten zunehmender Hitzewellen und Sommertrockenheit.

Although a number of comprehensive reviewshave examined global ecosystem services (ES), few havefocused on studies that assess urban ecosystem services(UES). Given that more than half of the world’s populationlives in cities, understanding the dualism of the provisionof and need for UES is of critical importance. Which UESare the focus of research, and what types of urban land useare examined? Are models or decision support systemsused to assess the provision of UES? Are trade-offs con-sidered? Do studies of UES engage stakeholders? Toaddress these questions, we analyzed 217 papers derivedfrom an ISI Web of Knowledge search using a set ofstandardized criteria. The results indicate that most UESstudies have been undertaken in Europe, North America,and China, at city scale. Assessment methods involve bio-physical models, Geographical Information Systems, andvaluation, but few study findings have been implementedas land use policy., QC 20161212