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The terrestrial, freshwater and marine realms all provide essential ecosystem services in urban environments. However, the services provided by each realm are often considered independently, which ignores the synergies between them and risks underestimating the benefits derived collectively. Greater research collaboration across these realms, and an integrated approach to management decisions can help to support urban developments and restoration projects in maintaining or enhancing ecosystem services. The aim of this paper is to highlight the synergies and trade-offs among ecosystem services provided by each realm and to offer suggestions on how to improve current practice. We use case studies to illustrate the flow of services across realms. In our call to better integrate research and management across realms, we present a framework that provides a 6-step process for conducting collaborative research and management with an Australian perspective. Our framework considers unifying language, sharing, and understanding of desired outcomes, conducting cost-benefit analyses to minimise trade-offs, using multiple modes of communication for stakeholders, and applying research outcomes to inform regulation. It can be applied to improve collaboration among researchers, managers and planners from all realms, leading to strategic allocation of resources, increased protection of urban natural resources and improved environmental regulation with broad public support.

A workshop was held in Wageningen, The Netherlands, in September 2017 to collate data and literature on three aquatic ecosystem types (agricultural drainage ditches, urban floodplains, and urban estuaries), and develop a general framework for the assessment of multiple stressors on the structure and functioning of these systems. An assessment framework considering multiple stressors is crucial for our understanding of ecosystem responses within a multiply stressed environment, and to inform appropriate environmental management strategies. The framework consists of two components: (i) problem identification and (ii) impact assessment. Both assessments together proceed through the following steps: 1) ecosystem selection; 2) identification of stressors and quantification of their intensity; 3) identification of receptors or sensitive groups for each stressor; 4) identification of stressor-response relationships and their potential interactions; 5) construction of an ecological model that includes relevant functional groups and endpoints; 6) prediction of impacts of multiple stressors, 7) confirmation of these predictions with experimental and monitoring data, and 8) potential adjustment of the ecological model. Steps 7 and 8 allow the assessment to be adaptive and can be repeated until a satisfactory match between model predictions and experimental and monitoring data has been obtained. This paper is the preface of the MAEGA (Making Aquatic Ecosystems Great Again) special section that includes three associated papers which are also published in this volume, which present applications of the framework for each of the three aquatic systems.

A workshop was held in Wageningen, The Netherlands, in September 2017 to collate data and literature on three aquatic ecosystem types (agricultural drainage ditches, urban floodplains, and urban estuaries), and develop a general framework for the assessment of multiple stressors on the structure and functioning of these systems. An assessment framework considering multiple stressors is crucial for our understanding of ecosystem responses within a multiply stressed environment, and to inform appropriate environmental management strategies. The framework consists of two components: (i) problem identification and (ii) impact assessment. Both assessments together proceed through the following steps: 1) ecosystem selection; 2) identification of stressors and quantification of their intensity; 3) identification of receptors or sensitive groups for each stressor; 4) identification of stressor-response relationships and their potential interactions; 5) construction of an ecological model that includes relevant functional groups and endpoints; 6) prediction of impacts of multiple stressors, 7) confirmation of these predictions with experimental and monitoring data, and 8) potential adjustment of the ecological model. Steps 7 and 8 allow the assessment to be adaptive and can be repeated until a satisfactory match between model predictions and experimental and monitoring data has been obtained. This paper is the preface of the MAEGA (Making Aquatic Ecosystems Great Again) special section that includes three associated papers which are also published in this volume, which present applications of the framework for each of the three aquatic systems.

Urbanisation and climate change are pervasive stressors to natural ecosystems and have been linked to decreased biodiversity and ecological function. At the coastal fringe, intertidal rocky shores are threatened by urbanisation along shorelines and sea level rise, with the result that complex intertidal habitats are becoming rare and often replaced with simpler concrete structures. Communities that remain also experience altered light climates due to shading by engineered structures. To effectively manage and conserve urban intertidal ecosystems, we require a greater understanding of the drivers of diversity at micro- to macro scales. I begin by investigating the drivers of biodiversity on the small scale, where I was able to identify relationships between rock pool physical characteristics and associated biota around Sydney Harbour. Maximum width and depth, volume and height on shore were important drivers of biodiversity, but effects varied among organisms (i.e. sessile vs. mobile taxa) and between inner and outer locations of the lower estuary. I also found that the structure within rock pools can influence species abundances. Microhabitats such as overhangs were important to support grazers and rare species. I then investigated the effect of another potential driver of biodiversity common in urban intertidal areas: shading by engineered structures. Using a manipulative experiment, I found that the effect of varying levels of shading can influence taxa in different ways. Whereas high light intensities promoted greater algal cover, low light intensities supported higher abundances of mobile taxa. Finally, I worked at a larger scale and used predictive modelling to assess potential habitat loss of intertidal rocky shores due to sea level rise. I found that rocky shore communities in the Sydney area are likely to lose substantial habitat and may be considered ‘near threatened’ (under one category of the IUCN communities listing criteria) under the predicted 11.2mm/y