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Stakeholders’ views on the creation of a Water Quality Digital Twin, for assessing the impacts of multiple stressors on standing and flowing freshwaters, were sought through an anonymous survey composed of closed and open questions. The work was funded as part of the UKSCAPE integration fund (https://ukscape. ceh.ac.uk/about ) and sought to co-develop a blueprint for a UKCEH water quality digital twin. Fifty-nine participants responded and provided a wealth of viewpoints, from academia, industry, regulators, and policy makers’ perspectives. In general, the catchment scale was considered the most feasible, useful, realistic, and deliverable scale for a Water Quality Digital Twin. Respondents considered the desired temporal scale to be dependent on the use envisaged for the digital twin. However, sub-daily or daily scales emerged as providing the most actionable knowledge if data were available and it was computationally feasible. Overall, there was consensus that nutrient concentrations were the most important determinands to include in a water quality digital twin (100% of respondents scoring these as one of their three most important determinand categories). However, several additional abiotic and biotic determinands were also scored highly, partly depending on the required use of the resultant digital twin.

Wetland bird species have been declining in population size worldwide as climate warming and land-use change affect their suitable habitats. We used species distribution models (SDMs) to predict changes in range dynamics for 64 non-passerine wetland birds breeding in Europe, including range size, position of centroid, and margins. We fitted the SDMs with data collected for the first European Breeding Bird Atlas (EBBA1) and climate and land-use data to predict distributional changes over a century (the 1970s–2070s). The predicted annual changes were then compared to observed annual changes in range size and range centroid over a time period of 30 years using data from the second European Breeding Bird Atlas (EBBA2). Our models successfully predicted ca. 75% of the 64 bird species to contract their breeding range in the future, while the remaining species (mostly southerly breeding species) were predicted to expand their breeding ranges northward. The northern margins of southerly species and southern margins of northerly species, both, predicted to shift northward. Predicted changes in range size and shifts in range centroids were broadly positively associated with the observed changes, although some species deviated markedly from the predictions. The predicted average shift in core distributions was ca. 5 km/year towards the north (5% Northeast, 45% North, and 40% Northwest), compared to a slower observed average shift of ca. 3.9 km/year. Predicted changes in range centroids were generally larger than observed changes, which suggests that bird distribution changes may lag behind environmental changes leading to "climate debt. We suggest that predictions of SDMs should be viewed as qualitative rather than quantitative outcomes, indicating that care should be taken concerning single species. Still, our results highlight the urgent need for management actions such as wetland creation and restoration to improve wetland birds' resilience to the expected environmental cha

Long-term population trends are considerable sources of information to set wildlife conservation priorities and to evaluate the performance of management actions. In addition, trends observed in functional groups (e.g., trophic guilds) can provide the foundation to test specific hypotheses about the drivers of the observed population dynamics. The aims of this study were to assess population trends of breeding birds in Lombardy (N Italy) from 1992 to 2019 and to explore the relationships between trends and species sharing similar ecological and life history traits. Trends were quantified and tested for significance by weighted linear regression models and using yearly population indices (median and 95% confidence interval) predicted through generalized additive models. Results showed that 45% of the species increased, 24% decreased, and 31% showed non-significant trends. Life history traits analyses revealed a general decrease in migrants of species with short incubation periods and of species with high annual fecundity. Ecological traits analyses showed that plant-eaters and species feeding on invertebrates, farmland birds, and ground-nesters declined, while woodland birds increased. Further studies should focus on the investigation of the relationship between long-term trends and species traits at large spatial scales, and on quantifying the effects of specific drivers across multiple functional groups.

Diese Festschrift erscheint anlässlich des 65. Geburtstages von Harm-Peer Zimmermann – Professor und Lehrstuhlinhaber für Populäre Literaturen und Medien am Institut für Sozialanthropologie und Empirische Kulturwissenschaft – Populäre Kulturen – der Universität Zürich. Sie vereint Beiträge von Weggefährt*innen, Kolleg*innen und Freund*innen aus den Themengebieten Kulturtheorie, Altersforschung, Erzählforschung und Populärkulturforschung. Die Beiträge stehen in unterschiedlicher Weise im Zusammenhang mit dem Denken und Forschen Harm-Peer Zimmermanns. In ihrem Zusammenspiel bringen sie eine epistemische Haltung zum Ausdruck, die Zimmermanns Wirken grundlegend prägt: seine analytische Fantasie, die immer wieder originelle Zugänge zur Empirischen Kulturwissenschaft ermöglicht.

Several model inter-comparison projects (MIPs) have been carried out recently by the climate, hydrological, agricultural and other modelling communities to quantify modelling uncertainties and improve modelling systems. Here we focus on MIP design for large-scale water quality models. Water quality MIPs can be useful to improve our understanding of pollution problems and facilitate the development of harmonized estimates of current and future water quality. This can provide new opportunities for assessing robustness in estimates of water quality hotspots and trends, improve understanding of processes, pollution sources, water quality model uncertainties, and to identify priorities for water quality data collection and monitoring. Water quality MIP design should harmonize relevant model input datasets, use consistent spatial/temporal domains and resolutions, and similar output variables to improve understanding of water quality modelling uncertainties and provide harmonized water quality data that suit the needs of decision makers and other users.