WSL Extremes Research Program: Building Resilience for an Uncertain Future ¶

This paper focuses on the critical role of integrative leadership in inter- and transdisciplinary (ITD) research programs. ITD programs have become one of academia's responses to address contemporary sustainability challenges. Fulfilling the promise of such programs is extraordinarily challenging for all involved participants, but especially for program leaders who have to ensure that the perspectives of the involved program participants become truly integrated and that final and useful synthesis outputs are created. We present six core leadership challenges and respective strategies to address them to advance integration within ITD programs. These challenges include (1) mastering complexity and ambiguity, (2) advancing decision-making with lateral leadership, (3) ensuring responsibility and accountability, (4) setting program boundaries, (5) selecting suitable projects, and (6) dealing with misconceptions. We derived these challenges and respective strategies from both leading and studying in-depth three ITD programs focusing on sustainability issues in Switzerland. With this paper, we intend to promote awareness about the range of leadership challenges in ITD programs and provide actionable knowledge, which can support in particular fellow and future leaders, but also funders and heads of research institutions in their efforts to realize the integrative potential of such programs.

Mountain forests provide not only wood as a raw material but also numerous ecosystem services, such as protection against natural hazards, recreation and carbon sequestration, and they are important hosts for biodiversity. To manage these forests efficiently and in a target-oriented manner, both forest management planning and efficient harvesting operations are required. However, in most cases these two aspects are handled independently from each other. To link planning with forest operations, it is essential to divide forests into smaller areas with characteristics that are as homogeneous as possible, so-called forest management units (FMUs). The goal is that each FMU has self-contained fine access (e.g. skid roads, cable roads), and that the FMUs can be managed and planned independently. The aim of this study was to develop a spatial optimisation model that automatically identifies FMUs. The optimisation has three goals: [I] FMUs should be as compact as possible (spatially contiguous as the best case); [II] forest management should be technically and operationally coordinated within an FMU; and [III] FMUs should be as homogeneous as possible, for example regarding site properties, ecosystem service provided, and administrative affiliation. Results showed that our presented spatial optimisation model is a capable method for automatically identifying FMUs. The approach used to set up the model based on a p-median problem formulation (mixed integer linear programming) led to clearly comprehensible solutions that can be achieved in a reasonable computation time. Three solving strategies for successful computation implementation are described. Although the raw results must be reviewed by experts, they facilitate the planning process. More scenarios can be evaluated compared with the classical manual planning approach, ultimately leading to higher-quality solutions.

Angesichts zunehmender Störungsrisiken und anderer Auswirkungen des Klimawandels sind proaktive Bewirtschaftungsansätze und eine effiziente Bewältigung von Störungen in Gebirgswäldern von entscheidender Bedeutung. Eine gute Zusammenarbeit zwischen Forschung und Praxis ist entscheidend, um diese Herausforderungen zu bewältigen. Wir präsentieren zwei Projekte, in denen dies bereits umgesetzt wird: earlyBEETLE und MountEx. Das earlyBEETLE-Projekt konzentriert sich auf die Früherkennung und Bewältigung von Buchdruckerschäden, während das MountEx-Projekt darauf abzielt, Leitlinien für die Bewirtschaftung von Gebirgswäldern unter dem Einfluss extremer Störungen zu entwickeln. Beide Projekte kombinieren sich ergänzende methodische Ansätze und nutzen Synergien zwischen Forschung und Praxis im Hinblick auf die gemeinsame Erarbeitung von umfassenden Lösungen für das Gebirgswaldmanagement in Zeiten des globalen Wandels. Wichtige Erfolgsfaktoren für eine erfolgreiche Zusammenarbeit zwischen Forschung und Praxis sind, dass Praxispartner bereits in einer frühen Phase in die Projektplanung einbezogen werden und dass die Zusammenarbeit sowohl seitens der Forschungs- wie auch der Praxispartner als Chance und Mehrwert gesehen wird.

Mountain forests offer a range of ecosystem services and products. Under increasing disturbance risks and other climate change impacts, proactive management approaches and efficient management of disturbances in mountain forests are crucial. In this context, a good collaboration between research and practice is crucial to address these challenges. Two projects that aim to do this are presented as examples: earlyBEETLE and MountEx. The earlyBEETLE project focuses on early detection and an management of bark beetle damage, while the MountEx project aims to develop guidelines for the management of mountain forests under the influence of extreme disturbances. By combining different data and methods, the two projects demonstrate the increasing recognition of the potential synergies between research and practice and the promising development towards comprehensive solutions for mountain forest management under global change. Important factors for successful cooperation between research and practice are that practice partners are involved in project planning at an early stage and that cooperation is seen as added value by both research and practice partners.

Gebirgswälder bieten ein breites Spektrum an Waldleistungen, stehen aber aufgrund des globalen Wandels vor grossen Herausforderungen. Aufgrund zunehmender natürlicher Störungen sind gute lanungsgrundlagen zur Priorisierung der Bewirtschaftung von fichtendominierten Gebirgswäldern besonders wichtig. Dafür erstellen wir flächendeckende, interaktive Karten zur Waldstruktur und Störungsanfälligkeit der Wälder. Die Karten repräsentieren den aktuellen Waldzustand und weisen die Anfälligkeit der Schutzwälder gegen verschiedene Störungen aus. Kombiniert mit Informationen zur Schutzfunktion und Grundlagen bezüglich waldbaulicher und erntetechnischer Optimierung, dienen sie der Priorisierung von forstlichen Eingriffen in fichtendominierten Gebirgswäldern.

Across the globe, there has been an increasing interest in improving the predictability of subseasonal hydrometeorological forecasts, as they play a valuable role in medium- to long-term planning in many sectors, such as agriculture, navigation, hydropower, and emergency management. However, these forecasts still have very limited skill at the monthly time scale; hence, this study explores the possibilities for improving forecasts through different pre- and postprocessing techniques at the interface with a Precipitationn–Runoff–Evapotranspiration Hydrological Response Unit Model (PREVAH). Specifically, this research aims to assess the benefit of European weather regime (WR) data within a hybrid forecasting setup, a combination of a traditional hydrological model and a machine learning (ML) algorithm, to improve the performance of subseasonal hydrometeorological forecasts in Switzerland. The WR data contain information about the large-scale atmospheric circulation in the North Atlantic–European region, and thus allow the hydrological model to exploit potential flow-dependent predictability. Four hydrological variables are investigated: total runoff, baseflow, soil moisture, and snowmelt. The improvements in the forecasts achieved with the pre- and postprocessing techniques vary with catchments, lead times, and variables. Adding WR data has clear benefits, but these benefits are not consistent across the study area or among the variables. The usefulness of WR data is generally observed for longer lead times, e.g., beyond the third week. Furthermore, a multimodel approach is applied to determine the “best practice” for each catchment and improve forecast skill over the entire study area. This study highlights the potential and limitations of using WR information to improve subseasonal hydrometeorological forecasts in a hybrid forecasting system in an operational mode.

Accelerating glacier melt rates were observed during the last decades. Substantial ice loss occurs particularly during heat waves that are expected to intensify in the future. Because measuring and modelling glacier mass balance on a daily scale remains challenging, short-term mass balance variations, including extreme melt events, are poorly captured. Here, we present a novel approach based on computer-vision techniques for automatically determining daily mass balance variations at the local scale. The approach is based on the automated recognition of colour-taped ablation stakes from camera images and is tested and validated at six stations installed on three Alpine glaciers during the summers of 2019-2022. Our approach produces daily mass balance with an uncertainty of ±0.81 cm w.e. d-1, which is about half of the accuracy obtained from visual readouts. The automatically retrieved daily mass balances at the six sites were compared to average daily mass balances over the last decade derived from seasonal in situ observations to detect and assess extreme melt events. This allows analysing the impact that the summer heat waves which occurred in 2022 had on glacier melt. Our results indicate 23 d with extreme melt, showing a strong correspondence between the heat wave periods and extreme melt events. The combination of below-average winter snowfall and a suite of summer heat waves led to unprecedented glacier mass loss. The Switzerland-wide glacier storage change during the 25 d of heat waves in 2022 is estimated as 1.27 ± 0.10 km3 of water, corresponding to 35 % of the overall glacier mass loss during that summer. The same 25 d of heat waves caused a glacier mass loss that corresponds to 56 % of the average mass loss experienced over the entire melt season during the summers 2010-2020, demonstrating the relevance of heat waves for seasonal melt.

Ziel des adaptiven Waldbaus ist es, die Waldbewirtschaftung nach Bedarf an die sich ändernden Umweltbedingungen anzupassen, damit Waldleistungen und Biodiversität angesichts der durch den Klimawandel immer häufigeren und auch extremeren Störungsereignisse erhalten bleiben. Dieser Artikel fasst die Kernaussagen der in dieser Schwerpunktausgabe vorgestellten Beispiele aus Forschung und Praxis zum aktuellen Stand des adaptiven Waldbaus zusammen. Und er zeigt auf, dass der adaptive Waldbau in der Praxis voranschreitet. Gleichzeitig müssen sowohl Praxis als auch Forschung weiter und zusammen daran arbeiten, bestehende Unsicherheiten im Hinblick auf die zukünftige Klimaentwicklung und die Eignung verschiedener waldbaulicher Anpassungsmassnahmen zu reduzieren.

The objective of adaptive forest management is a directed adjustment of silvicultural measures wherever necessary to ensure provision of forest services and biodiversity in the face of more frequent and more intense disturbance events due to climate change in the future. This paper synthesises the main points of the examples from practitioners and scientists that are presented in this special issue and shows that there is good progress towards the adaptation of forest stands to climate change. At the same time, forest practitioners and scientists need to further collaborate to reduce existing uncertainties regarding the future development of the climate and the effectiveness of specific silvicultural adaption measures.

Hybrid hydroclimatic forecasting systems employ data-driven (statistical or machine learning) methods to harness and integrate a broad variety of predictions from dynamical, physics-based models - such as numerical weather prediction, climate, land, hydrology, and Earth system models - into a final prediction product. They are recognized as a promising way of enhancing the prediction skill of meteorological and hydroclimatic variables and events, including rainfall, temperature, streamflow, floods, droughts, tropical cyclones, or atmospheric rivers. Hybrid forecasting methods are now receiving growing attention due to advances in weather and climate prediction systems at subseasonal to decadal scales, a better appreciation of the strengths of AI, and expanding access to computational resources and methods. Such systems are attractive because they may avoid the need to run a computationally expensive offline land model, can minimize the effect of biases that exist within dynamical outputs, benefit from the strengths of machine learning, and can learn from large datasets, while combining different sources of predictability with varying time horizons. Here we review recent developments in hybrid hydroclimatic forecasting and outline key challenges and opportunities for further research. These include obtaining physically explainable results, assimilating human influences from novel data sources, integrating new ensemble techniques to improve predictive skill, creating seamless prediction schemes that merge short to long lead times, incorporating initial land surface and ocean/ice conditions, acknowledging spatial variability in landscape and atmospheric forcing, and increasing the operational uptake of hybrid prediction schemes.

Der Klimawandel verändert die Wuchsbedingungen der Waldbäume, weshalb langfristig markante Verschiebungen in der Baumartenzusammensetzung des Schweizer Waldes zu erwarten sind. Die TreeApp ist ein Werkzeug für die Forstpraxis zur Ermittlung von Baumarten, die für das zukünftige Klima wahrscheinlich geeignet sind. In dieser Arbeit vergleichen wir Empfehlungen der TreeApp mit der im 4. Landesforstinventar (LFI4) beobachteten Artenzusammensetzung der Bäume (≥12 cm Brusthöhendurchmesser [BHD]) und der Verjüngung (<12 cm BHD), wobei wir auch die Präsenz von potenziellen Samenbäumen berücksichtigten. Wir stellen ein einfaches Bewertungsschema vor, mit dem wir die Stichprobenflächen des LFI in drei Stufen der Zukunftsfähigkeit (Grad der Anpassung an das Klima am Ende dieses Jahrhunderts) einteilen konnten. Schweizweit wurde der Wald auf 57% der Stichprobenflächen als zukunftsfähig, auf 23% als bedingt zukunftsfähig und auf 17% als nicht zukunftsfähig beurteilt. Dabei zeigte sich eine Häufung von nicht zukunftsfähigen Flächen in Fichtenwäldern in den Kantonen Graubünden und Wallis. Im Schutzwald der Voralpen, der Alpen und der Alpensüdseite wurde die Verjüngung auf 25% der Stichprobenflächen als nicht zukunftsfähig eingeschätzt, und auf 22% wurde keine Verjüngung beobachtet. Mit steigendem Fichtenanteil nahm der Anteil des Baumbestands ohne Zukunftsfähigkeit zu. Im Mittelland und im Jura wurde die Verjüngung auf einem grösseren Flächenanteil als zukunftsfähig eingeschätzt als der Baumbestand. Wenn Samenbäume berücksichtigt wurden, war der Stichprobenflächenanteil mit zukunftsfähiger Bestockung um bis zu 16 Prozentpunkte (Voralpen) höher, als wenn nur die Verjüngung betrachtet wurde. Diese Resultate unterstreichen die Notwendigkeit der Förderung einer zukunftsfähigen Verjüngung im Gebirgswald, bieten nützliche Grundlagen für die strategische Waldplanung und tragen so zur Anpassung des Waldes an den Klimawandel bei.

Medium to subseasonal hydrological forecasts contain more information relevant to water and environmental management tasks than climatological forecasts. However, extracting this information at the most appropriate level of accuracy and spatiotemporal resolution remains a difficulty. Many studies show that the skill of the extended range forecasts with daily resolution tends toward zero after 7-14 days for small mountainous catchments. Beyond that forecast horizon the application of highly sophisticated pre- and postprocessing methods generally produce limited gains. Consequently, current forecasting techniques cannot effectively represent forecast extremes at extended ranges such as anomalously high and low runoff or soil moisture. To tackle these deficiencies, this study analyzes the value of tercile forecasts for weekly aggregates of runoff and soil moisture forecasts available at a daily resolution for Switzerland. The forecasts are classified into three categories: below, above, and normal conditions, which are derived from long-term simulations and correspond approximately to climatological conditions. To achieve improved reliability and skill of the predicted tercile probabilities, a nonparametric probabilistic classification method has been tested. It is based on Gaussian process (GP), which is attractive in machine learning (ML) applications because of its ability to estimate the predictive uncertainty. The outcome of these postprocessed forecasts was compared to preprocessing methods where the meteorological predictions are statistically corrected before passing to the hydrological model. Our results indicate that tercile forecasts of weekly aggregates produce a suitable skill up to 3 weeks lead time using the preprocessed input and up to 4 weeks lead time using the GP method.

Recent debates on insect decline require sound assessments on the relative drivers that may negatively impact insect populations. Often, baseline data rely on insect monitorings that integrate catches over long time periods. If, however, effects of time-critical environmental factors (e.g., light pollution) are of interest, higher temporal resolution of insect data is required during very specific time intervals (e.g., between dusk and dawn). Conventional time-critical insect trapping is labour-intensive (manual activation/deactivation) and temporally inaccurate as not all traps can be serviced synchronically at different sites. Also, temporal shifts of environmental conditions (e.g., sunset/sunrise) are not accounted for. We present a battery-driven automated insect flight-interception trap which samples insects during seven user-defined time intervals. A commercially available flight-interception trap is fitted to a turntable containing eight positions, seven of them holding cups and one consisting of a pass-through hole. While the cups sample insects during period of interest, the pass-through hole avoids unwanted sampling during time-intervals not of interest. Comparisons between two manual and two automated traps during 71 nights in 2018 showed no difference in caught insects. A study using 20 automated traps during 104 nights in 2019 proved that the automated flight-interception traps are reliable. The automated trap opens new research and application possibilities as arbitrary insect-sampling intervals can be defined. The trap proves efficient, saving manpower and associated costs as activation/deactivation is required only every seven sampling intervals. In addition, the timing of the traps is accurate, as all traps sample at exactly the same intervals and ensure comparability. The automated trap is low maintenance and robust due to straightforward technical design. It can be controlled manually or via smartphone through a Bluetooth connection. Full construction details are given in Appendices.

New technological developments modulate the light levels of LED street luminaires according to traffic volumes: light levels are increased given traffic and reduced in its absence. Such dimming of street lights reduces the level of artificial light at night (ALAN) and may thus contribute to mitigate light pollution. To quantify the impact of traffic-driven dimming of street lights on nocturnal insect abundance and bat activity in comparison to full light (i.e., dimming functions of luminaires switched off), we mounted 20 insect flight-interception traps and ten batloggers on street light poles along two dimmable street light sections. Insect abundance and bat activity were measured alternately with one week of full street lighting followed by a week with light levels modulated by traffic volumes. In total, 16 dimmed and 16 full-light days were investigated. Overall, traffic-driven dimming reduced light levels by 35%. Weather conditions (warm, dry nights) were the main drivers of insect abundance and bat activity, but traffic-driven dimming resulted in lower numbers of insects caught and reduced bat activity. Among insect groups, Heteroptera benefited most from dimming. For bats, urban exploiters (Pipistrellus spp.) benefited from increased availability of prey at brightly lit street lights, while less frequent species (Myotis spp.) did not benefit from street lighting. We conclude that street light dimming technology may contribute to mitigate negative effects of ALAN on nocturnal organisms, although the measure may not be efficient enough to support light-sensitive and threatened species.

Artificial light at night (ALAN) is an important driver of change in ecological environments of the 21th century. We investigated the impact on nocturnal insect abundance and bat activity of two LED light colors (warm-white 2700 K, cold-white 6500 K) in a peri-urban environment. Bat activity (predominantly Pipistrellus pipistrellus) was largely driven by prey availability (insects), while insect abundance was responsive to nightly weather conditions (precipitation, temperature). Thus, both insects and bats were not differentially responsive to cold-white or warm-white LEDs. These findings are largely in contrast with literature, particularly for insects. However, as most published experiments on ALAN were conducted in areas that were lit solely for the purpose of the experiment, we would like to bring forward that (1) adaptation to environmental constraints may play a role in peri-urban environments that have been exposed to ALAN for many decades; or (2) impacts of cold-white LEDs on nocturnal insects may be lower than expected, because nocturnal insects adapted to low-light conditions may be put off by cold white light sources (6500 K).

Wird künstliches Nachtlicht übermässig eingesetzt, bedroht es zunehmend die Ökosystemfunktionen. Mittels steuerbarer LED-Aussenbeleuchtungen lassen sich die negativen Folgen von Kunstlicht mildern. Die gesteigerte Energieeffizienz von LEDs trägt zudem dazu bei, die Lichtversorgung zu optimieren, und dank intelligenter,
adaptiver Licht- und Kommunikationstechnik gelangt weniger Licht in die Umwelt. Diese neuen technologischen Entwicklungen können Auswirkungen auf die Umwelt minimieren und gleichzeitig die (Strassenverkehrs-)Sicherheit gewährleisten. Nötig ist eine inter- und transdisziplinäre Zusammenarbeit zwischen Umweltfachleuten und Beleuchtungsplanerinnen und -planern. Dieser Artikel zeigt auf, wie sich die Nachtbeleuchtung auf die Umwelt auswirkt und welche Möglichkeiten die neueste Beleuchtungstechnologie bietet.

Artificial night light is increasingly recognized as a threat to ecosystem functions. LED outdoor lighting can help to conserve resources with the help of long-life light sources and lowered energy consumption. Increased efficiency of LEDs also contribute to an optimization of the light supply and intelligent, adaptive lighting and communication technology allow to reduce light emissions into the environment. In order to value these new technical developments, a common denominator is required that minimizes the impact on the environment, meets the needs of the population and at the same time ensures (traffic) safety. In order to ensure this, inter- and transdisciplinary cooperation is necessary to successfully integrate the effects of night light on the ecological environment into lighting design. The aim of this article is to give an overview of the effects of night lighting on the ecological environment, as well as the possibilities and meanings of the latest lighting technology.

The need to assess landscape qualities has become increasingly important over the past decades, with landscapes being continuously shaped and re-shaped through dynamic natural and anthropogenic processes. It is now widely recognised that landscapes need to be studied both in terms of their physical and ecological elements as well as how people living in or visiting landscapes perceive and interact with them. Different approaches have been developed over time for assessing these variegated aspects of landscape qualities, which range from methods in the natural sciences to the social sciences and humanities. Using the three examples of wilderness, tranquillity and dark skies as landscape qualities, we review existing quantitative and qualitative approaches to illustrate the potential of interdisciplinary landscape research. Furthermore, we highlight the potential of novel methodologies and data sources to study these landscape qualities, including the use of machine learning for automated image recognition, analysis of social media data (tags, location and image content), as well as citizen science approaches.