Dr. Dirk Schmatz

Gegitterte Klimadaten mit einer regelmässigen räumlichen Auflösung sind eine wichtige Grundlage für Umweltstudien. Sie werden mithilfe statistischer Methoden aus Punktdaten von Messstationen erzeugt und haben insbesondere in topografisch komplexen Gebirgsregionen wie den Schweizer Alpen eine limitierte Genauigkeit. Dieser Artikel vergleicht vier für die Schweiz entwickelte gegitterte Datensätze unterschiedlicher Temperatur- und Niederschlagsvariablen mit unabhängigen Messdaten von 14 Dauerbeobachtungsflächen der Langfristigen Waldökosystemforschung (LWF) über einen Zeitraum von 20 Jahren. Die Resultate dienen als Entscheidungshilfe zur Wahl eines für eine grossflächige Anwendung zuverlässigen und homogenen Datensatzes. Die untersuchten Datensätze mit individuellen Stärken und Schwächen kommen für Anwendungen in der Schweiz infrage.

Predicting future climatic conditions at high spatial resolution is essential for many applications and impact studies in science. Here, we present monthly time series data on precipitation, minimum- and maximum temperature for four downscaled global circulation models. We used model output statistics in combination with mechanistic downscaling (the CHELSA algorithm) to calculate mean monthly maximum and minimum temperatures, as well as monthly precipitation at ~5 km spatial resolution globally for the years 2006-2100. We validated the performance of the downscaling algorithm by comparing model output with the observed climate of the historical period 1950-1969.

Projections of landscape dynamics are uncertain, partly due to uncertainties in model formulations. However, quantitative comparative analyses of forest landscape models are lacking. We conducted a systematic comparison of all forest landscape models currently applied in temperate European forests (LandClim, TreeMig, LANDIS-II, iLand). We examined the uncertainty of model projections under several future climate, disturbance, and dispersal scenarios, and quantified uncertainties by variance partitioning. While projections under past climate conditions were in good agreement with observations, uncertainty under future climate conditions was high, with between-model biomass differences of up to 200 t ha^-1. Disturbances strongly influenced landscape dynamics and contributed substantially to uncertainty in model projections (~25-40% of observed variance). Overall, model differences were the main source of uncertainty, explaining at least 50% of observed variance. We advocate a more rigorous and systematic model evaluation and calibration, and a broader use of ensemble projections to quantify uncertainties in future landscape dynamics.

Species distribution models (SDMs) constitute the most common class of models across ecology, evolution and conservation. The advent of ready-to-use software packages and increasing availability of digital geoinformation have considerably assisted the application of SDMs in the past decade, greatly enabling their broader use for informing conservation and management, and for quantifying impacts from global change. However, models must be fit for purpose, with all important aspects of their development and applications properly considered. Despite the widespread use of SDMs, standardisation and documentation of modelling protocols remain limited, which makes it hard to assess whether development steps are appropriate for end use. To address these issues, we propose a standard protocol for reporting SDMs, with an emphasis on describing how a study's objective is achieved through a series of modeling decisions. We call this the ODMAP (Overview, Data, Model, Assessment and Prediction) protocol, as its components reflect the main steps involved in building SDMs and other empirically-based biodiversity models. The ODMAP protocol serves two main purposes. First, it provides a checklist for authors, detailing key steps for model building and analyses, and thus represents a quick guide and generic workflow for modern SDMs. Second, it introduces a structured format for documenting and communicating the models, ensuring transparency and reproducibility, facilitating peer review and expert evaluation of model quality, as well as meta-analyses. We detail all elements of ODMAP, and explain how it can be used for different model objectives and applications, and how it complements efforts to store associated metadata and define modelling standards. We illustrate its utility by revisiting nine previously published case studies, and provide an interactive web-based application to facilitate its use. We plan to advance ODMAP by encouraging its further refinement and adoption by the scientific community.

Alpine and Arctic species are considered to be particularly vulnerable to climate change, which is expected to cause habitat loss, fragmentation and—ultimately—extinction of cold-adapted species. However, the impact of climate change on glacial relict populations is not well understood, and specific recommendations for adaptive conservation management are lacking. We focused on the mountain hare (Lepus timidus) as a model species and modelled species distribution in combination with patch and landscape-based connectivity metrics. They were derived from graph-theory models to quantify changes in species distribution and to estimate the current and future importance of habitat patches for overall population connectivity. Models were calibrated based on 1,046 locations of species presence distributed across three biogeographic regions in the Swiss Alps and extrapolated according to two IPCC scenarios of climate change (RCP 4.5 & 8.5), each represented by three downscaled global climate models. The models predicted an average habitat loss of 35% (22%–55%) by 2100, mainly due to an increase in temperature during the reproductive season. An increase in habitat fragmentation was reflected in a 43% decrease in patch size, a 17% increase in the number of habitat patches and a 34% increase in inter-patch distance. However, the predicted changes in habitat availability and connectivity varied considerably between biogeographic regions: Whereas the greatest habitat losses with an increase in inter-patch distance were predicted at the southern and northern edges of the species’ Alpine distribution, the greatest increase in patch number and decrease in patch size is expected in the central Swiss Alps. Finally, both the number of isolated habitat patches and the number of patches crucial for maintaining the habitat network increased under the different variants of climate change. Focusing conservation action on the central Swiss Alps may help mitigate the predicted effects of climate change on population connectivity.

Mountain regions are sensitive to climate changes, which make them good indicators of climate change. The aim of this study is to investigate the spatial and temporal variability of air temperature and precipitation in the Polish Carpathians. This study consists of climatological analyses for the historical period 1851-2010 and future projections for 2021-2100. The results confirm that there has been significant warming of the area and that this warming has been particularly pronounced over the last few decades and will continue in the oncoming years. Climate change is most evident in the foothills; however, these are the highest summits which have experienced the most intensive increases in temperature during the recent period. Precipitation does not demonstrate any substantial trend and has high year-to-year variability. The distribution of the annual temperature contour lines modelled for selected periods provides evidence of the upward shift of vertical climate zones in the Polish Carpathians, which reach approximately 350 meters, on average, what indicates further ecological consequences as ecosystems expand or become extinct and when there are changes in the hydrological cycle.

Understanding drivers of forest-cover change is essential for a broad range of ecosystem properties. In this work, we assessed changes in forest cover using physical, climatic and socio-economic drivers, including forest neighbourhood effects representing spatial interactions within and between two time periods (1880–1940; 1940–2010), for a mountainous study area located in eastern Switzerland. The robust assessment relied on an ensemble modelling approach that combined projections of six statistical models (GAM, CART, ANN, RF, GBM, GLM). A generic neighbourhood variable (distance to forest edge) explained most of the forest-cover change (variable importance of >90%) for both forest gain and loss, whereas socio-economic, physical and climatic variables were of least importance. The performance of models of forest loss was consistently higher and less varied (TSS of model ensembles 0.65–0.82) compared to models of forest gain (TSS of model ensembles 0.2–0.62) independent of the time period considered. We concluded that (a) the relative importance of drivers for the simulated processes is independent of the time period considered; (b) ensemble modelling proves a powerful tool to assess projection robustness by considering a suite of models rather than a single model type and (c) the inclusion of generic neighbourhood variables such as distance to forest edge improves model performance significantly.

Tree populations usually show adaptations to their local environments as a result ofnatural selection. As climates change, populations can become locally maladapted and decline in fitness. Evaluating the expected degree of genetic maladaptation due to climate change will allow forest managers to assess forest vulnerability, and develop strategies to preserve forest health and productivity. We studied potential genetic maladaptation to future climates in three major European tree species, Norway spruce (Picea abies), silver fir (Abies alba), and European beech (Fagus sylvatica). A common garden experiment was conducted to evaluate the quantitative genetic variation in growth and phenology of seedlings from 77 to 92 native populations of each species from across Switzerland. We used multivariate genecological models to associate population variation with past seed source climates, and to estimate relative risk of maladaptation to current and future climates based on key phenotypic traits and three regional climate projections within the A1B scenario. Current risks from climate change were similar to average risks from current seed transfer practices. For all three climate models, future risks increased in spruce and beech until the end of the century, but remained low in fir. Largest average risks associated with climate projections for the period 2061–2090 were found for spruce seedling height (0.64), and for beech bud break and leaf senescence (0.52 and 0.46). Futurerisks for spruce were high across Switzerland. However, areas of high risk were also found in drought-prone regions for beech and in the southern Alps for fir. Genetic maladaptation to future climates is likely to become a problem for spruce and beech by the end of this century, but probably not for fir. Consequently, forest management strategies should be adjusted in the study area for spruce and beech to maintain productive and healthy forests in the future.

Targeting of agri-environmental measures (AEMs) is a key to increasing the cost-effectiveness of governmental support for biodiversity conservation and the provision of ecosystem services from agriculture. Existing literature, however, often focuses on single measures without considering that policies are usually bundles of different measures addressing multiple non-marketed goods and services. Thus, interaction effects of a set of policies in a given policy mix may influence the cost-effectiveness of single measures. Recently, Swiss agricultural policy was redesigned using the Tinbergen rule as its basis, i.e., a single measure for each policy goal, including additional targeted direct payments. This facilitates testing for interaction effects of multiple targeted AEMs. Here we use a social-ecological, agent-based modelling framework to assess interaction effects of these agricultural policies while accounting for climate change impacts in our analysis. The results from our case study in a mountain region show that ecosystem service provision increases with targeted payments. However, interaction effects of the different targeted policies affect the provision levels of all goods and services. In particular, changes at the extensive margin, i.e., the total amount of land that is under production, largely determine the amount of ecosystem services provided. Thus, climate change driven productivity increases and policies that keep land in production may substantially support the provision of non-marketed goods and services in marginal agricultural production regions with a high potential for land abandonment. Consequently, the effectiveness of targeted policy measures should also consider changes at the extensive margin and be assessed in the context of bundles or portfolios of different policy measures.

The spatial distribution of forests in Europe represents the legacy of centuries of human land use decisions. Due to the limited availability of historical data, most studies on forest cover change focus only on analyzing recent decades, thereby overlooking the important long-term context. However, the latter is essential to improve our understanding of present landscape patterns. This study quantifies the spatiotemporal dynamics in drivers of forest gain in Switzerland. Specifically, we model forest gain in a long-term study covering 150 years (1850–2000) split into periods of similar length (∼30 years). This makes it possible to identify nonlinear dynamics and whether drivers have changed over time. The rates of forest change are quantified based on analyzing historical maps and contemporary forest inventory data. Generalized additive models (GAMs) are fitted to examine the variation in the relative importance of socioeconomic and biophysical explanatory variables. Our results suggest that both biophysical and socioeconomic variables co-drive forest gain. Biophysical variables (such as temperature and slope) were identified as the major drivers explaining variations in forest gain. The most important socioeconomic driver was the change in the percentage of people employed per economic sector, although its effect came with a substantial time lag. Changes in employment per sector for the periods 1920– 1941 and 1941–1980 were relevant for forest gain between 1980 and 2000. The identified time lag effect emphasizes the added value of long-term studies, since legacies may persist for decades, adding further complexity to contemporary land change processes. These findings are relevant to many temperate ecosystems that are experiencing increases in forest cover. Such insights can improve both future forest change predictions as well as the development of policies for sustainable landscape management.

Mountain forest areas are key for providing a wide range of ecosystem services and are hot spots for land use change processes, in particular, increase in forest cover at the expense of mountain pastures and meadows. Mountain forest systems in eastern and western Europe have likely similar future socio-economic situations but significantly different socio-economic history. Using a scenario-based land use modelling approach (Dyna-CLUE framework) we model three scenarios (trend, liberalisation and self-sufficiency) of future land use in the Polish Carpathians and the Swiss Alps, focussing on forest cover change. We find that forest cover increase can be expected to continue in European mountainous regions under all likely scenarios, limited only by relatively strict policy interventions. Biophysical factors, rather than socio-economic ones, are key for defining the suitability for, and therefore likely locations of future forest cover, but land use legacy plays a very important role in the spatial patterns of future forest cover, particularly in eastern Europe.

The European beech (Fagus sylvatica L.) is one of the most ecologically and economically important tree species in Europe. Nonetheless, post-fire ecological processes in beech forests have only been marginally studied although they might become more important for forest management in the light of global climate change drought effects. Focusing on the Southern European Alps, where numerous forest fires have affected beech stands, we assessed temporal trends and detected factors that influence beech regeneration in beech forests burnt between 1970 and 2012. Beech regeneration was found to occur abundantly in fire sites of mixed burn severity, and often co-occurred with light-demanding pioneer trees (mostly Betula pendula Roth). These pioneers declined in abundance from 20 years post-fire onwards, whereas beech dominance increased. Beech regeneration density was best explained in regression models by the canopy of remnant trees and the abundance of competing ground vegetation. As fire-injured beech trees slowly die back, the canopy gradually opens, favouring beech recruitment for as long as decades, depending on the light conditions. In contrast, dense layers of early post-fire colonisers may delay beech regeneration for many years. Generally, single fire events favour beech regeneration except in areas where the burn severity is extraordinarily high.

Statistische Modelle können die Verbreitung unter heutigen und die potenzielle Verbreitung unter zukünftigen Klimabedingungen vorhersagen. Gemäss diesen Modellen werden in der Schweiz vor allem die montanen und subalpinen Baumarten an Arealgrösse einbüssen, teils weil in höheren Lagen immer weniger Fläche vorhanden ist, teils weil diese Arten eher humide, kühle Bedingungen vorziehen. Demgegenüber können kollin/submontane, trockenheitsangepasste Arten ihr Areal ausdehnen und im Mittelland neu geeignete Standorte vorfinden. Wo das Klima ungünstig wird, heisst dies nicht zwingend, dass eine Baumart nicht mehr gedeiht, sondern nur, dass heute die Art nicht unter solchen Bedingungen beobachtet wird. Unklar bleibt, wie rasch sich die Vegetation von selbst an diese neuen Klimabedingungen anpassen wird. Wahrscheinlich lösen vor allem Klimaextreme diese Anpassung aus, weniger die Änderungen der Mittelwerte. Bisher war die beobachtete Geschwindigkeit der Anpassung in der Vegetation klar langsamer, als sich geeignete Klimabedingungen vertikal und lateral verschoben.
Während des Blattaustriebs limitieren Tiefsttemperaturen die Höhenobergrenze einzelner Laubbaumarten. Keimlinge und Jungpflanzen sind anfälliger als adulte Bäume, weil sie früher austreiben und weniger Reserven haben, um Blattschäden zu kompensieren. Klimaphänomene wie Föhn und Kaltluftseen haben lokal einen grossen Einfluss auf die Verbreitung der Baumarten.
Für die Waldbewirtschaftung sind Prognosen zu Baumartenverbreitung nicht einfach umzusetzen, da nicht immer klar ist, welche Klimaänderungen zu physiologischem Stress führen. Zudem ist die Prognose von Extremereignissen unpräzise. Eine Strategie basierend auf einer Mischung unterschiedlicher Arten mindert aber das Risiko von Ausfällen unter Klimaextremen. Mittelfristig sollten in tieferen Lagen wärmebedürftige oder trockenheitsangepasste Arten gefördert oder aktiv eingebracht werden. In subalpinen Lagen sind bald auch die Buche und andere Laubhölzer konkurrenzfähig.

Les modèles statistiques permettent de déterminer la répartition des espèces dans les conditions climatiques actuelles et futures. D’après ces modèles, les essences forestières montagnardes et subalpines devraient voir leur aire de répartition diminuer en Suisse, parce que l’espace disponible se réduit en altitude d’une part, et qu’elles préfèrent des conditions fraîches et humides d’autre part. Les essences collinéennes, submontagnardes ou adaptées à la sécheresse, elles, étendront leur aire de répartition et trouveront de nouvelles stations adaptées sur le Plateau. Lorsque les conditions climatiques sont défavorables, cela ne signifie pas que les essences ne prospèrent plus mais seulement qu’elles ne sont plus observées dans les conditions données. On ne sait en effet pas à quelle vitesse la végétation s’adapte aux nouvelles conditions. L’adaptation semble induite davantage par les extrêmes climatiques que par l’évolution des valeurs moyennes. Jusqu’ici, la vitesse d’adaptation observée a été nettement plus faible que celle du déplacement vertical et latéral des conditions climatiques.
Pendant le débourrement, les minimas de température influent sur la limite altitudinale de certains feuillus. Les plantules et les jeunes plants sont plus sensibles que les arbres adultes dans la mesure où leurs feuilles apparaissent plus tôt et où ils ont moins de réserves pour compenser les dommages subis. Des phénomènes tels que le foehn et les lacs d’air froid influent localement sur la distribution des essences.
Les prévisions de répartition ne sont pas simples à transposer en gestion forestière car les conditions climatiques induisant un stress physiologique ne sont pas toujours clairement identifiables. En outre, les événements extrêmes sont difficiles à prévoir. Cependant, la définition d’une stratégie reposant sur un mélange d’essences réduit le risque de pertes en conditions extrêmes. À moyen terme, les essences thermophiles ou adaptées à la sécheresse devraient être privilégiées ou implantées activement à basse altitude. À une altitude subalpine, le hêtre et d’autres feuillus seront bientôt concurrentiels.

– Projected changes in species composition (i.e., turnover) of birds and vascular plants, two important components of biodiversity, are widespread across Switzerland, with especially strong turnover at both low and middle (~2000 m asl) elevations by the end of the century under the A1B scenario.

– Areas with large changes in number of species and turnover in composition do not completely coincide because areas initially with few species can experience high turnover with the influx of just a few species, as in Graubünden and Valais.

– Uncertainty in the turnover of species composition that is associated with different climate models decreases with increasing time as impacts become stronger. Uncertainty in turnover is initially found both in high and low elevations in the first simulation period (2020), but predominately in mountainous areas in the third simulation period (2090).

– By using an approach that should better capture the limits on species distributions imposed by warm, dry conditions, these projections suggest that low-elevation cantons will be among the most highly impacted by climate-driven changes in species distributions.

Scenario analysis is a widely used approach to incorporate uncertainties in global change research. In the context of regional ecosystem service and landscape management where global IPCC climate simulations and their downscaled derivates are applied, it can be useful to work with regional sodo-economic scenarios that are coherent with the global IPCC scenarios. The consistency with the original source scenarios, transparency and reproducibility of the methods used as well as the internal consistency of the derived scenarios are important methodological prerequisites for coherently downscaling pre-existing source scenarios. In contrast to well-established systematic-qualitative scenario techniques, we employ here a formal technique of scenario construction which combines expert judgement with a quantitative, indicator-based selection algorithm in order to deduce a formally consistent set of focus scenario. In our case study, these focus scenarios reflect the potential development pathways of major national-level drivers for ecosystem service management in Swiss mountain regions. The integration of an extra impact factor ("Global Trends") directly referring to the four principle SRES scenario families, helped us to formally internalise base assumptions of IPCC SRES scenarios to regional scenarios that address a different thematic focus (ecosystem service management), spatial level (national) and time horizon (2050). Compared to the well-established systematic-qualitative approach, we find strong similarities between the two methods, including the susceptibility to personal judgement which is only partly reduced by the formal method. However, the formalised scenario approach conveys four clear advantages, (1) the better documentation of the process, (2) its reproducibility, (3) the openness in terms of the number and directions of the finally selected set of scenarios, and (4) its analytical power.

Mountain ecosystems provide a broad range of ecosystem services (ES). Trade-offs between different ES are an important aspect in the assessment of future sustainable land-use. Management of ES in mountain regions must confront the challenges of spatial and temporal heterogeneity, and interaction with structural changes in agriculture and forestry. Using a social-ecological modeling framework, we assess the relationships between forest and agricultural ES in a mountain region in Switzerland. Based on the concept of jointness in production, we evaluated trade-offs and synergies among food provision, biodiversity conservation, carbon sequestration, and protection against natural hazards. Results show that increasing the provision of a focal ES in a mountain region may result in alternating trade-offs and synergies, depending on the interaction of economic and technological interdependencies. Thus, management schemes aiming to increase the provision of one focal ES have to consider not only the technological or biological nature of interrelationships, but also the economic interdependencies among different ES. Trade-offs and synergies from these interactions strongly depend on the underlying structural and environmental conditions driven by socioeconomic and climatic developments.

Quantitative estimates of the range loss of mountain plants under climate change have so far mostly relied on static geographical projections of species' habitat shifts^1-3. Here, we use a hybrid model⁴ that combines such projections with simulations of demography and seed dispersal to forecast the climate-driven spatio-temporal dynamics of 150 high-mountain plant species across the European Alps. This model predicts average range size reductions of 44-50% by the end of the twenty-first century, which is similar to projections from the most 'optimistic' static model (49%). However, the hybrid model also indicates that population dynamics will lag behind climatic trends and that an average of 40% of the range still occupied at the end of the twenty-first century will have become climatically unsuitable for the respective species, creating an extinction debt^5,6. Alarmingly, species endemic to the Alps seem to face the highest range losses. These results caution against optimistic conclusions from moderate range size reductions observed during the twenty-first century as they are likely to belie more severe longer-term effects of climate warming on mountain plants.