Dr. Nica Huber

Information regarding the spatial arrangement and extent of past habitats is important for understanding present biodiversity, restoration potential, and fighting extinction-debt effects. European landscapes have changed profoundly over recent decades, with the trend accelerating following World War 2. We develop a proof of concept for mapping historic habitat distribution for Switzerland from black and white aerial imagery compatible with the present-day habitat map. Recently available orthorectified 1946 aerial imagery (1 m resolution) was segmented based on spectral and shape characteristics for training areas (320–508 km²) representing the main biogeographical regions of Switzerland. Initial training data was derived by manual aerial orthoimage interpretation differentiating 15 habitat classes. A random forest model was trained to classify the segments using variables describing spectral information, image texture, segment shape, topography, climate, and anthropogenic influence. Classification accuracy was improved with additional training samples derived in a stepwise approach, applying three different sampling techniques. Highest class accuracies (producer's and user's accuracies ≥ 0.75) were achieved for the habitats ‘Standing water’, ‘Flowing water’, ‘Glaciers, permanent ice and snow’, and ‘Forests and other wooded land’. Particularly low user's accuracies were found for ‘Wetlands’, ‘Hedges and tree rows’ and ‘Buildings’. The comparison to independent data further revealed minor differences in overall accuracy for the three different sampling strategies. Yet, map predictions sometimes varied substantially, indicating that the sampling strategies address different classification issues. Hence, we conclude that combining different sampling strategies for training data collection has the potential to improve the mapping, particularly in the case of multi-class classifications.

Process-based forest models combine biological, physical, and chemical process understanding to simulate forest dynamics as an emergent property of the system. As such, they are valuable tools to investigate the effects of climate change on forest ecosystems. Specifically, they allow testing of hypotheses regarding long-term ecosystem dynamics and provide means to assess the impacts of climate scenarios on future forest development. As a consequence, numerous local-scale simulation studies have been conducted over the past decades to assess the impacts of climate change on forests. These studies apply the best available models tailored to local conditions, parameterized and evaluated by local experts. However, this treasure trove of knowledge on climate change responses remains underexplored to date, as a consistent and harmonized dataset of local model simulations is missing.
Here, our objectives were (i) to compile existing local simulations on forest development under climate change in Europe in a common database, (ii) to harmonize them to a common suite of output variables, and (iii) to provide a standardized vector of auxiliary environmental variables for each simulated location to aid subsequent investigations. Our dataset of European stand- and landscape-level forest simulations contains over 1.1 million simulation runs representing 135 million simulation years for more than 13,000 unique locations spread across Europe. The data were harmonized to consistently describe forest development in terms of stand structure (dominant height), composition (dominant species, admixed species), and functioning (leaf area index). Auxiliary variables provided include consistent daily climate information (temperature, precipitation, radiation, vapor pressure deficit) as well as information on local site conditions (soil depth, soil physical properties, soil water holding capacity, plant-available nitrogen). The present dataset facilitates analyses across models and locations, with the aim to better harness the valuable information contained in local simulations for large-scale policy support, and for fostering a deeper understanding of the effects of climate change on forest ecosystems in Europe.

Land-use intensification in grassland ecosystems (i.e. increased mowing frequency, intensified grazing) has a strong negative effect on biodiversity and ecosystem services. However, accurate information on grassland-use intensity is difficult to acquire and restricted to the local or regional level. Recent studies have shown that mowing events can be mapped for large areas using satellite image time series. The transferability of such approaches, especially to mountain areas, has been little explored, however, and the relevance for ecological applications in biodiversity and conservation has hardly been investigated. Here, we used a rule-based algorithm to produce annual maps for 2018–2021 of grassland-management events, that is, mowing and/or grazing, for Switzerland using Sentinel-2 and Landsat 8 satellite data. We assessed the detection of management events based on independent reference data, which we acquired from daily time series of publicly available webcams that are widely distributed across Switzerland. We further examined the relationships between the generated grassland-use intensity measures and plant species richness and ecological indicator values derived from a nationwide field survey. The webcam-based verification for 2020 and 2021 revealed that most detected management events were actual mowing/grazing events (≥78%), but that a substantial number of events were not detected (up to 57%), particularly grazing events at higher elevations. We found lower plant species richness and higher mean ecological indicator values for nutrients and mowing tolerance with more frequent management events and those starting earlier in the year. A large proportion of the variance was explained by our use-intensity measures. Our findings therefore highlight that remotely assessed management events can characterise land-use intensity at fine spatial and temporal resolutions across broad scales and can explain plant biodiversity patterns in grasslands.

Die Intensität der Landnutzung hat einen grossen Einfluss auf die Biodiversität unseres Grünlands. Es ist jedoch aufwändig, sie flächendeckend und detailliert zu erfassen. Wir haben die Nutzungsintensität in der ganzen Schweiz mit Satellitenbildern über mehrere Jahre kartiert. Die frei verfügbaren Karten des Schweizer Grünlands haben ein grosses Potenzial für verschiedene ökologische Anwendungen und die Biodiversitätsforschung.

L'intensité d'exploitation du sol a de grands effets sur la biodiversité de nos surfaces herbagères. Toutefois, recenser cette intensité sur tout le territoire et de manière détaillée nécessite des moyens. Grâce à des images satellite, nous l'avons cartographiée sur plusieurs années et dans toute la Suisse. Les cartes, en libre accès, recèlent un grand potentiel pour différentes applications écologiques et pour la recherche dans le domaine de la biodiversité.

Die Population des Grauspechts (Picus canus) ist seit den 1990er-Jahren in der Schweiz um zwei Drittel zurückgegangen, weshalb er seit 2021 auf der Roten Liste als stark gefährdet geführt wird. Die Ursachen für den markanten Populationsrückgang sind bislang jedoch unklar. Um mehr über seine Habitatansprüche zu erfahren, wurden im Schweizer Jura in den Jahren 2020 bis 2022 insgesamt 55 Grauspecht-Individuen besendert. In diesem methodischen Beitrag stellen wir vor, wie wir mithilfe von Telemetriedaten und hochaufgelösten Fernerkundungsdaten ein Modell zur kleinräumigen Habitatpräferenz während der Brutzeit erstellen werden. Die in diesem Projekt gewonnenen Erkenntnisse sollen dabei helfen, Massnahmen für die Erhaltung und die Förderung dieser heimlichen Spechtart zu erarbeiten.

The population of the grey-headed woodpecker (Picus canus) in Switzerland has declined by two thirds since the 1990s, which is why it is now considered endangered in the national Red List. The causes of this significant population decline are unclear. To learn more about the habitat requirements of this elusive species, we tagged 55 grey-headed woodpecker individuals in the Swiss Jura mountains over a period of three years (2020-2022). In this report we present our approach to use telemetry data and high-resolution remote sensing data to model fine-scale habitat preferences of grey-headed woodpeckers during the breeding season. The use of high-density airborne laser scanning data will allow us to explore habitat preferences regarding vertical and horizontal forest structures, which are reportedly key variables for this species. The knowledge gained in this project will be used to help developing measures to protect and promote this species.

European grasslands face strong declines in extent and quality. Many grassland types are priority habitats for national and European conservation strategies. Countrywide, high spatial resolution maps of their distribution are often lacking. Here, we modelled the spatial distribution of 20 permanent grassland habitats at the level of phytosociological alliances across Switzerland at 10x10 m resolution. First, we applied ensemble models to provide distribution maps of the individual habitat types, using training data from various sources. Copernicus Sentinel satellite imagery and variables describing climate, soil and topography were used as predictors. The performance of these models was assessed based on the true skill statistics with a split-sampling of the data. Second, the individual maps were combined into countrywide maps of the most and second most likely habitat type, respectively, using an expert-based weighting approach. The performance of the combined map for the most likely habitat type was assessed via an independent testing dataset and a comparison of the predicted habitat-type proportions with extrapolations from field surveys. Most individual maps had useful to excellent predictive performance (TSS ≥ 0.6). For most grid cells in the combined maps, the most and second most likely habitat types were either ecologically closely related or representing two grassland types along a nutrient gradient. The same was true for omission errors. We found good agreement between the predicted and estimated proportions from field surveys. The area of raised bogs appears to be underestimated, while dry grasslands showed highest agreement. This work highlights the potential of earth observation data at fine spatial and temporal resolution to map habitats at broad scales, thereby providing the foundation for diverse conservation applications. A particular challenge remains in capturing the transition from nutrient-poor to nutrient-rich grasslands, which is highly important for biodiversity conservation.

Lebensraumkarten mit hoher thematischer und räumlicher Auflösung, die weiträumige Gebiete abdecken, sind grundlegende Instrumente für die Planung ökologischer Netzwerke und das Management von Biodiversität. Um eine Lebensraumkarte für die Schweiz zu erstellen, haben wir die besten verfügbaren räumlichen Daten und Verbreitungsmodelle in einer integrierten Methode zusammengeführt. Der Ansatz stützt sich auf die Segmentierung und Klassifizierung von Fernerkundungsdaten mit hoher räumlicher Auflösung, inklusive Orthobilder (1 m Auflösung) und Satellitenbilder von Planet (3 m Auflösung) und Sentinel-1 und -2 (10 m respektive 20 m Auflösung). 84 TypoCH Lebensräume in 32 Gruppen und 9 übergreifenden Klassen wurden schweizweit räumlich explizit mit feiner räumlicher und thematischer Auflösung kartiert. Die erstellte Karte ist im WSL-Datenportal EnviDat und auf map.geo.admin.ch frei zugänglich.

Habitat maps with high thematic and spatial resolution covering broad extents are fundamental tools for planning ecological networks and managing biodiversity. To produce a habitat map for Switzerland, we brought together the best available spatial data and distribution models in an integrated method. The approach is based on the segmentation and classification of remote sensing data with high spatial resolution. 84 TypoCH habitats in 32 groups and 9 overarching classes were mapped in a spatially explicit manner for Switzerland. The map produced is freely accessible on the WSL data portal EnviDat and map.geo.admin.ch.

Habitat maps at high thematic and spatial resolution and broad extents are fundamental tools for biodiversity conservation, the planning of ecological networks and the management of ecosystem services. To derive a habitat map for Switzerland, we used a composite methodology bringing together the best available spatial data and distribution models. The approach relies on the segmentation and classification of high spatial resolution (1 m) aerial imagery. Land cover data, as well as habitat and species distribution models built on Earth observation data from Sentinel 1 and 2, Landsat, Planetscope and LiDAR, inform the rule-based classification to habitats defined by the hierarchical Swiss Habitat Typology (TypoCH). A total of 84 habitats in 32 groups and 9 overarching classes are mapped in a spatially explicit manner across Switzerland. Validation and plausibility analysis with four independent datasets show that the mapping is broadly plausible, with good accuracy for most habitats, although with lower performance for fine-scale and linear habitats, habitats with restricted geographical distributions and those predominantly characterised by understorey species, especially forest habitats. The resulting map is a vector dataset available for interactive viewing and download from open EnviDat data sharing platform. The methodology is semi-automated to allow for updates over time.

Forest models are instrumental for understanding and projecting the impact of climate change on forests. A considerable number of forest models have been developed in the last decades. However, few systematic and comprehensive model comparisons have been performed in Europe that combine an evaluation of modelled carbon and water fluxes and forest structure. We evaluate 13 widely used, state-of-the-art, stand-scale forest models against field measurements of forest structure and eddy-covariance data of carbon and water fluxes over multiple decades across an environmental gradient at nine typical European forest stands. We test the models' performance in three dimensions: accuracy of local predictions (agreement of modelled and observed annual data), realism of environmental responses (agreement of modelled and observed responses of daily gross primary productivity to temperature, radiation and vapour pressure deficit) and general applicability (proportion of European tree species covered). We find that multiple models are available that excel according to our three dimensions of model performance. For the accuracy of local predictions, variables related to forest structure have lower random and systematic errors than annual carbon and water flux variables. Moreover, the multi-model ensemble mean provided overall more realistic daily productivity responses to environmental drivers across all sites than any single individual model. The general applicability of the models is high, as almost all models are currently able to cover Europe's common tree species. We show that forest models complement each other in their response to environmental drivers and that there are several cases in which individual models outperform the model ensemble. Our framework provides a first step to capturing essential differences between forest models that go beyond the most commonly used accuracy of predictions. Overall, this study provides a point of reference for future model work aimed at predicting climate impacts and supporting climate mitigation and adaptation measures in forests.

Agricultural landscapes support multiple functions and are of great importance for biodiversity. Heterogeneous agricultural mosaics of cropland and grassland commonly result from variable land use practices and ecosystem service demands. Switzerland's agricultural land use is considerably spatially heterogeneous due to strong variability in conditions, especially topography and climate, thus presenting challenges to automated agricultural mapping. Nationwide knowledge of the location of cropland and grassland is necessary for effective conservation and land use planning. We mapped the distribution of cropland and permanent grassland across Switzerland. We used several indices largely derived from Sentinel-2 satellite imagery captured over multiple growing seasons and parcel-based training data derived from landholder reporting. The mapping was conducted within Google Earth Engine using a random forest classifier. The resulting map has high accuracy in lowlands as well as in mountainous areas. The map will act as a base agricultural land cover dataset for researchers and practitioners working in agricultural areas of Switzerland and interested in land cover and landscape structure. The map as well as the training data and calculation algorithms (using Google Earth Engine) are freely available for download on the EnviDat platform https://doi.org/10.16904/envidat.205 (Pazúr et al., 2021).

The increasing impacts of climate change on forest ecosystems have triggered multiple model-based impact assessments for the future, which typically focused either on a small number of stand-scale case studies or on large scale analyses (i.e., continental to global). Therefore, substantial uncertainty remains regarding the local impacts over large areas (i.e., regions to countries), which is particularly problematic for forest management. We provide a comprehensive, high-resolution assessment of the climate change sensitivity of managed Swiss forests (~10,000 km²), which cover a wide range of environmental conditions. We used a dynamic vegetation model to project the development of typical forest stands derived from a stratification of the Third National Forest Inventory until the end of the 22^nd century. Two types of simulations were conducted: one limited to using the extant local species, the other enabling immigration of potentially more climate-adapted species. Moreover, to assess the robustness of our projections, we quantified and decomposed the uncertainty in model projections resulting from the following sources: (1) climate change scenarios, (2) local site conditions, and (3) the dynamic vegetation model itself (i.e., represented by a set of model versions), an aspect hitherto rarely taken into account. The simulations showed substantial changes in basal area and species composition, with dissimilar sensitivity to climate change across and within elevation zones. Higher-elevation stands generally profited from increased temperature, but soil conditions strongly modulated this response. Low-elevation stands were increasingly subject to drought, with strong negative impacts on forest growth. Furthermore, current stand structure had a strong effect on the simulated response. The admixture of drought-tolerant species was found advisable across all elevations to mitigate future adverse climate-induced effects. The largest uncertainty in model projections was associated with climate change scenarios. Uncertainty induced by the model version was generally largest where overall simulated climate change impacts were small, thus corroborating the utility of the model for making projections into the future. Yet, the large influence of both site conditions and the model version on some of the projections indicates that uncertainty sources other than climate change scenarios need to be considered in climate change impact assessments.

In der Schweiz gibt es zahlreiche unterschiedliche Lebensräume. Die WSL hat eine digitale Verbreitungskarte erstellt.

En Suisse, il existe d'innombrables milieux naturels différents, dont l'Institut fédéral de recherches sur la forêt, la neige et le paysage (WSL) a dressé une carte synoptique numérique.

Im naturnahen Waldbau liegt der Schwerpunkt auf Beständen mit mehreren Baumarten und einer stufigen Struktur. Um deren zukünftige Entwicklung abzuschätzen, sind dynamische Modelle nützlich. Mit der Familie der Gap-Modelle, die ursprünglich aus der Ökologie stammen, sind solche Analysen möglich. Am Beispiel des Modells ForClim wird aufgezeigt, wie diese Modelle strukturiert sind, wie sie eingesetzt werden können und wo ihre Grenzen liegen. Anhand einer Stratifizierung der schweizerischen Waldfläche nach Standortregion, Höhenstufe, Struktur und Baumartenzusammensetzung wurden 71 typische Bestände (Straten) hergeleitet. Für jedes Stratum wurden Simulationen mit vier Klimaszenarien, zwei verschiedenen Annahmen über die Bodeneigenschaften sowie acht Modellvarianten durchgeführt. Letzteres erfolgte, weil bisher weitgehend unbekannt war, wie stark sich die Unsicherheiten in den Modellformulierungen auf die Simulationsergebnisse auswirken. Die Simulationsergebnisse zeigen ein regional und nach Höhenstufen differenziertes Bild, mit teils starken Veränderungen der Bestandesgrundfläche und der Artenzusammensetzung. Je nach Stratum waren bei den einzelnen Arten Abnahmen oder Zunahmen zu verzeichnen. Die Bodeneigenschaften erwiesen sich als sehr wichtig, überraschenderweise auch in der subalpinen und der obersubalpinen Stufe. Die Unsicherheiten in den Modellformulierungen beeinflussen die Simulationsergebnisse nicht wesentlich, d.h., das Modellverhalten ist robust. Die Ergebnisse der einzelnen Straten können für die waldbauliche Planung auf der betrieblichen oder überbetrieblichen Ebene verwendet werden. Sie liefern zwar keine handfesten Empfehlungen für die zukünftige Bewirtschaftung der konkreten Bestände (d.h., sie sollen nicht wörtlich genommen werden), verdienen es aber, ernst genommen zu werden, da sie Trends in der zukünftigen Entwicklung aufzuzeigen vermögen.

Close-to-nature silviculture is emphasizing mixed-species, multi-layered stands. Dynamic models are appropriate tools for estimating their future development. Specifically, the family of gap models, which originate from ecology, renders such analyses possible. We use the example of the ForClim model to illustrate how these models are structured, how they can be used, and where their limits lie. Based on a stratification of the Swiss forest area, 71 typical stands (strata) were derived, differentiated according to location region, elevational level, structure and tree species composition. For each stratum, simulations were carried out with four climate scen arios, two different assumptions about soil properties and eight model variants. The latter was done because it was largely unknown to what extent the uncertainties in the model formulations affect the simulation results. Simulation results show a regionally and elevationally differentiated picture, partly with strong changes of stand basal area and species composition. Depending on the stratum, increases or decreases were recorded. Soil properties proved to be quite important, surprisingly also in the subalpine and upper subalpine zones. Uncertainties in the model formulations do not considerably influence simulation results, i.e. model behaviour is robust. The results of the individual strata can be used for forest management planning at the operational or regional level. Although they do not provide any firm recommendations for the future management of specific stands (i.e., they should not be taken literally), they deserve to be taken seriously as they are able to show trends of future forest development.

The study of population dynamics and species–habitat interactions is important for many ecological and conservation issues. We analysed the occupancy dynamics of the Wood Warbler Phylloscopus sibilatrix, a forest interior passerine that has suffered long-term declines in many European countries. Considering a broad range of habitat descriptors, including LiDAR-based variables characterizing forest structure, we identified environmental factors influencing the probabilities of occupancy, colonization, extinction and detection, and mapped these probabilities at a landscape scale. We used presence–absence data collected between 1999 and 2013 in a robust-design protocol with replicated surveys within each primary sampling season (i.e. breeding season). To analyse occupancy dynamics, we fitted dynamic occupancy models with covariates describing topography, forest extent and structure, soil, seed masting (as a proxy for rodent abundance) and weather conditions during settlement. Initial occupancy was positively related to slope, forest cover and the proportion of broadleaf forest, and negatively related to forest edge length, canopy height variation and soil nutrients. Colonization probability was positively associated with slope and negatively with canopy height variation and soil nutrients. Extinction probability was negatively related to slope, positively related to forest edge length and was lowest at intermediate vegetation heights. Detection probability decreased during the season and was positively related to forest cover. This study provides insights into the settlement dynamics of a declining forest species by identifying potential drivers of the processes underlying occupancy dynamics, instead of simply modelling species abundance or occurrence. Forest-related covariates were of overwhelming importance for the settlement dynamics of the Wood Warbler. Conservation measures should focus on providing and maintaining the species' preferred forest structure, specifically in extended forests. In Switzerland, forests located on slopes and on nutrient-poor soils should be prioritized for conservation. Finally, comparing findings derived from the relatively coarse scale of this study with those from the small scale of individual territories suggests that conservation recommendations deduced from largescale monitoring schemes alone may be incomplete, and vice versa.

Replacement of conventional energy sources with renewables such as solar panels and wind turbines requires adequate land. Impact assessments should be conducted to identify sites exhibiting least conflict with current and future land-uses and corresponding ecosystem services. We assessed the electricity potential and geographical distribution of wind turbines and solar panels for current land-use and under three Swiss land-change scenarios. The future scenario A2 with limited construction regulations, a liberalized market and more building surfaces increases the electricity potential of solar panels by 69% from 16.6 TWh (potential under current land-use and regulations) to a future 28.2 TWh. An increase of approximately 26% electricity potential from solar panels is expected for scenario B2 (regionalized economy) and the trend scenario. Wind-electricity potential could increase by 61% from 93 to 150 TWh under A2, and 29% under a B2 or trend scenario. The electricity potential for solar panels remains largely unaffected by conflicts with ecosystem services, but electricity production from wind could be reduced by as much as 98% due to conflicts with ecosystem services. Depending on the scenario used, low-conflict sites for solar panels and wind turbines could contribute between 85% (trend and B2 scenario) and >100% (A2 scenario) to the Swiss energy target of generating 25 TWh from new renewable energy sources by 2050. This includes expected technological developments. Positive impacts of sustainable energy production on regional economies are moderate and will not lead to strong changes in regional-economic development.

Context. Detailed information on habitat needs is integral to identify conservation measures for declining species. However, field data on habitat structure is typically limited in extent. Remote sensing has the potential to overcome these limitations of field-based studies.
Objective. We aimed to assess abiotic and biotic characteristics of territories used by the declining wood warbler (Phylloscopus sibilatrix), a forest-interior migratory passerine, at two spatial scales by evaluating a priori expectations of habitat selection patterns.
Methods. First, territories established by males before pairing, referred to as pre-breeding territories, were compared to pseudo-absence control areas located in the wider forested landscape (first spatial scale, N_territories = 66, N_controls = 66). Second, breeding territories of paired wood warblers were compared to true-absence control areas located immediately close-by in the forest (second spatial scale, N_territories = 78, N_controls = 78). Habitat variables predominantly described forest structure and were mainly based on first and last pulse lidar (light detection and ranging) data.
Results. Occurrence of pre-breeding territories was related to vegetation height, vertical diversity and stratification, canopy cover, inclination and solar radiation. Occurrence of breeding territories was associated to vegetation height, vertical diversity and inclination.
Conclusions. Territory selection at the two spatial scales addressed was governed by similar factors. With respect to conservation, habitat suitability for wood warblers could be retained by maintaining a shifting mosaic of stand ages and structures at large spatial scales. Moreover, leaf-off lidar variables have the potential to contribute to understanding the ecological niche of species in predominantly deciduous forests.