A5031627703- Species Distribution and Climate Change
- Ecology and Vegetation Dynamics Studies
- Plant and animal studies
- Wildlife Ecology and Conservation
- Plant Water Relations and Carbon Dynamics
- Genetic diversity and population structure
- Forest ecology and management
- Land Use and Ecosystem Services
- Remote Sensing in Agriculture
- Climate variability and models
- Botany and Plant Ecology Studies
- Tree-ring climate responses
- Forest Management and Policy
- Cryospheric studies and observations
- Atmospheric and Environmental Gas Dynamics
- Fire effects on ecosystems
- Plant Diversity and Evolution
- Geology and Paleoclimatology Research
- Remote Sensing and LiDAR Applications
- Meteorological Phenomena and Simulations
- Climate change and permafrost
- Forest Insect Ecology and Management
- Lichen and fungal ecology
- Evolution and Paleontology Studies
- Peatlands and Wetlands Ecology
Swiss Federal Institute for Forest, Snow and Landscape Research
2016-2025
ETH Zurich
2016-2025
Board of the Swiss Federal Institutes of Technology
2024
Poznan School of Logistics
2022
Schlumberger (British Virgin Islands)
2021
ORCID
2021
John Wiley & Sons (United States)
2019
Ecosystem Sciences
2019
Norwegian Biodiversity Information Centre
2019
Ecological Society of America
2019
Prediction of species’ distributions is central to diverse applications in ecology, evolution and conservation science. There increasing electronic access vast sets occurrence records museums herbaria, yet little effective guidance on how best use this information the context numerous approaches for modelling distributions. To meet need, we compared 16 methods over 226 species from 6 regions world, creating most comprehensive set model comparisons date. We used presence‐only data fit models,...
Abstract We present new global maps of the Köppen-Geiger climate classification at an unprecedented 1-km resolution for present-day (1980–2016) and projected future conditions (2071–2100) under change. The map is derived from ensemble four high-resolution, topographically-corrected climatic maps. 32 model projections (scenario RCP8.5), by superimposing change anomaly on baseline high-resolution For both time periods we calculate confidence levels spread, providing valuable indications...
High resolution information on climatic conditions is essential to many applications in environmental and ecological sciences. Here we present the CHELSA Climatologies at high for earths land surface areas data of downscaled model output temperature precipitation estimates ERA Interim reanalysis a 30 arc seconds. The algorithm based statistical downscaling atmospheric temperatures. incorporates orographic predictors including wind fields, valley exposition, boundary layer height with...
ABSTRACT Aim Concerns over how global change will influence species distributions, in conjunction with increased emphasis on understanding niche dynamics evolutionary and community contexts, highlight the growing need for robust methods to quantify differences between or within taxa. We propose a statistical framework describe compare environmental niches from occurrence spatial data. Location Europe, North America South America. Methods The applies kernel smoothers densities of gridded...
Abstract Aim To assess the geographical transferability of niche‐based species distribution models fitted with two modelling techniques. Location Two distinct study areas in Switzerland and Austria, subalpine alpine belts. Methods Generalized linear generalized additive (GLM GAM) a binomial probability logit link were for 54 plant species, based on topoclimatic predictor variables. These then evaluated quantitatively used spatially explicit predictions within (internal evaluation prediction)...
Species distribution models (SDMs) constitute the most common class of across ecology, evolution and conservation. The advent ready‐to‐use software packages increasing availability digital geoinformation have considerably assisted application SDMs in past decade, greatly enabling their broader use for informing conservation management, quantifying impacts from global change. However, must be fit purpose, with all important aspects development applications properly considered. Despite...
Species distribution models (SDMs) are widely used to explain and predict species ranges environmental niches. They most commonly constructed by inferring species' occurrence–environment relationships using statistical machine‐learning methods. The variety of methods that can be construct SDMs (e.g. generalized linear/additive models, tree‐based maximum entropy, etc.), the ways such implemented, permits substantial flexibility in SDM complexity. Building with an appropriate amount complexity...
Abstract Questions: Did the forest area in Swiss Alps increase between 1985 and 1997? Does expansion near tree line represent an invasion into abandoned grasslands (ingrowth) or a true upward shift of local line? What land cover / use classes did primarily regenerate to forest, what structural types regenerate? And, are possible drivers regeneration ecotone, climate and/or change? Location: Alps. Methods: Forest was quantified using data from repeated statistics GEOSTAT. A moving window...
Continental-scale assessments of 21st century global impacts climate change on biodiversity have forecasted range contractions for many species. These coarse resolution studies are, however, limited relevance projecting risks to in mountain systems, where pronounced microclimatic variation could allow species persist locally, and are ill-suited assessment species-specific threat particular regions. Here, we assess the 2632 plant across all major European ranges, using high-resolution (ca....
Abstract Mountain ecosystems will likely be affected by global warming during the 21st century, with substantial biodiversity loss predicted species distribution models (SDMs). Depending on geographic extent, elevation range, and spatial resolution of data used in making these models, different rates habitat have been predicted, associated risk extinction. Few coordinated across‐scale comparisons made using resolutions extents. Here, we assess whether climate change‐induced losses at...
Abstract: Because data on rare species usually are sparse, it is important to have efficient ways sample additional data. Traditional sampling approaches of limited value for because a very large proportion randomly chosen sites unlikely shelter the species. For these species, spatial predictions from niche‐based distribution models can be used stratify and increase efficiency. New sampled then improve initial model. Applying this approach repeatedly an adaptive process that may allow...
Abstract A large array of species distribution model ( SDM ) approaches has been developed for explaining and predicting the occurrences individual or assemblages. Given wealth existing models, it is unclear which models perform best interpolation extrapolation data sets, particularly when one concerned with We compared predictive performance 33 variants 15 widely applied recently emerged s in context multispecies data, including both joint that multiple together, stacked each individually...