Environmental Science workshops

Design restoration projects using ecological principles and the Society for Ecological Restoration standards. Case studies connect limiting factors, community assembly and reference ecosystems with diagnoses of degradation, project objectives and intervention choices. Participants compare passive and active restoration, monitoring and adaptive management, ecological recovery indicators and public participation. Collaborative exercises culminate in proposing restoration of a degraded ecosystem and explaining its expected societal and ecological benefits. Live sessions: 26 and 29 October; 2, 5, 9, 12 and 16 November, 15:00–18:00, Europe/Madrid (CET, UTC+01:00). Total 28 hours: 21 live plus seven independent. English-language live online course; Fee €530; Ambassador Institution rate €424. VAT included. Capacity: 16. Basic ecology and a graduate or postgraduate Life Sciences or related degree are expected. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

Build reproducible marine analyses by combining habitat, oceanographic, biodiversity and human-activity data in R. Practical sessions work with bathymetry and benthic habitats, three-dimensional and time-varying ocean observations, species records and distribution resources, animal movements and fisheries data. Participants connect these sources with marine protected areas and jurisdictional boundaries to address conservation and spatial-planning questions. Sessions: 3–6 November, 15:00–18:00 each day, Europe/Berlin (CET, UTC+01:00). Live online training; fee €430. Basic R knowledge is required; aimed at marine researchers and conservation practitioners.

Turn multispectral, hyperspectral and lidar observations into analysis-ready datasets with R. Using forest and ecological examples, participants assess metadata and data quality, correct geometric and radiometric errors, reduce noise, and derive spectral indices and structural features. Exercises connect temporal change analysis and classification with scale, accuracy and uncertainty, producing reproducible workflows for spatial research. 2026-11-10–2026-11-13, 12:00–16:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €420. Participants need basic competence and confidence in R and RStudio; prior remote-sensing experience is optional.

Build reproducible maps and spatial analyses of biodiversity and environmental data using R’s terra package. Practical work covers vector and raster data, projections, thematic and interactive maps, spatial queries, geometry operations and layer transformations. Participants calculate distances, buffers and home ranges, examine terrain and spatial autocorrelation, and combine raster and vector information through extraction, interpolation, map algebra and zonal statistics. Demonstrations and supervised exercises support automated workflows for research datasets; participants may bring their own spatial data. 23–27 November 2026, daily 15:00–18:00, Europe/Madrid (CET, UTC+1). Fifteen live hours plus 20 hours of exercises; instructor consultations 09:00–21:00. Spoken Spanish with English slides and scripts; prior R experience required. Sixteen places. Regular fee EUR 485, or EUR 388 for Ambassador Institutions. Live attendance is required for the certificate. Payment follows acceptance; advertised fees include VAT.

Estimate species occurrence while accounting for imperfect detection. Participants prepare repeated survey histories, distinguish occupancy from observation processes and fit single-season models with ecological and survey covariates. Exercises compare two-stage estimation in tsoccu with likelihood-based analysis in unmarked, then develop predictions, uncertainty estimates, diagnostics and reproducible reporting. The final day introduces dynamic, multispecies, spatial and false-positive extensions through ecological applications. Sessions: 1–4 December, 09:00–13:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €420. No prior occupancy-modelling experience is required; practical work is in R.

Growing transport demand and decarbonisation targets motivate new approaches to ground improvement and reuse of industrial waste. This workshop examines how recycled rubber, plastics, glass, fly ash and slag can improve infrastructure performance while reducing demand for virgin materials. Research and engineering case studies combine laboratory characterisation, computational modelling, bio-mediated treatment, fatigue and dynamic-load analysis, and lifecycle assessment. AI applications address hazard assessment, predictive monitoring, ground-engineering workflows and material behaviour. Three technical sessions examine sustainable ground improvement, circular use of waste and marginal materials, and the responsible application of AI. The programme on 2 December 2026 includes presentations, facilitated discussion and networking. Registration and refreshments begin at 07:45, opening addresses at 08:30 and research presentations at 08:45; closing remarks are at 17:30, followed by networking cocktails. Times are AEDT (Australia/Sydney). Researchers, engineers, industry and government participants, and postgraduate students are welcome. Early-bird tickets are AUD363 general admission or AUD253 for students, including GST, through 1 November; booking fees may apply. Refund requests are accepted through 15 November.

Learn regression models that estimate nonlinear relationships from data using splines. Starting from generalised linear models, the course develops fitting and visualisation with mgcv and gratia, explains how smoothing controls overfitting, and covers model checking, selection and inference. Further exercises introduce interacting smooths, hierarchical models with group and individual effects, and posterior simulation, using ecological and environmental examples. Sessions: 7–10 December, 14:00–20:00 daily, Europe/Berlin (CET, UTC+01:00). Live online training; fee €480. R/RStudio fluency is required. Familiarity with generalised linear models and fixed/random effects is useful.

Build and evaluate short-term ecological forecasts by repeatedly linking observations, models and predictions. A biodiversity challenge uses shrub, rabbit and dung-beetle data from Doñana with remote-sensing measurements. Participants process time series and satellite indices, compare autoregressive, hierarchical, correlational and mechanistic models, propagate uncertainty and assess forecasts against benchmarks. Reproducible R workflows lead to a submitted forecast and discussion of how predictions support conservation and adaptive management. Live sessions: 25–29 January, 14:00–18:30 daily, Europe/Madrid (CET, UTC+01:00). Total 27.5 hours: 22.5 live plus five independent. English-language live online course; Fee €236 until 30 November, then €290; Ambassador rates €188.80/€232. VAT included. Capacity: 25. Basic R and an ecology or environmental-science background are required; forecasting experience is unnecessary. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

Build and evaluate correlative species-distribution and ecological-niche models with R. The course connects niche theory with occurrence-data quality, environmental predictors, model fitting and validation, then examines spatial and temporal projections and their limitations. Participants learn to recognize common modelling pitfalls, automate reproducible analyses and apply workflows to example or personal species datasets. 2027-02-01–2027-02-05, 15:00–18:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €480. Basic R knowledge is strongly recommended. Live classes are complemented by about four hours of independent work daily and annotated scripts, with remote support available between 09:00 and 23:00 Berlin time.

Design and analyse environmental-DNA metabarcoding studies with portable Nanopore sequencing. The workshop links field sampling, contamination controls, extraction and PCR to barcoding, library preparation and sequencing. Guided bioinformatics practicals cover basecalling, demultiplexing, filtering, clustering and taxonomic assignment before analysing biodiversity patterns in R. Participants compare alpha and beta diversity and ordination methods, while learning how laboratory choices and sequencing errors affect ecological interpretation. Live online, 2–4 February, 14:00–18:00 Europe/Berlin (CET). Fee €380. Intended for researchers, ecologists and bioinformaticians planning biodiversity assessments or developing metabarcoding workflows.

This course develops a species-distribution modelling workflow using Bayesian additive regression trees. Participants compare BART with other modelling approaches and use the R packages embarcadero and dbarts to choose environmental predictors, train and evaluate occurrence models, and predict presence or absence in new places or periods. The programme introduces Bayesian regression and boosted trees, then examines predictor effects, interactions, spatial effects and random-intercept BART models, with practical troubleshooting and interpretation. Live online teaching takes place from 15:00 to 18:00 Berlin time (CET, UTC+1) on 9–11 February 2027. The programme also specifies four additional hours of independent practical work using annotated R scripts and online support. Advanced students, researchers and practitioners should already know the basics of species-distribution modelling and be comfortable using RStudio, installing packages and editing simple scripts. A laptop, webcam and reliable internet connection are required. The standalone course fee is EUR 390.

Participants turn GEDI spaceborne LiDAR footprints into maps useful for ecological research. The course covers waveform and product interpretation, data-quality filtering and QGIS workflows, followed by models combining GEDI measurements with multispectral, radar and geospatial foundation-model predictors. Practical work produces continuous estimates of canopy structure and biomass with uncertainty, then explores forest disturbance, recovery and species distribution modelling in R. Live teaching runs 14:00–17:00 Berlin time. The listed course package costs €380.

The workshop examines environmental governance and social sustainability in astronomy, bringing early-career researchers together with scientific leaders. Discussion covers data-intensive research and AI, measures of scientific success, observatory design and resource use. Talks are combined with practical work on life-cycle assessment and engagement concerning dark and quiet skies. The aim is to develop a shared account of sustainable astronomy and practical recommendations for researchers and decision-makers.