sMon - Analysing trends in German species data

Collage Deutschland (c) D. Eichenberg, J. Dengler
Collage Deutschland (c) D. Eichenberg, J. Dengler

date: 27.-28.11.2017

PIs: Florian Jansen; Aletta Bonn; Helge Bruelheide

associated postdoc: David Eichenberg

sMon is a two-year Synthesis Project of the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. We aim at combining and harmonizing exemplary datasets of different taxa and habitats and to evaluate the potentials and limits for analysing changes in the state of biodiversity  in Germany. based on these insights, we will derive perspective for future biodiversity monitoring programs in Germany.

Motivation

  • Many species in Germany are are  threatened  or endangered and many indicators point at an progressive loss in species occurrences and/or abundances 
  • statistically sound data for changes in biodiversity is lacking for most species grooups in Germany or such information is only available in coarse scales

Aims

  • Screening, harmonizing and integrating heterogeneous time series data from different sources and from exemplary species groups (e.g. vascular plants, amphibians, orthopterans)
  • Development of statistical methods to derive statistically sound trends for species from these taxa based on this heterogeneous data
  • Assisting in the indentification of statistical cornerstones for the collection of biodiversity data within an efficient future biodiversity monitoring scheme in Germany

Methods

  • We will focus on data from federal agencies, nature conservation organisations and professional societies for the exemplay taxa as well as scientific institutions
  • we will carry out exemplary time-series analyses Exemplarische Zeitreihenanalysen based on non-systematic, non- random and potentially spatially and temporally misaligned species-observation data. Here, we will account for the heterogeneity in the methods and the origin of the data. Moreover, we will try to integrate potential drivers for the changes in biodiversity data
  • We will identify gaps in existing data and assist in developping potential improvements for future data assessment
  • In cooperation with stakeholders from a variety of organisations and experts in data analysis, we will organize two or more sDiv-Workshops to bring together a broad spectrum of knowledge and expertise

 

Poster of an exemplary analysis of vegetation data in Mecklenburg-Vorpommern (Presented at the "Ecology across Borders" conference 2017 in Ghent (BES/GfÖ/NECOV/EEF)

 

Contact

Dr. David Eichenberg
david.eichenberg@idiv.de

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