Robust Modelling of the Impacts of Climate Change on the Habitat Suitability of Forest Tree Species
de Rigo, D., Caudullo, G., San-Miguel-Ayanz, J, Barredo, J.I., 2017. Robust modelling of the impacts of climate change on the habitat suitability of forest tree species. Publication Office of the European Union, 58 pp. ISBN:978-92-79-66704-6 , doi/10.2760/296501
58 Pages Posted: 5 May 2017
Date Written: March 15, 2017
Abstract
In Europe, forests play a strategic multifunctional role, serving economic, social and environmental purposes. However, forests are among the most complex systems and their interaction with the ongoing climate change – and the multifaceted chain of potential cascading consequences for European biodiversity, environment, society and economy – is not yet well understood.
The JRC PESETA project series proposes a consistent multi-sectoral assessment of the impacts of climate change in Europe. Within the PESETA II project, a robust methodology is introduced for modelling the habitat suitability of forest tree species (2071-2100 time horizon). Abies alba (the silver fir) is selected as a case study: a main European tree species often distributed in bioclimatically complex areas, spanning over various forest types and with multiple populations adapted to different conditions.
The modular modelling architecture is based on relative distance similarity (RDS) estimates which link field observations with bioclimatic patterns, projecting their change under climate scenarios into the expected potential change of suitable habitat for tree species. Robust management of uncertainty is also examined. Both technical and interpretation core aspects are presented in an integrated overview. The semantics of the array of quantities under focus and the uneven sources of uncertainty at the continental scale are discussed (following the semantic array programming paradigm), with an effort to offer some minimal guidance on terminology, meaning and methodological limitations not only of the proposed approach, but also of the broad available literature – whose heterogeneity and partial ambiguity might potentially reverberate at the science-policy interface.
Note: © European Union, 2017 The reuse of the document is authorised, provided the source is acknowledged and the original meaning or message of the texts are not distorted. The European Commission shall not be held liable for any consequences stemming from the reuse.
Keywords: Abies alba, ANN, climate change, diversity, Europe, forest resources, free software, fuzzy, GDAL, GNU bash, GNU/Linux, GNU Octave, integrated modelling, Mastrave modelling library, Maximum Habitat Suitability, Relative Distance Similarity, robust modelling, Semantic Array Programming, uncertainty
JEL Classification: C02, C31, C45, C6, Q2, Q23, Q5, Q54, Q57
Suggested Citation: Suggested Citation