The focus of this analysis is on the early detection of forest health changes, specifically that of Norway spruce (Picea abies L. Karst.). In this analysis, we planned to examine the time (degree of early detection), spectral wavelengths and appropriate method for detecting vitality changes. To accomplish this, a ring-barking experiment with seven subsequent laboratory needle measurements was carried out in 2013 and 2014 in an area in southeastern Germany near Altötting. The experiment was also accompanied by visual crown condition assessment. In total, 140 spruce trees in groups of five were ring-barked with the same number of control trees in groups of five that were selected as reference trees in order to compare their development. The laboratory measurements were analysed regarding the separability of ring-barked and control samples using spectral reflectance, vegetation indices and derivative analysis. Subsequently, a random forest classifier for determining important spectral wavelength regions was applied. Results from the methods are consistent and showed a high importance of the visible (VIS) spectral region, very low importance of the near-infrared (NIR) and minor importance of the shortwave infrared (SWIR) spectral region. Using spectral reflectance data as well as indices, the earliest separation time was found to be 292 days after ring-barking. The derivative analysis showed that a significant separation was observed 152 days after ring-barking for six spectral features spread through VIS and SWIR. A significant separation was detected using a random forest classifier 292 days after ring-barking with 58% separability. The visual crown condition assessment was analysed regarding obvious changes of vitality and the first indication was observed 302 days after ring-barking as bark beetle infestation and yellowing of foliage in the ring-barked trees only. This experiment shows that an early detection, compared with visual crown assessment, is possible using the proposed methods for this specific data set. This study will contribute to ongoing research for early detection of vitality changes that will support foresters and decision makers.

Climate change can have severe impacts on tree species distributions. Models consistently show that tree species will follow climate towards higher elevations and latitudes. This has various effects on forest ecosystems. Forests have a slow dynamic compared to other ecosystems and are affected severely by tree species distribution shifts. Forested conservation areas with limited management reveal a slow adaptation process to a changing climate. In this study, we have modelled and analysed the effect of possible tree species distribution shift in Norway spruce (Picea abies), European beech (Fagus sylvatica), and two oak species (Quercus petraea and Quercus robur), considered jointly on forested Natura 2000 sites, an EU-wide conservation area network. The modelling procedure was performed using 3 to 4 bio-climatic variables derived from 26 variables of the EURO-CORDEX Coupled Model Intercomparison Project Phase 5 (CMIP5) climate simulations for the Representative Concentration Pathways (RCPs) 2.6, 4.5, and 8.5 until 2098. Our results reveal a severe decline in Picea within Natura 2000 sites in central Europe and lower elevations and confirm a strong shift towards higher elevations and latitudes. This amounts to an 18 % absolute mean change (−18 % mean loss, 15 % mean gain). Quercus sp. reveal similar results, with 23 % absolute mean change (−23 % loss, 24 % gain) at Natura 2000 sites, whereas Fagus remains stable throughout the model results with 8 % absolute mean change (−7 % loss, 9 % gain). The best model algorithms for all species were the generalised additive models (GAMs). As ecosystems of any type are highly dynamic, climate change can lead to additional severe pressure on statically defined conservation goals and associated management activities.

Ongoing ecological research is concerned with analysing climate-induced changes in species distribution. For this purpose, the projection must have high-quality bioclimatic variables from historical and future climatic periods for the projection. To date, there are many global bioclimatic variables on this topic. Nevertheless, a consistent dataset with identical model variables from historic and projected periods is rare. We present 26 bioclimatic variables that are calculated based on a large ensemble consisting of 70 bias-adjusted GCM-RCM simulations for 1971–2098. Both, the historic and the projection periods were calculated using the same models to ensure consistency between the periods. The variables are validated against E-OBS observations from which we calculated the same bioclimatic variables. For projection periods we chose 20 year ranges between 2021–2098. Here, we offer two versions of them: (1) variables separated into RCP 2.6, 4.5 and 8.5, including percentiles among the realisations and within the RCPs; and (2) variables per realisation separately. We then extracted the temporal 5th, 50th and 95th percentile per period as representing values.

The climate crisis leads to a change in forest tree species distributions, favouring most likely heat and drought tolerant species. As a consequence, many forest sites across Europe will become unsuitable for drought sensitive species. The combination of climate change and conservation goals of Natura2000 forest habitat types will lead to severe conflicts in conservation and forestry. The concept of “no deterioration” in article 6 of the Habitats Directive supports a static conservation of the prevalent flora and fauna. In those areas forestry is oriented towards conservation of natural forest habitat types. Especially areas with reduced silvicultural activities or strict silvicultural requirements, such as Natura 2000 sites, are prone to a long forest conversion process towards more suitable tree species. As forestry is based on long-term life cycles, this development will impact forest condition, forest cover, silviculture and conservation negatively. The Natura2000 legislation is under pressure.This study aims at analysing (1) the changes of future tree species ranges in Europe, (2) how severe changes will impact current natural forest habitat types of Natura 2000 sites and (3) which new tree species might be present in future climate scenarios. We selected a combination of generalised additive models, generalised linear models and boosted regression trees for the modelling process. As model input serve four preselected bio-climatic variables from a total of 26 bio-climatic variables, derived from EURO-CORDEX CMIP5 climate simulations for 1971-2098 for IPCC’s representative concentration pathways 2.6, 4.5 and 8.5. JRC soil characteristics and JRC European tree species data serve as additional input variables. Potential tree species ranges with 1km spatial resolution as model outcome is compared to current definition of natural forest habitat types of Natura 2000 sites. This allows conclusions about their potential future occurrence and endangered static protection state. Most tree species reveals a severe decline of suitable ranges in all RCP scenarios and range shift towards polwards regions and higher elevations. As a consequence protection goals of forest Natura 2000 areas are at stake.