Mapping carbon sequestration in forests at the regional scale - a climate biomonitoring approach by example of Germany

Background

The United Nations Framework Convention on Climate Change recognizes carbon (C) fixation in forests as an important contribution for the reduction of atmospheric pollution in terms of greenhouse gases. Spatial differentiation of C sequestration in forests either at the national or at the regional scale is therefore needed for forest planning purposes. Hence, within the framework of the Forest Focus regulation, the aim of this investigation was to statistically analyse factors influencing the C fixation and to use the corresponding associations in terms of a predictive mapping approach at the regional scale by example of the German federal state North Rhine-Westphalia. The results of the methodical scheme outlined in this article should be compared with an already-published approach applied to the same data which were used in the investigation at hand.

Methods

Site-specific data on C sequestration in humus, forest trees/dead wood and soil from two forest monitoring networks were intersected with available surface information on topography, soil, climate and forestal growing areas and districts. Next, the association between the C sequestration and the influence factors were examined and modelled by linear regression analyses. The resulting regression equations were applied on the surface data to predicatively map the C sequestration for the entire study area.

Results

The computations yielded an estimation of 146.7 mio t C sequestered in the forests of North Rhine-Westphalia corresponding to 168.6 t/ha. The calculated values correspond well to according specifications given by the literature. Furthermore, the results are almost identical to those of another pilot study where a different statistical methodology was applied on the same database. Nevertheless, the underlying regression models contribute only a low degree of explanation to the overall variance of the C fixation. This might mainly be due to data quality aspects and missing influence factors in the analyses.

Discussion

In another study, an alternative approach was introduced to map the spatial differentiation of C sequestration in North Rhine-Westphalia based on the combination of geostatistics, decision tree analyses and GIS techniques. As a result, the overall mean of C sequestration amounted for 177 t C/ha which is 8.4 t C/ha higher than what was calculated in the study at hand and 14 t C/ha below the roughly guessed German-wide mean of 191 t C/ha.

Conclusions

The surface estimations of C pools in living forest trees/dead wood, the humus layer and the mineral soil enable to map the fixation of the greenhouse gas CO₂ in forests at the regional scale. The estimations that were derived in this study are in good accordance with estimations based on techniques which, in contrast, did neither allow for spatial differentiation nor for mapping. The presented approach should be validated by application of other statistical techniques and by use of German wide inventory data. Furthermore, C sequestration should be modelled according to different climate change scenarios by combining statistical methods and dynamic modelling.