Part 2 Progress in Biodiversity Modelling
3 Critical Loads for Plant Species Diversity
3.7 Robustness analysis of exceedances of ECLAIRE scenarios for N-S critical loads
Both the critical loads for biodiversity (CLbio) and the acidity critical loads (CLaci) depend on N and S depositions, i.e. they are characterized by a critical load function. It is therefore of interest to compare these two N-S CLs, and respectively their exceedances. While the exceedances of CLbio for four ECLAIRE scenarios are shown in Figure 3.7, the corresponding exceedances of CLaci, taken from the European background database for all countries (see Chapter 2), are shown in Figure 3.8. And in Table 3.1, the exceeded areas under the four scenarios are listed for the sake of comparison.
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of biodiv.CLs CLE-2010
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of biodiv.CLs CLE-2050
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of biodiv.CLs DECARB-2050
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of biodiv.CLs MCE-2050
Dep-data: EMEP/MSC-WCCE
Figure 3.8 Exceedances (AAE) of critical loads of acidification (from the EU-DB) under ECLAIRE scenarios CLE-2010 (left), CLE-2050 (centre left), DECARB-2050 (centre right) and MCE-2050 (right). Note: The size of the grid shading reflects the ecosystem area exceeded.
Table 3.1 European ecosystem area (in %) where CLbio and CLaci (both from the EU-DB) are exceeded under ECLAIRE scenarios CLE-2010, CLE2050, DECARB-2050 and MCE-2050
Exceedance of: CLE
2010 CLE
2050 DECARB
2050 MCE 2050
CLbio 18 12 8 4
CLaci 8 6 3 1
The robustness of exceedances (Hettelingh et al. 2015) was derived by analogy to the way in which uncertainties are addressed in the Fourth Assessment Report of the IPCC, as described in IPCC (2005). According to this logic, the robustness of an assessment that ecosystems are at risk can range on a scale from ‘exceptionally unlikely’ to ‘virtually certain’. In this chapter, the robustness analysis of ecosystem impacts of the four ECLAIRE scenarios is based on the analysis of the location and
magnitudes of exceedances for the CLaci and CLbio critical load functions.
The method is based on the analysis of the location, coverage and the magnitudes of exceedances of CLaci and CLbio, following the principle of ensemble assessment (Hettelingh et al. 2015), whereby an exceedance is more likely when it occurs using different methods (here: two types of critical load functions). Here, the robustness analysis focuses on the question of whether the combination of sulphur and nitrogen deposition causes scenario-specific exceedances to point in the same direction. The consideration of different endpoints (soil chemistry for CLaci and plant species diversity for CLbio) leads to two sets of critical load functions.
This leaves an ecosystem area with the following possibilities of being at risk of atmospheric deposition of sulphur and nitrogen:
None of the critical loads are exceeded (i.e. exceedance is
‘unlikely’).
Exactly one of the critical load functions is exceeded (i.e.
exceedance is ‘as likely as not’).
Both critical load functions are exceeded:
a. with a likelihood in the interval (0, 0.33] ; i.e. the ecosystem is ‘likely’ to be at risk;
b. with a likelihood in the interval (0.33, 0.67]; i.e. the ecosystem is ‘very likely’ to be at risk;
c. with a likelihood > 0.67; the ecosystem is ‘virtually certain’ to be at risk.
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of CLaci CLE-2010
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of CLaci CLE-2050
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of CLaci DECARB-2050
Dep-data: EMEP/MSC-WCCE
eq ha-1a-1 no exceedance 0 - 200 200 - 400 400 - 700 700 - 1200
> 1200
AAE of CLaci MCE-2050
Dep-data: EMEP/MSC-WCCE
The likelihood of an exceedance in a grid cell is defined as the square root of the product of the percentages of exceeded ecosystem areas (i.e. their geometric mean) with respect to CLaci and CLbio (Hettelingh et al. 2015).
Following this approach, it can be concluded that the likelihood of exceedances under CLE-2010 varies between ‘as likely as not’ (green shading) in many parts of Europe and ‘virtually certain’ (red shading) in broad areas in Central-Western Europe, in particular (Figure 3.9, left).
Note that the 2010 exceedance in Central Europe was driven mostly by the exceedance of CLaci (see Figure 3.8, left), especially in Poland, while high exceedances of CLaci and CLbio concentrated at the Dutch-German border made the likelihood of exceedances ‘virtually certain’.
Under the ECLAIRE scenario MCE-2050, a different picture emerges (Figure 3.9, right), as exceedances are ‘as likely as not’ (green) in most European countries, with ‘likely’, ‘very likely’ and ‘virtually certain’
(yellow to red) exceedances scattered over Poland, northern and
southern Germany, Switzerland, and on the Dutch-German border area, in particular. From the comparison between the AAE of CLaci under MCE-2050 (Figure 3.8, right) and the AAE of CLbio (Figure 3.7, bottom right), it is noted that the robustness of the estimated European area at risk seems driven mostly by CLbio exceedances.
Figure 3.9 The likelihood of a positive exceedance (AAE) under CLE-2010 (left) and MCE-2050 (right), i.e. that the respective grid cell contains at least one ecosystem of which CLaci and/or CLbio is exceeded. Note: The size of the grid shading reflects the ecosystem area exceeded.
References
Hettelingh J-P, Posch M, Slootweg J, Reinds GJ, De Vries W, Le Gall A-C, Maas R, 2015. Effects-based integrated assessment modelling for the support of European air pollution abatement policies. Chapter 25 in:
De Vries W, Hettelingh J-P, Posch M (eds): Critical Loads and
Dynamic Risk Assessments: Nitrogen, Acidity and Metals in Terrestrial and Aquatic Ecosystems. Environmental Pollution Series Vol. 25, pp.
613-635, Springer Science+Business Media, Dordrecht, xxviii+662 pp.; DOI: 10.1007/978-94-017-9508-1_25
ICP M&M, 2014. Mapping Manual, www.icpmapping.org, accessed 22 October 2015
unlikely as likely as not likely very likely virtually certain
Exc. of CLaci & CLbio (EU-DB) CLE-2010
CCE
unlikely as likely as not likely very likely virtually certain
Exc. of CLaci & CLbio (EU-DB) MCE-2050
CCE
IPCC, 2005. Guidance notes for lead authors of the IPCC fourth assessment report on addressing uncertainties.
http://www.ipccwg1.unibe.ch/publications/supportingmaterial/uncert aintyguidance- note.pdf, accessed 23 June 2015.
Posch M, Hettelingh J-P, Slootweg J, Reinds GJ, 2014. Deriving critical loads based on plant diversity targets. In: Slootweg J, Posch M, Hettelingh J-P, Mathijssen L (eds): Modelling and mapping the impacts of atmospheric deposition on plant species diversity in Europe: CCE Status Report 2014. Report 2014-0075, RIVM, Bilthoven, the Netherlands, pp.41-46; ISBN 978-90-6960-276-9;
www.wge-cce.org
Posch M, De Vries W, Sverdrup HU, 2015. Mass balance models to derive critical loads of nitrogen and acidity for terrestrial and aquatic ecosystems. Chapter 6 in: De Vries W, Hettelingh J-P, Posch M (eds):
Critical Loads and Dynamic Risk Assessments: Nitrogen, Acidity and Metals in Terrestrial and Aquatic Ecosystems. Environmental Pollution Series Vol. 25, pp. 171-205, Springer Science+Business Media, Dordrecht, xxviii+662 pp.; DOI: 10.1007/978-94-017-9508-1_6 Reinds GJ, Mol-Dijkstra J, Bonten L, Wamelink W, De Vries W, Posch M,
2014. VSD+PROPS: Recent developments. In: Slootweg J, Posch M, Hettelingh J-P, Mathijssen L (eds): Modelling and mapping the impacts of atmospheric deposition on plant species diversity in Europe: CCE Status Report 2014. Report 2014-0075, RIVM, Bilthoven, the Netherlands, pp.47-53; ISBN 978-90-6960-276-9;
www.wge-cce.org