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ateam - Potsdam Institute for Climate Impact Research

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ATEAM final report Section 5 and 6 (2001-2004) 50<br />

and <strong>for</strong>est management. Nevertheless a recurring theme during the dialogue was to learn just how<br />

complex human-environment interactions are in a context of EU, national and regional policies and<br />

under socio-economic constraints. To give one example, the diversity of <strong>for</strong>est ownership and <strong>for</strong>est use<br />

in terms of area owned, financial relevance relative to other income sources of the stakeholder and<br />

management goals was even greater than anticipated. Forest owners can rely on <strong>for</strong>est ecosystem<br />

services <strong>for</strong> almost all or next to none of their income, sometimes independent of the area of <strong>for</strong>est<br />

owned. Forests are managed to optimise many outcomes, ranging from commercial use, over<br />

recreational to spiritual meaning. Here our choice of indicators (i.e. wood production, carbon stored in<br />

vegetation and soil, species turnover, tree species distribution) fall short of the in<strong>for</strong>mation needs of all<br />

possible stakeholders. These complexities were discussed during stakeholder interactions and explored<br />

especially in the land use modelling work. Two detailed reports on <strong>for</strong>est policy have been produced<br />

(Kankaanpää and Carter 2004ab, see Annex 2).<br />

We conclude that our assessment was both valuable and useful <strong>for</strong> stakeholders and relevant in<br />

scientific terms. We also conclude that future analysis can be based on our concepts and results and <strong>for</strong><br />

some sectors should especially target local scales and shorter time scales. Ecosystem modelling should<br />

continue to mature into human-environment-system modelling, by accounting <strong>for</strong> management and<br />

decision making in the socio-economic and policy context of the relevant stakeholders. This can be<br />

greatly facilitated by continued stakeholder interaction, making use of as well as advancing the tools<br />

and the stakeholder network developed in ATEAM.<br />

6.2.5 Integrating potential impacts and adaptive capacity into maps of vulnerability (WP1, 5<br />

and 6)<br />

Principal investigators: Marc J. Metzger, Dagmar Schröter, Rik Leemans, Wolfgang Cramer<br />

The term vulnerability stems from everyday language – the Ox<strong>for</strong>d English Dictionary defines it as “the<br />

undesirable state of being open to attack or damage”. At the time the ATEAM proposal was submitted to<br />

the EU, researchers from different disciplines used the term ‘vulnerability’ intuitively as the risk of harm<br />

to something they, or somebody else values caused by global change. Since then, the concept of<br />

vulnerability has been debated in the scientific community, with considerable contributions by ATEAM<br />

researchers. By now a common definition of vulnerability, as well as an assessment concept have<br />

emerged (Turner et al. 2003, Schröter et al. 2004). ATEAM defines vulnerability as the degree to which<br />

an ecosystem service is sensitive to global environmental change and the degree to which the sector<br />

that relies on the service is unable to adapt to the changes (Metzger and Schröter 2004). Hence,<br />

potential impacts (the resultant of exposure and sensitivity) and adaptive capacity constitute a region’s<br />

vulnerability. Table 13 gives an overview of important terminology developed in ATEAM related to<br />

vulnerability, with examples <strong>for</strong> the sectors agriculture and carbon storage.<br />

In Figure 38 we illustrate how the terms presented in Table 13 fit into the ATEAM vulnerability<br />

assessment. The future scenarios (exposure) feed into the ecosystem models, which determine future<br />

ecosystem service supply, i.e. potential impacts. The change in potential impacts compared to baseline<br />

conditions will be expressed in a stratified potential impact index. The socio-economic scenarios are<br />

translated into a generic adaptive capacity index, which can be combined with the potential impact index<br />

to map vulnerability.

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