Adaptation discussions at Forest Day 3, a parallel event at the United Nations Climate change conference COP15 in Copenhagen, Denmark. Photo by Neil Palmer (CIAT).

BOGOR, Indonesia (14 September, 2011)_It is a tough job to attend international climate change meetings. Endless sessions without consensus, buzzing protestors and media, and always a lot of unmet expectations. It is only natural after long days like this, to unwind with a good cocktail in hand. But regardless of any Caipirinhas consumed in the bar, all decision-makers have another hangover to worry about during negotiations – the one from the adaptation-mitigation cocktail.

And this cocktail has the potential to turn into a Molotov one for forests, with far more serious implications than a simple hangover.

A current and rapidly expanding research body is trying to indicate the optimal and most efficient mix of the two strategies through integrated assessment models (IAMs). Although most models illustrate that adaptation and mitigation are strategic complements, they also acknowledge trade-offs and substitution effects (meaning that successful adaptation reduces the marginal benefit of mitigation and that successful mitigation effort reduces the damage to which it is necessary to adapt).

The majority of the assessments however exclude low-probability/ high impact events, characterized by great uncertainty and extreme catastrophes. A new publication by Bosello and Chen, Adapting and Mitigating to Climate Change: Balancing the Choice Under Uncertainty, attempts to fill this gap by introducing two sources of uncertainty: event uncertainty or the uncertain occurrence of a climate catastrophe triggered by temperature increase, and spatial uncertainty i.e. an imperfect knowledge on the geographic distribution of the climatic damage.

The economists conclude that under both uncertainty cases, mitigation is a more advantageous and efficient strategy than adaptation. Under event uncertainty, mitigation becomes relatively more important as it reduces temperature increase and hence the probability of event occurrence.

Adaptation has no impact on this. Optimal mitigation responses are much less sensitive to spatial uncertainty as well. Adaptation responds to damages that are region and site specific but an exact prediction of where and with which intensity impacts will hit is not possible.

They argue that this is particularly concerning for anticipatory adaptation that requires huge and almost irreversible upfront investments, such as coastal hard infrastructure, where the burden of a planning mistake falls on to the entire community. Mitigation aims to revert damages on a global level and it is thus a “safer” and more robust strategy for policy-makers under catastrophic event uncertainty.

The results above strengthen the case for more stringent mitigation goals and this is very important. But although the modeling results are correct, their interpretation by decision makers can be potentially dangerous with severe implications for adaptation policy and finance, and for forests in particular.

Adaptation had long been the neglected child at the climate negotiations dinner table. Discussions had primarily focused on mitigation, in part because of a taboo on adaptation: the need for adaptation was being perceived as a failure of mitigation, or a way to weaken mitigation efforts.

While this is changing now with growing scientific evidence about the inevitability of specific impacts, the optimal mix debate might stall critical adaptation decisions and funding. This can have serious consequences as delays might increase vulnerability and costs in the future for both societies and forests.

Everybody now acknowledges that forests are important for mitigation, with mechanisms such as REDD acquiring rock-star popularity in negotiations. If adaptation is neglected, forests might discontinue to provide mitigation services and it will be just like throwing a Molotov cocktail right at them, setting them ablaze.

Even under the most stringent mitigation scenario, some climate change impacts will inevitably hit forests and people. Certain impacts are already occurring, are jeopardizing the permanence of carbon storage in forest ecosystems and are also rendering forest-dependent people more vulnerable.

Adaptation strategies aiming at buffering forest ecosystems from climate change impacts such as fire should become an essential component of forest management. Furthermore, a REDD+ project is more likely to be sustainable if it integrates adaptation measures for communities and ecosystems, taking into account local needs and thus increasing its local legitimacy.

Adaptation should be a process of learning-by-doing, through adaptive management and flexible options, which enhances the adaptive capacity of society to deal with uncertainty as a whole. It would be wrong to focus exclusively on the “irreversibility of anticipatory adaptation” because it should not only be about hard infrastructure.

Investing in ecosystem services for the reduction of people’s vulnerability can be a no-regret option because it is flexible and adaptable to change and can yield multiple benefits such as poverty reduction, biodiversity and increased social capacity.

Ecosystem options can also foster synergies between adaptation and mitigation, and forests can play a critical role in this through afforestation, reforestation and conservation projects (e.g. REDD+). Furthermore, we should not assume that people are completely helpless against catastrophic climatic events. Effective disaster-risk reduction strategies can go a long way in minimizing damage.

In another analysis, van Vuuren and colleagues use a variety of scenarios and combine results of different assessments only to conclude that it is not feasible to determine an optimal mix. While most models suggest that costs and benefits of mitigation, adaptation and residual damages can be traded-off against each other, there are many conceptual and analytical problems with such an approach due to the different spatial and temporal scales of the two response strategies, potential risks and uncertainty. The weighing of climate change consequences and policy responses is complicated further by differences in the interests between actors and subjective interpretation of risks.

The authors also raise another concern. Even under the most stringent mitigation scenario, the world is likely to warm-up more than the ambitious 2°C limit. This means that hedging adaptation policies against more warming might have considerable value. Mitigation policies should aim for 2°C warming, but adaptation strategies should prepare for 3°C.

Whether mitigation is a “safer” or more efficient strategy also depends on the sector.  In the scenarios of van Vuuren and colleagues it is shown that in the health sector for example, adaptation has a much more decisive influence on malaria control than mitigation.

In the publication of de Bruin and Dellnik, the way adaptation levels are included in integrated models is questioned altogether. The dominant assumption in IAMs is that adaptation will be implemented in an optimal manner, ‘calculating’ it into the estimate of damages.

The authors believe however that adaptation will not be undertaken optimally and mention several restrictive factors such as capacity gaps, lack of information and inertia in the decision making process. There is a significant gap in science regarding the effects of these restrictions and there are basically no economic analyses of suboptimal adaptation scenarios.

But overall, the general problem with such models is that all climate impacts are monetarised and damages are expressed solely in dollar terms. While this is comfortable for comparing policies, it cannot capture the full environmental impact of climate change.

Furthermore, the time preference usually employed leads to a relatively high discount rate and potential problems of intergenerational justice. Cost-benefit analysis best fits assessments of policies whose impacts do not extend far into the future and have less issues of uncertainty, conflicting ethical choices, distributional biases and extensive ecological impacts attached to them.

Policy evaluation based on inadequate theoretical assumptions can cause a serious hangover of inaccurate estimates and misguided decisions. Instead of debating the optimal mix, it would be better for decision makers to channel their efforts in achieving a global agreement on a fair and ambitious mitigation goal and enough finance to support adaptation in the most vulnerable countries, the ones that are the least responsible for climate change yet are bearing the majority of its costs.