Climate Endgame: Exploring catastrophic climate change scenarios.

Prudent risk management requires consideration of bad-to-worst-case scenarios. Yet, for climate change, such potential futures are poorly understood. Could anthropogenic climate change result in worldwide societal collapse or even eventual human extinction? At present, this is a dangerously underexplored topic. Yet there are ample reasons to suspect that climate change could result in a global catastrophe. Analyzing the mechanisms for these extreme consequences could help galvanize action, improve resilience, and inform policy, including emergency responses. We outline current knowledge about the likelihood of extreme climate change, discuss why understanding bad-to-worst cases is vital, articulate reasons for concern about catastrophic outcomes, define key terms, and put forward a research agenda. The proposed agenda covers four main questions: 1) What is the potential for climate change to drive mass extinction events? 2) What are the mechanisms that could result in human mass mortality and morbidity? 3) What are human societies' vulnerabilities to climate-triggered risk cascades, such as from conflict, political instability, and systemic financial risk? 4) How can these multiple strands of evidence-together with other global dangers-be usefully synthesized into an "integrated catastrophe assessment"? It is time for the scientific community to grapple with the challenge of better understanding catastrophic climate change.

Multiple Climate Tipping Points Metrics for Improved Sustainability Assessment of Products and Services.

Mounting evidence indicates that climate tipping points can have large, potentially irreversible, impacts on the earth system and human societies. Yet, climate change metrics applied in current sustainability assessment methods generally do not consider these tipping points, with the use of arbitrarily determined time horizons and assumptions that the climate impact of a product or service is independent of emission timing. Here, we propose a new method for calculating climate tipping characterization factors for greenhouse gases (carbon dioxide, methane, and nitrous oxide) at midpoint. It covers 13 projected tipping points, incorporates the effect that the crossing of a given tipping point has on accelerating the crossing of other tipping points, and addresses uncertainties in the temperature thresholds that trigger the tipping points. To demonstrate the added value of the new metric, we apply it to emissions stemming from end-of-life of plastic polymers and compare them with commonly used metrics. This highlights the need to consider climate tipping in sustainability assessment of products and services.

Environmental tipping points significantly affect the cost-benefit assessment of climate policies.

Most current cost-benefit analyses of climate change policies suggest an optimal global climate policy that is significantly less stringent than the level required to meet the internationally agreed 2 °C target. This is partly because the sum of estimated economic damage of climate change across various sectors, such as energy use and changes in agricultural production, results in only a small economic loss or even a small economic gain in the gross world product under predicted levels of climate change. However, those cost-benefit analyses rarely take account of environmental tipping points leading to abrupt and irreversible impacts on market and nonmarket goods and services, including those provided by the climate and by ecosystems. Here we show that including environmental tipping point impacts in a stochastic dynamic integrated assessment model profoundly alters cost-benefit assessment of global climate policy. The risk of a tipping point, even if it only has nonmarket impacts, could substantially increase the present optimal carbon tax. For example, a risk of only 5% loss in nonmarket goods that occurs with a 5% annual probability at 4 °C increase of the global surface temperature causes an immediate two-thirds increase in optimal carbon tax. If the tipping point also has a 5% impact on market goods, the optimal carbon tax increases by more than a factor of 3. Hence existing cost-benefit assessments of global climate policy may be significantly underestimating the needs for controlling climate change.

Natural selection for costly nutrient recycling in simulated microbial metacommunities.

Recycling of essential nutrients occurs at scales from microbial communities to global biogeochemical cycles, often in association with ecological interactions in which two or more species utilise each others' metabolic by-products. However, recycling loops may be unstable; sequences of reactions leading to net recycling may be parasitised by side-reactions causing nutrient loss, while some reactions in any closed recycling loop are likely to be costly to participants. Here we examine the stability of nutrient recycling loops in an individual-based ecosystem model based on microbial functional types that differ in their metabolism. A supplied nutrient is utilised by a "source" functional type, generating a secondary nutrient that is subsequently used by two other types-a "mutualist" that regenerates the initial nutrient at a growth rate cost, and a "parasite" that produces a refractory waste product but does not incur any additional cost. The three functional types are distributed across a metacommunity in which separate patches are linked by a stochastic diffusive migration process. Regions of high mutualist abundance feature high levels of nutrient recycling and increased local population density leading to greater export of individuals, allowing the source-mutualist recycling loop to spread across the system. Individual-level selection favouring parasites is balanced by patch-level selection for high productivity, indirectly favouring mutualists due to the synergistic productivity benefits of the recycling loop they support. This suggests that multi-level selection may promote nutrient cycling and thereby help to explain the apparent ubiquity and stability of nutrient recycling in nature.