Estimating impact likelihoods from probabilistic projections of climate and socio-economic change using impact response surfaces.

Estimates of future climate change impacts using numerical impact models are commonly based on a limited selection of projections of climate and other key drivers. However, the availability of large ensembles of such projections offers an opportunity to estimate impact responses probabilistically. This study demonstrates an approach that combines model-based impact response surfaces (IRSs) with probabilistic projections of climate change and population to estimate the likelihood of exceeding pre-specified thresholds of impact. The changing likelihood of exceeding impact thresholds during the 21st century was estimated for selected indicators in three European case study regions (Iberian Peninsula, Scotland and Hungary), comparing simulations that incorporate adaptation to those without adaptation. The results showed high likelihoods of increases in heat-related human mortality and of yield decreases for some crops, whereas a decrease of NPP was estimated to be exceptionally unlikely. For a water reservoir in a Portuguese catchment, increased likelihoods of severe water scarce conditions were estimated for the current rice cultivation. Switching from rice to other crops with lower irrigation demand changes production risks, allowing for expansion of the irrigated areas but introducing a stronger sensitivity to changes in rainfall. The IRS-based risk assessment shown in this paper is of relevance for policy making by addressing the relative sensitivity of impacts to key climate and socio-economic drivers, and the urgency for action expressed as a time series of the likelihood of crossing critical impact thresholds. It also examines options to respond by incorporating alternative adaptation actions in the analysis framework, which may be useful for exploring the types, choice and timing of adaptation responses.

Lessons from COVID-19 for managing transboundary climate risks and building resilience.

COVID-19 has revealed how challenging it is to manage global, systemic and compounding crises. Like COVID-19, climate change impacts, and maladaptive responses to them, have potential to disrupt societies at multiple scales via networks of trade, finance, mobility and communication, and to impact hardest on the most vulnerable. However, these complex systems can also facilitate resilience if managed effectively. This review aims to distil lessons related to the transboundary management of systemic risks from the COVID-19 experience, to inform climate change policy and resilience building. Evidence from diverse fields is synthesised to illustrate the nature of systemic risks and our evolving understanding of resilience. We describe research methods that aim to capture systemic complexity to inform better management practices and increase resilience to crises. Finally, we recommend specific, practical actions for improving transboundary climate risk management and resilience building. These include mapping the direct, cross-border and cross-sectoral impacts of potential climate extremes, adopting adaptive risk management strategies that embrace heterogenous decision-making and uncertainty, and taking a broader approach to resilience which elevates human wellbeing, including societal and ecological resilience.

Achievements and needs for the climate change scenario framework.

Long-term global scenarios have underpinned research and assessment of global environmental change for four decades. Over the past ten years, the climate change research community has developed a scenario framework combining alternative futures of climate and society to facilitate integrated research and consistent assessment to inform policy. Here we assess how well this framework is working and what challenges it faces. We synthesize insights from scenario-based literature, community discussions and recent experience in assessments, concluding that the framework has been widely adopted across research communities and is largely meeting immediate needs. However, some mixed successes and a changing policy and research landscape present key challenges, and we recommend several new directions for the development and use of this framework.

Improving the representation of adaptation in climate change impact models.

Climate change adaptation is a complex human process, framed by uncertainties and constraints, which is difficult to capture in existing assessment models. Attempts to improve model representations are hampered by a shortage of systematic descriptions of adaptation processes and their relevance to models. This paper reviews the scientific literature to investigate conceptualisations and models of climate change adaptation, and the ways in which representation of adaptation in models can be improved. The review shows that real-world adaptive responses can be differentiated along a number of dimensions including intent or purpose, timescale, spatial scale, beneficiaries and providers, type of action, and sector. However, models of climate change consequences for land use and water management currently provide poor coverage of these dimensions, instead modelling adaptation in an artificial and subjective manner. While different modelling approaches do capture distinct aspects of the adaptive process, they have done so in relative isolation, without producing improved unified representations. Furthermore, adaptation is often assumed to be objective, effective and consistent through time, with only a minority of models taking account of the human decisions underpinning the choice of adaptation measures (14%), the triggers that motivate actions (38%) or the time-lags and constraints that may limit their uptake and effectiveness (14%). No models included adaptation to take advantage of beneficial opportunities of climate change. Based on these insights, transferable recommendations are made on directions for future model development that may enhance realism within models, while also advancing our understanding of the processes and effectiveness of adaptation to a changing climate.

A randomized controlled pilot study of VO2 max testing: a potential model for measuring relative in vivo efficacy of different red blood cell products.

BACKGROUND: Randomized trials, for example, RECESS, comparing "young" (median, 7-day) versus "middle-aged" (median, 28-day) red blood cells (RBCs), showed no difference in outcome. These data are important; however, they do not inform us about the safety and effectiveness of the oldest RBCs, which some patients receive. It may not be feasible to conduct a clinical trial randomizing patients to receive the oldest blood. Therefore, we propose strenuous exercise (VO2 max testing) as a model to study the relative efficacy to increase oxygen delivery to tissue of different RBC products, for example, extremes of storage duration. STUDY DESIGN AND METHODS: In this pilot study, eight healthy subjects had 2 units of leukoreduced RBCs collected by apheresis in AS-3 using standard methods. Subjects were randomized to receive both (2) units of their autologous RBCs at either 7 or 42 days after blood collection. VO2 max testing on a cycle ergometer was performed 2 days before (Monday) and 2 days after (Friday) the transfusion visit (Wednesday). This design avoids confounding effects on intravascular volume from the 2-unit blood transfusion. The primary outcome was the difference in VO2 max between Friday and Monday (delta VO2 max). RESULTS: VO2 max increased more in the 7-day RBC arm (8.7 ± 6.9% vs. 1.9 ± 6.5%, p = 0.202 for comparison between arms). Exercise duration (seconds) increased in the 7-day RBC arm (8.4 ± 1.7%) but actually decreased in the 42-day arm (-2.6 ± 3.6%, p = 0.002). CONCLUSIONS: This pilot study suggests that VO2 max testing has potential as a rigorous and quantitative in vivo functional assay of RBC function. Our preliminary results suggest that 42-day RBCs are inferior to 7-day RBCs at delivering oxygen to tissues.

Modelling shifts in agroclimate and crop cultivar response under climate change.

THIS PAPER AIMS: (i) to identify at national scale areas where crop yield formation is currently most prone to climate-induced stresses, (ii) to evaluate how the severity of these stresses is likely to develop in time and space, and (iii) to appraise and quantify the performance of two strategies for adapting crop cultivation to a wide range of (uncertain) climate change projections. To this end we made use of extensive climate, crop, and soil data, and of two modelling tools: N-AgriCLIM and the WOFOST crop simulation model. N-AgriCLIM was developed for the automatic generation of indicators describing basic agroclimatic conditions and was applied over the whole of Finland. WOFOST was used to simulate detailed crop responses at four representative locations. N-AgriCLIM calculations have been performed nationally for 3829 grid boxes at a 10 × 10 km resolution and for 32 climate scenarios. Ranges of projected shifts in indicator values for heat, drought and other crop-relevant stresses across the scenarios vary widely - so do the spatial patterns of change. Overall, under reference climate the most risk-prone areas for spring cereals are found in south-west Finland, shifting to south-east Finland towards the end of this century. Conditions for grass are likely to improve. WOFOST simulation results suggest that CO2 fertilization and adjusted sowing combined can lead to small yield increases of current barley cultivars under most climate scenarios on favourable soils, but not under extreme climate scenarios and poor soils. This information can be valuable for appraising alternative adaptation strategies. It facilitates the identification of regions in which climatic changes might be rapid or otherwise notable for crop production, requiring a more detailed evaluation of adaptation measures. The results also suggest that utilizing the diversity of cultivar responses seems beneficial given the high uncertainty in climate change projections.

The next generation of scenarios for climate change research and assessment.

Advances in the science and observation of climate change are providing a clearer understanding of the inherent variability of Earth's climate system and its likely response to human and natural influences. The implications of climate change for the environment and society will depend not only on the response of the Earth system to changes in radiative forcings, but also on how humankind responds through changes in technology, economies, lifestyle and policy. Extensive uncertainties exist in future forcings of and responses to climate change, necessitating the use of scenarios of the future to explore the potential consequences of different response options. To date, such scenarios have not adequately examined crucial possibilities, such as climate change mitigation and adaptation, and have relied on research processes that slowed the exchange of information among physical, biological and social scientists. Here we describe a new process for creating plausible scenarios to investigate some of the most challenging and important questions about climate change confronting the global community.

Ecosystem service supply and vulnerability to global change in Europe.

Global change will alter the supply of ecosystem services that are vital for human well-being. To investigate ecosystem service supply during the 21st century, we used a range of ecosystem models and scenarios of climate and land-use change to conduct a Europe-wide assessment. Large changes in climate and land use typically resulted in large changes in ecosystem service supply. Some of these trends may be positive (for example, increases in forest area and productivity) or offer opportunities (for example, "surplus land" for agricultural extensification and bioenergy production). However, many changes increase vulnerability as a result of a decreasing supply of ecosystem services (for example, declining soil fertility, declining water availability, increasing risk of forest fires), especially in the Mediterranean and mountain regions.

Predicting spring phenology and frost damage risk of Betula spp. under climatic warming: a comparison of two models.

Timing of bud burst and frost damage risk for leaves of Betula spp. in response to climatic warming in Finland was examined with two models. In the first model, ontogenetic development in spring was triggered by an accumulation of chilling temperatures. The second model assumed an additional signal from the light climate. The two models gave radically different estimates of frost damage risk in response to climate warming. The chilling-triggered model forecast a significant and increasing risk with increased warming, whereas the light-climate-triggered model predicted little or no risk. The chilling-triggered model is widely applied in phenological research; however, there is increasing experimental evidence that light conditions play a role in the timing of spring phenology. Although it is not clear if the light response mechanisms are appropriately represented in our model, the results imply that reliance on a light signal for spring development would afford a degree of protection against possible frost damage under climate warming that would not be present if chilling were the sole determinant. Further experimental tests are required to ascertain the light-related mechanisms controlling phenological timing, so that credible model extrapolations can be undertaken.