Drought sensitivity in mesic forests heightens their vulnerability to climate change.

Climate change is shifting the structure and function of global forests, underscoring the critical need to predict which forests are most vulnerable to a hotter and drier future. We analyzed 6.6 million tree rings from 122 species to assess trees' sensitivity to water and energy availability. We found that trees growing in wetter portions of their range exhibit the greatest drought sensitivity. To test how these patterns of drought sensitivity influence vulnerability to climate change, we predicted tree growth through 2100. Our results suggest that drought adaptations in arid regions will partially buffer trees against climate change. By contrast, trees growing in the wetter, hotter portions of their climatic range may experience unexpectedly large adverse impacts under climate change.

Incorporating human behaviour into Earth system modelling.

Climate change and other challenges to the stability and functioning of natural and managed environmental systems are driven by increasing anthropogenic domination of the Earth. Models to forecast the trajectory of climate change and to identify pathways to sustainability require representation of human behaviour and its feedbacks with the climate system. Social climate models (SCMs) are an emerging class of models that embed human behaviour in climate models. We survey existing SCMs and make recommendations for how to integrate models of human behaviour and climate. We suggest a framework for representing human behaviour that consists of cognition, contagion and a behavioural response. Cognition represents the human processing of information around climate change; contagion represents the spread of information, beliefs and behaviour through social networks; and response is the resultant behaviour or action. This framework allows for biases, habituation and other cognitive processes that shape human perception of climate change as well as the influence of social norms, social learning and other social processes on the spread of information and factors that shape decision-making and behaviour. SCMs move beyond the inclusion of human activities in climate models to the representation of human behaviour that determines the magnitude, sign and character of these activities. The development of SCMs is a challenging but important next step in the evolution of Earth system models.

Comprehensive evidence implies a higher social cost of CO2.

The social cost of carbon dioxide (SC-CO2) measures the monetized value of the damages to society caused by an incremental metric tonne of CO2 emissions and is a key metric informing climate policy. Used by governments and other decision-makers in benefit-cost analysis for over a decade, SC-CO2 estimates draw on climate science, economics, demography and other disciplines. However, a 2017 report by the US National Academies of Sciences, Engineering, and Medicine1 (NASEM) highlighted that current SC-CO2 estimates no longer reflect the latest research. The report provided a series of recommendations for improving the scientific basis, transparency and uncertainty characterization of SC-CO2 estimates. Here we show that improved probabilistic socioeconomic projections, climate models, damage functions, and discounting methods that collectively reflect theoretically consistent valuation of risk, substantially increase estimates of the SC-CO2. Our preferred mean SC-CO2 estimate is $185 per tonne of CO2 ($44-$413 per tCO2: 5%-95% range, 2020 US dollars) at a near-term risk-free discount rate of 2%, a value 3.6 times higher than the US government's current value of $51 per tCO2. Our estimates incorporate updated scientific understanding throughout all components of SC-CO2 estimation in the new open-source Greenhouse Gas Impact Value Estimator (GIVE) model, in a manner fully responsive to the near-term NASEM recommendations. Our higher SC-CO2 values, compared with estimates currently used in policy evaluation, substantially increase the estimated benefits of greenhouse gas mitigation and thereby increase the expected net benefits of more stringent climate policies.

Biodiversity mediates ecosystem sensitivity to climate variability.

A rich body of evidence from local-scale experiments and observational studies has revealed stabilizing effects of biodiversity on ecosystem functioning. However, whether these effects emerge across entire regions and continents remains largely overlooked. Here we combine data on the distribution of more than 57,500 plant species and remote-sensing observations throughout the entire Western Hemisphere to investigate the role of multiple facets of plant diversity (species richness, phylogenetic diversity, and functional diversity) in mediating the sensitivity of ecosystems to climate variability at the regional-scale over the past 20 years. We show that, across multiple biomes, regions of greater plant diversity exhibit lower sensitivity (more stable over time) to temperature variability at the interannual and seasonal-scales. While these areas can display lower sensitivity to interannual variability in precipitation, they emerge as highly sensitive to precipitation seasonality. Conserving landscapes of greater diversity may help stabilize ecosystem functioning under climate change, possibly securing the continuous provisions of productivity-related ecosystem service to people.

Land-use emissions embodied in international trade.

International trade separates consumption of goods from related environmental impacts, including greenhouse gas emissions from agriculture and land-use change (together referred to as "land-use emissions"). Through use of new emissions estimates and a multiregional input-output model, we evaluated land-use emissions embodied in global trade from 2004 to 2017. Annually, 27% of land-use emissions and 22% of agricultural land are related to agricultural products ultimately consumed in a different region from where they were produced. Roughly three-quarters of embodied emissions are from land-use change, with the largest transfers from lower-income countries such as Brazil, Indonesia, and Argentina to more industrialized regions such as Europe, the United States, and China. Mitigation of global land-use emissions and sustainable development may thus depend on improving the transparency of supply chains.

Determinants of emissions pathways in the coupled climate-social system.

The ambition and effectiveness of climate policies will be essential in determining greenhouse gas emissions and, as a consequence, the scale of climate change impacts1,2. However, the socio-politico-technical processes that will determine climate policy and emissions trajectories are treated as exogenous in almost all climate change modelling3,4. Here we identify relevant feedback processes documented across a range of disciplines and connect them in a stylized model of the climate-social system. An analysis of model behaviour reveals the potential for nonlinearities and tipping points that are particularly associated with connections across the individual, community, national and global scales represented. These connections can be decisive for determining policy and emissions outcomes. After partly constraining the model parameter space using observations, we simulate 100,000 possible future policy and emissions trajectories. These fall into 5 clusters with warming in 2100 ranging between 1.8 °C and 3.6 °C above the 1880-1910 average. Public perceptions of climate change, the future cost and effectiveness of mitigation technologies, and the responsiveness of political institutions emerge as important in explaining variation in emissions pathways and therefore the constraints on warming over the twenty-first century.

Estimates of country level temperature-related mortality damage functions.

Many studies project that climate change is expected to cause a significant number of excess deaths. Yet, in integrated assessment models that determine the social cost of carbon (SCC), human mortality impacts do not reflect the latest scientific understanding. We address this issue by estimating country-level mortality damage functions for temperature-related mortality with global spatial coverage. We rely on projections from the most comprehensive published study in the epidemiology literature of future temperature impacts on mortality (Gasparrini et al. in Lancet Planet Health 1:e360-e367, 2017), which estimated changes in heat- and cold-related mortality for 23 countries over the twenty-first century. We model variation in these mortality projections as a function of baseline climate, future temperature change, and income variables and then project future changes in mortality for every country. We find significant spatial heterogeneity in projected mortality impacts, with hotter and poorer places more adversely affected than colder and richer places. In the absence of income-based adaptation, the global mortality rate in 2080-2099 is expected to increase by 1.8% [95% CI 0.8-2.8%] under a lower-emissions RCP 4.5 scenario and by 6.2% [95% CI 2.5-10.0%] in the very high-emissions RCP 8.5 scenario relative to 2001-2020. When the reduced sensitivity to heat associated with rising incomes, such as greater ability to invest in air conditioning, is accounted for, the expected end-of-century increase in the global mortality rate is 1.1% [95% CI 0.4-1.9%] in RCP 4.5 and 4.2% [95% CI 1.8-6.7%] in RCP 8.5. In addition, we compare recent estimates of climate-change induced excess mortality from diarrheal disease, malaria and dengue fever in 2030 and 2050 with current estimates used in SCC calculations and show these are likely underestimated in current SCC estimates, but are also small compared to more direct temperature effects.

Climate adaptation by crop migration.

Many studies have estimated the adverse effects of climate change on crop yields, however, this literature almost universally assumes a constant geographic distribution of crops in the future. Movement of growing areas to limit exposure to adverse climate conditions has been discussed as a theoretical adaptive response but has not previously been quantified or demonstrated at a global scale. Here, we assess how changes in rainfed crop area have already mediated growing season temperature trends for rainfed maize, wheat, rice, and soybean using spatially-explicit climate and crop area data from 1973 to 2012. Our results suggest that the most damaging impacts of warming on rainfed maize, wheat, and rice have been substantially moderated by the migration of these crops over time and the expansion of irrigation. However, continued migration may incur substantial environmental costs and will depend on socio-economic and political factors in addition to land suitability and climate.

Using remarkability to define coastal flooding thresholds.

Coastal flooding is increasingly common in many areas. However, the degree of inundation and associated disruption depend on local topography as well as the distribution of people, infrastructure and economic activity along the coast. Local measures of flooding that are comparable over large areas are difficult to obtain. Here we use the remarkability of flood events, measured by flood-related posts on social media, to estimate county-specific flood thresholds for shoreline counties along the east coast of the United States. While thresholds in most counties are statistically-indistinguishable from minor flood thresholds of nearby tide gauges, we find evidence that several areas experience noticeable flooding at tide heights lower than existing flood thresholds. These 22 counties include several major cities such as Miami, New York, and Boston, with a total population over 13 million. Our analysis implies that large populations might currently be exposed to nuisance flooding not identified via standard measures.

Rapidly declining remarkability of temperature anomalies may obscure public perception of climate change.

The changing global climate is producing increasingly unusual weather relative to preindustrial conditions. In an absolute sense, these changing conditions constitute direct evidence of anthropogenic climate change. However, human evaluation of weather as either normal or abnormal will also be influenced by a range of factors including expectations, memory limitations, and cognitive biases. Here we show that experience of weather in recent years-rather than longer historical periods-determines the climatic baseline against which current weather is evaluated, potentially obscuring public recognition of anthropogenic climate change. We employ variation in decadal trends in temperature at weekly and county resolution over the continental United States, combined with discussion of the weather drawn from over 2 billion social media posts. These data indicate that the remarkability of particular temperatures changes rapidly with repeated exposure. Using sentiment analysis tools, we provide evidence for a "boiling frog" effect: The declining noteworthiness of historically extreme temperatures is not accompanied by a decline in the negative sentiment that they induce, indicating that social normalization of extreme conditions rather than adaptation is driving these results. Using climate model projections we show that, despite large increases in absolute temperature, anomalies relative to our empirically estimated shifting baseline are small and not clearly distinguishable from zero throughout the 21st century.

Mimi-PAGE, an open-source implementation of the PAGE09 integrated assessment model.

Integrated Assessment Models (IAMs) have become critical tools for assessing the costs and benefits of policies to reduce greenhouse gas emissions. Three models currently inform the social cost of carbon dioxide (SCCO2, the net present value of damages from one additional ton of CO2) used by the US federal government, several states, and Canada. Here we present a new open-source implementation of one of these models (PAGE09) in the Julia programming language using a modular modeling framework (Mimi). Mimi-PAGE was coded using best coding practices (such as multiple code reviews by different individuals during development, automated testing of newly-committed code, and provision of documentation and usage notes) and is publicly available in a GitHub repository for community inspection and use under an open source license. In this paper we describe the Julia implementation of PAGE09, show that output from Mimi-PAGE matches that of the original model, and perform comparisons of the run time between the two implementations.

New science of climate change impacts on agriculture implies higher social cost of carbon.

Despite substantial advances in climate change impact research in recent years, the scientific basis for damage functions in economic models used to calculate the social cost of carbon (SCC) is either undocumented, difficult to trace, or based on a small number of dated studies. Here we present new damage functions based on the current scientific literature and introduce these into an integrated assessment model (IAM) in order to estimate a new SCC. We focus on the agricultural sector, use two methods for determining the yield impacts of warming, and the GTAP CGE model to calculate the economic consequences of yield shocks. These new damage functions reveal far more adverse agricultural impacts than currently represented in IAMs. Impacts in the agriculture increase from net benefits of $2.7 ton-1 CO2 to net costs of $8.5 ton-1, leading the total SCC to more than double.

The fingerprint of climate trends on European crop yields.

Europe has experienced a stagnation of some crop yields since the early 1990s as well as statistically significant warming during the growing season. Although it has been argued that these two are causally connected, no previous studies have formally attributed long-term yield trends to a changing climate. Here, we present two statistical tests based on the distinctive spatial pattern of climate change impacts and adaptation, and explore their power under a range of parameter values. We show that statistical power for the identification of climate change impacts is high in many settings, but that power for identifying adaptation is almost always low. Applying these tests to European agriculture, we find evidence that long-term temperature and precipitation trends since 1989 have reduced continent-wide wheat and barley yields by 2.5% and 3.8%, respectively, and have slightly increased maize and sugar beet yields. These averages disguise large heterogeneity across the continent, with regions around the Mediterranean experiencing significant adverse impacts on most crops. This result means that climate trends can account for ∼ 10% of the stagnation in European wheat and barley yields, with likely explanations for the remainder including changes in agriculture and environmental policies.

Emotional intelligence instruction in a pharmacy communications course.

OBJECTIVES: To determine the benefits of incorporating emotional intelligence instruction into a required pharmacy communications course. DESIGN: Specific learning objectives were developed based upon the emotional intelligence framework and how it can be applied to pharmacy practice. Qualitative data on student perceptions were collected and analyzed using theme analysis. ASSESSMENT: Students found instruction on emotional intelligence to be a positive experience. Students reported learning the taxonomy of emotional intelligence--a concept that previously was difficult for them to articulate or describe, and could use this knowledge in future pharmacy management situations. Students also recognized that their new knowledge of emotional intelligence would lead to better patient outcomes. CONCLUSION: Students had positive perceptions of the importance of emotional intelligence. They valued its inclusion in the pharmacy curriculum and saw practical applications of emotional intelligence to the practice of pharmacy.