Unprecedented climate events: Historical changes, aspirational targets, and national commitments

Exploring the Influence of Summer Temperature on Human Mobility During the COVID-19 Pandemic in the San Francisco Bay Area

Studies on the relationship between temperature and local, small scale mobility are limited, and sensitive to the region and time period of interest. We contribute to the growing mobility literature through a detailed characterization of the observed temperature-mobility relationship in the San Francisco Bay Area at fine spatial and temporal scale across two summers (2020-2021). We used anonymized cellphone data from SafeGraph's neighborhood patterns data set and gridded temperature data from gridMET, and analyzed the influence of incremental changes in temperature on mobility rate (i.e., visits per capita) using a panel regression with fixed effects. This strategy enabled us to control for spatial and temporal variability across the studied region. Our analysis suggested that all areas exhibited lower mobility rate in response to higher summer temperatures. We then explored how several additional variables altered these results. Extremely hot days resulted in faster mobility declines with increasing temperatures. Weekdays were often more resistant to temperature changes when compared to the weekend. In addition, the rate of decrease in mobility in response to high temperature was significantly greater among the wealthiest census block groups compared with the least wealthy. Further, the least mobile locations experienced significant differences in mobility response compared to the rest of the data set. Given the fundamental differences in the mobility response to temperature across most of our additive variables, our results are relevant for future mobility studies in the region.

Diversifying agrifood systems to ensure global food security following the Russia–Ukraine crisis

The recent Russia–Ukraine conflict has raised significant concerns about global food security, leaving many countries with restricted access to imported staple food crops, particularly wheat and sunflower oil, sending food prices soaring with other adverse consequences in the food supply chain. This detrimental effect is particularly prominent for low-income countries relying on grain imports, with record-high food prices and inflation affecting their livelihoods. This review discusses the role of Russia and Ukraine in the global food system and the impact of the Russia–Ukraine conflict on food security. It also highlights how diversifying four areas of agrifood systems—markets, production, crops, and technology can contribute to achieving food supply chain resilience for future food security and sustainability.

Data-driven predictions of the time remaining until critical global warming thresholds are reached

Leveraging artificial neural networks (ANNs) trained on climate model output, we use the spatial pattern of historical temperature observations to predict the time until critical global warming thresholds are reached. Although no observations are used during the training, validation, or testing, the ANNs accurately predict the timing of historical global warming from maps of historical annual temperature. The central estimate for the 1.5 °C global warming threshold is between 2033 and 2035, including a ±1σ range of 2028 to 2039 in the Intermediate (SSP2-4.5) climate forcing scenario, consistent with previous assessments. However, our data-driven approach also suggests a substantial probability of exceeding the 2 °C threshold even in the Low (SSP1-2.6) climate forcing scenario. While there are limitations to our approach, our results suggest a higher likelihood of reaching 2 °C in the Low scenario than indicated in some previous assessments-though the possibility that 2 °C could be avoided is not ruled out. Explainable AI methods reveal that the ANNs focus on particular geographic regions to predict the time until the global threshold is reached. Our framework provides a unique, data-driven approach for quantifying the signal of climate change in historical observations and for constraining the uncertainty in climate model projections. Given the substantial existing evidence of accelerating risks to natural and human systems at 1.5 °C and 2 °C, our results provide further evidence for high-impact climate change over the next three decades.

Seed sourcing strategies for ecological restoration under climate change: A review of the current literature

Climate change continues to alter the seasonal timing and extremes of global temperature and precipitation patterns. These departures from historic conditions along with the predicted variability of future climates present a challenge to seed sourcing, or provenance strategy decisions, within the practice of ecological restoration. The “local is best” for seed sourcing paradigm is predicated upon the assumption that ecotypes are genetically adapted to their local environment. However, local adaptations are potentially being outpaced by climate change, and the ability of plant populations to naturally migrate or shift their distribution accordingly may be limited by habitat fragmentation. Restoration practitioners and natural area managers have a general understanding of the importance of matching the inherent adaptations of source populations with the current and/or future site conditions where those seeds or propagules are planted. However, for many species used in seed-based restoration, there is a lack of empirical evidence to guide seed sourcing decisions, which are critical for the longevity and ecological function of restored natural communities. With the goal of characterizing, synthesizing, and applying experimental research to guide restoration practice, we conducted a systematic review of the literature on provenance testing of taxa undertaken to inform seed sourcing strategies for climate resiliency. We found a strong bias in the choice of study organism: most studies have been conducted on tree species. We also found a strong bias regarding where this research has been conducted, with North America (52%) and Europe (31%) overrepresented. Experiments were designed to assess how propagule origin influences performance across both climatic (26%) and geographic (15%) distance, with some studies focused on determining how climate normal conditions (39%) impacted performance related to survivorship, growth and other parameters. We describe the patterns and gaps our review identified, highlight specific topics which require further research, and provide practical suggestions of immediate and longer-term tools that restoration practitioners can use to guide and build resilient natural communities under future climate scenarios.

Plasticity of salmonfly (Pteronarcys californica) respiratory phenotypes in response to changes in temperature and oxygen

Like all taxa, populations of aquatic insects may respond to climate change by evolving new physiologies or behaviors, shifting their ranges, exhibiting physiological and behavioral plasticity, or by going extinct. We evaluated the importance of plasticity by measuring changes in growth, survival, and respiratory phenotypes of salmonfly nymphs (the stonefly Pteronarcys californica) in response to experimental combinations of dissolved oxygen and temperature. Overall, smaller individuals grew more rapidly during the six-week experimental period, and oxygen and temperature interacted to affect growth in complex ways. Survival was lower for the warm treatment, though only four mortalities occurred (91.6 vs 100%). Nymphs acclimated to warmer temperatures did not have higher critical thermal maxima (CTMAX), but those acclimated to hypoxia had CTMAX values (in normoxia) higher by approximately 1 °C. These results suggest possible adaptive plasticity of systems for taking up or delivering oxygen. We examined these possibilities by measuring the oxygen-sensitivity of metabolic rates and the morphologies of tracheal gill tufts located ventrally on thoracic and abdominal segments. Mass-specific metabolic rates of individuals acclimated to warmer temperatures were higher in acute hypoxia but lower in normoxia, regardless of their recent history of oxygen exposure during acclimation. The morphology of gill filaments, however, changed in ways that appeared to depress rates of oxygen delivery in functional hypoxia. Our combined results from multiple performance metrics indicate that rising temperatures and hypoxia may interact to magnify the risks to aquatic insects, but that physiological plasticity in respiratory phenotypes may offset some of these risks.

Sub-national climate change risk assessment: A case analysis for Tibet and its prefecture-level cities

Avoiding climate change from exceeding its critical threshold is a serious challenge facing humanity at present and in the future. As the mode of global cooperative action is stranded, multi-center and multi-level efforts are needed to deal with global warming in the future. In order to provide information for the formulation of low-carbon development policies, it is essential to assess the maintain or cross of climate change threshold on different scales. In this study, the carbon footprint calculated based on the process coefficient approach is systematically integrated with the climate change indicator of the planetary boundaries framework improved with the goals of the Paris Agreement to identify the climate change risks of Tibet and its prefecture-level cities from 2000 to 2017. Moreover, the main driving factors behind carbon footprint were analyzed. The findings showed that: (1) Since 2000, Tibet's CO₂ emissions have demonstrated steady and rapid increase. The sector composition is dominated by cement production-related and transportation sector-related emissions. The type composition is dominated by diesel-related, process-related, and coal-related emissions. There are significant differences in CO₂ emissions among all prefecture-level cities, with Lhasa having the largest contribution. (2) Except for Lhasa and Shannan's CO₂ emissions that have crossed their critical threshold of climate change and are in an unsafe state, Tibet and other prefecture-level cities have not yet crossed their critical threshold. (3) Except for Ngari, per capita GDP, energy intensity, population size, and carbon intensity positively affect the increase of CO₂ emissions in Tibet and its prefecture-level cities. Our study helps actors at less aggregated scales to determine appropriate policy strengths based on globally agreed goals and ambitions in the process of responding to global warming in a bottom-up manner.

The impact of global climate change on the number and replacement of provisioning ecosystem services of Brazilian Cerrado plants

It is essential to predict areas of losses or exchanges of ecosystem services to adapt communities to the impacts caused by climate change. Particularly for provisioning ecosystem services provided by economically important plant species, understanding the association between climate change impacts and deforestation of native vegetation increases the accuracy of those predictions. Thus, we aim to (i) map the richness of provisioning ecosystem services from economically important native plants; (ii) use forecasts (present and future) of the distribution of ecosystem services to assess areas of changes in the number and type of provisioning ecosystems services. We evaluated provisioning ecosystem services from 110 Cerrado native species of economic importance for the local population. We determined the potential distribution of these plants using ecological niche modeling techniques, which were grouped according to the 21 different services provided. The forecasts for variation in richness and type of service used four future climate change scenarios (RCPs 4.5 and 8.5 in 2050 and 2070). The service losses detected in our models were associated with variables representing the progress of native vegetation deforestation in the biome due to agricultural expansion. Currently, ecosystem services can be found simultaneously in practically the entire biome. However, changes in the global climate will impact the potential geographic distribution of those plants, causing many areas in the biome to have reduced availability of potential ecosystem services. Moreover, due to the association between exposure to climate change and deforestation of native vegetation, the northern region of the biome will likely have the distribution of ecosystem services severely affected.

Genomic Responses to Climate Change: Making the Most of the Drosophila Model

It is pressing to understand how animal populations evolve in response to climate change. We argue that new sequencing technologies and the use of historical samples are opening unprecedented opportunities to investigate genome-wide responses to changing environments. However, there are important challenges in interpreting the emerging findings. First, it is essential to differentiate genetic adaptation from phenotypic plasticity. Second, it is extremely difficult to map genotype, phenotype, and fitness. Third, neutral demographic processes and natural selection affect genetic variation in similar ways. We argue that Drosophila melanogaster, a classical model organism with decades of climate adaptation research, is uniquely suited to overcome most of these challenges. In the near future, long-term time series genome-wide datasets of D. melanogaster natural populations will provide exciting opportunities to study adaptation to recent climate change and will lay the groundwork for related research in non-model systems.

Variability effects by consumers exceed their average effects across an environmental gradient of mussel recruitment

The implicit assumption that properties of natural systems deduced from the average statistics from random samples suffice for understanding them focuses the attention of ecologists on the average effects of processes and responses, and often, to view their variability as noise. Yet, both kinds of effects can drive dynamics of ecological systems and their covariation may confound interpretation. Predation by crabs and snails on competitively dominant mussels has long been recognized as an important process structuring communities on rocky shores of the Northwest Atlantic Ocean. We experimentally manipulated the average intensity of predation in plots across a gradient of mussel recruitment to separately estimate the average and variability of responses of mussel recruitment and community composition. Predation did not affect the average number of mussels recruited to plots, nor the average multivariate composition of the community. Plots from which predators were excluded showed a ~ 30% increase in spatial variability of mussel recruitment. After 1 year, the spatial variability in community composition was greater than that observed among plots that predators could access. An important, but less recognized, aspect of predation is its dampening effect on variability of community structure. As accelerating rates of environmental change disrupt species interactions, variability effects of ecological processes and corresponding responses are likely to be increasingly important determinants of community dynamics.

Annual aboveground carbon uptake enhancements from assisted gene flow in boreal black spruce forests are not long-lasting

Assisted gene flow between populations has been proposed as an adaptive forest management strategy that could contribute to the sequestration of carbon. Here we provide an assessment of the mitigation potential of assisted gene flow in 46 populations of the widespread boreal conifer Picea mariana, grown in two 42-year-old common garden experiments and established in contrasting Canadian boreal regions. We use a dendroecological approach taking into account phylogeographic structure to retrospectively analyse population phenotypic variability in annual aboveground net primary productivity (NPP). We compare population NPP phenotypes to detect signals of adaptive variation and/or the presence of phenotypic clines across tree lifespans, and assess genotype-by-environment interactions by evaluating climate and NPP relationships. Our results show a positive effect of assisted gene flow for a period of approximately 15 years following planting, after which there was little to no effect. Although not long lasting, well-informed assisted gene flow could accelerate the transition from carbon source to carbon sink after disturbance.

The Conflicting Impact of COVID-19’s Health and Economic Crises on Helping

Helping behaviors are considered critical for business and societal recovery in light of economic crises and natural disasters, including the COVID-19 pandemic that has both economic and health disaster elements. However, because the current COVID-19 pandemic has both of these elements, it is unclear how helping may be impacted. Economic crisis research suggests that such events are associated with less helping, whereas disaster research suggests that such events are associated with greater helping. We pair the event system theory (Morgeson, F. P., Mitchell, T. R., & Liu, D. (2015). Event system theory: An event-oriented approach to the organizational sciences. Academy of Management Review, 40(4), 515-537) with these two logics (economic downturn and disaster) to suggest that health and economic threats within the COVID-19 pandemic operate with potentially opposing forces on helping-related outcomes. To test these ideas at a macro-level, we examined internet search volume for recession, COVID-19, and interest in helping. At a micro-level, we examined the relationships between work- hour insecurity and perceived job-related COVID-19 risk—two salient COVID-19-related economic and health threats—and helping customers and coworkers. Consistent with economic crisis logic, macro-level concern about recession was negatively associated with interest in helping. Moreover, at the individual level, work-hour insecurity negatively predicted helping coworkers. Consistent with disaster logic, at the individual level, perceived job-related COVID-19 threat was positively associated with helping coworkers and negatively associated with helping customers. These findings suggest that the specific feature of the COVID-19 event system (economic versus health) and the target (organizational insiders versus outsiders) matter for shaping helping behavior. These findings have implications for helping during crises that involve economic and/or disaster elements.

Verification of extreme event attribution: Using out-of-sample observations to assess changes in probabilities of unprecedented events

Independent verification of anthropogenic influence on specific extreme climate events remains elusive. This study presents a framework for such verification. This framework reveals that previously published results based on a 1961-2005 attribution period frequently underestimate the influence of global warming on the probability of unprecedented extremes during the 2006-2017 period. This underestimation is particularly pronounced for hot and wet events, with greater uncertainty for dry events. The underestimation is reflected in discrepancies between probabilities predicted during the attribution period and frequencies observed during the out-of-sample verification period. These discrepancies are most explained by increases in climate forcing between the attribution and verification periods, suggesting that 21st-century global warming has substantially increased the probability of unprecedented hot and wet events. Hence, the use of temporally lagged periods for attribution-and, more broadly, for extreme event probability quantification-can cause underestimation of historical impacts, and current and future risks.

Harmful algae at the complex nexus of eutrophication and climate change

Climate projections suggest-with substantial certainty-that global warming >1.5 °C will occur by mid-century (2050). Population is also projected to increase, amplifying the demands for food, fuel, water and sanitation, which, in turn, escalate nutrient pollution. Global projections of nutrient pollution, however, are less certain than those of climate as there are regionally decreasing trends projected in Europe, and stabilization of nutrient use in North America and Australia. In this review of the effects of eutrophication and climate on harmful algae, some of the complex, subtle, and non-intuitive effects and interactions on the physiology of both harmful and non-harmful taxa are emphasized. In a future ocean, non-harmful diatoms may be disproportionately stressed and mixotrophs advantaged due to changing nutrient stoichiometry and forms of nutrients, temperature, stratification and oceanic pH. Modeling is advancing, but there is much yet to be understood, in terms of physiology, biogeochemistry and trophodynamics and how both harmful and nonharmful taxa may change in an uncertain future driven by anthropogenic activities.

Reduced tree growth in the semiarid United States due to asymmetric responses to intensifying precipitation extremes

Earth's hydroclimatic variability is increasing, with changes in the frequency of extreme events that may negatively affect forest ecosystems. We examined possible consequences of changing precipitation variability using tree rings in the conterminous United States. While many growth records showed either little evidence of precipitation limitation or linear relationships to precipitation, growth of some species (particularly those in semiarid regions) responded asymmetrically to precipitation such that tree growth reductions during dry years were greater than, and not compensated by, increases during wet years. The U.S. Southwest, in particular, showed a large increase in precipitation variability, coupled with asymmetric responses of growth to precipitation. Simulations suggested roughly a twofold increase in the probability of large negative growth anomalies across the Southwest resulting solely from 20th century increases in variability of cool-season precipitation. Models project continued increases in precipitation variability, portending future growth reductions across semiarid forests of the western United States.

Universal health coverage and primary care, Thailand

Thailand’s policy on universal health coverage (UHC) has made good progress since its inception in 2002. Every Thai citizen is now entitled to essential preventive, curative and palliative health services at all life stages. Like its counterparts elsewhere, however, the policy faces challenges. A predominantly tax-financed system in a nation with a high proportion of people living in poverty will always strive to contain rising costs. Disparities exist among the different health insurance schemes that provide coverage for Thai citizens. National health expenditure is heavily borne by the government, primarily to reduce financial barriers to access for the poor. The population is ageing and the disease profiles of the population are changing alongside the modernization of Thai people’s lifestyles. Thailand is now aiming to enhance and sustain its UHC policy. We examine the merits of different policy options and aim to identify the most promising and feasible way to enhance and sustain UHC. We argue that developing the existing primary care system in Thailand has the greatest potential to provide more self-sustaining, efficient, equitable and effective UHC. Primary care needs to move from its traditional role of providing basic disease-based care, to being the first point of contact in an integrated, coordinated, community-oriented and person-focused care system, for which the national health budget should be prioritized.

Satellite and In Situ Observations for Advancing Global Earth Surface Modelling: A Review

In this paper, we review the use of satellite-based remote sensing in combination with in situ data to inform Earth surface modelling. This involves verification and optimization methods that can handle both random and systematic errors and result in effective model improvement for both surface monitoring and prediction applications. The reasons for diverse remote sensing data and products include (i) their complementary areal and temporal coverage, (ii) their diverse and covariant information content, and (iii) their ability to complement in situ observations, which are often sparse and only locally representative. To improve our understanding of the complex behavior of the Earth system at the surface and sub-surface, we need large volumes of data from high-resolution modelling and remote sensing, since the Earth surface exhibits a high degree of heterogeneity and discontinuities in space and time. The spatial and temporal variability of the biosphere, hydrosphere, cryosphere and anthroposphere calls for an increased use of Earth observation (EO) data attaining volumes previously considered prohibitive. We review data availability and discuss recent examples where satellite remote sensing is used to infer observable surface quantities directly or indirectly, with particular emphasis on key parameters necessary for weather and climate prediction. Coordinated high-resolution remote-sensing and modelling/assimilation capabilities for the Earth surface are required to support an international application-focused effort.

Strengthened scientific support for the Endangerment Finding for atmospheric greenhouse gases

We assess scientific evidence that has emerged since the U.S. Environmental Protection Agency’s 2009 Endangerment Finding for six well-mixed greenhouse gases and find that this new evidence lends increased support to the conclusion that these gases pose a danger to public health and welfare. Newly available evidence about a wide range of observed and projected impacts strengthens the association between the risk of some of these impacts and anthropogenic climate change, indicates that some impacts or combinations of impacts have the potential to be more severe than previously understood, and identifies substantial risk of additional impacts through processes and pathways not considered in the Endangerment Finding.

Climate-driven declines in arthropod abundance restructure a rainforest food web

A number of studies indicate that tropical arthropods should be particularly vulnerable to climate warming. If these predictions are realized, climate warming may have a more profound impact on the functioning and diversity of tropical forests than currently anticipated. Although arthropods comprise over two-thirds of terrestrial species, information on their abundance and extinction rates in tropical habitats is severely limited. Here we analyze data on arthropod and insectivore abundances taken between 1976 and 2012 at two midelevation habitats in Puerto Rico's Luquillo rainforest. During this time, mean maximum temperatures have risen by 2.0 °C. Using the same study area and methods employed by Lister in the 1970s, we discovered that the dry weight biomass of arthropods captured in sweep samples had declined 4 to 8 times, and 30 to 60 times in sticky traps. Analysis of long-term data on canopy arthropods and walking sticks taken as part of the Luquillo Long-Term Ecological Research program revealed sustained declines in abundance over two decades, as well as negative regressions of abundance on mean maximum temperatures. We also document parallel decreases in Luquillo's insectivorous lizards, frogs, and birds. While El Niño/Southern Oscillation influences the abundance of forest arthropods, climate warming is the major driver of reductions in arthropod abundance, indirectly precipitating a bottom-up trophic cascade and consequent collapse of the forest food web.

Climate Shifts within Major Agricultural Seasons for +1.5 and +2.0 °C Worlds: HAPPI Projections and AgMIP Modeling Scenarios

This study compares climate changes in major agricultural regions and current agricultural seasons associated with global warming of +1.5 or +2.0 °C above pre-industrial conditions. It describes the generation of climate scenarios for agricultural modeling applications conducted as part of the Agricultural Model Intercomparison and Improvement Project (AgMIP) Coordinated Global and Regional Assessments. Climate scenarios from the Half a degree Additional warming, Projections, Prognosis and Impacts project (HAPPI) are largely consistent with transient scenarios extracted from RCP4.5 simulations of the Coupled Model Intercomparison Project phase 5 (CMIP5). Focusing on food and agricultural systems and top-producing breadbaskets in particular, we distinguish maize, rice, wheat, and soy season changes from global annual mean climate changes. Many agricultural regions warm at a rate that is faster than the global mean surface temperature (including oceans) but slower than the mean land surface temperature, leading to regional warming that exceeds 0.5 °C between the +1.5 and +2.0 °C Worlds. Agricultural growing seasons warm at a pace slightly behind the annual temperature trends in most regions, while precipitation increases slightly ahead of the annual rate. Rice cultivation regions show reduced warming as they are concentrated where monsoon rainfall is projected to intensify, although projections are influenced by Asian aerosol loading in climate mitigation scenarios. Compared to CMIP5, HAPPI slightly underestimates the CO2 concentration that corresponds to the +1.5 °C World but overestimates the CO2 concentration for the +2.0 °C World, which means that HAPPI scenarios may also lead to an overestimate in the beneficial effects of CO2 on crops in the +2.0 °C World. HAPPI enables detailed analysis of the shifting distribution of extreme growing season temperatures and precipitation, highlighting widespread increases in extreme heat seasons and heightened skewness toward hot seasons in the tropics. Shifts in the probability of extreme drought seasons generally tracked median precipitation changes; however, some regions skewed toward drought conditions even where median precipitation changes were small. Together, these findings highlight unique seasonal and agricultural region changes in the +1.5°C and +2.0°C worlds for adaptation planning in these climate stabilization targets.