Future Climate Research Articles

Impact of Fire Recurrence and Water Stress on the Root Nucleolar Activity of Maritime Pine (Pinus pinaster Ait.) Individuals Whose Seeds Were Harvested in Post-Fire Naturally Regenerated Stands

The main role of the nucleolus is ribosomal biogenesis, but it also responds to stress with changes in number, area, and/or morphology. Nucleoli with transcriptionally active ribosomal RNA genes are selectively stained by silver nitrate. Hypothesising that fire recurrence and/or polyethylene glycol (PEG)-induced water stress would cause nucleolar changes in Pinus pinaster roots, nucleolar parameters were analysed upon the germination of seeds harvested in post-fire naturally regenerated stands with different fire regimes. An unburned stand was used as a control. The nucleoli number varied from 1 to 15 among stands and PEG treatments, but a mode of five or six nucleoli was found. The number of nucleoli per interphase (N) increased (p < 0.001) with fire recurrence (stand effect). Increasing PEG concentration (treatment effect) decreased the nucleoli number, notably in the stand with the highest fire recurrence. The nucleolar area decreased (p < 0.001) with increased nucleoli number, fire recurrence, and/or PEG concentration. Fire recurrence and water scarcity are forecasted for future climate scenarios. As demonstrated earlier, these factors could influence protein synthesis or the cell cycle’s regularity, which are crucial processes for root growth and pine seedling establishment. Furthermore, this work revealed that nucleolar parameters could be suitable biomarkers for pine stress studies.

Investigation of the impact of diverse climate conditions on the cultivation suitability of Cinnamomum cassia using the MaxEnt model, HPLC and chemometric methods in China

Cinnamomum cassia Presl. is a subtropical plant that is used for food and medicine. Climate change has changed the suitable habitats of medicinal plants, which might have repercussions for the efficacy of herbal remedies. In this study, the potential distribution in each period of Cinnamomum cassia was predicted and the quality in different suitable habitats was evaluated. According to the results, (1) precipitation, temperature, and soil are the primary environmental variables influencing C. cassia distribution. (2) The high-suitable habitats of current climate scenarios were predominantly located in the southern regions (Guangdong and Guangxi etc.) of China, with an area of 706,129.08 km2. Under future climate scenarios, suitable habitats will increasingly move northward, with a greater concentration south of the Yangtze River, particularly in the 2090s SSP585 scenario, the total area of newly extended suitable habitat reaches 312,963.53 km2. (3) HPLC and FTIR, combined with chemometrics, can be effective methods for identifying different suitable habitats of C. cassia. The content of trans-cinnamaldehyde (0.85%) is significantly higher in the high suitability habitat compared to the medium-low suitability habitat (0.30%). Our findings can offer valuable guidance for the identification of suitable C. cassia cultivation areas in China, as well as for the evaluation of C. cassia resource quality and the rational use of resources in different suitable habitats.

Ex situ spawning, larval development, and settlement in massive reef‐building corals (Porites) in Palau

AbstractReproduction, embryological development, and settlement of corals are critical for survival of coral reefs through larval propagation. Yet, for many species of corals, a basic understanding of the early life‐history stages is lacking. In this study, we report our observations for ex situ reproduction in the massive reef‐building coral Porites cf. P. lobata across 2 years. Spawning occurred in April and May, on the first day after the full moon with at least 2 h of darkness between sunset and moonrise, on a rising tide. Only a small proportion of corals observed had mature gametes or spawned (14–35%). Eggs were 185–311 μm in diameter, spherical, homogenous, and provisioned with 95–155 algal cells (family Symbiodiniaceae). Males spawned before females, and ex situ fertilization rates were high for the first 2 h after egg release. Larvae were elliptical, ~300 μm long, and symbiotic. Just 2 days after fertilization, many larvae swam near the bottom of culture dishes and were competent to settle. Settlers began calcification 2 days after metamorphosis, and tentacles were developed 10 days after attachment. Our observations contrast with previous studies by suggesting an abbreviated pelagic larval period in Porites cf. P. lobata, which could lead to the isolation of some populations. The high thermal tolerance and broad geographic range of Porites cf. P. lobata suggest that this species could locally adapt to a wide range of environmental conditions, especially if larvae are locally retained. The results of this study can inform future work on reproduction, larval biology, dispersal, and recruitment in Porites cf. P. lobata, which could have an ecological advantage over less resilient coral species under future climate change.

Linking individualistic growth stability of trees to the complexity of understorey layers

Abstract Tree‐growth stability is crucial in upholding forest ecosystem services. Despite extensive research on the correlation between tree growth and climate, the influence of forest understorey on tree‐growth stability remains understudied. We surveyed forest plots and collected tree‐ring samples along two elevational gradients, ranging from 3600 to 4400 m a.s.l., in the southeastern Tibetan Plateau. An index was developed to quantify individualistic growth stability of trees, and its linkage with the complexity of forest understorey structure was examined. We found that tree‐growth stability is more pronounced in complex forest communities. In forests with higher understorey complexity, the proportion of trees experiencing growth release increased during wet years, while those with growth suppression augmented during dry years. Interestingly, a subset of trees exhibits abnormal growth increases even during the driest years, whereas another subset shows abnormal growth reductions during the wettest years. Furthermore, forests with more complex understorey structures exhibited a higher proportion of trees showcasing these two types of ‘anti‐phase’ growth statuses. Synthesis. Our study underscores the linkage between individualistic growth stability of trees and the complexity of understorey structures. The growth stability of the overstorey layer is conveyed at the expense of individual‐level growth stability and synchrony in forests with complex understorey structures. These findings emphasize the necessity for attention to the interplay between tree growth and understorey community structures when assessing the impacts of future climate change on forest dynamics.

EVALUATION OF CLIMATE CHANGE IMPACTS ON SUGARCANE AND CITRUS CROPS IN BRAZIL

Agricultural production is directly related to the environmental conditions. Favorable conditions can lead to higher productivity and product quality. However, climate change may pose a threat to agricultural production across the globe, as a rise in temperature may cause a decrease in the extent of suitable areas for growing certain crops. Using spatial analysis and data from future climate change scenarios developed by the IPCC, this research aims to evaluate the impact of climate change on the sugarcane and citrus plantations in the state of Sao Paulo from agroclimatic zoning mapping. The results of this research demonstrate that both crops can suffer great reduction of areas suitable for cultivation if there are severe changes in the climate regime, and these results can be used by managers and researchers to mitigate these potential impacts, as well as to clarify how climate change affects life on the planet, with the possible reduction of food and bioenergy production.

High-resolution modeling and projection of heat-related mortality in Germany under climate change

Abstract Heat is a leading cause of premature deaths during summer months. Understanding the relationship between high temperatures and excess mortality is crucial for designing effective prevention and adaptation plans. Traditional statistical methods have been repeatedly applied to analyze heat-related mortality. However, spatially and temporally high-resolution analyses are challenging due to fragmented data archives across different agglomeration levels, especially for mortality data. We propose a neural network-based model to estimate heat-related mortality. This approach allows for high temporal and spatial resolution estimations, such as regional heat risk during specific heatwaves. Using Germany as a case study, we calculated heat-related excess mortality rates at the district level and visualized the dynamics of local health risks within a heatwave. Overall, we estimated a total of 48,000 heat-related deaths in Germany over the last decade (2014-2023), with most occurring during specific heatwave events. For example, in 2023, the heatwave from July 7-14 contributed approximately 28% (1100 deaths) to the total of about 3,900 heat-related deaths for the entire year. This estimation is consistent with previously published reports from the Robert Koch Institute (RKI), considering the resolution differences in the input data. In addition, we combined our model with shared socio-economic pathways (SSPs) of future climate change, assuming a static population and baseline mortality rate. The results suggest that heat-related risk in Germany could further increase by a factor of 2.5 (SSP245) to 9 (SSP370) without adaptation to extreme heat. Our approach is a valuable tool for the monitoring of regional heat-related risks as well as scenario-based risks projections for the future. The results of the model can help develop climate-driven public health strategies, aiding in the identification of local risks during heatwaves and in long-term resilience planning. Key messages • High-resolution modeling of heat-related mortality helps us to develop targeted adaptation and prevention plans. • The majority of heat-related mortality occurs during heatwaves in summer.

Exploring the effectiveness of virtual reality in combating misinformation on climate change

AbstractOur research examines the potential of immersive virtual reality (VR) in countering climate change misinformation. By creating VR simulations of future climate scenarios, we visually depict the potential impacts of rising temperatures and sea level rise on communities and ecosystems. Our objective is to determine whether immersive VR can achieve more effective correction outcomes compared to social media. We employ a mixed experimental design, manipulating the provision of correction through either VR or social media. We measure the impact of these interventions on belief in and skepticism toward climate change, and on inferential reasoning at three different points over a month. Furthermore, we explore the effectiveness of human actors and the level of presence in the VR experience as strategies to combat climate change misinformation. We find that VR conditions might lead to increased certainty in the belief that climate change is really happening and lowered skepticism toward the clarity of the effects of climate change. Moreover, we find significant differences in the heart rate (HR) of the participants in the VR conditions. The use of avatars in VR environments may contribute to heightened HR variability during misinformation correction, potentially due to increased emotional engagement and cognitive load.

The Vulnerability of Malagasy Protected Areas in the Face of Climate Change

This study examines the vulnerability of Madagascar’s protected areas (PAs) to climate change, focusing on climate change velocity, and its impact on biodiversity. We analyzed current and near future climate data using principal component analysis (PCA) and climate change velocity metrics to predict shifts in climatic conditions from the present to the near future, while under the mild and extreme emission scenarios (SSP 126, SSP 585). Forward velocities, which are characterized by the minimum distances that must be overcome by species to keep in track with their appropriate comparative climate, are most pronounced in western and southern Madagascar. In contrast, the backward velocity, which uses future climatic conditions in grid cells in comparison to current conditions, is more common in the eastern regions of the island, and hints at the minimum distance that organisms would have to overcome in colonizing a new habitat. Even though the correlations between PA size and climate change velocity are weak, there is a tendency for larger PAs to exhibit more stable climatic conditions. Conservation strategies must prioritize enhancing the resilience of PAs through adaptive management to mitigate climate impacts. Our findings provide crucial insights for policymakers and conservation planners to develop climate-smart strategies that ensure the long-term efficacy of Madagascar’s PA network.

Non-adaptedness and vulnerability to climate change threaten Plathymenia trees (Fabaceae) from the Cerrado and Atlantic Forest

Climate change is increasing species extinction risk. The ability of a species to cope with climate change can be quantified by projecting distribution models and by estimating the risk of non-adaptedness using genomic data. The Cerrado and the Atlantic Forest in Tropical South America are increasingly threatened by habitat loss and anthropogenic climate change. This work aims to evaluate the ecological and genomic vulnerability of Plathymenia taxa and its lineages, P. reticulata, a Cerrado species, and P. foliolosa, an Atlantic Forest species, to determine their current and future habitat suitability and the mismatch between current local adaptation with the expected climate changes. The species distribution models predicted a high range loss for the Plathymenia lineages. The genotype-environment association analyses showed that the Plathymenia lineages have populations adapted to different precipitation and temperature seasonality regimes. The genomic offset analyses predict a mismatch between local adaptations and future climate for the Plathymenia indicating a high risk of non-adaptedness, especially in the pessimistic scenario. Our results show an elevated extinction risk of the species due to climate change. We suggest reevaluating the extinction risk and management of the Plathymenia species separately based on their differences in vulnerability to climate change.

Assessing Climate Change Impact on Habitat Suitability and Ecological Connectivity of Wych Elm (Ulmus glabra Huds.) in Türkiye

Understanding how climate change influences the geographical distribution of species within an ecological niche is essential for predicting habitat shifts and informing conservation efforts. This study evaluates the impact of climate change on habitat suitability and ecological connectivity of wych elm (Ulmus glabra Huds.) in Türkiye. The study explores the future distribution of U. glabra and how its connectivity is affected by habitat fragmentation arising from changing climatic conditions. Contextually, this paper aims to achieve two primary objectives: estimating the potential geographical ranges of U. glabra under different climate scenarios and assessing alterations in ecological connections between current and future habitats. The maximum entropy (MaxEnt) model was used along with Morphological Spatial Pattern Analysis (MSPA), and the Probability of Connectivity (PC) index was applied to show possible transformations in distribution patterns of U. glabra over time. The findings suggest that there will be a reduction in the suitability of locations for the species. Moreover, it is expected that under future climate scenarios, ecological connectivity will decline, especially from 2061 to 2100 in the SSP585 scenario. Notably, significant alterations are anticipated during the latter half of the twenty-first century, mainly outside the coastal areas of the Black Sea, where extensive regions would become unsuitable. Additionally, the species is projected to shift its range, decreasing its presence in inland regions while expanding along the coasts. The results show the vulnerability of this species against climate change, thereby demanding adaptive conservation measures to preserve it within the forest ecosystems of Türkiye.

Integrating Machine Learning and Genetic Algorithms to Optimize Building Energy and Thermal Efficiency Under Historical and Future Climate Scenarios

As the global energy demand rises and climate change creates more challenges, optimizing the performance of non-residential buildings becomes essential. Traditional simulation-based optimization methods often fall short due to computational inefficiency and their time-consuming nature, limiting their practical application. This study introduces a new optimization framework that integrates Bayesian optimization, XGBoost algorithms, and multi-objective genetic algorithms (GA) to enhance building performance metrics—total energy (TE), indoor overheating degree (IOD), and predicted percentage dissatisfied (PPD)—for historical (2020), mid-future (2050), and future (2080) scenarios. The framework employs IOD as a key performance indicator (KPI) to optimize building design and operation. While traditional indices such as the predicted mean vote (PMV) and the thermal sensation vote (TSV) are widely used, they often fail to capture individual comfort variations and the dynamic nature of thermal conditions. IOD addresses these gaps by providing a comprehensive and objective measure of thermal discomfort, quantifying both the frequency and severity of overheating events. Alongside IOD, the energy use intensity (EUI) index is used to assess energy consumption per unit area, providing critical insights into energy efficiency. The integration of IOD with EUI and PPD enhances the overall assessment of building performance, creating a more precise and holistic framework. This combination ensures that energy efficiency, thermal comfort, and occupant well-being are optimized in tandem. By addressing a significant gap in existing methodologies, the current approach combines advanced optimization techniques with modern simulation tools such as EnergyPlus, resulting in a more efficient and accurate model to optimize building performance. This framework reduces computational time and enhances practical application. Utilizing SHAP (SHapley Additive Explanations) analysis, this research identified key design factors that influence performance metrics. Specifically, the window-to-wall ratio (WWR) impacts TE by increasing energy consumption through higher heat gain and cooling demand. Outdoor temperature (Tout) has a complex effect on TE depending on seasonal conditions, while indoor temperature (Tin) has a minor impact on TE. For PPD, Tout is a major negative factor, indicating that improved natural ventilation can reduce thermal discomfort, whereas higher Tin and larger open areas exacerbate it. Regarding IOD, both WWR and Tin significantly affect internal heat gains, with larger windows and higher indoor temperatures contributing to increased heat and reduced thermal comfort. Tout also has a positive impact on IOD, with its effect varying over time. This study demonstrates that as climate conditions evolve, the effects of WWR and open areas on TE become more pronounced, highlighting the need for effective management of building envelopes and HVAC systems.

How does temperature affect rural income: Channels and implication of adaptation

AbstractThis paper examines the impact of daily temperature variations on rural income per capita and evaluates the effectiveness of adaptation based on China's county‐level socioeconomic statistics and household survey data. We find that high temperatures have significant negative effects on rural income per capita. Relative to the physically comfortable reference temperature between 10 and 15°C, an additional day with a daily average temperature above 30°C reduces the rural income per capita by 0.12% in the year. Evidence from micro‐data indicates that agricultural income of rural households is sensitive to high temperatures relative to other components of household income, such as wage income and transfer income, which leads to a reallocation of rural laborers across sectors. In addition, we indeed find some evidence of adaptation, but we conclude that the current adaptation pattern of rural households probably magnifies the threat of future climate change to China's agricultural sector.

Identifying key monitoring areas for tree insect pest risks in China under climate change.

Climate change can exacerbate pest population growth, posing significant threats to ecosystem functions and services, social development, and food security. Risk assessment is a valuable tool for effective pest management that identifies potential pest expansion and ecosystem dispersal patterns. We applied a habitat suitability model coupled with priority protection planning software to determine key monitoring areas (KMA) for tree insect pest risks under climate change and used forest ecoregions and nature reserves to assess the ecological risk of insect pest invasion. Finally, we collated the prevention and control measures for reducing future pest invasions. The KMA for tree insect pests in our current and future climate is mainly concentrated in eastern and southern China. However, with climate change, the KMA gradually expands from southeastern to northeastern China. In the current and future climate scenarios, ecoregions requiring high monitoring levels were restricted to the eastern and southern coastal areas of China, and nature reserves requiring the highest monitoring levels were mainly distributed in southeastern China. Tree insect pest invasion assessment using ecoregions and nature reserves identified that future climates increase the risk of pest invasions in forest ecoregions and nature reserves, especially in northeastern China. The increased risk and severity of tree insect pest invasions require implementing monitoring and preventative measures in these areas. We effectively assessed the pest invasion risks using forest ecoregions and nature reserves under climate change. Our assessments suggest that monitoring and early prevention should focus on southeastern and northeastern China.

Comparative analysis of cloud properties over drought- and flood-prone regions of western India using machine learning techniques

ABSTRACT Cloud properties are pivotal in analyzing rainfall patterns globally, especially in monsoon-dependent countries such as India. The impact of climate change becomes more important in regions susceptible to hydrometeorological events due to different monsoon regimes. To examine regional heterogeneity of cloud properties, this study investigates long-term trends and predictive capabilities for cloud properties in drought-prone and flood-prone regions of western India, utilizing satellite data and employing various machine learning (ML) models to comprehend intricate data patterns and enhance predictive accuracy. The results show higher mean and variability in cloud parameters over the flood-prone area due to favorable rain conditions, reflecting higher cloud microphysical and optical properties. These parameters negatively correlate with some cloud macrophysical properties along with the aerosol property in the drought-prone area. Additionally, a moderate correlation exists between certain cloud characteristics of one region and another. Employing ML algorithms for regression analysis and comparing them for cloud effective radius across regions shows promising results, with random forest (RF) demonstrating high coefficient of determination (0.86, 0.93) and low root mean squared error (0.76, 1.15) due to its robustness and high accuracy. This research enhances the understanding of regional heterogeneity in India and shows that ML can be helpful in predicting future cloud dynamics and climate variables identifying the most suitable model.

The influence of aridity on plant intraspecific chemical diversity supports adaptive differentiation and convergent evolution.

Plants synthesize a broad array of specialized chemical compounds that mediate their interactions with the surrounding environment. Some of this chemical diversity is functional and subject to natural selection, but the factors underlying chemical evolution at the intraspecific level remain largely unknown. Here, we combined chemical, environmental and genetic data to investigate the effect of aridity on the expression of chemotypes in the invasive shrub Senecio pterophorus. We studied the variation in pyrrolizidine alkaloids (PAs), a group of specialized metabolites widespread across the families Boraginaceae, Asteraceae and Fabaceae, from native populations spanning a cline of aridity and from three cross-continental introductions, under natural and common garden conditions. We examined whether the relationship between chemistry and aridity was compatible with a process of adaptive differentiation using a method that partitions the variance and covariance by controlling for the population neutral genetic structure. We found a consistent shift from retrorsine-like to seneciphylline-like compounds under increasing aridity in both natural and controlled conditions in coherence with the biosynthetic pathways. This pattern was independent of the neutral genetic structure and occurred along the environmental gradient in the native range and in a convergent manner in all nonnative regions, which suggests adaptive differentiation in response to aridity. Our findings show that the diversity of PAs in S. pterophorus has been partially shaped by aridity. Investigating how abiotic factors influence chemical evolution is key to elucidating the plant responses in future climate scenarios and the cascading effects on other trophic levels.

Quantifying the rainfall variability effects on crop growth and production in the intensified annual forage - winter wheat rotation systems in a semiarid region of China

Replacing summer fallow period (July to September, SF) with annual short-season forages in the traditional fallow-winter wheat (Triticum aestivum L.) system may maintain grain yield and improve productivity in the semi-arid environments. But the uneven and variability rainfall led to instable productivity of the annual forage–winter wheat cropping system. The aims of this study were to 1) quantifying rainfall variability effects on annual forage–winter wheat system crop growing process and productivity; 2) determine the optimal annual forage–winter wheat production system that will response better to future climate change. A four-year (2016–2020) field experiment was conducted to investigate the impact of replacing summer fallow period with annual forages including oat (FO, Avena sativa L.), soybean (SB, Glycine max L.), and vetch (FV, Vicia sativa L.) on plant height (H), leaf area index (LAI), and above-ground biomass (AByield) growth index dynamics under three different levels of rainfall manipulation i.e. 30 % of ambient rainfall exclusion (R-30 %), natural rainfall (CK), and 30 % of ambient rainfall increase (R+30 %). Additionally, we assessed the correlations between forage and winter wheat production with growing season precipitation across 12 rainfall scenarios. Average forage biomass values of oat, soybean, and vetch were 5.50, 4.29, and 2.82 t ha−1, respectively during summer fallow period. The average winter wheat grain yield values in SF, FO, SB, and FV were 3.78, 3.12, 4.02, and 3.18 t ha−1, respectively. Integrating oat into fallow period had negative effects on wheat growth and production, and the H, LAI, and AByield for FO were 63.7 %, 50.9 %, and 29.9 % lower than SF in dry year, but the wheat grain yield in SB were 18.2 % and 24.8 % greater than SF in normal and wet years. Across the four growing seasons, the forage and wheat yields were shown to be strongly related to precipitation, and increasing precipitation significantly enhanced the production. In 2016–2017 growing season, LAI of wheat in SF, FO, SB, and FV with R+30 % scenario was increased by 30.2 %, 21.7 %, 32.7 %, and 19.8 % and that with R-30 % scenario decreased by 23.2 %, 17.8 %, 24.7 %, 16.5 % compared CK, respectively. The traditional summer fallow practice had advantage for maintaining stability in wheat gain production, especially under dry years. In consideration of forage and wheat production to rainfall variability, integrating soybean into fallow season may be an efficient option to maintain wheat yield and produce high forage amount under future climate change on the Loess Plateau and similar semi-arid regions.

Corrosion on cultural heritage buildings in Jordan in current situation and in future climate scenarios

This study examines the impact of air pollution on Jordan’s cultural heritage sites, focusing on key pollutants (SO2, HNO3, O3, PM10) and climate conditions. Using 2019 data and future projections for 2040–2059 and 2080–2099, the research reveals significant material corrosion in urban areas like Amman and Irbid, driven by pollutants such as SO₂ and PM10. Random Forest Analysis identifies these pollutants as primary contributors to material degradation. Future scenarios indicate corrosion rates exceeding safe limits across Jordan, underscoring the need for proactive conservation strategies. This work highlights the critical role of air quality management in protecting cultural heritage, especially under climate change pressures, and provides guidance for national policy development.

Effects of short- and long-term thermal stress on developmental stages and adults vis-à-vis reproductive physiology of Spodoptera litura

Abstract Temperature is a critical environmental factor influencing insect development, physiology, and distribution. Global warming is predicted to increase the frequency and severity of extreme heat events, influencing insects differently across life stages. This study investigates the effects of short- and long-term thermal stress on the tobacco cutworm, Spodoptera litura, a polyphagous pest damaging over 389 plant species. We exposed eggs, larvae, pupae, and adults to elevated temperatures of 42°C and 46°C for four hours and one hour, respectively, in single and repeated occasions for two, four, two and two days for egg, larva, pupa and adults, respectively. Our results demonstrate significant variation in biological and reproductive fitness parameters across treatments. Notably, thermal stress skewed the sex ratio towards females. We also observed impacts on offspring survival and potential negative carry-over effects. Overall, the effects of heat stress were dependent on temperature, exposure duration, and life stage, with adults exhibiting the highest tolerance. These findings suggest that S. litura possesses a degree of heat tolerance that may enable it to survive summer heat waves, but its offspring and other life stages could be more vulnerable under future climate scenarios.

Consecutive one-week model predictions of land surface temperature stay on track for a decade with chaotic behavior tracking

Temperature prediction over decades provides crucial information for quantifying the expected effects of future climate changes. However, such predictions are extremely challenging due to the chaotic nature of temperature variations. Here we devise a prediction method involving an information tracking mechanism that aims to track and adapt to changes in temperature dynamics during the prediction phase by providing probabilistic feedback on the prediction error of the next step based on the current prediction. We integrate this information tracking mechanism, which can be considered as a model calibrator, into the objective function of the proposed method to obtain the corrections needed to avoid error accumulation. Experimental results on the task of global weekly land surface temperature prediction over a decade validate the effectiveness of the proposed method.

Extracting the Ultradeep Oil: David Mitchell’s The Bone Clocks

ABSTRACT David Mitchell’s The Bone Clocks reworks the novel form with its generic experimentation, a gesture in response to the transformed geosocial contours of the Anthropocene. Straddling between the realist and the fantastical, the novel decentralizes human perspective that proves increasingly unsatisfactory to confront the complex causality of climate change for imaginative and conceptual limits. In this essay, I argue that Mitchell attends to a conceptual limit imposed by petroculture, one that refuses to connect the future warming climate with the present large-scale combustion of fossil fuels. The temporal disjunction evolves into a strong antagonism between present and future, which can be tellingly revealed by the coupling of realist and fantastical traditions. Mitchell’s genre-blending device therefore pushes the novel form beyond its usual near-sightedness, excavating a deeper layer of climate-induced crisis of human imagination, namely the present’s inability to recognize the delayed effects of its unsustainable consumption pattern. Viewed through an energy-oriented perspective, The Bone Clocks engages with modernity’s ultradeep relationship with oil, complicating our understanding of climate temporality that matters in terms of intergenerational justice.