Simulated Climate Change Research Articles

Patterns of foliar fungal diseases and the effects on aboveground biomass in alpine meadow under simulated climate change

1.Global warming and changes in precipitation patterns significantly affect plant fungal diseases, especially plant foliar fungal diseases. Research surrounding the effects of climate change on plants are mostly concentrated on aboveground vegetation and belowground soil microorganisms, with limited attention given to foliar fungal disease. Additionally, little is known whether climate change experiments can simulate the impact of variations on foliar diseases within real natural communities.2.We conducted a long-term experiment to investigate the effect of warming and altered precipitation on plant disease in an alpine grassland on the north-eastern Tibetan Plateau. Our study tracked foliar disease across 26 species of plants including non-legume forbs, legumes, grasses and sedges from 2019 to 2021. Each species was included in a two-factor full factorial experiment manipulating both temperature and precipitation.3.In our study the non-legume forb functional group carried the primary pathogen load, sedges maintained a near zero pathogen load across all investigated scenarios. Warming significantly elevated the pathogen load in legumes and non-legume forbs, while it reduced the pathogen load of grasses. Conversely, decreased precipitation significantly increased the pathogen load of non-legume forbs and increased the pathogen load of grasses. Notably, we found that pathogen load was primarily influenced by the direct effects of warming and precipitation, rather than indirectly through changes in plant community structure. Meanwhile, interannual climate variability exhibited a strong correlation with plant community pathogen loads. Areas experiencing increased temperature and precipitation showed lower fungal disease pressure, whereas regions with elevated temperatures combined with decreased precipitation faced a heightened risk of disease in alpine meadows on the Qinghai-Tibet Plateau.4.Our findings reveal that warming and decreased precipitation led to a reduction in above-ground biomass associated with increased the pathogen load of legumes. This underscores the importance of pathogen effects in both climate change prediction and ecological management.

Response of the upper ocean to northeast Pacific atmospheric rivers under climate change

Atmospheric rivers are important transport vehicles for Earth’s water cycle. Using a high-resolution, eddy-resolving Earth System Model, atmospheric river impacts on the upper ocean are investigated by analyzing historical and climate change simulations. For atmospheric rivers along the North American coastline, strong winds cause significant dynamic and thermodynamic upper ocean responses. They push ocean water towards the coast, measured by sea surface height, a process that is amplified under climate change. Mixed layers are deeper upstream of atmospheric rivers, and shallower downstream, however for climate change, shoaling downstream is subdued. Air-sea heat fluxes tend to promote ocean cooling upstream and warming downstream, although different regions have different climate change heat flux signals. Southern California heat flux changes due to warming are driven by evaporative processes and strengthen the ocean responses seen in historical simulations. The regions north are primarily dominated by sensible heat flux changes and counter the historical patterns.

Increasing temperature threatens post‐fire auto‐successional dynamics of a Mediterranean obligate seeder

Abstract Reproductive traits influence plant auto‐successional dynamics in post‐fire regeneration. Obligate seeding species rely on their seedbank and on the climatic conditions following the fire to ensure a successful recovery, defining the window of opportunity for seedling emergence. In the Mediterranean basin, emergence opportunities generally begin with autumnal rains. However, climate change‐induced increases in temperature and drought could jeopardise the regeneration capacity of seeding species by causing temporal shifts in emergence opportunities or by modifying wildfire seasonality. This study aimed to explore the impact of experimentally induced climate change on regeneration dynamics of Aleppo pine (Pinus halepensis), a serotinous Mediterranean obligate seeder. In March 2021, we set up an 18‐month climate change simulation experiment with 15 open‐top chambers (OTC), each paired with a control subplot (CON) on top of Aleppo pines that were naturally regenerating after a stand‐replacing wildfire in SW Catalonia (June 2019). We tagged 178 young Aleppo pine recruits in OTC and CON subplots (98 and 81 respectively), classified according to their initial size, to periodically measure height growth and survival throughout the experiment duration. Furthermore, Aleppo pine seeds were seasonally sown (7900 total seeds) in 10 subplot pairs between May 2021 and April 2022, to monthly monitor temporal patterns of seedling emergence and survival. We found that OTCs reduced overall emergence rates and caused the loss of the autumnal window of opportunity for the emergence of Aleppo pine seedlings. Furthermore, seedlings which emerged within OTCs faced higher mortality rates in all seasons, with only 1% of seedlings surviving compared with 21.1% of seedlings in control plots. The OTC‐induced conditions were also detrimental to the survival of recruited seedlings, especially those with a smaller initial size, although no significant effects of temperature increase were found on growth. Synthesis. Climate change is likely to interfere with the post‐fire regeneration dynamics of obligate seeders by shortening the temporal window of opportunities for emergence and by enhancing the bottleneck effects throughout the recruitment process in the early phases of pine demographic recovery. Altogether, it could threaten post‐fire regeneration by increasing the hazard of a demographic collapse of Aleppo pine.

Climate decision making: influence of prevailing social norms and probability of climate change

IntroductionThe global rise in climatic calamities necessitates effective strategies for understanding and addressing Earth’s climate complexities. Although recent research underscores simulation tools’ effectiveness in elucidating complex concepts related to Earth’s climate, partner influence on climatic decisions within simulation studies has been overlooked.MethodsEmploying the Partner Interactive Climate Change Simulator (P-ICCS), we examined 180 participants across varied conditions. The study manipulated partner nature (optimal, irrational, or none) and climate change probability (high or low) to observe effects on participants’ responses (mitigation or adaptation) within P-ICCS.ResultsResults revealed a significant impact of partner presence, with the optimal partner notably enhancing monetary investments against climate change compared to the irrational partner. Intriguingly, climate change probability did not sway participants’ investment behavior.DiscussionThe findings emphasize the pivotal role of partner influence in climate decision-making, offering insights for effective mitigation and adaptation strategies.

Projected impact of solar radiation modification geoengineering on water deficit risk over major Central African river basins

Abstract The economy of Central African countries strongly depends on rain-fed agriculture and hydropower generation. However, most countries in this subregion do not yet have the irrigation technologies that are already applied in many more advanced nations, which further exposes them to the serious risk of severe drought caused by global warming. This study investigates the potential impact of solar radiation modification (SRM) geoengineering on the water availability over the four major river basins that cross most of Central African countries (i.e. Niger Basin, Lake Chad Basin, Cameroon Atlantic Basin (CAB) and Congo Basin). For this purpose a potential water availability index was computed based on an ensemble-mean simulations carried out in the framework of Phase 6 of the Geoengineering Model Intercomparison Project considering two SRM simulation experiments: the stratospheric sulphate aerosol injection (G6sulfur) and the global solar dimming (G6solar). The climate change simulation results in a robust decreases by up to 60% in water availability, most pronounced over the CAB under the high radiative forcing scenario. Therefore, in a business-as-usual world, the reduction in water availability combined with the rapid population growth expected by 2050 in the studied subregion, could result in a significant water deficit over Central African countries towards the end of the 21st century. This water deficit could affect all activities that depend on water resources, such as water supply, agriculture and hydropower generation. Furthermore, the results also show that SRM methods have the potential to significantly reduce this deficit by increasing water availability (as compared to climate change) by up to 50% over the affected river basins, with a more accentuated increase found in the CAB when the global solar dimming is applied. These results suggest good possibilities of adaptation for populations living in the geographical areas of these river basins.

Evaluating MONICA's capability to simulate water, carbon and nitrogen fluxes in a wet grassland at contrasting water tables

Wet grasslands, which are vital for water and nutrient regulation, are characterised by distinct water, carbon (C) and nitrogen (N) dynamics, and their interactions. Due to their shallow groundwater table, wet grasslands promote a strong interconnection between diverse vegetation and soil water. Researchers have investigated how wet grasslands respond to environmental changes, using various simulation models to understand how these sites contribute to water, C and N dynamics. However, a comprehensive, simultaneous study of all three of these dynamics is still lacking. This study makes use of a grassland lysimeter study with differently managed groundwater levels and employs the process-based MOdel for NItrogen and Carbon dynamics in Agroecosystems (MONICA) to simulate these dynamics. By using SPOTPY (Statistical Parameter Optimization Tool) to optimise the relevant parameters, we find that MONICA performs well in simulating vegetation growth (aboveground biomass), and elements of the water (evapotranspiration), C (gross primary productivity, ecosystem respiration) and N (N in aboveground biomass, nitrate in soil solution, Nitrous oxide emissions) balance, with Willmott's Refined Index of Agreement always larger than 0.35. This level of accuracy demonstrates that MONICA is ready to be applied for scenario simulations of groundwater management and climate change to evaluate their impact on greenhouse gas emissions and long-term carbon storage, as well as water and nitrogen losses in wet grasslands.

Simulations of Climate Change: CGI and Hyperreal Representation in The Day After Tomorrow (2004) and Geostorm (2017)

Simulations of Climate Change: CGI and Hyperreal Representation in The Day After Tomorrow (2004) and Geostorm (2017)

Organic matter decay and bacterial community succession in mangroves under simulated climate change scenarios.

Mangroves are coastal environments that provide resources for adjacent ecosystems due to their high productivity, organic matter decomposition, and carbon cycling by microbial communities in sediments. Since the industrial revolution, the increase of Greenhouse Gases (GHG) released due to fossil fuel burning led to many environmental abnormalities such as an increase in average temperature and ocean acidification. Based on the hypothesis that climate change modifies the microbial diversity associated with decaying organic matter in mangrove sediments, this study aimed to evaluate the microbial diversity under simulated climate change conditions during the litter decomposition process and the emission of GHG. Thus, microcosms containing organic matter from the three main plant species found in mangroves throughout the State of São Paulo, Brazil (Rhizophora mangle, Laguncularia racemosa, and Avicennia schaueriana) were incubated simulating climate changes (increase in temperature and pH). The decay rate was higher in the first seven days of incubation, but the differences between the simulated treatments were minor. GHG fluxes were higher in the first ten days and higher in samples under increased temperature. The variation in time resulted in substantial impacts on α-diversity and community composition, initially with a greater abundance of Gammaproteobacteria for all plant species despite the climate conditions variations. The PCoA analysis reveals the chronological sequence in β-diversity, indicating the increase of Deltaproteobacteria at the end of the process. The GHG emission varied in function of the organic matter source with an increase due to the elevated temperature, concurrent with the rise in the Deltaproteobacteria population. Thus, these results indicate that under the expected climate change scenario for the end of the century, the decomposition rate and GHG emissions will be potentially higher, leading to a harmful feedback loop of GHG production. This process can happen independently of an impact on the bacterial community structure due to these changes.

Morphological changes in eggs and embryos of Aedes aegypti (Diptera: Culicidae) exposed to predicted climatic scenarios for the year 2100 in the Central Amazon

According to the IPCC, by the year 2100, rises in global temperature could reach up to 5 °C above current averages. On a planet-wide scale, this is one of the effects of climate changes that could have repercussions on the biological cycle of Aedes aegypti, the main arbovirus vector in urban environments and a transmitter of the arboviruses that cause dengue, Zika, chikungunya and urban yellow fever. The objective of this study was to evaluate morphological changes in Ae. aegypti eggs and embryos maintained in a climate change simulator. For this, specimens obtained from an insectarium were kept in four chambers that simulated the range of environmental scenarios predicted by the IPCC for the year 2100. The eggs obtained from each room were collected and transported to the laboratory for morphometric and morphological analysis, using confocal and scanning microscopy. Aedes aegypti eggs (n=20) were used to obtain the following variables: total width, total length, length-width ratio and diameter of the micropylar disc. Additionally, 20 embryos were used to obtain the data on head capsule length, width and length-width ratio. The data were subjected to a normality test and the means of each variable were compared using ANOVA and Tukey's post-hoc test, considering (p ≤ 0.05). A significant reduction (p < 0.05) was observed mainly in the mean lengths under the current-extreme scenario (587.5 and 553.6 μm, respectively), as well as in the widths under the current-mild scenario (171 and 158.4 μm, respectively). The length of the cephalic capsule was also affected, showing significant differences in the means under the current-intermediate scenario (189.5 and 208.5 μm, respectively), as well as in the widths between the current-intermediate scenarios (173.7 and 194.9 μm, respectively). The results suggest significant changes in the morphometry of Ae. aegypti eggs and embryos as a result of the climatic influences to which the adults were subjected, which may have an impact on vector population density and, consequently, on arbovirus dynamics in urban environments.

Methane-cycling microbial communities from Amazon floodplains and upland forests respond differently to simulated climate change scenarios

Seasonal floodplains in the Amazon basin are important sources of methane (CH4), while upland forests are known for their sink capacity. Climate change effects, including shifts in rainfall patterns and rising temperatures, may alter the functionality of soil microbial communities, leading to uncertain changes in CH4 cycling dynamics. To investigate the microbial feedback under climate change scenarios, we performed a microcosm experiment using soils from two floodplains (i.e., Amazonas and Tapajós rivers) and one upland forest. We employed a two-factorial experimental design comprising flooding (with non-flooded control) and temperature (at 27 °C and 30 °C, representing a 3 °C increase) as variables. We assessed prokaryotic community dynamics over 30 days using 16S rRNA gene sequencing and qPCR. These data were integrated with chemical properties, CH4 fluxes, and isotopic values and signatures. In the floodplains, temperature changes did not significantly affect the overall microbial composition and CH4 fluxes. CH4 emissions and uptake in response to flooding and non-flooding conditions, respectively, were observed in the floodplain soils. By contrast, in the upland forest, the higher temperature caused a sink-to-source shift under flooding conditions and reduced CH4 sink capability under dry conditions. The upland soil microbial communities also changed in response to increased temperature, with a higher percentage of specialist microbes observed. Floodplains showed higher total and relative abundances of methanogenic and methanotrophic microbes compared to forest soils. Isotopic data from some flooded samples from the Amazonas river floodplain indicated CH4 oxidation metabolism. This floodplain also showed a high relative abundance of aerobic and anaerobic CH4 oxidizing Bacteria and Archaea. Taken together, our data indicate that CH4 cycle dynamics and microbial communities in Amazonian floodplain and upland forest soils may respond differently to climate change effects. We also highlight the potential role of CH4 oxidation pathways in mitigating CH4 emissions in Amazonian floodplains.

Carbon Pricing, Carbon Dividends and Cooperation: Experimental Evidence

We investigated whether carbon taxes with and without carbon dividends improve cooperative behavior to mitigate simulated climate change. We implemented a randomized controlled trial on a large sample of the U.S. general population (N=2,116). Played in real-time in groups of four, we tested three carbon-pricing treatments and a baseline condition within a modified threshold public goods game of loss avoidance. We found that a carbon tax coupled with carbon dividends reduces carbon-emitting group consumption relative to a baseline condition with no tax, and relative to a carbon tax only. A carbon tax coupled with carbon dividends paid out to below-average polluters (asymmetric dividend) worked best, with 94% of groups remaining below a critical consumption (emission) threshold. We also found that experiencing the asymmetric dividend condition positively affected perceptions of carbon pricing with carbon dividends.

Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model

Simulation of climate changes in Northern Eurasia by two versions of the INM RAS Earth system model

Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change

Climate sensitivity and relative humidity changes in global storm-resolving model simulations of climate change

Simulated climate change and atrazine contamination can synergistically impair zebrafish testicular function

Elements that interfere with reproductive processes can have profound impacts on population and the equilibrium of ecosystems. Global warming represents the major environmental challenge of the 21st century, as it will affect all forms of life in the coming decades. Another coexisting concern is the persistent pollution by pesticides, particularly the herbicide Atrazine (ATZ), which is responsible for a significant number of contamination incidents in surface waters worldwide. While it is hypothesized that climate changes will significantly enhance the toxic effects of pesticides, the actual impact of these phenomena remain largely unexplored. Here, we conducted a climate-controlled room experiment to assess the interactive effects of the projected 2100 climate scenario and environmentally realistic ATZ exposures on the reproductive function of male zebrafish. The gonadosomatic index significantly decreased in fish kept in the extreme scenario. Cellular alterations across spermatogenesis phases led to synergic decreased sperm production and increased germ cell sloughing and death. ATZ exposure alone or combined with climate change effects, disrupted the transcription levels of key genes involved in steroidogenesis, hormone signaling and spermatogenesis regulation. An additive modulation with decreased 11-KT production and increased E2 levels was also evidenced, intensifying the effects of androgen/estrogen imbalance. Moreover, climate change and ATZ independently induced oxidative stress, upregulation of proapoptotic gene and DNA damage in post-meiotic germ cell, but the negative effects of ATZ were greater at extreme scenario. Ultimately, exposure to simulated climate changes severely impaired fertilization capacity, due to a drastic reduction in sperm motility and/or viability. These findings indicate that the future climate conditions have the potential to considerably enhance the toxicity of ATZ at low concentrations, leading to significant deleterious consequences for fish reproductive function and fertility. These may provide relevant information to supporting healthcare and environmental managers in decision-making related to climate changes and herbicide regulation.

Analyzing single-action bias in dynamic climate change environments: insights from feedback and probability

“Single action bias” (SAB) characterizes individuals’ inclination to undertake only one preventive measure against climate change, disregarding potentially more effective alternatives. This bias poses a significant obstacle to comprehensive responses to climate change. While dynamic climate simulators have been developed to raise awareness of climate change and encourage pro-environmental behaviors, the prevalence of SAB within these tools remains unexplored. This study introduces the “Single Action Bias-Interactive Climate Change Simulator” (SAB-ICCS) to investigate SAB’s manifestation in dynamic scenarios. Utilizing the framework of the Interactive Climate Change Simulator (ICCS), known for its efficacy in fostering pro-environmental actions, the SAB-ICCS explores how feedback, probability, and their interplay influence SAB prevalence during climate mitigation and adaptation decision-making. A total of 160 participants were randomly assigned to four conditions in the SAB-ICCS, varying feedback presence and climate change probability. Participants engaged in climate mitigation and adaptation actions, simulating the repercussions of climate change through investment choices in climate mitigation and adaptation (consisting of three insurance plans). The study’s dependent variables were the participants’ actions towards climate mitigation and adaptation. Results revealed a substantial prevalence of single action proportion (42%) compared to other action proportions. Furthermore, the total monetary investment was significantly higher when taking optimal actions than when exhibiting SAB. Moreover, a higher probability of climate change resulted in a higher prevalence of SAB (49%) than a lower probability (35%). Interestingly, feedback availability did not significantly impact SAB prevalence. Though both feedback and the probability of climate change influenced how participants exhibited SAB, and the absolute monetary investment was also significantly affected. This research enhances our comprehension of SAB within educational climate simulations, which is vital for informing climate education and policymaking. It offers insights for policymakers and educators to develop interventions addressing SAB, enhancing climate action strategies by understanding probability and feedback influences.

Spatial Monte Carlo Simulation and Analysis of Climate Change Enhanced Fire and Projected Landscape-Scale Variation in Vegetation Heterogeneity

Spatial Monte Carlo Simulation and Analysis of Climate Change Enhanced Fire and Projected Landscape-Scale Variation in Vegetation Heterogeneity

Data Assimilation Informed Model Structure Improvement (DAISI) for Robust Prediction Under Climate Change: Application to 201 Catchments in Southeastern Australia

AbstractThis paper presents a method to analyze and improve the set of equations constituting a rainfall‐runoff model structure based on a combination of a data assimilation algorithm and polynomial updates to the state equations. The method, which we have called “Data Assimilation Informed model Structure Improvement” (DAISI) is generic, modular, and demonstrated with an application to the GR2M model and 201 catchments in South‐East Australia. Our results show that the updated model generated with DAISI generally performed better for all metrics considered included Kling‐Gupta Efficiency, NSE on log transform flow and flow duration curve bias. In addition, the elasticity of modeled runoff to rainfall is higher in the updated model, which suggests that the structural changes could have a significant impact on climate change simulations. Finally, the DAISI diagnostic identified a reduced number of update configurations in the GR2M structure with distinct regional patterns in three sub‐regions of the modeling domain (Western Victoria, central region, and Northern New South Wales). These configurations correspond to specific polynomials of the state variables that could be used to improve equations in a revised model. Several potential improvements of DAISI are proposed including the use of additional observed variables such as actual evapotranspiration to better constrain internal model fluxes.

The relative importance of precipitation change and temperature sensitivity in determining the population viability of a threatened sub‐tropical rainforest endemic plant Triunia robusta (Proteaceae)

AbstractThreatened species in rainforests may be vulnerable to climate change, because of their potentially narrow thermal tolerances, small population sizes, restricted distributions and limited dispersal. We investigated the relative influence of potential climate change on the population viability of Triunia robusta (Proteaceae), an endangered rainforest shrub endemic to southeast Queensland, Australia. A spatially explicit, stochastic population model with seven stage classes was developed and linked with the species distribution model (SDM) to explore a variety of hypothetical climate change simulations over a 90‐year period from 2010 to 2100: (1) constant population dynamics, (2) changes in habitat distributions as trend in carrying capacity and (3) changes in habitat distributions, precipitation and temperature regime as relative change in seedling survival and fecundity. The results revealed high vulnerability of small populations to local extinction regardless of geographical location or climatic stressors, while some larger populations located in the southern end of the species distribution range showed persistence in‐situ. Triunia robusta was found to be sensitive to reduced precipitation and increased temperature, limiting the species reproductive activities and seedling establishment and reducing the overall abundance consequently. Integration of population models and SDM allowed for the evaluation of multiple climatic stressors that may affect habitat distributions and population dynamics of T. robusta and ultimately suggest potential implications for future conservation and management planning with respect to climate change.

Regional uniqueness of tree species composition and response to forest loss and climate change

The conservation and restoration of forest ecosystems require detailed knowledge of the native plant compositions. Here, we map global forest tree composition and assess the impacts of historical forest cover loss and climate change on trees. The global occupancy of 10,590 tree species reveals complex taxonomic and phylogenetic gradients determining a local signature of tree lineage assembly. Species occupancy analyses indicate that historical forest loss has significantly restricted the potential suitable range of tree species in all forest biomes. Nevertheless, tropical moist and boreal forest biomes display the lowest level of range restriction and harbor extremely large ranged tree species, albeit with a stark contrast in richness and composition. Climate change simulations indicate that forest biomes are projected to differ in their response to climate change, with the highest predicted species loss in tropical dry and Mediterranean ecoregions. Our findings highlight the need for preserving the remaining large forest biomes while regenerating degraded forests in a way that provides resilience against climate change.

Applicability of CHIRPS-based Pitman model for simulation of climate change flows

Hydrological modelling and continuous monitoring are important for the management of water resources, especially with intensified climate variability. Effective water management is reliant on the availability of climate data and simulations of future projections of the available water resources. The increased likelihood of climatic extremes has made effective water management challenging, especially for vulnerable data-scarce catchments that are highly reliant on natural water resources and have low adaptive capacities. However, advancements in remote sensing have availed alternative sources of climate data for hydrological studies of such catchments. This research evaluated the applicability of Climate Hazards Group Infrared Precipitation with Station data (CHIRPS) in simulating climate change flows. Climate change data of 11 Global Circulatory Models (GCMs), enforced by Representative Concentration Pathways (RCP) 4.5 & 8.5 were downloaded and downscaled to represent near (2021–2060) and far (2061–2099) future scenarios. Climate change signals were derived by comparing future scenarios with the present-day period (1981–2019). Climate change signals were then used to adjust input climate data for the Pitman model. The Pitman model was calibrated and projected future flows were simulated for study catchments in drainage regions B, V and G of South Africa. Climate change simulation results demonstrated projected decreases of between 1.49% and 29.96% for the near future scenarios & between 0.45% and 40.31% for the far future scenarios in all the study catchments. Simulated flows for drainage region B recorded contrasting increasing projections of between 17.18% and 24.88% (RCP 4.5) for the near future scenarios while drainage region G also illustrated contrasting increasing projections of between 6.23% and 7.67% (RCP 4.5) for the far future scenarios. Generally, the results of simulated climate change flows based on observed rainfall and CHIRPS data demonstrated decreasing future flows for the South African case study catchments, corroborating with previous studies in projecting a drier future. This research hence recommends the application of CHIRPS estimates as a suitable substitute to dwindling observed rainfall data in the simulation of climate change flows for data-scarce catchments using the Pitman model.