Effects Of Climate Variability Research Articles

Predicting the potential distribution of Dendrolimus punctatus and its host Pinus massoniana in China under climate change conditions

IntroductionDendrolimus punctatus, a major pest endemic to the native Pinus massoniana forests in China, displays major outbreak characteristics and causes severe destructiveness. In the context of global climate change, this study aims to investigate the effects of climatic variations on the distribution of D. punctatus and its host, P. massoniana. MethodsWe predict their potential suitable distribution areas in the future, thereby offering a theoretical basis for monitoring and controlling D. punctatus, as well as conserving P. massoniana forest resources. By utilizing existing distribution data on D. punctatus and P. massoniana, coupled with relevant climatic variables, this study employs an optimized maximum entropy (MaxEnt) model for predictions. With feature combinations set as linear and product (LP) and the regularization multiplier at 0.1, the model strikes an optimal balance between complexity and accuracy.ResultsThe results indicate that the primary climatic factors influencing the distribution of D. punctatus and P. massoniana include the minimum temperature of the coldest month, annual temperature range, and annual precipitation. Under the influence of climate change, the distribution areas of P. massoniana and its pests exhibit a high degree of similarity, primarily concentrated in the region south of the Qinling−Huaihe line in China. In various climate scenarios, the suitable habitat areas for these two species may expand to varying degrees, exhibiting a tendency to shift toward higher latitude regions. Particularly under the high emission scenario (SSP5-8.5), D. punctatus is projected to expand northwards at the fastest rate. DiscussionBy 2050, its migration direction is expected to closely align with that of P. massoniana, indicating that the pine forests will continue to be affected by the pest. These findings provide crucial empirical references for region-specific prevention of D. punctatus infestations and for the rational utilization and management of P. massoniana resources.

Contrasting responses of forest phenological guilds to complex floodplain change

Abstract Understanding the seasonal dynamics of the forest herb layer and the factors that influence it is essential for predicting how the forest ecosystem, including mutualistic interactions, will respond to global change. However, to date, no research has investigated how understorey phenological guilds respond to major environmental threats and forest interventions. We showed the marked changes in the phenological structure of floodplain forest plant communities over half a century at a multi‐regional scale in Central Europe. Unlike previous studies focusing on individual species' responses to climate change, we examined shifts in species richness, frequency and abundance between phenological guilds within the plant community. We examined the effects of temporal variation in climate, hydrology, soil conditions and canopy structure, and assessed the effects of non‐intervention and intervention management on phenological guild responses. Our results show a significant loss of local species richness and a decline in species frequency in the forest understorey vegetation, associated with species exhibiting summer phenology. In contrast, an increase in abundance and richness of spring flowering species was observed, attributed to high nutrient loads and reduced flooding, respectively. The abundance of spring species increased only in stands where canopy cover increased over time, probably due to the suppression of summer flowering species, allowing spring flowering species to spread on open, bare ground. The community experienced a shift in maximum flowering plant richness from June to May. Despite management interventions such as clearcutting and tree planting, our data show similar temporal trajectories in intervention and non‐intervention forests, indicating that changes in phenological structure are largely independent of recent management activities. Synthesis. We propose that a complex interplay of environmental factors, rather than climate change alone, is shaping shifts towards earlier phenological guilds in floodplain forests. This study highlights the importance of considering a comprehensive view of phenological guild dynamics and the impact of environmental factors on forest plant community structure in the face of global change.

Influence of Climatic Variables on the Stem Growth Rate in Trees of a Tropical Wet Forest

The growth of tropical wet forests has a significant relationship with the climate; aspects such as temperature and precipitation affect the species; however, few studies have characterized the stem growth rate of tropical tree species. This study’s objective was to characterize the effects of climatic variation on the interannual stem growth rate of eight species in tropical wet forest. Six trees per species were selected (n = 48 trees), and a dendrometer was installed to measure diametric growth bi-monthly between 2015 and 2018 (3 years), complemented with environmental measurements, to determine their growth equations from environmental variables and, finally, to define the relationship between the wood density and the stem growth rate. The results showed an average stem growth from 0.45 to 4.35 mm year−1, and 40 to 70% growth occurred in the months with the highest rainfall. Also, species with higher wood densities were found to have lower stem growth rates. Finally, the analysis of stem growth rate showed a significant relationship in all species between the variables of temperature and precipitation (R2 adj 0.88 to 0.96). Our results suggest that species with greater stem growth rates in wet tropical forests are more susceptible to climate changes, which may affect their dynamics in the face of potential drought scenarios and heat waves associated with climate change.

Global relevance of Argentinean rainfed crops in a climatic variability context: A water footprint assessment in Buenos Aires province

Argentina has a relevant international role as a producer of agricultural commodities. Buenos Aires is the province with the largest cultivated area of cereals and oilseeds of the country. Rainfed crops depend exclusively on green water, meaning a comparative advantage for Buenos Aires province. The green virtual water content in the crops produced in Buenos Aires has implications for water allocation at international level. A great amount of countries depends on the Argentinean rainfed agriculture. Therefore, it is important to understand the effects of climate variations on Argentinean crop production at local level and the role of rainfed crops in regional and international trade. We analysed the temporal and territorial variations of crops green water demand in a climatic variability context and their influence on the water footprint. The green water footprint of the main crops of Buenos Aires was assessed, including soybeans, maize, sunflower, wheat and barley, in different climatic conditions: for the period 2008–2018, which include a dry year, a humid year and an ordinary year. A dataset about the green water footprint at municipality level was provided, and the results were presented on maps for each crop and for the different climatic conditions. The relevance of green water of main crops in the world water-dependent supply chains was shown. This comprehensive green water footprint assessment provides a useful database for researchers, companies and policy makers in Argentina and beyond.

Effects of Climatic Variations and Changing Land Use/Land Cover on Flooding in Southern Nigeria

The prevalence of flooding in Nigeria in the past few years (with its devastating consequences) has become a source of concern for policymakers and researchers alike. Scholars have attributed the high frequency of flooding, particularly in the southern region of Nigeria, to several factors; climatic variation and land use/land cover changes are themes that fall under the domain of natural and anthropogenic causes of flooding, respectively. This study examined climatic variations and changing land use/land cover in southern Nigeria with the view of determining their synergistic effects on flooding. We adopted a mixed approach for data collection with the use of Geographic Information System (GIS), retrieval of primary data from meteorological stations in the region, and field surveys. Findings show a significant decrease in rural land uses like arable lands, wetlands, and undisturbed forests; while there was a corresponding increase in urban/peri-urban land uses like settlements and tree-crop plantations over the period from 1999 to 2019. The land use/land cover changes have manifested in the destabilization of the microclimate, distortion of the carbon circle, loss of biodiversity, reduction of ecosystem services of the natural areas, and flooding. The decadal rainfall trends over the past three decades show consistent extremities with mean rainfall duration decreasing while the mean intensity increases; aggravating soil erosion, urban runoff challenges, and flooding. Climatic variations (mainly extreme rainfall patterns) synergize with inefficient land use management to exacerbate flooding in southern Nigeria. While policymakers in this region may not have the standalone capacity to significantly control climate change and the consequential variations in the local microclimate, they can re engineer land use policies to eliminate or substantially degrade anthropogenic factors that exacerbate flooding.

Global malaria predictors at a localized scale

Malaria is a life-threatening disease caused by Plasmodium parasites transmitted by Anopheles mosquitoes. In 2022, more than 249 million cases of malaria were reported worldwide, with an estimated 608,000 deaths. While malaria incidence has decreased globally in recent decades, some public health gains have plateaued, and many endemic hotspots still face high transmission rates. Understanding local drivers of malaria transmission is crucial but challenging due to the complex interactions between climate, entomological and human variables, and land use. This study focuses on highly climatically suitable and endemic areas in Côte d’Ivoire to assess the explanatory power of coarse climatic predictors of malaria transmission at a fine scale. Using data from 40 villages participating in a randomized controlled trial of a household malaria intervention, the study examines the effects of climate variation over time on malaria transmission. Through panel regressions and statistical modeling, the study investigates which variable (temperature, precipitation, or entomological inoculation rate) and its form (linear or unimodal) best explains seasonal malaria transmission and the factors predicting spatial variation in transmission. The results highlight the importance of temperature and rainfall, with quadratic temperature and all precipitation models performing well, but the causal influence of each driver remains unclear due to their strong correlation. Further, an independent, mechanistic temperature-dependent R0 model based on laboratory data, which predicts that malaria transmission peaks at 25°C and declines at lower and higher temperatures, aligns well with observed malaria incidence rates, emphasizing the significance and predictability of temperature suitability across scales. By contrast, entomological variables, such as entomological inoculation rate, were not strong predictors of human incidence in this context. Finally, the study explores the predictors of spatial variation in malaria, considering land use, intervention, and entomological variables. The findings contribute to a better understanding of malaria transmission dynamics at local scales, aiding in the development of effective control strategies in endemic regions.

Remote sensing assessment of anthropogenic and climate variation effects on river channel morphology and vegetation: Impact of dry periods on a European piedmont river

AbstractRivers are subject to increasing human pressure, resulting in a loss of their natural characteristics, further enhanced by climate change. The present study focuses on a piedmont reach of the Italian Po River and combines Landsat satellite information with hydrological records to investigate changes in sandbars exposure and riparian vegetation coverage, considering the summer period of 1984–2022. Satellite data were handled via Google Earth Engine, looking at common indexes such as the Modified Normalized Difference Water Index, which was used to identify temporal variations in wetted channel area, and the Normalized Difference Vegetation Index, considered as a proxy of vegetation coverage variations. Changes in the river hydrology were analysed by looking at the annual minimum water levels, the discharge duration curve, the stage–discharge relationship and the yearly annual water volume. Results suggest that a process of oversimplification is affecting this reach of the Po River, showing how climate change can affect piedmont European watercourses. Indeed, after an initial period where bars tended to be barer and somehow stable over time, in the most recent decade a different trend appeared, with vegetation able to colonize the exposed sandbars more. Using the Po River as an exemplary case study, this work suggests that prolonged dry periods, which are more common in recent decades, might impact large and medium rivers located in temperate climates, favouring the development of vegetation on exposed sandbars, eventually resulting in a less dynamic active channel.

The heterogeneous impacts of climate finance on environmental sustainability and social welfare in developing countries

PurposeDue to their limited capacity for adaptation and dependence on natural resources for economic growth, developing countries (DCs) tend to be more prone to climate change. It is argued that climate finance (CF) is a significant financial innovation to mitigate the negative effects of climate variation. However, the heterogeneous impacts of CF on environmental sustainability (ES) and social welfare (SW) have been masked. Thus, this study aims to investigate the heterogeneous effects of CF on ES and SW in 80 CF receipt DCs from 2002 to 2018. This study also aims to investigate the effects of CF on ES and SW based on population size, income heterogeneity and the type of CF.Design/methodology/approachThe method of moments quantile regression (MMQR) with fixed effects is utilized. Alternatively, the fully modified least square (FMOLS) and dynamic least square (DOLS) estimators are used for the robustness test.FindingsThe findings revealed that DCs with the lowest and middle quantiles of EF, carbon dioxide (CO2) emissions and human development exhibit large beneficial impacts of CF on ES and SW. In contrast, the positive effects of CF on ES breakdown for countries with the largest distributions of EF and CO2 emissions. Besides, the impacts of CF on ES and SW depend on income heterogeneity, population size and the type of CF.Practical implicationsThis study calls for a framework to integrate CF into all economic development decisions to strengthen climate-resilient SW and ES in DCs.Originality/valueTo the best of the authors’ knowledge, this is the first study to investigate the effects of CF on ES and SW in a wide range of DCs. Thus, it complements existing related literature focusing on the effects of CF on ES and SW.

Perception of Adaptation Strategies to Climate Variability in Machakos County, Kenya

The study was designed to assess climate variability trends on rainfall and temperature data between 1990 and 2020, analyse community perception to climate variability, evaluate adaptation strategies and their effectiveness and examined the challenges of adaptation to climate variability. Farmers were randomly selected and questionnaires administered, while focused group discussions were conducted to obtain farmer’s perceptions of climate variability. Rainfall and temperature data was statistically analysed using Mann Kendall test and Sen’s slope estimator (p<0.05. The study found out there was a significant variation in the amount of annual rainfall received of (p< 0.004) (S= -53) which showed a decreasing trend, while temperature showed a warming trend of (p>0.099) (S=29). Also, farmers perceived that climate variability events were real with (71.1%) and (68.0%) noticing a change in rainfall and temperature respectively over the same period. The study established that community perceptions on rainfall and temperature trends agreed with meteorological data on observed climatic trends. Planting of drought resistant crops was most popular with (89.8%) (n=255) agreeing, while (79.2%) said it was the most effective strategy. The study found that although some farmers have adopted some adaptation strategies, they were constrained with (82.4%) agreeing that age was a great challenge to adaptation and had a moderate negative correlation with adaptation of (0.097) with labour and (25.5%) saying it was not a challenge. The study recommends farmers use the study findings on rainfall and temperature trends and data recordings on local agricultural performances to enhance their ability to adapt. To researchers and academic community the study recommends the intensification of research on ecosystem-based adaptation and the use of the results in mainstreaming policy making, planning and implementation of climate related decisions. The results reveal important knowledge that if effectively applied will inform the county government in climate management decisions and reduce farmer’s vulnerability.

Synergistic evolution and attribution analysis of water-sediment in the middle and lower reaches of the Yangtze River

Study area: The Yangtze RiverStudy focus: Climatic variation and anthropogenic factors have a far-reaching impact on the evolution of runoff and sediment in the middle and lower Yangtze River. We introduced IHA-RVA and Copula functions, and used Budyko and sediment decomposition method. Under the effect of climatic variation and anthropogenic factors, the co-evaluation system and attribution analysis of runoff and sediment change are established. This study clarified the synergistic evolution law of water-sediment.New hydrological insights for the area: We found that the interannual variation trends of sediment transport at various stations in the middle and lower reaches of the Yangtze River during the period from 1954 to 2019 were more pronounced compared to the variations in runoff. Moreover, the degree of changes in water-sediment consistency varied among these stations, with water-sediment consistency gradually recovering with an increase in distance from the upstream cascade reservoirs. Human factors contributed 52.68–74.16% to the changes in runoff and 89.40–94.15% to the changes in sediment transport. Variation of water-sediment and its consistency in the middle and lower reaches of the Yangtze River are mainly related to human factors. The research results can provide some assistance to decision-makers in formulating regional water-sediment regulation planning frameworks.

Mathematical analysis of a time-delayed model for cocoa yield

Abstract Cocoa is an important crop that is predominantly grown in the western part of Africa. However, there have been fluctuations and declining trends in production and several factors have been identified to be responsible for this. A significant factor is the effect of climate variation, which could result in a low farm-level yield. Therefore, to understand the contribution of climate variability on the farm-level yield, we construct and analyse a time-delayed model to capture the effect of rainfall on cocoa production. This work uses a system of differential equations to model the crop transition from the flowering stage to pod formation, pod ripening and then to harvesting. We introduce a periodic forcing function into the model of flowering to account for the impact of seasonal rainfall variations. This leads to a novel nonlinear parametrically forced ODE for the flowering with periodically varying coefficients, which is coupled to a time-delayed model for the ripened pod formation and then harvesting. We perform an analysis of all parts of the system proving that it has a periodic solution when (parametrically) forced periodically, and we then conduct an asymptotic analysis on this periodic solution to show how its rich behaviour depends on the parameters of the climatic forcing in the model.

Effect of Climatic Variations in the Floral Phenology of Berberis microphylla and Its Pollinator Insects

Effect of Climatic Variations in the Floral Phenology of Berberis microphylla and Its Pollinator Insects

Effects of freezing temperatures on early life stages of native trees of different elevational origin: implications for tree recruitment in seasonally dry mountain forests.

In mountain forests, tree regeneration is limited by increasingly frequent frosts with increasing elevation. We investigated the effects of exposure to freezing temperature on early life stages of two native trees of different elevational origin in a seasonally dry mountain forest. We hypothesized that the negative effects of freezing exposure on performance of early life stages increases as freezing temperature decreases, and that frost resistance increases in plants of high elevational origin. We collected seeds of two tree species (Kageneckia lanceolata and Lithraea molleoides) from populations located at different elevations and grew seedlings and saplings in a greenhouse. Dry seeds, imbibed seeds and 1-month-old seedlings were exposed to seven temperature treatments ranging from 4 °C to -20 °C, while 12-month-old saplings were exposed to four temperature treatments from -8 °C to -20 °C. After freezing exposure in a climate chamber, we monitored seed germination and seedling and sapling survival. Germination of K. lanceolata decreased with decreasing temperature only for imbibed seeds from mid- and high elevations, whereas germination of L. molleoides slightly increased with decreasing temperature only for imbibed seeds from high elevations. For both species, seedling survival decreased with decreasing temperature. For K. lanceolata, the negative effects of freezing temperatures were weaker as elevational origin of seeds increased, whereas L. molleoides showed the opposite pattern. For both species, saplings only survived at the mildest applied freezing temperature (-8 °C). We conclude that effects of climatic variation associated with elevation depend on the study species and life stage. The observed patterns could be caused by maternal effects, which are absent at the sapling stage. Moreover, temperatures below -8 °C can limit recruitment since partial mortality of seedlings and saplings occurred at such values.

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia.

Characterization of Meteorological Drought Using Standardized Precipitation Index and Standardized Precipitation Evapotranspiration Index Methods in North Sumatera

Climate variability in Indonesia is influenced by several global factors including El Niño Southern Oscillation and Indian Ocean Dipole, one consequence of climate variability is drought. The drought index is used to identify and describe the level of drought in an area, the methods used in this study are the Standardized Precipitation Index and the Standardized Precipitation Evapotranspiration Index which are calculated based on climate data with a span of 24 years as many as 67 rain observation posts in North Sumatra using R Studio software. The purpose of this study is to determine the factors of global climate phenomena that affect drought in North Sumatra and its impact on rice crop productivity and analyze drought characteristics spatially and temporarily. The resulting index values are then analyzed using correlation methods to see their relationship with ENSO and IOD. The results showed that the incidence of the ENSO phenomenon had a very strong relationship with meteorological drought in North Sumatra with a correlation value range of -0.85 to -0.97, and as many as 62.5% of 32 districts experienced a decrease in rice crop productivity during El Niño with strong intensity in 2015.

Impacts of hydrometeorological factors on discharge simulation in the North West Himalayas: a SUFI-2 algorithm-driven investigation using the SWAT model.

The Soil and Water Assessment Tool (SWAT) is a computational hydrological model extensively utilised for developing sustainable strategies and viable approaches for prudent management of water resources. The central emphasis of this study is on the utilisation of SWAT model along with SWAT-CUP (SWAT calibration toolbox) to simulate streamflow in the upper Jhelum basin, the North West Himalayas, for a period of 20years from 2000 to 2019. The global sensitivity analysis algorithm, Sequential Uncertainty Fitting 2 (SUFI-2) of SWAT-CUP, is used for sensitivity and uncertainty analysis. The optimised parameter set estimated by SUFI-2 constitutes 11 parameters that are found to be sensitive with soil conservation service (SCS) curve number (CN) being the most influential parameter followed by snowmelt base temperature. Autocorrelation analysis using the autocorrelation function was conducted on the temperature and precipitation time series data, followed by a pre-whitening procedure to remove any autocorrelation effects. Subsequently, the modified Mann-Kendall (MMK) test was applied to examine trends in the annual temperature and precipitation data. The results indicated statistically significant positive trends in both datasets on an annual scale. The results for the calibration period (2003-2014) for monthly simulation displayed good model performance at three gauging stations, Rambiara, Sangam and Ram Munshi Bagh with R2 values of 0.83, 0.847, 0.829, P factor values of 0.73, 0.76, 0.75 and R factor values of 0.61, 0.58, 0.63, respectively. The validation results for monthly simulation for the 2015-2019 period showed good model agreement with R2 values of 0.817, 0.853, and 0.836, P factor values of 0.76, 0.8, and 0.75 and R factor values of 0.62, 0.53, and 0.65, respectively. The study concludes that the SWAT hydrological model can perform satisfactorily in high mountainous catchments and can be employed to analyse the impact of land use-land cover changes and the effect of climate variation on streamflow dynamics.

Mechanistic modeling of climate effects on redistribution and population growth in a community of fish species.

Understanding community responses to climate is critical for anticipating the future impacts of global change. However, despite increased research efforts in this field, models that explicitly include important biological mechanisms are lacking. Quantifying the potential impacts of climate change on species is complicated by the fact that the effects of climate variation may manifest at several points in the biological process. To this end, we extend a dynamic mechanistic model that combines population dynamics, such as species interactions, with species redistribution by allowing climate to affect both processes. We examine their relative contributions in an application to the changing biomass of a community of eight species in the Gulf of Maine using over 30 years of fisheries data from the Northeast Fishery Science Center. Our model suggests that the mechanisms driving biomass trends vary across space, time, and species. Phase space plots demonstrate that failing to account for the dynamic nature of the environmental and biologic system can yield theoretical estimates of population abundances that are not observed in empirical data. The stock assessments used by fisheries managers to set fishing targets and allocate quotas often ignore environmental effects. At the same time, research examining the effects of climate change on fish has largely focused on redistribution. Frameworks that combine multiple biological reactions to climate change are particularly necessary for marine researchers. This work is just one approach to modeling the complexity of natural systems and highlights the need to incorporate multiple and possibly interacting biological processes in future models.

Untangling the effects of climate variation and human interference on grassland dynamics in North China

AbstractClimatic and anthropogenic disturbances play pivotal roles in shaping the dynamics of grassland. Quantifying their impacts on grassland variation is essential to ensure sustainable grassland management. In this study, we employed the Thornthwaite Memorial and Carnegie–Ames–Stanford‐approach (CASA) models to investigate the spatiotemporal effects of these two variables on grassland variation in northern China from 2000 to 2016, using the net primary productivity (NPP) as a measure. Our findings reveal that approximately 25.92% of the grassland in northern China experienced degradation, while restored grasslands occupied 45% of the total grassland area. The average grassland actual NPP (ANPP) and human‐induced NPP decreased at rates of −0.60 and −5.62 gC m−2 a−1, respectively. Conversely, potential NPP exhibited an upward trend with an average increase of 2.27 gC m−2 a−1. Furthermore, grassland ANPP showed a projected increase in most parts of northern China. Climate change emerged as the primary driver for grassland restoration in Xinjiang, Qinghai, and Inner Mongolia, leading to an increase of 21582.79 Gg C in grassland NPP. In contrast, human activities were the dominant catalysts for grassland degradation, resulting in a reduction of 51932.3 Gg C in grassland NPP. Human‐induced grassland degradation was ubiquitous in northwest and northeast China. With the exception of slope grassland, climate change primarily influenced the restoration of most grassland types, while human activities were the primary cause of degradation. Our analysis indicated a strong correlation between temperature and grassland degradation, while precipitation played a pivotal role in grassland restoration in northern China. Human interference demonstrated both positive and negative impacts on grassland changes. In conclusion, the increase in precipitation and the implementation of ecological restoration plans have effectively promoted the restoration of grasslands in northern China.

Combining Tree-Ring Width and Density to Separate the Effects of Climate Variation and Insect Defoliation

Though frequently used in dendroclimatology, European larch (Larix decidua Mill.) is regularly defoliated by mass outbreaks of the larch budmoth (Zeiraphera griseana Hb., LBM). The near-cyclic growth depressions are unrelated to but possibly coincide with cold summers, which challenges signal detection on interannual timescales. LBM defoliation events cause sharp maximum latewood density declines and irregular earlywood/latewood ratios in the outbreak year, followed by one or two anomalously narrow rings. Here, we present a process-based method integrating these diverse response patterns to identify and distinguish LBM-related signals from climate-induced deviations. Application to larch sites along elevational transects in the Swiss Alps reveals the algorithm to perform better than existing extreme event detection methods, though our approach enables additional differentiation between insect- and climate-induced signatures. The new process-based multi-parameter algorithm is a suitable tool to identify different causes of growth disturbances and will therefore help to improve both tree-ring-based climate and insect defoliation reconstructions.

Financial risk under the shock of global warming: Evidence from China

AbstractThe economic and financial risks of global warming have become a hot issue of academic interest. This article analyzes global warming, financial risk, and the economic statistics of 30 provinces in China from 2010 to 2020 as a sample to assess the influence of the severity of global warming on financial risk. Global warming is found to affect financial risk and to have a substantial favorable influence on the amount of financial risk. Global warming also has significant effects on households, enterprises, financial institutions, and governments. There is heterogeneity in the effects of climate variation on financial risk. Global warming will cause a greater accumulation of financial risk in economically developed regions. Additionally, it will lead to financial risks by causing a decline in the incomes of residents, a decline in the profits of enterprises, growth in the number of loans that financial institutions consider to be nonperforming, and a widening of the gap between government revenue and expenditures. All of these effects will have an adverse domino effect on the economy. To reduce the financial risks caused by global warming, countermeasures are being offered to ensure social cohesion, conduct risk stress testing, create risk mitigation instruments, and encourage environmentally responsible development. This paper discusses policies and provides policymakers with recommendations on how to cope with the systematic financial risks induced by climate variation.