Annual Temperature Research Articles

Developing a Method to Estimate Above-Ground Carbon Stock of Forest Tree Species Pinus densata Using Remote Sensing and Climatic Data

Forest above-ground carbon stock (AGCS) is one of the primary ecological evaluation indicators, so it is crucial to estimate the AGCS accurately. In this research, we added the climatic and topographic factors to the estimation process by a remote sensing approach to explore their impact and to achieve more precise estimations. We hope to develop a more accurate estimation method for AGCS based on remote sensing data and climate data. The random forest (RF) method has good robustness and wide applicability. Therefore, we modeled and predicted the AGCS by RF based on sixty field sample plots of Pinus densata pure forests in southwest China and the factors extracted from Landsat 8 OLI images (source I), Sentinel-2A images (source II), and combined Landsat 8 OLI and Sentinel-2A images (source III). We added the topographic and climatic factors to establish the AGCS estimation model and compared the results. The topographic factors contain elevation, slope, and aspect. Climatic factors contain mean annual temperature, annual precipitation, annual potential evapotranspiration, and monthly mean potential evapotranspiration. It was found that the R2 and RMSE of the model based on source III were better than the R2 and RMSE of the models based on source I and source II. Compared to the models based on source I and source II, the model based on source III improved R2 by up to 0.08, reduced RMSE by up to 2.88 t/ha, and improved P by up to 4.29%. Among the models without adding factors, the model based on source III worked the best, with an R2 of 0.87, an RMSE of 10.81 t/ha, an rRMSE of 23.19%, and a P of 79.71%. Among the models that added topographic factors, the model based on source III worked best after adding elevation, with an R2 of 0.89, an RMSE of 10.01 t/ha, an rRMSE of 21.47%, and a P of 82.17%. Among the models that added climatic factors, the model that added the annual precipitation factor had the best modeling result, with an R2 of 0.90, an RMSE of 9.53 t/ha, an rRMSE of 20.59%, and a P of 83.00%. The prediction result exhibited that the AGCS of the Pinus densata forest in 2021 was 9,737,487.52 t. The combination of Landsat 8 OLI and Sentinel-2A could improve the prediction accuracy of the AGCS. The addition of annual precipitation can effectively improve the accuracy of AGCS estimation. Higher resolution of climate data is needed to enhance the modeling in future work.

Prediction of the potentially suitable areas of Eucommia ulmoides Oliver in China under climate change based on optimized Biomod2 and MaxEnt models

Eucommia ulmoides Oliver is a medicinal plant of significant economic importance. Its cortex has been employed for centuries to alleviate various conditions such as lumbar pain, knee pain, and osteoporosis. Additionally, E. ulmoides possesses substantial industrial value. With the growing demand for this medicinal herb, ensuring its sustainable supply has become imperative. Climate change has caused habitat restrictions or migration of medicinal plants. Therefore, predicting the impact of climate change on the distribution of E. ulmoides is crucial for its conservation and sustainable use. This study evaluated the potential distribution of E. ulmoides across China under various climate change scenarios since the last interglacial period by modeling suitable areas based on 257 distribution records and 19 major environmental factors related to E. ulmoides. The model selection process initially identified the MaxEnt model as the most suitable. The optimized MaxEnt model, with RM = 2.0 and FC = LQHPT settings, generated the most precise predictions. Results indicate that the minimum temperature of the coldest month, annual mean temperature, and annual precipitation significantly affect the distribution of E. ulmoides. Under current environmental conditions, highly suitable areas for E. ulmoides are found in Southwest and Southeast China, with a total suitable habitat area of 23.12 × 104 km2. However, the range of suitable habitat has shifted due to global warming’s negative impact. Under different climate scenarios, suitable areas for E. ulmoides have either increased or decreased, with expansions primarily in high-latitude regions. Future climate scenarios predict shifts in the centroid of suitable E. ulmoides habitat towards Yichang City in Hubei Province. The findings of this study support the development, artificial cultivation, and conservation of E. ulmoides resources.

Impact of livestock activity on near-surface ground temperatures in central Mongolian grasslands

Abstract. Grazing by livestock can alter the surface conditions at grassland sites, impacting the transfer of energy between the atmosphere and ground and consequentially ground temperatures. In this study, we investigate surface cover in summer and winter and measure ground surface temperatures over 14 months at sites in central Mongolia that feature different grazing intensities (intensely and ungrazed) and topographic aspects (north- and south-facing). Overall, intense grazing leads to a substantially reduced vegetation cover, altered snow conditions, and lack of surface litter accumulation. Comparing intensely grazed and ungrazed plots shows large seasonal differences in ground surface temperatures, with grazed plots being up to +5.1 °C warmer in summer and −5.4 °C colder in winter at a south-facing site. We also find that the effect of grazing intensity depends on topographic aspect, with smaller seasonal differences of +1.4 °C and −2.5 °C found between grazed and ungrazed plots at a north-facing site. This relates to the lower available solar radiation at north-facing sites, which reduces the differences in vegetation cover between open and fenced plots. For both aspects, the seasonal differences largely offset each other, with both a small net cooling and warming depending on effects in spring and autumn. Our study suggests that livestock management could be used to modify the annual ground temperature dynamics, possibly even influencing local permafrost dynamics.

Selecting Suitable Sites for Wind Energy Harvesting in Iraq using GIS Techniques

Wind energy harnesses the kinetic force of the wind through turbines to produce electricity. As a critical renewable energy source, it presents a sustainable alternative to fossil fuels. The availability of wind energy is geographically contingent. This paper aims to pinpoint optimal sites for wind energy development in Iraq and to secure future energy needs from renewable sources to achieve this, a multi-criteria analysis utilizing Geographic Information Systems (GIS) was employed to determine the prime locations for wind energy extraction. Vital climatic data incorporated into this analysis included a RASTER file of the study area's annual wind speed, temperature, precipitation, soil moisture, and NDVI (Normalized Difference Vegetation Index) roads, urban centers, terrain gradients, and land utilization patterns were instrumental in constructing a GIS-based model. This model harnessed the weighted overlay tool within ArcGIS 10.7.1's Spatial Analysis Tools to classify and integrate various raster datasets. Findings reveal that the most favorable locations for wind energy exploitation are in Iraq's southeastern sectors. These zones are not only marked by vigorous winds averaging speeds over 6.2 meters per second but also benefit from their proximity to power grids, accessible roads, and gentle slopes, making them prime candidates for wind farm installation. The research also notes that regions with a high suitability index for wind energy development constitute 5.3% of the total examined area. This is a robust indicator of Iraq's capacity for wind energy utilization. Meanwhile, 79.7% of the territory received a moderate suitability rating, 9.5% was categorized as poorly suitable, and 5.4% was considered unsuitable for wind energy projects. These insights underscore the significant potential for harvesting wind energy in Iraq and guide strategic planning for its implementation.

Revealing How Human Activity and Native Plants Outshine Climate in Shaping New Invasive Alien Plant Elevational Patterns in Nature Reserves

ABSTRACTAimWe aim to investigate whether invasive alien plants introduced at different times exhibit variations in elevational distribution patterns and to explore the correlations of these patterns with climate, native plants and human activity.LocationGuangxi, China.MethodsWe recorded plant richness and cover across elevational gradients at 25–34 sites within each reserve, utilising 84–134 roadside plots per site. Using generalised linear mixed model (GLMM), we assessed the impacts of climate, native plants and human activity on the distributions of all, old and new invasive alien plants across the region and within the nature reserves.ResultsAt regional scales, the cover of all, new and old invasive alien plants decreased with increasing elevation, while only the richness of old invasive alien plants exhibited a similar pattern. Contrasting patterns were observed in Dayao Mountain, where the cover of old invasive alien plants decreased while the cover of new invasive alien plants increased. The richness patterns of all and new invasive alien plants were opposite between Dayao Mountain and Yachang Orchid. Moreover, native plant richness was negatively correlated with the richness of invasive alien plants, while interference intensity positively affected new invasive alien plants at both regional and reserve scales. At the regional scale, native plant richness accounted for 78.27%, 91.94% and 60.9% of all, old and new invasive alien plants respectively. Interference intensity accounted for 33.85% of the variation in new invasive alien plants. Annual mean temperature positively influenced the cover of all and old invasive alien plants at both regional and reserve scales, explaining 36.91% and 74.28% of their regional variation. Additionally, interference intensity and distance to human settlements positively impacted the cover of new invasive alien plants, contributing to 50.95% and 31.92% of their variation at regional scales.Main ConclusionThe distinct distribution patterns of old and new invasive alien plants highlight the significance of residence time in understanding their dynamics. Climate factors constrain the cover distribution of all and old invasive alien plants, whereas interference intensity and distance to settlements determine the distribution of new invasive alien plants. Notably, native plants play a vital role in preventing the establishment and spread of invasive alien plants within nature reserves, and their effectiveness increases with longer residence times. Our findings highlight the critical importance of minimising human interference and conserving native species for the effective management of invasive alien plants in nature reserves.

Characterizing Long-term Astroclimate Parameters at the Muztagh-Ata Site in the Pamir Plateau with ERA5 and MERRA-2 Data

Abstract The Muztagh-Ata site, an excellent high-altitude ground-based astronomical observing site was discovered and monitored in the eastern part of the Pamir Plateau in the southwestern Xinjiang Uygur Autonomous Region of China. This site has been systematically monitored using various observational parameters since the spring of 2017. Yet, the site lacks long-term monitoring and statistical characterization of key variables such as: precipitable water vapour (PWV) and air temperature. These factors directly influence whether a site is suitable for hosting large ground-based telescopes across optical, infrared, submillimeter, and millimeter wavelengths in later stages. In this study, we utilized atmospheric reanalysis datasets from the Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) and ERA5, the fifth edition of the European Centre for Medium-Range Weather Forecasts (ECMWF). These datasets were combined with local observations from the weather station at the Muztagh-Ata site. Following the validation of ground-based and satellite data, we conducted a comparative analysis of PWV and temperature trends at the Muztagh-Ata site over a period of 24 years. The weighted annual mean nighttime temperature and PWV increase at rates of 0.18 ∼ 0.38 ○C decade−1 and 0.02 ∼ 0.15 mm decade−1, respectively. The nighttime PWV slightly decrease during the winter with rates of −0.01 ∼ −0.03 mm decade−1. This findings reveal that the PWV and temperature variation patterns at the Muztagh-Ata site are consistently stable, particularly in the results derived from the ERA5 dataset. The comprehensive conditions at this site are highly suitable and advantageous for hosting large optical, infrared, submillimeter, and millimeter wavelengths telescope installations.

Classification Importance of Seed Morphology and Insights on Large-Scale Climate-Driven Strophiole Size Changes in the Iberian Endemic Chasmophytic Genus Petrocoptis (Caryophyllaceae)

Recruitment poses significant challenges for narrow endemic plant species inhabiting extreme environments like vertical cliffs. Investigating seed traits in these plants is crucial for understanding the adaptive properties of chasmophytes. Focusing on the Iberian endemic genus Petrocoptis A. Braun ex Endl., a strophiole-bearing Caryophyllaceae, this study explored the relationships between seed traits and climatic variables, aiming to shed light on the strophiole’s biological role and assess its classificatory power. We analysed 2773 seeds (557 individuals) from 84 populations spanning the genus’ entire distribution range. Employing cluster and machine learning algorithms, we delineated well-defined morphogroups based on seed traits and evaluated their recognizability. Linear mixed-effects models were utilized to investigate the relationship between climate predictors and strophiole area, seed area and the ratio between both. The combination of seed morphometric traits allows the division of the genus into three well-defined morphogroups. The subsequent validation of the algorithm allowed 87% of the seeds to be correctly classified. Part of the intra- and interpopulation variability found in strophiole raw and relative size could be explained by average annual rainfall and average annual maximum temperature. Strophiole size in Petrocoptis could have been potentially driven by adaptation to local climates through the investment of more resources in the production of bigger strophioles to increase the hydration ability of the seed in dry and warm climates. This reinforces the idea of the strophiole being involved in seed water uptake and germination regulation in Petrocoptis. Similar relationships have not been previously reported for strophioles or other analogous structures in Angiosperms.

Climate change and lethal violence: a global analysis

Purpose The study aims to uncover the relationship between rising temperatures, increased greenhouse gas emissions and the prevalence of lethal violence, encompassing suicides and homicides. It also sought to identify how climate change affects different economic strata in countries, notably in high and middle-income nations, and across Asia and Africa. Design/methodology/approach This study rigorously explored the link between global climate change and lethal violence across 201 countries from 1970 to 2020. Climate change was measured using annual surface temperature fluctuations and greenhouse gas emissions, while lethal violence was estimated using data on suicides and homicides. Findings The analysis revealed significant positive associations between escalating temperatures, heightened greenhouse gas emissions and lethal violence. These connections were evident across different economic levels and geographic regions in Asia and Africa. Originality/value This study emphasizes the urgent need for comprehensive interventions to combat human-induced climate change and mitigate its extensive negative impacts on society, particularly its association with increased violent behavior.

Development of a global thermal detection index to prioritize primate research with thermal drones.

Thermal Infrared (TIR) drones are emerging as effective tools for wildlife ecology monitoring and are increasingly employed in primate surveys. However, systematic methods for assessing primate detectability are lacking. We present a comprehensive approach utilizing a novel Thermal Detection Index (TDI) to evaluate the potential of TIR drones for primate monitoring. We developed TDIs for 389 primate species, considering activity patterns, locomotion types, body mass, densities, habitat utilization, and sleeping behaviors during diurnal and nocturnal surveys. Through the integration of TDIs with primates' distribution and climatic variables (average annual temperature, precipitation, and wind speed), we established a Global TDI Suitability Score aimed at pinpointing species and regions most compatible with TIR drone-based monitoring. Atelidae, Cercopithecidae, and Indridae showed the highest TDI values, suggesting their suitability for TIR-drone surveys. We identified optimal regions in Africa, Asia and Latin America for primate monitoring with TIR drones, driven by favorable ecological conditions, habitat types, and high TDI species diversity. However, local ecological factors and regulatory frameworks also influence drone survey feasibility, necessitating careful consideration prior to implementation. Overall, our study provides a valuable framework for prioritizing primate species and regions for TIR drone-based monitoring, facilitating targeted conservation efforts and advancing primate monitoring research.

Effect of Global Warming on the Fish Population Parameters in the Upper Volga Reservoirs

As a result of global warming, the average annual water temperature has significantly increased in the Upper Volga reservoirs. Warming and the subsequent deterioration of the oxygen regime had a significant effect on most of the fish populations inhabiting temperate waters. This led to changes in the population structure of many fish species. Such phenomena as the disappearance or a sharp decline in the abundance of cold-water species (European smelt, vendace, burbot and pike) in the Rybinsk reservoir coincided with the period of warming. The disappearance of European smelt in the Rybinsk Reservoir and the favorable temperature regime contributed to the appearance and rapid increase in the abundance of the Caspian invader, the Black Sea sprat, which occupied the empty niche of the European smelt and became instead the dominant species in the pelagic zone of the Upper Volga reservoirs. Warming resulted in a decrease in the abundance and the growth rate of burbot and pike. Climate warming had an indirect effect on many species through oxygen deficiency or transformation of the forage base (ruff, zander, perch, roach), which also led to a decrease in abundance and the growth rate.

Climatic factors, but not geographic distance, promote genetic structure and differentiation of Cleistogenes squarrosa (Trin.) Keng populations

Climate can shape plant genetic diversity and genetic structure, and genetic diversity and genetic structure can reflect the adaptation of plants to climate change. We used rbcl and trnL-trnF sequences to analyze the genetic diversity and genetic structure of C. squarrosa under the influence of different environmental factors in Inner Mongolia grassland. The results showed that the genetic diversity of this species was low. (The trnL-trnF sequences have higher genetic diversity than rbcl sequences.) C. squarrosa had low genetic diversity compared to other prairie plants, but had a more pronounced genetic structure. The haplotype network diagram of the combined sequences could be divided into two categories, and the results of the NJ, MP, and ML trees also showed that the haplotypes were divided into two branches. The results of genetic structure analysis showed that that the populations located in the desert steppe fall into exactly one cluster, and the populations located in the typical steppe fall into exactly another cluster. The neutrality tests were all negative and the mismatch distribution also showed a single peak across the population, suggesting that C. squarrosa had undergone population expansion and was well adapted to the local environment. The results of the mantel test showed that climate had a greater influence on the genetic distance of C. squarrosa, with annual precipitation having a higher influence than mean annual temperature. This study provided basic genetic information on the genetic structure of C. squarrosa and contributes to the study of genetic adaptation mechanisms in grassland plants.

Impact of climate change on vegetation growth trends in a citrus farmland in the south-eastern Sicily

Abstract. The environmental repercussions of climate change triggered substantial alterations in existing ecosystem balances leading to a gradual reduction in biodiversity and the increasing degradation of soil and the built environment. This has a direct effect on agricultural production in particular, leading to increased crop water requirements, the spread of new pests and pathogens that are difficult to manage, and, thus, a general reduction in productivity. Through the analysis of multispectral data remotely sensed with latest generation of optical sensors (RGB, thermal, NIR and multi-spectral cameras), it is possible to recognize the health status and growth stages of crops. In fact, in relation to the amount of radiation reflected in the different bands it is possible to calculate spectral indices, or vegetation indices. The main vegetative indices are NDVI, SAVI, MSAVI2, GNDVI and NDRE, which are calculated by differentially combining the ultraviolet spectrum, the visible range, and the near and mid-infrared band.In this paper the outcomes of a multi-year monitoring of a citrus grove field near Rosolini (Syracuse), in south-eastern Sicily-Italy, are presented. This monitoring activity was conducted to highlight areas of productive greenery under stress, on which to act as a priority with specific agronomic interventions. In parallel with the direct monitoring phases of the citrus grove, the trend of average monthly and annual temperature and precipitation values over the past 24 years was also studied to more specifically contextualize the possible presence of significant variations in climatic trends and relate them to the results returned by the calculation of the indices.

Perception of smallholder farmers about climate change and its impacts on crop production across agroecological zones of the Gassera District, Southeastern Ethiopia.

Climate change and variability have threatened rainfed agriculture by affecting the livelihoods of rural communities in Ethiopia. The study area, Gassera District, is among the high-potential crop production areas of the Bale Zone and is severely impacted by recurrent droughts resulting from climate change. This study evaluated smallholder farmers' perceptions of significant climate change and its effects on food crop production across the agroecological zones of the Gassera District. A cross-sectional survey design was employed to collect data from 444 farm households via multistage random sampling techniques. Multiple linear regression (MLR) models were used for the data analysis. The results revealed that 98.5% of the interviewed farmers were aware of climate variability and that 51.6% understood its impact to a reasonable extent. However, over half of the farmers did not perceive climate change as the greatest threat to their livelihood. Most farmers experienced rain becoming more erratic, starting late, and ending early as medium climatic factors (60.4%, 68.1%, and 66.2%, respectively), affecting their crop production. The results revealed that rainfall had a negative and insignificant decreasing trend (2.92mm/year). The annual mean temperature exhibited a positive and statistically significant increasing trend (Ρ < 0.01). Crop production is positively and linearly correlated with the amount of annual rainfall at the Ρ ≤ 0.05 level of significance. The findings revealed that the greatest crop yield loss was associated with lowland agroecology. The MLR results revealed that farmer agroecology, age, sex, and chemical use had substantial impacts on crop yield loss. We urge farmers to understand the long-term effects of climate change on their livelihoods.

Multi-Omics Analysis Uncovers the Mechanism for Enhanced Organic Acid Accumulation in Peach (Prunus persica L.) Fruit from High-Altitude Areas

The early-ripening peach industry has undergone rapid development in the Panxi region of the Sichuan Basin in recent years. However, after the introduction of some new peach varieties to the high-altitude peach-producing areas in Panxi, the titratable acid content in peach fruit has significantly increased. This study compared the fruit quality indicators of early-ripening peach varieties cultivated in Xide County (a high-altitude peach-producing area) and Longquanyi District (a low-altitude peach-producing area) in Sichuan Province and analyzed the differences in organic acid metabolism by combining primary metabolomic and transcriptomic approaches. The results showed that the ‘Zhongtaohongyu’ fruit from the high-altitude peach-producing area had a much higher accumulation of malic acid and, accordingly, a significantly higher organic acid content than the other samples. The lower annual average temperature and stronger ultraviolet radiation in high-altitude peach-producing areas may lead to the increased expression of genes (PpNAD-ME1, PpNADP-ME3, and PpPEPC1) in the organic acid synthesis pathway and the decreased expression of genes (PpACO2, PpNAD-MDH2/3/4/5, and PpPEPCK2) in the organic acid degradation pathway in peach fruit, ultimately resulting in the accumulation of more organic acids. Among them, the downregulation of the key genes PpNAD-MDH3/4/5 involved in malic acid metabolism may be the main reason for the higher malic acid accumulation in peach fruit from high-altitude peach-producing areas. Overall, this study elucidates the mechanism by which environmental factors enhance the accumulation of organic acids in peach fruit from high-altitude peach-producing areas from a multi-omics perspective, as well as providing a theoretical basis for screening key genes involved in organic acid metabolism in peach fruit.

Influence of climate and landscape structure on soil erosion in China's Loess Plateau: Key factor identification and spatiotemporal variability.

Climate and landscape structure are widely recognized as the primary drivers of soil erosion; however, the spatiotemporal variability of their effects remains insufficiently understood, limiting our comprehension of the dynamic processes of soil erosion. To address this gap, this study analyzed soil erosion trends on the Loess Plateau from 2000 to 2018. extreme Gradient Boosting was used to identify key climatic and landscape structural factors, while a geographically and temporally weighted regression model was applied to assess the spatiotemporal variability of these influences. The results indicate a decreasing trend in soil erosion from 2000 to 2008, followed by a sharp increase from 2008 to 2018. Grassland edge density emerged as the most important factor, followed closely by grassland percentage and annual precipitation. Temporally, the positive effect of annual precipitation has been intensifying since 2010, contributing to increased erosion, while landscape structural factors progressively enhanced their hydrological regulatory roles, reflecting dynamic interactions with climate. Spatially, the direction of climatic influences remained generally stable, consistently promoting erosion, although by 2018, the effects of average annual temperature and annual sunshine duration reversed to suppress erosion in specific areas. In contrast, landscape structural influences exhibited greater spatial variability, often fluctuating or reversing depending on topography, human activity, and land use. This variability applied specifically and differentially to each metric of fragmentation and diversity, highlighting the critical importance of trade-offs in landscape management. The findings emphasize the complexity and dynamics of soil erosion in response to climate and landscape structure, suggesting implications for the development of spatially targeted soil erosion control strategies that accommodate the phases of temporal variation.

Species distribution modeling of North American beavers from the late Pliocene into the future

Abstract Beavers have occurred in North America since at least 7 Ma, but relatively little is known about their distribution across the continent. We modeled distributions of beavers in the late Pliocene (3.3 Ma), Pleistocene (130 ka and 21 ka), and recent Holocene (1970 to 2000) to understand their dispersal across North America, predict future distributions and predict their possible response to future climate and habitat changes. Occurrence data for Castor canadensis were derived from the Global Biodiversity Information Facility. Those data were used with both modern (1970 to 2000) and modeled future (EC-Earth-Veg 2081 to 2100) bioclimatic variables from WorldClim as well as past (Pliocene Marine Isotope Stage M2, Pleistocene Last Interglacial, and Pleistocene Last Glacial Maximum) bioclimatic variables from PaleoClim to model beaver distributions through time. Fossil locality points for Castor extracted from the New and Old Worlds Database of Fossil Mammals (NOW), NEOTOMA Paleoecology Database, and Paleobiology Database were overlain on past projection models to use as validation points. Models were run using MaxEnt with post-processing in ArcGIS. Accuracy for the 5 models ranged between 59.6% and 60.2%. Results for the present model (1970 to 2000) showed habitat suitability in areas beavers inhabit today. During the Pliocene MIS M2 cooling event (3.3 Ma) and Pleistocene Last Glacial Maximum (21 ka), habitat suitability shifted further south into Mexico and peninsular Florida and away from more periglacial northern regions. During the Last Interglacial period (130 ka) and modeled future (2081 to 2100) EC-Earth-Veg 2081 to 2100, habitat suitability was higher in coastal and central regions in North America and lower in southern regions compared to their present distribution. Distributions were most affected by precipitation seasonality, isothermality, and mean annual temperature. High variability in seasonal precipitation and temperatures is likely to influence surface water availability, vegetation type, and riparian vegetation composition, which consequently may reduce available food resources and habitat for beavers. Observed shifts during warmer periods may indicate areas in the late Miocene that facilitated dispersal into North America. Future models using other predicted climatic scenarios and shared socioeconomic pathways may provide better resolution of potential future shifts in beaver distribution with best- and worst-case climate scenarios, thereby permitting at-risk areas to be prioritized for conservation in the face of climate change.

A 903-year annual temperature reconstruction for the southeastern tibetan plateau from the tree ring widths of Juniperus saltuaria.

Precisely dated paleoclimatic records are essential for understanding natural and anthropogenic climate influences. Here, an annually resolved absolutely dated Juniperus saltuaria tree ring width chronology from the Haizi mountain, southeastern Tibetan Plateau (TP) was developed. The chronology shows the annual- to decadal-scale paleoclimatic variability of the southeastern TP over the past 903years (1115-2017 CE). The tree ring widths correlate significantly with mean annual temperature (Tmean). A linear regression model between ring width and Tmean, accounting for 57% of the variance in temperature from 1959 to 2017 CE, was used to reconstruct the past 903years of Tmean variation in the southeastern TP. The chronology aligns with other temperature records from the TP, Asia, and the Northern Hemisphere (NH), indicating a marked temperature increase since the late twentieth century, with 1998-2017 CE identified as the warmest period. The coldest thirty years occurred in 1115-1145 CE. Solar activity and the Atlantic Multidecadal Oscillation exert notable influences on temperature fluctuations in this region. Superposed epoch analysis indicates that volcanic eruptions had significantly impacted southeastern TP temperatures, causing dramatic cooling for 2-4years. Our study presents the longest width chronology developed by Juniperus saltuaria to date, offering a long-term perspective on recent climatic shifts across the southeastern TP. This work enhances understanding of historical climate variability, providing critical insights to refine projections of future climate variability.

Spatio-temporal trends in the frost regime reveal late frost exposure to white spruce (Picea glauca [Moench] Voss) persists in northeastern America

Abstract The characteristics of the frost regime (intensity, frequency, and timing) contribute to shaping tree species adaptations and distribution as well as ecosystem productivity and functions. However, climate change increases the variability in extreme events; therefore, the different characteristics of the frost regime may diverge under climate change. Using the BioSim 11 software, we simulated daily air temperature at 512 locations over northeastern North America between 1901–2021 to determine how the spatio-temporal trends in the frost regime varied over this complex landscape and if spatio-temporal trends in extreme climatic events such as frosts are stronger compared to changes in aggregated climate variables such as mean annual air temperature and growing degree-days. We also used an eco-physiological model to conduct a case study focussing on white spruce to determine if trees are currently more exposed to growing season frosts than they were in the past by modelling the timings of budburst using the thermal time model. Our results showed that, at 67% of locations (343 locations), the day of the year of the last frost in spring (minimum daily air temperature&lt;0 °C) occurred, on average, earlier by seven days during 2001–2021 compared to 1901–1920, whereas it occurred, on average, later by four days at 33% of locations (169 locations). The average temporal trends in frost occurrence were similar in magnitude to the average trends in aggregated climate variables; however, their variances were larger compared to the aggregated climate metrics, showing that the frost regime does not change uniformly throughout our study area. Our case study also revealed that white spruce remains exposed to late frosts of low and intermediate intensities (minimum daily air temperature &lt;0; &lt;−2 °C) compared to the past but exposure to high-intensity frosts (minimum daily air temperature &lt;−4 °C) is rare. Since extreme events such as late frosts diverge in their response to climate change compared to aggregated climate variables, the mean annual temperature is not sufficient to predict how climate change will impact ecosystems through frost regimes.

Has There Been a Recent Warming Slowdown over North China?

The warming slowdown observed between 1998 and 2012 has raised concerns in recent years. To examine the temporal and spatial variations in annual mean temperature (Tmp) as well as 12 extreme temperature indices (ETIs), and to assess the presence of a warming slowdown in North China (NC), we analyzed homogenized daily observational datasets from 79 meteorological stations spanning 1960 to 2020. Additionally, we investigated the influences of 78 atmospheric circulation indices (ACIs) on ETIs during the period of warming slowdown. To compare temperature changes, the study area was divided into three parts based on topographic conditions: Areas I, II, and III. The results revealed significant warming trends in Tmp and the 12 ETIs from 1960 to 2020. Comparing the time frames of 1960–1998, 2012–2020, and 1998–2012, both Tmp and the 12 ETIs displayed a cooling trend in the latter period, confirming the existence of a warming slowdown in NC. Notably, indices derived from daily maximum temperature exhibited higher cooling rates during 1998–2012, with winter contributing most significantly to the cooling trend among the four seasons. The most pronounced warming slowdown was observed in Area I, followed by Area III and Area II. Furthermore, our attribution analysis of ACIs concerning the temperature change indicated that the Asia Polar Vortex Area Index may have had the greatest influence on ETIs from 1960 to 2016. Moreover, the weakening of the Tibet Plateau Index Band and the Asian Latitudinal Circulation Index, and the strengthening of the Eurasian Latitudinal Circulation Index, were closely associated with ETIs during the warming slowdown period in NC. Through this research, we aim to deepen our understanding of climate change in NC and offer a valuable reference for the sustainable development of its natural ecology and social economy.

Formation of single-dominant-species patches of Dicranopteris dichotoma primarily influenced by understory light intensity

IntroductionThe Dicranopteris dichotoma fern community plays vital roles in nutrient sequestration, succession regulation, and ecological threshold control. However, the mechanisms underlying the formation of the D. dichotoma–dominant community remain unclear.MethodsThis study established four different community types to investigate the effects of environmental factors on the formation of a D. dichotoma–dominant community.ResultsWe found that climate was the primary factor affecting the formation of patches dominated by D. dichotoma at the regional scale. Specifically, higher annual mean temperature and annual mean precipitation were associated with larger single-dominant-species patches of D. dichotoma. Understory light intensity was the major factor affecting the formation of the D. dichotoma community at the community scale. Light intensity ranging from 200 to 500 µmol·m⁻²·s⁻¹ was most conducive to the development of a large D. dichotoma community. Additionally, understory light intensity enhanced the importance value of D. dichotoma in the herb community by decreasing its biomass proportion of support modules and increasing its biomass proportion of photosynthetic and reproductive modules. Soil properties and D. dichotoma characteristics showed interactions with each other. Acidic red-yellow soil was most suitable for the formation of single-dominant-species patches of D. dichotoma, and the growth of D. dichotoma further decreased the soil pH. Soil total phosphorus content was identified as a limiting factor for formation of the D. dichotoma community.DiscussionIn summary, the formation of single-dominant-species patches of D. dichotoma is mainly influenced by a combination of climate, community, and soil.