Changes In Spatial Patterns Research Articles

Global burden of self-harm and interpersonal violence and influencing factors study 1990–2019: analysis of the global burden of disease study

IntroductionWidespread concern exists in today’s world regarding self-harm and interpersonal violence. This study to analyze the changes in temporal trends and spatial patterns of risk factors and burdens of self-harm and interpersonal violence using the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2019.MethodsTemporal trends in self-harm and interpersonal violence were initially summarized using the estimated annual percentage change (EAPC). Data were compiled and visualized to delineate changes in disease burden and factors influencing self-harm and interpersonal violence from 1990 to 2019, stratified by gender, age and GBD region.ResultsIn 2019, the DALY rates of self-harm were 424.7(95% UI 383.25, 466.93). Over the period from 1999 to 2019, self-harm exhibited an overall decreasing trend, with the EAPC of -1.5351 (95% CI -1.6194, -1.4507), -2.0205 (95% CI -2.166, -1.8740) and -2.0605 (95% CI -2.2089, -1.9119), respectively. In contrast, the incidence rate of interpersonal violence was significantly higher than self-harm, with a rate of 413.44 (95% UI 329.88, 502.37) per 100,000 population. Mortality and DALYs of interpersonal violence were lower than those of self-harm, at 5.22 (95% UI 4.87, 5.63) and 342.43 (95% UI 316.61, 371.55). Disease burden of self-harm and interpersonal violence varied by gender, age groups and region. Specific risk factors showed that alcohol use, high temperature and drug use were the main risk factors for self-harm, while alcohol use, intimate partner violence and high temperature were associated with interpersonal violence. Low temperature was a common protective factor for both self-harm and interpersonal violence. The burden of self-harm and interpersonal violence was attributed to different factors influences in different SDI regions.ConclusionsThe study explored temporal trends and spatial distribution of the global disease burden of self-harm and interpersonal violence, emphasizing the significant impact of factors such as alcohol use, temperature, and drug use on disease burden. Further research and policy actions are needed to interpret recent changes of disease burden of self-harm and interpersonal violence, and dedicated efforts should be implemented to devise evidence-based interventions and policies to curtail risk factors and protect high-risk groups.

Spatiotemporal Land Use/Land Cover Changes and Impact on Urban Thermal Environments: Analyzing Cool Island Intensity Variations

This study pioneers the comprehensive evaluation of the spatiotemporal evolution of land use/land cover (LULC) in Hangzhou city, introducing the novel water body shape index (WBSI) to analyze its seasonal impacts on the urban thermal environment and urban cool island (UCI) effects, uncovering distinct patterns of thermal regulation. It particularly investigates how distance gradients and the water body shape index (WBSI) influence land surface temperature (LST) in the urban core. The region’s climate, featuring hot summers and cold winters, highlights significant seasonal LST variations. Addressing a gap in existing UCI research, the analysis extends beyond the typical large-scale planning focus to include small-scale, high-resolution aspects. Employing remote sensing and geographic information system (GIS) analysis techniques, this study analyzes the seasonal dynamics in Hangzhou’s central urban area. High-resolution LST data, obtained through single-channel inversion and resolution enhancement algorithms, are crucial to this analysis. This study employs the maximum likelihood classification method to analyze land use and land cover changes from 1990 to 2020. This analysis reveals potential drivers of urban thermal environment changes, such as the expansion of residential and commercial areas and the reduction in green spaces. Different regions in LST data are delineated to assess the cool island effect, and the complexity of water body boundaries is quantified using the water body shape index. Spatial and temporal patterns of LST changes are investigated using multivariate regression and time-series analysis models. We identified significant changes in LULC over the past 30 years in Hangzhou, closely correlating with a continuous rise in LST. This observation underscores a clear finding: the strategic importance of blue–green infrastructure in mitigating urban heat, a novel insight that extends the current understanding of urban thermal dynamics. A clear and novel finding of this study is that the intensity of the cool island effect from large water bodies not only diminishes with distance but is intricately influenced by the complexity of their shapes, as quantified by the WBSI, whereas the complexity of their boundaries enhances this effect. Additionally, the regulatory role of the cool island effect is observed to vary seasonally, being most pronounced in summer and less so in autumn and winter, thereby demonstrating a positive impact. In conclusion, our findings innovatively highlight how the specific shapes of water bodies, quantified through the water body shape index (WBSI), emerge as critical, yet previously underappreciated, drivers in modulating the urban thermal environment. This underscores a new avenue for urban planning, advocating for the strategic design of water bodies within urban landscapes. It also finds that spatial factors and seasonal variations significantly affect the intensity of the cool island effect. These findings offer valuable evidence for urban planning and climate change adaptation, emphasizing balancing natural elements with the built environment in urban design.

Long-Term Spatial Pattern Predictors (Historically Low Rainfall, Benthic Topography, and Hurricanes) of Seagrass Cover Change (1984 to 2021) in a Jamaican Marine Protected Area

Climate change and other anthropogenic factors have caused a significant decline in seagrass cover globally. Identifying the specific causes of this decline is paramount if they are to be addressed. Consequently, we identified the causes of long-term change in seagrass/submerged aquatic vegetation (SAV) percentage cover and extent in a marine protected area on Jamaica’s southern coast. Two random forest regression (RFr) models were built using 2013 hydroacoustic survey SAV percentage cover data (dependent variable), and auxiliary and 2013 Landsat 7 and 8 reflectance data as the predictors. These were used to generate 24 SAV percentage cover and benthic feature maps (SAV present, absent, and coral reef) for the period 1984–2021 (37 years) from Landsat satellite series reflectance data. These maps and rainfall data were used to determine if SAV extent/area (km2) and average percentage cover and annual rainfall changed significantly over time and to evaluate the influence of rainfall. Additionally, rainfall impact on the overall spatial patterns of SAV loss, gain, and percentage cover change was assessed. Finally, the most important spatial pattern predictors of SAV loss, gain, and percentage cover change during 23 successive 1-to-4-year periods were identified. Predictors included rainfall proxies (distance and direction from river mouth), benthic topography, depth, and hurricane exposure (a measure of hurricane disturbance). SAV area/extent was largely stable, with >70% mean percentage cover for multiple years. However, Hurricane Ivan (in 2004) caused a significant decline in SAV area/extent (by 1.62 km2, or 13%) during 2002–2006, and a second hurricane (Dean) in 2007 delayed recovery until 2015. Additionally, rainfall declined significantly by >1000 mm since 1901, and mean monthly rainfall positively influenced SAV percentage cover change and had a positive overall effect on the spatial pattern of SAV cover percentage change (across the entire bay) and gain (close to the mouth of a river). The most important spatial pattern predictors were the two rainfall proxies (areas closer to the river mouth were more likely to experience SAV loss and gain) and depth, with shallow areas generally having a higher probability of SAV loss and gain. Three hurricanes had significant but different impacts depending on their distance from the southern coastline. Specifically, a hurricane that made landfall in 1988 (Gilbert), resulted in higher SAV percentage cover loss in 1987–1988. Benthic locations with a northwestern/northern facing aspect (the predominant direction of Ivan’s leading edge wind bands) experienced higher SAV losses during 2002–2006. Additionally, exposure to Ivan explained percentage cover loss during 2006–2008 and average exposure to (the cumulative impact of) Ivan and Dean (both with tracks close to the southern coastline) explained SAV loss during 2013–2015. Therefore, despite historic lows in annual rainfall, overall, higher rainfall was beneficial, multiple hurricanes impacted the site, and despite two hurricanes in three years, SAV recovered within a decade. Hurricanes and a further reduction in rainfall may pose a serious threat to SAV persistence in the future.

Influence of New Parameterization Schemes on Arctic Sea Ice Simulation

Two coupled climate models that participated in the CMIP6 project (Coupled Model Intercomparison Project Phase 6), the Earth System Model of Chinese Academy of Sciences version 2 (CAS-ESM2-0), and the Nanjing University of Information Science and Technology Earth System Model version 3 (NESM3) were assessed in terms of the impact of four new sea ice parameterization schemes. These four new schemes are related to air–ice heat flux, radiation penetration and absorption, melt ponds, and ice–ocean flux, respectively. To evaluate the effectiveness of these schemes, key sea ice variables with and without these new schemes, such as sea ice concentration (SIC) and sea ice thickness (SIT), were compared against observation and reanalysis products from 1980 to 2014. The simulations followed the design of historical experiments within the CMIP6 framework. The results revealed that both models demonstrated improvements in simulating Arctic SIC and SIT when the new parameterization schemes were implemented. The model bias of SIC in some marginal sea ice zones of the Arctic was reduced, especially during March. The SIT was increased and the transpolar gradient of SIT was reproduced. The changes in spatial patterns of SIC and SIT after adding new schemes bear similarities between the two coupled models. This suggests that the new schemes have the potential for broad application in climate models for simulation and future climate scenario projection, especially for those with underestimated SIT.

Spatial–temporal patterns of ecological changes in the Dongting Lake region and their responses to climate factors and human activities

ABSTRACT The Dongting Lake region is an important ecological and environmental protection zone in the Yangtze River Economic Belt of China. Long-term monitoring and evaluation of its ecological environment is of great significance. In this study, the spatio-temporal pattern of ecological condition change and its response to climate factors and human activities in the Dongting Lake region was quantitatively analyzed using RSEI (Remote Sensing Ecological Index) model. The primary conclusions are as follows: (1) The temporal pattern of ecological changes has a small fluctuation period (1990–2007) and a continuous improvement period (2007–2020) with an ecological improvement rate of 1.17% per year. (2) The spatial pattern of ecological changes is directly tied to the land use types in this area. 17.36% of the regions with an excellent ecological level are primarily woodland, whereas 4.45% of the areas with a low ecological level are mostly urban. (3) The deterioration in ecological conditions in urban areas is primarily attributable to human activities, whereas the decline in ecological conditions in surrounding mountainous regions and central agricultural regions is primarily attributable to climate factors. Our research provides valuable support for ecological environment monitoring and management strategy formulation in the Dongting Lake region.

Satellite-Derived Indicators of Drought Severity and Water Storage in Estuarine Reservoirs: A Case Study of Qingcaosha Reservoir, China

Estuarine reservoirs are critical for freshwater supply and security, especially for regions facing water scarcity challenges due to climate change and population growth. Conventional methods for assessing drought severity or monitoring reservoir water level and storage are often limited by data availability, accessibility and quality. We present an approach for monitoring estuarine reservoir water levels, storage and extreme drought via satellite remote sensing and waterline detection. Based on the CoastSat algorithm, Landsat-8 and Sentinel-2 images from 2013 to 2022 were adopted to extract the waterline of Qingcaosha Reservoir, the largest estuarine reservoir in the world and a key source of freshwater for Shanghai, China. This study confirmed the accuracy of the satellite-extracted results through two main methods: (1) calculating the angle of the central shoal slope in the reservoir using the extracted waterline data and measured water levels and (2) inverting the time series of water levels for comparison with measured data. The correlation coefficient of the estimated water level reached ~0.86, and the root mean square error (RMSE) of the estimated shoal slope was ~0.2°, indicating that the approach had high accuracy and reliability. We analyzed the temporal and spatial patterns of waterline changes and identified two dates (21 February 2014 and 15 October 2022) when the reservoir reached the lowest water levels, coinciding with periods of severe saltwater intrusions in the estuary. The extreme drought occurrences in the Qingcaosha Reservoir were firstly documented through the utilization of remote sensing data. The results also indicate a strong resilience of the Qingcaosha Reservoir and demonstrate that the feasibility and utility of using satellite remote sensing and waterline detection for estuarine reservoir storage can provide timely and accurate information for water resource assessment, management and planning.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease.

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

Mobility restrictions in response to local epidemic outbreaks in rock-paper-scissors models

We study a three-species cyclic model whose organisms are vulnerable to contamination with an infectious disease which propagates person-to-person. We consider that individuals of one species perform a self-preservation strategy by reducing the mobility rate to minimise infection risk whenever an epidemic outbreak reaches the neighbourhood. Running stochastic simulations, we quantify the changes in spatial patterns induced by unevenness in the cyclic game introduced by the mobility restriction strategy of organisms of one out of the species. Our findings show that variations in disease virulence impact the benefits of dispersal limitation reaction, with the relative reduction of the organisms’ infection risk accentuating in surges of less contagious or deadlier diseases. The effectiveness of the mobility restriction tactic depends on the deceleration level and the fraction of infected neighbours which is considered too dangerous, thus triggering the defensive strategy. If each organism promptly reacts to the arrival of the first viral vectors in its surroundings with strict mobility reduction, contamination risk decreases significantly. Our conclusions may help biologists understand the impact of defensive strategies in ecosystems during an epidemic.

Spatial patterns analysis of land use changes using spatial metrics in the peri-urban area of Surakarta City 2023

The development of cities and the transformation of suburbs are interrelated. Limited land in urban areas causes urban development to move outward towards peri-urban areas. Morphologically, the spatial development of urban fairy areas causes land use change. Surakarta City, as the mother city of the Subosukowonosraten Area, has experienced over-capacity, causing the effect of Surakarta City towards its periphery. This study aims to analyze spatial patterns of land use change using a spatial metrics approach. Research is quantitative descriptive research with a spatial approach. The results showed an increasing trend of residential land use change in all peri-urban zones of Surakarta City, with a faster rate of land use change in the peri-urban area of the inner zone as an area directly adjacent to the core city. The pattern of land use change shows the inner zone, and the outer zone shows the development of clustering patterns. In contrast, the urban shadow zone and rural hinterland zone show the development of longitudinal patterns.

Spatial and Temporal Changes in Social Vulnerability to Natural Hazards in Mexico

The spatial and temporal changes in social vulnerability to natural hazards in Mexico are analyzed. To this end, using census data from 2000, 2010, and 2020, and a statistical method, different indices were computed, and with a GIS-based approach, patterns of social vulnerability are examined. In addition, a risk assessment test for severe weather (thunderstorms, hailstorms, and tornadoes) is made out. The results show different common social vulnerability driving factors in the 3 analyzed years, with root causes that have not been addressed since the beginning of the century. Likewise, a wider gap between Mexico’s most and least vulnerable populations is identified. The changes in spatial patterns respond to different historical situations, such as migration, urbanization, and increased population. Also, poverty, ethnicity, and marginalization factors located in very particular regions in Mexico have remained relatively the same in the last 20 twenty years. These situations have strongly influenced the spatial–temporal distribution of vulnerability in the country. The role of social vulnerability in the disaster risk to extreme events such as thunderstorms, hailstorms, and tornadoes in Mexico is fundamental to understanding changes in disaster distribution at the national level, and it is the first step to generating improvements in integrated risk management.

The Expanding of Proglacial Lake Amplified the Frontal Ablation of Jiongpu Co Glacier since 1985

In High Mountain Asia, most glaciers and glacial lakes have undergone rapid variations throughout changes in the climate. Unlike land-terminating glaciers, lake-terminating glaciers show rapid shrinkage due to dynamic interactions between proglacial lakes and glacier dynamics. In this study, we conducted a detailed analysis of the changes in the surface elevation, velocity, and especially frontal ablation on Jiongpu Co lake-terminating glacier. The results show that the Jiongpu Co glacier has twice as much negative mass balance compared to other glaciers, and the annual surface velocity has anomalously increased (3.6 m a−1 per decade) while other glaciers show a decreased trend. The frontal ablation fraction in the net mass loss of the Jiongpu Co glacier increased from 26% to 52% with the accelerated expansion of the proglacial lake. All available evidence indicates the presence of positive feedback between the proglacial lake and its host glacier. Our findings highlight the existence of proglacial lake affects the spatial change patterns of the lake-terminating glacier. Furthermore, the ongoing enlargement of the lake area amplifies the changes associated with the evolution of the lake-terminating glacier.

Spatial patterns of Holocene temperature changes over mid-latitude Eurasia

The Holocene temperature conundrum, the discrepancy between proxy-based Holocene global cooling and simulated global annual warming trends, remains controversial. Meanwhile, reconstructions and simulations show inconsistent spatial patterns of terrestrial temperature changes. Here we report Holocene alkenone records to address spatial patterns over mid-latitude Eurasia. In contrast with long-term cooling trends in warm season temperatures in northeastern China, records from southwestern Siberia are characterized by colder conditions before ~6,000 years ago, thus long-term warming trends. Together with existing records from surrounding regions, we infer that colder airmass might have prevailed in the interior of mid-latitude Eurasian continent during the early to mid-Holocene, perhaps associated with atmospheric response to remnant ice sheets. Our results challenge the proposed seasonality bias in proxies and modeled spatial patterns in study region, highlighting that spatial patterns of Holocene temperature changes should be re-considered in record integrations and model simulations, with important implications for terrestrial hydroclimate changes.

Spatial and Temporal Water Pattern Change Detection through the Normalized Difference Water Index (NDWI) for Initial Flood Assessment: A Case Study of Kuala Lumpur 1990 and 2021

Surface water pattern changes in terms of quantity and directions is caused by many hydrological hazards such as flooding. Rapid urbanization in Kuala Lumpur has destroyed urban forest trees as the most valuable urban green infrastructure (UGI). Then surface, vegetation changes and land transformation, concrete roads, covered roofs, and climate changes impacts changed the water pattern and hydrological system in Kuala Lumpur. Satellite data used to collect data from 1990 and 2021 to show how significant has been these changes. To demonstrate the spatial and temporal changes of hydrological changes in Kuala Lumpur The Normalized Difference Water Index (NDWI) applied for a 30 years assessment. Remote sensing (RS) and Geographical Information Systems (GIS) have helped us detect dynamic changes on the Earth's surface. The mean NDWI of one year was calculated in this study using Kuala Lumpur NDWI from 1990/01/01 to 1990/12/30. The extracted image is larger than the study area and extends beyond Kuala Lumpur's city limits. This image only detected water bodies on the surface of Kuala Lumpur, which is represented in grey or white, such as lakes, rivers, ponds, or any degree of wetness. Because urban forest covered more than 15% of Kuala Lumpur in 1990, surface water was naturally controlled and saved by forest tree and forest soil. Image data for 2021 was taken from Landsat 8, which uses different bands and the same algorithm to visualize NDWI based on the availability of satellite data. The data was averaged over a one-year period between 2021/01/01 to 2021/12/30; as a result, the NDWI in Kuala Lumpur was depicted using the same algorithm from Landsat 8 with different bands. The researchers discovered that urban surface water bodies have increased over the last 30 years, rising from 0.383635 and -.0593184 in 1990 to 0.593288 and -0.44379 in 2021. This indicates that the NDWI index has increased the most in Kuala Lumpur. As previously stated, rapid changes in land use and land cover in the last 30 years have had a negative impact on Kuala Lumpur's NDWI.

Forest and Natural Vegetation Cover Loss Over 2000 to 2020 in Sri Lanka; A Canopy Density Base Analysis

As one of the most important biodiversity hotspot, forest and natural vegetation areas play an essential role in the global ecosystem. It provides an uncountable number of ecosystem services while controlling the adverse impacts of climatic changes. With the expansion of civilization and fulfilling the infinite needs of man, forests and natural vegetation areas were destroyed, especially for agricultural purposes, development projects and timber. Due to this, the accelerated growth of deforestation and loss of natural vegetation can be observed in Sri Lanka in the past few decades. This study aimed to identify the forest and natural vegetation area loss from 2000 to 2020 with a particular focus on the Canopy Density (CD) of tree cover (>25%, >50% and >75%) in Sri Lanka. The satellite estimated data (30 mx30 m resolution) was downloaded from the 2000 to 2020 time period from the Global Forest Watch (GFW) online platform conducted by the World Resource Institute were used. Spatial and temporal changing patterns of the forest and natural vegetation areas have been identified using descriptive analysis methods (percentage) using MS Excel 2019 software. Results of the study found that in 2000, 61.38 percent of the country was covered with above 25% tree cover CD, while 53.86 percent and 39.76 percent of areas have covered with the tree cover CD above 50% and 75%, respectively. However, when it has come to 2020, these areas have decreased by 52.78 percent (>25% CD), 44.27 percent (>50% CD) and 28.65 percent (>75% CD). During this period, 8.6 percent (>25% CD), 9.59 percent (>50% CD) and 11.11 percent (>75% CD) of the forest and natural vegetation areas of Sri Lanka have lost the country. Throughout this period, 2016 can be identified as a year at risk for deforestation due to its annual deforestation rate (>8.8 percent). The total area of forest cover lost in 2016 is 17799 ha (>25% CD), 15583 ha (>50% CD) and 9865 ha (>75% CD). This is nearly 13 percent of forest cover loss for all three types of CD tree cover areas. According to the calculations of the forest areas that have >75% of CD, Anuradhapura (12.06%), Kurunegala (9.82%), and Monaragala (8.49%) districts are the areas that contributed to forest cover loss in the country during 2000 to 2020. According to the study, the annual deforestation rate is still very high. Hence should be needed to monitor and take action to stop deforestation and achieve sustainability in natural resource management in Sri Lanka. 
 Keywords: Deforestation, Canopy density, Tree cover, Natural resource management, Sri Lanka

Climate Change and Human Health: Impacts and Vulnerability

Background: Climate change is a global health emergency, with its impacts being profoundly felt across various regions of Pakistan. Rising temperatures, changing precipitation patterns, and increased frequency of extreme weather events pose significant threats to public health, agriculture, and water resources. Understanding these impacts is crucial for developing targeted interventions to mitigate health risks associated with climate change. Objective: This study aims to assess the effects of climate change on health outcomes in Pakistan, focusing on temperature variations, precipitation changes, agricultural impacts, vector-borne diseases, and socio-economic vulnerabilities. Methods: A cross-sectional study was conducted in four regions of Pakistan (Punjab, Sindh, KPK, and Balochistan) from January 2022 to January 2023. A sample size of 3000 participants was selected through systematic random sampling. Meteorological data was collected from local weather stations, and health data was gathered through structured surveys, interviews, and medical examinations. Descriptive and inferential statistics were used to analyze the data, employing SPSS version 25 for statistical analysis. GIS mapping visualized the spatial patterns of climate change impacts. Results: The study found significant regional variations in climate change impacts. Temperature increases were most pronounced in Sindh (1.8°C), leading to heightened risks of heat-related ailments. Precipitation changes showed decreased rainfall in Punjab, causing water scarcity and an increase in waterborne diseases. Agricultural impacts revealed a 10% crop yield reduction in Punjab, resulting in increased malnutrition rates. Vector-borne diseases saw a noticeable rise in Sindh due to habitat expansion of disease vectors. Socio-economic vulnerability analysis indicated high vulnerability in urban areas of Sindh, with limited adaptive capacities. Conclusion: Climate change significantly affects health outcomes in Pakistan, with regional disparities necessitating targeted interventions. The study underscores the importance of incorporating climate change considerations into public health planning and policy-making to enhance resilience and adaptive capacities across vulnerable regions.

Effects of Diesel Emissions on Black Carbon and Particle Number Concentrations in the Eastern U.S.

The effects of emissions of diesel engines on black carbon and particle number concentrations, as well as climate-relevant aerosol properties, are explored for a summertime period in the Eastern U.S. using the chemical transport model PMCAMx-UF. A 50% reduction in diesel particulate emissions results in lower (23%) black carbon mass concentrations, as expected, and similar changes both in magnitude (27–30%) and spatial pattern for the absorption coefficient. However, an average 2% increase in the total particle number concentrations is predicted due to a decrease in the coagulation and condensation sinks and, at the same time, a 2% decrease in N100 (particles larger than 100 nm) concentrations. The diesel reduction results suggest that mitigation of large diesel particles and/or particle mass emissions can reduce climate-relevant properties related to the absorption of black carbon and provide health benefits; however, the changes could also have the unintended effect of increased ultrafine particle number concentrations. Changes in cloud condensation nuclei are predicted to be significantly less than expected, assuming a proportional reduction during this photochemically active period. Doubling the diesel emissions results in a domain-averaged 3% decrease in total particle number concentrations and a 3% increase in N100 concentrations. PM2.5 BC concentrations increase on average by 46%, and similar changes (52–60%) are predicted for the absorption coefficient. Extinction coefficients for both perturbation simulations changed by only a few percent due to the dominance of scattering aerosols in the Eastern U.S. during this period characterized by high photochemical activity.

Climate change and the biodiversity of alpine ponds: Challenges and perspectives.

Inland waters are among the most threatened biodiversity hotspots. Ponds located in alpine areas are experiencing more rapid and dramatic water temperature increases than any other biome. Despite their prevalence, alpine ponds and their biodiversity responses to climate change have been poorly explored, reflecting their small size and difficult access. To understand the effects of climate change on alpine pond biodiversity, we performed a comprehensive literature review for papers published since 1955. Through analysis of their geographic distribution, environmental features, and biodiversity values, we identified which environmental factors related to climate change would have direct or indirect effects on alpine pond biodiversity. We then synthesized this information to produce a conceptual model of the effects of climate change on alpine pond biodiversity. Increased water temperature, reduced hydroperiod, and loss of connectivity between alpine ponds were the main drivers of biodiversity geographic distribution, leading to predictable changes in spatial patterns of biodiversity. We identified three major research gaps that, if addressed, can guide conservation and restoration strategies for alpine ponds biodiversity in an uncertain future.

Proglacial lake evolution coincident with glacier dynamics in the frontal zone of Kvíárjökull, South‐East Iceland

AbstractThe termini of Icelandic glaciers are highly dynamic environments. Pronounced changes in frontal ablation in recent years have consequently changed ice dynamics. In this study, we reveal the inter‐seasonal dynamics of the Kvíárjökull ablation zone and proglacial zone using ArcticDEM and Sentinel‐2 images acquired between 2011 and 2021 and intra‐seasonal dynamics with repeated UAV surveys during summer 2021. Average glacier surface velocity in the ablation zone ranged from 51 m year−1 in 2015 up to 199 m year−1 in 2018, with maxima within the axial zone of the glacier and minima on the glacier edges. Coincidentally, and in accordance with glacier retreat/advance, the ice‐marginal proglacial lake fluctuated in its area, and we interpret that it was also a key factor in the development of the glacier terminus morphology. A complex spatial pattern of glacier surface elevation changes, including thickening in the frontal true left margin of the terminus, is interpreted to be due to variable subglacial topography, relatively fast ice flow from the accumulation zone and an insulating effect of glacier surface debris cover. In contrast, the true right (southern) part of the glacier terminus experienced thinning and retreat/disintegration also during the 2021 summer season, which we attribute to enhanced frontal ablation connected to the intrusion of lake water into the crevassed glacier terminus. Overall, this study suggests that where glaciers are developing ice‐marginal lakes complex patterns of glacier dynamics and mass loss can be expected, which will confound understanding of the short‐term evolution of these environments.

Hotspot Identification and Causal Analysis of Chinese Rural Tourism at Different Spatial and Temporal Scales Based on Tourism Big Data

Rural tourism serves as a crucial means for fostering rural economic prosperity and inheriting rural culture. The assessment of the quality of rural tourism development and the identification of disparities in rural tourism development among regions have become focal points in current research. This paper utilizes tourism big data to establish a system for evaluating rural tourism popularity and proposes a method for identifying rural tourism hotspots. The study explores the spatiotemporal evolution characteristics and formation mechanisms of the cold and hot patterns of rural tourism in China during two periods (pre-pandemic and post-pandemic) and on two spatial scales (provincial and municipal levels). The research findings indicate that (1) the annual variation in rural tourism popularity exhibits a fluctuating upward trend, with significant seasonal variations on a monthly basis. (2) The spatial pattern of rural tourism popularity changes with the scale effect. At the provincial level, hotspot areas form an east–west dual-core pattern, while at the municipal level, hotspot areas demonstrate an evolution from a three-core to a four-core pattern. In the post-pandemic era, rural tourism popularity in the northwest and southwest regions is experiencing a counter-trend growth. (3) At different spatiotemporal scales, influencing factors and their impact intensities vary. At the provincial level, road density and reception capacity consistently play dominant roles, and per capita disposable income significantly influences early-stage popularity enhancement. At the municipal level, resident population and tourism resources influence are the dominant factors, and the influence of air quality and regional media attention gradually strengthens. This article provides a new perspective on quantitative research in rural tourism, offering significant guidance for the rational allocation of resources in rural tourism, regional tourism collaboration, and the sustainable development of rural tourism in the post-pandemic era.

Spatiotemporal change of cultivated land in China during 2000-2020.

Cultivated land is of great significance for ensuring food security. Since the 21st century, China's rapid development has led to urban construction occupying a lot of cultivated land. The understanding of stage characteristics and regional differences needs to be improved. And it is necessary to quantify the temporal and spatial pattern of cultivated land changes since the 21st century. We used the global land cover dataset (GlobeLand30) to investigate the quantity and spatial distribution of cultivated land change in China from 2000 to 2020. The results show that: 1) Over the last two decades, China's arable land has diminished by 54,996 square kilometers. Notably, the arable land loss between 2010 and 2020 was 1.74 times greater than that from 2000 to 2010. This decline has been exacerbated by factors such as the expansion of urban and rural areas, as well as initiatives to revert farmland to forests and grasslands; 2) The eastern coastal regions experienced the most severe net arable land loss, with a net reduction of 42,989 square kilometers from 2000 to 2020, primarily driven by urban expansion; 3) In contrast, the western regions demonstrated the most substantial net increase in arable land, expanding by 11,583 square kilometers from 2000 to 2020, primarily driven by the development of forests and grasslands. It is noteworthy that despite some areas successfully implementing policies to return farmland to forests and grasslands, the ecologically fragile western regions continue to experience accelerated conversion of these natural landscapes into arable land, partly to compensate for the farmland decrease driven by urbanization in the eastern regions. Looking ahead, China's cultivated protection policy must strike a balance between the ecological value of the western region and the economic value of the eastern region.