Search

Forest soils are considered the largest carbon and nitrogen pools in soil organic matter among terrestrial ecosystems, and soil carbon and nitrogen dynamics and greenhouse gas (GHG) emissions are normally affected by climate change and human activity. The collection of recent research on this scientific theme would provide a basis for understanding the responses of soil carbon and nitrogen dynamics and GHG fluxes in forest ecosystems to climate change and human activity. A Special Issue was, thus, organized to discuss recent research achievements, including a total of nine research articles and one review. This Special Issue includes the effects of climate changes such as changes in throughfall, snow cover, and permafrost degradation; human activities such as nitrogen and/or phosphorus addition and the use of biochar; and soil–plant interactions on soil carbon and nitrogen dynamics and GHG fluxes in forest ecosystems. Although this collection of papers reflects only a small part of this scientific theme, it can, to some extent, provide a basis for understanding some important research aspects related to the future of forest soil carbon and nitrogen dynamics and GHG fluxes in a changing world, thereby enabling sustainable development and the mitigation of climate change. [ABSTRACT FROM AUTHOR]

Understanding the environmental significance of pollen and spores in alluvial plains is important for stratigraphic correlation and paleoenvironmental reconstruction. This paper presents palynological data from the North China Plain and explores their relationship with paleoflood records and human impacts since the Holocene. Our data reveal that pollen concentration and pollen assemblage vary in flood deposits (including overbank deposits and slackwater deposits) and inter-flood deposits (including sandy soils and lacustrine deposits). Flood deposits have higher fern percentages (28.6%) and lower herbaceous percentages (14.8%) compared to inter-flood deposits, though slackwater deposits share similar pollen concentrations and assemblages with sandy soils. Notably, overbank deposits are characterized by pollen-poor zones and aggregation of deteriorated pollen grains, especially in Unit III (755-385 cm, ca. 3.2-2.2 ka) and Unit V (190-0 cm, after ca. 0.6 ka). These findings suggest that overbank deposits correspond to strengthened hydrodynamic conditions at the flood-peak stage. Furthermore, the indicative pollen and spores provide compelling evidence for intensifying human impact in the North China Plain since the late Holocene. An aggregation of Selaginella sinensis at the depth of 640-610 cm indicates deforestation in the uplands since ca. 2.9 ka. Similarly, a sharp increase in Malvaceae percentage at the depth of 285-215 supports historical records of initial cotton planting in the Tang Dynasty (ca. 1.4-1.1 ka). The study underscores the value of palynological analysis for reconstructing paleoenvironment and human-environment interactions, providing a robust framework for understanding landscape evolution in the North China Plain. [ABSTRACT FROM AUTHOR]

Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important factors influencing water quantity and quality, and there is a need to integrate watershed socioeconomic activities into the paradigm of watershed ecohydrological process studies. Then, we propose a new framework for integrated watershed management. It includes (1) data collection: building an integrated observation network; (2) theoretical basis: attribution analysis; (3) integrated modeling: medium- and long-term prediction of ecohydrological processes by human–nature interactions; and (4) policy orientation. The paper was a potential solution to overcome challenges in the context of frequent climate extremes and rapid land-use change. [ABSTRACT FROM AUTHOR]

Lakes are sensitive indicators of climatic change and are important resources for regional economic development. In recent years, there have been many studies related to the changes in lake area and lake volume. However, further studies are still required to understand the responses of lakes to climatic change and human activities. This paper utilizes lakes in the Qaidam Basin, an inland arid region of China, as the object of study and investigates the characteristics of variability in lake changes and its driving forces by combining multi-source remote sensing, model simulations and historical data. We first analyzed the spatiotemporal pattern of climatic change in the basin under the background of global warming. The response of lake water volume to climatic change and human activities is then discussed. Finally, the main factors that affect the change in lake water volume in different regions of the basin are delineated. The water volume of lakes in the Qaidam Basin increased by 3.81 km3 from 1990 to 2020. Particularly since the 21st century, the water volume of lakes has increased rapidly, and an increasingly abrupt change appeared around 2015. The increases in precipitation and vegetation area are the main and secondary factors that led to the increase in total lake water volume in the basin, respectively. However, the main influencing factors still vary in different regions. The impact of air temperature, evaporation, and changes in the cropland area on the change in lake water volume is generally not obvious. Human activities, such as the development of salt lakes and damming, have led to substantial changes in the spatial pattern of lakes in the middle of the basin and are associated with the replacement, genesis, and disappearance of Yiliping Lake, Yahu Lake and West Taijinar Lake, respectively. This study reveals the changing characteristics of climate and lake water volume in inland arid basins in China, which are highly important to understand the responses of lakes to climatic change and human activities, and provides a scientific basis for the rational development and utilization of lake resources in arid basins. [ABSTRACT FROM AUTHOR]

Research on precipitation regularity in the past 120 years is an important link in analyzing the precipitation characteristics of watersheds. This paper systematically analyzes the characteristic changes of centennial precipitation data in the Haihe River basin with the help of CRU data, PCI, SPI, and the Pearson type III curve. The results show that the spatial and temporal distribution of precipitation in the Haihe River basin has a more obvious inconsistency. The temporal distribution shows the characteristics of relatively stable in the early period and increasing fluctuation in the later period, the concentration of precipitation gradually decreases, and the overall drought level decreases. The spatial distribution shows a general pattern of gradually decreasing from southwest to northeast, the overall trend of summer precipitation changes from stable to north–south extremes, and the distribution probability of extreme precipitation events in the basin decreases from southeast to northwest, while the drought-prone area transitions from the northeast to the west and southwest of the basin. Under the influence of both climate change and human activities, the seasonal distribution of precipitation tends to be average, the area affected by extreme precipitation rises, and the arid area shifts to the inland area. [ABSTRACT FROM AUTHOR]

Many studies have explored divergent deep neural networks in human activity recognition (HAR) using a single accelerometer sensor. Multiple types of deep neural networks, such as convolutional neural networks (CNN), long short-term memory (LSTM), or their hybridization (CNN-LSTM), have been implemented. However, the sensor orientation problem poses challenges in HAR, and the length of windows as inputs for the deep neural networks has mostly been adopted arbitrarily. This paper explores the effect of window lengths with orientation invariant heuristic features on the performance of 1D-CNN-LSTM in recognizing six human activities; sitting, lying, walking and running at three different speeds using data from an accelerometer sensor encapsulated into a smartphone. Forty-two participants performed the six mentioned activities by keeping smartphones in their pants pockets with arbitrary orientation. We conducted an inter-participant evaluation using 1D-CNN-LSTM architecture. We found that the average accuracy of the classifier was saturated to 80 ± 8.07% for window lengths greater than 65 using only four selected simple orientation invariant heuristic features. In addition, precision, recall and F1-measure in recognizing stationary activities such as sitting and lying decreased with increment of window length, whereas we encountered an increment in recognizing the non-stationary activities. [ABSTRACT FROM AUTHOR]

As elicitors of terrestrial system change (e.g., land use transformation) through the introduction of anthropogenic causes, the spatial patterns and levels of roads might be more detrimental to the long-term health of ecosystems at a large scale than the road paving itself. This paper reveals the relationship between soil erosion and roads from a large-scale perspective in Jiangxi Province, China. Temporal and spatial distribution characteristics of artificial and natural drive factors of soil erosion alongside roads were addressed. It was found that, from 1990 to 2010, Jiangxi Province experienced an obvious reduction in soil erosion (the mean annual soil erosion rate decreased from 930.8 t.km-2.a-1 to 522.0 t.km-2.a-1), which was positively correlated with road density (p < 0.01). The maximum soil erosion reduction occurred at a distance of 0-1 km from the village roads. The order of soil erosion effects of the four levels of roads is: Village road > county road > provincial/national road. We emphasize that studying the indirect roles of roads in soil erosion is strongly dependent on a comprehensive consideration of historical policy and the economic development stage in a study area. This paper highlights the indirect role of village roads in soil erosion evolution. [ABSTRACT FROM AUTHOR]

Vision-based control systems play an important role in modern robotics systems. An important task in implementing such a system is developing an effective algorithm for recognizing human actions and the working environment and the design of intuitive gesture commands. This paper proposes an action recognition algorithm for robotics and manufacturing automation. The key contributions are (1) fusion of multimodal information obtained by depth sensors and cameras of the visible range, (2) modified Gabor-based and 3-D binary-based descriptor using micro-block difference, (3) efficient skeleton-based descriptor, and (4) recognition algorithm using the combined descriptor. The proposed binary micro-block difference representation of 3-D patches from video with a complex background in several scales and orientations leads to an informative description of the scene action. The experimental results showed the effectiveness of the proposed algorithm on datasets. [ABSTRACT FROM AUTHOR]

Integrated assessment models and coupled earth system models both have their limitations in understanding the interactions between human activity and the physical earth system. In this paper, a new human-earth system model, BNU-HESM1.0, constructed by combining the economic and climate damage components of the Dynamic Integrated Model of Climate Change and Economy to the BNU-ESM model, is introduced. The ability of BNU-HESM1.0 in simulating the global CO concentration and surface temperature is also evaluated. We find that, compared to observation, BNU-HESM1.0 underestimates the global CO concentration and its rising trend during 1965-2005, due to the uncertainty in the economic components. However, the surface temperature simulated by BNU-HESM1.0 is much closer to observation, resulting from the overestimates of surface temperature by the original BNU-ESM model. The uncertainty of BNU-ESM falls within the range of present earth system uncertainty, so it is the economic and climate damage component of BNU-HESM1.0 that needs to be improved through further study. However, the main purpose of this paper is to introduce a new approach to investigate the complex relationship between human activity and the earth system. It is hoped that it will inspire further ideas that prove valuable in guiding human activities appropriate for a sustainable future climate. [ABSTRACT FROM AUTHOR]

The cognitive goal of this paper is to assess whether marker-less motion capture systems provide sufficient data to recognize human postures in the side view. The research goal is to develop a new posture classification method that allows for analysing human activities using data recorded by RGB-D sensors. The method is insensitive to recorded activity duration and gives satisfactory results for the sagittal plane. An improved competitive Neural Network (cNN) was used. The method of preprocessing the data is first discussed. Then, a method for classifying human postures is presented. Finally, classification quality using various distance metrics is assessed. The data sets covering the selection of human activities have been created. Postures typical for these activities have been identified using the classifying neural network. The classification quality obtained using the proposed cNN network and two other popular neural networks were compared. The results confirmed the advantage of cNN network. The developed method makes it possible to recognize human postures by observing movement in the sagittal plane. [ABSTRACT FROM AUTHOR]

With the advent of miniature sensor technology, it is now possible to collect data on various aspects of human movement under free-living conditions. This technology has the potential to be used in activity monitoring systems in several areas, including health, military, sports applications, and human monitoring. The majority of research in wearables technology is focused on skin-mounted sensors or embedded in tight clothes. However, most of our daily clothes are loose or contain wide parts. This paper is interested in analyzing measurements of an accelerometer embedded in loose clothes. Experiments are conducted using a wearable node embedded in an oblong piece of cloth to emulate loose clothes. The piece is attached to a participant's arm while performing daily activities. Measurements are collected and presented in both time and frequency domains. Finally, activity measurements are classified using SVM and KNN algorithms. Results indicate that the differences in measurements between loose and tight clothes are noticeable in both domains, but the degradation in classification accuracy is unneglectable. When the sensor was embedded in 10 cm long piece of cloth the classification accuracies are over 80% and 90% for SVM and KNN, respectively, which is approximate, 5% less than the tight clothes accuracies. [ABSTRACT FROM AUTHOR]

The successful launch of Luojia 1-01 complements the existing nighttime light data with a high spatial resolution of 130 m. This paper is the first study to assess the potential of using Luojia 1-01 nighttime light imagery for investigating artificial light pollution. Eight Luojia 1-01 images were selected to conduct geometric correction. Then, the ability of Luojia 1-01 to detect artificial light pollution was assessed from three aspects, including the comparison between Luojia 1-01 and the Suomi National Polar-Orbiting Partnership Visible Infrared Imaging Radiometer Suite (NPP-VIIRS), the source of artificial light pollution and the patterns of urban light pollution. Moreover, the advantages and limitations of Luojia 1-01 were discussed. The results showed the following: (1) Luojia 1-01 can detect a higher dynamic range and capture the finer spatial details of artificial nighttime light. (2) The averages of the artificial light brightness were different between various land use types. The brightness of the artificial light pollution of airports, streets, and commercial services is high, while dark areas include farmland and rivers. (3) The light pollution patterns of four cities decreased away from the urban core and the total light pollution is highly related to the economic development. Our findings confirm that Luojia 1-01 can be effectively used to investigate artificial light pollution. Some limitations of Luojia 1-01, including its spectral range, radiometric calibration and the effects of clouds and moonlight, should be researched in future studies. [ABSTRACT FROM AUTHOR]

Copyright of Propósitos y Representaciones is the property of Universidad San Ignacio de Loyola and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Women face disproportionate challenges while undertaking coastal fieldwork. We draw on 18 responses that specifically raise fieldwork issues from an international survey about perceptions and experiences of gender inequality for those working in coastal sciences to discuss two common themes. These themes are barriers to fieldwork participation and challenges for women working in coastal field settings such as boats or working on beaches, including discrimination and sexual harassment. We suggest five priority behavioural and policy changes to improve the fieldwork experience for women in coastal sciences: (i) publicise field role models and trail blazers, (ii) improve opportunities and capacity for women to undertake fieldwork, (iii) establish field codes of conduct, (iv) acknowledge the challenges women face in the field and provide support where possible, and (v) foster an enjoyable and supportive fieldwork culture. [ABSTRACT FROM AUTHOR]

Desertification greatly threatens the ecological environment and sustainable development over approximately 30% of global land. In this study, the contributions of climate drivers and human activity in shaping the desertification process from 1984 to 2014 were quantified in the desertification-prone region (DPR) in Northern China (NC) by employing net primary productivity (NPP) as a proxy. The results reveal that 72.74% of the DPR experienced desertification mitigation and 27.26% experienced exacerbation. Climate drivers acted as primary drivers, contributing to both the mitigation (47.2%) and exacerbation (48.5%) of desertification, while human activity also played a crucial role, with contributions of 39.6% to mitigation and 41.0% to exacerbation of desertification. Furthermore, a shift in desertification dynamics emerged around 2000, with climate drivers promoting the mitigation process (66.8%), and precipitation was a dominant climatic factor for the mitigation of desertification after 2000, which was related to internal atmospheric variability. This study highlights changes in the contributions of different factors to desertification, underscoring the need for policy adjustment to attain sustainable land management in NC. [ABSTRACT FROM AUTHOR]

The Qinba Mountain range is a typical climate-sensitive and ecologically fragile region. Monitoring of vegetation dynamics is crucial for ecological protection and achieving sustainable development goals. Various mutation-detection methods, along with slope analysis, hot-spot analysis, and residual analysis, were used to examine changes in the Normalized Difference Vegetation Index (NDVI) during the growing and non-growing seasons over 41 years and to distinguish the relative effects of the drivers. This revealed four key findings. (1) NDVI increased at 0.02 decade−1, with mutation points in 2006 for growing-season NDVI and 2007 for non-growing-season NDVI. (2) The trend in NDVI changed markedly at the mutation point. After the mutation point, NDVI was impacted more by human activity than by climate change. The hot and cold spots of the NDVI trend rate change in location and range in the growing season; in the non-growing season, it shows an obvious north–south distribution. (3) The spatial patterns in the effects of the drivers changed at this point. In the growing season, before this point, climate change and human activity collectively enhanced NDVI in ca. 81.3% of the region; after the mutation point, this value declined to 59.9% of the area, and human activity became the dominant driver in the area formerly dominated by both factors in combination. In the non-growing season, after the mutation point, the areas where both factors promoted vegetation growth decreased by 12.6% and those where climate change alone promoted it decreased by 11.1%, whereas the area affected only by human activity increased by 11.6%. (4) Before this point, human activity contributed >60% to the change in NDVI in the western Qinling region, with climate change contributing >60% in the other areas. After this point, human activity exerted a stronger influence than climate change, contributing >60% to enhancing vegetation growth and >80% reducing it. These findings provide a scientific basis for protecting the Qinba Mountain ecosystem and are essential for achieving sustainable development goals. [ABSTRACT FROM AUTHOR]

Determining the relative roles of climatic versus anthropogenic factors in runoff alterations is important for sustainable water resource utilization and basin management. The Danjiang River watershed is a crucial water resource area of the middle route of the South-to-North Water Transfer Project. In this study, four widely used quantitative methods, including the simple linear regression, the double mass curve, the paired year with similar climate conditions, and an elasticity method based on the Budyko framework were applied to detect the relative contribution of climatic and anthropogenic factors to runoff variation in the Danjiang River watershed. The calculation processes of each method were systematically explained, and their characteristics and applications were summarized. The results showed that runoff decreased significantly (p < 0.05) with an average change rate of −3.88 mm year−1 during the period of 1960–2017, and a significant change year was detected in 1989 (p < 0.05). Generally, consistent estimates could be derived from different methods that human activity was the dominant driving force of significant runoff reduction. Although the impacts of human activity estimated by the paired year with similar climate conditions method varied among paired years, the other three methods demonstrated that human activity accounted for 80.22–92.88% (mean 86.33%) of the total reduction in the annual runoff, whereas climate change only contributed 7.12–19.78% (mean 13.67%). The results of this study provide a good reference for estimating the effects of climate change and human activities on runoff variation via different methods. [ABSTRACT FROM AUTHOR]

Anthropogenic activities are driving significant changes in coastal ecological environments, increasingly spotlighting microorganisms associated with seagrass bed ecosystems. Labyrinthula is primarily recognized as a saprophytic protist associated with marine detritus, and it also acts as an opportunistic pathogen affecting marine algae, terrestrial plants and mollusks, especially in coastal environments. The genus plays a key role in the decomposition of marine detritus, facilitated by its interactions with diatoms and through the utilization of a diverse array of carbohydrate-active enzymes to decompose seagrass cell walls. However, human activities have significantly influenced the prevalence and severity of seagrass wasting disease (SWD) through factors such as climate warming, increased salinity and ocean acidification. The rise in temperature and salinity, exacerbated by humaninduced climate change, has been shown to increase the susceptibility of seagrass to Labyrinthula, highlighting the adaptability of pathogen to environmental stressors. Moreover, the role of seagrass in regulating pathogen load and their immune response to Labyrinthula underscore the complex dynamics within these marine ecosystems. Importantly, the genotype diversity of seagrass hosts, environmental stress factors and the presence of marine organisms such as oysters, can influence the interaction mechanisms between seagrass and Labyrinthula. Besides, these organisms have the potential to both mitigate and facilitate pathogen transmission. The complexity of these interactions and their impacts driven by human activities calls for the development of comprehensive multi-factor models to better understand and manage the conservation and restoration of seagrass beds. [ABSTRACT FROM AUTHOR]

Meditation practice is mental health training. It helps people to reduce stress and suppress negative thoughts. In this paper, we propose a camera-based meditation evaluation system, that helps meditators to improve their performance. We rely on two main criteria to measure the focus: the breathing characteristics (respiratory rate, breathing rhythmicity and stability), and the body movement. We introduce a contactless sensor to measure the respiratory rate based on a smartphone camera by detecting the chest keypoint at each frame, using an optical flow based algorithm to calculate the displacement between frames, filtering and de-noising the chest movement signal, and calculating the number of real peaks in this signal. We also present an approach to detecting the movement of different body parts (head, thorax, shoulders, elbows, wrists, stomach and knees). We have collected a non-annotated dataset for meditation practice videos consists of ninety videos and the annotated dataset consists of eight videos. The non-annotated dataset was categorized into beginner and professional meditators and was used for the development of the algorithm and for tuning the parameters. The annotated dataset was used for evaluation and showed that human activity during meditation practice could be correctly estimated by the presented approach and that the mean absolute error for the respiratory rate is around 1.75 BPM, which can be considered tolerable for the meditation application. [ABSTRACT FROM AUTHOR]

Aim:Prediction of human activity data using Random forest algorithm against Decision tree algorithm for better accuracy using machine learning. Materials and Methods: Random forest algorithm (N=20)and Decision Tree algorithm (N=20) these two algorithms are calculated by using 2 Groups and I have taken 20 samples for both algorithm and accuracy in this work. Results: Based on the Results Accuracy obtained in terms of accuracy is identified by Random forest algorithm (90.6%) over Decision Tree algorithm algorithm(86.66%). Statistical significance difference between Random forest algorithm and Decision Tree algorithm was found to be 0.001 (p<0.05), using a=0.05 and power=0.80.conclusion: From the analysis it was observed that the human activity data using Random forest algorithm is better than Decision Tree algorithm for better accuracy using machine learning. [ABSTRACT FROM AUTHOR]

The current trend toward longer spans and lighter floor systems, combined with reduced damping and new activities, have resulted in an increasing complaints on floor vibration from building owners and occupants. Heel-drop, jumping, and walking impacts, which may lead to discomfort problems in daily life, were imposed on a large-span arched prestressed concrete truss (APT) girder system studied. The natural frequencies, peak acceleration, average root-mean-square acceleration (ARMS), maximum transient vibration value (MTVV), and perception factor for the girder were obtained and checked against the existing codes and standards. The purpose of this paper is to provide researchers and engineers with a detailed evaluation on the vibration behavior of the APT girder under different human activities, with a comprehensive review on the relevant criteria and some suggestions. Lastly, the following threshold peak accelerations are suggested: 650 mm/s2 for transient heel-drop impact, 1450 mm/s2 for transient jumping impact, and 250 mm/s2 for steady-state walking. In addition, the threshold values of 90 mm/s2 and 50 mm/s2 are suggested for MTVV and ARMS, respectively, under steady-state walking. [ABSTRACT FROM AUTHOR]

The quality of urban green space has an impact on the health and well-being of populations. Previous studies have shown that consideration of crowd activity characteristics is the key premise of landscape space design and planning. However, there is limited research on the correlation between features of the spatial layout of Mini Urban Green Spaces (MUGS) and the behavior of people, and it is difficult to take into account the possible distribution of people and their activity characteristics during the design phase of MUGS. This study aims to construct a technical workflow utilizing the AnyLogic platform and agent-based simulation methods for analyzing the characteristics of landscape spatial layouts considering dynamic human behavior. One MUGS, named 511 Park in Nanjing, China, was selected as the case for the application of the method and exploration of the impacts of spatial elements and layout on crowd activity types and density. We investigated the impact of four types of spatial elements—paths, facilities, nodes, and entrances—on human activities in MUGS. The results showed that path layout emerged as the most significant influencing factor. Changes in nodes and the number of facilities have a relatively minor impact on people's activities. There was an apparent impact of changes in path orientation around nodes on the dynamics of the flow of people. This study could provide valuable insights for landscape designers, aiding informed decision-making during the construction, renovation, and management of MUGS. [ABSTRACT FROM AUTHOR]

Copyright of Advances in Atmospheric Sciences is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Flash floods are important natural disasters in China that can result in casualties and property losses. In this paper, we present a quantitative approach to examine the driving factors of the spatiotemporal distribution of flash floods based on a geographical detector. The environmental background condition (elevation, slope, etc.), precipitation, and human activity factors, as well as changes in these factors, are investigated in Sichuan Province via a driving force analysis. The results show that heavy precipitation is the most important driver, with power of determinant (PD) values of 0.71 and 0.77 for the spatial distributions of flash floods from 1995 to 2004 and from 2005 to 2014, respectively. The PDs of population density are 0.65 and 0.78 in the same two periods, while those of elevation are 0.59 and 0.73. Precipitation variability is the most important driver of the spatiotemporal variability of flash floods, followed by GDP density and population density, with PDs of 0.48, 0.29, and 0.27, respectively. The results show that human activities and precipitation are the primary driving forces of the spatiotemporal variability of flash floods and should be the focus of flash flood prevention and forecasting. [ABSTRACT FROM AUTHOR]

Grassland, as one of the most important ecosystems on Earth, experiences fires that affect the local ecology, economy and society. Notably, grassland fires occur frequently each year in northeastern China. Fire occurrence is a complex problem with multiple causes, such as natural factors, human activities and land use. This paper investigates the disruptive effects of grassland fire in the northeastern Inner Mongolia Autonomous Region of China. In this study, we relied on thermal anomaly detection from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor to identify fire occurrences, and land use data were acquired by Landsat Thematic Mapper/Enhanced Thematic Mapper (TM/ETM). We discussed the relationship between land use and the spatial distribution of grassland fires. The results showed that the impact of land use on grassland fires was significant. Spatially, approximately 80% of grassland fires were clustered within 10 km of cultivated land, and grassland fires generally occurred in areas of intense human activity. The correlation between the spatial distribution of grassland fires and the land use degree in 2000, 2005 and 2010 was high, with R2 values of 0.686, 0.716, 0.633, respectively (p < 0.01). These results highlight the importance of the relationship between land use and grassland fire occurrence in the northeastern Inner Mongolia Autonomous Region. This study provides significance for local fire management and prevention. [ABSTRACT FROM AUTHOR]

[Objective] This study is aimed to understand the spatiotemporal changes in vegetation in the Qinghai Hehuang Valley and clarify the effects of climate change, land development and utilization and human activities on vegetation change. [Methods] The MODIS NDVI dataset from 2000 to 2020 was used to characterize vegetation changes. Based on Theil-Sen Median trend test, partial correlation analysis, geographical detectors and other methods, this paper explored the spatiotemporal changes of NDVI in Qinghai Hehuang Valley and its relationship with temperature, precipitation, slope, soil type, human activities and other influencing factors. [Results] (1) In the past 20 years, the vegetation NDVI in the Hehuang Valley region had shown a fluctuating growth trend, with a significant increase in the area of 2.21×104 km2 (p

Human activity is omnipresent in our landscapes. Animals can perceive risk from humans similar to predation risk, which could affect their fitness. We assessed the influence of the relative intensity of recreational activities on the bodyweight and pregnancy rates of red deer (Cervus elaphus) between 1985 and 2015. We hypothesized that stress, as a result of recreational activities, affects the pregnancy rates of red deer directly and indirectly via a reduction in bodyweight. Furthermore, we expected non‐motorized recreational activities to have a larger negative effect on both bodyweight and fecundity, compared to motorized recreational activities. The intensity of recreational activities was recorded through visual observations. We obtained pregnancy data from female red deer that were shot during the regular hunting season. Additionally, age and bodyweight were determined through a post‐mortem examination. We used two Generalized‐Linear‐Mixed Models (GLMM) to test the effect of different types of recreation on (1) pregnancy rates and (2) bodyweight of red deer. Recreation had a direct negative correlation with the fecundity of red deer, with bodyweight, as a mediator as expected. Besides, we found a negative effect of non‐motorized recreation on fecundity and bodyweight and no significant effect of motorized recreation. Our results support the concept of humans as an important stressor affecting wild animal populations at a population level and plead to regulate recreational activities in protected areas that are sensitive. The fear humans induce in large‐bodied herbivores and its consequences for fitness may have strong implications for animal populations. [ABSTRACT FROM AUTHOR]

Background: Urban green spaces are important for human health, but they may expose visitors to tick-borne diseases. This not only presents a potential public health challenge but also undermines the expected public health gains from urban green spaces. The aim of this study is to assess the public health risk of tick-borne diseases in an urban green space used for recreation in Stockholm, Sweden. Methods: We used a mixed method approach identifying both the magnitude of the tick hazard and the extent of the human exposure to tick-borne diseases. At six entry points to an urban green space, we sampled ticks and documented microhabitat conditions from five randomly assigned 2 m × 2 m plots. Surrounding habitat data was analyzed using geographical information system (GIS). Nymphs and adult ticks were tested for Borrelia burgdorferi sensu lato and Anaplasma phagocytophilum using TaqMan qPCR. Positive B. burgdorferi (s.l.) ticks were further analyzed by nested PCR amplification and sequence analysis. Population census data and visitor count data were used to estimate the degree of human exposure to tick-borne diseases. To further understand the degree to which visitors get in contact with infected ticks we also conducted interviews with visitors to green spaces. Results: High tick densities were commonly found in humid broadleaved forest with low field vegetation. High pathogen prevalence was significantly correlated with increasing proportions of artificial areas. Integrating the tick hazard with human exposure we found that the public health risk of tick-borne diseases was moderate to high at most of the studied entry points. Many of the visitors frequently used urban green spaces. Walking was the most common activity, but visitors also engaged in activities with higher risk for tick encounters. Individual protective measures were connected to specific recreational activities such as picking berries or mushrooms. Conclusions: The number of visitors can be combined with tick inventory data and molecular analyses of pathogen prevalence to make crude estimations of the public health risk of tick-borne diseases in urban green spaces. The risk of encountering infected ticks is omnipresent during recreational activities in urban green spaces, highlighting the need for public health campaigns to reduce the risk of tick-borne diseases. [ABSTRACT FROM AUTHOR]

The instability of the river channels has increased in response to the combined effects of global warming and human activity. This instability threatens the lives and property of people who live along river courses. This study takes the Pingluo section of the upper Yellow River, which is ~28 km long and ~400 m wide, as its research focus. We studied 11 periods of Landsat remote sensing images from 1973 to 2023 and analyzed the evolutionary characteristics of the Pingluo section over the past 50 years. The channel morphology indices included the channel braiding index (BIT), the bar braiding index (BIB), the average area of the bar (Ab), and the width of the wet channel area (BW). The results showed that there was an overall shrinking trend in this section of the Yellow River; more particularly, fluctuations in indicators such as the river width and the braiding index highlighted an increasing–decreasing–increasing pattern of change. During the 1973–1986 period, the river showed a widening trend, with narrow anabranches cutting through the floodplain and both the river width and the braiding index increasing dramatically over a short period. Over the 1986–2018 period, the area of the wet channel continued to shrink to its lowest level for the past 50 years, the river's branches were diverted and abandoned, and the channel tended to straighten out. Between 2018 and 2023, the river showed a slightly expanding trend. The evolution of the river channel appears to be related to regional human activity and climate change. For example, after the joint filling of the Longyangxia and Liujiaxia reservoirs in the upper reaches of the Pingluo section of the Yellow River in 1986, runoff and sediment load along this section decreased, flood events became less frequent, and the channel tended to contract. In addition, the increase in extreme precipitation events over the last five years has led to an increase in the magnitude and frequency of peak discharge values in the region, which is the main reason for the increase in the river braiding index and area. [ABSTRACT FROM AUTHOR]

Wetlands within dryland regions are highly sensitive to climate change and human activities. Based on three types of land use data sources from satellite images and a spatial data analysis, the spatiotemporal characteristics of wetland evolution in China's drylands and their relationship with human interference and climate change from 1990 to 2020 were analyzed. The results were as follows: (1) The wetlands within China's drylands expanded, including rivers, lakes, and artificial wetlands, apart from marshes, which shrunk. Meanwhile, wetland fragmentation increased, with rivers being particularly severely fragmented. (2) Temperature and precipitation showed an increasing trend from 1990 to 2020 in China's drylands. Lakes and rivers expanded with regional differences due to the uneven distribution of precipitation and rising temperature. (3) Human activities, more than climate change, became the key driving factor for the changes in wetland patterns in China's drylands. The increased areas of farmland and grassland along with increased levels of drainage and irrigation activities led to the shrinkage of marshes and the fragmentation of rivers. The increase in the number of artificial reservoirs was the main reason for the expansion of artificial wetlands. This study clarifies the specific driving factors of different types of wetlands within China's drylands, which is of great use for better protecting wetlands and the gradual restoration of degraded wetlands. [ABSTRACT FROM AUTHOR]

The distribution of cultivated land in prehistoric times was primarily influenced by natural conditions and population density. This article presents a case study on modern cultivated land simulation to analyze the potential impact of variable selection and validation data accuracy on model precision. Additionally, methods were explored to enhance the accuracy of prehistoric cultivated land simulation. Seven natural variables and one settlement density variable were selected to simulate the distribution of cultivated land based on a Binary Logistic Regression model. The simulated results were then compared with real land use data from 1985, which are commonly used as validation data for prehistoric farmland reconstruction. The findings revealed that all eight selected parameters could explain the distribution of cultivated land in the research area, with annual precipitation being the most influential factor. The initial prediction accuracy was relatively low at 65.8%, with a Kappa coefficient of 0.316. Several factors were identified as affecting the prediction accuracy. Firstly, the scale effect diminished the impact of the slope and elevation on cultivated land distribution, and errors were introduced in the method used to calculate the distance from residential areas. Secondly, the loess hilly area in the southeastern part of the research area overpredicted cultivated land due to insufficient data on actual residential land demand. Lastly, strong human activity since the 1950s has altered the natural distribution of cultivated land, resulting in poor consistency ratings. To address these issues, a batch modification method was employed to correct the 1985 data. The validation of the prediction model using the corrected data demonstrated a significant improvement in accuracy. Therefore, it is recommended to use the revised 1985 land use data for verifying prehistoric cultivated land simulation in the region. However, further research is required to mitigate the impact of the first two errors. [ABSTRACT FROM AUTHOR]

Basin ecohydrological processes are essential for informing policymaking and social development in response to growing environmental problems. In this paper, we review watershed ecohydrology, focusing on the interaction between watershed ecological and hydrological processes. Climate change and human activities are the most important factors influencing water quantity and quality, and there is a need to integrate watershed socioeconomic activities into the paradigm of watershed ecohydrological process studies. Then, we propose a new framework for integrated watershed management. It includes (1) data collection: building an integrated observation network; (2) theoretical basis: attribution analysis; (3) integrated modeling: medium- and long-term prediction of ecohydrological processes by human–nature interactions; and (4) policy orientation. The paper was a potential solution to overcome challenges in the context of frequent climate extremes and rapid land-use change.

The interaction between human activity and landscape pattern has been a hot research topic during the last few decades. However, scholars used to measure human activity by social, economic and humanistic indexes. These indexes cannot directly reflect human activity and are not suitable for fine-grained analysis due to the coarse spatial resolution. In view of the above problems, this paper proposes a method that obtains the intensity of human activity from GPS trajectory data, collects landscape information from remote sensing images and further analyzes the interaction between human activity and landscape pattern at a fine-grained scale. The Lijiang River Basin is selected as the study area. Experimental results show that human activity and landscape pattern interact synergistically in this area. Built-up land and water boost human activity, while woodland restrains human activity. The effect of human activity on landscape pattern differs by the land cover category. Overall, human activities make natural land, such as woodland and water, scattered and fragmented, but cause man-built land, such as built-up land and farmland, clustered and regular. Nevertheless, human activities inside and outside urban areas are the opposite. The research findings in this paper are helpful for designing and implementing sustainable management plans. [ABSTRACT FROM AUTHOR]

This paper introduces a novel top-down approach to geospatially identify and distinguish areas of mixed use from predominantly residential areas within urban agglomerations. Under the framework of theWorld Bank's Central American Country Disaster Risk Profiles (CDRP) initiative, a disaggregated property stock exposure model has been developed as one of the key elements for disaster risk and loss estimation. Global spatial datasets are therefore used consistently to ensure wide-scale applicability and transferability. Residential and mixed use areas need to be identified in order to spatially link accordingly compiled property stock information. In the presented study, multi-sensor nighttime Earth Observation data and derivative products are evaluated as proxies to identify areas of peak human activity. Intense artificial night lighting in that context is associated with a high likelihood of commercial and/or industrial presence. Areas of low light intensity, in turn, can be considered more likely residential. Iterative intensity thresholding is tested for Cuenca City, Ecuador, in order to best match a given reference situation based on cadastral land use data. The results and findings are considered highly relevant for the CDRP initiative, but more generally underline the relevance of remote sensing data for top-down modeling approaches at a wide spatial scale. [ABSTRACT FROM AUTHOR]

Marine primary production and terrestrial input are the main sources of buried carbon in sediments of marginal seas. Only marine-source carbon buried in sediments, fixed and stored by marine ecosystems, belongs to "blue carbon" and reflects marine ecosystems' carbon sink function. The pattern of buried blue carbon in sediments, its flux, and its relationship with environmental changes remain unclear. The study aimed to investigate the composition of blue carbon in the sediments of Sanggou Bay, a special type of marginal sea. The analysis of sediment carbon sources was conducted through the C/N ratio and microscopic examination. The study also examined the long-term changes in the blue carbon burial fluxes. Results showed Blue carbon, which is sea-sourced carbon, accounted for about 23% of the total carbon content and its concentration ranged from 0.17% to 0.51%, with an average of about 0.25% ± 0.10%. The content of organic blue carbon in this sea area ranges from 0.09% to 0.26%, with an average of around 0.18% ± 0.04%. It constitutes approximately 72% of the buried blue carbon in the sediment, making it the primary component of buried blue carbon. Meanwhile, the content of inorganic blue carbon ranges from 0.01% to 0.32%. Over the past 70 years, the burial fluxes of sedimentary blue carbon, organic blue carbon and inorganic blue carbon in the Sanggou Bay are about 0.54 ± 0.22 mmol/(cm²a), 0.38 ± 0.07 mmol/(cm²a) and 0.17 ± 0.22 mmol/(cm²a), respectively; their long-term changes have been significantly affected by human aquaculture activities. Large-scale raft-rack aquaculture activities have caused a reduction in water flow velocity and an increase in the deposition of particulate organic matter, which in turn has led to the burial of organic blue carbon in the sediment. Additionally, the competition between aquaculture products and small calcareous organisms, such as mussels, foraminifera, may have inhibited the growth of small calcareous organisms. We suggest this has resulted in reduced burial fluxes of inorganic blue carbon and a decrease in its proportion among total blue carbon in the sea area. Our findings imply that aquaculture activities in Sanggou Bay had a negative impact on the burial of blue carbon in the sediments. [ABSTRACT FROM AUTHOR]

Rivers are an important source of water in humid regions, but their availability is greatly limited by water chemistry. In order to accurately identify the changes in river water chemical composition, the compositional analysis method (CoDA) is proposed from the perspective of compositional data analysis theory, which considers the geochemical riverine system as a whole and detects the compositional changes of the entire watershed. The basic data analysis is carried out by traditional analysis methods, and the results show that the hydrochemical characteristics of different sections of the basin have significant features. The water chemistry of Dongxi River is of the HCO3− Ca type. The water of the Xixi River shows a gradual evolution from the HCO3-Ca type and high SO42− content in the upper reaches to the Cl-Ca type in the lower reaches. The hydrochemistry of river water in the watershed is mainly affected by rock weathering leaching (PC1) and agricultural and domestic pollutant discharge (PC2), with a contribution rate of 48.4% and 19.7%, respectively. Rock weathering, mining, and agricultural pollution are the main factors affecting the chemical composition of river water in different regions. The spatial composition of a single sample at different scales is monitored by the Mahalanobis distance approach in an iterative manner to minimize the influence of a single anomaly on the composition center. The results show that the main reasons for the change in river water chemical composition along the Xixi River are attributed to mine pollution, domestic pollution, and tea plantation and that along the Dongxi River is caused by domestic pollution. The hydrochemical composition changes after the confluence of the Xixi River and Dongxi River are mainly affected by human activities and seawater in urban areas. This research could provide new perspectives and methods for detecting the influences of human and natural factors on the hydrochemistry of river water in humid regions worldwide. [ABSTRACT FROM AUTHOR]

This study analyzed the effects of climate variability and human activities on runoff and sediment yield of a watershed in the Central Rift Valley of Ethiopia since the 1980s. In the study, innovative trend analysis, the Pettitt test, and sequential regime shift detector methods were used to analyze trends and abrupt changes during the period 1981-2020. The Soil and Water Assessment Tool model was then integrated to disaggregate the contributions of climate variability, land-use change, and direct human activities on runoff and sediment yield at the watershed scale. The result indicates that the runoff and sediment yield decreased significantly with a sudden change in 2001. The study found that direct human activities played a dominant role, accounting for 57.9%, and 53.4% of annual runoff and sediment yield reduction, respectively. On the contrary, changes in climate and land use have led to a slight increase in runoff and sediment yield after 2001. The greater impacts of human activities can be attributed to the growth rate of water abstraction, and riverbed sand excavation during the past four decades. The findings of the result could be useful in supporting decision- makers in achieving watershed sustainability. [ABSTRACT FROM AUTHOR]

The loss of life and property in economically developed areas due to geological hazards caused by intense ground subsidence is incalculable. As one of the fastest growing areas in the Guangdong-Hong Kong-Macao Greater Bay Area, the study of ground subsidence in Nansha will help to provide a scientific basis for urban planning and improve the capacity of monitoring and prevention of ground subsidence. The combination of coastal soft soil foundation and urbanization conditions creates a certain risk of land subsidence. We chose Nansha District, the geographical center of the Greater Bay Area, as the study area to analyze its surface subsidence characteristics in recent years. The 20-view Sentinel-1A data and SBAS-InSAR technique were used to monitor the ground subsidence in Nansha from 2017 to 2023. The main rate of ground subsidence in Nansha ranges from −19.4 to 7.7 mm/yr and is distributed in the urban area, along the rivers, in the construction area, and in the reclamation area. As of 4 May 2023, the average ground settlement in Nansha is 10.05 mm and the maximum settlement can be up to 142.45 mm. The 6-year total settlement at all four settlement intensities is greater than 60 mm, with the highest value exceeding 110 mm. The cumulative settlement increases with time, but inverse settlement and no settlement also occur at points where settlement is severe. For settlement caused by soft soil consolidation, it is recommended that drainage pipes be installed to accelerate drainage as a means of stabilizing settlement. For settlement caused by groundwater extraction and additional loads on the road surface, it is recommended to rationally extract groundwater and reinforce the foundation of the road surface with severe settlement. [ABSTRACT FROM AUTHOR]

In recent decades, Digital transformation has significantly shifted human activities from physical space to cyber space. When users access the internet, uniform resource locator (URL) data are autogenerated. Using URLs, this study presents a novel framework for exploring cyber space structure from the perspectives of complex networks and activity fragmentation. Web domains within URL data are metaphorically regarded as 'digital locations,' and consecutive digital locations form 'cyber trajectories.' Human activities that occur at digital locations are semantically labeled and used to generate activity-based motifs. Motifs are defined as frequently occurring processes in cyber trajectories. Based on this, three network types are constructed: Global cyber human activity network, including all trajectories, and space-dependent and motif-dependent cyber human activity networks, focusing on specific regions and motifs. A case study conducted in Jilin, China, using approximately 4.3 gigabytes of URL data, revealed: 1) Cyber human activity patterns exhibit strong regularity and clustering of several types, with metropolitan regions favoring simpler patterns; 2) Cyber human activity networks demonstrate heavy-tailed and hierarchically polycentric structures; 3) The importance of websites in information dissemination increases super linearly along with their increased connectivity. This work deepens our understanding of cyber space functionality, offering insights into cyber information propagation. [ABSTRACT FROM AUTHOR]

Wetlands have powerful runoff regulation functions, which can effectively store and retain surface runoff. The runoff regulation function of wetlands is affected by wetland areas, which affect the capacity of flood control. To explore the law of the area change of the main wetlands of the Naolihe River Basin (MWNRB), the visual interpretation method was used to extract wetlands. To identify the reasons for area changes in the MWNRB, the maximum likelihood method, minimum distance method, and neural network method were used to classify land use types from remote sensing images; the M-K variation point test and Theil-Sen trend analysis were used to test the variation point and calculate the trend of precipitation and temperature series. To clarify the influence of wetland areas on runoff, the Gini coefficient and SRI of runoff were used to calculate runoff temporal inhomogeneity. The results showed that the area of the MWNRB obviously decreased, with 74.5 × 106 m2/year from 1993 to 2008, and increased slowly from 2008 to 2015, with 27.7 × 106 m2/year. From 1993 to 2008, 50.74% and 38.87% of wetlands were transformed into paddy fields and dry fields, respectively. From 2008 to 2015, 61.69% and 7.76% of wetlands were transformed from paddy fields and dry fields, respectively. The temperature of the MWNRB increased slowly by 0.04 °C/year from 1993 to 2008 and increased obviously by 0.16 °C/year from 2008 to 2015. The precipitation decreased by 5.6–8.1 mm/year and increased by 16.6–41.2 mm/year in 1993–2008 and 2008–2015, respectively. Compared with precipitation and temperature, land use change caused by human activities is the main cause of wetland area change. The area change of the MWNRB has a certain influence on the runoff regulation and storage capacity. The Gini coefficient and SRI index increased from 0.002/year (0.008) to 0.023/year from 1993 to 2008 and decreased from 0.046/year (0.045) to 0.161/year from 2008 to 2015, respectively. [ABSTRACT FROM AUTHOR]

Vegetation net primary productivity (NPP) is critical to maintaining and enhancing the carbon sink of vegetation. Shaoguan is a characteristic forest city in the subtropical region of South China and an ecological barrier in the Guangdong–Hong Kong–Macau Greater Bay Area (GBA), playing an instrumental role in protecting water resources, purifying air, and maintaining ecological balance. However, studies that quantify subtropical vegetation NPP dynamics in Shaoguan under the influence of climate and human drivers are still incomplete. In this research, vegetation NPP at 30 m resolution was estimated from 2001 to 2020 using the enhanced CASA model based on the GF-SG algorithm in Shaoguan. The RESTREND method was then utilized to quantify climatic and human effects on NPP. The results indicated that the vegetation NPP in Shaoguan increased rapidly (4.09 g C/m2/yr, p < 0.001) over the past 20 years. Climate and human drivers contributed 0.948 g C/m2/yr and 3.137 g C/m2/yr to vegetation NPP, respectively. Human activity plays a major role in vegetation restoration through ecological projects, whereas vegetation deterioration is primarily attributable to the combined action of climate change and human activity, such as urban expansion, deforestation, and meteorological disasters. The results emphasize the importance of ecological projects for the restoration of vegetated ecosystems and ecological construction in Shaoguan. [ABSTRACT FROM AUTHOR]