Intensive Human Activities Research Articles

Grassland productivity increase was dominated by climate in Qinghai-Tibet Plateau from 1982 to 2020

Grassland areas occupy 60% of the Qinghai-Tibetan Plateau (QTP) and play a critical role in enhancing the ecological barrier functions of the QTP. Grassland ecosystems, and net primary productivity (NPP) in general, have dramatically changed in time and space since the 1980s, with climate warming and the intensification of human activities. Current research widely believes that climate and human activities are the common driving factors of grassland ecosystem changes on the QTP. However, there is still controversy over their dominant driving factors and their contribution rates, especially during different research periods. Therefore, this study calculated the relative contributions of climate change, human activities (except LUCC) and LUCC to actual NPP (aNPP) changes during the two periods from 1982 to 2000 to 2001–2020. This study simulated three kinds of NPPs, that is, actual NPP, potential NPP, and human-appropriated NPP, using climate productivity, the light use efficiency model, and the residual method, respectively. Moreover, the study area was divided into two parts, and then the contributions of the three factors were calculated objectively. The results showed that (1) the actual NPP (aNPP) of the QTP increased dramatically from 1982 to 2000 but did not change obviously from 2001 to 2020. (2) Comprehensive evaluation showed that climate was the dominant factor for the aNPP net increase, and its contribution rate dramatically increased from 36.3% during 1982–2000 to 224.2% during 2001–2020. Human activities changed from a positive contribution (53.3%) to a negative contribution (−124.8%) to the aNPP net increase. The contribution rate of LUCC to the aNPP increase significantly decreased from 10.4% to 0.6%. Therefore, finer grassland restoration measures and government policies must be implemented to increase NPP against the background of favorable warm-wet climate conditions for increasing grassland NPP in the QTP. These results benefit the scientific management of grassland resources and ecological barrier building on the QTP.

Increased dominance of terrestrial component in dissolved organic matter in Chinese lakes

The source composition of chromophoric dissolved organic matter (CDOM) in lakes is closely related to regional environmental changes, human activities, and the carbon cycle. The spectral slope ratio (SR) is an important parameter of CDOM optical components, and combined with remote sensing technology, the source composition of CDOM can be tracked comprehensively and efficiently in large regions. Here, we proposed a CDOM source tracking remote sensing model (CDOM-SR) based on the hue angle (α) to assess the spatial pattern and long-term trend of the CDOM source composition in Chinese lakes (surface area ≥ 1 km2) from 1986 to 2021. Validation results show that the CDOM-SR model has a good SR estimation performance with a median absolute percentage difference, root mean square deviation, median ratio, and median deviation of 17.91 %, 0.23, 1.02, and 0.03, respectively. We found that the average SR of Chinese lakes presents an obvious spatial pattern of high in the west and low in the east due to the difference in human activity intensity and the natural geographical environment. Additionally, we found that the average SR of Chinese lakes from 1986 to 2021 decreased at a rate of - 0.06/10 years, of which 64.37 % of lakes decreased significantly, 15.42 % of lakes had no significant change, and only 20.20 % of lakes increased. The widespread decrease in the average SR indicates that the increasing human activity discharge of terrestrial organic matter has had an important impact on the source composition of the CDOM in Chinese lakes. Our results provide a new resource for remote sensing monitoring of CDOM sources and important insights into lake carbon cycling under the influence of ongoing human activities.

Sand fixation and human activities on the Qinghai-Tibet Plateau for ecological conservation and sustainable development

The sand fixation ecosystem services and human activities on the Qinghai–Tibet Plateau (QTP) play a crucial role in local sustainable development and ecosystem health, with significant implications for surrounding regions and the global ecological environment. We employed an improved integrated wind erosion modeling system (IWEMS) model for the QTP to simulate sand fixation quantities under the unique low temperature and low pressure conditions prevalent on the plateau. Using the human footprint index (HFI), the intensity of human activities on the plateau was quantified. Additionally, an econometric model was constructed to analyze the impacts of the natural factors, the HFI, and policy factors on the sand fixation capacity. The results revealed that the average sand fixation quantity was 1368.0 t/km2/a, with a standard deviation of 1725.4 t/km2/a, and the highest value during the study period occurred in 2003. The average value of the HFI for 2020 was 6.69 with a standard deviation of 6.61, and the HFI exhibited a continuous growth trend from 2000 to 2020. Despite this growth, the average human activity intensity remained at a low level, with over 50 % of the area having an index value of <4.84. Overall, a strong negative correlation was observed between the sand fixation ecological capacity and the HFI on the QTP. However, extensive regions exhibited high values or low values for both indicators. The sand fixation capacity on the QTP is influenced by both natural and human factors. In light of these findings, suggestions are made for optimizing protected area design, rational control of human activity scales, and targeted human activity aggregation within certain regions as part of ecological conservation strategies. This study has implications for assessing sand fixation ecological functions in high-altitude regions and enhancing sand fixation capacity within the region, providing valuable practical guidance.

Chipping in: functional morphology of the American beaver under range expansion

AbstractClimate warming combined with intensive human activities are modifying ecosystems globally, and the Arctic biota is shifting substantially faster than the global average, allowing many new species to expand their range poleward. One such species, is the American beaver (Castor canadensis), a highly specialized rodent capable of greatly modifying ecosystems by altering forest composition through selective foraging and by flooding the landscape through dam and channel building. As rodent cranial morphology is highly related to its functional requirements for foraging and feeding, the beaver provides an opportunity to evaluate the phenotypic response of species to changing environmental conditions. Here, we test the hypothesis that beaver skull morphology is optimized for its local environmental and habitat conditions across Canadian ecosystems. We found that temperature, precipitations, biomass, and local average tree hardness significantly affect the morphology of key masticatory functional traits of the skull, but not its size. Our results suggest that the beaver's phenotype is locally adapted to environmental conditions as a result of its selective foraging behavior. This work provides insight into the adaptive potential of newly established beaver populations in the sub‐Arctic to inform management strategies for this keystone species. More generally, our work emphasizes the need to consider traits other than body size in research seeking to better understand the response of species to current global change.

Modern pollen-vegetation coverage relationships and its application for Holocene vegetation reconstructions in the central Tianshan Mountains

The Tianshan Mountains are the largest mountain system in Central Asia and comprise islands of humidity within a widespread arid zone. In this study, we improve knowledge of the quantitative relationship between pollen and vegetation coverage in the region, to quantitatively reconstruct Holocene vegetation coverage. Specifically, we statistically analyzed 1058 modern pollen samples from the central Tianshan Mountains and neighbouring regions, utilizing redundancy analysis (RDA), and boosted regression trees (BRT), stepwise regression (Stepwise), the modern analogy technique (MAT), weighted average partial least squares (WA-PLS) and local weighted average (LWWA) methods, to construct a series of modern calibration sets between pollen and fractional vegetation cover (FVC). The results show that (1) FVC and modern pollen assemblages display a strong correlation (correlation coefficient of 0.66) and (2) BRT outperforms Stepwise, MAT, WA-PLS and LWWA under leave-one-out cross-validation, bootstrap, and spatial autocorrelation tests, making the BRT model the best choice. Applied to Holocene datasets, we infer that from 11.4 to 4.6 cal kyr BP, FVC changes were mainly influenced by natural climate changes. However, after 4.6 cal kyr BP, FVC changes were influenced by a combination of natural climate changes (with humidity playing a dominant role) and the intensity of human activities.

Humification levels of dissolved organic matter in the eastern plain lakes of China based on long-term satellite observations

Under the influence of intensive human activities and global climate change, the sources and compositions of dissolved organic matter (DOM) in the eastern plain lake (EPL) region in China have fluctuated sharply. It has been successfully proven that the humification index (HIX), which can be derived from three-dimensional excitation-emission matrix fluorescence spectroscopy, can be an effective proxy for the sources and compositions of DOM. Therefore, combined with remote sensing technology, the sources and compositions of DOM can be tracked on a large scale by associating the HIX with optically active components. Here, we proposed a novel HIX remote sensing retrieval (IRHIX) model suitable for Landsat series sensors based on the comprehensive analysis of the covariation mechanism between HIX and optically active components in different water types. The validation results showed that the model runs well on the independent validation dataset and the satellite-ground synchronous sampling dataset, with an uncertainty ranging from 30.85 % to 36.92 % (average ± standard deviation = 33.6 % ± 3.07 %). The image-derived HIX revealed substantial spatiotemporal variations in the sources and compositions of DOM in 474 lakes in the EPL during 1986–2021. Subsequently, we obtained three long-term change modes of the HIX trend, namely, significant decline, gentle change, and significant rise, accounting for 74.68 %, 17.09 %, and 8.23 % of the lake number, respectively. The driving factor analysis showed that human activities had the most extensive influence on the DOM humification level. In addition, we also found that the HIX increased slightly with increasing lake area (R2 = 0.07, P < 0.05) or significantly with decreasing trophic state (R2 = 0.83, P < 0.05). Our results provide a new exploration for the effective acquisition of long-term dynamic information about the sources and compositions of DOM in inland lakes and provide important support for lake water quality management and restoration.

Identification of bundles and driving factors of ecosystem services at multiple scales in the eastern China region

Intensive human activities have caused serious damage to the natural environment and threatened ecosystem services, while the relationships between ecosystem services at different spatial scales vary to some extent. Therefore, identifying different patterns, evolutionary trends, and influencing factors of ecosystem services at different scales is more helpful in providing scientific decision-making for sustainable ecosystem management. Taking eastern China as the research area, with the help of a Gaussian mixture model, redundancy analysis and geographically weighted regression models, the spatiotemporal pattern evolution of ecosystem services from multiple scale perspectives were conducted, and the interrelationships between ecosystem services and the driving factors were explored. It expanded the knowledge of ecosystem services, the relationships between ecosystem services, and how the socio-ecological drivers of ecosystems vary at different spatial scales, and enabled more precise manipulation of socio-ecological drivers through different driving models. The average value of ecosystem services in the southern region was 0.672, which was better than that in the northern region, which was 0.353. Ecosystem services were lower in regions with a wide distribution of arable land and high population density and economic development. The relationship between ecosystem services was more manifested as synergistic relationship. As the scale expanded, the synergies and trade-offs between most ESs were also stronger and the average increase was 18.42 %. Especially, the relationships between some services developed from synergistic relationships at small scales to trade-offs at the county level. From the perspective of ecosystem service bundle, the overall ecosystem environment of the research area has been greatly improved, with enhanced supply function and weakened vulnerability. The area of ecosystem provisioning bundles increased by an average of 10.31 % as the scale increased, while the ecosystem regulation bundle decreased by 7.33 %. By comparison, the non-spatially driven model had better accuracy at the scale of 1 km2 and 100 km2, while the spatially driven model had higher accuracy at the county scale. Besides, normalized difference vegetation index occupied an absolute dominant position, and the natural elements acted more at the micro-scale, while the socio-economic elements were more influential at the macro-scale. These results provided a basis for subsequent research on multi-scale ecosystem control and ecological compensation strategies, and showed that natural and social factors were scale-dependent, that it was necessary to study ecosystem services, and emphasized the importance of developing appropriate policies at particular scales.

Quantifying and assessing nitrogen sources and transport in a megacity water supply watershed: Insights for effective non-point source pollution management with mixSIAR and SWAT models

The expansion and intensification of human activities have resulted in excessive nitrogen (N) in rivers, causing worldwide concern. To effectively manage agricultural non-point source pollution and ensure a safe drinking water supply in watersheds, it is crucial to trace and quantify the primary sources and spatial distribution patterns of N. In response to the challenge of unclear sources and agricultural non-point source pollution, this study utilised the Bayesian isotope mixing model and Soil and Water Assessment Toolmodel to identify the dominant nitrate sources and transformation processes. These models were employed to quantify N retention by the mainstream and tributaries in the Bai River Basin, which directly impacts the safety of drinking water in Beijing. Total N (TN) concentrations in the Yunzhou Reservoir (4.22 ± 0.04 mg.L˗1) and Miyun Reservoir (2.88 ± 0.62 mg.L˗1) inlets in autumn and winter were V class (2 mg.L˗1) category as per GB 3838–2002 standards. This implies higher risks of eutrophication and algal blooms exceeding the standards at individual points and seasons in the Bai River. Fertilisers were the main nitrate source in the Bai River Basin, contributing 44.6% during the dry season and 62.9% during the wet season, suggesting that nitrate is more susceptible to leaching and runoff during rainy periods. Rainfall was not a major contributor, with only 3.2% and 2.9% originating from the Hebei and Beijing areas of the Bai River, respectively. Annually, the Bai River Basin exports loads of approximately 629.3 t.a˗1 of TN and 433.7 t.a˗1 of organic N (Org-N) from the Bai River Basin land to the river. The TN and Org-N loads at the final destination in the Miyun Reservoir were 521.3 t.a˗1 and 100.3 t.a˗1, respectively. Of the exported TN and Org-N, 17.16% and 76.87%, respectively, were retained in the river network. Consequently, N transformation occurred in the Bai River, with nitrification–denitrification being particularly dominant. Nitrification was more evident in the nitrate-enriched river.

Spatial–Temporal Evolution and Correlation Analysis of Human Activity Intensity and Resource Carrying Capacity in the Region around Poyang Lake, China, from 2010 to 2020

Spatial–Temporal Evolution and Correlation Analysis of Human Activity Intensity and Resource Carrying Capacity in the Region around Poyang Lake, China, from 2010 to 2020

Analysis of Temporal and Spatial Dynamics of Ecosystem Services and Trade-Offs/Synergies during Urbanization in the Loess Plateau, China

As a typical ecological fragile zone and an area with a high intensity of human activities, the Loess Plateau (LP) of China has significantly altered its ecosystem and the corresponding services under the influence of urbanization processes. However, most existing studies focus on the spatial and temporal changes of ecosystem services (ESs) and their interrelationships under the influence of ecological restoration works in the LP, leaving limited research on the impacts of urbanization on ESs. Therefore, this study constructed a research framework for exploring the spatio-temporal dynamics and interactions of ESs under the influence of urbanization based on time series data from 2000 to 2020. The results showed that: (1) based on the comprehensive urbanization level (CUL), developed and developing areas accounted for 5.63% of the total area; (2) for the whole LP, all ESs except Habitat Quality (HQ) showed an increased trend. HQ showed a trade-off with the other services, while there was a clear synergy between the other three types of services; (3) in terms of processes of urbanization, Carbon Sequestration, Water Yield and HQ gradually decreased with increased levels of urbanization, and Soil Conservation increased the least in developing areas. The trade-off between HQ and the other three services decreased with increasing urbanization, while the synergy between the other three services strengthened as urbanization deepened. These findings suggest that urbanization significantly impacts ESs. It is necessary to implement appropriate measures (e.g., sponge city construction, urban green space, etc.) to address the impacts of urbanization on ESs.

Spatiotemporal Changes of Terrestrial Carbon Storage in Rapidly Urbanizing Areas and Their Influencing Factors: A Case Study of Wuhan, China

Terrestrial carbon storage plays a vital role in limiting global climate change and achieving regional carbon neutrality. However, intensive human activities and rapid urbanization have led to a rapid decline in carbon storage. Understanding what causes carbon storage to decline and how this happens is important for the scientific regulation of urbanization and safeguarding of urban ecological security. This study takes Wuhan as an example and analyzes the quantity, structure, and spatial patterns of urban land-use changes in the context of human activities and natural conditions, and applies correlation methods to identify general relationships between influencing factors and carbon storage. The results of the study are as follows: over the 30-year period studied, the area devoted to construction land increased by 757 km2 and the carbon storage decreased by 7.68 × 106 t. Outside Wuhan’s Third Ring Road, there was a significant increase in the carbon storage, but in the areas where construction increased, there was a reduction in carbon storage. Carbon storage in the remote suburbs was significantly higher than in the city center, and the distribution pattern was characterized by significant spatial heterogeneity. Our analysis revealed that human economic and social activities have affected Wuhan’s ecosystem carbon storage to a significant extent. Policymakers should focus on industrial optimization, strictly control the red line of ecological protection, and ultimately achieve high-quality urban development.

Identification of Ecological Restoration Priority Areas Integrating Human Activity Intensity and Multi-Criteria Decision Analysis

Restoration action is critical to ensure a safe environment for humans. Reasonable planning is essential to optimize the efficiency of ecological restoration inputs and outputs when implementing restoration measures. In this study, a method that combines human activity intensity assessment and multi-criteria decision analysis to determine ecological restoration priority (ERP) areas was developed to identify priority and feasible areas for ecological restoration in Shaanxi Province in 2020. The results showed that the total area involved in restoration feasibility assessment in Shaanxi is 10.89 × 104 km2. Among them, the percentage of regions with low feasibility (less than 0.2) is 68.86%, mainly located in Qinling area. High feasibility areas (more than 0.6) accounted for 2.47%, mainly located in the Loess Plateau area of northern Shaanxi. The spatial distribution of the human activity intensity is concentrated in urban areas and extended with the distribution of roads. In total, 10.69% of the regions showed high and very high intensity of human activity, including the Guanzhong urban agglomeration region. This study identified 6078 km2 and 671 km2 of medium and high ecological restoration priority areas, which are more concentrated in the north of the study area. The need for ecological restoration work is even more urgent in northern Shaanxi. In general, the framework in this study has spatially located the priority and feasible areas for restoration, and may provide a useful reference for landscape-scale spatial conservation planning.

How Does Human Activity Shape the Largest Estuarine Bay of the Pearl River Estuary, South China (1964–2019)

The morphological changes in an estuarine bay are affected by fluvial and oceanic dynamics, as well as human activities. Human activity has increased considerably in recent years, especially in Lingding Bay of the Pearl River Estuary. Based on mass measured bathymetric data and remote sensing images, morphological changes in Lingding Bay were examined and its long-term morphological evolution from 1964 to 2019 was studied using GIS method and EOF methods. The water area of Lingding Bay gradually decreased through this period due to shore reclamation and the evolutionary characteristics of the underwater topography were different before and after 2007 due to changes in the intensity of human activities. From 1964 to 2007, the water depth and volume of Lingding Bay decreased slightly and the bay experienced a slow silting process with the geomorphic pattern of “three shoals and two troughs” under low-intensity human activity. From 2007 to present, high-intensity sand-dredging activities in the bay have led to considerable deepening and a significant increase in water volume in the East Trough and Middle Shoal areas. The amount of sediment loss caused by the sand-dredging activities after 2007 far exceeded the amount of sediment deposition over the past four decades prior to 2007. Therefore, even if the sand-dredging activities had been banned, the eroded parts of Lingding Bay (i.e., East Trough and Middle Shoal) may not recover in a short time due to the small sediment load from the Pearl River. These recent morphological changes in Lingding Bay may bring about challenges for estuary regulation, disaster control, environmental protection, and the operational safety of the nearby ports and channels. Consequently, the subsequent evolution of the bay requires further research. This will enrich the scientific work for estuarine and coastal research and be conducive to revealing the interaction mechanisms between humans and nature, guiding sustainable development, estuarine disaster control, and promoting interdisciplinary innovation in estuarine research.

Evaluation of mangrove restoration effectiveness using remote sensing indices - a case study in Guangxi Shankou Mangrove National Natural Reserve, China

As one of the most productive marine ecosystems in the coastal wetlands, mangrove forests have been severely threatened by intensive human activities. Many countries and regions have carried out mangrove restoration projects. The evaluation of mangrove restoration effectiveness is of great significance for scientific decision-making for restoration engineering and wetland management. In this study, we presented a remote-sensing-based Mangrove Restoration Effectiveness Index (MREI) to evaluate mangrove restoration effectiveness. We took the Guangxi Shankou Mangrove National Natural Reserve (GSMNNR) in China, a UNESCO Biosphere Reserve, as our study area, where four phases of afforestation were implemented during 1990-2022. The MREI was developed based on Landsat-series images by considering the change in mangrove area and the Normalized Difference Vegetation Index (NDVI) from the start year to the end year of each afforestation phase (evaluation period). We further evaluated the Persistence of Restoration Effectiveness (PRE) based on the MREI change trajectory during the whole evaluation period, and the Process-based Restoration Effectiveness Index (PREI) was developed to evaluate the restoration effectiveness at village scale. The results showed that MREI can effectively represent the trajectory of mangrove restoration and showed consistent pattern with high-spatial-resolution imagery. From 1990 to 2022, the mangrove forest area increased from 235.26 ha in 1990 to 873.27 ha in 2022, and 84.59% of the mangrove forest was converted from tidal flats in the reserve. The average value of MREI in the five evaluation phases were 0.48, 0.24, 0.29, 0.17, and 0.72, respectively. The dynamic change of MREI showed that 5.24% of the zones had poor PRE, 44.17% of the zones had excellent PRE. From the perspective of spatial distribution, the Zones with PREI values ranging from high to low were follows: Zone A, E, J, G, C, H, I (D), F, B. Overall, the high value zones of PREI were mainly distributed in the central of the Dandou Sea and the northern part of the Yingluo Bay. The low value zones were distributed in the northwest of the Dandou Sea. We expect the MREI and PREI have great potential to be applied to other regions to evaluate mangrove restoration effectiveness.

Identification of key brittleness factors and multi-scenario analysis of the water-energy-food-ecology nexus vulnerability based on NRS-BN

Water, energy and food are the basic resources on which human beings depend for survival. With the intensification of human activities, the demand for resources represented by water, energy and food continues to increase, resulting in increasing pressure on the ecological environment, and the vulnerability of water, energy, food and ecosystem becomes increasingly prominent. Identifying the critical vulnerability factors of the water-energy-food-ecology nexus and formulating targeted management measures have become the key to achieving sustainable development. This paper innovatively proposes to study the water-energy-food-ecology nexus from the perspective of vulnerability for the first time, in which the vulnerability evaluation index system of the water-energy-food-ecology nexus is firstly constructed based on the VSD framework, and the attribute reduction is carried out using neighborhood rough sets. Then, a Bayesian network model is built and parameter learning is performed by combining machine learning and expert experience. Finally, different scenarios are set up to identify the key factors that hinder the vulnerability reduction of the water-energy-food-ecology nexus and obtain the vulnerability probability of the nexus under different scenarios using forward and backward inference and sensitivity analysis of Bayesian networks, overcoming the drawback that many prediction models cannot achieve diagnostic inference. The results show that: 1) from 2008 to 2019, the overall vulnerability of the water-energy-food-ecology nexus in the Yangtze River Economic Belt is low. 2) The key factors at the indicator level that hinder the vulnerability reduction of the water-energy-food-ecology nexus mainly include the storage capacity of water conservancy projects, wastewater discharge per 10,000-yuan GDP, and water consumption per 10,000-yuan GDP, and the subsystem level is water, food, energy and ecology system, in that order. 3) The reduction in vulnerability within an individual subsystem can have a beneficial impact on reducing vulnerability within the water-energy-food-ecology nexus. However, this reduction may also lead to an increase in vulnerability within other subsystems. Therefore, in the process of developing water, energy, food, and ecology system, high priority should be given to the coordinated development of all four.

Distinct dynamics in mountain watersheds: Exploring mercury and microplastic pollution—Unraveling the influence of atmospheric deposition, human activities, and hydrology

The intensification of human activities all around the globe has led to the spread of micropollutants in high-mountain freshwater environments. We therefore aimed to assess the geospatial distribution and determine the potential sources of (total-) mercury (THg) and microplastics (MPs) in mountain freshwater ecosystems. To do so, we analyzed THg and MP concentrations in brown trout, biofilm, and sediments from lotic and lentic ecosystems in the Pyrenees – all subjected to different types of human pressure. Additionally, we assessed the potential impacts of these pollutants on fish, and explored the bioindication capacity of brown trout (Salmo trutta fario) and biofilm regarding THg and MP pollution. For the first time, we measured concentrations of MPs trapped in the matrix of freshwater biofilm. Our results suggest that THg in the Pyrenees might be explained by both legacy (regional) and distant sources, in combination with environmental characteristics such as the presence of peatlands or streamwater physicochemistry, while MPs in fish are linked to recent local pollution sources such as single-use plastics. In contrast, MPs in biofilm matrix and sediments indicate a combination of distant (i.e., atmospheric deposition) and recent local pollution sources. Moreover, hydrodynamics and plastic density likely control MP distribution in rivers. Based on Fulton's condition factor, we also found that higher THg concentrations caused a negative impact on fish health (K < 1), while no impact of MPs could be seen. Therefore, we suggest that brown trout and biofilm can serve as bioindicators of atmospheric deposition of THg in high-altitude lakes and that biofilm is a reliable bioindicator to assess MP pollution in remote environments. Brown trout may also act as a bioindicator of MP pollution, but only efficiently in more polluted areas.

Study on the water-carbon coupling coordination function on the eastern edge of the Qinghai-Tibet plateau

The Qilian Mountains on the eastern edge of the Tibetan Plateau are an important ecological security barrier in northwestern China and an extremely critical water-carbon conservation area. The water and carbon cycles are closely linked, and the water-carbon coupling process has become further complicated under global climate change and through the intensification of human activities. A better understanding of the impacts and potential mechanisms of water-carbon interactions is the key to improving the efficiency of water-carbon resource utilization. To rationalize the relationship between water and carbon, we used data from statistical almanacs, land use, DEM and various climatic elements to estimate the water-carbon nutrition in the Qilian Mountains from 2000 to 2020 based on the InVEST model and the Coupled Coordination Degree Model (CCDM) and to explore the coupling mechanism of water-carbon, spatial-temporal dynamics, and the influencing factors. The results showed that: 1). the average annual water and carbon storage in the Qilian Mountains are 63.21 × 108 m3 and 77.82 × 107 t, respectively, showing a spatial distribution pattern of high in the northeast and low in the southwest. The inter-annual changes in water (y=-0.451x+968.920) and carbon (y = 0.082x-87.808) showed different trends. 2). The annual average of the water-carbon coupling coordination degree of 0.280 in the Qilian Mountains was low in general, and the trends declined over time from 0.273 in 2000 to 0.264 in 2020. However, the spatial distribution was relatively clustered, and the spatial correlation improved from 0.69 in 2000 to 0.74 in 2020. 3). Precipitation, potential evapotranspiration and temperature were important elements driving water-carbon coupling. Among them, precipitation was significantly positively correlated with water-carbon coupling (r = 0.88), and potential evapotranspiration (r=-0.56) and temperature (r=-0.39) showed significant negative correlations with water-carbon coupling. This study can provide information for management and decision-making in carbon sequestration, water resource utilization, ecological protection and climate change, and promote the study of the spatial and temporal coupling functions of water and carbon with in the Qilian Mountains. Meanwhile, this study can provide a reference for the environmental management and protection of the Qilian Mountain ecosystem.

Atmospheric deposition is an important pathway for inputting microplastics: Insight into the spatiotemporal distribution and deposition flux in a mega city

Microplastics (MPs) refer to plastic particles with a size less than 5 mm, which attracted widespread attention as an emerging pollutant. The monitoring of atmospheric microplastics (AMPs) in a megacity was carried out to study the characteristics and spatiotemporal distribution of AMPs, explore the sources and estimate the deposition flux. The results showed that the annual average abundance of AMPs in Wuhan was 82.85 ± 57.66 n·m−2·day−1. The spatiotemporal distribution characteristics of AMPs show that spring was the highest season, followed by autumn, winter, and summer; the city center was higher than the suburbs. Fiber was the main type of AMPs in Wuhan, followed by fragment, film and pellet. The proportion of AMPs were mainly small (<0.5 mm) and medium (0.5–1.0 mm). Transparent and white were the main colors of AMPs, followed by red, brown. A total of 10 types polymers were detected, polyethylene terephthalate (PET) was dominant. There are positive correlations between AMPs and SO2, NO2 in the atmosphere, indicating that they might be influenced by intense human activity. The polycyclic aromatic hydrocarbons (PAHs) and AMPs in spring showed an extremely significant positive correlation (p < 0.05). AMPs might mainly originate from the wear and tear shedding of textiles, the aging of agricultural films and plastic waste based on their polymer types and main uses. The potential geographical sources of AMPs were mainly the surrounding cities. The annual deposition flux of AMPs was about 308 tons if there were no remove processes, which highlighted the importance of atmospheric transport and deposition of MPs. The analysis of the abundance, morphological characteristics and sources of AMPs can provide data support and reference for mega-cities with high global population activities, or cities in global mid-latitude regions.

Centennial Analysis of Human Activity Intensity and Associated Historical Events in the Heilongjiang River Sino-Russo Watershed

Centennial Analysis of Human Activity Intensity and Associated Historical Events in the Heilongjiang River Sino-Russo Watershed

A hypergraph-based hybrid graph convolutional network for intracity human activity intensity prediction and geographic relationship interpretation

Human activity intensity prediction, i.e., estimating the dynamic population distribution, is crucial to many location-based applications, particularly intelligent transportation systems and urban planning. Geographical artificial intelligence (GeoAI) is an emerging field that has contributed many new modeling approaches for spatiotemporal phenomena, especially spatiotemporal graph neural networks (ST-GNNs). However, there are two challenges to the prediction of human activity intensity. On the one hand, accurate predictions require modeling not only pairwise spatial relationships, e.g., distance and spatial flow but also complex high-order relationships, such as clusters and groups. On the other hand, it is not appropriate to incorporate prior knowledge on the spatial structure of data with subjective assumptions using graphs with predefined topologies or weights. To mitigate such challenges, a novel deep learning-based model was proposed, namely, the Hypergraph-based Hybrid Graph Convolutional Network (HyGCN). In our study, high-order relationships are modeled by hypergraph convolutions, and pairwise relationships are captured in graph convolutions. A spatial fusion layer is added to fuse the pairwise and high-order relationships. Then, adaptive graph and hypergraph generation methods are proposed to interpret edge weights and understand the learned geographic relationships in accordance with principles. After systematic experiments on large-scale mobility data, our results demonstrate that HyGCN outperforms state-of-the-art models. The learned geospatial knowledge can be disentangled and explained from the perspectives of geographic principles. This study offers new insights for not only revisiting geographic laws in GeoAI but also utilizing spatiotemporal knowledge in deep learning models.