Intensive Human Activities Research Articles

A significant loop of lake sedimentation state links catchment eco‐surroundings and lake biogenic regime shifts

AbstractAs an important destination for upstream materials and element accumulation, lake sediments hold a multitude of contextual information about climatic changes and anthropogenic disturbances. However, understanding the lake sedimentation state to link catchment pressures and biogenic regime shifts remains challenging. To address this, research was conducted on the lake sedimentation state, including the dynamics, catchment drivers, effects on biogenic regimes, and responses to typical historical events using nine sediment cores from Dongting Lake, China, a typical global priority ecoregion. Three transitions of lake sedimentation state were distinguished over the century (1937, 1968, and 1993), whereby hydrologic dynamics and land‐use changes in the watershed were the direct drivers with relative contributions of 16.30% and 14.56%, respectively. Lake sedimentation state and organic matter inputs not only preceded sediment biogenic elements at the shift time but also exhibited nonlinear trigger effects on biogenic element contents (R2 = 0.47, p < 0.01), which promoted an increase in sediment biogenic element burial rates. Rate of change analysis indicated that intensive human activities altered the relationship between the sedimentation state and biogenic regime shift, thus revealing the response to anthropogenic events in the catchment. Pathways quantified by the partial least squares path model established the link between watershed attributes and lake biogenic properties via the lake sedimentation state. Our findings revealed a cascading linkage among catchment eco‐surroundings, lake sedimentation states, and biogenic regime shifts. The research further provided insights into driver‐response relationships in lake‐catchment systems.

Changes and response mechanisms of leaf area index and evapotranspiration in the typical natural landscapes of the Loess Plateau in northern Shaanxi of China under the human intervention

Exploring the relationship between human activity, vegetation leaf area index (LAI), and land surface evapotranspiration (ET) on the Loess Plateau in northern Shaanxi is crucial for maintaining regional ecosystem functions and optimally allocating water resources. This study investigated the driving mechanism of LAI on ET under the intervention of the human activity intensity (HAIS) by analyzing seasonal and interannual variability characteristics and processes using remote sensing data of land use, LAI, and ET in typical natural landscapes (forest, grassland, and desert) in northern Shaanxi from 2000 to 2020. The primary findings were: (1) In the previous two decades, grassland HAIS was the largest, mainly distributed in central districts and counties, and gradually decreasing. The LAI and ET were ranked as follows: forest > grassland > desert, with an interannually increasing tendency, and the yearly mean LAI and ET of forest reached 2.18 and 16.47 mm, respectively. (2) The LAI and ET of the three typical natural landscapes changed substantially during the growing season (April-October) of vegetation, which increased and then decreased, reaching a maximum in June-August. The LAI and ET displayed noticeable numerical clustering among the months, with higher and concentrated values in June-August and lower values in April, May, and October. (3) Forest and grassland HAIS negatively affected LAI, and detrimentally regulated ET by primarily influencing LAI4-LAI7 (LAI from April to July). Desert HAIS had a significant positive link with the LAI and primarily regulated ET by positively influencing LAI6-LAI10. Compared to forest and grassland, the coregulatory effect of LAI on ET in the desert lagged relatively in the month. Our study recommends accelerating the conversion of the desert to forest and grassland on the Loess Plateau in northern Shaanxi for stabilizing landscape ecosystem function and the reciprocal feedback between vegetation and water resources faster.

Tide drives nutrients variation and exchange flux in the semi-enclosed Shuidong Bay coastal water in winter, South China Sea

Nutrients play a key role in coastal ecosystems. Coastal tide is an important driver of the daily nutrient variability in semi-enclosed bay under the intensive human activities and climate change. However, the extent of tidal effects on the nutrients variation and exchange flux in the semi-enclosed bay in winter is still scarcely. In this study, seawater samples were collected by synchronous continuous observation during winter in 2021, to investigate tide drives nutrients variation and exchange flux between Shuidong Bay (SDB) and South China Sea (SCS). The results showed most nutrients were significantly impacted by the tidal variation in the SDB with the semi-diurnal cycle. Coastal flood water can increase seawater exchange capacity due to strong dilution influenced by the outer SCS water, resulting mitigate adverse effects of nutrient enrichment in the semi-enclosed bay. In addition, the concentrations of total dissolved nitrogen (TDN), total dissolved phosphorus (TDP), and silicate (DSi) were 146.75 μmol/L, 1.06 μmol/L, and 6.15 μmol/L. Besides, there was a relative excess of nitrogen, phosphorus and silicate were limiting factors in the SDB, and nutrients significantly impacted the Chlorophyll-a in coastal water. Moreover, both TDP and DSi were transported from the SDB to the SCS with a net exchange flux of 0.23 t and 1.99 t, while TDN was transported from the SCS to the SDB with a net exchange flux of 0.14 t, resulting in nutrients ratio increase in the SDB coastal water. Statistical analysis identified the tide induced hydrological variations and terrestrial inputs dominated nutrient dynamics in the SDB coastal water. This study provided a new understanding of the variation and transport of nutrients driven by tide in the SDB, which is implications for understanding the biogeochemistry of nutrients in daily scale and water quality management in the semi-enclosed bay in future.

Climate-vegetation-erosion interactions revealed by the sediments of Huguangyan Maar Lake, southern China

Soil erosion is a serious environmental problem in the red soil region of southern China, yet little is known about the factors responsible and their specific effects on long-term soil erosion dynamics in this region. We addressed this issue via a study of the sediments of Huguangyan Maar Lake (HML), a crater lake in southern China. Our results confirm that the sediments in HML are mainly derived from the erosional input of weathering products of wall rocks, via catchment runoff. Having established the provenance of the HML sediments, the sediment accumulation rate, mass accumulation rate, and geochemical element fluxes were used to reconstruct soil erosion processes in the HML catchment over the past ∼1400 years. The potential drivers of soil erosion were explored, and regional comparisons were made to evaluate the representativeness of this study. The results show that: 1) Higher precipitation before ∼830 CE, coupled with a lower level of human activity, promoted increased vegetation coverage which reduced the rate of soil erosion. 2) Lower precipitation during 830 CE–1390 CE reduced the rate of soil loss. 3) Abundant precipitation was the main cause of the more intense soil erosion during 1390 CE–1878 CE, which may have been exacerbated by the reduced vegetation cover caused by intensive human activity. 4) During 1878 CE–2019 CE, the vegetation cover gradually recovered under the combined effects of vegetation restoration and higher precipitation, which reduced the rate of soil erosion within the HML catchment. Compared to the Chinese Loess Plateau, the erosion level in the HML catchment was relatively low during the period of intensive human activities. Overall, our results contribute to an improving understanding of the driving mechanisms of soil erosion, and they provide a guide for soil conservation measures in southern China.

Injuries and skin condition of Indo‐Pacific humpback dolphins (Sousa chinensis) in the northern South China Sea

AbstractIndo‐Pacific humpback dolphins (Sousa chinensis) inhabiting the Chinese coastline of the northern South China Sea are subject to intense human activity. To investigate potential impacts to dolphins, photographs taken from 2010 to 2021 in five different locations were analyzed. Among individual dolphins (N = 1,159), 10.6% presented human‐induced injuries. Adults were more frequently injured than young dolphins, and individuals from around Jiangmen, Hainan, and Sanniang Bay presented the highest injury prevalence. More research should be conducted in areas that have been subject to less research, such as Jiangmen and Hainan, and the dolphin watching activities occurring in Sanniang Bay should be monitored and regulated. Forty‐seven percent of dolphins presented skin conditions, with orange patches being the most frequent (41.5%). Orange patches and hyper‐pigmented pink spots were significantly less prevalent in summer and fall than in winter and spring. Orange patches were less frequent in females than in males, as well as with calves relative to older age classes. Seasonal patterns may be linked to water temperatures, while demographic patterns may be associated with immune defenses. These findings allow for a better understanding of the potential impact of human activities on Indo‐Pacific humpback dolphins and should inform further conservation measures.

Spatiotemporal Runoff Analysis and Associated Influencing Factors in Chitral Basin, Pakistan

Global warming has accelerated climate and weather changes, impacting the regional water cycle. This study assesses the temporal trends of seasonal and annual runoff in the Chitral River Basin (CRB) and its responses to regional climatic factors (i.e., temperature, precipitation, and Normalized Difference Vegetation Index (NDVI)) and oceanic indices at large scales (i.e., El Nino Southern Oscillation (ENSO), Indian Ocean Dipole (IOD), and Pacific Decadal Oscillation (PDO)). The non-parametric Mann–Kendall (MK) test, the Sequential Mann–Kendall test (SQMK) and Sen Slope (SS) is used to evaluate trends and magnitude. In contrast, wavelet analysis is used to assess the coherence. In general, precipitation increases in winter, summer and autumn, whereas it decreases in spring. The temperature increased significantly in winter and spring, while a significant increase in seasonal and annual runoff was evident. Annual NDVI increased, whereas the Normalized Difference Water Index (NDWI) and the Normalized Difference Snow Index (NDSI) decreased. Generally, runoff has significant inter-annual coherences with regional environmental factors, and a significant coherence with NDVI. Monthly runoff has a positive coherence with temperature and NDVI, whereas it has a negative correlation with precipitation, NDWI, and NDSI. In general, ENSO, IOD and PDO show a positive correlation with runoff. The MWC findings indicate that annual runoff prevailed interannual signals with local environmental factors and with the Pacific Ocean, whereas interannual and interdecadal coherences are obvious with the Atlantic Ocean. The results have significant implications for decision-makers seeking to enhance water resource planning, disaster prevention, and mitigation, especially in global warming and the intensification of human activities that influence hydroclimatic changes at high altitudes.

Determination of the Stability of a High and Steep Highway Slope in a Basalt Area Based on Iron Staining Anomalies

In recent years, geological disasters have frequently occurred on basarlt highway slopes. Studying the stability of highway slopes in this type of area is of great significance for traffic safety. However, due to the high cost and low efficiency of traditional monitoring and experimental methods for slope engineering, these methods are not conducive to the quick and comprehensive identification of regional slope stability. Due to the high iron content of basalt, iron staining anomalies in the ore prospecting field are reinterpreted from an engineering perspective in this study. Taking the S3K section of a highway in Changbai County, China, as an example, Landsat8 remote sensing (RS) images from 2014, 2016, 2018, 2020, and 2021 are selected, and principal component analysis is used to extract iron staining anomalies in the region. Combined with field investigation and evidence collection, the corresponding rock mass fragmentation is distinguished via iron staining anomalies. Then, according to previous research results, eight indexes including annual rainfall, slope, topographic relief, surface roughness, vegetation index, leaf area index (LAI), root depth of vegetation, and human activity intensity are selected for investigation. The artificial neural network–cellular automata (ANN-CA) model is established, and the rock fragmentation classification data obtained based on iron staining anomalies are used to simulate the area. Next, the calculation formula of slope stability is determined based on the simulation results, and the stability of a high and steep slope in the area is calculated and analyzed. Finally, a comparison with an actual field investigation shows that the effect of the proposed method is good. The research findings reveal that it is feasible to judge the stability of a high and steep slope in a basalt area via the use of iron staining anomalies as an indicator. The findings are tantamount to expanding the application scope of RS in practical engineering.

Trends of Grassland Resilience under Climate Change and Human Activities on the Mongolian Plateau

Grassland resilience is influenced by climate change and human activities. However, little is known about how grassland resilience has changed, driven by climate change and human activities, on the Mongolian Plateau. We calculated grassland resilience on the Mongolian Plateau from 2000 to 2021 using the kernel normalized difference vegetation index (kNDVI), quantified the trends of grassland resilience using a newly proposed “critical slowing down” indicator with a machine learning algorithm, and compared the driving forces for these changes between Inner Mongolia and Mongolia. The findings of this study demonstrate that heightened levels of precipitation and reduced temperature contribute to the enhanced resilience of grassland ecosystems on the Mongolian Plateau. Conversely, the presence of grazing activities exhibits a detrimental effect on such resilience. In semi-arid regions, approximately 43% of grassland areas are undergoing a discernible decline in resilience. This decline is particularly pronounced in regions characterized by heightened levels of grazing intensity. In addition, resilience declined in 54% of areas with population growth compared with 32% in areas with population decline. Inner Mongolia, with its higher intensity of human activities, has a more serious decline in ecological resilience than Mongolia, indicating that further ecological restoration measures are needed.

Ecological risk characteristics of sediment-bound heavy metals in large shallow lakes for aquatic organisms: The case of Taihu Lake, China

Heavy metal contamination in the surface sediments of large shallow lakes in China is becoming increasingly serious. However, more attention has been paid to the human health risk of heavy metals in the past, while little consideration has been given to aquatic organisms. Taking Taihu Lake as an example, we explored the spatial and temporal heterogeneity of the potential ecological risks of seven heavy metals (Cd, As, Cu, Pb, Cr, Ni, and Zn) to species at different taxonomic scales using an improved species sensitivity distribution (SSD) method. The results showed that all six heavy metals, except Cr, were exceeded to some extent compared to background levels, with Cd being the most severe exceedance. Based on the hazardous concentration for 5% of the species (HC5), Cd had the lowest HC5 value, implying the highest ecological risk of toxicity. Ni and Pb had the highest HC5 values and the lowest risk. Cu, Cr, As and Zn were at a relatively moderate levels. For the different groups of aquatic organisms, the ecological risk of most heavy metals was generally lower for vertebrates than for the whole species. The risk for invertebrates and algae was higher than that for all species. Zn and Cu had the highest potentially affected fractions (PAFs) for all classification cases, with mean PAFs of 30.25% and 47.2%, respectively. Spatially, the high ecological risk of sediment heavy metals was significantly related to the spatial characteristics of the type and intensity of human activities in the catchment. Administratively, the environmental quality standards for freshwater sediments proposed by America and Canada are insufficient to protected against the ecological risks of heavy metals in Taihu Lake. In the absence of such standards, China urgently needs to establish an approptiate system of environmental quality standards for heavy metals in lake sediments.

Source identification of trace elements in groundwater combining APCS-MLR with geographical detector

Accurately identifying the sources of trace elements in groundwater is difficult, especially in the areas with intensive human activities. This study proposes a framework to identify and quantify the contributions of potential sources of trace elements in groundwater. Health risk assessment is first conducted to identify the trace elements with the highest threats to groundwater quality, and then the geographical detector is used to qualitatively investigate the potential sources and processes dominating the pollution from identified trace elements, and the absolute principal component scores-multivariate linear regression (APCS-MLR) is used to quantify the contributions of different sources to the accumulation of trace elements. The proposed approach was applied to China’s Loess Plateau, a typical water-limited area with rapid urbanization and intensive agricultural activities, after conducting two groundwater sampling campaigns in a flood and a dry season. The trace element concentrations in groundwater exhibited significant spatial and seasonal differences. Health risk assessment revealed that Cr and As through oral ingestion were responsible for non-carcinogenic and carcinogenic risks in different seasons. Land use was the primary factor influencing the spatial heterogeneity of Cr in the flood season, while elevation and distance from city were dominant factors in the dry season. Normalized difference vegetation index (NDVI) and distance from city contributed the most to As change in the flood season, but NDVI was the major contributor in the dry season. The average contributions of potential pollution sources to trace elements in groundwater were in the order of natural source (35%) > geogenic process (17%) > industrial source (13%) in the flood season, but mixed sources (47%) > agricultural activities (18%) in the dry season. Distinguished from the traditional source apportionment methods, the newly proposed approach is not limited to identification of pollutant sources, but also can obtain the exact contributions of different sources. The findings provide useful information for groundwater management in the Loess Plateau.

Ensemble learning framework for landslide susceptibility mapping: Different basic classifier and ensemble strategy

The application of ensemble learning models has been continuously improved in recent landslide susceptibility research, but most studies have no unified ensemble framework. Moreover, few papers have discussed the applicability of the ensemble learning model in landslide susceptibility mapping at the township level. This study aims at defining a robust ensemble framework that can become the benchmark method for future research dealing with the comparison of different ensemble models. For this purpose, the present work focuses on three different basic classifiers: decision tree (DT), support vector machine (SVM), and multi-layer perceptron neural network model (MLPNN) and two homogeneous ensemble models such as random forest (RF) and extreme gradient boosting (XGBoost). The hierarchical construction of deep ensemble relied on two leading ensemble technologies (i.e., homogeneous/heterogeneous model ensemble and bagging, boosting, stacking ensemble strategy) to provide a more accurate and effective spatial probability of landslide occurrence. The selected study area is Dazhou town, located in the Jurassic red-strata area in the Three Gorges Reservoir Area of China, which is a strategic economic area currently characterized by widespread landslide risk. Based on a long-term field investigation, the inventory counting thirty-three slow-moving landslide polygons was drawn. The results show that the ensemble models do not necessarily perform better; for instance, the Bagging based DT-SVM-MLPNN-XGBoost model performed worse than the single XGBoost model. Amongst the eleven tested models, the Stacking based RF-XGBoost model, which is a homogeneous model based on bagging, boosting, and stacking ensemble, showed the highest capability of predicting the landslide-affected areas. Besides, the factor behaviors of DT, SVM, MLPNN, RF and XGBoost models reflected the characteristics of slow-moving landslides in the Three Gorges reservoir area, wherein unfavorable lithological conditions and intense human engineering activities (i.e., reservoir water level fluctuation, residential area construction, and farmland development) are proven to be the key triggers. The presented approach could be used for landslide spatial occurrence prediction in similar regions and other fields.

Body condition and corticosterone stress response, as markers to investigate effects of human activities on Adélie penguins (Pygoscelis adeliae)

IntroductionIn Antarctica, there is growing concern about the potential effect of anthropogenic activities (i.e., tourism, research) on wildlife, especially since human activities are developing at an unprecedented rate. Although guidelines exist to mitigate negative impacts, fundamental data are currently lacking to reliably assess impacts. Physiological tools, such as circulating corticosterone levels, appear promising to assess the potential impact of human disturbance on Antarctic vertebrates.MethodsIn this study, we compared the body condition, and the physiological sensitivity to stress (i.e., basal and stress-induced corticosterone level) of adult and chick Adélie penguins between a disturbed and an undisturbed area (i.e., 2 colonies located in the middle of a research station exposed to intense human activities and 2 colonies located on protected islands with minimal human disturbance).ResultsWe did not find any significant impact of human activities on body condition and corticosterone levels in adults (incubating adults, brooding adults). In chicks, there were significant inter-colony variations in stress-induced corticosterone levels. Specifically, the chicks from the disturbed colonies tended to have higher stress-induced corticosterone levels than the chicks from the protected areas although this difference between areas was not significant. In addition, and independently of human disturbance we also found significant differences in adult body condition, and chick corticosterone level between colonies.DiscussionOverall, our study suggests that this species is not dramatically impacted by human activities, at least when humans and penguins have cohabited for several decades. Our results support therefore the idea that this species is likely to be tolerant to human disturbance and this corroborates with the persistence of Adélie penguin colonies in the middle of the research station. However, our results also suggest that chicks might be more sensitive to human disturbance than adults and might therefore potentially suffer from human disturbance. Our study also suggests that specific individual and environmental variables outweigh the potential minor impact of human disturbance on these variables. Combining corticosterone with complementary stress-related physiological markers, such as heart rate, may strengthen further studies examining whether human disturbance may have subtle detrimental impacts on individuals.

Microbial community assembly responses to polycyclic aromatic hydrocarbon contamination across water and sediment habitats in the Pearl River Estuary

Along with rapid urbanization and intensive human activities, polycyclic aromatic hydrocarbon (PAH) pollution in the Pearl River Estuary (PRE) and its effects on the microbial community have attracted extensive attention. However, the potential and mechanism of microbial degradation of PAHs across water and sediment habitats remain obscure. Herein, the estuarine microbial community structure, function, assembly process and co-occurrence patterns impacted by PAHs were comprehensively analyzed using environmental DNA-based approaches. The contamination and distribution of PAHs were jointly affected by anthropogenic and natural factors. Some of the keystone taxa were identified as PAH-degrading bacteria (i.e., genera Defluviimonas, Mycobacterium, families 67–14, Rhodobacteraceae, Microbacteriaceae and order Gaiellales in water) or biomarkers (i.e., Gaiellales in sediment) that were significantly correlated with PAH levels. The proportion of deterministic process in the high PAH-polluted water (76%) was much higher than that in the low pollution area (7%), confirming the significant effect of PAHs on the microbial community assembly. In sediment, the communities with high phylogenetic diversity demonstrated a great extent of niche differentiation, exhibited a stronger response to environmental variables and were strongly influenced by deterministic processes (40%). Overall, deterministic and stochastic processes are closely related to the distribution and mass transfer of pollutants, and substantially affect the biological aggregation and interspecies interaction within communities in the habitats.

Spatio-temporal dynamics and sensitive distance of nighttime light environment in Pearl River Delta Protected Areas, China.

Protected areas (PAs) are important barriers to ensure the ecological security of territory. Light pollution is a threat to PAs, which is particularly obvious in the urban agglomeration environment. We used multi-source big data (satellite remote sensing light data, land cover types and points of interest) to quantitatively analyze the temporal and spatial dynamics of nighttime light in the PAs of the Pearl River Delta (PRD) urban agglomeration from 2000 to 2018, the correlation between the night light environment within the PAs and human activity intensity outside, as well as the sensitive distance of the PAs to artificial light interference. The results showed that the total value of nighttime light data of PAs in the PRD increased from 71107 nanoW·cm-2·sr-1 to 127682 nanoW·cm-2·sr-1 from 2000 to 2018, the mean value per pixel increased from 15.3 nanoW·cm-2·sr-1 to 23.7 nanoW·cm-2·sr-1, and the lighted ratio increased from 73.3% to 86.4%, indicating that the nighttime light environment of PAs in the region were facing cumulative deterioration risks and serious challenges. The nighttime light intensity of the PAs in the core area of the PRD was much higher than that in the peripheral areas such as Zhaoqing and Huizhou, whereas the expansion degree of the PAs in the peripheral areas was higher than that in the core area. The nighttime light environment inside the PAs was positively correlated with the intensity of human activities around it. The most sensitive distance of the PAs to the artificial light interference around it was 10 km, and the interference degree tended to be stable after 30 km. We proposed that 0-10 km area outside the boundary of the PAs should be the light control core zone and 10-20 km area as the control buffer zone.

Spatiotemporal trends in ecosystem carbon stock evolution and quantitative attribution in a karst watershed in southwest China

Karst ecosystems serve as a vital part of the Earth’s ecosystem and have a substantial influence on the worldwide carbon cycle. Revealing the features and driving factors of the spatiotemporal evolution of Carbon (C) stock in karst watersheds is critical for the in-depth exploration of the regional carbon cycle and carbon sources/sinks, as well as in regional ecological restoration. In this study, the Nanming River Basin, a representative karst basin in southwest China, was used as the subject region. Based upon data on land use change from 2000 to 2020, an Integrated Valuation of Ecosystem Services & Tradeoffs (InVEST) model was applied to calculate the C stock from 2000 to 2020 and identify the driving factors of the regional change of C stock using an optimal parameters-based geographical detector (OPGD) model. The findings indicate that: (1) the cumulative reduction of C stock in the basin from 2000 to 2020 was 3.16 × 105 t; the center of gravity of C stock increase has shifted to the southwest by 2434.16 m, and the center of gravity of the reduction has shifted to the southwest by 7260.53 m. (2) The transition of forest land into construction land had the highest contribution to the decrease of C stock (60.91%); the transition of cultivated land and grassland into forest land was conducive to a rise in the C stock, and these conversions contributed 45.93% and 35.00%, respectively, to the increase of C stock. (3) The normalized difference vegetation index (NDVI), population density, intensity of human activity, slope, and lithology all have annual average q-values greater than 10%, meaning they are the primary factors driving the spatial differentiation of C stock. The contribution of the NDVI ∩ slope direction to the regional heterogeneity of C stock was the largest among the interactive driving factors, with an explanatory power close to 30%. The interactive combinations of drivers all showed nonlinear enhancement or two-factor enhancement effects. To some extent, this study deepens the study of changes in C stock and related driving mechanisms in karst areas, intending to provide a scientific foundation for the recovery of fragile ecosystems and to support a regional low-carbon economy.

Assessing the dynamics of human activity intensity and its natural and socioeconomic determinants in Qinghai–Tibet Plateau

Investigating the spatiotemporal variation of human activity intensity and its determinants is a crucial basis for further revealing the mechanism of human-environment interaction and optimizing the human development mode. In this study, the human activity intensity on the Qinghai–Tibet Plateau (QTP) from 1990 to 2020 was measured based on the quantitative model of land use data and the actual regional background, and the underlying natural and socioeconomic determinants were investigated using spatial econometric methods. The results demonstrate that (1) the human activity intensity in QTP has increased by 11.96%, and there are differences in different spatial scales; the areas with high human activity intensity are distributed in the Hehuang Valley where Xining City and its surrounding areas are located, as well as the One-River and Two-River Area where Lhasa City and surrounding areas are located. (2) Human activity intensity has significant positive spatial spillover, suggesting that local changes will cause changes in the same direction in adjacent areas. (3) The human activity intensity in QTP is affected by various determinants. Concerning socioeconomic factors, the economic level has no significant impact on the human activity intensity in QTP, which differs from the general regional law. Both urbanization and traffic conditions have a significant positive effect, and the impact intensity continues to increase. Concerning natural factors, topographic relief has a significant positive effect; the impacts of temperature and vegetation coverage have changed from insignificant to a significant positive effect; the impacts of precipitation and river network density have not been verified; there is no linear relationship between altitude and human activity intensity in the entire QTP, while it exists in local regions. Finally, this study proposes three policy implications for the realization of a more harmonious human-environment relationship in QTP.

Differential roles of anthropogenic CO2 in mediating seasonal amplitudes of ocean acidification metrics over a coastal coral habitat

Seasonal-scale local forcings sharply reduce the coastal pH and aragonite saturation state (Ωaragonite). However, habitat-specific seasonality and control change signatures under increasing atmospheric CO2 are still poorly characterized. Here, we investigated carbonate system parameter dynamics over a Dongshan coral habitat that is greatly influenced by seasonal current patterns on the western Taiwan Strait coast. Specifically, relatively low pH and Ωaragonite were observed in the trial zone throughout the seasons. Using a first-order Taylor decomposition considering biological carbon metabolism, we suggest that the higher net aerobic respiration related to intense local human activities produced worse ocean acidity in the trial zone. Seasonally, a decreasing Ωaragonite trend was observed from the transition to the northeast monsoon seasons, mainly controlled by dissolved inorganic carbon (DIC) divergence among seasons. The pH/hydrogen ion concentration ([H+]) seasonal cycle was determined by both DIC and temperature components, revealing the lowest/highest value in the southwest monsoon season. Based on ocean acidification scenario modeling forced with a business-as-usual emissions scenario, the Ωaragonite seasonal amplitude attenuation was projected to exceed 30% during the 21st century. However, [H+] seasonal amplitude was amplified over 170%. The attenuation in the Ωaragonite seasonal amplitude mainly resulted from an increase in anthropogenic CO2 seasonal divergence. The increase in [H+] seasonal amplitude mostly followed from an increase in the [H+] sensitivities to DIC and temperature changes.

Evaluation on the adaptability of Yunnan karst ecosystems based on “rock-soil-water-vegetation”

Because of its fragile nature, the karst ecosystem is prone to instability and gradual degradation of the key elements with “rock-soil-water-vegetation” under the continuous interference of human unreasonable activity, resulting in the final formation of the rocky desertification landscape. Based on the research of the structure of karst critical zone, it was proposed to establish the concept of karst ecosystem adaptability with the evaluation system of “rock-soil-water-vegetation”. At the same time, the analysis of the stress and coupling relationship was conducted in combination with the analysis of human activity intensity in Yunnan karst rocky desertification areas. The results showed that: (1) On the county scale, the karst ecosystem adaptability mainly fell into Level 2–3 (0.10 < Ake ≤ 0.30). The contribution degree of indicators followed the order of annual precipitation > proportion of waterbody area, biological abundance index > rock outcrop rate > wetness index, vegetation cover > soil erosion index. (2) The synergistic relationship between karst ecosystem adaptability and human activity intensity was mainly characterized by ecological priority type (S ≥ 1.20), which was mainly found in West, Northwest and Southwest Yunnan. The development priority type (0 < S ≤ 0.80) was mainly centered around Kunming City, extending eastward to Qilin District of Qujing City, southward to Hongta District of Yuxi City, and further to Gejiu-Mengzi-Kaiyuan of Honghe Prefecture and Wenshan City of Wenshan Prefecture. (3) The coupling relationship between the karst ecosystem adaptability and human activity intensity was mainly in the running-in coupling state (0.50 < C ≤ 0.80). The coupling centers were mainly in Kunming City, Yuxi City, Qujing City and Honghe Prefecture (a high-level coupling, 0.80 < C < 1.00). (4) The coordination relationship between the karst ecosystem adaptability and human activity intensity mainly fell into the imbalanced development category, mostly moderately and mildly imbalanced development (0.20 ≤ D < 0.40). The coordinated development center was mainly centered in Kunming City of Central Yunnan (a coordinated development, D ≥ 0.5), which widely extended southward to Hongta-Jiangchuan-Chengjiang -Tonghai in Yuxi City and slightly spread eastward to Qilin District in Qujing City. The research results can provide effective ways and evaluation basis for enhancing the resilience and stability of the karst ecosystem and repairing damaged links, and also provide theoretical support for further studies on sustainable development of karst rocky desertification areas.

Evaluation of the Influence of Habitat Heterogeneity and Human Activities on the Distribution of Microbial Diversity in a High Elevation Drop River

The aim of this work was to investigate the microbial diversity characteristics and driving factors in a high elevation drop river and to analyze the potential risks of river microorganisms to human health. In March 2019, we analyzed the microbial diversity characteristics in surface water and sludge from the Huotong River using high-throughput sequencing. The Huotong River is of great importance to the production and life of the people living along this river. The sampling points were set at the estuary of the river, on a downstream section of the river, on an upstream section of the main river, at one tributary flowing through a town, at one tributary with a barrage, and at the source of one tributary. The results showed significant differences in bacterial diversity in different areas of the river. For example, actinomycetes were less abundant in water samples from the headwaters of tributaries and more abundant upriver. The results revealed that different intensities of human activities had significant different effects on functional flora. Anthropogenic disturbance and human activities reduced the abundance of probiotic bacteria and increased the abundance of pathogenic bacteria in the river. The changes in functional floral diversity may pose potential threats to human health.

Analyzing Spatial-Temporal Change of Vegetation Ecological Quality and Its Influencing Factors in Anhui Province, Eastern China Using Multiscale Geographically Weighted Regression

Vegetation is a crucial component of terrestrial ecology and plays a significant role in carbon sequestration. Monitoring changes in vegetation ecological quality has important guidance value for sustainable development. In this study, we investigated the spatial and temporal variation characteristics of Ecological Quality Index of Terrestrial Vegetation (EQI) in Anhui Province during the growing season from 2000 to 2020 using trend analysis, partial correlation analysis and bivariate spatial autocorrelation analysis. Based on the Multiscale Geographically Weighted Regression (MGWR), the spatial heterogeneity of the effects of average temperature, precipitation, elevation, slope, and human activity factors on EQI was explored. Our results showed an increasing trend in EQI during the growing season in Anhui Province from 2000 to 2020. The significantly increasing areas accounted for 43.49%, while the significantly decreasing areas accounted for 3.60%. EQI had a mostly positive correlation with precipitation and a negative correlation with average temperature (p &lt; 0.1), showing a higher sensitivity to precipitation than to temperature. Additionally, EQI tended to increase initially and then decrease with increasing elevation and slope. Furthermore, our analysis revealed a significant negative spatial correlation between human activity intensity and EQI (p &lt; 0.01). The bivariate global autocorrelation Moran index between EQI and human activity in 2000, 2005, 2010, 2015, and 2018 were −0.418, −0.427, −0.414, −0.487, and −0.470, respectively. We also found that the influencing factors explain 63–83% of the spatial variation of EQI, and the order of influence of factors on EQI is elevation &gt; human activity &gt; slope &gt; average temperature &gt; precipitation. MGWR results indicated that human activities and topographic factors had a stronger impact on EQI at the local scale, while climate factors tended to influence EQI at the global scale.