Land Use Variables Research Articles

Organic Carbon Storage and Structural-Hydraulic Properties of Ultisol under Agricultural Land Use Systems at Umuahia

The extent and pattern of interaction among organic carbon, structural and hydraulic properties of soils under varying land use systems are of great concern in the overall management of soil fertility and productivity. This study was conducted to examine the relationship among soil organic carbon storage, structural and hydraulic properties of soils under different agricultural land use systems at Umuahia, Abia State. The treatments were the four (4) land use systems (continuously cultivated arable farmland, 3 – year fallow land, oil palm plantation, and forest land) in which nine (9) replicates each of disturbed and undisturbed soil samples were randomly collected to give thirty six observational units laid out in a randomized complete block design. The soil samples were prepared and analysed in the laboratory. Analyses of variance, regression and correlation analyses were conducted on the data collected using Genstat version 14 and SPSS version 20. Results show that organic carbon had significant positive relationship with saturated hydraulic conductivity, macro porosity and total porosity but significant negative relationship with bulk density at all the land use systems. However, the influence of organic carbon on the other parameters was greatest at continuously cultivated arable land followed by the 3 – year fallow land. There is need to increase organic matter input at the continuously cultivated arable land and 3 – year fallow land through increased organic manuring and extension of the fallow period, respectively.

Assessing Groundwater Resources Vulnerability with the New DRASTIC-LP: A Case Study in Chiang Mai Province, Thailand

Groundwater vulnerability has gained widespread attention, particularly in Chiang Mai Province, one of Thailand’s fastest-growing cities, which is experiencing rapid development in both economic and social sectors. The expansion of urban communities and the industrial, tourism, and agriculture sectors has resulted in the overutilization of available resources, notably water resources. This overuse, coupled with the adoption of modern technology to boost productivity and meet market demands, has led to an increased reliance on groundwater to supplement surface water sources, providing benefits across all sectors. However, the economic and social growth plays a pivotal role in shaping the diversity of land use, encompassing residential, commercial, industrial, and agricultural activities. These activities, in turn, directly contribute to environmental pollution, particularly in terms of the risk of groundwater contamination in Chiang Mai Province. This study aims to predict the future vulnerabilities of groundwater resources under an ensemble of climate change scenarios and changes in land-use patterns. Chiang Mai Province in northern Thailand is one of the fastest-growing cities and therefore is experiencing rapid urbanization, as well as land-use pattern changes, which was important for the case study. The new DRASTIC model, namely the DRASTIC-LP model, combined with GIS-based techniques and overlay techniques, was used to generate the map of groundwater resource vulnerabilities. A point pollution source (P)-related land-use pattern (L) that represents contamination impacts was considered an additional new DRASTIC parameter. The study’s findings reveal the high reliability and maximum effectiveness of the new DRASTIC-LP model in assessing groundwater vulnerability and contamination-risk areas under a climate change scenario (by MIROC-ESM-CHEM model under RCP.8.5 scenario) and land-use pattern changes (by CA_Markov Chian Model) for both the current year (2020) and the next 50-year period (2021–2070). Furthermore, the new DRASTIC-LP model is employed to trace the movement of pollutants from high- to very high-risk areas based on the groundwater vulnerability and contamination-risk maps. The results highlight that waste disposal dumping sites pose a more critical distribution and movement of pollutants when compared to industrial sites. Additionally, unconsolidated aquifers and cracked consolidated rock aquifers show a potentially higher occurrence of pollutant distribution and movement when compared to consolidated aquifers. Consequently, the study’s outcomes are applied to formulate guidelines for the management and control of groundwater resource contamination. These guidelines serve as valuable tools for decision makers, aiding in pollution prevention and the effective management of contamination risks in groundwater resources.

In vitro bioaccessibility round robin testing for arsenic and lead in standard reference materials and soil samples.

In this study, we assessed the suitability of using a standard reference material (SRM) other than National Institute of Standards and Technology (NIST) 2710a or NIST 2711a in USEPA Method 1340 to determine arsenic (As) and lead (Pb) in vitro bioaccessibility (IVBA) and the capabilities of Canadian-based laboratories to perform the method. Five laboratories participated in an initial round robin study and analyzed NIST 2710a, NIST 2711a, BGS119, and Enviromat SS-2. Intra- and inter-laboratory variability were generally acceptable with percentage relative standard deviations (RSD) of less than 20%. The mean total As and Pb concentrations obtained for BGS119 (332 and 936 mg/kg, respectively) and the mean IVBA values (As = 14.3% and Pb = 78.1%) suggested it may be a suitable and acceptable SRM, whereas the concentration of As in Enviromat SS-2 as received (3.2 mg/kg) was deemed too low. Ten soil samples from sites with varying land use were analyzed in a follow-up round robin study using the modified IVBA method that included BGS119 as SRM. The concentrations of As and Pb in the IVBA extracts reported by the participating laboratories were comparable. The mean As IVBA values for the field-collected samples ranged from 0.1% to 56.4%; for Pb, they ranged from 7.0% to 121%. The lowest IVBA values were measured in mine site samples; the highest values were associated with smelter-affected soils. The low IVBA values correlated with high iron content. Intra- and interlaboratory reproducibility were acceptable (RSD < 30%). Based on the findings of the study, laboratories can use the modified method to provide reproducible and comparable As and Pb IVBA data. The use of BGS119 as an alternative SRM to assess contaminated sites in the province of British Columbia for regulatory purposes is recommended, as it is representative of As and Pb concentrations in contaminated soils in British Columbia. Integr Environ Assess Manag 2024;20:1486-1495. © 2024 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Land use change in coastal zones of China from 1985 to 2020

Coastal regions stand as pivotal zones of interaction between the marine and terrestrial environments, holding substantial significance for both ecosystems and human societies. Since the 1980s, China’s coastal zones (CCZ) have undergone rapid economic expansion, a surge in urban development activities, and a considerable population increase, instigating significant alterations in land use along the coast. However, in recent years, studies regarding changes in land use along China’s coastal zones have been notably scarce. Utilizing the Comprehensive Lands Cover Database (CLCD) dataset, this study scrutinized the spatiotemporal patterns of land use along the Chinese coastline since 1985. It delved into the temporal and spatial variations in land use, ecological land transformations, and the spatiotemporal evolution of land use development intensity, examining these facets across provinces, municipalities, and different distance bands from the coastal zone. The research findings indicated: Overall, cropland and forest land predominantly occupied coastal zones, encompassing over 80% of the total area. Between 1985 and 2020, the primary changes involved a decrease in cropland and an increase in construction land, with a reduction of 5.97% in cropland, largely transitioning into construction land (84927.21 km2) and forest land (4218.55 km2), resulting in a 5.98% increase in construction land. Despite the intensification of land development, ecological land exhibited an initial rise followed by a declining trend. There existed distinct disparities in land use patterns among provinces and cities, with cropland and forest land prevailing in all areas except Macau. Construction land and land use development intensity witnessed significant increases, most notably in Macau and least pronouncedly in Guangxi. Variations in ecological land alterations were considerable, with Hebei and Guangdong witnessing increases while other regions tended towards stability or reduction. Each distance band manifests a unique land use pattern. Except for the 100-150 km zone, construction land demonstrates an increasing trend across all bands. Ecological land expanded initially but fluctuated further from the coastline. Land use development intensity decreased initially, then stabilized, with the 0-10 km zone showed the highest development intensity. Analyzing the spatiotemporal changes in land use along China’s coastal zones from 1985 to 2020 can offer valuable insights into the management and sustainable development of China’s coastal zones.

Complexities of urban impacts on long-term seasonal trends in a mid-sized arid city

The variability of surface air temperature is of great importance for both society and the environment, is impacted by global warming and local-scale changes. In the arid eastern part of Washington state of USA, substantial urbanization has transformed the Tri-cities into the state’s third-largest urban cluster. This study utilizes a combination of in situ observations and reanalysis datasets to investigate the influence of land use changes on the region’s 2-meter temperature, revealing local effects that compensate for the background global warming. Within the urban fabric, distinct microclimates have emerged due to varying land use, establishing unique relationships between greenness and temperature alterations caused by land use transitions. Notably, our findings demonstrate that the observed compensating signal in the temperature of farmland locations is primarily attributed to local vegetation increases. Through these observations, this research highlights the urban impacts on local climate, offering valuable insights into the complexities surrounding land use and its consequences on the environment.

Rent growth near rail stations after the Great Recession

This study provides an incisive analysis of U.S. rail station area rent trends from 2012 to 2016, post-Great Recession. Utilizing Ordinary Least Squares (OLS), Hierarchical Spatial Autoregressive (HSAR), and Geographically Weighted Regression (GWR) models, it uncovers complex interplays between rent changes and socioeconomic, as well as built environment factors. Key findings reveal that increased rents are associated with walkability, higher housing density, and predominantly White neighborhoods. Conversely, rent decreases correlate with diverse land use, higher Black population percentages, and locations further from rail stations or business districts. These results are critical for understanding rent dynamics in transit-oriented development areas, impacting diverse housing market sectors, including workforce and affordable housing. The study’s regional analysis highlights the need for geographically tailored approaches. This research informs policy on housing development and affordability, aiming to mitigate displacement risks for low-income, transit-dependent communities in gentrifying urban areas.

Eco-epidemiology of Rickettsia amblyommatis and Rickettsia parkeri in naturally infected ticks (Acari: Ixodida) from South Carolina

BackgroundSpotted fever group Rickettsia (SFGR) is the largest group of Rickettsia species of clinical and veterinary importance emerging worldwide. Historically, SFGR cases were linked to Rickettsia rickettsii, the causal agent of Rocky Mountain spotted fever; however, recently discovered species Rickettsia parkeri and Rickettsia amblyommatis have been shown to cause a wide range of clinical symptoms. The role of R. amblyommatis in SFGR eco-epidemiology and the possible public health implications remain unknown.MethodsThis study evaluated statewide tick surveillance and land-use classification data to define the eco-epidemiological relationships between R. amblyommatis and R. parkeri among questing and feeding ticks collected across South Carolina between 2021 and 2022. Questing ticks from state parks and feeding ticks from animal shelters were evaluated for R. parkeri and R. amblyommatis using reverse transcriptase quantitative polymerase chain reaction (RT-qPCR) on pooled samples. A Bayesian multivariable logistic regression model for pool testing data was used to assess associations between R. parkeri or R. amblyommatis infection and land-use classification variables among questing ticks. The Spearman correlation was used to evaluate the relationship between the two tested pathogens.ResultsThe infection prevalence for R. amblyommatis was 24.8% (23.4–26.3%) among questing ticks, and 39.5% (37.4–42.0%) among feeding ticks; conversely, for R. parkeri it was 19.0% (17.6–20.5%) among questing ticks and 22.4% (20.3–24.5%) among feeding ticks. A negative, refractory correlation was found between the species, with ticks significantly more likely to contain one or the other pathogen, but not both simultaneously. The Bayesian analysis revealed that R. amblyommatis infection was positively associated with deciduous, evergreen, and mixed forests, and negatively associated with hay and pasture fields, and emergent herbaceous wetlands. Rickettsia parkeri infection was positively associated with deciduous, mixed, and evergreen forests, herbaceous vegetation, cultivated cropland, woody wetlands, and emergent herbaceous wetlands, and negatively associated with hay and pasture fields.ConclusionsThis is the first study to evaluate the eco-epidemiological factors driving tick pathogenicity in South Carolina. The negative interactions between SFGR species suggest the possible inhibition between the two pathogens tested, which could have important public health implications. Moreover, land-use classification factors revealed environments associated with tick pathogenicity, highlighting the need for tick vector control in these areas.Graphical

Study on the trade-off/synergy between ecosystem services and human well-being based on land use in Weinan City, China.

Change of land use have important impacts on ecosystem services (ESs) and human well-being (HWB), yet the trade-off/synergy among land use, ESs, and HWB has still not received sufficient attention at city regional scales level. Weinan City in the southern of the Loess Plateau of China was taken as the study area. Based on ArcGIS, InVEST model, and RUSLE model, the characteristics of spatial and temporal variations of land use and ESs from 2000 to 2020 were analyzed, and the trade-off/synergy relationship between land use, ESs, and HWB was quantified using correlation analysis. The results indicated that the area of cultivated land decreased significantly and the area of built-up land increased significantly from 2000 to 2020 in Weinan City. The grain production, soil conservation, and water yield functions showed an increasing trend, which was a synergistic relationship with HWB. Carbon storage and habitat quality functions showed a decreasing trend, which was a trade-off relationship with HWB. The index value of HWB has increased significantly, mainly in the added value of agricultural and rural per capita income. Land use intensity has a trade-off relationship with GP, WY functions, and HWB. There are many factors that affect this trade-off/synergy relationship, such as land use patterns, economic development, and population growth. The study can provide a theoretical basis for the sustainable development of regional economy and nature.

Low Flow of Cascade Reservoir in Sekampung Watershed

Purpose: This research intends to analyze the low flow in the cascade reservoir in Sekampung watershed Theoretical reference: The low flow analysis uses the HEC-HMS model with the input parameters are GPM satellite rainfall that is calibrated by the ground station data in the Sekampung watershed, variation of land use, and soil type. Method: The methodology consist of by using the HEC-HMS model. Then, this model is calibrated with the flow discharge in Batutegi reservoir. Result and Conclusion: The model result produces the linear average discharge with the comparation ratio of sub-watershed area in each outlet is as follow: 11.0% (W1), 10.4% (W2), 39.9% (B1), 9.2% (W3), and 30.5% (B2). Half monthly average discharge is in the range of 2.6-40.8 m3/s (W1), 2.6-35.8 m3/s (W2), 11.9-151.4 m3/s (B1), 2.6-34.8 m3/s (W3), and 8.8-116.2 m3/s (B2). Percentile of dependable discharge that is used is &gt;66.6% for dry year, 66.6%-33.3% for normal year, and &lt;33.3% for wet year with the value between 6.6-25.4 m3/s (W1), 5.7-23.2 m3/s (W2), 24.2-97.3 m3/s (B1), 5.4-22.4 m3/s (W3), and 18.0-74.8 m3/s (B2). Implication of research: The calibration of discharge as the modelling result to the observed discharge produces the RMSE value is 0.462, the NSE value is 0.787, the PBIAS is 0.04% with the result interpretation is very good. The validation produces the RMSE value is 0.632, the NSE value is 0.601, and the PBIAS value is 0.01% with the result interpretation is very good. Originality/ value: The model that is used for analyzing flood in the study location is the HEC-HMS software by carrying out the watershed division into smaller sub-watershed.

Investigating the Spatio-Temporal Relationship between NDVI and LST in Abakaliki LGA, Ebonyi State Nigeria, Using Landsat and Correlation Analysis: Implications for Landscape Management

Understanding spatiotemporal linkages between normalised difference vegetation index (NDVI) and land surface temperature (LST) is crucial for managing landscape resilience amid global change. This study applied correlation analyses to investigate NDVI-LST relationships across Abakaliki LGA, Nigeria from 2000-2022 using Landsat data. Multi-decadal trends revealed widespread LST increases exceeding 9°C, while NDVI declined, implying vegetation clearing transformed surfaces from carbon sinks to sources dampening temperatures. In 2000, NDVI positively correlated with LST (r=0.745, p&lt;0.01); by 2022, large-scale NDVI suppression drove strong negative correlations between NDVI and LST (r=-0.751, p&lt;0.01). Findings documented rapid decoupling of previously heterogeneous NDVI-LST couplings tied to diverse land use. Sustainable intensification offers potential to restore climate-buffering vegetation and recouple local anthropogenic-climatic systems. Continued monitoring can track restoration progress while adaptation evolves with socio-environmental change. This research advances understanding of anthropic impacts on landscape energetics using remote sensing and correlation analyses, with implications for integrated management under global change.

Where Are the Trade-Offs in Multiple Ecosystem Services in the Process of Ecological Restoration? A Case Study on the Vegetation Restoration Area in the Loess Plateau, Northern Shaanxi

Revealing trade-off and synergistic relationships among ecosystem services plays a key role in ensuring a stable ecosystem for long-term development. It is the crucial precondition for realizing watershed protection and high-quality development. The variations in land use during 1990–2020 are investigated by taking the typical areas for returning farmland to forests as an example. The spatiotemporal distributions of six key ecosystem services, namely carbon storage, water yield, net primary productivity (NPP), soil conservation, habitat quality, and forest recreation are quantified by the InVEST model and statistical data. We also uncover the spatial difference in the ecosystem in Loess Plateau, located in northern Shaanxi, with hot spot analysis and probe the trade-off and synergistic correlations among the investigated ecosystem services. The results show that: (1) the farmland decreased dramatically. On the contrary, the forests and orchards increased significantly. (2) During the same period, carbon storage and habitat quality increased, and water yield, NPP, soil conservation, and forest recreation initially declined, but subsequently rose to higher values than that in 1990. All these services in the southeastern part of the research area surpass those found in the northwest. (3) The ecosystem services relationships in northern Shaanxi are mainly characterized by synergistic correlations, which became stronger from 1990 to 2020. The trade-off effects mainly occur among the water yield and other ecosystem services and are distributed in the west and north of the investigated area. Based on these findings, this work provides scientific principles for improving the ecological environment and enhancing the resource sustainability of the study area.

Quantifying salinity in calcareous soils through advanced spectroscopic models: A comparative study of random forests and regression techniques across diverse land use systems.

Precise prediction of soil salinity using visible, and near-infrared (vis-NIR) spectroscopy is crucial for ensuring food security and effective environmental management. This paper focuses on the precise prediction of soil salinity utilizing visible and near-infrared (vis-NIR) spectroscopy, a critical factor for food security and effective environmental management. The objective is to utilize vis-NIR spectra alongside a multiple regression model (MLR) and a random forest (RF) modeling approach to predict soil salinity across various land use types, such as farmlands, bare lands, and rangelands accurately. To this end, we selected 150 sampling points representatives of these diverse land uses. At each point, we collected soil samples to measure the soil salinity (ECe) and employed a portable spectrometer to capture the spectral reflectance across the full wavelength range of 400 to 2400 nm. The methodology involved using both individual spectral reflectance values and combinations of reflectance values from different wavelengths as input variables for developing the MLR and RF models. The results indicated that the RF model (RMSE = 4.85 dS m-1, R2 = 0.87, and RPD = 3.15), utilizing combined factors as input variables, outperformed others. Furthermore, our analysis across different land uses revealed that models incorporating combined input variables yielded significantly better results, particularly for farmlands and rangelands. This study underscores the potential of combining vis-NIR spectroscopy with advanced modeling techniques to enhance the accuracy of soil salinity predictions, thereby supporting more informed agricultural and environmental management decisions.

Modelling Impact of Land Use Changes and Climate on Soil Erosion in the Uma Oya River Basin, Sri Lanka

Soil erosion is a significant environmental issue in most mountainous areas and is further exacerbated due to ongoing climatic changes and anthropogenic activities. Soil erosion not only triggers natural disasters like landslides but also degrades the fertile topsoil layers. Therefore, modeling and evaluation of soil erosion in mountainous areas and river basins are highly important. The Uma Oya River Basin (UORB), Sri Lanka is an area with rich biodiversity and is also important for agricultural production. Moreover, this area is frequently discussed due to the ongoing developments of the Uma Oya Project. This paper presents a comprehensive evaluation of soil erosion in the UORB and results are compared for two decades from 2000 to 2020. The Revised Universal Soil Loss Equation (RUSLE) was used to determine the annual soil erosion rates. In addition, the spatial-temporal variation of land use and land cover was assessed in the UORB. Results revealed that extreme soil erosion scenarios occur when forests and other vegetation lands are converted to agricultural lands and farmlands. We found that soil loss in the area largely happened due to steep slopes, reduction of vegetation and forest covers, and growth of cultivation lands. Erosion-prone areas in the river basin are identified and conservation strategies are discussed. In addition, the impact of the ongoing climate change on the UORB is highlighted.

Soil microbial activity profiles associated with organic compost fertilizers in an urban garden

AbstractBiological soil health is recognized as an important component of sustainable agriculture due to microbial biomineralization of nutrients. However, soil health can be difficult to assess consistently across urban agricultural systems due to diverse land use histories, soil heterogeneity, and lack of mechanistic links to agricultural management practices (e.g., recycled compost addition) and crop outcomes. In this study, we characterized soil microbial activity profiles in an urban agriculture system in Minnesota, USA, including microbial abundance, soil respiration, extracellular enzyme activity, and crop yield. Garden plots were fertilized with recycled organic compost (either manure or municipal) at high or low rates (ranging from 2.6 to 39 tons ha−1) targeted to crop N and P demands. Control plots received inorganic fertilizer or no fertilizer. We found that a high application rate of manure compost supported 6–10x higher basal respiration than municipal compost or inorganic fertilizer. Enzyme activity data demonstrated that soil microbial communities exhibited unique profiles of biochemical function that varied among fertilizers of different compositions. Microbial biochemical function predicted 50% of the variability in bell pepper (Capsicum annuum) yield, while soil microbial community size alone was a poor predictor of yield. Yield was highest in plots fertilized with municipal compost, outperforming inorganic fertilizer by threefold. High‐yield plots exhibited higher ratios of N to P enzyme activity compared to those with lower yield. Our findings demonstrate that “more is better” may not necessarily be true regarding soil microorganisms in biological soil health, and that measures of soil microbial biochemical function may be more important.

Improving Machine Learning Based PM2.5 Prediction by Segregating Biomass Emission Factor from Chemical Transport Model

Located in the heart of Mainland Southeast Asia, Thailand is associated with high biomass burning (BB) activities from local and neighbouring countries. The seasonal pattern of BB manifests itself as a potential predictor for PM2.5 concentration. Consequently, we enhanced machine learning based PM2.5 prediction by segregating BB factor from the Community Multiscale Air Quality (CMAQ). Two Light Gradient Boosting Machine (LightGBM) models with different CMAQ predictors were developed: the BB-integrated model, which incorporated CMAQ-simulated PM2.5 from all emission sources and the BB-segregated model, which incorporated CMAQ-simulated PM2.5 from sources other than BB (CMAQ_PM25_Othr) and CMAQ-simulated PM2.5 from BB emissions (CMAQ_PM25_BB). The two models had shared control predictors, which included simulated meteorological variables from WRF model, population, elevation, and land-use variables, and they were evaluated using a crossvalidation (CV). The BB-segregated model outperformed the BB-integrated model, achieving overall-CV R2 values of 0.86 and 0.82, respectively. The analysis of feature importance for the BB-segregated model indicates that CMAQ_PM25_Othr and CMAQ_PM25_BB are the two most significant predictors. These findings emphasize the importance of considering BB emissions when predicting PM2.5 concentrations, particularly in regions with high BB activities.

Application of Satellite Images and Artificial Intelligence to Monitor Land Cover Changes in Hanoi Area During 2013-2023 Period

Artificial intelligence (AI) and remote sensing technology have now increasingly improved their efficiency and reliability in monitoring the changes in land cover. With the amendment of the Vietnamese Law on Land in 2013 and the administrative boundary expansion of Hanoi, Hanoi experiences significant changes in land use and land cover for the last ten years. To monitor the actual land use changes in the area, this study used the Random Forest (RF) machine learning algorithm to classify the basic land covers, monitor, and analyze the spatial variation of land use and land cover in the 2013 to 2023 period. The study findings indicate a relatively high rate of expansion of construction zone area and a decrease in land cover related to water bodies and vegetated area. Water bodies decrease by an average of 0.8% annually, whereas the construction zone area increased by 7% of the total area.&#x0D;

Adaptation of the European Fish Index (EFI+) to Include the Alien Fish Pressure

The European Fish Index EFI+ is the only fish-based multimetric index for the assessment of the ecological status of running waters that is validated and thus applicable across most countries of the European Union. Metrics of the index rely on several attributes of the species present in the fish assemblage, irrespective of their native/alien status. The abundance of alien fish, together with other anthropogenic impacts, is one of the most important threats to the conservation of native fish and ecosystem health and is also an indicator of degraded stream conditions. Therefore, to improve the performance of the EFI+ in regions with high incidence of alien species, the EFI+ was adapted to include alien fish pressure as a new metric that reflects the number of alien species as well as the proportional abundance of alien individuals. The application of the adapted index (A-EFI+) is illustrated with data from several Iberian Mediterranean basins and showed similar or stronger correlations than the original EFI+ with anthropogenic pressure (land-use variables and alterations in hydrology and river morphology) and with other regional fish indices. EFI+ has been invaluable to intercalibrate fish indices across Europe, and A-EFI+ is similar but explicitly includes alien pressure, thus helping to provide a more comprehensive assessment of ecosystem health and to communicate it to society.

Assessment of Carbon Stock in Response to Varied Land Use Systems and Soil Depths in Chandel District, Manipur, India

To understand the effects of land use system and its cropping techniques, the study on carbon stock and soil nutrients in response to varied land use systems and soil depths in Chandel district was carried out during 2020 from five different locations in the Chandel district that include a variety of land use systems such as Forest area, Jhum cultivation after 15 years, Jhum cultivation after 10 years, Jhum cultivation after 10 years from different sub division of the district, Jhum cultivation after 5 years, Intermittent Jhum area, Oak forest area, Teak forest area, Pine forest area, Agri-horti jhum cropping system area and Maize based cropping system area. The study revealed that Forest soils shows significantly higher Organic carbon content of 2.73 % in 0-15 cm and 2.04% in 30-45 cm soil depth respectively than the other land use system of Chandel district. Available N was also found to be significantly higher in forest soils i.e. 533.49 kg/ha in 0-15 cm soil depth and 475.14 kg/ha in 30-45 cm soil depth as compared to other land use systems. Similarly, available P2O5 of 10.92 kg/ha and 9.97 kg/ha in 0-15 cm and 30-45 cm soil depth respectively and K2O of 278.08 kg/ha in 0-15 cm and 266.11 kg/ha in 30-45 cm were also recorded to be significantly higher in forest soil which was followed by the Jhum cultivation after 15 years in Chandel district. Next to forest area soils, Jhum cultivation after 15 years shows higher organic carbon content and other soil nutrients as compare to other land use systems due to the longer waiting period of cultivation. These results indicated that the land under more vegetation and less disturbed areas have higher soil nutrient and organic carbon as compared to other land use system. Thus it may be concluded that, variations in soil fertility parameters need immediate improvement in soil health of Jhum lands and other land use systems.

DIRECT AND INDIRECT CAUSAL EFFECTS OF AIR POLLUTANTS ON ALZHEIMER’S DISEASE RISK AND DISPARITIES

Abstract Ambient air contaminants have been associated with higher risk of Alzheimer’s disease (AD), related dementia, and cognitive impairment; however, mechanisms that underlay these effects remain unclear. Pre-existing arterial hypertension, diabetes mellitus, cerebrovascular disease, and renal disease have a strong impact on AD risk and disparities. These diseases, in turn, are associated with exposure to air contaminants, including particulate matter (PM2.5). We applied causal mediation analysis in the formulation of VanderWeele which provides causal estimates of the direct and indirect (through the effects on pre-existing diseases) effects of PM2.5 exposure on the risk of AD. We used Administrative Health Insurance Claims from 5%-Medicare (N=6,042,239; 1991-2020) to identify the date of onset for AD and risk related diseases such as arterial hypertension, diabetes, cerebrovascular, and kidney diseases that were considered mediators in these analyses. Information on ambient PM2.5 at the zip code level were derived from the Socioeconomic Data and Applications Center (SEDAC) that incorporates air monitoring data, satellite aerosol optical depth, meteorological conditions, chemical transport model simulations, and land-use variables. The estimates supported the hypotheses on the linear dependence of the dose-response function with higher effects for Males vs. Females, White vs. Black subpopulations, and stroke-belt states vs. other U.S. regions. We found that the contributions of indirect effects were stronger for younger older adults and reached up to 13% for cerebrovascular disease, 10% for arterial hypertension, 5% for diabetes, and 4% for chronic kidney disease. Analysis in subpopulations demonstrated health disparities in the effects of PM2.5 on AD risk.

Analysis and prediction of the spatiotemporal characteristics of land-use ecological risk and carbon storage in Wuhan metropolitan area

In the context of global warming, understanding the spatiotemporal dynamic of carbon storage, land-use related ecological risks, and how ecological risks are correlated with carbon storage, is vitally significant for enhancing regional carbon-sequestration capacity, promoting the rational exploitation of land and green and low-carbon development. Using land-use data, this study employed the InVEST and PLUS models to analyze and forecast spatiotemporal variation in land-use, land-use ecological risks, and terrestrial ecosystem carbon storage in the Wuhan metropolitan area under multiple-scenarios. Spearman’s correlation and spatial autocorrelation analyses were used to explore spatial correlations between carbon storage and land-use ecological risk. The following was found: (1) From 2000 to2020, the area of arable land, grassland, water body, and unused land reduced. In contrast, the area of forestland and built-up land increased. Similar land-use changes were observed in 2030 under the natural development scenario. The area of forestland, grassland, and water body increased, and the expansion of built-up land is effectively controlled under the ecological protection scenario. (2) Land-use ecological risks in the study area first declined and then increased over the research period, with an overall increase. (3) From 2000 to 2030, the carbon storage within the Wuhan metropolitan area declined. In the 2030 ecological protection scenario, the reduction in carbon storage is lower than under the natural development scenario. Through the lens of land-use categories, the entire carbon storage was, in descending order, arable land, forestland, built-up land, grassland, unused land, and water body. (4) Land-use ecological risk and carbon storage were negatively correlated and dominated by Low-High and High-Low aggregation zones. This study can serve as a reference for the future optimal layout of land-use and sustainable development of ecosystems in metropolitan areas.