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16 pages, 4016 KiB  
Article
Ten Candidate Genes Were Identified to Be Associated with the Great Growth Differentiation in the Three-Way Cross Hybrid Abalone
by Qizhen Xiao, Shihai Gong, Zekun Huang, Wenzhu Peng, Zhaofang Han, Yang Gan, Yawei Shen, Weiwei You, Caihuan Ke and Xuan Luo
Animals 2025, 15(2), 211; https://doi.org/10.3390/ani15020211 - 14 Jan 2025
Abstract
Abalone is an economically important mollusk, whose slow growth has impeded the recovery of its wild populations and development of aquaculture. The three-way cross hybrid abalone ((Haliotis discus hannai♀ × H. fulgens♂)♀ × H. gigantea♂, DF × SS) demonstrated [...] Read more.
Abalone is an economically important mollusk, whose slow growth has impeded the recovery of its wild populations and development of aquaculture. The three-way cross hybrid abalone ((Haliotis discus hannai♀ × H. fulgens♂)♀ × H. gigantea♂, DF × SS) demonstrated notable diversity in growth traits across the population with genetic differentiation, offering a model for exploring the molecular mechanisms of abalone growth. In this study, a total of 89 SNPs and 97 candidate genes were identified to be associated with growth-related traits of abalone using whole-genome resequencing and a genome-wide association study (GWAS) analysis. Then, ten overlap genes were found among these candidate genes by combining the results of GWAS and comparative transcriptomic analyses between the large individuals (L group) and small individuals (S group) of DF × SS. These overlap genes include up-regulated genes (fabG) and down-regulated genes (HMCN1, TLR3, ITIH3) between the L and the S groups, which are thought to function in growth in other organisms. The biological functions of these candidate genes in abalone still have to be confirmed, but they have improved our understanding of the molecular mechanisms behind abalone growth traits and provided molecular markers for abalone breeding programs. Full article
(This article belongs to the Section Aquatic Animals)
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Figure 1

Figure 1
<p>Growth-related traits and genetic variants distribution of individuals used for GWAS. (<b>A</b>) Box plots of eight growth-related traits of 115 individuals of three-way cross hybrid abalone (DF × SS). (<b>B</b>) Distribution of SNPs on each chromosome (the number of SNPs within a 0.1 Mb window size). (<b>C</b>) The gravel plot in principal component analysis (PCA). (<b>D</b>) 3D PCA plot.</p>
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<p>Manhattan plots and QQ plots of (<b>A</b>) <span class="html-italic">SL</span>, (<b>B</b>) <span class="html-italic">SW</span>, (<b>C</b>) <span class="html-italic">TW</span>, (<b>D</b>) <span class="html-italic">TS</span>, (<b>E</b>) <span class="html-italic">TM</span>, (<b>F</b>) <span class="html-italic">LW</span>, (<b>G</b>) <span class="html-italic">F</span>, and (<b>H</b>) <span class="html-italic">MR</span>. The black line represents the genome-wide significance threshold (−log10<span class="html-italic">P</span> = 5). The horizontal bars represent marker density on each chromosome. <span class="html-italic">SL:</span> shell length; <span class="html-italic">SW:</span> shell width; <span class="html-italic">TW:</span> total weight; <span class="html-italic">TS</span>: shell weight; <span class="html-italic">TM</span>: foot muscle weight; <span class="html-italic">LW</span>: the ratio of shell length and shell width; <span class="html-italic">MR</span>: the ratio of foot muscle weight and wet weight; <span class="html-italic">F</span>: the ratio of wet weight and shell length.</p>
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<p>Comparative transcriptomic analysis of L group and S group in DF × SS. (<b>A</b>) PCA plot of transcriptome of abalone muscle samples. (<b>B</b>) Genome-wide clustering of foot muscle samples. (<b>C</b>) Volcano plot of gene expression in the muscle of the L group and the S group in DF × SS. The up-regulated and down-regulated differentially expressed genes (DEGs) are shown in red and blue dots, respectively. (<b>D</b>) Heatmap of overlap genes between GWAS candidate genes and differentially expressed genes in the transcriptome analyses.</p>
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<p>(<b>A</b>) GO and (<b>B</b>) KEGG pathway enrichment analysis for all DEGs.</p>
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<p>Expression of ten overlap candidate genes by RNA-seq in the L and S group. (<b>A</b>): <span class="html-italic">tarbp</span>; (<b>B</b>): <span class="html-italic">JAKMIP3</span>; (<b>C</b>): <span class="html-italic">fabG</span>; (<b>D</b>): <span class="html-italic">ITIH3</span>; (<b>E</b>): <span class="html-italic">Gpr34</span>; (<b>F</b>): <span class="html-italic">WASF3</span>; (<b>G</b>): <span class="html-italic">FAM47C</span>; (<b>H</b>): <span class="html-italic">LGSN</span>; (<b>I</b>): <span class="html-italic">TLR3</span>; (<b>J</b>): <span class="html-italic">HMCN1</span>.</p>
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23 pages, 9842 KiB  
Article
Assessing Groundwater Connection/Disconnection to Waterholes Along the Balonne River and in the Barwon–Darling River System in Queensland and New South Wales, Australia, for Waterhole Persistence
by Harald Hofmann and Jonathan Marshall
Hydrology 2025, 12(1), 15; https://doi.org/10.3390/hydrology12010015 - 14 Jan 2025
Abstract
Waterholes in semi-arid environment are sections of rivers that fill during high river flows or floods and keep water once flow ceases. They are essential water sources for rive ecosystems. Some waterholes remain even during prolonged droughts. The resilience of ecosystems in these [...] Read more.
Waterholes in semi-arid environment are sections of rivers that fill during high river flows or floods and keep water once flow ceases. They are essential water sources for rive ecosystems. Some waterholes remain even during prolonged droughts. The resilience of ecosystems in these environments depends on the persistence of the waterholes. While most semi-arid, ephemeral river systems are disconnected from regional groundwater and losing in most parts there may be some sections that can be connected to localised groundwater or parafluvial areas. To assess the persistence of waterholes the groundwater contribution to the water balance needs to be addressed. This study assesses groundwater connectivity to waterholes in a part of the Murray-Darling Basin, one of the largest watersheds in the world, using environmental tracers radon and stable isotopes. Approximately 100 samples were collected from 27 waterholes along the Narran, Calgoa, Barwon and Darling rivers, as well as 8 groundwater bore samples. The assessment of groundwater connectivity or the lack of is necessary from water balance modelling and estimation of persistence of these waterholes. As expected, the results indicate consistently low radon concentrations in the waterholes and very small deviation in stable isotopes δ18O and δ2H. In general, most of these waterholes are losing water to groundwater, indicated by low salinity (EC values) and low radon concentrations. While radon concentrations are small in most cases and indicative of little groundwater contributions, some variability can be assigned to bank return and parafluvial flow. It indicates that these contributions may have implications for waterhole persistence in ephemeral streams. The study demonstrates that in some cases local bank return flow or parafluvial flow may contribute to waterhole persistence. Full article
23 pages, 6752 KiB  
Article
Development of Fractional Vegetation Cover Change and Driving Forces in the Min River Basin on the Eastern Margin of the Tibetan Plateau
by Shuyuan Liu, Li Zhou, Huan Wang, Jin Lin, Yuduo Huang, Peng Zhuo and Tianqi Ao
Forests 2025, 16(1), 142; https://doi.org/10.3390/f16010142 - 14 Jan 2025
Abstract
Fractional vegetation cover (FVC) is an important indicator of regional ecological environment change, and quantitative research on the spatial and temporal distribution of FVC and the trend of change is of great significance to the monitoring, evaluation, protection, and restoration of regional ecology. [...] Read more.
Fractional vegetation cover (FVC) is an important indicator of regional ecological environment change, and quantitative research on the spatial and temporal distribution of FVC and the trend of change is of great significance to the monitoring, evaluation, protection, and restoration of regional ecology. This study estimates the FVC of the eastern Tibetan Plateau margin from 2000 to 2020 using the image element dichotomous model based on the Google Earth Engine platform using MODIS-NDVI images. It also investigates the temporal and spatial changes of the FVC in this region and its drivers using the Theil–Sen and Mann–Kendall trend tests, spatial autocorrelation analysis, geodetector, and machine learning approaches impact. The results of this study indicated a generally erratic rising tendency, with the Min River Basin (MRB) near the eastern tip of the Tibetan Plateau having an annual average FVC of 0.67 and an annual growth rate of 0.16%. The percentage of places with better vegetation reached 60.37%. The regional FVC showed significant positive spatial autocorrelation and was clustered. Driver analyses showed that soil type, DEM, temperature, potential evapotranspiration, and land use type were the main drivers influencing FVC on the eastern margin of the Tibetan Plateau. In addition, the random forest (RF) model outperformed the support vector machine (SVM), backpropagation neural network (BP), and long short-term memory network (LSTM) in FVC regression fitting. In summary, this study shows that the overall FVC in the eastern margin of the Tibetan Plateau is on an upward trend, and the regional ecological environment has improved significantly over the past two decades. Full article
(This article belongs to the Section Forest Inventory, Modeling and Remote Sensing)
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Figure 1
<p>Location of the MRB study area, (<b>a</b>) Specific location on the Tibetan Plateau, (<b>b</b>) DEM, (<b>c</b>) Land use.</p>
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<p>Spatial distribution of the drivers in 2015.</p>
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<p>(<b>a</b>) Proportion of each FVC type from 2000 to 2020; (<b>b</b>) temporal trend of FVC variation.</p>
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<p>Spatial pattern of different classes of FVC on the eastern margin of the Tibetan Plateau, 2000–2020.</p>
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<p>FVC spatial transfer area distribution (<b>a</b>) from 2000 to 2010; (<b>b</b>) from 2010 to 2020.</p>
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<p>Trends in FVC and their significance.</p>
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<p>FVC global spatial autocorrelation.</p>
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<p>FVC localized spatial autocorrelation LISA aggregation distribution.</p>
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<p>FVC factor detection results.</p>
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<p>Interaction test results of vegetation cover drivers in different years (NE indicates nonlinear enhancement, BE indicates two-factor enhancement).</p>
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<p>Significance statistics for differences in the impact of each driver.</p>
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<p>Statistical findings for various FVC types or ranges for every factor.</p>
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<p>Comparison of true and regression values of FVC: (<b>a</b>) SVM, (<b>b</b>) BP, (<b>c</b>) LSTM, (<b>d</b>) RF.</p>
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29 pages, 43098 KiB  
Article
Sedimentary Characteristics of Shallow Water Delta: A Case Study from the Paleogene Funing Formation in the Haian Sag of the Subei Basin, China
by Zhao Ma, Guiyu Dong, Tianwei Wang, Yongfeng Qiu, Tianzhuo Bi and Ziyi Yang
Minerals 2025, 15(1), 75; https://doi.org/10.3390/min15010075 - 14 Jan 2025
Abstract
Haian Depression is one of the key areas for oil and gas resource replacement in Jiangsu Oilfield. Since the 13th cycle of the Five Year Plan, with the continuous improvement in the exploration level of the Taizhou Formation (K2t), the difficulty [...] Read more.
Haian Depression is one of the key areas for oil and gas resource replacement in Jiangsu Oilfield. Since the 13th cycle of the Five Year Plan, with the continuous improvement in the exploration level of the Taizhou Formation (K2t), the difficulty of tapping potential has gradually increased. It is urgent to change our thinking and expand new exploration layers. From the perspective of oil and gas display frequency in different layers of the Haian Depression, except for K2t, the oil and gas systems with the Fusan Member (E1f3) as the main reservoir have good oil and gas display frequency, demonstrating great exploration potential. This study of sedimentary characteristics is the basis of analyzing the sedimentary environment and lithofacies paleogeographic conditions and is of great significance for determining the distribution range of subtle oil and gas reservoirs. Based on this understanding, this study was specially established to systematically analyze the logging curves of forty-three wells in the research area, combined with core observations of eighteen coring wells and the analysis of eight seismic profiles. The results show that the low slope, warm and humid climate, sufficient provenance, and frequent lake level rise and fall cycles during the deposition period of the E1f3 member of the Haian Sag provide a favorable depositional background for the development of shallow water delta in the study area. There are many gullies in the research area, mainly consisting of U-shaped gullies and W-shaped gullies. Slope breaks are mainly affected by structural factors leading to fractures, and the types are mostly fault terrbreakslope breaks. In the study area, the shallow water delta deposits during the deposition period of the four key sand groups in the Fu3 Formation are dominated by the shallow water delta front and shallow water prodelta. The shallow water delta plain subfacies are not significantly developed because of erosion. The sand bodies are mainly distributed in the Sunjiawa Subdepression, and the Fuan Subdepression in the north of the depression, and the sand bodies in the plane show the filling characteristics of the strip. Based on the above research, a sedimentary model of shallow water delta during the E1f3 section of the Haian Depression was established, providing a geological basis for the design of exploration and development plans for hidden oil and gas reservoirs in the next step. Full article
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Figure 1

Figure 1
<p>Schematic diagram of location (<b>A</b>) and structural unit division of the Haian Depression (<b>B</b>).</p>
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<p>Comprehensive histogram of the stratum of the Haian Sag.</p>
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<p>Stratigraphic division and main tectonic evolution of the Haian Depression. (According to Qiu xuming, 1992 [<a href="#B20-minerals-15-00075" class="html-bibr">20</a>]).</p>
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<p>Tectonic evolution map of the Haian Depression Haibei Subconcave (<b>A</b>), Fuan Subconcave (<b>B</b>), Sunjiawa Subconcave (<b>C</b>). Different colors represent different strata, and the age of the strata decreases from bottom to top.</p>
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<p>Paleoclimate evolution and paleosalinity map of the Haian Depression.</p>
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<p>Luminescence characteristics of the E<sub>1</sub>f<sub>3</sub> cathode in the Haian Sag Well L2, 1909.45 m, quartz mostly does not emit light, a small amount of dark brown light, feldspar light blue light, yellow light, brown light, red light, yellow-green light, rock debris composite color light, red light, dark light (<b>A</b>); Well An1, 2446.34 m, quartz mostly does not emit light, feldspar light blue, yellow, brown, red, yellow-green light, rock debris hair composite color light, dark light (<b>B</b>); Well An16, 3509.20 m, quartz mostly does not emit light, a small amount of dark brown light, feldspar light blue light, green light, brown light, pink light, yellow-green light, rock debris hair composite color light, dark light (<b>C</b>); Well An12, 2238.60 m, quartz does not emit light, feldspar light blue, yellow–green, red light, brown light (<b>D</b>).</p>
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<p>Color characteristics of mudstone in the Fu3 member of the Haian Sag. Well AN6, 2567.86 m, dark brown mudstone (<b>A</b>); Well AN16, 3510.02 m, gray–green silty mudstone, bioturbation (<b>B</b>); Well L2, 1913.88 m, brownish yellow mudstone (<b>C</b>); Well L2, 1938.38 m, gray–green silty mudstone, bioturbation, transitional bedding (<b>D</b>); Well L4, 2231.80 m, gray silty mudstone, bioturbation (<b>E</b>); Well L2, 1910.93 m, light gray silty mudstone (<b>F</b>); Well AN16, 3448.50, dark gray mudstone (<b>G</b>); Well AN12, 2238.60 m, mudstone color change, bioturbation (<b>H</b>); Well L2, 1919.69 m, mudstone color change (<b>I</b>).</p>
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<p>Well AN10, 2621.81 m, Grey and dark grey siltstone with mud content, fine sandstone and coarse sandstone, transitional bedding, and strong hydrodynamics.</p>
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<p>Types of E<sub>1</sub>f<sub>3</sub> downcut valley and fault trough in the Haian Depression. E<sub>1</sub>f<sub>3</sub><sup>3</sup>U downcut valley in the Haian Depression (<b>A</b>); E<sub>1</sub>f<sub>3</sub><sup>1</sup> bottom sand double fault trough in the Haian Depression (<b>B</b>); E<sub>1</sub>f<sub>3</sub><sup>3</sup>U + W type downcut valley in the Haian Depression, ① E<sub>1</sub>f<sub>3</sub><sup>3-1</sup> ② E<sub>1</sub>f<sub>3</sub><sup>2-2</sup> ③ E<sub>1</sub>f<sub>3</sub><sup>2-1</sup> ④ E<sub>1</sub>f<sub>3</sub><sup>1-3</sup> ⑤ E<sub>1</sub>f<sub>4</sub> ⑥ E<sub>1</sub>d<sub>1</sub> (<b>C</b>).</p>
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<p>Seismic reflection characteristics of structural slope break zone of fault step type fault in the Haian Depression.</p>
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<p>Sedimentation rock type in the Fu3 member of the Haian Sag. Well Z2, 1467.32 m, grey black mudstone (<b>A</b>); Well AN6,2916.25 m, dark brown mudstone (<b>B</b>); Well L2, 1910.93 m, light gray silty mudstone (<b>C</b>); Well Z2, 1628.92 m, grey gray mudstone (<b>D</b>); Well W19, 1322.14 m, grey white siltstone (<b>E</b>); Well T2, 2047.45 m, grey mudstone sandstone (<b>F</b>); Well S36, 2073.13 m, grey white fine sandstone (<b>G</b>); Well L5, 2499.85 m, light gray medium sandstone (<b>H</b>); Well L5, 2500.05 m, matrix-supported conglomerate (<b>I</b>).</p>
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<p>Main sedimentary structure types of shallow water delta in the Haian Depression. Well AN16, 3450.77 m, small erosion surface, transitional bedding (<b>A</b>); Well AF7, 2223.60 m, scouring surface (<b>B</b>); Well L2, 1910.70 m, gray fine sandstone, plate cross-bedding, wavy cross-bedding (<b>C</b>); Well L5, 2194.70 m, parallel bedding, wavy crossbedding (<b>D</b>); Well L5, 2192.35 m, flush surface, light gray fine sandstone (<b>E</b>); Well L5, 2192.10 m, overlying scour, small trough cross-bedding (<b>F</b>); Well L5, 2191.23 m, overlying scour, wavy crossbedding (<b>G</b>); Well L10, 2187.60 m, overlap scour (<b>H</b>); well L10, 2186.13 m, overlap scour (<b>I</b>); well L10, 2184.45 m, wavy cross-bedding, plate cross-bedding, parallel bedding (<b>J</b>); Well L6, 2026.50 m, overlap scour (<b>K</b>); well AN1, 2448.93 m, wavy cross-bedding (<b>L</b>).</p>
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<p>Particle size characteristics of E<sub>1</sub>f<sub>3</sub> in the Haian Sag. Particle size characteristics of E<sub>1</sub>f<sub>3</sub> in the Haian Sag. C-M map of E1f3 traction flow deposit in the Haian Depression (<b>A</b>); E<sub>1</sub>f<sub>3</sub> grain size probability cumulative curve of the Haian Depression (<b>B</b>).</p>
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<p>Core facies analysis of single well E<sub>1</sub>f<sub>3</sub> shallow water delta front sub-facies in the Haian Depression.</p>
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<p>Different sedimentary microfacies curves during the E<sub>1</sub>f<sub>3</sub> deposition period in the Haian Sag. Underwater distributary channels (<b>A</b>); Natural underwater levees (<b>B</b>); Diversion Bay (<b>C</b>); Estuary sand bars (<b>D</b>); Predelta mud (<b>E</b>).</p>
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<p>Schematic diagram of seismic facies of E<sub>1</sub>f<sub>3</sub> in the Haian Depression. (Line P1-P2 is shown in <a href="#minerals-15-00075-f001" class="html-fig">Figure 1</a>B).</p>
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<p>Coupling effect of paleogeomorphic core feature parameters on sand control.</p>
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<p>Contour map of sandstone thickness (<b>A</b>) and percentage content (<b>B</b>) of E<sub>1</sub>f<sub>3</sub><sup>2-2</sup>+ E<sub>1</sub>f<sub>3</sub><sup>3-1</sup> sand formation in the Haian Depression.</p>
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<p>Contour map of sandstone thickness (<b>A</b>) and percentage content (<b>B</b>) of the E<sub>1</sub>f<sub>3</sub><sup>2-1</sup> sand formation in the Haian Depression.</p>
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<p>Contour map of sandstone thickness (<b>A</b>) and percentage content (<b>B</b>) of the E<sub>1</sub>f<sub>3</sub><sup>1-3</sup> sand formation in the Haian Depression.</p>
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<p>Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub> key sand formation in the Haian Depression. Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>2-2</sup> + E<sub>1</sub>f<sub>3</sub><sup>3-1</sup> sand formation in the Haian Depression (<b>A</b>); Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>2-1</sup> sand formation in the Haian Depression (<b>B</b>); Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>1-3</sup> sand formation in the Haian Depression (<b>C</b>).</p>
Full article ">Figure 21 Cont.
<p>Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub> key sand formation in the Haian Depression. Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>2-2</sup> + E<sub>1</sub>f<sub>3</sub><sup>3-1</sup> sand formation in the Haian Depression (<b>A</b>); Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>2-1</sup> sand formation in the Haian Depression (<b>B</b>); Sedimentary facies plan of the E<sub>1</sub>f<sub>3</sub><sup>1-3</sup> sand formation in the Haian Depression (<b>C</b>).</p>
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<p>E<sub>1</sub>f<sub>3</sub> sedimentary facies model in the Haian Depression.</p>
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17 pages, 3556 KiB  
Article
Quantification of Soil–Water Erosion Using the RUSLE Method in the Mékrou Watershed (Middle Niger River)
by Rachid Abdourahamane Attoubounou, Hamidou Diawara, Ralf Ludwig and Julien Adounkpe
ISPRS Int. J. Geo-Inf. 2025, 14(1), 28; https://doi.org/10.3390/ijgi14010028 - 14 Jan 2025
Abstract
Despite nearly a century of research on water-related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet, to date, data on water erosion needed to develop mitigation strategies are scarce, especially in [...] Read more.
Despite nearly a century of research on water-related issues, water erosion remains one of the greatest threats to soil health and soil ecosystem services around the world. Yet, to date, data on water erosion needed to develop mitigation strategies are scarce, especially in the Sahelian regions. The current study therefore sets out to estimate annual soil losses caused by water erosion and to analyze trends over the period of 1981–2020 in the Mékrou watershed, located in the Middle Niger river sub-basin in West Africa. The Revised Universal Soil Loss Equation, remote sensing, and the Geographic Information System (GIS) were deployed in this study. Several types of data were used, including rainfall data, sourced from meteorological stations and reanalysis datasets, which capture the temporal variability of erosive forces. Soil properties, including texture and organic matter content, were derived from FAO global soil databases to assess soil erodibility. High-resolution digital elevation models (30 m) provided detailed topographic information, crucial for calculating slope length and steepness factors. Land use and land cover data were extracted from satellite imagery, enabling the analysis of vegetation cover and anthropogenic impacts over four decades. By integrating and treating these data, this study reveals that the estimated average annual amount of water erosion in the Mékrou watershed is 6.49 t/ha/yr over 1981–2020. The dynamics of the ten-year average are highly variable, with a minimum of 3.45 t/ha/yr between 1981 and 1990, and a maximum of 8.50 t/ha/yr between 1991 and 2000. Even though these average soil losses in the Mékrou basin are below the tolerable threshold of 10 t/ha/yr, mitigation actions are needed for prevention. In addition, the spatial dynamics of water erosion are noticeably heterogeneous. The study reveals that 72.7% of the surface area of the Mékrou watershed is subject to slight water erosion below the threshold, compared with 27.3%, particularly in the mountainous south-western part, which is subject to intense erosion above the threshold. This research is the first study of soil erosion quantification with the RUSLE method and GIS in the Mékrou watershed, and fills a critical knowledge gap of the water erosion in this watershed, providing insights into erosion dynamics and supporting future sustainable land management strategies in vulnerable Sahelian landscapes. Full article
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Figure 1
<p>Mékrou watershed in Middle Niger.</p>
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<p>The workflow of the study in the Mékrou watershed.</p>
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<p>A soil map of the Mékrou watershed.</p>
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<p>Yearly average precipitation in the Mékrou watershed.</p>
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<p>The temporal evolution of the erosivity factor (R) in the Mékrou watershed.</p>
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<p>The spatial distribution of water erosion factors (R, K, LS, C and P) in the Mékrou basin.</p>
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<p>The temporal dynamics of water erosion at decadal intervals within the Mékrou watershed.</p>
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<p>The spatiotemporal dynamics of water erosion within the Mékrou watershed.</p>
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15 pages, 5122 KiB  
Article
Strength Tests and Mechanism of Composite Stabilized Lightweight Soil Using Dredged Sludge
by Qizhi Hu, Zitian Li, Qiang Ma, Junjie Li and Wei Yao
Materials 2025, 18(2), 348; https://doi.org/10.3390/ma18020348 - 14 Jan 2025
Abstract
To achieve resourceful utilization of dredged sludge, lightweight treatment was performed on sludge from Xunsi River in Wuhan using fly ash, cement, and expanded polystyrene (EPS) particles. Density tests and unconfined compressive strength (UCS) tests were conducted on the composite stabilized sludge lightweight [...] Read more.
To achieve resourceful utilization of dredged sludge, lightweight treatment was performed on sludge from Xunsi River in Wuhan using fly ash, cement, and expanded polystyrene (EPS) particles. Density tests and unconfined compressive strength (UCS) tests were conducted on the composite stabilized sludge lightweight soil to determine the optimal mix ratio for high-quality roadbed fill material with low self-weight and high strength. Subsequently, microstructural tests, including X-ray diffraction (XRD) and scanning electron microscopy (SEM), were conducted. The Particle (Pore) and Crack Analysis System (PCAS) was used to analyze the SEM images, investigating the cement–fly ash composite stabilization mechanism. The experimental results showed that the optimal lightweight treatment was achieved with an EPS content of 80% (by volume ratio to dry soil), cement content of 7.5% (by mass ratio to dry soil), and fly ash content of 5% (by mass ratio to dry soil). The density of the optimized lightweight soil was 1.04 g/cm3, a reduction of 28.27% compared to the density of raw sludge soil (1.45 g/cm3). The UCS increased significantly from 110 kPa for raw sludge soil to 551 kPa. The addition of fly ash enhanced the hydration and secondary hydration reactions between cement and sludge, generating more calcium silicate hydrate (C-S-H) gel, which filled the larger pores between the EPS particles and soil particles, as well as those between the soil particles themselves, making the structure denser. Compared to single cement stabilization, composite stabilization resulted in a lower content of expansive ettringite crystals, a more uniform pore distribution, fewer pores, and a lower surface porosity ratio. These research findings can provide theoretical support and practical references for the lightweight treatment of dredged sludge in the Yangtze River Basin of Central China. Full article
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<p>Test materials: (<b>a</b>) dredged silt, (<b>b</b>) dried dredged silt [<a href="#B20-materials-18-00348" class="html-bibr">20</a>], (<b>c</b>) EPS particles.</p>
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<p>Test Instruments: (<b>a</b>) density test, (<b>b</b>) UCS test.</p>
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<p>Density Variation Curve Under Different EPS Contents.</p>
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<p>Density Variation Curve Under Different Fly Ash Contents.</p>
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<p>Stress–Strain Curve for Different Fly Ash Contents at Different EPS Contents: (<b>a</b>) EPS content 60%, (<b>b</b>) EPS content 80%, (<b>c</b>) EPS content 100%.</p>
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<p>Effect of EPS Content on Unconfined Compressive Strength Curve.</p>
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<p>Effect of Fly Ash Content on Unconfined Compressive Strength Curve.</p>
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<p>XRD Pattern of Stabilized Soil.</p>
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<p>SEM Images of Lightweight Soil: (<b>a</b>) cement stabilized (500 times), (<b>b</b>) composite stabilized (50 times), (<b>c</b>) composite stabilized (500 times), (<b>d</b>) composite stabilized (2000 times).</p>
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<p>SEM Image Processing of Composite Stabilized Lightweight Soil: (<b>a</b>) SEM image, (<b>b</b>) binarization, (<b>c</b>) vectorization.</p>
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<p>SEM Image Processing of Cement Stabilized Lightweight Soil: (<b>a</b>) SEM image, (<b>b</b>) binarization, (<b>c</b>) vectorization.</p>
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<p>Schematic Diagram of Composite Stabilization Mechanism.</p>
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21 pages, 3535 KiB  
Review
Coal-Hosted Al-Ga-Li-REE Deposits in China: A Review
by Yanbo Zhang, Xiangyang Liu and Wei Zhao
Minerals 2025, 15(1), 74; https://doi.org/10.3390/min15010074 - 14 Jan 2025
Viewed by 120
Abstract
Investigation of the critical metal elements in coal and coal-bearing strata has become one of the hottest research topics in coal geology and coal industry. Coal-hosted Ga-Al-Li-REE deposits have been discovered in the Jungar and Daqingshan Coalfields of Inner Mongolia, China. Gallium, Al, [...] Read more.
Investigation of the critical metal elements in coal and coal-bearing strata has become one of the hottest research topics in coal geology and coal industry. Coal-hosted Ga-Al-Li-REE deposits have been discovered in the Jungar and Daqingshan Coalfields of Inner Mongolia, China. Gallium, Al, and Li in the Jungar coals have been successfully extracted and utilized. This paper reviews the discovery history of coal-hosted Ga-Al-Li-REE deposits, including contents, modes of occurrence, and enrichment origin of critical metals in each coal mine, including Heidaigou, Harewusu, and Guanbanwusu Mines in the Jungar Coalfield and the Adaohai Coal Mine in the Daqingshan Coalfield, as well as the recently reported Lao Sangou Mine. Gallium and Al in the coals investigated mainly occur in kaolinite, boehmite, diaspore, and gorceixite; REEs are mainly hosted by gorceixite and kaolinite; and Li is mainly hosted by cholorite. Gallium, Al, and REEs are mainly derived from the sediment-source region, i.e., weathered bauxite in the Benxi Formation. In addition, REE enrichment is also attributed to the intra-seam parting leaching by groundwater. Lithium enrichment in the coals is of hydrothermal fluid input. The content of Al2O3 and Ga in coal combustions (e.g., fly ash) is higher than 50% and ~100 µg/g, respectively; concentrations of Li in these coals also reach the cut-off grade for industrial recovery (for example, Li concentration in the Haerwusu coals is ~116 µg/g). Investigations of the content, distribution, and mineralization of critical elements in coal not only provide important references for the potential discovery of similar deposits but also offer significant coal geochemical and coal mineralogical evidence for revealing the geological genesis of coal seams, coal seam correlation, the formation and post-depositional modification of coal basins, regional geological evolution, and geological events. Meanwhile, such investigation also has an important practical significance for the economic circular development of the coal industry, environmental protection during coal utilization, and the security of critical metal resources. Full article
(This article belongs to the Section Mineral Geochemistry and Geochronology)
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<p>Location of the Jungar and Daqingshan Coalfields (<b>A</b>) and distribution of the Guanbanwusu, Heidaigou, and Haerwusu Mines in the Jungar Coalfield (<b>B</b>) [<a href="#B49-minerals-15-00074" class="html-bibr">49</a>].</p>
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<p>Minerals in the No. 6 coal from the Heidaigou mine, Jungar Coalfield. (<b>A</b>) Boehmite, goethite, and rutile; (<b>B</b>) boehmite and rutile. SEM back-scattered electron images.</p>
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<p>Fusinite and inertodetrinite in the No. 6 Coal from the Haerwusu mine, Jungar Coalfield, using reflected light and oil immersion. (<b>A</b>): Fusinite and inertodetrinite; (<b>B</b>) Fusinite and inertodetrinite. The width of the photo is 500 µm.</p>
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<p>Boehmite, kaolinite, and pyrite in the No. 6 Coal from the Haerwusu mine, Jungar Coalfield, using reflected light. (<b>A</b>) Boehmite and kaolinite in the fusinite cells. (<b>B</b>) Boehmite and pyrite in the fusinite cells. The width of the photo is 500 µm.</p>
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29 pages, 10143 KiB  
Article
Identifying Key Nodes and Enhancing Resilience in Grain Supply Chains Under Drought Conditions
by Shuiwang Zhang and Chuansheng Zhou
Systems 2025, 13(1), 49; https://doi.org/10.3390/systems13010049 - 14 Jan 2025
Viewed by 202
Abstract
Grain supply chains remain stable in the face of natural disasters, and the resilience of the grain supply chain plays an important role. In a complex scenario of exposure to shocks, it is significant to identify the critical nodes of the grain supply [...] Read more.
Grain supply chains remain stable in the face of natural disasters, and the resilience of the grain supply chain plays an important role. In a complex scenario of exposure to shocks, it is significant to identify the critical nodes of the grain supply chain and propose countermeasures accordingly to enhance the resilience of the grain supply chain. In this paper’s study, firstly, a triangular model of contradictory events is used to describe complex scenarios and obtain Bayesian network nodes. Secondly, the fragmentation of the scenario is based on the description of the scene, the scene stream is constructed, the event network is obtained, and the Bayesian network structure is built on the basis. Then, combining expert knowledge and D–S evidence theory, the Bayesian network parameters are determined, and the Bayesian network model is built. Finally, the key nodes of the grain supply chain are identified in the context of the 2022 drought data in the Yangtze River Basin in China, and, accordingly, a strategy for improving the resilience of the grain supply chain is proposed in stages. This study provides a new research perspective on issues related to grain supply-chain resilience and enriches the theoretical foundation of research related to supply-chain resilience. Full article
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<p>Triangular model of contradictory events.</p>
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<p>Schematic of causality.</p>
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<p>Schematic diagram of coupling relations.</p>
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<p>Scene flow.</p>
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<p>Scenario-driven Bayesian network modeling.</p>
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<p>Probability benchmark.</p>
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<p>Scene fragments and scene flows.</p>
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<p>Merger of E<sub>2</sub> and E<sub>3</sub> Bayesian networks.</p>
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<p>Overall Bayesian network structure.</p>
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<p>S1, S2, S3 Bayesian network node relationships.</p>
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<p>S3 node conditional probability synthesis results.</p>
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<p>Bayesian network inference.</p>
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<p>Prevention phase sensitivity analysis.</p>
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<p>Parent node change difference analysis.</p>
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<p>Antagonistic phase sensitivity analysis.</p>
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<p>Analysis of variation difference of the crop disaster area.</p>
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<p>Recovery phase sensitivity analysis.</p>
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<p>The cumulative share of influence of each organization at each stage.</p>
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19 pages, 3067 KiB  
Article
Nitrogen Transformation Mechanisms and Compost Quality Assessment in Sustainable Mesophilic Aerobic Composting of Agricultural Waste
by Lin Zhao, Yuhan Huang, Xue Ran, Yuwei Xu, Yuanyuan Chen, Chuansheng Wu and Jun Tang
Sustainability 2025, 17(2), 575; https://doi.org/10.3390/su17020575 - 13 Jan 2025
Viewed by 296
Abstract
This study examines nitrogen transformation mechanisms and compost quality in mesophilic aerobic composting of wheat straw, utilizing cow manure as a co-substrate to promote sustainable agricultural waste management. Two composting systems were established: group A (control) and group B (10% cow manure addition [...] Read more.
This study examines nitrogen transformation mechanisms and compost quality in mesophilic aerobic composting of wheat straw, utilizing cow manure as a co-substrate to promote sustainable agricultural waste management. Two composting systems were established: group A (control) and group B (10% cow manure addition by wet weight). The addition of cow manure accelerated early organic matter decomposition and increased total nitrogen retention in group B. Nitrogen losses occurred primarily via ammonia volatilization during the initial and final composting stages, while functional gene analysis revealed enhanced ammonification and nitrification in both systems. Microbial community analysis showed that cow manure addition promoted nitrogen-fixing bacteria in the early phase and fungi associated with complex organic degradation in later stages. These findings underscore the potential of cow manure to enhance compost maturity, improve nitrogen efficiency, and support the development of sustainable composting practices that contribute to resource conservation. Full article
(This article belongs to the Section Sustainable Agriculture)
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<p>Variations in physicochemical parameters during the composting. (<b>a</b>) Temperature variation trends; (<b>b</b>) Moisture content variation trends; (<b>c</b>) pH variation trends; (<b>d</b>) Electrical conductivity variation trends.</p>
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<p>Changes in the content of representative carbon and nitrogen compounds during the composting process. (<b>a</b>) Organic matter content variation trend; (<b>b</b>) Ammonia nitrogen content and ammonia volatilization trend; (<b>c</b>) Total nitrogen content variation trend; (<b>d</b>) Total organic carbon content variation trend; (<b>e</b>) Carbon-to-nitrogen ratio variation trend; (<b>f</b>) T-value variation trend.</p>
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<p>The heavy metal content and maturity of composting samples. (<b>a</b>) Trend of As content; (<b>b</b>) Trend of Hg content; (<b>c</b>) Trend of Pb content; (<b>d</b>) Trend of Cd content; (<b>e</b>) Trend of Cr content; (<b>f</b>) Germination index of Chinese cabbage seeds and amaranth seeds.</p>
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<p>Profiles of microbial community during composting. Bacterial communities at phylum level (<b>a</b>), genus level (<b>b</b>); fungal communities at phylum level (<b>c</b>), genus level (<b>d</b>).</p>
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<p>Abundance of functional genes involved in carbon and nitrogen metabolism predicted by PICRUSt2. (<b>a</b>) The abundance of pathways related to “Degradation/Utilization/Assimilation” in fungi base on the MetaCyc database. (<b>b</b>) The abundance of pathways involved in carbon and nitrogen metabolism in bacteria based on the KEGG database. (<b>c</b>) The abundance of pathways related to “Degradation/Utilization/Assimilation” in bacteria based on the MetaCyc database. (<b>d</b>) The abundance of genes involved in nitrogen transformation of bacteria based on the KEGG database.</p>
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<p>Correlation analyses. Correlation networks between environmental factors and dominant bacteria of group A (<b>a</b>) and group B (<b>b</b>), respectively. Correlation networks between environmental factors and dominant fungi of group A (<b>c</b>) and group B (<b>d</b>), respectively.</p>
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20 pages, 5521 KiB  
Article
Impact of Urbanization on Water Resource Competition Between Energy and Food: A Case Study of Jing-Jin-Ji
by Kuan Liu, Lichuan Wang, Jiaqi Zhai, Yong Zhao, Haodong Deng and Xing Li
Sustainability 2025, 17(2), 571; https://doi.org/10.3390/su17020571 - 13 Jan 2025
Viewed by 280
Abstract
Water resources, energy, and food are important resources in China, which play an important role in the process of urban development and are important basic resources for sustainable urban development. This study applied water footprint theory to water–energy–food relations. The regional integration of [...] Read more.
Water resources, energy, and food are important resources in China, which play an important role in the process of urban development and are important basic resources for sustainable urban development. This study applied water footprint theory to water–energy–food relations. The regional integration of the Jing-Jin-Ji region faced new challenges during urbanization, and unified measures were applied to quantify the urban water demands and energy and food competition in the Jing-Jin-Ji region from 2003 to 2017. The index was used to evaluate the intensity of the competition for water for food and energy. The results indicated that from 2003 to 2017, the water footprint of grain production in the Jing-Jin-Ji region decreased from 30.984 billion m3 to 21.36 billion m3, of which the blue water footprint decreased from 13.032 billion m3 to 9.854 billion m3. The water footprint of energy production increased from 578 million m3 to 1.175 billion m3. The competition relation between cities in the Jing-Jin-Ji region was obtained according to the competition index, and corresponding measures were identified according to different competition levels. This study provides valuable insights for policymakers in designing sustainable urban development strategies for cities facing similar challenges of water resource, energy, and food competition during rapid urbanization. Full article
(This article belongs to the Special Issue Sustainable Water Management in Rapid Urbanization)
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<p>The spatial distribution of study area.</p>
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<p>Urbanization level of Jing-Jin-Ji region.</p>
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<p>Methodological framework for water footprint analysis and water resources competition intensity index.</p>
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<p>Analysis of the spatiotemporal distribution and evolution trends of food water footprint in the Jing-Jin-Ji region from 2003 to 2017.</p>
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<p>Analysis of the spatiotemporal distribution and evolution trends of energy water footprint in the Jing-Jin-Ji Region from 2003 to 2017.</p>
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<p>Indicators of competition between food and energy production for water.</p>
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<p>The Jing-Jin-Ji regional urban zoning.</p>
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26 pages, 5937 KiB  
Article
A Novel Method to Forecast Nitrate Concentration Levels in Irrigation Areas for Sustainable Agriculture
by Halil Karahan and Müge Erkan Can
Agriculture 2025, 15(2), 161; https://doi.org/10.3390/agriculture15020161 - 13 Jan 2025
Viewed by 382
Abstract
This study developed an ANN-based model to predict nitrate concentrations in drainage waters using parameters that are simpler and more cost-effective to measure within the Lower Seyhan Basin, a key agricultural region in Turkey. For this purpose, daily water samples were collected from [...] Read more.
This study developed an ANN-based model to predict nitrate concentrations in drainage waters using parameters that are simpler and more cost-effective to measure within the Lower Seyhan Basin, a key agricultural region in Turkey. For this purpose, daily water samples were collected from a drainage measurement station during the 2022 and 2023 water years, and nitrate concentrations were determined in the laboratory. In addition to nitrate concentrations, other parameters, such as flow rate, EC, pH, and precipitation, were also measured simultaneously. The complex relationship between measured nitrate values and other parameters, which are easier and less costly to measure, was used in two different scenarios during the training phase of the ANN-Nitrate model. After the model was trained, nitrate values were estimated for the two scenarios using only the other parameters. In Scenario I, random values from the dataset were predicted, while in Scenario II, predictions were made as a time series, and model results were compared with measured values for both scenarios. The proposed model reliably fills dataset gaps (Scenario I) and predicts nitrate values in time series (Scenario II). The proposed model, although based on an artificial neural network (ANN), also has the potential to be adapted for methods used in machine learning and artificial intelligence, such as Support Vector Machines, Decision Trees, Random Forests, and Ensemble Learning Methods. Full article
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<p>Location of the study area in Turkiye, irrigation and drainage water flow directions, and the water sampling station (Drainage gauging station).</p>
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<p>The correlation relationship between NO<sub>3</sub> and model parameters.</p>
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<p>The temporal variation in nitrate concentrations and model inputs.</p>
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<p>A three-layer feed-forward ANN.</p>
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<p>The typical structure of multi-layer ANNs used in this study.</p>
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<p>Model results for Scenario I.</p>
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<p>Model results for Scenario I.</p>
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<p>Model results for Scenario I.</p>
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<p>Model results for Scenario I.</p>
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<p>Model results for Scenario II.</p>
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<p>Model performance for Scenario II.</p>
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<p>Model results for Scenario II.</p>
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<p>Model performance for Scenario II.</p>
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22 pages, 5098 KiB  
Article
Optimization of Development Strategies and Injection-Production Parameters in a Fractured-Vuggy Carbonate Reservoir by Considering the Effect of Karst Patterns: Taking C Oilfield in the Tarim Basin as an Example
by Mengqin Li, Qi Wang, Chao Yao, Fangfang Chen, Qinghong Wang and Jing Zhang
Energies 2025, 18(2), 319; https://doi.org/10.3390/en18020319 - 13 Jan 2025
Viewed by 248
Abstract
The spatial structural characteristics of fractured-vuggy units vary greatly in different karst patterns, which significantly influence the study of remaining oil distribution patterns in ultra-deep fractured-vuggy reservoirs and the determination of the most efficient development strategies. However, few numerical simulation studies have focused [...] Read more.
The spatial structural characteristics of fractured-vuggy units vary greatly in different karst patterns, which significantly influence the study of remaining oil distribution patterns in ultra-deep fractured-vuggy reservoirs and the determination of the most efficient development strategies. However, few numerical simulation studies have focused on improving water and gas injection in fractured-vuggy reservoirs by considering the effect of karst patterns. By taking a typical fractured-vuggy reservoir in C oilfield in Tarim Basin, China as an example, the development dynamic characteristics of eight typical fractured-vuggy units in three different karst patterns are analyzed, and based on the newly proposed numerical simulation method of fluid vertical equilibrium, the residual oil reservoir distribution in different karst pattern fractured-vuggy units are studied, and the effects of fracture-vuggy karst patterns on the development characteristics, on the remaining oil morphology pattern, on the development strategies, and on the injection-production parameters are explored. This study shows that for different karst patterns fractured-vuggy units, the complexity of spatial structure, reserve scale, and oil-water relationship aggravates the heterogeneity of reservoirs and results in substantial differences in the development of dynamic patterns. In the northern facing karst fractured-vuggy units, there are two main types of remaining oil: well-spacing type and local-blocking type, and the reasonable development strategies are affected by reservoir morphology and the connectivity of structure patterns. Attic-type remaining oil mainly occurs in platform margin overlay and fault-controlled karst fractured-vuggy units. In the southern fault-controlled karst area, the remaining oil is mostly found along the upper part, and periodic gas injection or N2 huff-n-puff is recommended with priority for potential tapping. The fractured-vuggy karst patterns show a significant influence on the optimal level of injection-production parameters for improving the development of gas injection development strategies. The ideas of improving water injection and gas injection for fracture-vuggy reservoirs proposed in this paper also provide a good reference to further improve water control and increase oil production in other similar carbonate reservoirs. Full article
(This article belongs to the Section H: Geo-Energy)
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<p>Planar distribution karst zone of Lianglitage Formation in C oilfield.</p>
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<p>Vertical distribution of typical fractured-vuggy units under different karst patterns: (<b>a</b>) bedding karst; (<b>b</b>) platform margin overlay and fault-controlled karst; (<b>c</b>) fault-controlled karst.</p>
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<p>Dynamic curves of C3-O producer in bedding karst fractured-vuggy unit.</p>
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<p>Dynamic curve of C5-O producer in platform margin overlay-controlled fractured-vuggy unit.</p>
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<p>Dynamic curve of C7-O producer in fault-controlled fractured-vuggy unit.</p>
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<p>Fluid distribution of C3 fractured-vuggy unit after production history matching.</p>
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<p>Incremental oil recovery of C3 fractured-vuggy unit by gas or water injection.</p>
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<p>Fluid distribution evolution during WAG injection in C3 fractured-vuggy unit.</p>
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<p>Dynamic responses of C3 fractured-vuggy unit via gas or water injection.</p>
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<p>Fluid distribution of C5 fractured-vuggy unit after production history matching.</p>
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<p>Incremental oil recovery of C5 fractured-vuggy unit by gas or water injection.</p>
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<p>Fluid distribution evolution during N<sub>2</sub> huff-n-puff in C5 fractured-vuggy unit.</p>
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<p>Dynamic responses of C5 fractured-vuggy unit by gas or water injection.</p>
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<p>Fluid distribution of C7 fractured-vuggy unit after production history matching.</p>
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<p>Incremental oil recovery of C7 fractured-vuggy unit by gas or water injection.</p>
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<p>Fluid distribution evolution during periodic gas injection in C7 fractured-vuggy unit.</p>
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<p>Dynamic responses of C7 fractured-vuggy unit by gas or water injection.</p>
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<p>Influence of different injection-production parameters on incremental oil recovery of WAG injection in C3 fractured-vuggy unit.</p>
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<p>Influence of different injection-production parameters on incremental oil recovery by N<sub>2</sub> huff-n-puff in C5 fractured-vuggy unit.</p>
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<p>Influence of different injection-production parameters on incremental oil recovery of periodic gas injection in C7 fractured-vuggy unit.</p>
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17 pages, 3835 KiB  
Article
U-Pb and Hf Isotopic Analyses for Detrital Zircon of the Danzhou Group in the Western Jiangnan Orogenic Belt and Tectonic Implications
by Jingna Liu, Xianglin Huang, Xiyue Xia and Xiuping Li
Minerals 2025, 15(1), 70; https://doi.org/10.3390/min15010070 - 13 Jan 2025
Viewed by 266
Abstract
In order to better constrain the specific depositional age and provenance of the Danzhou Group and understand the geological evolution of the Jiangnan Orogenic Belt, we conducted a combined U-Pb and Hf-isotope analysis of detrital zircons from the Gongdong and Hetong formations of [...] Read more.
In order to better constrain the specific depositional age and provenance of the Danzhou Group and understand the geological evolution of the Jiangnan Orogenic Belt, we conducted a combined U-Pb and Hf-isotope analysis of detrital zircons from the Gongdong and Hetong formations of the Danzhou Group in the Longsheng area of the Western Jiangnan Orogenic Belt. Detrital zircons from the Gongdong Formation yield three age populations of 2658–2517 Ma, 2427–1678 Ma and 891–781 Ma, and the youngest ages suggest that the sedimentation began after ca. 783 Ma. U-Pb ages of detrital zircons from the Hetong Formation yield major populations at 2769–2502 Ma, 2492–2100 Ma, and 991–731 Ma, and the youngest ages redefine the maximum depositional age of this unit is 760 Ma, much younger than previously considered. Thus, the upper part of the Hetong Formation in the Longsheng area is newly subdivided into the Sanmenjie Formation, which is characterized by a large amount of 765–761 Ma volcanic rocks. The dominant 991–731 Ma detrital zircons for all samples were likely sourced from the Neoproterozoic igneous rocks of the southeast margin of the Yangtze Block. The subordinate 2494–1678 Ma detrital zircons were probably sourced from the Cathaysia Block. Minor amounts of 2769–2502 Ma detrital zircons may have been sourced from the Yangtze Block. Detrital zircons from the Gongdong Formation have mainly negative εHf (t) values (−1.1 to 21.8, 90%), suggesting that the detritus of the Gongdong Formation is dominated by the recycling of old crustal materials. The εHf (t) values of detrital zircons from the Hetong Formation have a large spread of −22.2 to +9.7, indicating that the source material of the Hetong Formation includes both the juvenile crustal materials and the recycled ancient crustal materials. The above age populations and Hf isotopic characteristics are consistent with the magmatic rocks in the Jiangnan Orogenic Belt and the Southeast Yangtze Block. Taking into account the lithostratigraphic features, provenances, and depositional ages, the Danzhou Group in the Western Jiangnan Orogenic Belt was deposited in a back-arc basin. Full article
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<p>(<b>a</b>) Geological sketch map of the Jiangnan Orogenic Belt in the South China Block (modified after Yao et al. [<a href="#B9-minerals-15-00070" class="html-bibr">9</a>]); (<b>b</b>) Sketch geological map of the Longsheng area (Guilin, Guangxi) with sampling location (modified after GXRGST [<a href="#B22-minerals-15-00070" class="html-bibr">22</a>,<a href="#B23-minerals-15-00070" class="html-bibr">23</a>]). The yellow part of (<b>a</b>) is South China Block.</p>
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<p>Stratigraphic column of the Neoproterozoic Danzhou Group in the Longsheng area (modified after GXRGST [<a href="#B23-minerals-15-00070" class="html-bibr">23</a>]).</p>
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<p>Field photographs and photomicrographs of the meta-sedimentary rock of the Danzhou Group from the Longsheng area. (<b>a</b>,<b>b</b>) Quartz sandstone (Sample LM01-1) from the Gongdong Formation. (<b>c</b>,<b>d</b>) Metamorphic siltstone (Sample XL03-1) from the Hetong Formation. Qtz—quartz, Pl—plagioclase.</p>
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<p>Representative cathodoluminescence (CL) of dated zircons from samples of the Gongdong and Hetong formations. The small solid circles denote the sites of U-Pb age analyses, and the large, dashed circles denote the sites of Hf isotope analyses.</p>
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<p>Th/U ratios of zircon grains from sample LM01-1 and XL03-1 (modified after Rubatto et al. [<a href="#B52-minerals-15-00070" class="html-bibr">52</a>]).</p>
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<p>U-Pb Concordia age and probability density plots (PDPs) and proportions of detrital zircons of the Gongdong and Hetong formations in the Danzhou Group. Blue PDPs fills: Neoproterozoic zircon ages; Orogen PDPs fills: Paleoproterozoic zircon ages; Yellow PDPs fills: Archean zircon ages; Gray PDPs fills: Triassic zircon ages.</p>
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<p>Hf isotopic features for detrital zircon through stratigraphy in the Danzhou Group. (<b>a</b>) εHf (t) versus age for detrital zircon from the Gongdong Formation. (<b>b</b>) Probability density plots of <span class="html-italic">T</span><sub>DM</sub><sup>C</sup> age of the detrital zircon from the Gongdong Formation. (<b>c</b>) εHf (t) versus age for detrital zircon from the Hetong Formation. (<b>d</b>) Probability density plots of <span class="html-italic">T</span><sub>DM</sub><sup>C</sup> age of the detrital zircon from the Hetong Formation. DM—depleted mantle; CHUR—chondritic uniform reservoir.</p>
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<p>Cumulative probability curves diagram of detrital zircons age from the Gongdong and Hetong formations in the Longsheng area (modified after Cawood et al. [<a href="#B70-minerals-15-00070" class="html-bibr">70</a>]). Orange—A: convergent basin, Blue—B: collisional basin, Green—C: extensional basin.</p>
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22 pages, 5461 KiB  
Article
Projecting Water Yield Amidst Rapid Urbanization: A Case Study of the Taihu Lake Basin
by Rui Zhou, Yanan Zhou, Weiwei Zhu, Li Feng and Lumeng Liu
Land 2025, 14(1), 149; https://doi.org/10.3390/land14010149 - 13 Jan 2025
Viewed by 221
Abstract
Changes in land cover and land use (LULC) can impact water availability by altering the structure and functioning of land ecosystems. Accurately projecting the impacts of LULC on water yield (WY) is of utmost importance for regional landscape management. Taking the rapidly urbanizing [...] Read more.
Changes in land cover and land use (LULC) can impact water availability by altering the structure and functioning of land ecosystems. Accurately projecting the impacts of LULC on water yield (WY) is of utmost importance for regional landscape management. Taking the rapidly urbanizing Taihu Lake Basin (TLB) as an example, coupled with the PLUS-InVEST model, three scenarios of a natural development (ND) scenario, urban development (UD) scenario, and ecological protection (EP) scenario were set to simulate the response mechanisms of land use changes for WY and the influence of policy-making on the water conservation capacity of river basins. (1) During 2000 and 2020, the Taihu Lake Basin (TLB) experienced rapid urbanization, which was evident in the conversion of forest and cropland for urban development. (2) From 2000 to 2020, the TLB’s WY first decreased and then increased, ranging from 201.52 × 108 m3 to 242.70 × 108 m3. Spatially, an uneven distribution pattern of WY depth emerged, with mountainous and hilly regions exhibiting higher WY compared to plain areas. Temporally, changes in total WY were primarily influenced by precipitation, while areas with increased WY showed a certain correlation with regions experiencing an expansion of construction land. (3) By 2030, the TLB will continue to expand construction land under the UD scenario, while the area of ecological land will expand under the EP scenario. WY is expected to vary across scenarios, with the highest yield observed under the UD scenario, followed by the ND scenario, while the EP scenario exhibits the lowest yield. These findings can offer scientifically informed insights and guidance for future WY changes, carrying substantial effects for maintaining ecological preservation and promoting high-quality development in the TLB. Full article
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<p>Geographical location and water distribution of the TLB.</p>
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<p>Flowchart for evaluating the spatiotemporal patterns of WY under multiple future scenarios in the TLB.</p>
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<p>The proportions of land use types under three future scenarios.</p>
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<p>Changes in LULC types in the TLB from 2000 to 2020.</p>
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<p>LULC transfer Sankey map for 2000—2020 (km<sup>2</sup>).</p>
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<p>Comparison of the 2020 forecasted results and actual situation.</p>
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<p>LULC changes in the TLB in 2030 under different scenarios.</p>
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<p>Water yield and the precipitation in the TLB from 2000 to 2020.</p>
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<p>WY depths of different LULC types.</p>
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<p>WY changes in the TLB under different scenarios.</p>
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14 pages, 6053 KiB  
Article
The Source and Significance of Silicon in the Late Permian Dalong Formation, Northeastern Sichuan Basin
by Xiaotong Ge, Xun Ge, Daizhao Chen, Yali Liu, Ruyue Wang and Min Li
Minerals 2025, 15(1), 69; https://doi.org/10.3390/min15010069 - 13 Jan 2025
Viewed by 227
Abstract
The Late Permian was a critical interval in geological history, during which dramatic changes occurred in the Earth’s surface system, and a set of black rock series rich in organic matter and silicon, the Dalong Formation, was deposited in the northeastern Sichuan Basin. [...] Read more.
The Late Permian was a critical interval in geological history, during which dramatic changes occurred in the Earth’s surface system, and a set of black rock series rich in organic matter and silicon, the Dalong Formation, was deposited in the northeastern Sichuan Basin. We conducted a detailed sedimentological and petrological investigation integrated with (major and trace) element contents in the deep-water sequence of the Xibeixiang and Jianfeng sections. It demonstrates the source of silicon, tectonic background, and sedimentary environment of the Dalong Formation, and explores the influence of hydrothermal activities on organic matter enrichment. The results show that the upper part of the Dalong Formation contained more radiolarians in the Xibeixiang section compared to the Jianfeng section. Hydrothermal proxies such as Eu/Eu*, Al-Fe-Mn diagram, Al/(Al + Fe + Mn), and LuN/LaN suggest a biotic origin for the chert in the Dalong Formation in the Xibeixiang and Jianfeng sections, while the Xibeixiang section was slightly affected by hydrothermal activities. The La-Th-Sc diagram and the La/Sc and Ti/Zr crossplots point to a continental island arc and active continental margin origins for the Xibeixiang and Jianfeng sections. Combined with previous research, the silicon of the Dalong Formation in the northeastern Sichuan Basin is mainly derived from biological sources. The Xibeixiang section was affected by a small amount of hydrothermal fluid due to its proximity to the Paleo-Tethys Ocean and continental island arcs. Furthermore, the enrichment of organic matter was predominantly driven by high productivity, with minimal impact from hydrothermal activities. These insights hold significant research value and practical implications for shale gas exploration in the Sichuan Basin. Full article
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<p>Paleogeographic map of South China during the deposition period of the Dalong Formation, showing the location of the Xibeixiang and Jianfeng sections (modified from [<a href="#B11-minerals-15-00069" class="html-bibr">11</a>]).</p>
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<p>(<b>a</b>) The lithological column of the Xibeixiang section. Photomicrographs under plane-polarized light show (<b>b</b>) ampelitic limestone in the middle part of the Dalong Formation, (<b>c</b>) bedded chert bearing large numbers of radiolarians in the upper part of the Dalong Formation, and (<b>e</b>) lime mudstone in the uppermost Dalong Formation. (<b>d</b>) The limestone lens of the upper part of the Dalong Formation. (<b>f</b>) Ammonite fossils in the upper part of the Dalong Formation. (<b>g</b>) The photomacrograph of the Permian-Triassic boundary (PTB). A standing person for scale (1.65 m).</p>
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<p>(<b>a</b>) Lithological column of the Jianfeng section. (<b>b</b>) Photomicrographs under plane-polarized light show carbonaceous limestone in the middle part of the Dalong Formation. (<b>c</b>) Volcanic ash in the middle Dalong Formation. (<b>d</b>) Photomicrographs under plane-polarized light show bedded chert bearing large numbers of radiolarians in the upper part of the Dalong Formation. See <a href="#minerals-15-00069-f002" class="html-fig">Figure 2</a> for legends.</p>
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<p>Al-Fe-Mn diagram of the Dalong Formation in the (<b>a</b>) Xibeixiang and (<b>b</b>) Jianfeng sections (after reference [<a href="#B15-minerals-15-00069" class="html-bibr">15</a>]).</p>
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<p>Chemostratigraphic profiles for the hydrothermal proxies of Dalong Formation in the Xibeixiang section. See <a href="#minerals-15-00069-f002" class="html-fig">Figure 2</a> for legends. The dotted line represents the boundary of the condition, as explained in detail in the text.</p>
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<p>Post-Archean Australian shale (PAAS)-normalized REE pattern of the siliceous rock in the Dalong Formation at (<b>a</b>) the Xibeixiang section and (<b>b</b>) the Jianfeng section.</p>
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<p>Chemostratigraphic profiles for the hydrothermal proxies of the Dalong Formation in the Jianfeng section. See <a href="#minerals-15-00069-f002" class="html-fig">Figure 2</a> for legends.</p>
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<p>La-Th-Sc diagram of Dalong cherts at (<b>a</b>) the Xibeixiang section and (<b>b</b>) the Jianfeng section (base map after reference [<a href="#B29-minerals-15-00069" class="html-bibr">29</a>]).</p>
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<p>Cross-plot between La/Sc and Ti/Zr of Dalong cherts at (<b>a</b>) the Xibeixiang section and (<b>b</b>) the Jianfeng section (base map after reference [<a href="#B29-minerals-15-00069" class="html-bibr">29</a>]).</p>
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<p>Cross-plot between TOC and indicators of hydrothermal activities in (<b>a</b>–<b>d</b>) the Xibeixiang section and (<b>e</b>–<b>h</b>) the Jianfeng section.</p>
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