Geoderma最新文献

{"title":"Predicting the soil bulk density using a new spectral PTF based on intact samples","authors":"","doi":"10.1016/j.geoderma.2024.117005","DOIUrl":"10.1016/j.geoderma.2024.117005","url":null,"abstract":"<div><p>Sample collection and measurement of soil bulk density (BD) are often labor-intensive and expensive in large regions. Conversely, soil spectra are easy to measure and facilitate BD prediction. However, the literature suggests that the damage to the physical structure of soil during scanning spectra on the ground and/or sieved samples might hinder the capacity of spectral technology to accurately predict BD. In addition, because some soil properties that have high correlations with BD, such as the soil organic matter (SOM), are routinely measured and available in most soil databases, coupling them with soil spectra may improve BD prediction compared to using soil properties or spectra. Therefore, in this study, we propose a novel spectral pedo-transfer function (spectral PTF) that couples the measured visible and near-infrared spectra of soils on intact samples and other soil properties to accurately predict the BD (BD = f (soil spectra, soil properties)), which is different from the traditional PTF that uses only soil properties (BD = f (soil properties)) or spectra alone (BD = f (soil spectra)). In this study, we collected topsoil (0–20 cm) and subsoil (20–40 cm) samples from 586 sites in Northeast China, covering a large area of 1.09 million km² characterized by black soils with high SOM contents. Five routinely measured soil properties were selected: SOM, moisture content (MC), Sand, Silt, and Clay, and various spectral PTFs with one, two, and three soil properties were calibrated using the partial least square regression. The cross-validation results show that the traditional PTF can only predict BD for subsoil with an R² of 0.51 and an RMSE of 0.11 g·cm⁻³ when using SOM + MC + Silt or SOM + MC. Compared to subsoil, topsoil and all layers (topsoil + subsoil) had a lower BD prediction accuracy, and a saturation effect was observed for BD values above 1.5 g·cm⁻³. Unexpectedly, the soil spectra did not provide a higher BD prediction accuracy than traditional PTFs, although the spectra were measured on intact samples. However, adding soil properties to the spectral PTF improved the prediction accuracy and saturation effect for high BD values. The optimal spectral PTF with a single soil property (MC) showed an acceptable BD prediction performance with R²≥0.49, RPD&gt;1.4, and RPIQ&gt;1.7 regardless of whether the sample was topsoil, subsoil, or all layers. Furthermore, the spectral PTF with two or three soil properties yielded a slightly better prediction performance and a more stable prediction among different combinations of soil properties. These results indicate that soil properties and spectra are irreplaceable for BD prediction. Our study demonstrates the potential of spectral PTFs for the accurate prediction of BD and offers insights into the prediction of other soil properties using soil spectra.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002349/pdfft?md5=ec7c5e79bab36b1060d226e4233d16e5&pid=1-s2.0-S0016706124002349-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141986334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Labile not stable SOC fractions constitute the manageable drivers of soil health advances in carbon farming","authors":"","doi":"10.1016/j.geoderma.2024.116991","DOIUrl":"10.1016/j.geoderma.2024.116991","url":null,"abstract":"<div><p>The assessment of soil health and the determination of carbon stability in soils are current challenges that have gained momentum through initiatives at national as well as international scales. However, inferring universally valid soil health parameters that are directly linked to carbon permanence remains challenging. Our aim was to evaluate the potential of simultaneous thermal analysis (STA) for an improved monitoring of soil health advances in the context of carbon farming strategies. For this purpose, an on-farm comparison of soil health in ten conservation agricultural systems with adjacent conventional farms was performed based on STA and thermal measures were related to key biological and physical indicators for monitoring soil functions. Using an autocorrelation-based approach, we identified independent thermal indicators, revealing that carbon farming efforts predominantly increased labile soil organic matter fractions in the range of 300–400 °<span><math><mi>C</mi></math></span>, while thermally more recalcitrant fractions did not respond to farming system transformation. Similarly, most soil health indicators revealed highest correlation with temperature ranges of mass loss of labile organic matter fractions. The relation of STA with commonly used soil health indicators was highest for soil organic carbon (SOC, <span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>971</mn></mrow></math></span>) and total nitrogen (TN, <span><math><mrow><mi>r</mi><mo>=</mo><mn>0</mn><mo>.</mo><mn>981</mn></mrow></math></span>). However, also inference on microbial activity parameters such as dimethylsulfoxid reduction, microbial biomass carbon and substrate-induced respiration could be demonstrated with <span><math><mrow><mi>r</mi><mo>&gt;</mo><mn>0</mn><mo>.</mo><mn>663</mn></mrow></math></span>. The results thus highlight key temperature ranges of organic matter stability for future soil monitoring tasks of climate change mitigation potentials of carbon farming and related advances in soil health.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002209/pdfft?md5=0f84492cfd359647f97364a3017b48a5&pid=1-s2.0-S0016706124002209-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141985219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving global soil moisture prediction through cluster-averaged sampling strategy","authors":"","doi":"10.1016/j.geoderma.2024.116999","DOIUrl":"10.1016/j.geoderma.2024.116999","url":null,"abstract":"<div><p>Understanding and predicting global soil moisture (SM) is crucial for water resource management and agricultural production. While deep learning methods (DL) have shown strong performance in SM prediction, imbalances in training samples with different characteristics pose a significant challenge. We propose that improving the diversity and balance of batch training samples during gradient descent can help address this issue. To test this hypothesis, we developed a Cluster-Averaged Sampling (CAS) strategy utilizing unsupervised learning techniques. This approach involves training the model with evenly sampled data from different clusters, ensuring both sample diversity and numerical consistency within each cluster. This approach prevents the model from overemphasizing specific sample characteristics, leading to more balanced feature learning. Experiments using the LandBench1.0 dataset with five different seeds for 1-day lead-time global predictions reveal that CAS outperforms several Long Short-Term Memory (LSTM)-based models that do not employ this strategy. The median Coefficient of Determination (R²) improved by 2.36 % to 4.31 %, while Kling-Gupta Efficiency (KGE) improved by 1.95 % to 3.16 %. In high-latitude areas, R² improvements exceeded 40 % in specific regions. To further validate CAS under realistic conditions, we tested it using the Soil Moisture Active and Passive Level 3 (SMAP-L3) satellite data for 1 to 3-day lead-time global predictions, confirming its efficacy. The study substantiates the CAS strategy and introduces a novel training method for enhancing the generalization of DL models.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002283/pdfft?md5=7b7a5fc5b0181bfd9cd70f884cf867ba&pid=1-s2.0-S0016706124002283-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974334","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Plant responses to nitrate and ammonium availability in Australian soils as measured by diffusive gradients in thin-films (DGT) and KCl extraction","authors":"","doi":"10.1016/j.geoderma.2024.116997","DOIUrl":"10.1016/j.geoderma.2024.116997","url":null,"abstract":"<div><p>Determining soil nitrogen (N) availability is essential in agriculture to minimise over-application, maximise growers’ returns and reduce potential environmental consequences. The present study assesses soil mineral N (nitrate-N and ammonium-N) using the diffusive gradients in thin-films (DGT) technique against the conventional potassium chloride (KCl) extraction. The DGT technique has demonstrated reliable predictability for plant-available P, Cu and Zn. However, the use of DGT to quantify soil N bioavailability is underreported and N measurements made with DGT have not been compared to plant growth responses or N uptake. A pot trial using wheat was performed to determine the suitability of the DGT technique to predict N plant uptake and plant biomass. Four contrasting soil types from South Australia were used, and four rates of N were applied to the soil. DGT devices and KCl extraction were used at sowing to measure soil mineral N. These data were then compared with plant relative yield (<em>Y</em>_R) and N uptake after harvesting the plants. Soil mineral N, as measured by both the DGT and KCl extraction techniques, demonstrated a significant positive correlation with <em>Y</em>_R, with an <em>R</em>² value of 0.6; however, DGT-N extracted comparatively more nitrate (NO₃^–, &gt;87 % of C_N) than KCl-N (65 % of E_N). Mineral N and NO₃^– extracted by both DGT and KCl significantly correlated with plant N uptake albeit this correlation was stronger for KCl (<em>R</em>² = 0.8) than DGT (<em>R</em>² = 0.6). The same parameters also positively and significantly correlated with <em>Y</em>_R, however in this case, both correlations were similar and only modest (<em>R</em>² &lt; 0.6 in all cases). These results are explained in terms of the differences between the pools of N accessed by these techniques and limitations related to soil N dynamics. In conclusion, KCl showed similar or better predictive ability for N uptake and yield response (<em>Y</em>_R) in wheat compared to DGT across four Australian soils. Given its low cost and ease of application, KCl presents a competitive advantage in this study.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S001670612400226X/pdfft?md5=cd5222447b030bfb5f3cc5a4e7b8ff13&pid=1-s2.0-S001670612400226X-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141979088","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"On the parsimony, interpretability and predictive capability of a physically−based model in the optical domain for estimating soil moisture content","authors":"","doi":"10.1016/j.geoderma.2024.116996","DOIUrl":"10.1016/j.geoderma.2024.116996","url":null,"abstract":"<div><p>Soil moisture plays an important role in the transpiration, evaporation and plant growth processes at the land surface-atmosphere interface. Optical remote sensing has great potential for the retrieval of surface soil moisture content (SMC), with many empirical data-driven models or physical models developed to address this issue. Nevertheless, most data-driven models face the challenge of poor interpretability, while the application of many existing physical models is limited by complicated calibration steps. The aim of this work is to validate the potential of a physically-based approach based on the Kubelka-Munk (KM) radiative transfer theory to strike a balance between physical significance and practical applicability in the optical estimation of SMC. Specifically, an adequate and heterogeneous soil dataset in Jianghan Plain, China was used to calibrate the model wavelength by wavelength under laboratory conditions. The performance of the approach (at the optimal band) was compared with several commonly used methods. The effect of soil organic matter (SOM) on the estimation of SMC was also investigated by validating the model transferability between subsets with different SOM levels. Results showed that there were two local optimal bands at around 1460 and 1940 nm in the full band analysis of the approach, and the performance at around 1940 nm is better or comparable to linear regression, logarithmic regression, and spectral index models. Although partial least squares regression (PLSR) could achieve higher prediction accuracy with the enrichment of band information, this approach stood out for its balance of model parsimony with single-band calibration, model interpretability with the incorporation of physical mechanisms and predictive capability. More importantly, we found that the approach could enhance the spectral sensitivity in the water absorption region, avoid negative predictions at low SMCs, and reduce the interference effect of SOM on the estimation of SMC, probably due to the physical constraints inside the approach. This paper demonstrates the parsimony, interpretability, and predictive capability of the physically-based approach in the optical estimation of SMC, and provides new insights into the application of this approach in the airborne/satellite imaginary spectroscopy sensing of SMC.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002258/pdfft?md5=a62189e9c900e258ba6b12d559e42f18&pid=1-s2.0-S0016706124002258-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974324","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Specific root length regulated the rhizosphere effect on denitrification across distinct macrophytes","authors":"","doi":"10.1016/j.geoderma.2024.117002","DOIUrl":"10.1016/j.geoderma.2024.117002","url":null,"abstract":"<div><p>Macrophytes influence nitrogen (N) removal from wetlands. However, the specific plant traits responsible for this effect and the related microbial mechanisms remain largely unknown, especially root traits. In a mesocosm experiment, we determined the rhizosphere effect (RE) on microbial N removal processes by incubating rhizosphere and bulk soils collected from 11 macrophyte species. In addition, we examined root traits (involved in chemistry and morphology), along with examining the diversity, compositions, and abundance of bacterial communities involved in denitrification (<em>nirS</em> and <em>nirK</em>) and anammox (<em>hzsB</em>). Across the 11 macrophyte species, the positive RE on denitrification ranged from 66% to 412%, with an average of 194.72%. RE on denitrification was significantly and positively correlated with the recruitment of <em>nir-type</em> denitrifiers in the rhizosphere. We found that higher specific root length (SRL) root promoted the stronger RE, by increasing the abundance of <em>nir</em>-type denitrifiers and further enhancing N removal. Net N removal from water in the wetlands increased with a higher positive RE on <em>nir-type</em> denitrifiers. In addition, SRL significantly influenced the compositions of denitrifiers in the rhizosphere soil. We further found that the enrichment of <em>Azospira</em>, <em>Bradyrhizobium</em>, <em>Sinorhizobium</em>, <em>Rhodopseudomonas</em>, Alcaligenaceae, Bradyrhizobiaceae, and <em>Pleomorphomonas</em> improved the denitrification rate. These findings highlight the potential of root morphology in regulating plant–microbe interactions, thereby improving water purification.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002313/pdfft?md5=ae5949ef90c62cb9919a6c981c1c1104&pid=1-s2.0-S0016706124002313-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141974333","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights on soil carbon cycling in intercropped maize-forage systems as affected by nitrogen","authors":"","doi":"10.1016/j.geoderma.2024.116998","DOIUrl":"10.1016/j.geoderma.2024.116998","url":null,"abstract":"<div><p>Intercropping maize with forage grasses is an economical and environmentally sound practice that is increasingly being adopted to enhance resilience in tropical agriculture. Although intensifying integrated cropping systems can increase the sequestration of carbon (C) from plant residues, it also unleashes priming of old soil C enhancing C cycling, particularly under nitrogen (N) fertilization. However, the extent of these competing processes in intercropped maize–forage systems is poorly understood. This four-year study assessed whether new C inputs from maize (<em>Zea mays</em>) intercropped with ruzigrass (<em>Urochloa ruziziensis</em>), palisade grass (<em>Urochloa brizantha</em>), or Guinea grass (<em>Megathyrsus maximum</em>) in the presence or absence of N fertilization affect soil aggregation and C cycling in the soil and within macroaggregates (&gt;0.250 mm) and microaggregates (&lt;0.250 mm) down the soil profile. C cycling was assessed by measuring variations in the abundance of the natural isotope ¹³C. N fertilization of the intercropped maize–forage systems reduced the proportion of aggregates &gt; 2 mm and the mean weight diameter of aggregates by reducing soil pH. Under N fertilization, the geometric mean diameter of aggregates were 42 % larger under palisade than under Guinea grass. New C inputs from intercropping maize with forage grasses promoted C cycling in bulk soil, particulate organic matter (POM), mineral-associated organic matter (MAOM), and macro- and microaggregates, although these effects were restricted to topsoil. No N fertilization increased ruzigrass C input into MAOM with no clear link with ¹³C enrichment, suggesting that N fertilization does not impair C stabilization in this pool. Aggregates &gt;2 mm and &gt;0.5 mm were key sinks of C and N up to a soil depth of 40 cm in this intercropped system. Our findings provide insights into the extension of C cycling across SOM pools and aggregates, and the role of N management in intercropping maize forage systems.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002271/pdfft?md5=31d57b3efe481a7f04a6b70002b44cd7&pid=1-s2.0-S0016706124002271-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141915343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Land use selectively impacts soil carbon storage in particulate, water-extractable, and mineral-associated forms across pedogenetic horizons","authors":"","doi":"10.1016/j.geoderma.2024.116992","DOIUrl":"10.1016/j.geoderma.2024.116992","url":null,"abstract":"<div><p>Improved understanding of land use derived changes in soil organic matter (OM) compartments stabilized to different degrees against microbial decomposition is required for outlining efficient land use strategies aimed at improving soil ecosystem functions that are strongly coupled to gains and losses of soil organic carbon (OC). However, such data is scarce, particularly in subsoil environments. Consequently, in this study, we analyzed OC storage in topsoils and subsoils, as well as OM fractions with different OC turnover dynamics, including particulate (free and occluded), water-extractable, and mineral-associated OM. We sampled soils under native prairie (10 sites) and long-term arable use (&gt; 40 years, 10 sites) to a depth of 3 m in the central U.S. Our results showed that the arable bulk soils had significantly lower OC content in the A horizon and across all analyzed OM fractions compared to native prairie soils. This reduction was primarily derived from OC losses in the mineral-associated OM (arable: 7.2 ± 0.5 g kg⁻¹; native prairie: 12 ± 0.7 g kg⁻¹), which retained the most significant portion (50–56 %) of bulk soil OC among all fractions. No significant impact of land use on OC storage in the bulk soil and fractions was observed in the subsoil B and C horizons, except for water-extractable OM, which had lower amounts in arable soils in the C horizon than native prairie soils. This underscores the relevance of this fraction for the translocation of OC across the soil profile in undisturbed systems. Our results highlight the crucial role of mineral-associated OM for soil OC storage, but also its sensitivity to land use change, especially in the topsoil, suggesting this fraction is highly relevant for strategies aiming at restoring pre-disturbance soil OC levels.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002210/pdfft?md5=17d47de67d100823cd550be868cab6b2&pid=1-s2.0-S0016706124002210-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141904887","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Soil organic matter properties drive microbial enzyme activities and greenhouse gas fluxes along an elevational gradient","authors":"","doi":"10.1016/j.geoderma.2024.116993","DOIUrl":"10.1016/j.geoderma.2024.116993","url":null,"abstract":"<div><p>Mountain ecosystems, contributing substantially to the global carbon (C) and nitrogen (N) biogeochemical cycles, are heavily impacted by global changes. Although soil respiration and microbial activities have been extensively studied at different elevation, little is known on the relationships between environmental drivers, microbial functions, and greenhouse gas fluxes (GHGs; carbon dioxide [CO₂], methane [CH₄] and nitrous oxide [N₂O]) in soils of different elevation. Here, we measured how <em>in situ</em> GHG fluxes were linked to soil properties, soil organic matter (SOM) quantity and composition (the proportion of humic-like vs. protein-like OM), microbial biomass, enzyme activities and functional gene abundances in natural soils spanning an elevational gradient of ∼2400 m in Switzerland. Soil CO₂ fluxes did not significantly vary from low (lowland zone) to higher (montane and subalpine zones) elevation forests, but decreased significantly (P&lt;0.001) from the treeline to the mountain summit. Multivariate analyses revealed that CO₂ fluxes were controlled by C-acquiring enzymatic activities which were mainly controlled by air mean annual temperature (MAT) and SOM quantity and composition. CH₄ fluxes were characterized by uptake of atmospheric CH₄, but no trend was observed along the elevation. N₂O fluxes were also dominated by uptake of atmospheric N₂O. The flux rates remained stable with increasing elevation below the treeline, but decreased significantly (P&lt;0.001) from the treeline to the summit. N₂O fluxes were driven by specific nitrifying and denitrifying microbial genes (ammonia-oxidizing <em>amo</em>A and N₂O-producing <em>nor</em>B), which were again controlled by SOM quantity and composition. Our study indicates the treeline as a demarcation point changing the patterns of CO₂ and N₂O fluxes along the elevation, highlighting the importance of SOM quantity and composition in controlling microbial enzyme activities and GHG fluxes.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002222/pdfft?md5=131bffdda8976171dd460357e7dc457a&pid=1-s2.0-S0016706124002222-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141904763","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Agricultural land abandonment linked to pipe collapse and gully development: Reconstruction from archival SfM and LiDAR datasets","authors":"","doi":"10.1016/j.geoderma.2024.116995","DOIUrl":"10.1016/j.geoderma.2024.116995","url":null,"abstract":"<div><p>Land use and land cover changes such as agricultural land abandonment along with soil erosion are perceived to be important factors that add to land degradation worldwide. In this study, we used aerial imagery, archival-Structure from Motion (SfM) reconstruction and airborne-LiDAR surveys to reconstruct land abandonment along with pipe collapse and gully development in a semi-arid Mediterranean catchment area of the Ebro Valley (Spain) during 1957–2021. Agricultural land dynamics were analysed from the study of planform changes to field crops. Land degradation associated to pipe collapse and gully development was inferred from the geomorphic change detection deduced from the comparison of topographic models obtained from archival-SfM and LiDAR datasets. Through spatial correlation analysis, we identified that higher, steeper, and more hydrologically connected field crop areas were the first to be abandoned. Additionally, the extent of pipe collapses and gullying processes was significantly correlated with the degree of land abandonment over the duration of the study period. Our findings reveal that approximately 20 % of agricultural lands within the study area were abandoned during said study period, with up to 15 % of the abandoned area directly impacted by pipe collapse and gullying processes. Erosion rates associated with these processes within the catchment, implied erosion areas of 3.9 ha and 1.5 ha for the period 1977–2009 and 2009–2021, ranging between 120 Mg/ha yr⁻¹ and 203.2 Mg/ha yr⁻¹, respectively. Our study highlights that abandonment in said area is predominantly conditioned by land degradation resulting from pipe collapses and gully development. The recognition and protection of piping and gully affected areas as geodiversity sites is presented as an alternative at a local level to mitigate the economic impacts of soil degradation. Understanding the effects that pipe collapse and gully development have on arable lands over long-term study periods (i.e., &gt;50 years) is essential in order to shed light on the interconnected factors influencing land productivity and agricultural sustainability. This ultimately guides us to make informed policy decisions that mitigate these detrimental effects.</p></div>","PeriodicalId":12511,"journal":{"name":"Geoderma","volume":null,"pages":null},"PeriodicalIF":5.6,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S0016706124002246/pdfft?md5=db89ea9683fe51b58f62bb46b7207824&pid=1-s2.0-S0016706124002246-main.pdf","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141895736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"农林科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}