https://www.frontiersin.org/journals/soil-science RSS Feed for Frontiers in Soil Science | New and Recent Articles en-us Frontiers Feed Generator,version:1 2026-05-03T16:19:13.669+00:00 60 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1777598 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1777598 2026-04-30T00:00:00Z Original Research Tom KünnemannPatrice CannavoVincent GuérinRené Guénon https://www.frontiersin.org/articles/10.3389/fsoil.2026.1771112 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1771112 2026-04-29T00:00:00Z Original Research Sandra E. Rivas-MoralesRicardo Romero-ArguellesAntonio Guzmán-VelascoJosé I. González-RojasAlina Olalla-KerstuppAntonio Leija-TristanEsther E. Rios-del ToroAndres Abellán-BorjaDavid Valladares-SánchezGabriel Ruiz-AymaMayra A. Gomez-Govea 10 years; LPF), representing a site-based chronosequence rather than a replicated temporal trajectory. Bacterial communities were characterized using 16S rRNA amplicon sequencing (Illumina MiSeq) and analyzed with QIIME1. Soil physicochemical properties, including pH, moisture, texture, organic matter, and salinity, were also measured. ResultsTime-since-fire categories, along with pH and elevation gradients, were associated with differences in community composition. Although approximately 50% of taxa were shared among conditions, burned and unburned soils differed in the relative abundance of Actinobacteria and Acidobacteria, as well as in the occurrence of low-abundance taxa with reported thermotolerant and pollutant-degrading traits. Co-occurrence network analysis revealed differences in network structure between burned and unburned communities, although these results should be interpreted cautiously due to their correlational nature. Several genera commonly reported in post-fire environments, including Massilia, Arthrobacter, and Blastococcus, were detected. Notably, Arthrobacter and Blastococcus were part of the core microbiome, with Arthrobacter also showing differential abundance and high connectivity in unburned soil networks. Additional taxa of interest included Actinobacteria genera such as Gaiella, Jiangella, Krasilnikovia, Mycobacterium, and Rubrobacter, as well as the Proteobacteria genus Lysobacter.DiscussionCollectively, these findings highlight bacterial taxa associated with wildfire-affected soils and provide insights into microbial community shifts across post-fire chronosequences. These results may support future microbiome-based approaches for the management and restoration of fire-prone ecosystems.]]> https://www.frontiersin.org/articles/10.3389/fsoil.2026.1767992 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1767992 2026-04-27T00:00:00Z Original Research Gulom BekmirzaevRaxmontoy KurvantayevKasimbek IsabaevAbdurakhim BerdishevQosim RakhmonovSabirjan IsaevSunnat TadjievUmida ParpievaAzam AzimovJakhongir KhamraqulovSanoatxon ZakirovaMuhabbat DiyorovaElyor MalikovAbbosbek Akhmadaliyev https://www.frontiersin.org/articles/10.3389/fsoil.2026.1799970 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1799970 2026-04-27T00:00:00Z Original Research Evangelia A. KoukianakiMaria A. LilliRoberta FarinaSilvia VaninoCarlos Alberto Torres GuerreroEduardo Garcia BragaNikolaos P. Nikolaidis 250 μm) reflecting soil structural stability and resilience. The CAST model successfully simulated SOC turnover and aggregate fractions since the uncertainty of the simulation due to carbon input was low, demonstrating in this way its value for Monitoring, Reporting, and Verification (MRV) within CF schemes.]]> https://www.frontiersin.org/articles/10.3389/fsoil.2026.1752540 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1752540 2026-04-23T00:00:00Z Original Research Vojtěch PoláchSneha PatraDaniel RůžičkaViktor NagyVendula KoublováKarel Klem https://www.frontiersin.org/articles/10.3389/fsoil.2026.1768147 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1768147 2026-04-22T00:00:00Z Original Research Andrea Martín-PabloMilagros NavarroDomingo Javier López-RoblesDaniel Pérez-AlonsoRocío BarrosCarlos RadOscar AguadoGonzalo Sacristán-Pérez-Minayo https://www.frontiersin.org/articles/10.3389/fsoil.2026.1755770 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1755770 2026-04-22T00:00:00Z Original Research Floyd Muyembe ChipatelaLotfi KhiariAmine KassamOtmane RajiHamza Jouichat https://www.frontiersin.org/articles/10.3389/fsoil.2026.1736046 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1736046 2026-04-21T00:00:00Z Original Research Amine KassamLotfi KhiariIsmail KoueraHamza Jouichat https://www.frontiersin.org/articles/10.3389/fsoil.2026.1744337 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1744337 2026-04-15T00:00:00Z Original Research Khalid HussainJohn-Paul FoxAudrey H. BeanyLukas M. HallmanLorenzo Rossi https://www.frontiersin.org/articles/10.3389/fsoil.2026.1800936 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1800936 2026-04-15T00:00:00Z Original Research Falilou DialloKaramoko DiarraFrédéric Feder 0.1). These results indicate that OWP type and dose influence carrot growth, marketable quality, and susceptibility to pests and diseases through amendment-specific properties related to nutrient supply, moisture conditions, and probable biological interactions. Repeated applications of PL-2 resulted in the maintenance of a high proportion of first category roots over several cycles, while concurrently limiting pests and diseases pressure.ConclusionThis finding underscores the significance of judicious selection and optimisation of the type of organic matter applied.]]> https://www.frontiersin.org/articles/10.3389/fsoil.2026.1786422 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1786422 2026-04-15T00:00:00Z Original Research Henry Díaz-ChuquizutaLuis Fernando Manrique GonzalesMartín Sánchez OjanastaJuan Pablo Cuevas-GiménezBoris MartínezGeiner Flores SintiJuan Jose Kerry TanchivaGeomar Vallejos-Torres https://www.frontiersin.org/articles/10.3389/fsoil.2026.1809945 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1809945 2026-04-15T00:00:00Z Original Research Jing QiuJiemei LyuXiaolin WangYong Sik OkErik MeersHaichao Li 0.5). In contrast, mild extraction (water and CaCl2) released less DOC (5–15 mg L-¹) but preserved high-aromaticity components with larger molecular weights. Fluorescence analysis identified four distinct BDOM components: (1) a terrestrial humic-like substance (C4) preferentially extracted by water, (2) a fulvic-like component (C2) dominant in NaCl and SPLP extracts, (3) a protein-like component (C1) most abundant in NaCl extract, and (4) a transitional component (C3) that decreased under acidic conditions. The results demonstrate that extraction method influences BDOM quantity, optical characteristics, and compositional features, providing a useful framework for understanding BDOM behavior and informing the environmental management of invasive plant.]]> https://www.frontiersin.org/articles/10.3389/fsoil.2026.1717364 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1717364 2026-04-15T00:00:00Z Original Research Thiago de Carvalho Alexandre PereiraGabriel Augusto Teixeira DevolioCassiano Garcia RoqueRita de Cássia Félix AlvarezCid Naudi Silva CamposMayara Fávero CotrimRenato de Mello PradoRoberto Andreani JuniorGisele Herbst VazquezAndréa Cristiane SanchesAcacio Aparecido Navarrete https://www.frontiersin.org/articles/10.3389/fsoil.2026.1737123 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1737123 2026-04-14T00:00:00Z Original Research Lorena Estefani Romero-ChávezNilton A. Hermoza AymeRodolfo Chuchon-RemonUriel Aldava-PardaveRosa K. Arroyo-IsuizaRichard Solórzano AcostaGeomar Vallejos-Torres https://www.frontiersin.org/articles/10.3389/fsoil.2026.1780422 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1780422 2026-04-13T00:00:00Z Original Research Ping LiXuran LiPeng HeJingshu WangChenbo YangZelong YaoRutian BiLishuai XuHongfen ZhuFan Yang https://www.frontiersin.org/articles/10.3389/fsoil.2026.1806071 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1806071 2026-04-10T00:00:00Z Original Research Jianyong MiaoLan LiuFeifei SongHaishuan SunXiaodong DingJun Wang https://www.frontiersin.org/articles/10.3389/fsoil.2026.1773062 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1773062 2026-04-10T00:00:00Z Original Research Cheng YaofeiMo RixiongShi HaorongZheng Jian’anZhou YaoyaoWang ChenhaoYu Guanlong https://www.frontiersin.org/articles/10.3389/fsoil.2026.1783700 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1783700 2026-04-08T00:00:00Z Correction Gobinath RajendranVijayakumar ShanmugamAruna LakshminarayananLone Aabid HussainBiju JosephVipin KumarAnil Kumar PantAjith SPrasad Babu MBBMahendra Kumar RapoluSundaram Raman Meenakshi https://www.frontiersin.org/articles/10.3389/fsoil.2026.1754188 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1754188 2026-03-27T00:00:00Z Original Research Chen SunGuolong HuaiBin WangJiusheng SunLei Cui https://www.frontiersin.org/articles/10.3389/fsoil.2026.1745154 https://www.frontiersin.org/articles/10.3389/fsoil.2026.1745154 2026-03-26T00:00:00Z Original Research Wilian Salazar-CoronelCarlos Carbajal-LlosaRodolfo Chuchon-Remon 0.7%) in areas with greater vegetation density, within a semi-arid context where SOC levels are generally low. In contrast, lower areas exhibited reduced SOC contents (< 0.6%). The uncertainty analysis indicated that SOC predictions had high to moderate confidence (PIR < 0.2) in the middle-and upper zones of the basin, and moderate confidence (0.1–0.2) in the lower areas. The results suggest that machine learning and ensemble methods improve SOC prediction, benefiting the sustainable management of soil fertility and quality in arid and semi-arid ecosystems of northern Peru.]]>