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2,078 results for “soil data”
Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method
<p>Данные мониторинга микробиологического разложения хвойного опада сосны в почвах Московской области по методу ICP IM</p> <p>Data of microbiological decomposition monitoring of pine coniferous litter in the soils at the Moscow region by the ICP IM method</p> <p> </p> <p>Исследования проведены на базе двух особо охраняемых природных территориях (далее ООПТ) в Московской области и г. Москве, расположенных на расстоянии 90 км друг от друга. На обеих ООПТ работы проводились на постоянных пробных площадках (ППП) площадью 1 га.</p> <p>Эталон – Приокско-Террасный государственный природных биосферный заповедник. В заповеднике заложены 4 ППП, расположенные в бассейне малой реки Тоденка, большая часть бассейна которой находится в границах Заповедника. ППП расположены не далее 2 км от русла реки, в преобладающих по площади в ООПТ типах лесах: сосняке сложном (две ППП), березняке сложном широкотравном и дубраве широкотравной. В сосняках Заповедника были заложены 2 ППП, различающиеся по увлажнению и месторасположению, на террасе и на коренном берегу.</p> <p>Модельная находится под более высокой антропогенной нагрузкой в г. Москве с лесопарковая часть природно-исторического парка «Кузьминки-Люблино» (далее – Лесопарк), имеющая также схожий с Заповедником рельеф и породный состав лесов. Территории Заповедника и Лесопарка имеют сходство физико-географических условий формирования: обе ООПТ расположены на надпойменных террасах крупных рек Волжского бассейна (рек Оки и Москвы соответственно), на обеих территориях формируются слабо дифференцированные дерново-подзолистые почвы ржавоземы на флювиогляциальных песках (Brunic Arenosols) под сосновыми и березовыми лесами. Основные физико-химические свойства почв Лесопарка соответствуют естественным аналогам.</p> <p><strong>Метод изучения скорости разложения опада.</strong> Методической основой проводимых измерений скорости биоразложения опада является метод подпрограммы «MB Microbial decomposition» программы ICP IM [https://www.syke.fi/en-US/Research__development/Nature/Monitoring/Integrated_Monitoring/Manual_for_Integrated_Monitoring] с некоторыми изменениями.</p> <p>Изменения методики касались срока экспозиции. Мы использовали стандартный срок экспозиции в 1 год и отказались от экспозиции иголок более 1 года, как рекомендовано в методике ICP IM. Такая модификация метода позволила существенно сократить трудозатраты при получении сравнимых результатов.</p> <p>Измерение разложения опада проводились методом закладки конвертов из нейлоновой сетки 8 на 8 см с ячеей 1 мм с упакованными в них пробами на срок 1 год. Конверты запечатывались металлическими скобами. Пробы закладывались и снимались в последней декаде октября – начале ноября. В таблицах и тексте год указывается по году снятия образца, соответственно, пробы, заложенные в 2013 г. и собранные в 2014 г. относятся к 2014 г.</p> <p>Согласно методике, в экспериментах по изучению разложения опада использовались иголки сосны обыкновенной (<em>Pinus</em> <em>sylvestris</em> L.), которые собирались с ветвей невысоких деревьев (10–20 лет) в одном и том же квартале Заповедника и только пожелтевшие, перед их массовым опадом (обычно в начале октября). Предварительно все пробы высушивались до абсолютно сухого веса при 85 <sup>0</sup>С и взвешивались перед упаковкой в конверты. Взвешивание осуществлялось с точностью до 0.001 г, вес проб соснового опада 1 г.</p> <p>Конверты каждый год раскладывались на каждой ППП размерами 100×100 м возле углов и в центре пробных площадей в пределах квадрата 3×3 м в фиксированных точках. Конверты располагались в верхних 5 см почвы, под углом в 15<sup>0</sup>, под моховым покровом (при его наличии) или подстилкой и привязывались леской для удобства поиска. Не допускалось размещение конверта в приствольном круге деревьев. После экспозиции в течение 12 месяцев (350–380 суток) конверты снимались, а содержимое проб аккуратно с использованием пинцета промывалось дистиллированной водой от твердых частиц субстрата и мицелия грибов до остатков иголок и высушивалось до абсолютно сухого веса. Измерение потери массы каждой пробы проводилось методом взвешивания с точностью 0.001 г. Ежегодно закладывалось по 5 проб на каждой ППП в сосняке и березняке, но через год не всегда удавалось найти все заложенные конверты, так как происходили ветровалы и иные нарушения. На ППП в дубняке закладывалось по 10 конвертов.</p>
Data from: eDNA metabarcoding of log hollow sediments and soils highlights the importance of substrate type, frequency of sampling and animal size, for vertebrate species detection
<p>Fauna monitoring often relies on visual monitoring techniques such as camera trappings, which have biases leading to underestimates of vertebrate species diversity. Environmental DNA (eDNA) has emerged as a new source of biodiversity data that may improve biomonitoring; however, eDNA based assessments of species richness remain relatively untested in terrestrial environments. We investigated the suitability of fallen log hollow sediment as a source of vertebrate eDNA, across two sites in south-western Australia - one with a Mediterranean climate and the other semi-arid. We compared two different approaches (camera trapping and eDNA metabarcoding) for monitoring of vertebrate species, and investigated the effect of other factors (frequency of species, timing of visits, frequency of sampling, body size) on vertebrate species detectability. Metabarcoding of hollow sediments resulted in the detection of higher species richness in comparison Hollow sediment detected higher species richness (29 taxa: six birds, three reptiles and 20 mammals) to metabarcoding of soil at the entrance of the hollow (13 taxa: three birds, two reptiles and eight mammals). We detected 31 taxa in total with eDNA metabarcoding and 47 with camera traps, with 14 taxa detected by both (12 mammals and two birds). By comparing camera trap data with eDNA read abundance, we were able to detect vertebrates through eDNA metabarcoding that had visited the area up to two months prior to sample collection. Larger animals were more likely to be detected, and so were vertebrates that were identified multiple times in the camera traps. These findings demonstrate the importance of substrate selection, frequency of sampling, and animal size, on eDNA based monitoring. Future eDNA experimental design should consider all these factors as they affect detection of target taxa. </p>
GPM_API - Global Hourly Soil Moisture from GPM IMERG Data
<p>This repository serves as hub for the single <strong><em>GPM_API data set repositories</em></strong> related to the publication</p> <p>Ramsauer, T., & Marzahn, P. (2023). Global Soil Moisture Estimation based on GPM IMERG Data using a Site Specific Adjusted Antecedent Precipitation Index. <em>International Journal of Remote Sensing</em>, 44(2), 542-566.</p> <ul> <li>GPM_API 2015: <a href="https://doi.org/10.5281/zenodo.6353260">10.5281/zenodo.6353260</a></li> <li>GPM_API 2016: <a href="https://doi.org/10.5281/zenodo.6413889">10.5281/zenodo.6413889</a></li> <li>GPM_API 2017: <a href="https://doi.org/10.5281/zenodo.6413905">10.5281/zenodo.6413905</a></li> <li>GPM_API 2018: <a href="https://doi.org/10.5281/zenodo.6413907">10.5281/zenodo.6413907</a></li> <li>GPM_API 2019: <a href="https://doi.org/10.5281/zenodo.6413909">10.5281/zenodo.6413909</a></li> <li>GPM_API 2020: <a href="https://doi.org/10.5281/zenodo.6413911">10.5281/zenodo.6413911</a></li> </ul> <p> </p> <p>The related article can be found here:<br> Article: <a href="https://doi.org/10.1080/01431161.2022.2162351">https://doi.org/10.1080/01431161.2022.2162351</a></p> <p>Free PDF: <a href="https://www.tandfonline.com/eprint/6VHQ7JCCJXSPAMG3PVIG/full?target=10.1080/01431161.2022.2162351">www.tandfonline.com/eprint/6VHQ7JCCJXSPAMG3PVIG/full?target=10.1080/01431161.2022.2162351</a></p>
Data from: Soil mesofauna may buffer the negative effects of drought on alien plant invasion
<p>Although many studies have tested the direct effects of drought on alien plant invasion, less is known about whether drought affects alien plant invasion indirectly via interactions of plants with other groups of organisms such as soil mesofauna.</p> <p>To test for such indirect effects, we grew single plants of nine naturalized alien target species in pot-mesocosms with a community of five native grassland species under four combinations of two drought (well-watered vs drought) and two soil-mesofauna-inoculation (with vs without) treatments.</p> <p>We found that drought decreased the absolute and the relative biomass production of the alien plants, and thus reduced their competitive strength in the native community. Drought also decreased the abundance of soil mesofauna, particularly soil mites, but did not affect the abundance and richness of soil herbivores. Soil-fauna inoculation did not affect biomass of the alien plants but increased biomass of the native plant community, and thereby decreased the relative biomass production of the alien plants. This increased invasion resistance due to soil fauna, however, tended (p = 0.09) to be stronger for plants growing under well-watered conditions than under drought.</p> <p>Synthesis. Our multispecies experiment thus shows that soil fauna might help native communities to resist alien plant invasions, but that this effect might be weakened under drought. In other words, soil mesofauna may buffer the negative effects of drought on alien plant invasions.</p>
Data from: Pyrophilic plants respond to post-fire soil conditions in a frequently burned longleaf pine savanna
<p class="RealLife">Fire-plant feedbacks engineer recurrent fires in pyrophilic ecosystems like savannas. The mechanisms sustaining these feedbacks may be related to plant adaptations that trigger rapid responses to fire's effects on soil. Plants adapted for high fire frequencies should quickly regrow, flower, and produce seeds that mature rapidly and disperse post-fire. We hypothesized that offspring of such plants would germinate and grow rapidly, responding to fire-generated changes in soil nutrients and biota. We conducted an experiment using longleaf pine savanna plants that were paired based on differences in reproduction and survival under annual ("more" pyrophilic) vs. less frequent ("less" pyrophilic) fire regimes. Seeds were planted in different soil inoculations from experimental fires of varying severity. The "more" pyrophilic species displayed high germination rates followed by species specific, rapid growth responses to soil location and fire severity effects on soils. In contrast, the "less" pyrophilic species had lower germination rates that were not responsive to soil treatments. This suggests that rapid germination and growth constitute adaptations to frequent fires, and that plants respond differently to fire severity effects on soil abiotic factors and microbes. Further, variable plant responses to post-fire soils may influence plant community diversity and fire-fuel feedbacks in pyrophilic ecosystems.</p>
Data from: Plant community stability is associated with a decoupling of prokaryote and fungal soil networks
<p>Data from the manuscript Plant community stability is associated with a decoupling of prokaryote and fungal soil networks: https://doi.org/10.1101/2022.06.21.496867</p>
Compiled soil N2O emission data from Eastern China forests
<p>We searched the Thomson Reuters Web of Science Core Collection and China National Knowledge Infrastructure (CNKI) theses database for literature published before January 1, 2020, using the terms “forest” AND “greenhouse gas” OR “N<sub>2</sub>O” OR “nitrous oxide” in the titles, abstracts, and keywords; this returned 5,948 records and 590 records, respectively. Considering the different preferences for terminology (e.g., nutrient addition, simulated N deposition), we refined our search manually. The criteria for our refinement were as follows: (a) N addition experiment was conducted in eastern China forests with detailed records of N addition levels; (b) N<sub>2</sub>O flux was observed using the static chamber method so that data from different sites were comparable. A total of 58 papers from 38 research sites met our criteria. </p> <p>We also collected the data of soil N<sub>2</sub>O emission rates under natural conditions. The data were collected from literature that met the following criteria: (a) N<sub>2</sub>O fluxes were observed in eastern China forests using the static chamber method; (b) no manipulated experiments were conducted, and no nitrogen was added except for natural N deposition. There were 42 papers and theses that met these criteria, covering 30 different sites. </p> <p>From the abovementioned papers and theses, the soil N<sub>2</sub>O emission rates and the auxiliary information (coordinates, ecoregion type, natural N deposition rate, multi-year mean annual temperature, multi-year mean annual precipitation, and soil texture) were compiled (ds01).</p> <p>To obtain the soil N<sub>2</sub>O emission rates of Eastern China forests on grid level (10km × 10km), another dataset (ds02) on the environmental factors (ecoregion type, natural N deposition rate, multi-year mean annual temperature, multi-year mean annual precipitation, and soil texture) of each grid was compiled from the spatial datasets, including the Chinese vegetation ecoregion map from the Resources, Environmental Sciences, and Data Center at the Chinese Academy of Sciences (<a href="https://www.resdc.cn/">https://www.resdc.cn/data.aspx?DATAID=133</a>), as well as the soil texture raster data (<a href="https://www.resdc.cn/data.aspx?DATAID=260">https://www.resdc.cn/data.aspx?DATAID=260</a>), mean annual temperature raster data (1995–2015; <a href="https://www.resdc.cn/data.aspx?DATAID=228">https://www.resdc.cn/data.aspx?DATAID=228</a>), and mean annual precipitation raster data (1995–2015; <a href="https://www.resdc.cn/data.aspx?DATAID=229">https://www.resdc.cn/data.aspx?DATAID=229</a>). Land use and land cover raster data (2000–2015) were obtained from the Project on Big Earth Data Science Engineering (<a href="https://data.casearth.cn/sdo/detail/5c19a5650600cf2a3c557aae">https://data.casearth.cn/sdo/detail/5c19a5650600cf2a3c557aae</a>). Finally, annual N deposition rate and multi-year mean N deposition (MAN) data were derived from a N deposition dataset from mainland China previously constructed by our group. </p>
Data collected for: The contrasted impacts of grasshoppers on soil microbial activities in function of ecosystem productivity and herbivore diet
<p>Herbivory can have contrasted impacts on soil microbes and nutrient cycling, which has stimulated the development of conceptual frameworks exploring the links between below- and aboveground processes. The "productivity model" predicts that herbivores stimulate microbial activities and accelerate nutrient mineralization in productive ecosystems, while they have an opposite effect in less productive ecosystems. In parallel, the "diet model" predicts that herbivores feeding on conservative plants accelerate nutrient cycling while those feeding on exploitative plants decelerate nutrient cycling, due to changes in litter inputs. Since these two frameworks can lead to conflicting predictions in some cases, experimental evidence combining herbivore diet and productivity is required.</p> <p>During two consecutive years, we conducted an experiment controlling the presence of three grasshopper species consuming either grasses, forbs or both in twelve natural and managed alpine grasslands of contrasted productivities. In order to assess the effects of herbivory on soil microbes, we measured their enzymatic activities, their biomass and the soil potential nitrogen mineralization (PNM). Soil and vegetation characteristics were also determined in order to test if they modulated the effects of herbivory on microbes.</p> <p>Contrary to the predictions of the diet model, the effects of herbivory on microbial characteristics did not depend on the herbivores diet but relied on ecosystem productivity. The most productive sites were characterized by exploitative plant species which depleted N resources in the soil, and by microbes producing relatively few extracellular enzymes, leading to a lower PNM. Herbivory increased microbial biomass and decreased the production of extracellular enzymes in those sites, possibly through the stimulation of root exudates produced by exploitative species. The least productive sites were characterized by conservative plants, which led to the sequestration of soil C, and by microbes having a resource acquisition strategy (more extracellular enzymes, higher PNM). Herbivory decreased microbial biomass and increased the production of extracellular enzymes in those sites. This pattern can be explained by the loss of carbon associated with insect respiration, which increases the need for microbes to acquire resources and by a lower production of root exudates by conservative species. Therefore, the effects of two years of herbivory on soil microbes were at odds with the productivity model, which focuses instead on longer term effects corresponding to herbivory-induced changes in plant species composition. This highlights the multidimensional feature of the impacts of herbivory on ecosystem functioning, both in space and time.</p>
Data from: Controlled drainage and subirrigation suitability in the United States: A meta-analysis of crop yield and soil moisture effects
<p>Controlled drainage and subirrigation (CDSI) is an important water management strategy in many regions, but the conditions under which CDSI is most likely to increase crop yield and soil moisture are not fully understood. A meta-analysis, consisting of 154 pairwise observations from replicated and randomized trials in 30 peer-reviewed primary research articles on CDSI (6 controlled drainage, 24 CDSI, analyzed together due to data scarcity), was conducted to study the responses of yield and soil moisture to CDSI, and investigate how crop type, soil texture, and cumulative growing season precipitation (PGS) influence these responses. Based on the yield response to these moderating factors, we used a fuzzy-logic approach to map potentially suitable locations for CDSI in the conterminous United States. On average, CDSI increased yield by 8.0% (95% CI = 1.8–14.7%) compared with conventional free drainage. The yield response to CDSI did not differ among crops. However, a greater yield response to CDSI was observed in medium-textured soils (19.4% increase; 95% CI = 12.4–27.0%) than in coarse- or fine-textured soils. The positive effect of CDSI on yield increased with decreasing PGS in coarse- and medium-textured soils. There was no clear effect of CDSI on soil moisture, nor did any moderators influence this relationship, though this may be attributed to the scarcity of studies on CDSI reporting soil moisture. The fuzzy-logic-based approach revealed that while potentially suitable areas are mostly concentrated in the well studied U. S. Midwest, these areas also exist in other regions where CDSI may warrant further study.</p>
Dataset used in "Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis"
<p>Please see the paper "Deep learning with multisite data reveals the lasting effects of soil type, tillage and vegetation history on biopore genesis" how the images were captured, manual counting was performed, training datasets were prepared and models were trained.</p>
Data from: Treated like dirt: Robust forensic and ecological inferences from soil eDNA after challenging sample storage
<p>We investigated the effect of storage duration and conditions on the assessment of the soil biota with eDNA metabarcoding. We extracted eDNA from freshly collected soil samples and again from the same samples after storage under contrasting temperature conditions and contrasting exposure (open/closed tubes). We used four different primer sets targeting bacteria, fungi, protists (cercozoans), and general eukaryotes. <span>W</span>e quantified differences in richness, evenness, and community composition. Subsequently, we tested whether we could correctly infer habitat type and original sample identity after storage using a large reference dataset.</p> <p>This repository contains the un-demultiplexed fastq sequences.</p>
Fine-root biomass production, sedge root, sedge leaf, and moss shoot decomposition, soil water-table level, and temperature data from two sedge fens in Finland
<p>Dataset including fine-root biomass production, mass loss of sedge (<em>Carex rostrata</em>) roots and leaves, and moss (<em>Sphagnum</em> <em>fallax</em>) shoots, along with environmental data (soil water-table level, air temperature, soil temperature at 5 cm, and soil temperature at 15 cm) from two sedge fens located in southern Finland (Lakkasuo, Orivesi, 61°48' N 24°19'E) and northern Finland (Lompolojänkkä, Kittilä, 68°N 24°12'E). Data are from a climate change experiment, where warming was induced with open top chambers (OTCs) and drying with shallow ditching. Data are from years 2011-2013.</p>
Data for: Soil legacy effects of plants and drought on aboveground insects in native and range-expanding plant communities
<p><span>Soils contain biotic and abiotic legacies of previous conditions that may influence plant community biomass and associated aboveground biodiversity. However, little is known about the relative strengths and interactions of the various belowground legacies on aboveground plant-insect interactions. We used an outdoor mesocosm experiment to investigate the belowground legacy effects of range-expanding versus native plants, extreme drought, and their interactions on plants, aphids, and pollinators. We show that plant biomass was influenced more strongly by the previous plant community than by a previous summer drought. Plant communities consisted of four congeneric pairs of natives and range expanders, and their responses were not unanimous. </span><span>Legacy effects affected the abundance of aphids more strongly than pollinators</span><span>. We conclude that historical climate warming-induced plant latitudinal range expansion and extreme drought contingencies can be contained as soil 'memories' that influence plant performance and aboveground community interactions in the next growing season.</span></p>
Data set on soil physicochemical parameters, biomass accumulation and carbon credit generation in different management systems in Rio Verde, GO, Brazil
<h1>Description</h1> <p>This repository contains a comprehensive dataset focused on soil organic carbon and its role in mitigating climate change through carbon sequestration on agricultural lands in Rio Verde, GO, Brazil. With the global imperative to reduce anthropogenic CO2 emissions, our data highlights the effectiveness of no-till agricultural practices in both improving soil quality and enhancing carbon storage. This collection represents extensive soil and biomass sampling from five distinct areas within the Cerrado region, utilizing three priority management systems:</p> <p>No-till with soybean and maize in sequence under rainfed conditions. No-till with soybean and maize in sequence with central pivot irrigation. First and second cuts of sugarcane. The samples were meticulously collected post-harvest and used to estimate both soil biomass accumulation and carbon stock indices. A thorough analysis of the soil's physicochemical parameters was conducted for the 0-20 cm soil profile in each area. This dataset not only provides a valuable resource for studying the impact of different no-till practices on carbon sequestration but also serves as a critical input for modeling future contributions of conservation management systems to carbon trading markets.</p> <div> <div> </div> <div> <h2>Data Contents</h2> </div> <p>Soil organic carbon measurements for various no-till systems. Biomass accumulation data post-harvest. Carbon stock indices derived from biomass samples. Detailed physicochemical profiles of soil samples.</p> <div> <h2>Significance</h2> </div> <p>This dataset is pivotal for researchers and policymakers focusing on the potentials of agricultural carbon sequestration and its implications for carbon trading schemes. It offers insights into the current contributions of no-till conservation management systems and aids in the development of future strategies to enhance carbon</p> <h1>Metadata Description and Script</h1> </div> <p>This repository contains two key data files that encapsulate diverse aspects of soil physicochemical parameters, biomass accumulation, and carbon credit generation across different management systems in Rio Verde, GO, Brazil. Below are descriptions of each file's contents and structure.</p> <div> <h2>all.txt</h2> </div> <p>This text file presents aggregated data from various sites under different agricultural management systems. Each row in the dataset represents measurements from distinct sample plots, with the following fields:</p> <ul> <li><code>Sites</code> - Identifier for the plot location.</li> <li><code>SB</code> - Soil bulk density (g/cm³).</li> <li><code>SOC</code> - Soil organic carbon (%).</li> <li><code>Stock</code> - Carbon stock (ton/ha).</li> <li><code>Biomass</code> - Biomass accumulation (ton/ha).</li> <li><code>Credits</code> - Estimated carbon credits (ton CO2 equivalent/ha).</li> </ul> <div> <h2>Quimica.xlsx</h2> </div> <p>This Excel file provides detailed physicochemical analyses of soil samples from different management zones in the study area. The data is structured to support in-depth analysis of soil characteristics influencing carbon sequestration capabilities. Each sheet in the workbook corresponds to a specific area, with columns typically representing:</p> <ul> <li><code>pH</code> - Soil pH, indicating the acidity or alkalinity.</li> <li><code>EC</code> - Electrical conductivity (dS/m).</li> <li><code>Cation Exchange Capacity (CEC):</code> - (meq/100g).</li> <li><code>Organipont c Matter:</code> - (%).</li> <li><code>NPK levels</code> - Concentrations of Nitrogen (N), Phosphorus (P), and Potassium (K).</li> </ul>
Data supporting the manuscript entitled: 'Intermittent soil water stress history favors microbial traits that better mitigate wheat biomass losses during subsequent water stress.'
<p>Data living in this data repository supports the scientific article entitled: Intermittent soil water stress history favors microbial traits that better mitigate wheat biomass losses during subsequent water stress.</p> <p> </p> <p> </p> <p> </p>
Data for: Temporal variation of soil microarthropods in different forest types and regions of Central Europe
<p>Biodiversity and biomass of aboveground arthropods in Central European forests continuously declined during the last decade. However, whether belowground microarthropod communities follow similar patterns has not been investigated. In this study, we compared the abundance, diversity, community composition, stability and asynchrony of oribatid mites (Acari: Oribatida) sampled in four forest types of increasing management intensity (unmanaged beech, old managed beech, young managed beech, and coniferous) at three-year intervals from 2008 to 2020. Forest sites were replicated in three regions in southern, central and northern Germany, i.e. the Swabian Alb, Hainich-Dün and the Schorfheide Chorin, which differ in soil characteristics and climate. We found 25,152 individuals and 121 species of oribatid mites and detected no linear decline in abundance and diversity over the last decade, suggesting that microarthropods in forest soils are buffered against land-use effects. However, we observed that years with low winter precipitation in regions with soils that are prone to drought, resulted in significant decreases in oribatid mite densities. Community compositions remained similar across sampling years, but differed between regions and forest types, predominantly due to differences in the proportion of asexual individuals. The stability of oribatid mite communities did not decrease in managed forests and was highest in deep soils with high water-holding capacity, which may reduce temporal variation, suggesting that soil properties are more important for the stability of oribatid mite communities than forest management. However, stability patterns were not explained by asynchrony in species fluctuations, as all communities either showed a high degree of synchrony or were not different from random. Our study highlights that the temporal dynamics of belowground communities may differ from those aboveground, and that regional differences in precipitation and soil properties are more important than forest types.</p>
Data from: Interannual radial growth response of Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics
<p>Dataset related to the publication: „Interannual radial growth response of Douglas-fir (<em>Pseudotsuga menziesii</em> (Mirb.) Franco) to severe droughts: an analysis along a gradient of soil properties and rooting characteristics”</p> <p>Information on the data and the tree species_site_key used can be found in the attached Read me file.</p>
Data from: Higher spatial than seasonal beta diversity of soil protists along elevation gradients
<p>This data package contain the data and R script to reproduce the analyses of the paper from Bruni <em>et al.</em> (in press).</p> <p>It contains:</p> <ul> <li><strong>protist_spatiotemporal_turnover_site_parameters.xlsx</strong>: the list of sites used in this study with their (label, location, geography coordinates, habitat, ENA project and sample accessions) and soil abiotic parameters. Abbreviations and units are as follows: Res_hum, residual humidity [%]; Org_mat, soil organic matter [%]; C_org, organic carbon [mg ∙ g-1]; N_org, organic nitrogen [mg ∙ g-1]; P_bio, bioavailable phosphate [mg ∙ g-1]; C_N_ratio, carbon org. / nitrogen org. ratio; N_P_ratio: nitrogen org. / phosphorus bioavailable ratio.</li> <li><strong>protist_spatiotemporal_turnover_data.RData</strong>: dataset in rda format (R core team, 2024) containing the ASV read's abundance per site matrix (object "mat"), the ASV taxonomic assignments (object "taxo"), the ASV sequences (object "asv") and the CRU-TS monthly climatic data corresponding to the sampled site's location and dates (object "cruts").</li> <li><strong>protist_spatiotemporal_turnover_analyses.R</strong>: R script to reproduce all analyses and figures of Bruni <em>et al.</em> (in press)</li> </ul> <p> </p> <p>References:</p> <p>Bruni, E. P., Lorite, J., Peñas, J., Mulot, M., Fournier, B., Vittoz, P., Mitchell, E. A. D., & Lentendu, G. (2024). Higher spatial than seasonal beta diversity of soil protists along elevation gradients. Frontiers of Biogeography, 17, 1–17. DOI:<a href="https://doi.org/10.21425/fob.17.132637">10.21425/fob.17.132637</a></p> <div> <div>R Core Team. (2024). <em>R: a language and environment for statistical computing</em> (4.2.2) R Foundation for Statistical Computing. <a href="https://www.r-project.org/">https://www.r-project.org/</a></div> </div>
Data from: The PDI model system for parameterizing soil hydraulic properties
<p>The PDI ("Peters-Durner-Iden") model system represents a robust framework for parameterizing soil hydraulic properties, i.e. the water retention curve and the hydraulic conductivity curve, across the entire soil moisture spectrum. This model accounts for water retention and hydraulic conductivity in completely and partially-filled pores, including adsorption and film-flow. The model was developed in stages and a comprehensive overview of the model development and the model equations is provided in Peters et al. (2024). In this repository, we provide a Python file named "pdi.py" which can be used to compute the various submodels (PDI-VG, PDI-KOS, PDI-FX, ...) of the PDI model system. One MS Excel file is provided for easy access to one PDI model, the PDI-VG. The PYTHON functions contained in "pdi.py" can be used to calculate the water retention curve, the unsaturated hydraulic conductivity curve, the specific water capacity function, and the soil water diffusivity function. In addition, we provide five python scripts which illustrate how to call the various PDI functions in different contexts. Notably, "pdi.py" incorporates a utility function, 'export_hydrus_materin', which generates an ASCII file named "MATER.IN". This file serves as input for simulations with Hydrus-1D and Hydrus-2D3D, offering seamless integration with these simulation platforms. It's important to emphasize that the provided Python scripts and accompanying documentation are closely aligned with the research article by Peters et al. (2024). To streamline accessibility, the repository refrains from redundantly restating the theory or equations already detailed in the referenced publication.</p>
Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States: Data
<p>The data in this repository are associated with the manuscript from Huber et al. (2024) titled "Soil Moisture, Soil NOx and Regional Air Quality in the Agricultural Central United States" in the Journal of Geophysical Research: Atmospheres. Additional information regarding these data can be found in the attached readme file.</p>
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Allen Brain Atlas
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DANDI Archive for NWB datasets
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International Brain Laboratory public data
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OpenNeuro
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