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75 results for “Soil variables”
Seasonal and interannual variability of soil heterotrophic respiration and autotrophic respiration in typical grassland of Inner Mongolia
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Elevational variability and controls on temperature sensitivity of soil organic matter decomposition in alpine forests
<p>All data for ECS21-0520 "Elevational variability and controls on temperature sensitivity of soil organic matter decomposition in alpine forests"</p>
Raw data for "Plot-scale variability of organic carbon in temperate agricultural soils - Implications for soil monitoring"
<p>This dataset is the raw data that belongs to a peer-reviewed study on the small-distance variability of soil organic carbon in agricultural soils in Germany. It consists of three different files. The first file gives the coordinates of the 16 soil cores that were taken at each of the 16 sites (eight cropland and eight grassland sites). The second file gives the soil properties measured at each individual core (n=16 per site) and the third file the soil properties measured at each indivdual soil profile (n=6 per site).</p>
The main variables (soil moisture, net biome production and so on) of two experiments (CTRL and EXP) with the ORCHIDEE-MICT terrestrial biosphere model
<p class="MsoNormal"><span>Multiple linear regression (MLR) is widely used to attribute causes of the interannual variability (IAV) of land carbon uptake, yet, parameter estimation in MLR can be problematic if the predictors are strongly inter-correlated. Recently, Humphrey et al., (2021) used MLR method to conclude that the indirect effect of soil moisture (SM) via land-atmosphere coupling, rather than the direct effect of SM on photosynthesis and respiration, controls the IAV of NBP. Here we assess the validity of MLR as used by Humphrey et al. (2021) by comparing the true contribution of SM in a terrestrial biosphere model, derived from the difference between a control run (CTRL) and an experiment with prescribed climatological SM (EXP), with the MLR method applied to the CTRL outputs.</span></p> <p class="MsoNormal"><span><span>We ran two experiments (CTRL and EXP) with the ORCHIDEE-MICT</span><span> terrestrial biosphere model at 2º spatial resolution. The control (CTRL) run followed the protocol of "S3" experiment of TRENDY-v6</span><span>, forced by CRUNCEP-v8 climate forcing, increasing atmospheric CO<sub>2</sub> concentration, and varying land use maps. </span>Monthly outputs for the period 1960-2005 were used for analysis. For the EXP run, <a name="_Hlk107926231"></a>to remove the interannual variability (IAV) of soil moisture (SM) while keeping its seasonal cycle, a climatological monthly SM averaged for the years 1960-2005 simulated by the CTRL run was prescribed in the model. Note that the intrinsic time-step of hydrology and photosynthesis in ORCHIDEE-MICT is half-hourly, thus SM within the same month took the same monthly mean value. Other configurations in the EXP run were identical to the CTRL run. </span></p>
Supplementary material 2 from: Niemi M, Pöyry J, Heiskanen I, Uotinen V, Nieminen M, Erkomaa K, Wallenius K (2014) Variability of soil enzyme activities and vegetation succession following boreal forest surface soil transfer to an artificial hill. Nature Conservation 8: 1-25. https://doi.org/10.3897/natureconservation.8.6369
Figure S1: Explanation note: The studied sites at the onset of the study in June 2003: a) Top b) Grove c) Middle d) North e) Alder f) Spruce.
Supplementary material 5 from: Niemi M, Pöyry J, Heiskanen I, Uotinen V, Nieminen M, Erkomaa K, Wallenius K (2014) Variability of soil enzyme activities and vegetation succession following boreal forest surface soil transfer to an artificial hill. Nature Conservation 8: 1-25. https://doi.org/10.3897/natureconservation.8.6369
Figure S4: Explanation note: The studied s ites after a decade in June 2013: a) Top, b) Grove c) Middle d) North.
Data associated with "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales"
<p>The zipped folder contains the processed soil datasets including covariates, soil depths, and SOC concentrations for training the deep learning models described in the paper "The importance of terrain and climate for predicting soil organic carbon is highly variable across local to continental scales". </p> <p>"soil_profile/" contains a table including the geolocations of all the soil profiles in this study. "patch_data/" and "point_data/" contain the covariates to feed the models with patch input and point input respectively. "depth/" contains the upper and lower depths of the soil samples. "y/" contains the target variable - SOC concentration of the soil samples. The data files with suffix "_1" is a small subset of their counterparts without "_1" (10 % in sample size) used for model hyperparameters tuning.</p>
Changes in microbial community structure and functioning with elevation are linked to local soil characteristics as well as climatic variables
<p>Mountain forests are important carbon stocks but are threatened by increased insect outbreaks and climate driven forest conversion. Soil microorganisms play an eminent role in nutrient cycling in forests and form the basis of soil food webs. Uncovering the driving factors shaping microbial communities and functioning at mountainsides worldwide is of importance to better understand their dynamics at local and global scales. We investigated microbial communities and their drivers along an elevational gradient of primary forests at Changbai Mountain, China. We analysed substrate-induced respiration and phospholipid fatty acids (PLFA) in litter and two soil layers at seven sites. In the litter layer the increase in microbial biomass (Cmic) as well as in stress indicator ratios with elevation were negatively correlated with Ca concentrations indicating increased nutritional stress in high microbial biomass communities at sites with lower Ca availability. PLFA profiles in litter separated low and high elevations, this was less pronounced in soil, suggesting that leaflitter functions as buffer for soil microbial communities. Annual variations in temperature correlated with PLFA profiles in all layers, while annual variations in precipitation correlated with PLFA profiles in upper soil only. Furthermore, the availability of resources, soil moisture, Ca concentrations and pH structured the microbial communities. Pronounced changes in Cmic and stress indicator ratios in the litter layer between pine dominated (800 – 1100 m) and spruce dominated (1250 – 1700 m) forests indicated a shift in the structure and functioning of microbial communities between forest types. The study highlights strong changes in microbial community structure and functioning along elevational gradients, but also shows that these changes and their driving factors vary between layers. Besides annual variations in temperature and precipitation, carbon accumulation and nitrogen acquisition shape changes in microbial communities with elevation at Changbai Mountain.</p>
Small scale variability in soil moisture drives infection of vulnerable juniper populations by invasive forest pathogen
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Data from: Soil abiotic variables are more important than Salicaceae phylogeny or habitat specialization in determining soil microbial community structure
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Data from: Spatial variability in soil organic carbon in a tropical montane landscape: associations between soil organic carbon and land use, soil properties, vegetation, and topography vary across plot to landscape scales
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Data from: Impacts of climate variability and adaptation strategies on crop yields and soil organic carbon in the US Midwest
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The main variables (soil moisture, net biome production and so on) of two experiments (CTRL and EXP) with the ORCHIDEE-MICT terrestrial biosphere model
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Data from: Climate variability and community stability in Mediterranean shrublands: the role of functional diversity and soil environment
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Changes in microbial community structure and functioning with elevation are linked to local soil characteristics as well as climatic variables
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Catchment scale soil variably in Marshall Gulch, Santa Catalina Mountains Critical Zone Observatory (CZO), Arizona, 2012
The quantification and prediction of soil properties is fundamental to further understanding the Critical Zone (CZ). In this study we aim to quantify and predict soil properties within a forested catchment, Marshall Gulch, AZ. Input layers of soil depth (modeled), slope, Saga wetness index, remotely sensed normalized difference vegetation index (NDVI) and national agriculture imagery program (NAIP) bands 3/2 were determined to account for 95% of landscape variance and used as model predictors. Target variables including soil depth (cm), carbon (kg/m 2 ), clay (%), Na flux (kg/m 2 ), pH, and strain are predicted using multivariate linear step-wise regression models. Our results show strong correlations of soil properties with the drainage systems in the MG catchment. We observe deeper soils, higher clay content, higher carbon content, and more Na loss within the drainages of the catchment in contrast to the adjacent slopes and ridgelines.
Abundance of trees and seedlings, climatic, and soil variables in 36 20x20 m permanent plots in peri-urban Andean forests of Colombia
<p>The study was conducted on the Eastern Andean Cordillera of Colombia, in remnant forests occurring in the high-plain where Bogotá lies, one of the largest cities in Latin America. The high-plain covers an area of about 185,000 ha at an average altitude of 2600 meters above sea level (m a.s.l.). We selected six study sites, distributed in the Eastern and Western slopes of the mountain range that surrounds the high-plain, which exhibit different climatic and edaphic characteristics. Five of the sites were located in the suburban municipalities of Soacha (So), San Francisco (Sf), Guasca (Gu), Tabio (Ta), and the last one, Torca (To), located in a large forest fragment at the periphery of Bogotá. Sites were selected so that they encompassed both early- and late-successional or old-growth forest patches. <br> Within each site, we established three 20 m x 20 m plots in early-successional forests (E) and three 20 m x 20 m plots in late-successional (L) for a total of 36 permanent plots. Here, we present climatic and soil variables for each plot and also the abundances of all tree, shrub, palm, and tree-fern individuals with DAH> 5 cm included in each plot. For simplicity we refer to these as "trees" (-t). Within each plot, we additionally established four subplots of 2 m x 2 m, where we tagged and measured all seedlings> 5 cm in height and DAH ≤ 1 cm; we also present the abundances of the seedlings (-s).</p> <p>Vouchers were collected for each tree and seedling species or morphospecies and identified with the help of an expert botanist and using the resources of the herbarium of the Bogotá Botanical Garden (JBB). Vouchers specimens were stored at the herbarium of the Alexander von Humboldt Biological Resources Research Institute (FMB). Overall, we recorded Vouchers that were not identified to species were assigned a standardized morphospecies and were all included in the analyzes.</p>
What are the most crucial soil variables for predicting the distribution of mountain plant species? a comprehensive study in the Swiss Alps
Aim: To investigate the potential of a large range of soil variables to improve topo-climatic models of plant species distributions in a temperate mountain region encompassing complex relief. Location: The western Swiss Alps. Methods: Fitting topo-climatic models for >60 plant species across >250 sites with and without added soil predictor variables (>30). Testing included: (i) which soil variables improve plant species distribution models; (ii) whether an optimal subset of soil variables can improve models for the majority of species and habitat types; and (iii) how much variation in plant species distributions soil variables alone explain. Results: Geochemical variables (i.e., CaO, pH and inorganic carbon) and a drainage indicator (i.e., bulk soil water content) improved the predictive abilities of the models across the large majority of alpine plant species. The improvement of the models after the addition of soil information varied strongly between plant species and habitat types, but a trade-off was found between the number of soil variables and the associated gain in model performance. Finally, across all species, one specific combination of soil variables–bulk soil water content + total phosphorus + <i>δ</i><sup>13</sup>C–outperformed the commonly used topo-climatic variables. Main conclusions: Several soil variables significantly increased the predictive power of plant species distribution models in the temperate mountain region. Geochemical and drainage variables proved most important.
Data from: Spatial-temporal variability and related factors of soil organic carbon in Henan province
Spatial variability and influence factors are important to evaluate soil organic carbon(SOC) and the carbon pool in large areas. In the present study, sampling was conducted from May to November 2011 in Henan province, a typical agricultural region of central China, to study the effects of soil properties and anthropogenic factors on SOC variability in cropland. Physicochemical properties of soil samples were analyzed, which were collected at 280 sites from the surface layer (at a depth of 0–20 cm), and related data about the sampling sites were also collected from the Second State Soil Survey of China (SSSSC), conducted in 1981. The main results were as follows: 1) Increasing trends in soil organic carbon density (SOCD) and soil organic carbon pool (SOCP) were obvious from 1981 to 2011, and we conclude that cropland presents great carbon sequestration potential for the future. Carbon pool ability varied with soil properties: the order of fixed carbon amount in different soil types was found to be Inceptisols > Luvisols > Semi-hydromorphic soil > Anthrosols, and the average SOCP increased significantly from 1981 to 2011. 2) Soil bulk density, pH and returning straw are the key influence factors for SOCD in the past 30 years. 3) Although random factors (returning straw) only explain 29.1% of SOCD variability, the factor should be paid more attention, because application of returning strawwas the most dominant anthropogenic factors, which can be used to improve cropland productivity and carbon sink capacity within a short period if they are properly managed in the future.
Data from: Variability in potential to exploit different soil organic phosphorus compounds among tropical montane tree species
We hypothesized that tropical plant species with different mycorrhizal associations reduce competition for soil phosphorus (P) by specializing to exploit different soil organic P compounds. We assayed the activity of root/mycorrhizal phosphatase enzymes of four tree species with contrasting root symbiotic relationships–arbuscular mycorrhizal (angiosperm and conifer), ectomycorrhizal and non-mycorrhizal–collected from one of three soil sites within a montane tropical forest. We also measured growth and foliar P of these seedlings in an experiment with P provided exclusively as inorganic orthophosphate, a simple phosphomonoester (glucose phosphate), a phosphodiester (RNA), phytate (the sodium salt of myo-inositol hexakisphosphate), or a no-P control. The ectomycorrhizal tree species expressed twice the phosphomonoesterase activity as the arbuscular mycorrhizal tree species, but had similar phosphodiesterase activity. The non-mycorrhizal Proteaceae tree had markedly greater activity of both enzymes than the mycorrhizal tree species, with root clusters expressing greater phosphomonoesterase activity than fine roots. Both the mycorrhizal and non-mycorrhizal tree species contained significantly greater foliar P than in no-P controls when limited to inorganic phosphate, glucose phosphate, and RNA. The ectomycorrhizal species did not perform better than the arbuscular mycorrhizal tree species when limited to organic P in any form. In contrast, the non-mycorrhizal Proteaceae tree was the only species capable of exploiting phytate, with nearly three times the leaf area and more than twice the foliar P of the no-P control. Our results suggest that arbuscular and ectomycorrhizal tree species exploit similar forms of P, despite differences in phosphomonoesterase activity. In contrast, the mycorrhizal tree species and non-mycorrhizal Proteaceae appear to differ in their ability to exploit phytate. We conclude that resource partitioning of soil P plays a coarse but potentially ecologically important role in fostering the coexistence of tree species in tropical montane forests.
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.