Find research datasets worth reusing

Soil particle distribution data

This Excel file contains data on the mass proportions of soil particles across different size classes including unimodal, bimodal, trimodal, and irregular modal distributions, along with soil texture data using the USDA triangle (sand, silt, clay).

opencc-by-4.0May 2025View details →

Data for "Unexpected suppressive fungal diversity and stimulative soil carbon loss under soil acidification in an alkaline grassland"

This dataset was used to make tables and figures for the study entitled "Unexpected suppressive fungal diversity and stimulative soil carbon loss under soil acidification in an alkaline grassland", which was submitted to Functional Ecology in May 2024. It contains data of soil properties, plant and microbial communities under soil acidification in an alkaline grassland on the Loess Plateau.

Data for: Detection and diversity of Phytophthora species from declining Quercus suber stands using both DNA metabarcoding and soil baiting techniques

This dataset on Zenodo accompanies the manuscript Salvatore et al. (2024), Detection and diversity of Phytophthora species from declining Quercus suber stands using both DNA metabarcoding and soil baiting techniques. There are two files here on Zenodo: <ul> <li><code>metadata.tsv</code> - plain text table as tab-separated variables</li> <li><code>raw_data.tar.gz</code> - compressed archive of 56 paired raw FASTQ files</li> </ul> This represents a subset of one complete Illumina Nano MiSeq plate run at the James Hutton Institute also containing a small number of unrelated samples using the same protocol. To repeat the analysis described in the paper, first install THAPBI PICT. See <a href="https://github.com/peterjc/thapbi-pict/">https://github.com/peterjc/thapbi-pict/ </a>for instructions. At the time of the paper, v1.0.16 was the current release. Next, decompress the raw data into a folder of paired gzipped FASTQ files. There is no need to decompress those: <pre><code> $ tar -zxvf raw_data.tar.gz</code> <code> $ ls -1 raw_data/</code></pre> If you wish, verify the checksums to confirm the data integrity: <pre><code> $ cd raw_data/   $ md5sum -c MD5SUM.txt</code> <code> $ cd ..</code></pre> Setup output directories: <pre><code>   $ mkdir -p intermediate/ summary/</code></pre> Run the THAPBI PICT pipeline: <pre><code>   $ thapbi_pict pipeline -m 1s3g -f 0 -a 15 -i raw_data/ \</code> <code> -s intermediate/ -o summary/sardinia \</code> <code> -t metadata.tsv -u -x 8 -c 4,5,3,2,7,6</code></pre> The options here are as follows: <ul> <li><code>-m</code> - use the 1s3g classifier (see methods)</li> <li><code>-f</code> - set to zero to disable the fractional abundance threshold</li> <li><code>-a</code> - set a lower absolute abundance threshold</li> <li><code>-i</code> - location of the input raw data</li> <li><code>-s</code> - optional location to store intermediate files</li> <li><code>-o</code> - output stem for reports</li> <li><code>-t</code> - filename for tab-separated-variable metadata</li> <li><code>-u</code> - show unsequenced samples defined in the metadata</li> <li><code>-x</code> - which metadata column contains Illumina FASTQ filename stems</li> <li><code>-c</code> - which metadata columns to include in the report.</li> </ul> This leaves the <code>-d</code> option with the default provided ITS1 database. We are NOT taking advantage of the negative controls to automatically set a blanket minimum abundance as Control-Plate-3-Mix-3-Dry-P3-c_S56_L001 sadly has over 3000 Phytophthora reads. That takes under a minute to run, and classifies most of the samples. Opening the output file <code>summary/sardinia_20240912_v1.0.16.ITS1.samples.1s3g.xlsx</code> in Excel or similar should show you a table resembling Table 3 in the paper, without the baiting results, but with one row per sequencing sample, and additional columns with per-sample per-species read counts etc. The similarly named reads file as one row per unique amplicon sequence variant (ASV), and columns for each sequencing sample. All the Phytophthora classifications were to species level except a single ASV from E5BTB-DILUTE-Wet-P6_S17_L001 (S3  Bultei) with 15 reads, a perfect match to partial sequences MH588088.1 and MH593844.1, isolates Y1 and Y2, which is in the THAPBI PICT database but only at genus level: <pre><code>>bad82a53fff502146e7ea00cbf2d9d3e Phytophthora TTTCCGTAGGTGAACCTGCGGAAGGATCATTACCACACCTAAAACTTTCCACGTGAACCGTTTCAAACCAAATAGTTGGGGGTCTTGTCTGGTGGCGGCTGCTGGCTTTATTGTTGGCGGCTGCTGCTGGGTGAGCCCTATCATGGCGAGCGTTTGGGCTTCGGCCTGAGCTAGTAGCATTTCTTTTAAACCCATTCCTTAATACTGATTATACT</code></pre> There are 9 samples left simply as "Unknown" (all six from S2 Buddusò, one each from S3 Bultei, S4 Nuoro, and S6 Tempio). A further two samples contained low levels of an unknown sequence in addition to knowns. The unknown ASV from S1BTC-DILUTE-Wet-P6_S9_L001 (S3 Bultei) looks to be a novel Phytophthora if real, similar to P. quercina: <pre><code>>3cd110db0a0b8fa8b971ea6b61c53970 Phytophthora? TTTCCGTAGGTGAACCTGCGGAAGGATCATTACCACACCTAAAAAACTTTCCACGTGAACCGTTTCAACCAATATTTTGGGGGTCTCGTCTGGCGTGCGGCTGTTGCTGTAAAAGGCGGCGGCTGTTGCTGGGTGAGCCCTATCATGGCAAACGTTTGGGCTTCGGTCTGAACAAGTAGCTCTTTTTTAAACCATTACTTATTACTGATTATACT</code></pre> The unknown ASV from S4OC-DILUTE-Wet-P6_S2_L001 (S4 Nuoro) looks to be a Pythium (a perfect match to partial sequences MN269744 and KY822489 from uncultured clones): <pre><code>>eac8c1931b4f8c57803e6ad9ffb4eb56 Pythium? TTTCCGTAGGTGAACCTGCGGAAGGATCATTACCACACCAAAAAACTATCCACGTGAACCGTTAAGCAAAAGTCTAGTTGGCTTGTGTTGTTCGGGAGTGTGTTGGGAAGAGCTTGGAGATGTCTTCGGATATTTCGATGCCTAGTACTGGACATCCTGGCGAGCGAGTCGGCTAGCAACGAAGGTCGGGAGTTCGCTTGCGGACTGATGTGCGCTTGTCGCATGTCGGTCGAAAGGCTTGAGCAAACGGCTGATCTATTACTTTTAAACCATACCATAACTACTGATGATACT</code></pre> The unknown ASV from S9OC-Wet-P5_S12_L001 (S4 Nuoro) at only 38 reads seems to be an artefact of some kind, possibly chimeric: <pre><code>>74933d826f6077cd5f3dd036f894429d Artefact? TAGCCGTAGGGGAACCTGCGGCTGGATCACCTCCTTTCTGGATTCGGAAGGCAGGGATCAGTGATCAGTTATCAGAACCGATTGCTGCTCCTCTTCCGAGCATCCACAACGCCAGCTCTGGCAGGAATTCTGATATCTGATATCTGGTTTCTGCGATCTGGCAACGGCGCCGCCGTCTGCGCATCCCTTCTGCCGCGTTATTCCAGAGGGCAGTGATCAGTCATCAGAACCGATGGCGGATCCGCCCCCGGCTTCACGGCGAGCGCCCGAGCCTG</code></pre> The remaining unknown ASVs were likely Plasmopara.

Soil and environmental data for "Interacting management effects on soil microbial alpha and beta diversity in Swiss agricultural grassland"

This data shows the soil, environmental, and management data of 86 grassland sites that were sampled within the Canton of Solothurn, Switzerland. This data was used in the manuscript by F.J. Richter, R. Feola Conz, A. Lüscher, N. Buchmann, K.H. Valentin and M. Hartmann (2024): Interacting management effects on soil microbial alpha and beta diversity in Swiss agricultural grassland, which is published in the Journal of Applied Soil Ecology.

Data covering Q10 and soil physicochemical properties of China's forest ecosystems

Data including experiment description, site geographic location, climate variables, initial edaphic variables, and factors related to substrate quality, substrate availability, and microbial properties both before and after the treatments.

opencc-by-4.0Oct 2023View details →

Data covering soil microbial carbon use efficiency and soil properties along an aridity gradient

Data including experiment description, site geographic location, climate variables, soil microbial carbon use efficiency and soil properties along an aridity gradient.

opencc-by-4.0Oct 2024View details →

Data used in the manuscript "Pioneering evidence of the dynamics of water vapor and CO2 fluxes in Sahara Desert soils"

Open the record for dataset details and reuse information.

opencc-by-4.0Nov 2024View details →

An Integrated Approach for enhanced SMAP Soil Moisture Retrieval: Multi-Source Data Fusion and Data-Driven Machine Learning

Accurate satellite-based soil moisture (SM) retrieval is essential for hydrometeorological and agroecological applications, yet traditional physical models for L-band SM retrieval are hindered by uncertainties stemming from inaccuracies in prior parameters. This work combines multi-source data fusion and a physically-guided machine learning framework to develop a Soil Moisture Active Passive (SMAP) SM retrieval model (Fusion-LightGBM, F-LGB) that bypasses the need for static prior parameters, resulting in a new SM product. The retrieval benchmark is a new seamless SM data constructed by combining Triple Collection correlation coefficients (TC-R) and the Maximized-R method, which demonstrates superior temporal correlation on 20 International Soil Moisture Network (ISMN) in-situ networks compared to existing SM data, including ECMWF Reanalysis v5-Land (ERA5-Land), SMAP Level 4 (SMAP L4), and Global Land Data Assimilation System (GLDAS) Noah. The machine learning model incorporates input variables that represent the Tau-Omega model’s radiative transfer process, including brightness temperature, vegetation optical depth, soil temperature, and an external variable for precipitation. In the 2015-2020 validation set, F-LGB demonstrated the highest correlation (mean R = 0.72, significantly surpassing the second-best SMAP-INRAE-BORDEAUX (SMAP-IB) SM and deep neural network (DNN) SM at 0.67) and the lowest ubRMSE (mean value of 0.052 m3/m3, better than 0.055 m3/m3 for both DNN and SMAP-IB). F-LGB performed well across diverse land covers, vegetation densities, and climates, with SHAP analysis showing H-polarized brightness temperature as crucial, especially in areas with low to moderate vegetation. This new machine learning-based SMAP SM product may improve global satellite-based SM estimation capabilities.

Data from: Soil biota suppress positive plant diversity effects on productivity at high but not low soil fertility

1. Plant community productivity commonly increases with increasing plant diversity, which is explained by complementarity among plant species in resource utilization (complementarity effect), or by selection of particularly productive plant species in diverse plant communities (selection effect). Recent studies have also shown that soil biota can drive the positive plant diversity–productivity relationship by suppressing productivity more in low- than in high-diversity plant communities. However, much remains unknown about whether soil fertility plays a role in determining how soil biota affect plant diversity–productivity relationships. 2. We hypothesized that under high soil fertility conditions, negative soil biota effects dominate, which reduces plant monoculture biomass more than that of high-diversity plant communities. Conversely, under low soil fertility conditions, we hypothesized positive soil biota effects dominate, which facilitates plant resource partitioning and enhances community-level biomass in high-diversity plant communities. Hence we expected positive plant diversity–community productivity relationships under low and high soil fertility conditions but caused by different mechanisms. 3. We tested these hypotheses using woody seedlings and set up plant assemblages with four species richness levels (one, two, four and eight species), and grew them in sterilized and unsterilized (sterilized soil + living soil inoculum) soils at two nutrient levels (low vs. high fertility). 4. We found that at high fertility negative soil biota effects dominated and suppressed plant community biomass more in high-diversity plant communities than in monocultures, resulting in reduced complementarity effects of diverse plant communities and a non-significant plant species richness–community biomass relationship in unsterilized soil. Whereas at low fertility soil biota had net neutral to positive effects on plant community biomass but the beneficial effects did not increase with increasing plant species richness. Instead, soil biota neutrally affected the positive plant species richness–community biomass relationship, presumably due to non-specific effects of beneficial soil biota. 5. Synthesis. Soil biota and soil fertility interactively determine plant species richness–community biomass relationships. Moreover, soil biota modulate the complementary resource use among plant species. These findings suggest that environmental context plays an important role in determining whether and how soil biota generate the biodiversity–productivity relationship. Future studies would benefit from revealing the mechanisms underlying the interactive effects of soil biota, soil fertility, and plant diversity on ecosystem functioning.

Data from: Effects of radiation from contaminated soil and moss in Fukushima on embryogenesis and egg hatching of the aphid Prociphilus oriens

Radiation-contaminated soils are widespread around the Fukushima Daiichi Nuclear Power Plant, and such soils raise concerns over its harmful effect on soil-dwelling organisms. We evaluated the effects of contaminated soil and moss sampled in Fukushima on the embryogenesis and hatching of aphid eggs, along with the measurement of the egg exposure dose. Cs-137 concentration in soil and moss from Fukushima ranged from 2200 to 3300 Bq/g and from 64 to 105 Bq/g, respectively. Eggs of the eriosomatine aphid Prociphilus oriens that were collected from a non-contaminated area were directly placed on the soil and moss for 4 or 3 months during diapause and then incubated until hatching. The total exposure dose to the eggs was estimated as ca. 100–200 mGy in the 4-month soil experiment and 4–10 mGy in the 4-month moss experiment. There was no significant difference in egg hatchability between the contaminated soil treatment and the control. No morphological abnormalities were detected in the first instars that hatched from the contaminated soil treatment. However, we found weak effects of radiation on egg hatching; eggs placed on the contaminated moss hatched earlier than did the control eggs. On the contaminated soil, the effects of radiation on egg hatching were not obvious because of uncontrolled environmental differences among containers. The effects of radiation on egg hatching were detected only in containers where high hatchability was recorded. Through the experiments, we concluded that the aphid eggs responded to ultra-low-dose radiation by advancing embryogenesis.

Data from: Biochar from "Kon Tiki" flame curtain and other kilns: effects of nutrient enrichment and kiln type on crop yield and soil chemistry

Biochar application to soils has been investigated as a means of improving soil fertility and mitigating climate change through soil carbon sequestration. In the present work, the invasive shrub "Eupatorium adenophorum" was utilized as a sustainable feedstock for making biochar under different pyrolysis conditions in Nepal. Biochar was produced using several different types of kilns; four sub types of flame curtain kilns (deep-cone metal kiln, steel shielded soil pit, conical soil pit and steel small cone), brick-made traditional kiln, traditional earth-mound kiln and top lift up draft (TLUD). The resultant biochars showed consistent pH (9.1 ± 0.3), cation exchange capacities (133 ± 37 cmolc kg-1), organic carbon contents (73.9 ± 6.4 %) and surface areas (35 to 215 m2/g) for all kiln types. A pot trial with maize was carried out to investigate the effect on maize biomass production of the biochars made with various kilns, applied at 1% and 4% dosages. Biochars were either pretreated with hot or cold mineral nutrient enrichment (mixing with a nutrient solution before or after cooling down, respectively), or added separately from the same nutrient dosages to the soil. Significantly higher CEC (P< 0.05), lower Al/Ca ratios (P< 0.05), and high OC% (P<0.001) were observed for both dosages of biochar as compared to non-amended control soils. Importantly, the study showed that biochar made by flame curtain kilns resulted in the same agronomic effect as biochar made by the other kilns (P > 0.05). At a dosage of 1% biochar, the hot nutrient-enriched biochar led to significant increases of 153% in above ground biomass production compared to cold nutrient-enriched biochar and 209% compared to biochar added separately from the nutrients. Liquid nutrient enhancement of biochar thus improved fertilizer effectiveness compared to separate application of biochar and fertilizer.

opencc-zeroDec 2011View details →

Data from: Shrub encroachment does not reduce the activity of some soil enzymes in Mediterranean semiarid grasslands

Shrub encroachment is a worldwide phenomenon with implications for desertification and global change. We evaluated its effects on the activities of urease, phosphatase and b-glucosidase in Mediterranean semiarid grasslands dominated by Stipa tenacissima by sampling 12 sites with and without resprouting shrubs along a climatic gradient. The presence of shrubs affected the evaluated enzymes at different spatial scales. Soils under S. tenacissima tussocks and in bare ground areas devoid of vascular plants had higher values of phosphatase and urease when the shrubs were present. For the b-glucosidase, this effect was site-specific. At the scale of whole plots (30 m 30 m), shrubs increased soil enzyme activities between 2% (b-glucosidase) and 22% (urease), albeit these differences were significant only in the later case. Our results indicate that shrub encroachment does not reduce the activity of extracellular soil enzymes in S. tenacissima grasslands.

opencc-zeroDec 2017View details →

Data from: Soil erodibility differs according to heritable trait variation and nutrient-induced plasticity in the salt marsh engineer Spartina alterniflora

Use of landform engineers for habitat restoration has often resulted in unanticipated outcomes. It is possible that departures from expectation arise because applications do not adequately account for the influence of heritable and non-heritable phenotypic variation on ecosystem attributes. In this study, we performed a common garden greenhouse experiment to determine whether soil shear strength—a characteristic linked to erosion resistance—varies according to heritable and plastic trait expression in Spartina alterniflora grown under contrasting nutrient regimes. We detected heritable variation across a broad spectrum of functional traits, including nutrient uptake. We also found that S. alterniflora exhibited trait-specific differences in nutrient-induced phenotypic plasticity. Heritable trait differences and plasticity together explained approximately 70% of the observed variation in soil shear strength. Soil shear strength increased when plants received more nutrients, but the influence of heritable variation on soil shear strength was equal to or larger than that of nutrient-induced plasticity. These findings illustrate that heritable and non-heritable trait expression can potentially govern the fate of marsh ecosystems, which suggests that consideration should be given to both factors when deploying landform engineers for coastal restoration.

opencc-zeroDec 2014View details →

Data from: Soil nitrogen-cycling responses to conversion of lowland forests to oil palm and rubber plantations in Sumatra, Indonesia

Rapid deforestation in Sumatra, Indonesia is presently occurring due to the expansion of palm oil and rubber production, fueled by an increasing global demand. Our study aimed to assess changes in soil-N cycling rates with conversion of forest to oil palm (Elaeis guineensis) and rubber (Hevea brasiliensis) plantations. In Jambi Province, Sumatra, Indonesia, we selected two soil landscapes – loam and clay Acrisol soils – each with four land-use types: lowland forest and forest with regenerating rubber (hereafter, "jungle rubber") as reference land uses, and rubber and oil palm as converted land uses. Gross soil-N cycling rates were measured using the 15N pool dilution technique with in-situ incubation of soil cores. In the loam Acrisol soil, where fertility was low, microbial biomass, gross N mineralization and NH4+ immobilization were also low and no significant changes were detected with land-use conversion. The clay Acrisol soil which had higher initial fertility based on the reference land uses (i.e. higher pH, organic C, total N, effective cation exchange capacity (ECEC) and base saturation) (P≤0.05–0.09) had larger microbial biomass and NH4+ transformation rates (P≤0.05) compared to the loam Acrisol soil. Conversion of forest and jungle rubber to rubber and oil palm in the clay Acrisol soil decreased soil fertility which, in turn, reduced microbial biomass and consequently decreased NH4+ transformation rates (P≤0.05–0.09). This was further attested by the correlation of gross N mineralization and microbial biomass N with ECEC, organic C, total N (R=0.51–0. 76; P≤0.05) and C:N ratio (R=-0.71 – -0.75, P≤0.05). Our findings suggest that the larger the initial soil fertility and N availability, the larger the reductions upon land-use conversion. Because soil N availability was dependent on microbial biomass, management practices in converted oil palm and rubber plantations should focus on enriching microbial biomass.

opencc-zeroDec 2012View details →

Data from: Vascular plants mediate the effects of aridity and soil properties on ammonia-oxidizing bacteria and archaea

An integrated perspective of the most important factors driving the abundance of ammonia-oxidizing bacteria (AOB) and archaea (AOA) in natural ecosystems is lacking, especially in drylands. We evaluated how different climatic, abiotic, and nutrient-related factors determine AOA and AOB abundance in bare and vegetated microsites from grasslands throughout the Mediterranean Basin. We found a strong negative relationship between the abundance of AOA genes and soil fertility (availability of C, N, and P). Aridity and other abiotic factors (pH, sand content, and electrical conductivity) were more important than soil fertility in modulating the AOA/AOB ratio. AOB were more abundant under vegetated microsites, while AOA, highly resistant to stressful conditions, were more abundant in bare ground areas. These results suggest that AOA may carry out nitrification in less fertile microsites, while AOB predominate under more fertile conditions. Our results indicate that the influence of aridity and pH on the relative dominance of AOA and AOB genes is ultimately determined by local-scale environmental changes promoted by perennial vegetation. Thus, in spatially heterogeneous ecosystems such as drylands, there is a mutual exclusion and niche division between these microorganisms, suggesting that they may be functionally complementary.

opencc-zeroDec 2015View details →

Data from: Forest plant community as a driver of soil biodiversity: experimental evidence from collembolan assemblages through large-scale and long-term removal of oak canopy trees Quercus petraea

Plant–soil interactions are increasingly recognized to play a major role in terrestrial ecosystems functioning. However, few studies to date have focused on slow dynamic ecosystems such as forests. As they are vertically stratified by multiple vegetation strata, canopy tree removal by thinning operations could alter forest plant community through tree canopy opening. Very little is known about cascading effects on soil biodiversity. We conducted a large-scale, multi-site assessment of collembolan assemblage response to long-term canopy tree removal in sessile oak Quercus petraea temperate forests. A total of 33 experimental plots were studied covering a large gradient of canopy tree basal area, stand age and local abiotic contexts. Collembolan abundance strongly declined with canopy tree removal in early forest successional stage and this was mediated by negative effect of understory plant community composition changes, i.e. shift from moss and forb to tree seedling, fern, shrub and grass species. Negative effect of this composition shift on collembolan species richness was largely offset by positive effect of the increase in understory plant species richness. This gives support to both the plant mass-ratio and functional diversity hypotheses. Collembolan functional groups had contrasting response patterns, which were mediated by different ecological factors. Epedaphic (r-strategist) abundance and species richness increased with canopy tree removal in relation with the increase in understory plant species richness. In contrast, euedaphic (K-strategist) abundance and species richness declined with canopy tree removal in early forest successional stage in relation with changes in understory plant community composition and species richness, as well as microclimatic conditions. Overall, our study provides experimental evidence that forest plant community can be a strong driver of collembolan assemblages. It also emphasizes the role of trees as foundation species of forest ecosystems that can shape soil biodiversity through their regulation of understory plant community and ecosystem abiotic conditions.

opencc-zeroDec 2017View details →

Data from: Within-species tradeoffs in plant-stimulated soil enzyme activity and growth, flowering and seed size

1. Soil microbial communities affect species demographic rates of plants. In turn, plants influence the composition and function of the soil microbiome, potentially resulting in beneficial feedbacks that alter their fitness and establishment. For example, differences in the ability to stimulate soil enzyme activity among plant lineages may affect plant growth and reproduction. 2. We used a common garden study to test differences in plant-stimulated soil enzyme activity between lineages of the same species across developmental stages. 3. Lineages employed different strategies whereby growth, days to flowering and seed size traded-off with plant-stimulated soil enzyme activity. Specifically, the smaller seeded lineage stimulated more enzyme activity at the early stage of development and flowered earlier while the larger seeded lineage sustained lower but consistent enzyme activity through development. 4. We suggest that these lineages, which are both successful invaders, employ distinct strategies (a colonizer and a competitor) and differ in their influence on soil microbial activity. Synthesis. The ability to influence the soil microbial community by plants may be an important trait that trades-off with other growth, flowering and seed size for promoting plant establishment, reproduction and invasion.

Data from: The microbially-mediated soil organic carbon loss under degenerative succession in an alpine meadow

Land-cover change has long been recognized as having marked effect on the amount of soil organic carbon (SOC). However, the microbially-mediated processes and mechanisms on SOC are still unclear. In this study, the soil samples in a degenerative succession from alpine meadow to alpine steppe meadow in the Qinghai-Tibetan Plateau were analyzed using high-throughput technologies, including Illumina sequencing and GeoChip functional gene arrays. The soil microbial community structure and diversity were significantly (P < 0.05) different between alpine meadow and alpine steppe meadow, the microbial ɑ-diversity in alpine steppe meadow was significantly (P < 0.01) higher than in alpine meadow. Molecular ecological network analysis indicated that the microbial community structure in alpine steppe meadow was more complex and tighter than in the alpine meadow. The relative abundance of soil microbial labile carbon degradation genes (e.g., pectin and hemicellulose) was significantly higher in alpine steppe meadow than in alpine meadow, but the relative abundance of soil recalcitrant carbon degradation genes (e.g. chitin and lignin) showed the opposite tendency. The Biolog Ecoplate experiment showed that microbially-mediated soil carbon utilization was more active in alpine steppe meadow than in alpine meadow. Consequently, more soil labile carbon might be decomposed in alpine steppe meadow than in alpine meadow. Therefore, the degenerative succession of alpine meadow because of climate change or anthropogenic activities would most likely decreased SOC and nutrients medicated by changing soil microbial community structure and their functional potentials for carbon decomposition.

opencc-zeroDec 2014View details →

Data from: Forest management adaptation to climate change: a Cornelian dilemma between drought resistance and soil macro-detritivore functional diversity

1. Global warming induces new constraints on forest ecosystems and requires forest management adaptation. The reduction in stand density is currently debated as a potential tool to face increasing summer drought risk by improving forest resistance to climate change-induced tree mortality. However, few studies have yet assessed the impacts of this management change on soil biodiversity. 2. We conducted a large-scale, multi-site assessment of the response of soil macro-detritivore assemblages and soil functioning to experimental manipulations of stand density. A total of 33 stands were studied covering a wide gradient of stand density, that is stand basal area from 2·5 to 43·7 m2 ha−1, stand age, that is 18–171 years old, and local abiotic context. 3. We observed contrasting responses as a function of both taxonomic and functional groupings. Exploratory analysis using causal diagrams, that is path analysis, highlights that these changes were mainly related to alterations in understorey vegetation, microclimatic and soil pH conditions. The response of soil macro-detritivore assemblages to stand density manipulation was consistent over the gradient of stand ages. 4. Among the litter-dwelling macro-detritivores, millipede abundance and diversity decreased with stand density reduction, while woodlice and epigeic earthworms were unaffected. Further, a shift in soil-dwelling earthworm community composition was observed in mull stands. Endogeic earthworm abundance showed a sharp increase with stand density reduction, which translated into an increase in soil respiration. In contrast, anecic earthworm abundance decreased and was strongly associated with a decline of the rate of forest floor turnover. 5. Synthesis and applications. Our study provides strong evidence that reductions of stand density will have substantial impacts on soil macro-detritivore assemblages and cascading effects on soil functioning, particularly in mull stands. Managing stand density of oak forests at an intermediate level, that is 25 m2 ha−1, appears to be best to optimize the trade-off between improving forest resistance to climate change and ensuring the conservation of functional diversity to preserve forest ecosystem functioning and stability.