Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.
Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.
As part of the Changing the Face of the Mediterranean Project, we consider how human pressure and concomitant erosion has affected a range of Mediterranean landscapes between the Neolithic and, in some cases, the post-medieval period. Part of this assessment comprises an investigation of relationships among palaeodemographic data, evidence for vegetation change and some consideration of rapid climate change events. The erosion data include recent or hitherto unpublished work from the authors. Where possible, we consider summed probabilities of 14C dates as well as the first published synthesis of all known optically stimulated luminescence dated sequences. The results suggest that while there were some periods when erosion took place contemporaneously across a number of regions, possibly induced by climate changes, more often than not, we see a complex and heterogeneous interplay of demographic and environmental changes that result in a mixed pattern of erosional activity across the Mediterranean.
", "keywords": ["[SDE] Environmental Sciences", "demography", "human impact", "550", "[SDU.STU.GM] Sciences of the Universe [physics]/Earth Sciences/Geomorphology", "[SDU.STU.GP]Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph]", "[SDE.MCG]Environmental Sciences/Global Changes", "[SDU.STU]Sciences of the Universe [physics]/Earth Sciences", "Mediterranean", "01 natural sciences", "[SDU] Sciences of the Universe [physics]", "[SDE.ES] Environmental Sciences/Environment and Society", "0601 history and archaeology", "[SDU.STU.GM]Sciences of the Universe [physics]/Earth Sciences/Geomorphology", "[SDE.ES]Environmental Sciences/Environment and Society", "demography; erosion; geoarchaeology; Holocene; human impact; Mediterranean", "0105 earth and related environmental sciences", "Holocene", "06 humanities and the arts", "15. Life on land", "erosion", "[SDE.MCG] Environmental Sciences/Global Changes", "[SDU]Sciences of the Universe [physics]", "13. Climate action", "[SDE]Environmental Sciences", "[SDU.STU] Sciences of the Universe [physics]/Earth Sciences", "[SDU.STU.GP] Sciences of the Universe [physics]/Earth Sciences/Geophysics [physics.geo-ph]", "geoarchaeology"]}, "links": [{"href": "https://iris.unito.it/bitstream/2318/1858935/2/Walsh_etal_2019.pdf"}, {"href": "http://journals.sagepub.com/doi/pdf/10.1177/0959683619826637"}, {"href": "https://doi.org/10.1177/0959683619826637"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/The%20Holocene", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.1177/0959683619826637", "name": "item", "description": "10.1177/0959683619826637", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.1177/0959683619826637"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-02-14T00:00:00Z"}}, {"id": "10.5061/dryad.f45f410", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:45Z", "type": "Dataset", "title": "Data from: Environmental drivers of soil phosphorus composition in natural ecosystems", "description": "unspecifiedDeiss_etal_Biogeosciences_DATASET_bg-2017-307This dataset is associated with the following article: Deiss, L., Moraes, A., and Maire, V. Environmental drivers of soil phosphorus composition in natural ecosystems. Biogeosciences. bg-2017-307.Deiss_etal_Biogeosciences_DATASET.xlsx", "keywords": ["2. Zero hunger", "Holocene", "13. Climate action", "Phosphorus", "15. Life on land", "Boreal", "structural equation modeling", "temperate", "Nuclear magnetic resonance"], "contacts": [{"organization": "Deiss, Leonardo, de Moraes, Anibal, Maire, Vincent,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.f45f410"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.f45f410", "name": "item", "description": "10.5061/dryad.f45f410", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.f45f410"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-07-18T00:00:00Z"}}, {"id": "10.5061/dryad.51r23", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:42Z", "type": "Dataset", "title": "Data from: Foliar nutrient concentrations and resorption efficiency in plants of contrasting nutrient-acquisition strategies along a 2-million year dune chronosequence", "description": "unspecifiedJurien Bay leaf nutrient dataDescription Leaf nutrient concentration and C/N stable isotope data for 18 plant species across five dune chronosequence stages along the Jurien Bay chronosequence. Format A data frame with 508 observations on the following 22 variables: plot factor with names of 50 10x10-m plots stage factor indicating chronosequence stage (1 = youngest, 5 = oldest) species factor with full plant species names state factor with leaf state: mature or senesced date sampling date ICP factor stating whether nutrients other than C and N were analysed with a radial or axial ICP equipment for each sample C leaf carbon concentration (%) Ca leaf calcium concentration (microg g^-1) Cd leaf boron concentration (microg g^-1) Cu leaf copper concentration (microg g^-1) Fe leaf iron concentration (microg g^-1) K leaf potassium concentration (microg g^-1) Mg leaf magnesium concentration (microg g^-1) Mn leaf manganese concentration (microg g^-1) Mo leaf molybdenum concentration (microg g^-1) Na leaf sodium concentration (microg g^-1) P leaf phosphorus concentration (microg g^-1) S leaf sulfur concentration (microg g^-1) Zn leaf zinc concentration (microg g^-1) N leaf nitrogen concentration (microg g^-1) d15N delta-N-15 (permil Air) d13C delta-C-13 (permil VPDB) Details For leaf sampling, we used 50 plots (10 m x 10 m each) from five chronosequence stages where vegetation had been characterised previously. Using the vegetation survey data, we ranked species in each of the five chronosequence stages from the most to the least abundant, based on canopy cover estimates. We then selected 5\u20137 species from each stage, targeting the most abundant species for each of four contrasting nutrient-acquisition strategies: arbuscular mycorrhizal (AM), ectomycorrhizal (EM), N-fixing (NF) and non-mycorrhizal (NM) (see juriensp for strategies). Ericoid mycorrhizal species were not considered because they were not among the most abundant species. We note that N-fixing species are generally AM and/or EM, but we considered them as a separate group because they often show high foliar [N]. Species were selected from the ten most-abundant species per stage, with the exception of stage 4 where the 18 most-abundant species were considered. The selected species accounted for between 38% (stage 5) and 65% (stage 1) of the total canopy cover of each stage. A total of 18 species were selected for leaf sampling. All leaf material was collected over a two-month period between late March and early May 2012, near the end of the dry summer season. In each of the 50 plots, only healthy mature individuals were selected for sampling. In general, mature and senesced leaves were sampled from one individual plant per species in each plot. A species was considered absent from a plot if it could not be found within ~30 m of its centre. The number of individual collections (one collection = both mature and senesced leaves) per species in each chronosequence stage ranged from five to ten. In each case, representative samples of mature and senesced leaves were collected using nitrile gloves in order to minimise sample contamination. Leaves were not washed prior to nutrient analyses but we consider dust contamination to be highly unlikely, given the sandy nature of the soils. Mature leaves were undamaged, fully expanded and exposed to full sunlight. In most cases, senesced leaves were collected directly from the plant by gently shaking the plant and collecting fallen leaves. Senesced leaves were easily distinguished from green leaves, since they were yellow or brown and detached easily from the plant. However, for a few species it was not possible to collect senesced leaves from live plants, in which case senesced leaves were collected directly beneath the plant from recently fallen litter. In all cases, there was no visible degradation of senesced leaves collected from this litter, which had predominantly fallen during the summer and had not been exposed to any significant rain between litter fall and collection. Therefore, we assumed that losses of nutrients through leaching or decomposition were minimal, although some photodegradation may have occurred. A total of 508 leaf samples (mature and senesced) were collected for nutrient analyses. Each leaf sample was oven-dried (70 degrees C, 48 h) and finely ground using a Teflon-coated stainless steel ball mill. A subsample was analysed for carbon (C) and nitrogen (N) concentrations using a continuous-flow system consisting of a SERCON 20-22 mass spectrometer connected with an automated nitrogen/carbon analyser (Sercon, Crewe, UK). Stable isotopes of C and N were analysed using a continuous flow system consisting of a SERCON 20-22 mass spectrometer connected with an automated N/C analyser (Sercon, Crewe, UK). These analyses were done at the Western Australian Biogeochemistry Centre, located at the University of Western Australia. A second subsample was acid-digested using concentrated HNO3:HClO4 (3:1) and analysed for Ca, Cd, Cu, Fe, K, Mg, Mn, Mo, Na, P, S and Zn concentrations using inductively coupled plasma-atomic emission spectrometry (ICP-AES; ChemCentre, Perth, Australia). All digests were first analysed using a simultaneous Varian Vista Pro (Australia), radially configured ICP-AES equipment fitted with a charge-coupled device (CCD) detection system and an A.I. Scientific AIM-3600 auto-sampler. Samples with P concentrations close to minimum reporting limit were re-run on more sensitive axially-configured ICP-AES equipment. The ICP analyses were done at the WA Chemcentre.jurienleafnut.csv", "keywords": ["Banksia leptophylla", "soil fertility gradient", "nutrient-resorption efficiency", "Acacia rostellifera", "Acanthocarpus preissii", "Spyridium globulosum", "Conostylis candicans", "Banksia attenuata", "Jacksonia floribunda", "Scaevola crassifolia", "nutrient-use efficiency", "Holocene", "manganese accumulation", "nutrient-resorption proficiency", "Mesomelaena pseudostygia", "Phosphorus", "Melaleuca systena", "15. Life on land", "Olearia axillaris", "Banksia menziesii", "Lepidosperma squamatum", "Hardenbergia comptoniana", "Melaleuca leuropoma", "Zinc", "Banksia sessilis", "Hibbertia hypericoides", "Acacia spathulifolia"], "contacts": [{"organization": "Hayes, Patrick, Turner, Benjamin L., Lambers, Hans, Lalibert\u00e9, Etienne,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.51r23"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.51r23", "name": "item", "description": "10.5061/dryad.51r23", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.51r23"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2014-11-18T00:00:00Z"}}, {"id": "10.3389/feart.2021.727315", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:12Z", "type": "Journal Article", "created": "2021-11-12", "title": "Reconstructing Permafrost Sedimentological Characteristics and Post-depositional Processes of the Yedoma Stratotype Duvanny Yar, Siberia", "description": "Cryogenic weathering is a key driver of periglacial sediment composition and properties. Selective mineral-grain weathering caused by freeze-thaw cycles in permafrost environments has the ability to dominate this process, leading to silt-rich grain-size distributions. The cryogenic weathering index (CWI) is a promising tool to quantify cryogenic weathering and freezing conditions. It considers the low resistance of quartz to freeze-thaw cycles compared to feldspars. Using this approach, this study aims to decipher post-depositional weathering by reconstructing cryogenic late Pleistocene Yedoma origins of the Yedoma stratotype exposure Duvanny Yar. To estimate the recent environmental endmember and to determine the initial mineral composition of sediment until freezing, the distribution of CWI in the active layer was studied. In addition to CWI, we studied mineral composition, heavy mineral distribution, grain size distribution and grain morphology. We suggest that cryogenic weathering likely altered polygenetic deposits (fluvial, nival, colluvial, lacustrine, alluvial, and aeolian processes) during sediment and ground ice accumulation. Moreover, we found two CWI distribution peaks in the late Pleistocene - Holocene sediments at the boundaries between glacial and interglacial ages. In conclusion, we see that the Duvanny Yar sediment facies varied by CWI, but also with grain-size distribution, suggesting environmental changes during formation. Nevertheless, post-depositional processes like cryogenic weathering have influenced sediment characteristics and should be considered in paleoenvironmental reconstructions.
With permafrost thaw, significant amounts of organic carbon (OC) previously stored in frozen deposits are unlocked and become potentially available for microbial mineralization. This is particularly the case in ice-rich regions such as the Yedoma domain. Excess ground ice degradation exposes deep sediments and their OC stocks, but also mineral elements, to biogeochemical processes. Interactions of mineral elements and OC play a crucial role for OC stabilization and the fate of OC upon thaw, and thus regulate carbon dioxide and methane emissions. In addition, some mineral elements are limiting nutrients for plant growth or microbial metabolic activity. A large ongoing effort is to quantify OC stocks and their lability in permafrost regions, but the influence of mineral elements on the fate of OC or on biogeochemical nutrient cycles has received less attention and there is an overall lack of mineral element content analyses for permafrost sediments. Here, we combine portable X-ray fluorescence (pXRF) with a bootstrapping technique to provide i) the first large-scale Yedoma domain Mineral Concentrations Assessment (YMCA) dataset, and ii) estimates of mineral element stocks in never thawed (since deposition) ice-rich Yedoma permafrost and previously thawed and partly refrozen Alas deposits. The pXRF method for mineral element quantification is non-destructive and offers a complement to the classical dissolution and measurement by optical emission spectrometry (ICP-OES) in solution. Using this method, mineral element concentrations (Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr) were assessed on 1,292 sediment samples from the Yedoma domain with lower analytical effort and lower costs relative to the ICP-OES method. The pXRF measured concentrations were calibrated using alkaline fusion and ICP-OES measurements on a subset of 144 samples (R2 from 0.725 to 0.996). The results highlight that i) the mineral element stock in sediments of the Yedoma domain (1,387,000\uffc2\uffa0km2) is higher for Si, followed by Al, Fe, K, Ca, Ti, Mn, Zr, Sr, and Zn, and that ii) the stock in Al and Fe (598 \uffc2\uffb1 213 and 288 \uffc2\uffb1 104\uffc2\uffa0Gt) is in the same order of magnitude as the OC stock (327\uffe2\uff80\uff93466\uffc2\uffa0Gt).
", "keywords": ["ddc:550", "late pleistocene- holocene", "thermokarst", "Science", "Q", "X-ray fluorescence", "01 natural sciences", "6. Clean water", "13. Climate action", "arctic", "alas", "Institut f\u00fcr Geowissenschaften", "thaw", "mineralogy", "late pleistocene \u2013 holocene", "bootstrapping technique", "0105 earth and related environmental sciences"]}, "links": [{"href": "https://doi.org/10.3389/feart.2021.703304"}, {"rel": "related", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/Frontiers%20in%20Earth%20Science", "name": "related record", "description": "related record", "type": "application/json"}, {"rel": "self", "type": "application/geo+json", "title": "10.3389/feart.2021.703304", "name": "item", "description": "10.3389/feart.2021.703304", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.3389/feart.2021.703304"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2021-09-03T00:00:00Z"}}, {"id": "10.5061/dryad.2hd320d", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:42Z", "type": "Dataset", "title": "Data from: Unraveling the mechanisms underlying pulse dynamics of soil respiration in tropical dry forests", "description": "unspecifiedWaring&Powers_ERL_for Dryad", "keywords": ["Tropical dry forest", "Holocene", "13. Climate action", "Birch effect", "15. Life on land", "Soil carbon"], "contacts": [{"organization": "Waring, Bonnie G., Powers, Jennifer S.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.2hd320d"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.2hd320d", "name": "item", "description": "10.5061/dryad.2hd320d", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.2hd320d"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-07-19T00:00:00Z"}}, {"id": "10.5061/dryad.11m00", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:41Z", "type": "Dataset", "title": "Data from: Shrub encroachment can reverse desertification in semi-arid Mediterranean grasslands", "description": "unspecifiedEnvironmental and soil data from encroached/unencroached Stipa tenacissima steppes from SpainEnvironmental (coordinates, elevation, slope, aspect, mean annual rainfall and temperature) and soil (pH, organic carbon, total nitrogen, total phosphorus, soil respiration, potassium and nitrogen mineralization) variables at the microsite and site scales for Stipa tenacissima grasslands with and without sprouting shrubs in a gradient from central to southern Spain.Ecol_Lett_2009.zip", "keywords": ["2. Zero hunger", "Stipa tenacissima", "Holocene", "13. Climate action", "semi-arid", "15. Life on land", "Plant successional dynamics", "shrub encroachment", "Desertification"], "contacts": [{"organization": "Maestre, Fernando T., Bowker, Matthew A., Puche, Mar\u00eda D., Bel\u00e9n Hinojosa, M., Mart\u00ednez, Isabel, Garc\u00eda-Palacios, Pablo, Castillo, Andrea P., Soliveres, Santiago, Luzuriaga, Ar\u00e1ntzazu L., S\u00e1nchez, Ana M., Carreira, Jos\u00e9 A., Gallardo, Antonio, Escudero, Adri\u00e1n,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.11m00"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.11m00", "name": "item", "description": "10.5061/dryad.11m00", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.11m00"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-08-13T00:00:00Z"}}, {"id": "10.5061/dryad.3216c", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:42Z", "type": "Dataset", "title": "Data from: Peatland vascular plant functional types affect methane dynamics by altering microbial community structure", "description": "Open Access1. Peatlands are natural sources of atmospheric methane (CH4), an important greenhouse gas. It is established that peatland methane dynamics are controlled by both biotic and abiotic conditions, yet the interactive effect of these drivers is less studied and consequently poorly understood. 2. Climate change affects the distribution of vascular plant functional types (PFTs) in peatlands. By removing specific PFTs, we assessed their effects on peat organic matter chemistry, microbial community composition and on potential methane production (PMP) and oxidation (PMO) in two microhabitats (lawns and hummocks). 3. Whilst PFT removal only marginally altered the peat organic matter chemistry, we observed considerable changes in microbial community structure. This resulted in altered PMP and PMO. PMP was slightly lower when graminoids were removed, whilst PMO was highest in the absence of both vascular PFTs (graminoids and ericoids), but only in the hummocks. 4. Path analyses demonstrate that different plant\u2013soil interactions drive PMP and PMO in peatlands and that changes in biotic and abiotic factors can have auto-amplifying effects on current CH4 dynamics. 5. Synthesis. Changing environmental conditions will, both directly and indirectly, affect peatland processes, causing unforeseen changes in CH4 dynamics. The resilience of peatland CH4 dynamics to environmental change therefore depends on the interaction between plant community composition and microbial communities.", "keywords": ["methanotrophic communities", "Sphagnum cuspidatum", "Vaccinium oxycoccus", "Andromeda polifolia", "Sphagnum magellanicum", "Eriophorum angustifolium", "Graminoids", "Rhynchospora alba", "Sphagnum spp.", "path analysis", "mid\u2013infrared spectroscopy", "Empetrum nigrum", "Sphagnum rubellum", "CH4", "Holocene", "Ericoids", "Calluna vulgaris", "methanogenesis", "15. Life on land", "Eriophorum vaginatum", "Sphagnum\u2013dominated peatlands", "13. Climate action", "path analysis; Sphagnum magellanicum; Vaccinium oxycoccus; mid\u2013infrared spectroscopy; Graminoids; Plant\u2013soil (below-ground) interactions; Empetrum nigrum; Sphagnum spp.; Eriophorum vaginatum; Calluna vulgaris; methanotrophic communities; methanogenesis; CH4; PLFA; Sphagnum cuspidatum; Sphagnum\u2013dominated peatlands; Rhynchospora alba; Eriophorum angustifolium; Andromeda polifolia; pmoA; Ericoids; Sphagnum rubellum; Erica tetralix; Holocene", "PLFA", "pmoA", "Erica tetralix"], "contacts": [{"organization": "Robroek, Bjorn J. M., Jassey, Vincent E. J., Kox, Martine A. R., Berendsen, Roeland L., Mills, Robert T. E., C\u00e9cillon, Lauric, Puissant, J\u00e9remy, Meima\u2013Franke, Marion, Bakker, Peter A. H. M., Bodelier, Paul L. E., Meima-Franke, Marion,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.3216c"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.3216c", "name": "item", "description": "10.5061/dryad.3216c", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.3216c"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-04-20T00:00:00Z"}}, {"id": "10.5061/dryad.5jf6j1r", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-09-22T16:19:43Z", "type": "Dataset", "created": "2024-08-14", "title": "Data from: Large, climate-sensitive soil carbon stocks mapped with pedology-informed machine learning in the North Pacific coastal temperate rainforest", "description": "unspecified# North Pacific Coastal Temperate Rainforest (NPCTR) Pedon and Soil Carbon Database Access this dataset on Dryad: [https://doi.org/10.5061/dryad.5jf6j1r](https://doi.org/10.5061/dryad.5jf6j1r) This database compiles pedon data and soil organic carbon stock data (ca. 1300 soil profile descriptions) from various sources across coastal British Columbia and southeast Alaska. ## Description of the data and file structure The file entitled *McNicoletal-2024-NPCTR-Pedon-SOC-Database.xlsx* contains the data for all of the soil pedons and corresponding soil organic carbon stock data. The file has four tables: a master table with all the data, a pedon table with pedon-specific data, a horizon table with horizon-specific data, and a summary table. *McNicoletal-2024-NPCTR-Pedon-SOC-Database.xlsx* contains the following columns: * source: source reference (see Source References tab) for the pedon data. In most cases, these are published database data (e.g., Shaw et al. 2018), or published manuscripts, but include one thesis and unpublished data from the Hakai Institute. * pedon_id: this is the identifier extracted from the source reference. In many cases, these are named pedon locations, but sometimes they are pedon codes (e.g. NRCS data) or numeric identifiers (e.g. Shaw et al. 2018). ,* order: this is the soil order using the fullest taxonomic classification available in the source reference. It has not yet been simplified for aggregation, down to the singular order designations (e.g., HISTOSOL). * lat: the most accurate latitude value reported for the pedon location in decimal degrees. * lon: the most accurate longitude value reported for the pedon location in decimal degrees. * latlon_q: the quality flag for the LAT and LON values based upon criteria described in the manuscript (doi: 10.1088/1748-9326/aaed52). Generally, too few decimal places (low precision), obvious inaccuracy, or pre-gps sampling received LOW. * horizon: the detailed horizon designation from the source reference with as many suffixes (e.g., Bh\u2026) as was reported. * horizon_number: indicates the order of horizons within the master table. A horizon can be uniquely identified using its pedon id and horizon number. * horizon_type: organic or mineral horizon. * depth2: the depth of the top of the soil horizon in centimeters (cm). * depth1: the depth of the bottom of the soil horizon in centimeters (cm). * depth: the depth of the soil horizon (DEPTH2-DEPTH1) in centimeters (cm). * bulk_density: the measured or estimated/assigned (in beige) dry bulk density value in grams per cubic centimeter (g cm-3). The Supplementary Information provides a breakdown of steps to estimate bulk density. Most values are taken from Shaw et al. 2015 (Table 8). * bd_method: whether the assigned value was measured or estimated. 0 indicates that the value is measured. 1 indicates that the value is estimated using a lookup table. This procedure was replicated to fill data gaps in multiple datasets. (More information in manuscript supplement). * cf: the mineral coarse fragment content in percent (% volume). Generally, these values are reported, but where filled, they are highlighted and the Supplementary Information explains how. * cf_method: whether the assigned value was measured or estimated. 0 indicates that the value is measured. 1 indicates that the value is estimated using a lookup table or other methods. This procedure was replicated to fill data gaps in multiple datasets. (More information in manuscript supplement). 2 indicates that the cf was originally null and 0 was assumed for calculation purposes. * cconc: the reported or estimated horizon carbon concentration in percent (% mass). Where estimated, these values are highlighted in color, and source reference-specific methods are described in Supplementary Info. * cconc_method: whether the assigned value was measured or estimated. 0 indicates that the value is measured. 1 indicates that the value is estimated using a lookup table or other methods. This procedure was replicated to fill data gaps in multiple datasets. 2 indicates that the cconc was estimated using linear regression. (More information in manuscript supplement). * mineral_d: the deepest depth of the subsurface mineral horizons in centimeters (cm) (maximum value 100 cm). * ff_d: the total depth of forest floor organic horizons or Histosol depth in centimeters (cm) (no maximum value). * total_d: the total depth of soil accounted for in SOC stock estimate in centimeters (cm) (Mineral_D + FF_D). * ccontent: calculated carbon content in grams of carbon per square meter (gC m-2) for the horizon. * total_c: summed carbon content across all reported horizons in grams of carbon per square meter (gC m-2). * ccontent_1m: calculated carbon content in grams of carbon per square meter (gC m-2) for the horizon. Horizons below 100 cm in the subsurface mineral soil are assigned zero, while horizons that traverse this threshold are reduced proportionally by the fraction of the horizon below it. * total_c_1m: summed carbon content across all reported horizons down to 1 m in the subsurface mineral soils and 1 m in histosols in megagrams of carbon per hectare (Mg C ha-1). * pedon_start: a boolean value which, if true, indicates that the row contains pedon-specific data and is the master row for that pedon. The value 'NA' corresponds to any missing information in columns of type *object*. For columns that are *float64* or *int*, any empty cells represent missing information. #### Soil Organic Carbon Stock Map This raster [.tif] is the predicted soil organic carbon for the North Pacific coastal temperate rainforest. Content is displayed in megagrams of carbon per hectare (Mg ha-1) to 1 m in mineral soil, plus overlying organic horizons. Map values are the output of a random forest machine learning algorithm trained on pedon data from within British Columbia and southeast Alaska only, therefore confidence is low for predictions south of the US-Canada border and predictions in that region have not been validated. Lakes, glaciers, and ice fields have also not been masked from the map. More information on the map can be found in the associated manuscript. FluxProject_SOCmap.7z #### N Pacific coastal temperate rainforest pedon and soil carbon database ## Version changes **10-oct-2024:**\u00a0The original database was updated and cleaned using Python Pandas to create a standardized database that combined all data sources into one. Along with all of the original data characteristics, the database now denotes how missing data was gap-filled and includes other added columns to create a more user-friendly experience. The database includes four tables: a master table, a pedon-specific table, a horizon-specific table, and a summary table. References, acknowledgments, and field descriptors can be found within\u00a0the *McNicoletal-2024-NPCTR-Pedon-SOC-Database.xlsx*\u00a0and\u00a0*README.md*\u00a0file. The original data and the script used to clean the data can be found on GitHub (see below). ## Sharing/Access information Links to other publicly accessible locations of the data. Raw and cleaned data and code can be found on GitHub: * Github:\u00a0[https://github.com/McNicol-Lab/npctr-soil-carbon-dataset-tidying-Bothra](https://github.com/McNicol-Lab/npctr-soil-carbon-dataset-tidying-Bothra) Sources from which the data was derived can be found in\u00a0*McNicoletal-2024-NPCTR-Pedon-SOC-Database.xlsx*\u00a0and the primary article: * Primary article:\u00a0[https://doi.org/10.1088/1748-9326/aaed52](https://doi.org/10.1088/1748-9326/aaed52)", "keywords": ["Holocene", "temperate rainforest", "13. Climate action", "Anthropocene", "Pedology", "FOS: Earth and related environmental sciences", "15. Life on land", "16. Peace & justice", "Soil carbon"], "contacts": [{"organization": "McNicol, Gavin, Bulmer, Chuck, D'Amore, David, Sanborn, Paul, Saunders, Sari, Giesbrecht, Ian, Arriola, Santiago Gonzalez, Bidlack, Allison, Butman, David, Buma, Brian,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.5jf6j1r"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.5jf6j1r", "name": "item", "description": "10.5061/dryad.5jf6j1r", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.5jf6j1r"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-11-19T00:00:00Z"}}, {"id": "10.5061/dryad.8071s", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-09-22T16:19:44Z", "type": "Dataset", "title": "Data from: Soil organic matter quantity and quality shape microbial community compositions of subtropical broadleaved forests", "description": "unspecifiedAs two major forest types in the subtropics, broadleaved evergreen and broadleaved deciduous forests have long interested ecologists. However, little is known about their belowground ecosystems despite their ecological importance in driving biogeochemical cycling. Here, we used Illumina MiSeq sequencing targeting 16S rRNA gene and a microarray named GeoChip targeting functional genes to analyse microbial communities in broadleaved evergreen and deciduous forest soils of Shennongjia Mountain of Central China, a region known as \u2018The Oriental Botanic Garden\u2019 for its extraordinarily rich biodiversity. We observed higher plant diversity and relatively richer nutrients in the broadleaved evergreen forest than the deciduous forest. In odds to our expectation that plant communities shaped soil microbial communities, we found that soil organic matter quantity and quality, but not plant community parameters, were the best predictors of microbial communities. Actinobacteria, a copiotrophic phylum, was more abundant in the broadleaved evergreen forest, while Verrucomicrobia, an oligotrophic phylum, was more abundant in the broadleaved deciduous forest. The density of the correlation network of microbial OTUs was higher in the broadleaved deciduous forest but its modularity was smaller, reflecting lower resistance to environment changes. In addition, keystone OTUs of the broadleaved deciduous forest were mainly oligotrophic. Microbial functional genes associated with recalcitrant carbon degradation were also more abundant in the broadleaved deciduous forests, resulting in low accumulation of organic matters. Collectively, these findings revealed the important role of soil organic matter in shaping microbial taxonomic and functional traits.", "keywords": ["2. Zero hunger", "Holocene", "Microbial community", "Uncultured bacteria", "Species interactions", "15. Life on land"], "contacts": [{"organization": "Ding, Junjun, Zhang, Yuguang, Wang, Mengmeng, Sun, Xin, Cong, Jing, Deng, Ye, Lu, Hui, Yuan, Tong, Van Nostrand, Joy D., Li, Diqiang, Zhou, Jizhong, Yang, Yunfeng,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.8071s"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.8071s", "name": "item", "description": "10.5061/dryad.8071s", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.8071s"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2015-09-10T00:00:00Z"}}, {"id": "10.5061/dryad.926nd", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:44Z", "type": "Dataset", "title": "Data from: Do plant traits explain tree seedling survival in bogs?", "description": "unspecifiedSeedlingtraitdataexperiment2Experiment 2 Morphological traits were assessed independently of Experiment 1. We grew tree seedlings under optimal conditions by planting pre-grown 4 weeks old tree seedlings ( see plant material) into the center of a (10 cm wide) pot, using a density of one seedling per pot. The pots were filled with sterilized organic soil, watered daily and kept under the same glasshouse light and humidity conditions as Experiment 1. Pots were arranged in five replicated blocks. Both the blocks and the pots within a block were randomly moved once a week. For more information on columnheadings see Table 1 in the associated MSMotherfile.xlsTraitsandsurvivalTraits assessed in Experiment 2 were used to relate to seedling survival in Experiment 1. This file contains trait data from experiment 2 and seedling survival of seven conifer species in experiment 1 kept under contrasting moisture conditions (Dry, Wet)traitsandsurvival.xlsxTraitplasticityseedlingsmosssoilTo assess the plasticity of the morphological traits, we compared the morphological traits based on seedlings from Experiment 2 (grown on soil) with values measured on seedlings in Experiment 1 under contrasting moisture conditionsTraitflexibilitymosssoil.xlsxgerminationTo assess germination, we introduced seeds to Experiment 1 in the third week, corresponding to the time when pot water contents had stabilized. Three seeds were placed around the seedling of the same species, on the capitulum of a moss individual, using 3 x 140 = 420 seeds in total. Germination was checked twice a week until harvest, 5 weeks later. We considered a seed germinated when the integument had broken and a \u2018shoot\u2019 of at least 1 mm had emerged from the seed.Mossgrowth and seedling performanceThe file contains growth and survival of seedlings grown on moss in experiment 1 as well as the moss growth itselfRelatie tussen mosgroei en seedling performance.xlsx", "keywords": ["2. Zero hunger", "(Pinus sylvestris L.", "tree encroachment", "Holocene", "mires", "Picea sitchensis (Bong.) Carri\u00e8re", "15. Life on land", "Pinus sylvestris L.", "Picea rubens Sarg.", "Picea glauca (Moench) Voss", "Bogs", "Pinus banksiana Lamb", "Seedlings", "Picea glauca (Moench) Voss)", "Picea mariana (Mill.) Britton", "Picea mariana (Mill.) Britton Sterns & Poggenb.", "Sterns & Poggenb.", "peatlands", "Pinus nigra Arnold"], "contacts": [{"organization": "Limpens, Juul, van Egmond, Emily, Li, Bingxi, Holmgren, Milena,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.926nd"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.926nd", "name": "item", "description": "10.5061/dryad.926nd", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.926nd"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2013-06-24T00:00:00Z"}}, {"id": "10.5061/dryad.bj0436h", "type": "Feature", "geometry": null, "properties": {"license": "unspecified", "updated": "2026-09-22T16:19:45Z", "type": "Dataset", "title": "Data from: Difference in reproductive mode rather than ploidy explains niche differentiation in sympatric sexual and apomictic populations of Potentilla puberula", "description": "unspecifiedBioclimatic variables (bio01 - bio19) were obtained in April 2018 from CHELSA database at http://chelsa-climate.org/ with a spatial resolution of 30\u2033. If you reuse these variables, please cite the original data source: Karger DN, Conrad O, B\u00f6hner J, Kawohl T, Kreft H, Soria-Auza RW, Zimmermann NE, Linder HP, Kessler M (2017) Data from: Climatologies at high resolution for the earth's land surface areas. Dryad Digital Repository. https://doi.org/10.5061/dryad.kd1d4 And the associated publication: Karger DN, Conrad O, B\u00f6hner J, Kawohl T, Kreft H, Soria-Auza RW, Zimmermann NE, Linder HP, Kessler M (2017) Climatologies at high resolution for the earth's land surface areas. Scientific Data 4: 170122. https://doi.org/10.1038/sdata.2017.122 \u00a0 The normalised difference vegetation index (NDVI) was retrieved in April 2018 from NASA through a Moderate Resolution Imaging Spectroradiometer (MODIS; modis.gsfc.nasa.gov) that incorporates a MOD13Q1 sensor. If you reuse these data, please cite the original data source: Didan K (2015) MOD13Q1 MODIS/Terra Vegetation Indices 16-Day L3 Global 250m SIN Grid V006 [Data set]. NASA EOSDIS LP DAAC. https://doi.org/10.5067/MODIS/MOD13Q1.006 \u00a0 Potentilla_puberula_Alonso-Marcos_et_al_ecological_variables_population_level_2018 Appendix 1. Description of 238 populations of Potentilla puberula sampled between 1999 and 2015 in the Eastern European Alps. Geographical and collection information, number of sampled individuals (N) and cytotype composition, as well as source of flow cytometric data (FCM) are given. Topographic parameters (elevation, in m a.s.l.; inclination and aspect, in degrees), a variable representing the land use intensity, an index of vegetation density (NDVI) and bioclimatic descriptors (Bio01-Bio19, from the Chelsea Climate database) are noted per each population. Please see README for citation information. Soil parameters are reported for 121 populations visited in 2015, including pH, carbonate (CO3--), organic carbon (Corg) and nitrogen content (Ntot; in g/kg), cation exchange capacity (CEC), cations (in mmol/kg), and base saturation (BS, in %). Abbreviations: AT Andreas Tribsch; CD Christoph Dobe\u0161; FDN Flavia Domizia Nardi; HAM Henar Alonso-Marcos; JAH Julian Ananda Haider; JP Juraj Paule; RS Roswitha Schmickl; SSc Susanne Scheffknecht; SSt Simon Stifter; TW Thomas Wilhalm. \u00a0 \u00a0 Potentilla_puberula_Alonso-Marcos_et_al_Flow_Cytometry_2018 Appendix 2. Flow cytometric data of 1,878 individuals from 115 populations collected between 1999 and 2013. Identification, population and used device for the analyses are indicated. Used internal standards are provided: either Solanum pseudocapsicum (Sps) or Lycopersicon esculentum cv. Stupick\u00e9 poln\u00ed ty\u010dkov\u00e9 ran\u00e9 (Sly). Since several individuals from the same population were pooled in each measurement (the number of individuals included in each measurement is provided), more than one sample peak was found in some measurements. For each of these peaks (Peak1, Peak2, Peak3 and Peak4) and for the standard, the count of particles, the mean fluorescence and the coefficient of variation are reported. The sample/standard ratio was used to infer the ploidy level of each peak. The number of individuals (N_Peak1 to N_Peak4) per each determined ploidy level (Ploidy_Peak1 to Ploidy_Peak4) are given.", "keywords": ["bioclimatic variables", "Holocene", "15. Life on land", "Potentilla puberula"], "contacts": [{"organization": "Alonso-Marcos, Henar, Nardi, Flavia Domizia, Scheffknecht, Susanne, Tribsch, Andreas, H\u00fclber, Karl, Dobes, Christoph,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.bj0436h"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.bj0436h", "name": "item", "description": "10.5061/dryad.bj0436h", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.bj0436h"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2019-03-11T00:00:00Z"}}, {"id": "10.5061/dryad.p6s0407", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:19:47Z", "type": "Dataset", "title": "Data from: Litter type and termites regulate root decomposition across contrasting savanna land-uses", "description": "unspecifiedRoot litter mass loss in SerengetiRoot litter mass loss (undecomposed weights, ash contents and decomposed weights) for litter used in an experiment to determine the impact of land-use on belowground nutrient cycling inside and outside the Serengeti National Park, Tanzania from 2016 to 2017 as part of the AfricanBioServices project. Litter data includes the main land-use experiment and a supporting common garden experiment where several species of litter were buried in central Serengeti. The datafile also includes supporting data on tree allometrics (i.e. height, diameter at breast height) and soil properties (texture and organic carbon content).Root.decomp.Serengeti.landuse.common.garden.txtTermite cafeteria litter experiment in SerengetiRoot, leaf and stem mass loss (undecomposed weights, ashed contents and decomposed weights) for litter buried near termite mounds used to determine termite (non) preference for different litter types in Seronera, central Serengeti National Park, Tanzania during the wet season 2017 as part of the AfricanBioServices project.Termite.cafeteria.root.decomposition.txt", "keywords": ["2. Zero hunger", "Heteropogon contortus", "Cynodon dactylon", "Acacia gerrardii", "Microchloa kunthii", "leguminous trees", "Holocene", "Indigofera volkensii", "Pennisetum mezianum", "Themeda triandra", "15. Life on land", "termite ecology", "Zea mays", "Digitaria macroblephara", "Mariscus amourpus", "Acacia tortilis", "Chloris pycnothrix", "root traits", "root decomposition", "Crateostigma plantagineum", "Solanum incanum", "Balanites aegyptiaca", "Panicum maximum"], "contacts": [{"organization": "Smith, Stuart W., Speed, James D. M., Bukombe, John, Hassan, Shombe N., Lyamuya, Richard D., Mtweve, Philipo Jacob, Sundsdal, Anders, Graae, Bente J.,", "roles": ["creator"]}]}, "links": [{"href": "https://doi.org/10.5061/dryad.p6s0407"}, {"rel": "self", "type": "application/geo+json", "title": "10.5061/dryad.p6s0407", "name": "item", "description": "10.5061/dryad.p6s0407", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main/items/10.5061/dryad.p6s0407"}, {"rel": "collection", "type": "application/json", "title": "Collection", "name": "collection", "description": "Collection", "href": "https://repository.soilwise-he.eu/cat/collections/metadata:main"}], "time": {"date": "2018-10-16T00:00:00Z"}}, {"id": "1959.4/unsworks_64930", "type": "Feature", "geometry": null, "properties": {"updated": "2026-09-22T16:22:24Z", "type": "Journal Article", "created": "2017-04-14", "title": "Climate legacies drive global soil carbon stocks in terrestrial ecosystems", "description": "Our findings indicate the importance of paleoclimatic information to improve quantitative predictions of global soil C stocks.
With permafrost thaw, significant amounts of organic carbon (OC) previously stored in frozen deposits are unlocked and become potentially available for microbial mineralization. This is particularly the case in ice-rich regions such as the Yedoma domain. Excess ground ice degradation exposes deep sediments and their OC stocks, but also mineral elements, to biogeochemical processes. Interactions of mineral elements and OC play a crucial role for OC stabilization and the fate of OC upon thaw, and thus regulate carbon dioxide and methane emissions. In addition, some mineral elements are limiting nutrients for plant growth or microbial metabolic activity. A large ongoing effort is to quantify OC stocks and their lability in permafrost regions, but the influence of mineral elements on the fate of OC or on biogeochemical nutrient cycles has received less attention and there is an overall lack of mineral element content analyses for permafrost sediments. Here, we combine portable X-ray fluorescence (pXRF) with a bootstrapping technique to provide i) the first large-scale Yedoma domain Mineral Concentrations Assessment (YMCA) dataset, and ii) estimates of mineral element stocks in never thawed (since deposition) ice-rich Yedoma permafrost and previously thawed and partly refrozen Alas deposits. The pXRF method for mineral element quantification is non-destructive and offers a complement to the classical dissolution and measurement by optical emission spectrometry (ICP-OES) in solution. Using this method, mineral element concentrations (Si, Al, Fe, Ca, K, Ti, Mn, Zn, Sr and Zr) were assessed on 1,292 sediment samples from the Yedoma domain with lower analytical effort and lower costs relative to the ICP-OES method. The pXRF measured concentrations were calibrated using alkaline fusion and ICP-OES measurements on a subset of 144 samples (R2 from 0.725 to 0.996). The results highlight that i) the mineral element stock in sediments of the Yedoma domain (1,387,000\uffc2\uffa0km2) is higher for Si, followed by Al, Fe, K, Ca, Ti, Mn, Zr, Sr, and Zn, and that ii) the stock in Al and Fe (598 \uffc2\uffb1 213 and 288 \uffc2\uffb1 104\uffc2\uffa0Gt) is in the same order of magnitude as the OC stock (327\uffe2\uff80\uff93466\uffc2\uffa0Gt). Cryogenic weathering is a key driver of periglacial sediment composition and properties. Selective mineral-grain weathering caused by freeze-thaw cycles in permafrost environments has the ability to dominate this process, leading to silt-rich grain-size distributions. The cryogenic weathering index (CWI) is a promising tool to quantify cryogenic weathering and freezing conditions. It considers the low resistance of quartz to freeze-thaw cycles compared to feldspars. Using this approach, this study aims to decipher post-depositional weathering by reconstructing cryogenic late Pleistocene Yedoma origins of the Yedoma stratotype exposure Duvanny Yar. To estimate the recent environmental endmember and to determine the initial mineral composition of sediment until freezing, the distribution of CWI in the active layer was studied. In addition to CWI, we studied mineral composition, heavy mineral distribution, grain size distribution and grain morphology. We suggest that cryogenic weathering likely altered polygenetic deposits (fluvial, nival, colluvial, lacustrine, alluvial, and aeolian processes) during sediment and ground ice accumulation. Moreover, we found two CWI distribution peaks in the late Pleistocene - Holocene sediments at the boundaries between glacial and interglacial ages. In conclusion, we see that the Duvanny Yar sediment facies varied by CWI, but also with grain-size distribution, suggesting environmental changes during formation. Nevertheless, post-depositional processes like cryogenic weathering have influenced sediment characteristics and should be considered in paleoenvironmental reconstructions.