Mapping and validating predictions of soil bacterial biodiversity using European and national scale datasets

Griffiths, Robert I.; Thomson, Bruce C.; Plassart, Pierre; Gweon, Hyun S.; Stone, D.; Creamer, Rachel; Lemanceau, Philippe; Bailey, Mark

doi:10.1016/j.apsoil.2015.06.018

Cited by 66 publications

(48 citation statements)

References 26 publications

(28 reference statements)

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“…Another soil property that can play an important and significant role on C dynamics is pH; varying from each sampling areas and affecting soil reduction and oxidation processes into the soil can determine the fate of C substrate addressing to accumulation or mineralization [72] and vice versa. Indeed, in our soil survey, C accumulation in acid and sub-acid soil (OM, OF, CT, NAT) was higher than under neutral pH (ACI, ACR, V), thus confirming the negative correlation between soil pH and TOC content, as also observed by other authors [73], who related higher pH values to higher microbial mineralization activity. Soil pH, furthermore, is an important factor revealing TIC distribution across land uses and soil acidification processes [5].…”

Section: Main Factors Affecting C Accumulationsupporting

confidence: 92%

Factors Governing Total and Permanganate Oxidizable C Pools in Agricultural Soils from Southern Italy

et al. 2020

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The present investigation was aimed to quantify the three principal components of the soil carbon (C) stock, namely inorganic, organic and permanganate oxidizable, in 0–5 cm and 5–30 cm soil layers, of the main Mediterranean agricultural land coverages: olive grove, olive forest, citrus grove, vineyard, arable irrigated, arable rainfed and natural soil covered by Mediterranean scrub and garrigue. We assessed the contribution of soil properties and climatic variables on soil TOC and POxC by Pearson’s correlations, multiple linear regressions, principal component analyses and variance partitioning. NAT and both olive cropping systems showed the highest TOC concentration while the other land covers showed values ranging between 8.0 and 26.6 g kg−1. Soil POxC represented between 0.5% and 2.2% of the total soil C. A large number of interrelated factors govern soil C accumulation in Mediterranean agroecosystems. Rainfall and temperature had a selective effect on soil C distribution between the sampling areas, while among soil properties, texture exerted a prominent effect, resulting in positive effects from clay and negative effects from sand. Soil POxC concentration showed a similar trend to soil TOC in all land uses although on each of them represent a different TOC portion.

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Section: Main Factors Affecting C Accumulationsupporting

confidence: 92%

Factors Governing Total and Permanganate Oxidizable C Pools in Agricultural Soils from Southern Italy

et al. 2020

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“…The results in Fig 5c show that the observed and predicted first axis ordination scores were highly related ( r 2 = 0.88) demonstrating that it is possible to predict broad scale community change from individual OTU relative abundance pH models. These findings add to a growing body of literature on the predictability of soil bacterial communities 33–35 ; but furthermore demonstrate the utility of our overall approach in deriving meaningful ecological information from matches to a 16S rRNA sequence database incorporating ecological responses.…”

Section: Resultssupporting

confidence: 52%

Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database

Jones

Goodall

George

et al. 2019

Preprint

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12High-throughput sequencing 16S rRNA gene surveys have enabled new insights into the 13 diversity of soil bacteria, and furthered understanding of the ecological drivers of abundances 14 across landscapes. However, current analytical approaches are of limited use in formalising 15 syntheses of the ecological attributes of taxa discovered, because derived taxonomic units are 16 typically unique to individual studies and sequence identification databases only characterise 17 taxonomy. To address this, we used sequences obtained from a large nationwide soil survey 18 (GB Countryside Survey, henceforth CS) to create a comprehensive soil specific 16S reference 19 database, with coupled ecological information derived from the survey metadata. Specifically, 20 we modelled taxon responses to soil pH at the OTU level using hierarchical logistic regression 21 (HOF) models, to provide information on putative landscape scale pH-abundance responses. 22 We identify that most of the soil OTUs examined exhibit predictable abundance responses 23 across soil pH gradients, though with the exception of known acidophilic lineages, the pH 24 optima of OTU relative abundance was variable and could not be generalised by broad 25 taxonomy. This highlights the need for tools and databases to predict ecological traits at finer 26 taxonomic resolution. We further demonstrate the utility of the database by testing against 27 geographically dispersed query 16S datasets; evaluating efficacy by quantifying matches, and 28 accuracy in predicting pH responses of query sequences from a separate large soil survey. We 29 found that the CS database provided good coverage of dominant taxa; and that the taxa 30 indicating soil pH in a query dataset corresponded with the pH classifications of top matches 31 in the CS database. Furthermore we were able to predict query dataset community structure, 32 using predicted abundances of dominant taxa based on query soil pH data and the HOF models 33 of matched CS database taxa. The database with associated HOF model outputs is released as 34 an online portal for querying single sequences of interest (https://shiny-apps.ceh.ac.uk/ID-35 TaxER/), and flat files are made available for use in bioinformatic pipelines. The further 36 development of advanced informatics infrastructures incorporating modelled ecological 37 attributes along with new functional genomic information will likely facilitate large scale 38 exploration and prediction of soil microbial functional biodiversity under current and future 39 environmental change scenarios.40 41 42 Soil bacteria are highly diverse 1, 2 and are significant contributors to soil functionality. 43 Sequencing of 16S rRNA genes has enabled a wealth of new insights into the taxonomic 44 diversity of soil prokaryotic communities, revealing the ecological controls on a vast diversity 45 of yet to be cultured taxa with unknown functional potential 3 . However, despite thousands of 46 studies across the globe, we are still some way from synthesising the new knowledge on the ...

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“…As proof of the two concepts, we produced two maps of the soil biodiversity and habitat function of soils, one for the Netherlands and one for Europe. This work in progress is a follow up of earlier publications on a regional scale (e.g., Scotland [34], France [35,36], Netherlands [29]), and European scale (e.g., [20,21,30,32,37]). We took advantage of the progress of the monitoring of soil biological attributes in the Netherlands [11] and in many EU-projects, i.e., SoilTrec [38], Soilservice [16], EcoFINDERS [17,33], and LANDMARK [9].…”

Section: Introductionmentioning

confidence: 69%

“…The pilot contained samples from forestry, arable, and grassland systems in five climatic zones of Europe. Griffiths et al (2016) [20] found a strong correlation between soil pH and bacterial diversity (TRFLP analysis) in these samples, and produced a bacterial diversity map of Europe. Earthworms were excluded from the monitoring for logistical reasons [33], but [21] instead collected and harmonized existing earthworm data from 3838 sites in several European countries and applied digital soil mapping in order to produce a European map with earthworm community parameters, i.e., abundance, richness, and Shannon-Wiener index.…”

Section: Introductionmentioning

confidence: 89%

Mapping Soil Biodiversity in Europe and the Netherlands

et al. 2019

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Soil is fundamental for the functioning of terrestrial ecosystems, but our knowledge about soil organisms and the habitat they provide (shortly: Soil biodiversity) is poorly developed. For instance, the European Atlas of Soil Biodiversity and the Global Soil Biodiversity Atlas contain maps with rather coarse information on soil biodiversity. This paper presents a methodology to map soil biodiversity with limited data and models. Two issues were addressed. First, the lack of consensus to quantify the soil biodiversity function and second, the limited data to represent large areas. For the later issue, we applied a digital soil mapping (DSM) approach at the scale of the Netherlands and Europe. Data of five groups of soil organisms (earthworms, enchytraeids, micro-arthropods, nematodes, and micro-organisms) in the Netherlands were linked to soil habitat predictors (chemical soil attributes) in a regression analysis. High-resolution maps with soil characteristics were then used together with a model for the soil biodiversity function with equal weights for each group of organisms. To predict soil biodiversity at the scale of Europe, data for soil biological (earthworms and bacteria) and chemical (pH, soil organic matter, and nutrient content) attributes were used in a soil biodiversity model. Differential weights were assigned to the soil attributes after consulting a group of scientists. The issue of reducing uncertainty in soil biodiversity modelling and mapping by the use of data from biological soil attributes is discussed. Considering the importance of soil biodiversity to support the delivery of ecosystem services, the ability to create maps illustrating an aggregate measure of soil biodiversity is a key to future environmental policymaking, optimizing land use, and land management decision support taking into account the loss and gains on soil biodiversity.

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Mapping and validating predictions of soil bacterial biodiversity using European and national scale datasets

Cited by 66 publications

References 26 publications

Factors Governing Total and Permanganate Oxidizable C Pools in Agricultural Soils from Southern Italy

Factors Governing Total and Permanganate Oxidizable C Pools in Agricultural Soils from Southern Italy

Beyond taxonomic identification: integration of ecological responses to a soil bacterial 16S rRNA gene database

Mapping Soil Biodiversity in Europe and the Netherlands

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