6533b82ffe1ef96bd129475f
RESEARCH PRODUCT
Ecological network analysis reveals the inter-connection between soil biodiversity and ecosystem function as affected by land use across Europe
Carla PereiraMarie-lara BouffaudP.c. De RuiterRüdiger M. SchmelzDalila CostaP. Martins Da SilvaD. StoneD. StoneLaurent PhilippotRobert I. GriffithsMarc BuéePaula V. MoraisS.e. HannulaThomas BolgerFrancis MartinFilipe CarvalhoN.bohse HendriksenPierre PlassartPhilippe LemanceauSara MendesTara DirilgenRachel CreamerJörg RömbkeJ. Van LeeuwenDirk RedeckerRomeu FranciscoMarja WouterseMichiel RutgersBryan S. GriffithsJosé Paulo Sousasubject
0301 basic medicineSoil biodiversityNitrogenSoil biology[SDV]Life Sciences [q-bio]DIVERSITYSoil ScienceCarbon cycling and storageWiskundige en Statistische Methoden - BiometrisNutrient cyclingARBUSCULAR MYCORRHIZAL FUNGIFOOD WEBS03 medical and health sciencesFOREST SOILCARBON SEQUESTRATIONSoil functionsSoil ecologyQUALITYMICROBIAL COMMUNITIESMathematical and Statistical Methods - BiometrisBodembiologie2. Zero hungerSoil healthEcologyEcologySoil organic matterUSE SYSTEMSPhosphorus04 agricultural and veterinary sciencesSoil carbonSoil Biology15. Life on landPE&RCAgricultural and Biological Sciences (miscellaneous)Soil qualitySoil biodiversityTERRESTRIAL ECOSYSTEMS030104 developmental biologyAgronomyinternational040103 agronomy & agriculture0401 agriculture forestry and fisheriesEnvironmental scienceEXTRACELLULAR ENZYME-ACTIVITIESEcosystem functionNetwork analysisdescription
Soil organisms are considered drivers of soil ecosystem services (primary productivity, nutrient cycling, carbon cycling, water regulation) associated with sustainable agricultural production. Soil biodiversity was highlighted in the soil thematic strategy as a key component of soil quality. The lack of quantitative standardised data at a large scale has resulted in poor understanding of how soil biodiversity could be incorporated into legislation for the protection of soil quality. In 2011, the EcoFINDERS (FP7) project sampled 76 sites across 11 European countries, covering five biogeographical zones (Alpine, Atlantic, Boreal, Continental and Mediterranean) and three land-uses (arable, grass, forestry). Samples collected from across these sites ranged in soil properties; soil organic carbon (SOC), pH and texture. To assess the range in biodiversity and ecosystem function across the sites, fourteen biological methods were applied as proxy indicators for these functions. These methods measured the following: microbial diversity: DNA yields (molecular biomass), archaea, bacteria, total fungi and arbuscular mycorrhizal fungi; micro fauna diversity: nematode trophic groups; meso fauna diversity: enchytraeids and Collembola species; microbial function: nitrification, extracellular enzymes, multiple substrate induced respiration, community level physiological profiling and ammonia oxidiser/nitrification functional genes. Network analysis was used to identify the key connections between organisms under the different land use scenarios. Highest network density was found in forest soils and lowest density occurred in arable soils. Key taxomonic units (TUs) were identified in each land-use type and in relation to SOC and pH categorisations. Top-connected taxonomic units (i.e. displaying the most co-occurrence to other TUs) were identified for each land use type. In arable sites this was dominated by bacteria and fungi, while in grassland sites bacteria and fungi were most connected. In forest soils archaeal, enchytraeid and fungal TUs displayed the largest number of neighbours, reflecting the greatest connectivity. Multiple regression models were applied to assess the potential contribution of soil organisms to carbon cycling and storage and nutrient cycling of specifically nitrogen and phosphorus. Key drivers of carbon cycling were microbial biomass, basal respiration and fungal richness; these three measures have often been associated with carbon cycling in soils. Regression models of nutrient cycling were dependent on the model applied, showing variation in biological indicators. (C) 2015 Elsevier B.V. All rights reserved.
year | journal | country | edition | language |
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2016-01-01 |