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The curse of the past

  • One challenge for modern agricultural management schemes is the reduction of harmful effects on the envi-ronment, e.g. in terms of the emission of nutrients. Sampling the effluent of tile drains is a very efficient way to sample seepage water from larger areas directly underneath the main rooting zone. Time series of solute con-centration in tile drains can be linked to agricultural management data and thus indicate the efficacy of individual management measures. To that end, the weekly runoff and solute concentration were determined in long-term measurement campaigns at 25 outlets of artificial tile drains at 19 various arable fields in the German federal state of Mecklenburg-Vorpommern. The study sites were distributed within a 23,000 km(2) region and were deemed representative of intense arable land use. In addition, comprehensive meteorological and man-agement data were provided. To disentangle the different effects, monitoring data were subjected to a principal component analysis. Loadings on the prevailing principal componentsOne challenge for modern agricultural management schemes is the reduction of harmful effects on the envi-ronment, e.g. in terms of the emission of nutrients. Sampling the effluent of tile drains is a very efficient way to sample seepage water from larger areas directly underneath the main rooting zone. Time series of solute con-centration in tile drains can be linked to agricultural management data and thus indicate the efficacy of individual management measures. To that end, the weekly runoff and solute concentration were determined in long-term measurement campaigns at 25 outlets of artificial tile drains at 19 various arable fields in the German federal state of Mecklenburg-Vorpommern. The study sites were distributed within a 23,000 km(2) region and were deemed representative of intense arable land use. In addition, comprehensive meteorological and man-agement data were provided. To disentangle the different effects, monitoring data were subjected to a principal component analysis. Loadings on the prevailing principal components and spatial and temporal patterns of the component scores were considered indicative of different processes. Principal component scores were then related to meteorological and management data via random forest modelling. Hydrological conditions and weather were identified as primary driving forces for the nutrient discharge behaviour of the drain plots, as well as the nitrogen balance. In contrast, direct effects of recent agricultural management could hardly be identified. Instead, we found clear evidence of the long-term and indirect effects of agriculture on nearly all solutes. We conclude that tile drain effluent quality primarily reflected the soil-internal mobilisation or de-mobilisation of nutrients and related solutes rather than allowing inferences to be drawn about recent individual agricultural management measures. On the other hand, principal component analysis revealed a variety of indirect and long-term effects of fertilisation on solutes other than nitrogen or phosphorus that are still widely overlooked in nutrient turnover studies.show moreshow less

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Metadaten
Author details:Jörg SteidlORCiD, Gunnar LischeidORCiDGND, Clemens EngelkeORCiDGND, Franka Koch
DOI:https://doi.org/10.1016/j.agee.2021.107787
ISSN:0167-8809
ISSN:1873-2305
Title of parent work (English):Agriculture, Ecosystems & Environment
Subtitle (English):What can tile drain effluent tell us about arable field management?
Publisher:Elsevier
Place of publishing:Amsterdam
Publication type:Article
Language:English
Date of first publication:2021/12/09
Publication year:2021
Release date:2024/01/02
Tag:Agricultural management; Multivariate statistics; Nitrate; Phosphorus; Random forest modelling; Tile drains; Water; pollution
Volume:326
Article number:107787
Number of pages:14
Funding institution:State Office for the Environment, Nature Conservation and Geology,; Mecklenburg-Vorpommern, Germany
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Umweltwissenschaften und Geographie
DDC classification:9 Geschichte und Geografie / 91 Geografie, Reisen / 910 Geografie, Reisen
Peer review:Referiert
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