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262 Research products

  • Rural Digital Europe
  • Article
  • 15. Life on land
  • FORTHEM Alliance

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anna Smetanova; Stéphane Follain; Mélodie David; Rossano Ciampalini; +3 Authors

    International audience; Soil erosion is the primary process driving land degradation. Using multiple scales of management to minimize soil erosion is crucial to achieve land degradation neutrality targets within the Sustainable Development Goals agenda. Land management (LM) influences both on-site and off-site erosion on the event-scale and over the long-term. However, each LM differs in effectiveness depending on the temporal scale considered. In order to understand how LM effects internal and external catchment dynamics, we apply LandSoil, a physically based landscape evolution model, to evaluate 7 LM scenarios over long- (30 years) and short-terms (event scale). LM scenarios included changes in land use and/or landscape structure. Under current LM, mean surface soil erosion was similar to 0.69 +/- 39.10(-3) m over 30 years. In contrast, a single extreme event (435 mm/24 h) in January resulted in similar to 0.62 +/- 3.10(-3) In loss and similar to 0.04 +/- 2.10(-3) m if it occurred in October. Heterogeneous patterns of erosion and deposition developed after 30 years, whereas extreme events dominantly showed soil loss and high catchment connectivity. Effectiveness of LM in erosion mitigation and sediment trapping differed according to temporal and spatial scales for each scenario. We concluded that multiple temporal and spatial scales must be incorporated in order to adaptively manage land degradation and meet neutrality targets.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Horizon / Pleins tex...arrow_drop_down
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    Other literature type . 2019
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    Journal of Environmental Management
    Article
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    Journal of Environmental Management
    Article . 2019 . Peer-reviewed
    License: Elsevier TDM
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Horizon / Pleins tex...arrow_drop_down
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      Horizon / Pleins textes
      Other literature type . 2019
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Journal of Environmental Management
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      image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
      Journal of Environmental Management
      Article . 2019 . Peer-reviewed
      License: Elsevier TDM
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: L. T. Ellis; C. Ah-Peng; G. Aslan; V. A. Bakalin; +78 Authors

    Pseudoamblystegium subtile (Hedw.) Vanderp. & Hedenäs. CONTRIBUTORS: R. Gabriel, M. Kubová, C. Sérgio and I. Soares Albergaria. PORTUGAL, AZORES: Terceira Island, Angra do Heroísmo, municipal garden ‘Jardim Duque da Terceira’, 38° 39′ 24.0′′N, 27°13′ 05.99′′W, 31 m a.s.l, on the base of a shrub, in acidic conditions, 7 April 2017, leg. Michaela Kubová s.n. (AZU). A new understanding of the pleurocarpous moss species Pseudoamblystegium subtile was proposed by Vanderpoorten and Hedenäs (2009). The new genus is separated from the other Amblystegiaceae primarily due to its phylogenetic consistency and is characterised by the possession of leaves with a very short nerve, and erect capsules (Vanderpoorten and Hedenäs 2009). (excerpt) info:eu-repo/semantics/publishedVersion

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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Álvaro Moreno; Francisco García-Haro; Beatriz Martínez; María Gilabert;

    Time series of remotely sensed data are an important source of information for understanding land cover dynamics. In particular, the fraction of absorbed photosynthetic active radiation (fAPAR) is a key variable in the assessment of vegetation primary production over time. However, the fAPAR series derived from polar orbit satellites are not continuous and consistent in space and time. Filtering methods are thus required to fill in gaps and produce high-quality time series. This study proposes an adapted (iteratively reweighted) local regression filter (LOESS) and performs a benchmarking intercomparison with four popular and generally applicable smoothing methods: Double Logistic (DLOG), smoothing spline (SSP), Interpolation for Data Reconstruction (IDR) and adaptive Savitzky-Golay (ASG). This paper evaluates the main advantages and drawbacks of the considered techniques. The results have shown that ASG and the adapted LOESS perform better in recovering fAPAR time series over multiple controlled noisy scenarios. Both methods can robustly reconstruct the fAPAR trajectories, reducing the noise up to 80% in the worst simulation scenario, which might be attributed to the quality control (QC) MODIS information incorporated into these filtering algorithms, their flexibility and adaptation to the upper envelope. The adapted LOESS is particularly resistant to outliers. This method clearly outperforms the other considered methods to deal with the high presence of gaps and noise in satellite data records. The low RMSE and biases obtained with the LOESS method (|rMBE| < 8%; rRMSE < 20%) reveals an optimal reconstruction even in most extreme situations with long seasonal gaps. An example of application of the LOESS method to fill in invalid values in real MODIS images presenting persistent cloud and snow coverage is also shown. The LOESS approach is recommended in most remote sensing applications, such as gap-filling, cloud-replacement, and observing temporal dynamics in situ where rapid seasonal changes are produced.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
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    Remote Sensing
    Other literature type . Article . 2014 . Peer-reviewed
    License: CC BY
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Remote Sensing
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    Remote Sensing
    Article . 2014
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Remote Sensingarrow_drop_down
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Remote Sensing
      Other literature type . Article . 2014 . Peer-reviewed
      License: CC BY
      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Remote Sensing
      Article
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
      Remote Sensing
      Article . 2014
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Jiménez-Muñoz, JC; Sobrino, JA; Plaza, A; Guanter, L; +2 Authors

    Abstract: In this paper we compare two different methodologies for Fractional Vegetation Cover (FVC) retrieval from Compact High Resolution Imaging Spectrometer (CHRIS) data onboard the European Space Agency (ESA) Project for On-Board Autonomy (PROBA) platform. The first methodology is based on empirical approaches using Vegetation Indices (VIs), in particular the Normalized Difference Vegetation Index (NDVI) and the Variable Atmospherically Resistant Index (VARI). The second methodology is based on the Spectral Mixture Analysis (SMA) technique, in which a Linear Spectral Unmixing model has been considered in order to retrieve the abundance of the different constituent materials within pixel elements, called Endmembers (EMs). These EMs were extracted from the image using three different methods: i) manual extraction using a land cover map, ii) Pixel Purity Index (PPI) and iii) Automated Morphological Endmember Extraction (AMEE). The different methodologies for FVC retrieval were applied to one PROBA/CHRIS image acquired over an agricultural area in Spain, and they were calibrated and tested against in situ measurements of FVC estimated with hemispherical photographs. The results obtained from VIs show that VARI correlates better with FVC than NDVI does, with standard errors of estimation of less than 8% in the case of VARI and less than 13% in the case of NDVI when calibrated using the in situ measurements. The results obtained from the SMA-LSU technique show Root Mean Square Errors (RMSE) below 12% when EMs are extracted from the AMEE method and around 9% when extracted from the PPI method. A RMSE value below 9% was obtained for manual extraction of EMs using a land cover use map.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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    Europe PubMed Central
    Article . 2009
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    Sensors
    Article . 2009
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Europe PubMed Centra...arrow_drop_down
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  • image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Authors: Tuzet, Andree, A.; Perrier, A.; Oulid-Aissa, A.K.;

    Abstract A hay drying model with a multi-layer representation has been developed. This model, based on a heat balance method, was designed to compute hay drying dynamics in the field. It was implemented for hay spread over a field or in windrows. The necessary inputs are: (1) meteorological data (temperature, humidity, wind speed, solar and atmospheric radiation); (2) biological characteristics of the plant; (3) hay physical parameters (depth, leaf area index). The output provides time-dependent cumulative water losses and changes in water content and temperature in the different layers. The model was tested against data measured under experimental conditions with different kinds of grass (ryegrass, permanent pasture and alfalfa). It was shown that agreement between the simulated and measured parameters was fairly good. Further, the model was used to study the sensitivity of water loss to changes in input variables and plant characteristics.

    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Agricultural and For...arrow_drop_down
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Agricultural and Forest Meteorology
    Article . 1993 . Peer-reviewed
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    Authors: Charlotte De Grave; Luca Pipia; Bastian Siegmann; Pablo Morcillo-Pallarés; +3 Authors

    ESA’s Eighth Earth Explorer mission “FLuorescence EXplorer” (FLEX) will be dedicated to the global monitoring of the chlorophyll fluorescence emitted by vegetation. In order to properly interpret the measured fluorescence signal, essential vegetation variables need to be retrieved concomitantly. FLEX will fly in tandem formation with Sentinel-3 (S3), which conveys the Ocean and Land Color Instrument (OLCI) that is designed to characterize the atmosphere and the terrestrial vegetation at a spatial resolution of 300 m. In support of FLEX’s preparatory activities, this paper presents a first validation exercise of OLCI vegetation products against in situ data coming from the 2018 FLEXSense campaign. During this campaign, leaf chlorophyll content (LCC) and leaf area index (LAI) measurements were collected over croplands, while HyPlant DUAL images of the area were acquired at a 3 m spatial resolution. A multiscale validation strategy was pursued. First, estimates of these two variables, together with the combined canopy chlorophyll content (CCC = LCC × LAI), were obtained at the HyPlant spatial resolution and were compared against the in situ measurements. Second, the fine-scale retrieval maps from HyPlant were coarsened to the S3 spatial scale as a reference to assess the quality of the OLCI vegetation products. As an intermediary step, vegetation products extracted from Sentinel-2 data were used to compare retrievals at the in-between spatial resolution of 20 m. For all spatial scales, CCC delivered the most accurate estimates with the smallest prediction error obtained at the 300 m resolution (R2 of 0.74 and RMSE = 26.8 μμg cm−2). Results of a scaling analysis suggest that CCC performs well at the different tested spatial resolutions since it presents a linear behavior across scales. LCC, on the other hand, was poorly retrieved at the 300 m scale, showing overestimated values over heterogeneous pixels. The introduction of a new LCC model integrating mixed reflectance spectra in its training enabled to improve by 16% the retrieval accuracy for this variable (RMSE = 10 μμg cm−2 for the new model versus RMSE = 11.9 μμg cm−2 for the former model).

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    Other literature type . Article . 2021 . Peer-reviewed
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    Article . 2022
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    Authors: Sutcliffe, Laura M. E.; Batáry, Péter; Kormann, Urs; Baldi, Andras; +39 Authors

    A large proportion of European biodiversity today depends on habitat provided by low‐intensity farming practices, yet this resource is declining as European agriculture intensifies. Within the European Union, particularly the central and eastern new member states have retained relatively large areas of species‐rich farmland, but despite increased investment in nature conservation here in recent years, farmland biodiversity trends appear to be worsening. Although the high biodiversity value of Central and Eastern European farmland has long been reported, the amount of research in the international literature focused on farmland biodiversity in this region remains comparatively tiny, and measures within the EU Common Agricultural Policy are relatively poorly adapted to support it. In this opinion study, we argue that, 10 years after the accession of the first eastern EU new member states, the continued under‐representation of the low‐intensity farmland in Central and Eastern Europe in the international literature and EU policy is impeding the development of sound, evidence‐based conservation interventions. The biodiversity benefits for Europe of existing low‐intensity farmland, particularly in the central and eastern states, should be harnessed before they are lost. Instead of waiting for species‐rich farmland to further decline, targeted research and monitoring to create locally appropriate conservation strategies for these habitats is needed now. Volkswagen Foundation

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    NARCIS; Research@WUR
    Other literature type . Article . 2015
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    https://onlinelibrary.wiley.co...
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    https://doi.org/10.7892/boris....
    Other literature type . 2015
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    Authors: Chiara Corbari; José A. Sobrino; Marco Mancini; V. Hidalgo;

    Land surface temperature is the link between soil-vegetation-atmosphere fluxes and soil water content through the energy water balance. This paper analyses the representativeness of land surface temperature (LST) for a distributed hydrological water balance model (FEST-EWB) using LST from AHS (airborne hyperspectral scanner), with a spatial resolution between 2–4 m, LST from MODIS, with a spatial resolution of 1000 m, and thermal infrared radiometric ground measurements that are compared with the representative equilibrium temperature that closes the energy balance equation in the distributed hydrological model. <br><br> Diurnal and nocturnal images are analyzed due to the non stable behaviour of the thermodynamic temperature and to the non linear effects induced by spatial heterogeneity. <br><br> Spatial autocorrelation and scale of fluctuation of land surface temperature from FEST-EWB and AHS are analysed at different aggregation areas to better understand the scale of representativeness of land surface temperature in a hydrological process. <br><br> The study site is the agricultural area of Barrax (Spain) that is a heterogeneous area with a patchwork of irrigated and non irrigated vegetated fields and bare soil. The used data set was collected during a field campaign from 10 to 15 July 2005 in the framework of the SEN2FLEX project.

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    https://doi.org/10.5194/hessd-...
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    Hydrology and Earth System Sciences (HESS)
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      https://doi.org/10.5194/hessd-...
      Preprint . 2010
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      Hydrology and Earth System Sciences (HESS)
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    Authors: Sabrina Gaba; Rémi Perronne; Guillaume Fried; Antoine Gardarin; +12 Authors

    SummaryIntegrating principles of ecological intensification into weed management strategies requires an understanding of the many relationships among weeds, crops and other organisms of agro‐ecosystems in a changing context. Extensively used during the last two decades in weed science, trait‐based approaches have provided general insights into weed community response to agricultural practices, and recently to understanding the effect of weeds on agro‐ecosystem functioning. In this review, we provide a holistic synthesis of the current knowledge on weed response and effect functional traits. Based on the literature and recent advances in weed science, we review current knowledge on (i) weed functional groups and ecological strategies, (ii) weed functional response traits to cropping systems and (iii) weed functional effect traits affecting agro‐ecosystem functioning. For each functional trait, we explicitly present the assumptions and evidence on the linkage between trait values and ecological functions, in response to either management practices, for example tillage, sowing and herbicides, or biotic interactions, for example crop–weed competition and pollination. Finally, we address and discuss major research avenues that may significantly improve the use of traits and the knowledge of functional diversity in weed science for the future, especially to design and implement more environmentally sustainable weed management strategies.

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    Weed Research
    Article . 2017 . Peer-reviewed
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    Authors: Philippon, Nathalie; Mougin, E.; Jarlan, Lionel; Frison, Pierre-Louis;

    International audience; The European Remote Sensing Wind Scatterometer (ERS-WSC) backscattering coefficient, NOAA Advanced Very High Resolution Radiometer (NOAA-AVHRR) Normalized Difference Vegetation Index (NDVI), and Climate Prediction Center Merged Analysis Precipitation ( CMAP) precipitation data sets are studied over the period August 1991 to December 2000 to document ( 1) the interannual and intra-annual evolutions of vegetation photosynthetic activity and soil-vegetation water content over West Africa and ( 2) their two-way links with precipitation. Over the Sahel, at interannual timescales the strongest relationships between vegetation, soil moisture, and precipitation are observed from July to October and when 1-month lag is considered between the parameters. This delay reflects the vegetation response time to the moisture pulses that follow precipitation events. The high correlation between NDVI and sigma_0 at interannual timescales confirms the importance of vegetation in the backscattering coefficient. However, sigma_0 shows stronger statistical links with precipitation, suggesting that this product contains additional useful information related in particular to upper soil moisture. Over Guinea, large differences are observed between the two remote sensing products, and their relationship with precipitation at interannual timescales is weaker. Sigma_ 0 is significantly linked to precipitation from July to November, whereas NDVI does not show any significant relationship with precipitation. NDVI and sigma_0 serial correlations over the Sahel and Guinea suggest that a 2-month memory usually characterizes vegetation photosynthetic activity and soil-vegetation water content anomalies. However, anomalies disappearance in winter then reappearance in the following spring also suggests an interseason memory held by deep soil moisture reservoirs and deep-rooted plants. A composite analysis reveals that the wettest Sahelian rainy seasons were preceded by positive anomalies of soil-vegetation water content over Guinea from winter to spring. Cross correlations and Granger causality analyses partly relate these winter to spring land surface anomalies to those recorded in precipitation during the previous autumn. Spring soil-vegetation water content anomalies strengthen the meridional gradient of soil-vegetation water content over the subcontinent. This gradient is thought to contribute to the gradient of entropy that drives the West African monsoon.

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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Oskar Bordeaux
    Article . 2005
    Data sources: Oskar Bordeaux
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Journal of Geophysical Research Atmospheres
    Article . 2005 . Peer-reviewed
    License: Wiley Online Library User Agreement
    Data sources: Crossref
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Anna Smetanova; Stéphane Follain; Mélodie David; Rossano Ciampalini; +3 Authors

    International audience; Soil erosion is the primary process driving land degradation. Using multiple scales of management to minimize soil erosion is crucial to achieve land degradation neutrality targets within the Sustainable Development Goals agenda. Land management (LM) influences both on-site and off-site erosion on the event-scale and over the long-term. However, each LM differs in effectiveness depending on the temporal scale considered. In order to understand how LM effects internal and external catchment dynamics, we apply LandSoil, a physically based landscape evolution model, to evaluate 7 LM scenarios over long- (30 years) and short-terms (event scale). LM scenarios included changes in land use and/or landscape structure. Under current LM, mean surface soil erosion was similar to 0.69 +/- 39.10(-3) m over 30 years. In contrast, a single extreme event (435 mm/24 h) in January resulted in similar to 0.62 +/- 3.10(-3) In loss and similar to 0.04 +/- 2.10(-3) m if it occurred in October. Heterogeneous patterns of erosion and deposition developed after 30 years, whereas extreme events dominantly showed soil loss and high catchment connectivity. Effectiveness of LM in erosion mitigation and sediment trapping differed according to temporal and spatial scales for each scenario. We concluded that multiple temporal and spatial scales must be incorporated in order to adaptively manage land degradation and meet neutrality targets.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Horizon / Pleins tex...arrow_drop_down
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Horizon / Pleins textes
    Other literature type . 2019
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Journal of Environmental Management
    Article
    License: CC BY NC
    Data sources: UnpayWall
    image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
    Journal of Environmental Management
    Article . 2019 . Peer-reviewed
    License: Elsevier TDM
    Data sources: Crossref
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