A methodological framework to assess the multiple contributions of soils to ecosystem services delivery at regional scale

Calzolari, Costanza; Ungaro, Fabrizio; Filippi, Nicola; Guermandi, Marina; Malucelli, Francesco; Marchi, Nazaria; Staffilani, Francesca; Tarocco, P.

doi:10.1016/j.geoderma.2015.07.013

Cited by 96 publications

(63 citation statements)

References 53 publications

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“…They also provide information on land use pattern, at least at the time surveying took place. It would seem natural to think that this spatial information could serve as a foundation from which, in what is generally referred to as "bottom up" or "upscaling" approach, one could estimate soil functions or services over any surface area, small or large, and indeed that route has been explored by a number of researchers in the last few years (Lehmann et al, 2008;Lehmann and Stahr, 2010;Ungaro et al, 2014a;Calzolari et al, 2016).…”

Section: Using Soil Maps and Pedotransfer Functionsmentioning

confidence: 99%

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Baveye

Gowdy

2016

Front. Environ. Sci.

314

168

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Section: Using Soil Maps and Pedotransfer Functionsmentioning

confidence: 99%

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Baveye

Gowdy

2016

Front. Environ. Sci.

314

168

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“…Ecosystem services are determined by soil properties and their assessment requires the use of selected indicators (Calzolari et al, 2016). A wide range of soil indicators may be used, depending on the purpose and scale of evaluation.…”

Section: Soil Indicatorsmentioning

confidence: 99%

Soil indicators to assess the effectiveness of restoration strategies in dryland ecosystems

Costantini¹,

et al. 2016

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Abstract. Soil indicators may be used for assessing both land suitability for restoration and the effectiveness of restoration strategies in restoring ecosystem functioning and services. In this review paper, several soil indicators, which can be used to assess the effectiveness of ecological restoration strategies in dryland ecosystems at different spatial and temporal scales, are discussed. The selected indicators represent the different viewpoints of pedology, ecology, hydrology, and land management. Two overall outcomes stem from the review. (i) The success of restoration projects relies on a proper understanding of their ecology, namely the relationships between soil, plants, hydrology, climate, and land management at different scales, which are particularly complex due to the heterogeneous pattern of ecosystems functioning in drylands.(ii) The selection of the most suitable soil indicators follows a clear identification of the different and sometimes competing ecosystem services that the project is aimed at restoring.

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“…regulation of water, nutrient and carbon cycles, filtering of compounds, production of food and biomass or providing habitats for plants and soil fauna (Haygarth and Ritz, 2009;Robinson et al, 2013). The assessment of the multi-functionality of soils depends on the availability of datasets on chemical, physical and biological soil properties (Calzolari et al, 2016). Greiner et al (2017) compiled a set of approved assessment methods for soil functions from the applied soil science community that cover the multi-functionality of soils (Table 1).…”

Section: Introductionmentioning

confidence: 99%

Evaluation of digital soil mapping approaches with large sets of environmental covariates

Nussbaum¹,

Spiess²,

Baltensweiler³

et al. 2018

SOIL

214

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Abstract. The spatial assessment of soil functions requires maps of basic soil properties. Unfortunately, these are either missing for many regions or are not available at the desired spatial resolution or down to the required soil depth. The field-based generation of large soil datasets and conventional soil maps remains costly. Meanwhile, legacy soil data and comprehensive sets of spatial environmental data are available for many regions.Digital soil mapping (DSM) approaches relating soil data (responses) to environmental data (covariates) face the challenge of building statistical models from large sets of covariates originating, for example, from airborne imaging spectroscopy or multi-scale terrain analysis. We evaluated six approaches for DSM in three study regions in Switzerland (Berne, Greifensee, ZH forest) by mapping the effective soil depth available to plants (SD), pH, soil organic matter (SOM), effective cation exchange capacity (ECEC), clay, silt, gravel content and fine fraction bulk density for four soil depths (totalling 48 responses). Models were built from 300-500 environmental covariates by selecting linear models through (1) grouped lasso and (2) an ad hoc stepwise procedure for robust external-drift kriging (georob). For (3) geoadditive models we selected penalized smoothing spline terms by component-wise gradient boosting (geoGAM). We further used two tree-based methods: (4) boosted regression trees (BRTs) and (5) random forest (RF). Lastly, we computed (6) weighted model averages (MAs) from the predictions obtained from methods 1-5.Lasso, georob and geoGAM successfully selected strongly reduced sets of covariates (subsets of 3-6 % of all covariates). Differences in predictive performance, tested on independent validation data, were mostly small and did not reveal a single best method for 48 responses. Nevertheless, RF was often the best among methods 1-5 (28 of 48 responses), but was outcompeted by MA for 14 of these 28 responses. RF tended to over-fit the data. The performance of BRT was slightly worse than RF. GeoGAM performed poorly on some responses and was the best only for 7 of 48 responses. The prediction accuracy of lasso was intermediate. All models generally had small bias. Only the computationally very efficient lasso had slightly larger bias because it tended to under-fit the data. Summarizing, although differences were small, the frequencies of the best and worst performance clearly favoured RF if a single method is applied and MA if multiple prediction models can be developed.Published by Copernicus Publications on behalf of the European Geosciences Union.

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A methodological framework to assess the multiple contributions of soils to ecosystem services delivery at regional scale

Cited by 96 publications

References 53 publications

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Soil “Ecosystem” Services and Natural Capital: Critical Appraisal of Research on Uncertain Ground

Soil indicators to assess the effectiveness of restoration strategies in dryland ecosystems

Evaluation of digital soil mapping approaches with large sets of environmental covariates

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