Trade-offs among ecosystem services advance the case for improved spatial targeting of agri-environmental measures

Longo, Matteo; Ferro, Nicola Dal; Lazzaro, Barbara; Morari, Francesco

doi:10.1016/j.jenvman.2021.112131

Cited by 14 publications

(9 citation statements)

References 44 publications

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“…Due to their confined environment and the measuring instrumentation they may be equipped with, lysimeters are often considered excellent tools for studying water flow and chemical transport, and their data are often used to calibrate and test numerical models. Biogeochemical models capable of representing shallow water table conditions are necessary to describe the complex crop–soil interactions in the vadose zone of the Veneto low plain (Dal Ferro et al., 2016; Longo et al., 2021). Considering our literature review, our hypothesis is that the usage of the numerical solution of Richards equation is a prerequisite for adequate simulations of shallow water table conditions with EPIC, despite the higher requirements in terms of input data.…”

Section: Introductionmentioning

confidence: 99%

Testing the EPIC Richards submodel for simulating soil water dynamics under different bottom boundary conditions

Longo¹,

Jones

Izaurralde

et al. 2021

Vadose Zone Journal

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Most biogeochemical models simulate water dynamics using the tipping bucket approach, which has been often found to be too simplistic to represent vadose zone dynamics adequately under shallow groundwater conditions. Recently, a solution to the Richards equation using the Mualem-van Genuchten model (Rich-vGM) has been added into the EPIC (Environmental Policy Integrated Climate) model to address this shortfall. Its performance was tested using lysimeters operating under free drainage (FD) and at a shallow water table and 120-cm depth [WT120]). Model accuracy was also compared with the upgraded tipping bucketbased method implemented into EPIC (the variable saturation hydraulic conductivity method [VSHC]). Soil water content (SWC) data were split into calibration and validation subsets. Model evaluation also included annual evapotranspiration (ET), percolation (PRK), and upward water movements to assess underlying soil water balance factors. The submodels provided accurate and similar results upon comparison with SWC measures under FD (Nash-Sutcliffe coefficient [NSE] = 0.26 and 0.61 using VSHC and Rich-vGM, respectively). The Rich-vGM model accurately reproduced observed SWC and ET (e.g., NSE = 0.70 and percentage bias [PBIAS] = −3.7% for WT120, respectively) although it slightly overestimated PRK (PBIAS = 47.8%, on average). Instead, VSHC proved unable to correctly simulate shallow groundwater conditions (e.g., NSE = −1.85 for WT60 SWC). Under shallow groundwater conditions, the Rich-vGM method is recommended, despite the additional data required and the need to define the bottom boundary conditions according to water table fluctuations. In conclusion, the Richards solver introduced and tested in EPIC improved the model's ability to represent complex biophysical and biogeochemical processes in terrestrial ecosystems associated with the hydrological balance.

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Section: Introductionmentioning

confidence: 99%

Testing the EPIC Richards submodel for simulating soil water dynamics under different bottom boundary conditions

Longo¹,

Jones

Izaurralde

et al. 2021

Vadose Zone Journal

Self Cite

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“…These effects can be highly variable in space and time. Recognition of this variability has driven calls for indicator-based approaches to targeting assessment and the selection of priority criteria [2,19,94]. In the case of the PIASRE program, similar indicator-based approaches to assessment could be used to provide the framework for a more empirically grounded value ordering of criteria.…”

Section: Targeting Gaps In Agri-environmental Policy Implementationmentioning

confidence: 99%

“…Research into this policy diversification has focused on the Common Agricultural Policy of the European Union, where the term agri-environmental has come to describe a wide variety of policies, schemes, programs, and measures. Generally, findings show that better targeting of agri-environmental support leads to more effective and cost-efficient policy [2,3], so long as transaction costs are low [4] or are offset by enhanced provision of services [5]. Studies of targeting effectiveness tend to examine single support measures [6] and provide insights into specific policy actions and outcomes (i.e., levels of farmer participation, promotion of green farming practices, provision of ecosystem services, rural development, and equity) [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 97%

Spatial Targeting of Agricultural Support Measures: Indicator-Based Assessment of Coverages and Leakages

LaFevor

Ponette‐González

Larson

et al. 2021

Land

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Agricultural support programs distribute payments to farms based on a diverse set of policy objectives. Adequate targeting of this support to priority areas is key to efficient and effective policy. We evaluated the targeting strategy of a national-level program in Mexico that distributed support based on seven criteria that prioritized poor smallholder farming communities at high risk of cropland failure. We used a series of logistic models to assess the coverage and leakage rates of the program’s targeting strategy and found rates of about 80 and 20 percent, respectively. We also found significant differences between the targeting priorities specified in program rules and the observed distribution of support measures. In general, the program favored arid and semi-arid regions at high risk of soil erosion but neglected smallholder farms in high-poverty regions with elevated rates of cropland failure. Our findings highlight the continued lack of financial support for smallholder agriculture in Mexico, despite program rules and priority statements that stress the vulnerability of this sector. This study also illustrates the important role of spatial targeting in better aligning agricultural support payments with stated policy priorities. This alignment is often overlooked in ex-post assessment, but it is critical for improving targeting precision, equity, and overall policy effectiveness.

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“…Bassanino et al [6] proved how these indicators might allow a quick assessment of the agronomic management techniques sustainability in the Po valley. In the same area, Longo et al [7], coupling DayCent simulation and the GIS platform, showed how the site-specific indices application might be a suitable tool for agri-environmental measures evaluation. The Eurostat database shows that across the EU, the output-to-input ratio of nutrients is often below 1, suggesting that more effort Agronomy 2021, 11, 1472 2 of 13 should be put towards increasing the nutrient use efficiency of cropping systems.…”

Section: Introductionmentioning

confidence: 99%

“…Quemada et al [14] applied this approach on the evaluation of 1240 farms NUE and concluded that it is an effective tool to assess farming systems performances. To test the sustainability of cropping systems, short-term cropping experiments are often undertaken; however, their results may be impaired by their short-term nature [7,15]. Indeed, the effects of previous practices, such as the carryover effect from previous fertilisations, may influence short-term observations.…”

Section: Introductionmentioning

confidence: 99%

Can Long-Term Experiments Predict Real Field N and P Balance and System Sustainability? Results from Maize, Winter Wheat, and Soybean Trials Using Mineral and Organic Fertilisers

et al. 2021

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Agri-environmental indicators such as nutrient balance may play a key role in soil and water quality monitoring, although short-term experiments might be unable to capture the sustainability of cropping systems. Therefore, the objectives of this study are: (i) to evaluate the reliability of long-term experimental N and P balance estimates to predict real field (RF) (i.e., short-term transitory) conditions; and (ii) to compare the sustainability of short- and long-term experiments. The LTE-based predictions showed that crops are generally over-fertilised in RF conditions, particularly maize. Nutrient balance predictions based on the LTE data tended to be more optimistic than those observed under RF conditions, which are often characterised by lower outputs; in particular, 13, 44, and 47% lower yields were observed for winter wheat, maize, and soybean, respectively, under organic management. The graphical evaluation of N and P use efficiency demonstrated the benefit of adopting crop rotation practices and the risk of nutrient loss when liquid organic fertiliser was applied on a long-term basis. In conclusion, LTE predictions may depend upon specific RF conditions, representing potential N and P use efficiencies that, in RF, may be reduced by crop yield-limiting factors and the specific implemented crop sequence.

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Trade-offs among ecosystem services advance the case for improved spatial targeting of agri-environmental measures

Cited by 14 publications

References 44 publications

Testing the EPIC Richards submodel for simulating soil water dynamics under different bottom boundary conditions

Testing the EPIC Richards submodel for simulating soil water dynamics under different bottom boundary conditions

Spatial Targeting of Agricultural Support Measures: Indicator-Based Assessment of Coverages and Leakages

Can Long-Term Experiments Predict Real Field N and P Balance and System Sustainability? Results from Maize, Winter Wheat, and Soybean Trials Using Mineral and Organic Fertilisers

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