Dataset Information

A multi-criteria evaluation system for arable land resource assessment.

ABSTRACT: This study proposed a multi-criteria evaluation system for arable land resources by combining the soil integrated fertility index (IFI) with a soil cleanliness index (based on heavy metals and metalloid content). A total of 16 typical arable land units in Chongming District, China, were evaluated using the proposed evaluation system based on 104 collected soil samples in 16 towns. The comprehensive soil evaluation scores of arable lands in 16 towns were in the range of 90.7 to 99.2 with a mean of 96.2, indicating that the arable land in all 16 towns was at the level of excellent (??90.0). Lower cleanliness indices had a significant impact on the final evaluation score. In comparison with single-index evaluation systems (i.e., the IFI or soil cleanliness index), the proposed multi-criteria system better reflects the quality of the soil. In the practice of arable land requisition and subsidy policy, the proposed multi-criteria evaluation system not only encourages farmers to preserve arable lands during farming but also helps agricultural authorities make effective and reliable management decisions.

SUBMITTER: Li F

PROVIDER: S-EPMC6940353 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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A multi-criteria evaluation system for arable land resource assessment.

Li Feipeng F Liu Wei W Lu Zhibo Z Mao Lingchen L Xiao Yihua Y

Environmental monitoring and assessment 20200102 2

This study proposed a multi-criteria evaluation system for arable land resources by combining the soil integrated fertility index (IFI) with a soil cleanliness index (based on heavy metals and metalloid content). A total of 16 typical arable land units in Chongming District, China, were evaluated using the proposed evaluation system based on 104 collected soil samples in 16 towns. The comprehensive soil evaluation scores of arable lands in 16 towns were in the range of 90.7 to 99.2 with a mean o ...[more]

PMID: 31897735

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Project description:In densely populated areas, surface waters are affected by many sources of pollution. Besides classical pollutants like nutrients and organic matter that lead to eutrophication, micropollutants from various point- and non-point sources are getting more attention by water quality managers. For cost-effective management an integrated assessment is needed that takes into account all relevant pollutants and all sources of pollution within a catchment. Due to the difficulty of identifying and quantifying sources of pollution and the need for considering long-term changes in boundary conditions, typically substantial uncertainty exists about the consequences of potential management alternatives to improve surface water quality. We therefore need integrated assessment methods that are able to deal with multiple objectives and account for various sources of uncertainty. This paper aims to contribute to integrated, prospective water management by combining a) multi-criteria decision support methods to structure the decision process and quantify preferences, b) integrated water quality modelling to predict consequences of management alternatives accounting for uncertainty, and c) scenario planning to consider uncertainty from potential future climate and socio-economic developments, to evaluate the future cost-effectiveness of water quality management alternatives at the catchment scale. It aims to demonstrate the usefulness of multi-attribute value functions for water quality assessment to i) propagate uncertainties throughout the entire assessment procedure, ii) facilitate the aggregation of multiple objectives while avoiding discretization errors when using categories for sub-objectives, iii) transparently communicate the results. We show how to use such multi-attribute value functions for model-based decision support in water quality management. We showcase the procedure for the Mönchaltorfer Aa catchment on the Swiss Plateau. We evaluate ten different water quality management alternatives, including current practice, that tackle macro- and micropollutants from a wide spectrum of agricultural and urban sources. We evaluate costs and water quality effects of the alternatives under four different socio-economic scenarios for the horizon 2050 under present and future climate projections and visualize their uncertainty. While the performance of alternatives is catchment specific, the methods can be transferred to other places and other management situations. Results confirm the need for cross-sectoral coordination of different management actions and interdisciplinary collaboration to support the development of prospective strategies to improve water quality.

Project description:Declines in European farmland birds over past decades have been attributed to the combined effects of agricultural intensification and abandonment. Consequently, aspirations to stop declines should focus attention on reversing these changes through voluntary or policy-driven interventions. The design of such interventions should ideally be informed by scientific knowledge of which aspects of the transformation of agricultural landscapes have contributed to the farmland bird declines. Declines may be associated with loss of natural habitats or the intensification and homogenization of land use management on production land, and furthermore, these changes may interact. Here, we applied an orthogonal design exploiting spatial variation in land use in a major agricultural region of Sweden to seek evidence for benefits to farmland birds of reversing some of the intensifications on and among arable fields and whether effects are modified by the availability of seminatural habitats (pastures and field borders) in the landscape. We accounted for the potentially confounding effect of interactions between species by using a joint species distribution model explicitly controlling for additional variation and covariation among species. We found that interventions aimed specifically at land in production could provide benefits to farmland birds. Landscapes with a higher proportion leys or fallows and/or with a more diverse set of crops held higher abundances of most farmland birds. However, effects were only apparent in landscapes with low availability of seminatural habitats and were sometimes even negative in landscapes with high amounts of such habitats, demonstrating context dependence. Even if we found little evidence of interactions between species, the joint modeling approach provided several benefits. It allowed information to be shared between species making analyses robust to uncertainty due to low abundances and provided direct information about the mean and variability in effects of studied predictors among species. We also found that care needs to be taken regarding prior and distributional assumptions as the importance of species interactions might otherwise be overstated. We conclude that this approach is well suited for evaluating agricultural policies by providing evidence for or against certain interventions or to be linked to policy scenarios of land use change.

Dataset Information

A multi-criteria evaluation system for arable land resource assessment.

Publications

A multi-criteria evaluation system for arable land resource assessment.

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