Liu Q., Sun X., Wu W., Liu Z., Fang G., Yang P. (2022). Agroecosystem services: a review of concepts, indicators, assessment methods and future research perspectives. Ecological Indicators, 01/09/2022, vol. 142, p. 1-12.
https://doi.org/10.1016/j.ecolind.2022.109218
https://doi.org/10.1016/j.ecolind.2022.109218
Titre : | Agroecosystem services: a review of concepts, indicators, assessment methods and future research perspectives (2022) |
Auteurs : | Q. Liu ; X. Sun ; W. Wu ; Z. Liu ; G. Fang ; P. Yang |
Type de document : | Article |
Dans : | Ecological Indicators (vol. 142, September 2022) |
Article en page(s) : | p. 1-12 |
Langues : | Anglais |
Langues du résumé : | Anglais |
Catégories : |
Catégories principales 07 - ENVIRONNEMENT ; 7.1 - Généralités. Situation EnvironnementaleThésaurus IAMM AGROECOSYSTEME ; SERVICE ECOSYSTEMIQUE ; INDICATEUR ; AGRICULTURE ; DURABILITE |
Résumé : | Agroecosystems benefit from many ecosystem services and are frequently managed to increase productivity. In recent years, agricultural industrialization has caused the loss of some important ecosystem services in agroecosystems, hindering some sustainable development goals (SDGs). In order to promote sustainable agricultural development, it is necessary to restore the damaged agroecosystems and improve agroecosystem services (AES). However, there are relatively few studies on AES, and fewer studies concerning the definition or connotation of AES. Therefore, this paper reviews current AES research, indicators, and assessment methods, as well as directions for future research. AES are determined by agroecosystem functions and human agricultural practices, with both positive and negative effects, scale effects, and trade-offs and synergies between AES. AES indicators can be classified as provisioning services, regulating services, and cultural services, with a few studies including supporting services. Currently, the main AES assessment methods include public participation, empirical model, mechanism model, and value estimation. Multi-source data fusion for integrated models to assess multiple AES will be the future research trend. In addition, AES research should develop additional promising topics, including considering both AES and agroecosystem disservices (AEDS); assessing AES supply, demand, and flow; and analyzing AES trade-offs and synergies comprehensively. This will extend the research field to the links between AES and SDGs and their applications in agricultural landscape planning and governance. This review highlights the importance of AES research to more effectively manage agroecosystems and promote sustainable agricultural development. |
Cote : | En ligne |
URL / DOI : | https://doi.org/10.1016/j.ecolind.2022.109218 |