6533b7d3fe1ef96bd12601cd
RESEARCH PRODUCT
Indicators of agricultural intensity and intensification: a review of the literature
Elisa MarracciniIrune Ruiz-martinezMarta DeboliniEnrico Bonarisubject
[SDV.SA]Life Sciences [q-bio]/Agricultural sciences010504 meteorology & atmospheric sciencesagriculture intensiveAgronomia[SDV.SA.AGRO]Life Sciences [q-bio]/Agricultural sciences/Agronomy01 natural sciencesEcosystem servicesmedia_common2. Zero hungerFood securityIntensive farmingAgriculturaEnvironmental resource managementspatial scales[SHS.GEO]Humanities and Social Sciences/Geography04 agricultural and veterinary sciencesAgroécologiesustainabilityAgricultural sciencesindicateur de rechercheéchelle spatialeGeographyLand use intensity;ecosystem services;farming systems;indicators;spatial scales;sustainabilitymedia_common.quotation_subjectlcsh:Plant cultureEconomiaécosystèmelcsh:AgricultureLand use intensitysustainability.[SDV.EE.ECO]Life Sciences [q-bio]/Ecology environment/Ecosystemssystème agricolelcsh:SB1-1110farming systemsAgricultural productivity0105 earth and related environmental sciencesétat de l'artbusiness.industrylcsh:S[SDV.SA.AEP]Life Sciences [q-bio]/Agricultural sciences/Agriculture economy and politics15. Life on land[SDE.ES]Environmental Sciences/Environmental and SocietyindicatorsAgricultureSustainability040103 agronomy & agriculturedéveloppement agricole durable0401 agriculture forestry and fisherieslittératureMonocultureecosystem servicesbusinessAgronomy and Crop ScienceSciences agricolesDiversity (politics)description
Since the 1960s, research has dealt with agricultural intensification (AI) as a solution to ensure global food security. Recently, sustainable intensification (SI) has increasingly been used to describe those agricultural and farming systems that ensure adequate ecosystem service provision. Studies differ in terms of the application scales and methodologies, thus we aim to summarize the main findings from the literature on how AI and SI are assessed, from the farm to global levels. Our literature review is based on 7865 papers selected from the Web of Science database and analysed using CorText software. A further selection of 105 relevant papers was used for an in-depth full-text analysis on: i) farming systems studied; ii) related ecosystem services; iii) indicators of intensity; and iv) temporal and spatial scales of analysis. Through this two-step analysis we were able to highlight three main research gaps in the AI research indicators. Firstly, the farming systems analysed for assessing AI are often quite simplified or monoculture- oriented, and they do not take the diversity and complex organisation of farming systems into account. Secondly, these studies mainly focus on northern countries or developing countries, whereas there is a gap of knowledge in Mediterranean areas, which are the areas with a high complexity of farming systems and diversity in ecosystem services. Finally, AI is mostly assessed through nitrogen inputs and economic yield, which are used the most both at very local and global levels. Intermediate regional or local levels, which are relevant for policy implementation and local planning, are often neglected.
year | journal | country | edition | language |
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2015-06-09 | Italian Journal of Agronomy |