Special Issue on Synthesizing evidence on plant diversification in cropping systems
摘要截稿:
全文截稿: 2019-02-01
影响因子: 3.726
期刊难度:
CCF分类: 无
中科院JCR分区:
• 大类 : 农林科学 - 1区
• 小类 : 农艺学 - 2区
Overview
Diversification of plants in cropping systems is one of the pillars of agro-ecology. The amount of primary research (trials, surveys, simulation studies) on plant diversification is rapidly increasing. A large number of individual studies were conducted during the last two decades, especially on intercropping, cultivar mixing, agroforestry, and on crop rotations. However, the accumulating results are often variable, contradictory, or uncertain, making any attempt of generalization difficult.
A key purpose of research synthesis is to collate, synthesize, and report the available evidence on a given topic using transparent and replicable methods. Standard methods such as systematic review, evidence mapping, and meta-analyses are now available for the integration of results. Many new applications of these approaches are emerging in the agro-ecological science community.
The objective of this special issue is to shift the focus from individual studies to the accumulating body of evidence concerning the agronomic, economic, and environmental benefits of plant diversification. The scope of this issue covers all forms of diversification, from the mixing of cultivars or species at the field scale to the diversification of land use at large scale. Both qualitative (systematic reviews, evidence maps) and quantitative syntheses (meta-analyses, ensemble modelling) will be considered for publication. Authors are encouraged to use formal and rigorous protocols designed to reduce bias in the collection, synthesis, and reporting of results.
The topics of interest include, but are not limited to:
- Meta-analysis of published data on plant diversification
- Statistical analysis of experimental networks assessing cropping systems
- Quantitative analysis of farm surveys studying benefits of plant diversification
- Syntheses of simulated data produced by crop and ecological models
- Analysis of large datasets on intercropping, cultivar mixing, or agroforestry