Combination of observational and functional trait-based approaches in developing a polyculture design tool

ABSTRACT

Models of species composition in diversified cropping systems utilize mostly functional trait-based or observation-based approaches. We argue that a combination of these two approaches makes polyculture design tools more robust. We assessed quantity, quality, and complementarity of information from multiple sources for designing diversified cropping systems with vegetables and spice crops for cold temperate climate. Trait and observational data were integrated from: (i) two grower-oriented and one academic crop database, (ii) a survey of farmers practicing community-supported agriculture, and (iii) a systematic literature review on the use of spice crops in vegetable farming. Survey results reveal that the farmers were capable of achieving medium to good levels of their main goals, but failed to reach desired multifunctionality with their polycultures, which can be potentially improved with computational tools. None of the analyzed data sources provided a comprehensive dataset for all target crops and functional traits. However, source combination allowed for design from known crop companions (farmers survey and grower-oriented databases), to addressing specific pest problems (literature review), and increasing functional complementarity and facilitation by trait matching (academic and grower-oriented trait databases). Integrating information from different sources increased the number of crop combination options but also planning and management complexity.

GRAPHIC ABSTRACT

Combination of functional trait-based and observation-based approaches within a polyculture design tool.

KEYWORDS:

• Sustainable agriculture
• intercropping
• modeling
• vegetables
• spice and aromatic plants

Acknowledgments

We are extremely grateful to SOLAWI farmers for participation in the research survey and to network coordinator Katharina Kraiß for facilitating our contract with farmers. We would also like to express our sincere gratitude to contributors and administrators of crop databases Natural Capital Plant Database, Plants for a Future, and TRY database of plant traits for collecting, organizing, and making data accessible to the public. We thank the journal Editor and anonymous reviewers for their help.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Code availability

The codes generated during the current study are available from the corresponding author on reasonable request.

Consent to participate

Survey and interview respondents provided consent to participate in this study and to publish their anonymized data in scientific papers.

Consent for publication

Survey and interview respondents provided consent to publish their anonymized data collected during this study in scientific papers.

Data availability statement

The datasets generated during and/or analyzed during the current study are incorporated into Google Drive version of the polyculture design tool accessible at https://docs.google.com/spreadsheets/d/1JzS68FWbju8po9K-e-V5-6UsUjE3YXYdynLdrWyoMFs/edit?usp=sharing. Dataset generated after the systematic literature review is additionally deposited into the Bonares Repository (Ardanov et al. 2023).

Ethics approval

Template of a consent form developed by the Leibniz Centre for Agricultural Landscape Research (ZALF) e. V for research with human participants was utilized and adapted for study purposes.

Supplementary material

Supplemental data for this article can be accessed online at https://doi.org/10.1080/21683565.2023.2238438

Additional information

Funding

This work was supported by the Michael Succow foundation through Eva Kleinn fellowship, Consejo Nacional de Investigaciones Científicas y Técnicas, Argentina, Matching Fund Leibniz, and Ministry of Science, Research and Culture of the State of Brandenburg (Ukraine help) – personal fellowships to P.A.