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Agrobiodiversity characteristics for multiple benefits in restored agricultural systems

Washing clothes by the river. The Ethiopian agricultural landscape is dappled with African acacia trees (Vachellia abyssinica). Credit: Bioversity International/C. Zanzanaini
Washing clothes by the river. The Ethiopian agricultural landscape is dappled with African acacia trees (Vachellia abyssinica). Credit: Bioversity International/C. Zanzanaini

In the latest blog for the COP13 blog series, Natalia Estrada-Carmona and colleagues describe the behind-the-scenes work on a new tool that will 'triangulate' available plant traits linked to ecosystem processes to guide restoration efforts while facilitating to practitioners’ and other relevant stakeholders' selection of locally-adapted species for restoring ecosystem services.

In the latest blog for the COP13 blog series, Natalia Estrada-Carmona and colleagues describe the behind-the-scenes work on a new tool that will 'triangulate' available plant traits linked to ecosystem processes to guide restoration efforts while facilitating to practitioners’ and other relevant stakeholders' selection of locally-adapted species for restoring ecosystem services.

Better linkages between plant traits in agricultural systems, ecosystem processes and services can help restore functional and productive ecosystems that provide essential services contributing to health, livelihoods and well-being, in line with Aichi Target 14. The CBD Conference of Parties Short-term Action Plan on Ecosystem Restoration, which is expected to be adopted in Cancun as guidance to countries and other actors committed to land restoration, also calls for making better use of research on the functions of plant species in ecosystems and how they are linked to ecosystem functions and services.

Currently, there is strong evidence that plant traits - such as plant height, leaf size, leaf nutrient content, root depth, and ability to fix atmospheric nitrogen to ecosystem processes - are all linked. For example, the maintenance of soil fertility, an ecosystem service, is partly a product of ecosystem processes determining nitrate availability and de-nitrification potential which are largely predicted by leaf nitrogen content and root length trait values of the plant community. However, information is scattered across global datasets and is site or ecosystem specific.  

Furthermore, relationships between plant traits and ecosystem processes are commonly studied in natural ecosystems but less in semi-natural, and human-dominated ecosystems such as agricultural ecosystems. Agricultural systems occupy around 40% of the global land area and tend to have homogenized vegetation. For instance, there is a great opportunity to identify diversification strategies to restore ecosystem processes and services through plant diversification.

Bioversity International is studying evidence-based strategies for assembling and targeting plant traits that can deliver diverse ecosystem services that support food production. We started by focusing our efforts towards restoring ecosystem processes in and for agricultural systems in the Tigray, Oromia and Amhara regions of Ethiopia. These regions face high to severe degradation particularly due to water erosion. In each landscape, we triangulate plant information from three main data sources to identify the most complete range of locally-adapted plant species.

The first data source includes existing plant composition information such as that provided in the Vegetation map for Africa, which we used to identify plant traits that are locally adapted to abiotic conditions and disturbance, and the community-weighted value distributions of these traits, in 147 tree species.

The second data source includes evidence from literature, global datasets and genebanks with geo-located crop wild relatives, neglected and underutilized crops and engendered plants in each landscape (e.g. geo-located species from the Global Biodiversity Information Facility and the IUCN Red List ~450 species, Genesys pgr database ~612 species, Bioversity International collected sample database ~187 species).

The third data source is about local communities’ ecosystem service preferences and values. Through focus groups, field visits and interviews, communities indicated the benefits they get - such as consumption, firewood, medicinal and spiritual (~300 species) - for different plant species.

This triangulation and assessment of trait composition and variability across agricultural systems will guide the selection of locally-adapted species for restoring ecosystem processes that are either available in the landscape (remnant forest, community seedbanks) or genebanks.

We will create a trait hub or switchboard with current available information (plant-traits-ecosystem services) that can be easily linked and complemented with local preferences to identify agrobiodiversity strategies for restoration that are context-dependent, highlighting both the potential role of native site-adapted species and genetic diversity. This effort will more clearly articulate existing evidence on the linkages between plant traits and ecosystem services to inform policies and strategies on plant species selection for diversification and restoration efforts in agricultural ecosystems that provide multiple benefits. For example, the users will be able to identify locally-adapted and locally important species that supply nutritional services (e.g. based on nutritional traits) and other ecosystem services (e.g. soil fertility, soil stability, firewood) in agricultural land and their advantage over other approaches, such as reforestation using monocrops of exotic species.

In parallel to the Ethiopian case study, our team is reviewing literature and global databases to collate evidence linking traits or community to ecosystem processes and services in agricultural systems while highlighting current knowledge gaps. For example, nutrition-related traits are absent in currently available ontologies or global plant trait datasets. Our findings will complement in particular the Crop Ontology Project which is to date the most comprehensive open database on physiological, morphological and agronomical crop yield-related traits.

Our project includes data harmonization, connecting different sources of trait information and strong data collaboration and partnerships, producing an analytical inventory of available global databases and baseline data, and identifying ontologies needed to link all these data sources through data queries. We're about to start a challenging and exciting task. Contact us if you are interested in joining us!

By Natalia Estrada-Carmona, Post-Doctoral Fellow, Agricultural biodiversity and Ecosystem Services, Bioversity International, with input from Sarah Jones, Elizabeth Arnaud, Marie-Angélique Laporte, Celine Aubert, Fabrice DeClerck.

 

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The project 'Agrobiodiversity data for supporting restoration of degraded ecosystem services' is in collaboration with the Crop Ontology Project led by Bioversity International. The field work is embedded in the regional 'Blue Nile' innovation project of the CGIAR Research Program on Water, Land and Ecosystems (CRP-WLE) and the 'Seeds for Needs' approach of the CGIAR Research Program on Climate Change, Agriculture and Food Security (CRP-CCAFS) in Ethiopia. This work is funded by CRP-WLE and CGIAR Fund Donors.

This blog is part of a series that Bioversity International is rolling out around COP13 - Mainstreaming Biodiversity for Well-Being. The blogs explain why mainstreaming agricultural and tree biodiversity is critical in sustainable food and production systems if we are to achieve the Convention on Biological Diversity's Strategic Action Plan for Biodiversity 2011-2020 that "By 2050, biodiversity is valued, conserved, restored and widely used, maintaining ecosystem services, sustaining a healthy planet and delivering benefits essential for all people".

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Photo: Washing clothes by the river. The Ethiopian agricultural landscape is dappled with African acacia trees (Vachellia abyssinica). Credit: Bioversity International/C. Zanzanaini

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