What do we know about the future of agrobiodiversity in relation to food systems?

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By Nicola Cenacchi, Elisabetta Gotor, Athanasios Petsakos, and Benjamin Schiek

Food, land, and water systems face daunting challenges in the future, and the body of research exploring these challenges is growing rapidly. This note is part of a series developed by the CGIAR Foresight Initiative to summarize what we know today about the future of various aspects of food systems. The goal of these notes is to serve as a quick reference, point to further information, and help guide future research and decisions.

Key messages

  • Agrobiodiversity (or agricultural biodiversity) refers to the diversity of living organisms (plants, animals, bacteria, etc.) that underpin agricultural systems (Wood & Lenne’, 1999). It provides numerous critical benefits, from on-farm crop diversity and genetic resources that allow farmers to adapt crops to changing environments (Fowler & Hodgkin, 2004), to the provision of ecosystem services such as pollination, disease and pest resistance, soil health, and water conservation (Hajjar et al., 2008). These benefits in turn support resilient livelihoods, food security (Waha et al., 2022), and diversified, nutritious diets (Love & Spaner, 2007).
  • A number of ex ante theoretical and practical approaches have been used to show how greater agricultural biodiversity is connected to higher production and lower risk exposure, and assess the role that agrobiodiversity plays in supporting resilience of agricultural systems (Di Falco, 2012; Di Falco & Chavas, 2009). But little has been done to integrate the measurement of agrobiodiversity per se into foresight modeling, or to apply foresight tools and methods to study long-term effects of agrobiodiversity on a range of socioeconomic or environmental outcomes.
  • The recent development of the Agrobiodiversity Index and advances in integrated modeling systems provide opportunities for improved scenario analysis focused on agrobiodiversity and informed by agroecology and agricultural economics theory.

Recent trends and challenges

It is well established that protecting and investing in greater agrobiodiversity is needed to achieve multiple Sustainable Development Goals (SDGs) (S. L. R. Wood et al., 2018), and that this diversity is threatened by multiple factors, including climate change,  socioeconomic trends, and management decisions that have led to a global homogenization and degradation of both farmland and its genetic resources (IPBES, 2019; Purvis et al., 2019). For example, it is estimated that up to 22% of wild crop species may go extinct by 2055 (Brauman et al., 2019; Jarvis et al., 2008), and that over 9% of the mammal domesticated breeds had already become extinct by 2016 (IPBES 2019).

The magnitude of such threats is undermining the future sustainability of agricultural production and the food security and livelihoods of countless producers and consumers. For instance, it has been estimated that loss of pollinators has reduced the value of annual global crop production by between $235 and $577 billion (IPBES, 2019; Potts et al., 2016). The large uncertainty inherent in the evolution of global and local drivers of change, and the ensuing challenges, requires tools in support of urgent and informed decisions. However, few studies have applied foresight tools to analyze the medium- to long-term effects that investing in agrobiodiversity may have on socio-economic and ecological outcomes, as well as for adaptation to and mitigation of climate change. Such studies may also be useful to highlight the trade-offs between immediate human needs and the benefits that agrobiodiversity may provide in the long term through the provision of multiple ecosystem services.

What is the latest foresight research on this topic?

A mature literature exists on the farm level benefits, impact pathways, and non-market valuation of agrobiodiversity (Di Falco, 2012; Kontoleon et al., 2009). There remains a challenge of linking modeling insights developed at the farm scale with mechanisms and drivers at the ecosystem and global scale.

A rich literature also addresses the effects that alternative policies or management practices may have on levels of agrobiodiversity (Petsakos et al., 2022). However, to our knowledge such studies generally lack a time dimension and consideration of other important drivers of change in food systems over the medium to longer term.

Few studies based on scenario analysis have used integrated models to explore the effects of increased agrobiodiversity on farm productivity, incomes, diets, and ecosystem services (Enahoro et al., 2019, 2021; Kozicka et al., 2020, 2022). These studies commonly link a global partial equilibrium model of the agriculture sector to farm models, environmental simulation tools, and models that analyze changes in ecosystem services.

When agrobiodiversity is studied as a driver of change it is often represented through proxy indicators. For instance, scenario analysis has been used to explore how agroforestry compares to monocropping vis a vis the expansion of agricultural land to accommodate growing demand for animal sourced foods in Tanzania (Enahoro et al., 2019; Kozicka et al., 2022). In these studies, the two management systems were mainly distinguished in terms of the biomass they are able to produce to meet livestock production needs (e.g., yields of maize in monocropping double the yields of agroforestry), or characterized through parameters relevant to the delivery of specific ecosystem services (e.g., above- and below-ground carbon pools).

Foresight work looking at changes in the level of agrobiodiversity is also uncommon. In one example, the Shannon Index was used as a measure of change in agrobiodiversity following three possible scenarios of impacts on farming systems in Uganda (Kozicka et al., 2020)

What do those studies show?

Compared to monocropping, agroforestry-based interventions in Tanzania hold promise for mitigating losses to key ecosystem services; in particular, erosion was halved while increasing production of animal-source foods. However, because more agrobiodiverse systems generate lower yields and greater conversion to cropland, some trade-offs may arise between meeting the demand for animal source foods and maintaining ecosystem services (Enahoro et al., 2019; Kozicka et al., 2022).

The Uganda case study shows that for shocks such as those caused by climate change or long-lasting crop diseases, increasing on-farm crop diversity can improve soil and human health and lead to higher socioeconomic system resilience (Kozicka et al., 2019, 2020). However, trade-offs do exist. While greater diversity can boost revenues and could restore dietary vitamin A close to pre-shock levels, it may also lead to more volatility in revenues.

Similarly, other studies summarize the multiple avenues through which agroforestry interacts with planetary health and note the need for highly context-specific assessments (Rosenstock et al., 2019), and highlight the benefits of agroforestry for household asset accumulation while also pointing out the difficulties in achieving broad adoption (Hughes et al., 2020).

What are the key gaps, questions, and opportunities for further foresight research on agrobiodiversity?

There seems to be a lack of research and application of foresight analysis either to the measurement of agrobiodiversity or its role as a driver of ecosystem services and a key determinant of food security and resilient livelihoods. Factors that may contribute to this situation include (a) confusion around the definition of agrobiodiversity, and (b) the difficulty of capturing in foresight models the causal relationships between socio-economic factors and their impacts on agrobiodiversity. While these difficulties are not trivial, we see three possible ways of including agrobiodiversity in foresight-type scenario analysis.

First, long-run scenario analysis could be used to estimate how agrobiodiversity may be changing as a result of specific policies and management decisions, across geographies and farming systems. The recent publication of the Agrobiodiversity Index (ABDI) (Jones et al., 2021) provides an opportunity for foresight models to measure in a systematic way a broad range of aspects related to agrobiodiversity across both producer and consumer sides of the food system.

Second, agrobiodiversity can be analyzed in terms of the future effects it may have on outcomes from the provision of ecosystem services to agricultural productivity, incomes and livelihoods, and food security. This area of foresight research is still in its infancy. An additional path may be through the development of a feedback loop between a land-use change model and an integrated model such as IMPACT (Robinson et al., 2015), with possible links to biodiversity models.

And third, foresight tools and methods can be used to explore how major global drivers of change, as well as different policies, technologies, and trends, may affect biodiversity in general. These types of analysis are fairly well established from a methodology standpoint, but the emphasis is typically given to extinction risk, abundance, habitat loss and degradation, and changes in species distributions, especially for vascular plants and vertebrates (Flachsbarth et al., 2015; Leclère et al., 2020). But some such studies and methodologies may offer additional insights into impacts on agrobiodiversity as well.

Authors of this note are Nicola Cenacchi, Senior Research Analyst at the International Food Policy Research Institute (IFPRI); Elisabetta Gotor, Principal Scientist, Athanasios Petsakos, Scientist, and Benjamin Schiek, Senior Research Associate at the Alliance of Bioversity International and CIAT.

If you have any feedback or questions about this note, please get in touch with Nicola Cenacchi at n.cenacchi@cgiar.org.

For more information, check out these resources:

On foresight modelling for biodiversity: Leclère, David, Michael Obersteiner, Mike Barrett, Stuart H M Butchart, Abhishek Chaudhary, Adriana De Palma, Fabrice A J DeClerck, et al. 2020. “Bending the Curve of Terrestrial Biodiversity Needs an Integrated Strategy.” Nature 585 (7826): 551–56. https://doi.org/10.1038/s41586-020-2705-y.

On modelling for biodiversity and ecosystem services: Wood, Sylvia L R, Sarah K Jones, Justin A Johnson, Kate A Brauman, Rebecca Chaplin-Kramer, Alexander Fremier, Evan Girvetz, et al. 2018. “Distilling the Role of Ecosystem Services in the Sustainable Development Goals.” Ecosystem Services 29: 70–82. https://doi.org/https://doi.org/10.1016/j.ecoser.2017.10.010.

On the value of agrobiodiversity: Falco, Salvatore Di. 2012. “On the Value of Agricultural Biodiversity.” Annual Review of Resource Economics 4 (1): 207–23. https://doi.org/10.1146/annurev-resource-110811-114543

About the agrobiodiversity index, including links to the publications: https://www.bioversityinternational.org/abd-index/


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Photo: Palm nut fruits or areca nut at the farm at Lubuk Beringin village, Bungo district, Jambi province, Indonesia  (Tri Saputro/CIFOR).

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