### 2.2.2 The Solution: Sustain and Enhance the Nutritional Benefits of Blue Food Systems

To manage blue food systems for the benefit of nutrition and health, governments should:

(a) Recognize the centrality of the right to food in blue food trade and domestic policy

The right to food states that everyone is entitled to adequate, accessible and safe food that corresponds to their cultural traditions in a fulfilling and dignified manner (Fakhri 2020). A Right to Food means that governance of and investment in blue food systems should seek balance between economic opportunities and local rights to food provisioning (Bennett et al. 2021; Hicks et al. n.d.), aiming to sustain and innovate with the full diversity of species, production and harvest methods, product forms and distribution channels in mind (Golden et al. 2021). Recognizing the right to food requires taking a food systems approach in which nutrition, sustainability, climate-resilience and equity can be considered together (see Sect. 2.1) and which ensures that all actors are represented, including through engagement with grassroots and civil society organizations (see Sect. 2.3) (Bennett et al. 2021; Hicks et al. n.d.). Recognizing the food rights of Indigenous Peoples who harvest aquatic foods is of particular importance, whether such Peoples have Nation status or not. At a national level, blue foods should explicitly be included in food and nutrition policy (see Sect. 2.1) (Bennett et al. 2021; Thilsted et al. 2016; Koehn et al. 2021). Internationally, blue foods should be positioned as a vital food source in the context of the UN Sustainable Development Goals, health national adaptation plans (HNAPs), and other international efforts to alleviate malnutrition (Bennett et al. 2021).

(b) Harness the nutritional diversity of blue foods

Governments should ensure that the nutritional potential of blue foods serves to improve the health and diets of nutritionally vulnerable people. They should recognize and harness the diversity of local blue food nutritional profiles, preparation methods and dietary practices (Hilborn et al. 2020).

Governments should manage capture fisheries so as to optimize them for nutritional benefits, not just for maximum sustainable yield, which can uncover opportunities to diversify fish production without increasing pressure on existing stocks (Golden et al. 2021; Bernhardt and O'Connor 2021). Aquaculture development should foster the sustainable production of native small fish species that can supply context-specific nutrient needs. As an example, *mola*, a fish species from the Gangetic floodplains, can easily be produced in homestead ponds and offers 80 times more vitamin A than commonly farmed silver carp (Thilsted et al. 2016).

Governments should evaluate exports and licenses to distant water fleets to ensure that they don't compromise nutritional goals. In some cases (e.g., Namibia), retaining just a small portion of current exports could meet local nutrition goals
(Hicks et al. 2019), though this requires infrastructure to support equitable distribution and access to blue foods locally (see Sect. 2.3).

Public health policies and investments focused on reducing malnutrition should include blue foods in programs to address the specific nutritional needs of pregnant and lactating women, young children and the elderly – with appropriate consideration of food safety and pollutants – as was done with the introduction of dried small fish powder in Myanmar to support children’s health (Dried small fish powder provides opportunity for child health in Myanmar 2020).

(c) Halt loss of nutrients from blue food systems

To ensure that blue foods important for nutrition are available, accessible and affordable, governments should take steps to reduce losses in the system. Improved processing methods can preserve and concentrate nutrients and increase availability, as well as improve nutritional quality (Siddhnath et al. 2020).

In many places, better management of capture fisheries through harvest controls or spatial restrictions, for example, can restore fish stocks and increase yields (Hilborn et al. 2020; Melnychuk et al. 2021; Anderson et al. 2018). Better regulation of economic development in floodplains, riparian, coastal, and ocean ecosystems can help protect blue food production and reduce risks to food safety (Niane et al. 2015; de Oliveira Estevo et al. 2021).

Fisheries and aquaculture policy should also anticipate and adapt to projected impacts from climate change (FAO 2018; Tigchelaar et al. 2021). Governments should consider nature-based solutions like mangrove and seagrass restoration and restorative aquaculture that can help strengthen the resilience of aquatic ecosystems (Gattuso et al. 2018; Hoegh-Guldberg et al. 2019). Additional climate adaptation options are context-specific, but include shifting to offshore resources (McDonald and Torrens 2020), devising climate-smart agreements for transboundary resources (Oremus et al. 2020) and investing in climate information systems, including early warning systems for extreme events (Cinner et al. 2018; Turner et al. 2020). Place-based responses to climate change are particularly important for Indigenous Peoples whose cultures and identities are closely linked to their local environments (Whitney et al. 2020).

(d) Improve the distributional equity of blue food production and consumption

Participation in activities along the value chain is often socially differentiated; for example, men dominate blue food production and women blue food processing. Governments thus need to collect data on what roles, from fish producers to post-harvest processors, traders, and consumers, different groups in society hold and why. When divisions of labor exist because of unequal opportunities to participate across the value chain, they are likely to result in distributional and nutritional inequities (Udo and Okoko 2014). Investments to address the drivers of unequal opportunities, such as through strengthening women’s empowerment, are known to lead to improvements in outcomes for women and their families. For example, in Zambia, strategies to uncover underlying structural barriers that limit participation, such as unequal norms and attitudes, increased women’s participation in production
processes, and their control over resources (Kaminski et al. 2020). Governments need to ensure that the full diversity of actors, across social groups, including gender, class, and ethnicity, and along the value chain and scale of production, are fairly represented in decision-making processes (Hicks et al. n.d.) (see Sect. 2.3). In addition, governments should recognize subnational differences in nutritional vulnerability and blue food access in national policy and align subnational policies and instruments with nutritional goals.

## 2.3 Support the Central Role of Small-Scale Actors in Fisheries and Aquaculture

### 2.3.1 The Problem: Limited Recognition and Support for the SSFA Sector in Supporting Equitable and Sustainable Food Systems

Small-scale fisheries and aquaculture (SSFA) have been marginalized in dialogues about sustainable and equitable food system transformation, despite being central to it in many contexts (Bennett et al. 2021). SSFA play a key role in supplying nutrition and supporting local economies in many countries. They produce more than half of the global fish catch and contribute over two-thirds of aquatic foods destined for direct human consumption (FAO 2020a), with the potential for lower environmental footprints (e.g., lower fuel use than in large-scale operations (Gephart et al. 2021a)). In addition, the value chains that process and sell their products support about 800 million full- and part-time jobs, half of which are occupied by women (FAO 2012, 2020a). SSFA produce a high diversity of aquatic foods. This diversity underpins healthy diets, and resilience in the face of shocks, climate and market changes (Hicks et al. 2019; Gephart et al. 2021b; Bennett et al. 2020; Campbell et al. 2021). SSFA also contribute to intra-regional trade, especially in smoked and dried products, which can have more direct impacts on food security and poverty alleviation than the globalized system (Béné et al. 2010).

SSFA worldwide face a growing range of threats and challenges, including resource over-exploitation, habitat degradation, poor political representation, market-driven competition for resources (e.g., patterns of trade and foreign fishing), assumed links between informality and illegality (Song et al. 2020), climate change (Monnier et al. 2020), and shocks such as the current COVID-19 pandemic (Bennett et al. 2020; Farmery et al. 2021; Short et al. 2021). Cumulatively, SSFA are being ‘squeezed out’ of the spaces they occupy on the land-water margins by other more powerful sectors, such as tourism, residential and industrial land use, oil and gas exploration, industrial fisheries and aquaculture (Cohen et al. 2019). Within SSFA, inequitable access to resources and opportunities and limited gender and social inclusion are key threats. Indigenous Peoples whose lands and waters have been colonized by others, and whose harvesting activities tend to be small-scale, continue to be marginalized by public policy. Finally, pervasive data and monitoring limitations pose major challenges to understanding the status of SSFA (Pauly and Zeller
2016), as a lack of data leads to underestimating SSFA contributions and marginal-
izing SSFA in policy and decision-making, while aggregated and categorical data
fail to represent the diversity of SSFA actors and benefits.

Governments and policies predominantly focus on industrialized, large-scale
fisheries and aquaculture, leading to a lack of voice and support for SSFA. One
reason for this persistent neglect is that policymakers struggle with the diversity,
dynamism and perceived informality of SSFA and their associated cultures (Hicks
et al. n.d.). Most policies affecting the sector make unrealistic assumptions that
SSFA are a homogenous group limited to producers (Gelcich et al. 2018; Johnson
2006). In contrast, the sector is extraordinarily diverse along many dimensions
(Short et al. 2021). Successful transformations of SSFA require supporting current
activities while exploring new opportunities and encouraging both the entry of new
actors into the sector and the redeployment of some current actors to opportunities
outside it.

## 2.3.2 The Solution: Support SSFA Capabilities and Diversity Through Inclusive Blue Food Policy

Governments of countries where SSFA operate should place this sector at the center of their national human development and food security strategies, creating initiatives that support the capabilities of the diverse SSFA actors. Supporting the viability of SSFA requires governments to:

(a) Include actors from SSFA in decision-making and policy development

Inclusion of SSFA in decision-making is essential to enable more adaptive governance mechanisms and policies that build on the strengths of the diversity of SSFA, acknowledge the cultural importance and specific roles of blue foods for diverse actors and steer food systems towards a more equitable distribution of blue food benefits.

Women are greatly underrepresented in policy and decision-making, even though they make up half of the workforce in SSFA globally. Recent efforts to improve gender equity in blue food policy have tended to adopt a narrow focus on women, overlooking men or gender relations (Lawless et al. 2021). Such a narrow focus risks exacerbating inequities by placing the blame, or burden for change, on women (Hicks et al. n.d.). Blue food policy development therefore not only needs to involve more input and leadership from women, but also should take a gender transformative approach to improving intersectional equity in SSFA (Hicks et al. n.d.; Lawless et al. 2021; Cole et al. 2020).

Indigenous coastal and riparian Peoples tend to be more blue food-dependent
than the wider population in the countries they live in (Bayley 1981; Cisneros-
Montemayor et al. 2016). They also have proven systems for food system
governance – including knowledge systems – that, if recognized and supported,
could enable the ‘decolonization’ of their food systems (Coté 2016). As access to
traditional food sources has been lost, adoption of unhealthy diets based on
processed foods have led to high rates of diet-related non-communicable diseases (Kuhnlein and Receveur 2003; Hawley and McGarvey 2015). Thus, by supporting Indigenous Peoples' food (and wider) sovereignty claims, governments could contribute to transformative health benefits in these communities and nations.

Governments should support and strengthen multi-stakeholder initiatives that have the benefits of SSFA at their core, including organizations of fish workers, harvesters and producers at the global, regional, and national levels, such as the World Forum of Fish Harvesters and Fish Workers (WFF), the World Forum of Fisher Peoples (WFFP), and the International Collective in Support of Fish Workers (ICSF).

## (b) Expand capabilities through investment in institutions and human capital, and investment in environmental protection and restoration

Securing the future of SSFA requires adaptive action that supports the capabilities of SSFA to deliver both market and non-market societal benefits. Positive environmental outcomes, for example, require engagement of SSFA actors to co-produce knowledge, forge strategies for sustainability and climate adaptation, and participate in and lead environmental restoration, conservation and adaptation efforts.

Governments should create space for SSFA as they expand agricultural and industrial aquaculture and fishery sectors. They should use public and private regulation and financial mechanisms to enable SSFA actors – including Indigenous Peoples – to (re)gain control over the resources, rights, skills and knowledge necessary for environmentally resilient and socially equitable production and trade (including insurance, credit, and market mechanisms to buffer against extreme events).

Governments should also allocate and enforce land, water and labor rights to SSFA through user rights-based systems, the creation of preferential access areas, coastal and inland land use zoning, or other measures. To support the roles of SSFA in creating livelihoods and resilient and equitable food systems, governments should also provide capital, through public and private financial mechanisms that empower, rather than undermine, SSFA actors. In the case of Indigenous Peoples, recognition of their collective sovereign rights is the key starting point.

## (c) Support diversification and sustainable intensification

For many SSFA producers, it will be crucial to find pathways for sustainable intensification or expansion of their operations or for diversification into other SSFA products or other sources of livelihood. To that end, governments should invest in R&D and facilitate access to venture capital to support innovation in species/production systems that are of high value for nutrition, livelihoods, and justice. They should also support the development of complementary livelihoods, which are often critical to continued participation by SSFA actors, their control of the resource base and its sustainability.

Costs, trade-offs, and potential environmental and social impacts of intensification and diversification should be carefully considered, and diversification should be proactively designed and monitored. To this end, efforts should be made towards better integration of different data types and sources and enabling the effective and
timely access to and use of data by relevant actors. Investment is needed in monitoring systems for catch, effort, production and consumption, and in national surveys of engagement in SSFA that are fully gender-inclusive, and that reflect intersections of gender, age and ethnicity. Promotion of R&D towards technological solutions to data collection, storage and communication/accessibility barriers would effectively support these needs.

(d) Secure economic and nutritional benefits through trade policies and the
development and protection of local and national markets

Governments, in particular, those in low-income food insecure nations, need to be able to regulate the activities of large corporate actors and trade to protect the rights (e.g., labor rights, human rights, right to food) of SSFA workers, to ensure that terms, conditions, and revenues from trade are transparent and fair, do not impact local food security, and, where needed, retain high nutritional value products for local consumption. Regulation should consider the potential trade-offs and linkages between nutritional and economic value of resources. It should establish transparent processes, monitoring systems, and accountability mechanisms to ensure the traceability and visibility of social impacts. Market-based approaches that encourage actors to add value to products through processing, marketing or certification need to carefully consider trade-offs in economic, social, environmental, and public health outcomes (see Sect. 2.1).

Governments should also explore opportunities to support “alternative” systems based on short supply chains for products with strong local identities and local, decentralized production and processing. Diversity, deeply embedded in these food systems, could be supported by policies mandating or incentivizing local retention of SSFA products to ensure food self-sufficiency, for example, the development or control of local markets and school feeding programs.

**3 Conclusion**

Blue foods have vital roles to play in the transformation of the global food system. In the face of growing challenges and rising demand, governments must act now to support and expand these roles. They should bring blue foods into the heart of their food decision-making, by creating a Ministry of Food or other governance structures that integrate blue foods fully into food policies, budgets and programs, managing the terrestrial and aquatic food systems as a whole. They should recognize the right to food and harness the nutritional diversity of blue foods in ways that ensure the equitable distribution of blue food production and consumption. And they should empower and support the millions of small-scale actors in fisheries and aquaculture who produce, process, distribute and trade most of the food we eat, and can be the key to a vibrant, sustainable, healthy, and equitable blue food economy. Recognizing and acting upon the potential role of blue foods in all dimensions of food policy
would be a clear win for the 2021 UN Food Systems Summit and achieving the 2030
Agenda for Sustainable Development.

**Acknowledgments** This chapter was prepared by researchers who are part of the Blue Food Assessment (BFA; https://www/bluefood.earth/), a comprehensive examination of the role of aquatic foods in building healthy, sustainable, and equitable food systems. The key messages and recommendations in this chapter were derived from several papers that are part of the BFA, as well as related materials. A complete list of BFA papers can be found at https://www/bluefood.earth/science/.

Funding: the BFA was supported by the Builders Initiative, the MAVA Foundation, the Oak Foundation and the Walton Family Foundation.

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<figure><img src="image_85.png" /></figure>
# Food System Innovations and Digital Technologies to Foster Productivity Growth and Rural Transformation

<figure><img src="image_86.png" /></figure>

Check for
updates

Rui Benfica, Judith Chambers, Jawoo Koo, Alejandro Nin-Pratt, José Falck-Zepeda, Gert-Jan Stads, and Channing Arndt

## 1 Introduction

Food systems are a powerful lever for countries to overcome poverty, hunger, and malnutrition. In the next few decades, low- and middle-income countries (LMICs) will need to respond to numerous challenges, including rising food demand, shifts toward healthier diets, deleterious climate change effects, and the need to preserve biodiversity. Accelerated efforts to raise agricultural yields (Alexandratos and Bruinsma 2012) and increase productivity in agricultural value chains are needed, especially for vulnerable populations in LMICs. Innovations in food systems, facilitated by improved technology for more precise breeding and input use efficiency, the enabling of policy and regulatory environments, increased investments, and enhanced individual and institutional capacities (Fuglie 2018) in research development and delivery can significantly contribute to those goals.

Currently, many LMICs lack the capacity to innovate and/or benefit from global developments in agricultural innovations and digital technologies. Several factors are at play. First, while advanced and high-middle-income countries use R&D investments to catalyze technological and economic transformation (Ruttan 1982), many LMICs lag in both investment and human/institutional capacity (Beintema et al. 2012). Second, many countries are constrained by the inherent characteristics of their agrifood system operating environments, which are mostly rural, remote, and dominated by small farms, making it hard for innovations to take hold. They are

<footnote>R. Benfica (✉) · J. Koo · A. Nin-Pratt · J. Falck-Zepeda · G.-J. Stads
International Food Policy Research Institute (IFPRI), Washington, DC, USA
e-mail: R.Benfica@cgiar.org</footnote>

<footnote>J. Chambers
Program for Biosafety Systems, IFPRI, Washington, DC, USA</footnote>

<footnote>C. Arndt
Environment and Production Technology Division, IFPRI, Washington, DC, USA</footnote>
hampered by limited infrastructure density (roads, telecommunications, weather stations, energy grid, etc.); poorly developed markets and value chains; and inadequate financial services. They also lack efficient mitigation systems to address risks arising from climate change, global trade, and invasive species. Finally, they lack supportive enabling policies and regulations to facilitate the discovery, development, and delivery of food system and digital innovations.

Promising advancements in bioscience and digital technologies offer opportunities to address the innovation challenges and close the productivity gap for LMICs. Applications of biotechnology research have led to more precise introduction and enhancement of essential traits in crops, animals, and micro-organisms. The CRISPR-Cas9 genome editing system has become a viable tool for targeting specific genomic changes (Es et al. 2019), producing results similar to those achieved through conventional plant and animal breeding methods, but with more efficient, timely, and cost-effective R&D trajectories (Gao 2018). Likewise, digital technologies are contributing to accelerated food system transformation, optimizing management decisions (Basso and Antle 2020), facilitating information flows across food-land-water systems (von Braun et al. 2017), and facilitating regional and global trade (Jouanjean 2019).

Accordingly, this brief focuses on agricultural bio-innovations and digital technologies as important drivers of food system transformation over the next decade, and outlines elements relevant for all types of innovation to succeed. Taking a systems landscape perspective, it highlights R&D and economic viability, and environmental and social effects, while addressing enabling factors, such as R&D investment, institutional and human capacity, infrastructure, and the variety of socioeconomic, regulatory, and political economy factors that affect development, delivery, and adoption pathways for new technologies.

## 1.1 Agricultural Bio-Innovations

Agricultural bio-innovations comprise a broad suite of technologies, including conventional and marker-assisted breeding in crops, livestock, fish, and microorganisms, as well as biofertilizers and precision agriculture. Newer improvement techniques include genetic modifications (GM) and new breeding techniques (NBTs) such as genome editing. These confer protection from pests, diseases, and weeds, and offer other novel uses and applications that address environmental conditions and climate change effects.<fnref n="1" /> This paper highlights crop bio-innovations, as these have advanced significantly but are still facing challenges that could

<footnote n="1">¹New bio-innovations also revolutionized livestock and fish breeding, including aquaculture and embryo transplantation (Belton et al. 2020). Genome editing and other biotechnology-based livestock transformation technologies have vast potential to help address human and animal needs, as well as environmental challenges. R&D areas under development in the livestock sector include disease models, xenotransplantation, vaccine production, enhanced animal breeding and</footnote>
constrain their use and viability. Some of those challenges are also relevant for other
bio-innovations.

Historically, investments in crop improvement research, dominated by conven-
tional breeding, have led to gains in agricultural productivity. In a comprehensive
assessment, Evenson and Gollin (2003) documented high growth rates in the
productivity of most cereals. Their analysis suggests that at least half of all total
factor productivity (TFP) gains between 1960 and 2000 were attributable to crop
genetic improvements. They also found that countries without genetic improvements
were less likely to realize TFP gains from other sources (Evenson and Gollin 2003).
A study by Lantican et al. (2015), covering three-quarters of the world's wheat area,
shows that genetic improvement contributed to an increase in wheat yields from 2.5
tons/ha (hectare) in 1995 to 2.8 tons/ha in 2015, an increase of 0.6% annually. In the
case of maize, Krishna et al. (2021) find that genetic improvement efforts in 10 major
maize-producing countries in Africa<fnref n="2" /> increased yields from 1.4 tons/ha in 1995 to
1.7 tons/ha in 2015, an average annual increase of 1.0%.

Despite this, in the absence of infusions of new technology, conventional breeding has limited the potential to address increasing demand for food and biomass or to mitigate agro-environmental challenges in a timely manner (Gao 2018). Recent biotechnology applications offer multiple benefits to LMICs, given the array of biophysical, climate, and socioeconomic challenges these countries face. However, their adoption varies across developing economies. Differences in R&D capacity, delivery, adoption, and benefits often reflect disparities in the socioeconomic and political factors that affect public perceptions, and in the prevailing policy and governance environments. If such factors are limiting, they can restrict the technology frontier and constrain farmers’ access to potential solutions.

Consequently, more emphasis should be put on interventions that address the mix
of research and enabling policy factors necessary to realize the pro-poor benefits of
bio-innovations. To illustrate this consideration, we focus on genome editing,
specifically CRISPR-Cas9, given its transformative potential and the urgent need
to develop the enabling R&D and policy trajectories required for impact.

CRISPR-Cas9 uses targeting technologies that can produce new varieties that resemble “nature-identical” variants (Gao 2018). These varieties may be more resistant to disease, poor environmental conditions, and climate change; include desired agronomic and nutritional traits; and require fewer inputs. Compared to other methods, CRISPR-Cas9 is more targeted, faster, more efficient, more and cost-effective, making it a viable technology choice for revenue-stressed countries. Additionally, regulators who have evaluated the science recognize the need to examine those technologies and make decisions on a case-by-case basis, as gene editing can generate products that do not result in transgenic events, and thus do not necessarily require regulatory scrutiny. All of this makes CRISPR-Cas9 agricultural

<footnote>improvement, and bioreactors (Zhao et al. 2019). Some livestock technologies have been already deployed commercially (Perisse et al. 2021; Yum et al. 2018).</footnote>

<footnote n="2">²Benin, Cameroon, Ghana, Guinea, Madagascar, Mali, Rwanda, Senegal, Uganda, and Zambia.</footnote>
<figure><img src="image_87.png" /><figcaption>**Fig. 1** The enabling environment for technology transfer, adoption, and use. (Source: Based in part on Falck-Zepeda 2021)</figcaption></figure>

applications attractive investment options for global public goods research (Gao 2018; Pixley et al. 2019). Despite these advantages, however, poor enabling environments could still limit the value of and access to CRISPR-Cas9 agricultural bio-innovations for resource-poor farmers, traders, and consumers. Figure 1 illustrates the complex relationships among the factors required for the successful adoption and diffusion of bio-innovations.

The elements shown in Fig. 1 help determine whether a technology will succeed, including decision-maker support through enabling policies, economic benefits and functioning markets, and effective extension services. Some elements may be more relevant to genome editing bio-innovations, depending on the context in which these technologies operate. A discussion of factors most relevant to genome editing follows.<fnref n="3" />

* **Intellectual property (IP) considerations.** Evolving trends in IP rights and restrictions related to genome editing may drive technology access across organizations and influence the reach of public goods R&D efforts. Results of an analysis triangulating patents, published research, and public news searches reveal some important findings (Martin-Laffon et al. 2019; IPStudies 2019, 2020; Brinegar et al. 2017; Zambrano et al. 2021). First, globally, the public sector leads in the foundational CRISPR-Cas9 IP landscape. China leads in published research and patent filings, followed by the United States. Public institutions lead in both areas in China, while in the United States, the public sector dominates research, but the private sector dominates patent filings. Second, research and patent filings are dominated by rice, driven by China, with additional research focused on 17 other crops/plants across 24 countries. In the United States, the patent landscape is notable for its growing and diversified set of commodities and institutions. Third, foundational patent-holders are explicitly

<footnote n="3">³These likely apply to crops, animals, fish, and microorganisms.</footnote>
licensing their proprietary positions and providing incentives for strategic alli-
ances that promote access to IP-protected R&D inputs. In that context, interna-
tional and national agriculture research organizations (IARCs and NAROs) have
successfully negotiated licensing agreements for CRISPR-Cas9. Finally, more
private sector licensors of genome editing technologies are negotiating multiple-
partner IP licenses for the development of agricultural and industrial applications.
Major biotechnology firms are negotiating licenses with several CGIAR centers,
small private firms, and start-ups.

This evolving IP landscape points to the critical need to ensure and secure
continued development of novel, productive mechanisms to facilitate IP access
for pro-poor innovations to guarantee freedom to operate technology product
development and deployment. Despite the positive trends in licensing for public
good genome editing technologies, the CGIAR centers, IARCs, and NAROs still
lack sufficient capacity to ensure and self-determine their equitable access to
these technologies.

* **Regulatory considerations.** The costs of regulatory delays in the approval of innovations may reduce access to potentially valuable technologies and affect market entry, and thus the realization of potential benefits. Feasible regulatory frameworks are those that consider evidence-based scientific approaches balancing safety, time, and costs, and that are both risk-proportional and fair (Arndt et al. 2020; Falck-Zepeda et al. 2016), generally leading to valuable technologies being approved for potential producer use. Without this solid foundation for decision-making, regulatory frameworks could create large opportunity costs, as an examination of regulatory delays associated with GM crops has demonstrated.<fnref n="4" /> In the face of a similar regulatory environment, these opportunity costs could be even higher for genome editing, given the expanded licensing and R&D efforts across a growing array of food-security-relevant traits and crops (Chen et al. 2019). Conversely, the wider range of applications for genome editing, combined with lower development costs and enabling policy factors, implies greater potential for positive economic benefits. In fact, given that potential, the opportunity costs of excluding genome editing from the technology options available to improve agricultural productivity are quite significant (Wesseler and Zilberman 2014; Wesseler et al. 2017).

* **Socioeconomic and political economy issues.** It is widely recognized that socioeconomic and political economy factors can promote or prevent the successful deployment of bio-innovations. Current research indicates that GM crops can potentially address critical biotic and abiotic constraints in agriculture and livestock production efficiently but lack broad-based public acceptance (Ahmed

<footnote n="4">⁴The cost of regulatory delays for GM crops is well documented (Wesseler et al. 2014; Smyth et al. 2016). Costs of regulatory delays in livestock and fisheries sectors are also significant (Van Eenennaam et al. 2021).</footnote>
et al. 2021; Gouse et al. 2016; Chen et al. 2019).<fnref n="5" /> NBTs, including CRISPR-Cas9, risk facing the same impediments to adoption as GM crops, though many NBTs will not include foreign DNA. Extrapolation of results from economic impact assessments for conventional and GM-assisted plant breeding suggests that returns from genome editing technologies may be significant, with important implications for LMICs. It is therefore critical to develop science-based regulatory guidance that promotes the use of this technology to address the needs of the poor.

## 1.2 Digital Technologies in Agricultural Value Chains

Digital innovation is transforming lives worldwide. We work, learn, communicate, shop, and entertain online. More than half of the world's population uses the Internet, with the 4G mobile network now covering about 85% of the global population (ITU 2020). Digital technologies catalyze development and accelerate economic growth. The digital economy is now equivalent to 15.5% of global gross domestic product (GDP) and has grown 2.5 times faster than global GDP over the past fifteen years (Huawei and Oxford Economics 2017). The agriculture sector is no exception. For family farmers in Africa, digital technologies revolutionize livelihoods by overcoming isolation, as they connect farmers to markets and financial institutions, speeding up change through digital extension and taking success to scale by using granular data to better target innovations (Annan and Dryden 2015). Research shows that innovative applications of digital technologies in agriculture enable more productive, efficient, resilient, and sustainable food systems (Basso and Antle 2020).

Digital technologies in agriculture leverage digitally collected data and analytics to guide decisions along agricultural value chains. Farmers can access high-frequency, high-resolution data to make customized decisions. Traders can predict food supply and demand dynamically and connect producers and markets at the right time with the right volume. Policymakers can make informed decisions related to investments, smart subsidies, and risk management. The following are examples of promising digital applications that address challenges along agricultural value chains:

*   **Remote sensing.** The rapid technological improvement of remote sensing makes the precise and timely monitoring of agriculture and natural resources possible, providing actionable information for farmers, traders, and policymakers. For large areas (for example, a country or region), satellite remote sensing can be used to manage food-land-water systems in an integrated and efficient way (Sheffield et al. 2018), including monitoring potential risks to crop yields

<footnote n="5">⁵Projections of potential for technologies already advanced in the regulatory pipeline include: Dzanku et al. 2018; Kikulwe et al. 2020; Phillip et al. 2019; Ruhinduka et al. 2020; and Yirga et al. 2020.</footnote>
(Burke et al. 2021), flash floods (Liu et al. 2018), landslides (Casagli et al. 2017), and locust infestations (Piou et al. 2019). Crop and livestock insurance providers increasingly rely on information from remote sensing to profile the risks and damages to production (Benami et al. 2021). When used in small areas, unmanned aircraft vehicles (UAVs or drones) can capture very high-resolution imagery on demand and provide farmers and extension services with useful and timely monitoring information.

* **Connected sensors.** Low-cost, Internet-connected sensors can directly monitor crop and environmental field conditions with speed and precision. These data help farmers make real-time informed and customized management decisions. Antony et al. (2020) conducted an extensive review of the literature and expert interviews on the use of Internet of Things (IoT) devices for smallholder agriculture, including automated solar-powered drip irrigation for vegetables, water-level sensors in rivers for flood alerts, automatic climate control systems, and in-field multiparameter sensors to monitor real-time crop conditions, providing extension agents with information to advise farmers.

* **Artificial intelligence.** As large amounts of data from multiple sources become available in real time, artificial intelligence (AI) helps combine data streams from multiple sources, analyzes them quickly, and generates timely, actionable insights. In addition to processing remote-sensing and IoT data, AI could revolutionize farm mechanization in the near future, with the use of agricultural robots that can apply fertilizer, remove weeds, and harvest crops (Torero 2021).

* **Digital advisory services.** Resource-poor farmers often lack access to information and advisory services at times of critical need. While developing country extension services are improving, with the number of extension agents now exceeding one million, insufficient and unsustainable financing for extension services remains an information constraint (Davis et al. 2020). Through digital channels (for example, mobile phones, interactive voice response, and the Internet), farmers and extension agents can directly access timely agricultural information customized for individual farmers' needs.

Many private companies offer subscription-based information services through mobile phones. In sub-Saharan Africa, CTA (2019) identified 390 digital agriculture services, of which 15 reached more than one million farmers. There is evidence of some positive impacts. Fabregas et al. (2019) conducted a meta-analysis of studies in sub-Saharan Africa and India, finding that farmers who subscribed to digital services increased their adoption of recommended agro-chemical inputs by 22% and their yields by 4%. CTA (2019) analyzed 50 impact studies in sub-Saharan Africa and found that subscribers' income increased by 20–40%. In Ethiopia, video-mediated extension was shown to reach wider audiences, enhancing agricultural knowledge and the uptake of technologies compared with conventional approaches (Abate et al. 2019).

* **Digital financial services.** Farmers often use cash in financial transactions, and are excluded from credit, savings, and insurance services. The World Bank (Demirgüç-Kunt et al. 2018) reports that, globally, 1.7 billion adults (31%) do not have accounts at financial institutions or through mobile money providers.
Common reasons include not having enough money, physical distance from financial institutions, and documentation requirements. Digital financial services (DFS) can address those constraints, provided that an active mobile phone is available to use as an entry point for financial inclusion. Evidence points to positive DFS impacts on rural households. In Kenya, Kirui et al. (2013) report that use of mobile money in rural areas increased input use by 95%, agricultural commercialization by 37%, and annual household incomes by 71%. Suri and Jack (2016) estimate that the M-PESA mobile money service in Kenya helped 194,000 households escape poverty and diversify income sources. Evidence from India suggests that picture-based insurance, which verifies insurance claims using smartphone images of insured plots, minimizes asymmetric information and claim verification costs while reducing risk compared to index-based insurance (Ceballos et al. 2019).

* **E-commerce.** Unlike traditional agricultural value chains involving multiple intermediaries, e-commerce allows farmers to directly connect with buyers, and so increase income. Agricultural e-commerce is at an early stage in LMICs, yet, although comprehensive impact evidence is unavailable, its potential is undeniable. By shortening supply chains, e-commerce can also reduce food waste and benefit consumers with fresher produce (GSMA 2019). During the COVID-19 pandemic, e-commerce has been pivotal in connecting farmers to markets and consumers to fresh foods (Reardon et al. 2021).

Like bio-innovations, digital technologies in LMICs face important policy challenges related to data ownership and user rights that require well-defined guidelines in terms of IP frameworks and regulations.

## 2 Agricultural R&D Enabling Investments and Capacities

The rise of biological and digital technologies offers viable options for LMICs, but also raises concerns about their preparedness to take advantage of these opportunities and to foster an appropriate enabling environment to support product development, deployment, and adoption.

Public agricultural R&D investment is a recognized major engine for promoting food system innovations; this investment funds socially valuable research that can potentially lead to private innovation for local benefits. In recent decades, support for public agricultural research in high-income (HI) countries has stagnated, while private agricultural research spending has increased, reshaping the structure of the global agricultural research system (Fuglie and Toole 2014). Global agricultural R&D investments have shifted from HI countries toward large middle-income economies (Brazil, China and India), which have grown in importance as agricultural producers and research leaders. Meanwhile, most low-income countries continue to lag significantly in agricultural R&D investments and human and institutional capacity, having thus experienced limited agricultural productivity growth.
<table><caption>**Table 1** Countries grouped by level of development of their agricultural research systems, 2016</caption><thead><tr><th>Key indicators</th><th>Lagging</th><th>Average</th><th>Advanced</th><th>Brazil, China, &amp; India</th></tr></thead><tbody><tr><td>Number of countries</td><td>55</td><td>50</td><td>15</td><td>3</td></tr><tr><td>Total R&amp;D investment (million 2011 $)</td><td>17,679</td><td>83,170</td><td>212,256</td><td>202,615</td></tr><tr><td>Average R&amp;D investment (million 2011 $)</td><td>9</td><td>46</td><td>393</td><td>1876</td></tr><tr><td>Share of R&amp;D investment among LMICs</td><td>3%</td><td>16%</td><td>41%</td><td>39%</td></tr><tr><td>Annual agricultural TFP growth, 2000–2016 (%)</td><td>0.7%</td><td>1.0%</td><td>1.3%</td><td>2.6%</td></tr><tr><td>Published articles per FTE researcher</td><td>0.1</td><td>0.4</td><td>0.7</td><td>1.3</td></tr><tr><td>H index (quality and influence of publications)</td><td>26</td><td>72</td><td>160</td><td>266</td></tr><tr><td>Share of total population among LMICs</td><td>11%</td><td>26%</td><td>14%</td><td>50%</td></tr><tr><td>GDP per capita (2011 $)</td><td>5405</td><td>5146</td><td>11,832</td><td>11,419</td></tr><tr><td>Number of people living on under $1.9/day (million)</td><td>111</td><td>238</td><td>80</td><td>366</td></tr></tbody></table>

Source: ASTI (2021), SCImago (n.d.), USDA-ERS (2021), and World Bank (2021). These are gaps in investment, human capital, and institutional capacity.

To fully benefit from the range of bio-innovations and digital technologies, LMICs require focused efforts to close the gaps in R&D. Only 18 LMICs possess agricultural research systems comparable to HI countries in quality and productivity (Table 1).<fnref n="6" /> Overall, countries with *lagging* research systems account for only 3% of total R&D investment in LMICs. Their investments are significantly smaller and less productive than those in countries with *average* or *advanced* systems. Moreover, LMICs with *lagging* research systems also show considerably slower agricultural productivity growth. Similarly, LMICs with *average* research systems trail those with *advanced* research systems in terms of R&D investment and long-term agricultural productivity growth. Given their modest share in global agricultural R&D investments and over-representation in global extreme poverty, evidence suggests these *lagging* and *average* countries could make enormous progress if R&D efforts were to be stepped up. Three main R&D gaps differentiate LMICs with *lagging*, *average*, and *advanced* agricultural research systems.

* **The R&D investment gap.** A country's agricultural R&D investment capacity depends on factors beyond the size of its agricultural GDP. The overall size of the economy, its income level, and the availability of relevant technology spillovers from other countries also play important roles. When comparing R&D investments of a given country with those of countries with similar characteristics, it is

<footnote n="6">⁶We used the country's H index of agricultural science and biology publications from SCImago (n. d.) to classify countries by quality and productivity of the agricultural research system.</footnote>
<figure><img src="image_88.png" /><figcaption>**Fig. 2** Agricultural R&D investment gap, as a percentage of R&D investment by country group, 2014–2016. (Sources: ASTI (2021) and World Bank (2021). Note: The Lagging group includes 53 countries; Average 50; Advanced 15. Eastern European and former Soviet countries were excluded)</figcaption></figure>

possible to determine attainable R&D investment based on relative investment
differences. The ASTI intensity index (AII) does precisely this by quantifying the
gap between a country’s agricultural research investment and its potential, based
on country comparisons (Nin-Pratt 2016). Use of the index shows that the
investment gap is much higher in countries with *lagging* and *average* agricultural
research systems than in countries with *advanced* systems (Fig. 2). Economic
development, the quality of institutions, and political constraints are major factors
determining governments’ revenues and spending capacity. Total government
spending in the *lagging* group was only $0.7 per person in 2011, compared to
$1.95 in the *advanced* group. Only 3–6% of total government spending in LMICs
is for agriculture, and only a fraction of that is allocated to R&D. These findings
underscore the need to reconsider the generalized recommendation to “increase
R&D investment in LMICs” and examine the unique development challenges
faced by countries with weaker R&D systems.

* **The human capital gap.** Even more significant than the investment gap is the human capital gap affecting the quality, scope, and potential of research systems in LMICs. This gap limits their participation in the emerging opportunities presented by bio-innovations and digital technologies. Despite an increase in the number of PhD-qualified agricultural researchers in developing countries since 2000 (ASTI 2021), the composition of researchers by degree differs significantly—countries in the *lagging* group are clearly disadvantaged, with only 17% of their agricultural researchers holding PhD degrees, compared with 75% in Brazil, China and India, and 27% in countries with *advanced* systems (Fig. 3). Although researchers in the *average* group of countries hold higher qualification levels, a very large portion of their PhD-qualified researchers is set to retire in the coming decade, a situation that is particularly severe in sub-Saharan Africa.

* **The institutional capacity gap.** The suboptimal quality of institutions causes inefficiencies and results in the underperformance of agricultural R&D systems, especially in *lagging* and *average* countries. Some of these inefficiencies may emanate from decisions made within countries (for example, centralized versus
<figure><img src="image_89.png" /><figcaption>**Fig. 3** Researchers with PhD, MSc, and BSc degrees as a share of total full-time equivalent (FTE) researchers. (Source: ASTI 2021)</figcaption></figure>

decentralized systems); others are structural in nature. For countries with relatively small economies and/or agriculture sectors and a limited supply of researchers, overall development of their agricultural research system is constrained by the size of research teams and the capacity to develop a critical mass of diverse and relevant research platforms. The situation for research systems in these countries will likely worsen with the increasing demand for research-oriented responses to address climate change-related challenges.<fnref n="7" />

## 3 Actions and Solutions for Enabling Food System Innovations

This analysis proposes a way forward to advance agricultural research and accelerate the scaling and adoption of bio- and digital innovations for food systems by closing critical gaps and promoting the necessary investments, policies, and regulations through actions at the global, regional, and national levels. Synergistically, those efforts will help accelerate agricultural productivity growth and food system transformations, as well as the achievement of the Sustainable Development Goals (SDGs).

At the global level:

* Facilitate LMIC engagement with global players in food system innovations to strengthen IP access and management capacity. Given the role of IP frameworks in determining access to emerging bio- and digital innovations, it will be important to create the conditions for agricultural research entities—such as IARCs, NAROs, and national agricultural research systems—to negotiate IP agreements with global innovators and enhance their IP management capacity so

<footnote n="7">⁷The average number of researchers per country in the group of *lagging* research systems is below 300 full-time equivalents (FTEs), compared to 900 FTEs in the *average* group, 3700 FTEs in the *advanced* group, and more than 12,000, on average, in China, India, and Brazil.</footnote>
as to ensure jurisdictional freedom to operate while fostering strategic alliances. On the crop biotechnology side, it will be important to engage with China and the United States to secure and support public good technology flows to developing countries.<fnref n="8" /> For digital technologies, appropriate mechanisms need to be established with key global players to enable efficient and cost-effective access to data and digital applications for the relevant stakeholders in LMICs.

* **Promote North–South, South–South, and triangular cooperation to strengthen LMIC regulatory frameworks.** Building on their relatively more advanced regulatory framework development, countries in the global North, as well as emerging players such as China, India and Brazil, should use available mechanisms to support LMICs’ efforts to advance their regulatory capabilities, including strengthening institutional and stakeholder capacity at different levels (Arndt et al. 2020).

To complement these global efforts, programmatic and policy actions will be needed at the **national and/or regional levels** to improve the development, delivery, and use of food system and digital innovations.

* **Adapt emerging technologies to local conditions.** Countries will need to invest in science-based participatory approaches to benefit from the range of food system innovations highlighted here that have potential to help address multiple challenges. Given the diversity among countries, adapting these technologies to local conditions—in ways that make them accessible to farmers and retain much of the gain among consumers—is challenging, especially for developing economies, smallholder farmers, and small businesses (Hendriks et al. 2021). Therefore, investments in science-based, participatory processes to map out realistic and equitable options are needed (Basso and Antle 2020).

* **Close the regulatory gaps for enabling innovations.** To minimize opportunity costs associated with regulatory delays, governments must create evidence-based regulatory environments, in a timely manner, that enable the safe use and application of bio-innovations and digital technologies by stakeholders in LMICs. This involves working with a diverse set of actors, including local and international scientists, the private sector, and others, to provide a pathway that ensures timely, secure, and equitable access. While these processes can benefit from global engagement, they should be customized to country-specific circumstances.

* **Close human capital gaps at the country level.** Training for a new generation of scientists and researchers should emphasize the development of skills needed to generate and deliver emerging and fast-changing biotechnology and digital innovations relevant to food systems, including the capacity to integrate local knowledge with modern science. Managerial capacity, business education, and multidisciplinary thinking are also critical. At the same time, work with governments and the private sector should improve the capacity of farmers, farmer organizations, and other value chain actors to adopt transformative food system innovations.

<footnote n="8">⁸For livestock, other players such as Argentina and Brazil are also critical.</footnote>
* **Close institutional capacity gaps.** Increasing institutional capacity will require addressing limitations in organizations' capacities and strengthening institutional coordination among food system stakeholders. Efforts by regional institutions and organizations to achieve long-term reforms could provide a more efficient and cost-effective way for groups of countries to work together to target specific goals and escape the trap of lagging research systems. In this context, it will be critical to create policy environments that stimulate cooperation among agricultural R&D agencies so as to maximize synergies and efficiencies, rather than solely relying on individual country efforts. The restructured One CGIAR can play a constructive role in this regard.

* **Develop a deeper understanding of political economy factors.** These factors impact the development and deployment of food system innovations to and within countries. A more nuanced understanding of actors, agendas (both social and economic), and influence relationships may better inform the understanding of technology hesitancy and will better support targeted communications and outreach efforts to build consumer confidence and enable pro-poor technology access. Informed political will is also essential for building local, regional, and global policy platforms in support of safe and timely access to these technologies in emerging economies.

* **Strengthen communications and public acceptance of modern biotechnology innovations.** Early and enhanced communication efforts to inform decision-makers and the public are needed in order to develop a climate of transparency and trust about the safety and socioeconomic benefits of genome editing applications. This will be critical for policy development and public/market acceptance (Gao 2018). Similarly, discussions on the costs of regulatory delays and the results of losing access to important food security, productivity, and environmental solutions must be part of the policy and public dialogues.

* **Close digital infrastructure gaps in rural areas.** Although 50% of the global population has Internet connectivity, significant digital divides exist between rural and urban areas. Only 6% of rural households in Africa have Internet access, compared with 28% in urban areas (ITU 2020). Data costs remain prohibitive, and technology ownership and access are gender-divided (GSMA 2020). Crop-lands with severe yield gaps, climate-stressed locations, and food-insecure populations have relatively poorer service coverage (Mehrabi et al. 2021). Enabling policies and investments targeting rural households are urgently needed. Connecting all of Africa is estimated to cost $100 billion and would only be feasible with strong private sector involvement (Broadband Commission 2019). Slow progress on electrification in LMICs further limits the affordability and coverage of digital technologies. The number of people without access to electricity in sub-Saharan Africa likely increased in 2020 due to the COVID-19-related economic slowdown (IEA 2020). Research is needed to develop business cases for simultaneous investment in digital infrastructure and electrification and to provide evidence of their synergistic impact for creating value and achieving the SDGs (GeSI 2019).
* Develop sustainable business models for digital service providers across food systems. Most digital service providers lack viable business models and revenues. In sub-Saharan Africa, only 26% of agricultural information service providers generate enough revenue to break even (CTA 2019). Achieving profitability, interoperability and scale is essential to reaching a sustainable critical mass. This would facilitate the use of financially viable digital technologies across value chains, thus increasing the adoption of various innovations, including new bio-innovations.

Additionally, as digital information comes to play an increasingly vital role in LMICs, clear policies and secure infrastructure are needed to protect the privacy of farmers and value chain actors while ensuring transparency and inclusivity. Strengthening technology capacity and digital literacy and skills (OECD 2019) will further accelerate the prospects for the democratization of digital technologies as part of game-changing solutions to end hunger.

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# Leveraging Data, Models & Farming Innovation to Prevent, Prepare for & Manage Pest Incursions: Delivering a Pest Risk Service for Low-Income Countries

Bryony Taylor, Henri Edouard Zefack Tonnang, Tim Beale, William Holland, MaryLucy Oronje, Elfatih Mohamed Abdel-Rahman, David Onyango, Cambria Finegold, Jessica Zhu, Stefania Pozzi, and Sean T. Murphy

## 1 Introduction

Globally, pests (invertebrates, vertebrates, pathogens, weeds) remain a major barrier to crop production, with annual losses estimated at between 20–40% (FAO, 2019). The impact of pests is particularly acute in many low-income countries, as agriculture is the mainstay of the majority of the people and also of the national economies (Perrings, 2007; Pratt et al. 2018; Wiggins et al. 2010). Additionally, climate change is predicted to increase the likelihood, frequency, and impact of pests in the future, resulting in increased crop losses, thus causing damage to the economy of low-income countries. For instance, Deutsch et al. (2018) predicted that global yield losses of major grains will increase by 10–25% per degree of global mean surface warming. The vulnerabilities of these countries are further exacerbated because of the small size of farms, which often witness outbreaks of transboundary

<footnote>B. Taylor (✉) · T. Beale · W. Holland · D. Onyango · C. Finegold
Centre for Agriculture and Bioscience International (CABI), Wallingford, UK
e-mail: b.taylor@cabi.org</footnote>

<footnote>H. E. Z. Tonnang · E. M. Abdel-Rahman
Modelling and Geo-Information Unit, International Centre of Insect Physiology and Ecology
(icipe), Nairobi, Kenya</footnote>

<footnote>M. Oronje
Centre for Agriculture and Bioscience International (CABI), Nairobi, Kenya</footnote>

<footnote>J. Zhu · S. Pozzi
Precision Development, Nairobi, Kenya</footnote>

<footnote>S. T. Murphy
Centre for Agriculture and Bioscience International (CABI), Egham, UK</footnote>
and/or new invasive pests (Early et al. 2016) and multiple indigenous pests (Constantine et al. 2021).

A number of factors, such as weak phytosanitary systems and inadequate human, financial and infrastructure capacity, are exacerbating the problem caused by these pests. There are weak linkages between research and national systems, resulting in gaps in effectively translating research into policy for their management. Significant progress has been made in the last decade in providing means for access to important knowledge about the identification of important pest groups such as arthropods, plant pathogens and weeds and their controls, both at the national and smallholder farmer levels (e.g., the global Plantwise program (www.plantwise.org) and PlantVillage (https://plantvillage.psu.edu/)), but information about pests is generally not accessed by users until a pest has reached a damaging stage; for example, in the case of farmers, this is when pest symptoms become most apparent. Thus, crop yield losses remain high (Pratt et al. 2017). Additionally, existing knowledge on how to manage pest and disease incursions has also become more difficult to apply, given the changing backdrop of weather patterns and the effect this has on the phenology of pest and disease outbreaks (Castex et al. 2018; Chidawanyika 2019) or the range expansion of invasive alien species (Kalnicky et al. 2019). In all, pests pose a major barrier to these countries' ability to meet the aims of the UN Sustainable Development Goals (SDGs), particularly SDG2, “End hunger, achieve food security and improved nutrition and promote sustainable agriculture,” but all the SDGs depend to some extent on the delivery of improved food systems. However, solutions, in the form of pest risk alert systems, do exist that address this barrier, and major advances in technology are now providing opportunities to apply these in low-income countries.

It is well established in integrated pest management (IPM) that ‘prevention is far more effective than cure’ (Barzman et al. 2015; Pretty and Bharucha 2015), and this critical tenet of IPM is key to reducing losses from pests and improving crop yields. Although preventative measures emphasize aspects such as the use of healthy seed or maintaining healthy soil, etc., the colonization by multiple indigenous pests or even the invasion of new pests in smallholder farms within a cropping season is inevitable in most regions. Hence, the provision of timely pest risk prediction information through risk-mapping or early warning systems is of paramount importance. Active communication of real-time information enables the intelligent mobilization of resources by national governments and other actors in the food value chains and/or early action by farmers to prevent pest populations from reaching economically damaging levels.

The development of national pest risk assessment and early warning systems can be complex, though. It requires the combining of expertise of different actors, well beyond those in pest modeling and pest management alone (Magarey and Sutton 2007; FAO 2007). Many advances have been made in pest modeling, and several types of models are now available for pest risk-mapping and early warning (Orlandini et al. 2017; Tonnang et al. 2017). However, equally important is the
availability of and access to suitable input data sources (e.g., pest data, weather data) to build or drive such systems, a deep understanding of farmer decision-making, and efficient communication means to deliver risk information to end users; for the last, in the case of farmers, this involves large numbers of people spread over vast areas. As a result, pest risk systems have mostly been developed in high income countries and only applied in low-income countries for a handful of significant pests (e.g., transboundary pests in Africa, see Box 1) and for import and export market access, but this situation is now changing. Recent innovations and advances in data availability (e.g., earth observation (EO) data, meteorological data), data architectures, data management workflows, computing power and communications technology has allowed for increasingly sophisticated risk assessment and decision support systems to be developed and extended to end users. In particular, there has been a developing interest in the use of weather and environmental data derived from EO sources, as such data are available for large areas (Marques da Silva et al. 2015). EO data have already proved to be useful in broad scale alert systems such as Global Forest Watch (GFW), the Famine Early Warning Systems Network (FEWS NET) and the Group on Earth Observations Global Agricultural Monitoring Initiative (GEOGLAM).

These advances in data availability and data management may now be combined with advances made in the field of extension and have the opportunity to make significant improvements in the field of pest prediction and subsequent extension of messages. Increasing access to mobile phone technology (World Bank 2019), along with the emergence of ICT-based advisory extension services, has allowed the extension sector to disseminate advice through multiple complementary communication channels, such as Short Message Services (SMS) and Unstructured Supplementary Service Data (USDD), on broader scales than previously possible (Thakur et al. 2016; Tambo et al. 2019).

Here, we discuss how these advances, in terms of data availability, management and modeling and communication technology, have provided new and novel solutions for the development of agricultural pest and disease early warning and risk-mapping systems in low-income countries. In particular, we explore how this provides opportunities to improve food systems and identify key areas for the UNFSS that will help guide governments in engaging with these developments.

## 2 Technology Developments and Their Application to Pest Risk

Several pest risk prediction systems are now in place or in development for low-income countries that forewarn of within season pest and disease incursions. These systems provide alerts about near-future potential geographic hotspots of transboundary pests or build-up of local pests that can be used at any scale (national, regional and local) for warning of potential pest outbreaks.
The development of these systems with a wide outreach has been possible thanks to the onset of increasingly accessible high-quality data with high spatial resolution derived from EO and meteorological sources used to drive the models, and the collation and generation of field and laboratory data to build, train and test the models.

## 2.1 Access to Datasets and Data Management

Through numerous projects, an immense number of datasets on occurrence, abundance, and prevalence of pests has been collected across many countries. However, these data remain scattered, are not widely accessed and used, and no mechanisms exist for bringing these datasets together, enabling sharing for multiple uses. Data are heterogeneous, owing to the diversity of their sources, differences in objectives for collection, and multiple storage and retrieval formats. However, recently, with the advancement in data collection and collation instruments like crowdsourcing, EO and geospatial tools, and cross-cutting analytics like artificial intelligence (AI) and the internet of things (IoT), the development of cloud-based platforms (e.g., ‘data hubs’) and mobile apps for real-time pest detection and risk profiling is highly possible. This enables the integration of data on historical and ongoing collections of pests and associated natural enemies from disparate sources as its centerpiece and may act as repositories that can be utilized to build and validate pest risk prediction systems.

With the availability of such diverse data sources, several initiatives have been underway to combine and utilize these data for the development of pest risk or other applications. For example, *icipe* through the data management, modeling, and geo-information (DMMG) unit is establishing a state-of-art data management workflow (DMWf) and advancing the use of ‘big data’ and cloud-based cross-cutting processing technologies that allow for harmonized storage and analysis of petabytes of various data types. This includes observational, experimental, simulation and derived datasets. The observational data are commonly collected through open-ended survey, observation and the use of equipment and devices to monitor and record information. Experimental data are obtained through functional involvement by the data collector that creates and gauges the change to establish causal relationships. Simulation data are obtained through mimicking known processes and applying computer-based methods for reproduction, while derived data are the result of the application of formulae used to transform the information. The DMWf provides a collaborative framework with cooperation between data scientists and information communication technology (ICT) experts.

With relatively more complex datasets, the opportunity for more sophisticated data handling methods has emerged. The AI allows for the exploration and utilization of large datasets and predictors and the expansion of assessments beyond binary outcomes, and considers the costs of different types of forecasting errors to generate improved and accurate knowledge for decision-making with feedback and
accountability in the context of IPM. Approaches such as machine learning (ML) and deep learning (DL) enable the characterization, discrimination, classification, prediction, forecast and utilization of existing knowledge in pest management for appropriate interventions.

## 2.2 Improved Access to Earth Observation and Meteorological Data

EO data are complex and require specialized human and technical capacity to process and manipulate the source data into compatible formats for analysis, which can often be lacking in developing countries and organizations. Space agencies are leaders in the use of EO data and are increasingly driving initiatives to make data more widely accessible and standardized to require less processing (O'Connor et al. 2020). One such initiative is the Group on Earth Observations (GEO), an intergovernmental partnership developed to promote accessibility and the subsequent use of EO. Key goals of GEO are to promote the use of open access and sustainable data sharing to support research, to facilitate improved decision-making, and therefore to benefit agricultural stakeholders.

Increased collaboration between EO and biological pest risk modeling experts and cutting-edge actors in extension of information have allowed these data sources to be utilized at a broad spatial scale to benefit those in receipt of early warning information. Data derived from EO sources can provide a consistent stream of measurements at regular time intervals with global coverage. These data can include various vegetation indices, which may be related to plant biomass or vigor (i.e., Normalized Difference Vegetation Index: NDVI), or used within reanalysis datasets to give a broad range of atmospheric, land and oceanic climate variables (i.e., ERA5 ECMWF dataset https://www.ecmwf.int/en/forecasts/datasets/reanalysis-datasets/era5). The quality, accuracy and availability of these data are increasing with each new space program (ESA 2020).

Well-established vegetation proxies, such as the NDVI, have been used effectively by the FAO since 2010 to measure the amount of 'green area' so as to monitor potential locust habitat recession and growth (see Box 1). These data have helped direct local teams on the ground to survey localities at higher risk of locust population build-up, and thus help direct monitoring and control resources (Renier et al. 2015). Recently, data from the European Space Agency (ESA) have been used to classify different tree species and crop types (Persson et al. 2018; Van Tricht et al. 2018), and now such data are being used to monitor agricultural weed problems such as Striga or 'witchweed' in Kenya (Mudereri et al. 2020) and *Parthenium hysterophorus* or 'famine weed' in Africa and Asia. These weeds can be successfully mapped using EO technology (Kganyago et al. 2017; CABI 2021) and species-level mapping solutions can offer great benefits to policymakers, who, with knowledge of
a weed’s distribution at a national scale, can implement suitable management programs.

High-quality data feeds of meteorological observations are essential, as broad-scale modeling approaches such as those used in pest risk prediction systems rely on an accurate estimation of localized conditions like temperature, humidity and rainfall (Magarey et al. 2005). Mechanistic or deductive models use detailed knowledge of the pest/disease biology to predict the response of the organism to a specific climatic driver (Venette 2010; Donatelli et al. 2017), therefore access to accurate, high spatial and temporal resolution datasets is essential for the correct estimation of insect and disease outbreaks. In the recent past, weather data feeds for early warning systems have used observations from meteorological stations set up as either regional networks or farmer-owned stations (Gleason et al. 2008; Magarey et al. 2001; Cressman 2016). However, networks require funds for their upkeep and coverage can be either geographically unrepresentative of the needs of a study or altogether limited (Colston et al. 2018). Climate data products derived from EO sources and reanalysis datasets have the potential to overcome these issues by providing complete coverage at good spatial and temporal resolutions and can offer a wider range of variables that may be applicable to modeling needs (Colston et al. 2018). Improved access to sophisticated weather models, such as the Unified Model (a numerical weather prediction model) available from the UK Met office, have also contributed to the development of disease early warning systems. Recent advances in the availability and access to these data have advanced the capabilities of models to deliver near real-time information. This increasing amount and accessibility of data from varied sources offers great opportunities to inform agricultural stakeholders so that they can make better decisions when it comes to plant health challenges, and thus move towards reducing crop losses as outlined in SDG2. Recent projects such as the PRISE (Pest Risk Information Service) project funded by the UK Space Agency (UKSA), and a near real-time early warning system to predict future potential hotspots of two wheat diseases in Ethiopia (Allen-Sader et al. 2019), have utilized access to these improved data sources for the purpose of pest and disease early warning systems. Both systems have extended messages to relevant stakeholders (governments, farmers, extension workers) in order to inform better management decisions with the ultimate aim of reducing crop losses.

## 2.3 Validation of EO Data and Models

Pest and disease risk prediction models driven using EO data inputs require field data for testing and validating species' presence, incidence and development. Historically, data collection in pest early warning systems has been limited by ground surveys, which may fail as a result of political unrest, border disputes, and inaccessible terrain, or can be limited by funds to generate these data. However, although detailed controlled studies remain vital for testing EO and pest models, there are now opportunities to collect supporting data from a much larger source. Increase in access
to digital communication technology (GSMA 2020) enables data to be collected directly from farmers and to enrich early warning systems. This citizen science approach is adapting to new technologies that smartphones provide (GPS, digital cameras, internet connectivity). Many efforts are also ongoing to build AI-based tools (applications and sensors) for pest and disease detection and identification through image processing (www.plantvillage.psu.edu; https://www.inaturalist.org/home), which may be used for in-field diagnostics of pests and diseases or to assess local pest/disease pressure. The collation of accurate, or, in the term of iNaturalist, “research grade” datasets (Ueda 2021) relating to pest presence may contribute to the building, calibration and validation of early warning models. There is a growing societal acceptance of mass participation projects, and advances in statistical approaches allow these data to be analyzed in a less structured way (Pocock et al. 2017). In order to be sustainable, these systems need to consider the incentives and motivations for users to contribute data. This surveillance method contributes vital observations in support of national and international programs, detecting pest incidence outside of formal research studies, extension services, border control checks and the work of plant protection organizations (Brown et al. 2020).

**Box 1: Rolling Out a Cost-Effective Surveillance and Early Warning System to Manage the Acute Desert Locust Crisis**

The desert locust, *Schistocerca gregaria* (Orthoptera:Acrididae) is an eruptive, transboundary pest, which affects Africa and parts of Asia. Under certain conditions, the locust forms large swarms, which affect large geographies and severely impact food production. Given the relationship between local environmental conditions, abundance of vegetation and locust biology, it is possible to use state-of-the-art approaches to collect data on locust presence, monitor movement, model the potential spatial extent of the locusts and assess crop damage to produce a dynamic and reactive response to locust outbreaks. In addition, schemes such as the FAO Desert Locust Information Service (DLIS) are able to forewarn of potential conditions, which may lead to the formation of swarms, thus preventing future swarms. Below are the ways in which technology and data should be utilized in frontline countries in response to the *S. gregaria* outbreak 2019–2021.

<table><thead><tr><td>Activity</td><td>Example</td></tr></thead><tbody><tr><td>Monitoring presence of populations</td><td>Innovative digital tools like smart phone apps (e.g., e-locust3M), as means of crowdsourcing, for real-time desert locust data collections, tracking and monitoring the spread of the pest.<br>High-resolution remote sensing systems mounted on unmanned aerial vehicles (UAV), i.e., drones, for timely desert locust surveillance and monitoring in remote and/ or inaccessible areas.</td></tr></tbody></table>

(continued)
**Box 1 (continued)**

<table><thead><tr><td>Activity</td><td>Example</td></tr></thead><tbody><tr><td>Monitoring of habitats/ potential habitats</td><td>Use of newly-launched earth observation (EO) tools (e.g., satellite-based vegetation coverage, wind speed/ direction and soil moisture) of relatively better spatial and temporal resolutions to monitor desert locust habitats.</td></tr><tr><td>Monitoring of movement</td><td>Ground-based radar systems to track and monitor desert locust breeding sites and hoppers migrations.</td></tr><tr><td>Collation of data</td><td>Harmonize and standardize the existing national and centralized open-source desert locust data systems/platforms to receive and store 'big data' transmitted from crowdsourcing tools and drones.</td></tr><tr><td>Early warning</td><td>Develop desert locust early warning and early action platforms using combinations of above-mentioned tools, machine learning (ML) and artificial intelligence (AI) algorithms.</td></tr><tr><td>Future situations/scenarios</td><td>Assess vegetation and crop damage due to desert locust using long-term EO data, ML and AI algorithms. Use of historical long-term (e.g., 30 years) satellite-based climate data and AI algorithms to assess the impacts of climate change on desert locust occurrence and forecast future desert locust outbreaks weeks and months in advance to enhance targeted and effective interventions</td></tr></tbody></table>

**3 Potential for Improving Plant Health Systems and Livelihoods: The Requirement for Effective Extension**

The key aim of pest risk prediction systems should be to communicate risks and mitigation strategies to those who need the information most, with the aim of reducing potential losses, and allow time for sustainable interventions to be made. Such extension messaging should consider the technological capabilities of the end user. Rapid large-scale investment in telecommunication and the subsequent reduced cost of mobile phones and internet connectivity has resulted in the widespread accessibility of mobile phones across Africa and Asia, including their most rural areas (World Bank 2019), with an estimated 34% of the surveyed population owning a smartphone in Kenya, and 53% owning an older device without internet connectivity (Krell et al. 2020).

As a result of the increase in mobile phone ownership, ICT-based advisory extension services have evolved to use communication channels such as SMS and USDD. With the direct-to-farmer and local language adoption capabilities of SMS, it is considered the most impactful single communication method in terms of improving farmers' knowledge and practice changes in Sub-Saharan Africa (Silvestri et al. 2020). A recent example is an initiative set up in 2018 through collaboration between Kenya's Ministry of Agriculture, Livestock, Fisheries and Cooperatives (MoALFC) and Precision Agriculture and Development (PAD) to disseminate advisory
messages relating to the fall armyworm (Spodoptera frugiperda) (Bakirdjian 2020). The initiative has grown to provide actionable advice for ten crops, and has demonstrated broadscale uptake by reaching over half a million farmers, and, in an additional pilot study on the fall armyworm, in collaboration with PRISE, 59% of 6,000 farmers who received timely SMS pest alert warnings self-reported changing their management practices with positive outcomes (Mbugua et al. 2021). Similar programs across Africa and India showed that a 4% average yield gain has been associated with digital agriculture programs, demonstrating a positive impact on livelihoods (Fabregas et al. 2019). This can be achieved at significantly lower costs compared with traditional agricultural advisory services. Estimates show the cost per farmer reached by SMS services to be between 28 and 122 times cheaper per year compared to funding in-person farmer field days (Low and Thiele 2020; Quizon et al. 2001; Ricker-Gilbert et al. 2008). An integrated approach that includes in-person farmer visits, farmer field days and digital advisory services can offer more sustainable and effective extension.

# 4 Conclusions and Future Actions

The bringing together of state-of-the-art advances in data availability, resolution, management and architecture, along with new extension approaches that can deliver rapid and timely information, stands to make real changes in the way in which pest risk can be communicated to end users in a timely way. The resulting synergy in these individual improvements can be combined to result in real gains in terms of yield on the ground and make headway towards the sustainable development goals such as SDG2. To maintain the momentum of the synergy of these approaches, there are several aspects that could be considered in the near future.

The collation and curation of data from disparate sources is key to being able to drive the construction and validation of pest risk models and to exploit opportunities from the ‘big data’ and ML approaches. Data should be published openly (when possible) following FAIR (findability, accessibility, interoperability, and reusability) principles, so that data are findable, accessible, interoperable and reusable. Openly accessible data can be shared through common interactive web platforms such as the Global Biodiversity Information Facility (GBIF) or institutional repositories such as those hosted by CABI, FAO or IITA. This will bridge the data gap in national, regional and local surveillance and improve data systems, linkage and the sharing of pest data. Overall, the modeling platforms themselves can serve as means of communication and networking. It is important to ensure that these early warning and monitoring systems are truly sustainable (self-managing and self-funding) in the long-term, and public-private partnerships will be key in ensuring this. Moreover, projects should ensure that the data and related materials, both digital and non-digital, should be accompanied by proper metadata and documentation in a way that facilitates the verification, replication and, if possible, reuse and remixing of the data.

The exploitation and interpretation of ‘big data’ can be used to develop geospatial cloud-based tools and mobile apps that can be operationally utilized for ‘real-time’
insect and weed surveillance, monitoring and forecasting. To do this, a complete, accurate and reliable DMWf is required, with advanced skills in common data models (CDM), data warehouse and repository, modeling methods and analytics, including ML, AI, design thinking, system thinking, system dynamics and computer vision algorithms. This information can be used to better learn, adapt and transform risk into knowledge to change practice. For instance, applying AI on a CDM extract could uncover hidden patterns, unknown correlations, trends, preferences, and other information that can help stakeholders make better and more informed decisions for the target insect pests and weeds. The AI may be utilized for the optimization of spatial positioning of pest traps that auto-disseminate sustainable interventions such as biopesticides (Guimapi et al. 2019).

Global environmental monitoring platforms provide portals for policy and national and regional decision-makers to view datasets and reports, however, there is now an opportunity to bring early warning to the farmer level. Advances in digital technology have demonstrated great opportunities for disseminating data to local scales and communicating this information so as to aid decisions made in the field. To achieve greater impact, these large datasets must be turned into timely information that can support agricultural decision-making at a local scale, to avoid preventable losses. To be effective, pest early warning system outputs must reach the farmer in the form of actionable advice. In order to effectively manage pests and diseases, farmers need timely warnings on taking preventative actions, advice on when to prepare and stock plant protection products, and alerts on the optimum times to monitor their crops for particular problems in order to act. The combination of this improved extension with the availability of high-quality, high temporal and spatial resolution datasets that can drive models within pest risk prediction systems is opening up opportunities to extend the outputs of models to broader geographical audiences and reach those who need the information most. There is also an opportunity to combine early warning model outputs with models related to management practices. Research projects investigating the estimated time to kill of traditionally slower acting biopesticides, combined with information of pest phenology, can lead to optimization of the timing of application of more sustainable interventions such as entomopathogenic fungi (CABI 2021).

For smallholder farmers and rural communities, the uptake of new digital solutions can often be limited by access to smartphones and other mobile tools, technological literacy, and willingness to change farming practices, many of which can be linked to gender and wealth (World Bank 2019). As such, the diversity of target users needs to be incorporated into the development and rollout of new services, with users taking on different roles that may not require high-level digital literacy. Numerous studies have agreed with the statement that digital extension will not replace face-to-face and more traditional advisory practices, and therefore new services need to take a more user-centered approach to support smallholder decision-making (Steinke et al. 2020).

Looking to the future, for the successful uptake of pest risk prediction systems, there needs to be a sufficient level of multidisciplinary involvement across the plant health sector, from governments and policymakers to extension services and
smallholder farmers (Winarto 2018). The adoption of novel technologies into existing plant health services needs to be taken up at a national level, with the ability to be disaggregated across regional and local platforms. National-level uptake or endorsement of early warning pest services could potentially benefit existing pest monitoring and plant health systems, notably, in low-income countries, by supporting the sharing of knowledge across boundaries and improving decision-making, resulting in improved food security and farmer incomes (Rivera and Alex 2004; Chapman and Tripp 2003).

For the long-term sustainability of early warning systems, the technological infrastructure and capabilities that are available in western countries need to be made accessible to low-income countries. Capacity-building for key actors, organizations and services in the plant health system is an integral part of promoting the uptake and success of such innovations that incorporate EO data and the use of models. Sufficient training and support are required to promote the adoption of novel systems into national, regional and local early warning dissemination services.

If digital-based technologies of any theme are to create sustainable lasting impacts on farmers and crop health systems, policymakers need to shift to a more inclusive digital understanding and acceptance (Steinke et al. 2020). Governments, the private sector, development partners and donors can promote successful digital services through increased investment, rather than short-term projects, with more focus on capacity-building and user-centered design processes. For example, governments may seek to partner with private sector and development partners in the provision of digital services, especially when incentives align, including commercial terms, data privacy and ownership rights (Lutz et al. 2021). Innovation at any level will always require investment, but with an extensive portfolio of existing technologies and services in the agricultural advisory sector, it is apparent that novel applications must be applied under collaborative and cross-cutting processes.

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Kalpana Beesabathuni ID, Klaus Kraemer ID, Sufia Askari, Srijith Lingala ID, Madhavika Bajoria, Martin Bloem, Breda Gavin-Smith, Hamid Hamirani, Priyanka Kumari ID, Anne Milan, Puja Tshering, Kesso Gabrielle van Zutphen ID, and Kris Woltering

## 1 Introduction

Our food systems are under pressure and failing us. This failure includes the inability to (a) produce and deliver high-quality diets to meet nutritional needs, (b) produce equal and equitable benefits, and (c) mitigate negative consequences (Baker 2020).

The threats and consequences of such failing food systems are wide-ranging. Diets are a significant predictor for the nutritional status and overall health of vulnerable groups. In 2019, 21.3% (144 million) of children under five were estimated to be stunted, 6.9% (47 million) wasted, and 5.6% (38.3 million) overweight, while at least 340 million children suffer from micronutrient deficiencies (Advisory Board 2020). Although child stunting is declining, global hunger is on the rise again (Advisory Board 2020). Simultaneously, over one-third of the global adult population is overweight or obese. Furthermore, sub-optimal diets serve

K. Beesabathuni (✉) · S. Lingala · M. Bajoria · B. Gavin-Smith · P. Kumari · A. Milan

P. Tshering · K. G. van Zutphen · K. Woltering

Sight and Life Foundation, Sydney, Australia

e-mail: Kalpana.beesabathuni@sightandlife.org

K. Kraemer

Sight and Life Foundation, Sydney, Australia

The Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

S. Askari

Children's Investment Fund Foundation, London, UK

M. Bloem

The Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA

H. Hamirani

Food Systems for the Future Institute, Chicago, IL, USA
as a major risk factor for non-communicable diseases, driving up morbidity and mortality risks, especially in low- and middle-income countries (LMICs) (Afshin et al. 2017; Arneth et al. 2019).

Malnutrition results in an unacceptably high economic burden for individuals, communities and entire economies. Direct costs of poor nutrition relate, for instance, to the treatment of overweight-related conditions, underweight-related conditions, and diet-related non-communicable diseases. All of these contribute to significant and rapidly rising health care costs. In fact, government spending on healthcare increased by a factor of 2.5 in the last 20 years (Ball et al. 2018). Such dramatic trends are clearly unsustainable. Indirect costs are also generated in the form of preventable child deaths and impaired cognitive development.

Food systems are, however, driving additional economic losses due to supply chain inefficiencies. Approximately 14% of all food produced globally is lost, or significantly reduced in quality, before reaching the retail stage of the supply chain (Beesabathuni et al. 2018). Moreover, considering that food systems are the major driver of global greenhouse gas (GHG) emissions, contributing 21–37% of total emissions, there is an urgent need to explore opportunities and innovative approaches to accelerate sustainable transformation (Béné et al. 2019; Bora et al. 2020).

Although information on ‘how’ to transform food systems remains scarce, innovative approaches and opportunities exist. These include the innovative use of technology, the reallocation of government expenditure, and the promotion of more nutritious diets. However, scaling these innovations requires capital and a platform to connect stakeholders and facilitate the transfer of technology and know-how.

Food system innovation hubs provide an opportunity to address these challenges. They have the potential to stimulate investments in resilient and responsive food systems with the goal of alleviating malnutrition through corporate partnerships, impact investors and government collaboration. These hubs can encourage food companies to expand into LMICs, facilitate investments in local companies, and stimulate supply chain innovations.

This chapter aims to draw attention to the role that **food system innovation hubs** can play in creating healthy, resilient and inclusive communities in LMICs. First, eight different archetypes of food innovation hubs are described. Future opportunities for these hubs to deliver planet-friendly nutritious and safe foods are then explored. It is argued that the complexity of food systems calls for context-specific transformations, and that innovation hubs have a key role to play here. Three key actions are identified as essential for developing effective food system innovation hubs in LMICs: Inspire! Invest! And Innovate!

## 2 The Current Landscape

Thus far, most recommended changes in food systems have involved incremental adjustments to existing technologies. Examples include improving egg consumption through backyard farming(Busby and Macpherson 2020), improving yields through
new varieties and alternative farming practices (Crippa et al. 2021; Davies and Macpherson 2020; FAO, IFAD, UNICEF, WFP, WHO 2020; Farm Together 2021; Florida and Hathaway 2018; Foley et al. 2011), and reducing micronutrient deficiencies through biofortification (FAO 2019a). Evidence nevertheless suggests that, even with these changes, it will be challenging to nourish ourselves adequately while observing planetary boundaries (Crippa et al. 2021; FAO 2010, 2019b; Frank et al. 2017; Gao and Bryan 2017; World Health Organization 2019; Gursel 2014).

The future of food systems hinges on disruptive new solutions that can help us achieve our collective Sustainable Development Goals (SDGs). We define ‘innovation’ broadly to include new products, business models, policy practices, technologies, behavioral insights, or ways of delivering products and services that benefit the poor in LMICs — any solution that has the potential to address malnutrition more effectively than existing approaches. However, innovations at a systems level are not easy to implement. While solutions are in the pipeline, they vary in their degree of maturity and require patient capital allocation and robust implementation strategies. Moreover, far too many promising innovations fail to scale their impact due to a lack of ability to manage the lengthy and demanding processes they entail (Havlík et al. 2014).

Food system innovation hubs can provide transformative solutions to food systems by bringing the right innovations to market faster in a cost-effective manner. We mapped different types of innovation hubs based on their coverage, capacity and capabilities. In our mapping (Fig. 1), we identified eight archetypes. The archetype nomenclature is similar to what we see in other peripheral sectors, such as education, housing, water and sanitation (Herrero et al. 2020).

1. Science and technology parks are usually established by governments in transition economies characterized by market imperfections, limited access to knowl edge and finance, high transaction costs due to lack of infrastructure, and weak institutions (Ittersum et al. 2016). They are often seen as developing the innova tion ecosystem. Further, they subsidize research and development (R&D) costs for companies and eventually foster collaboration and capital between industry and universities (Katz and Wagner 2014). When there is a strong political will to nurture innovation and facilitate ease of doing business, they can attract interna tional investors.

2. Research centers combine infrastructure and talent to unlock the next big scien tific breakthrough and take it to market. An example is the International Crop Research Institute for the Semi-Arid Tropics (ICRISAT). ICRISAT adopts inte grated genetic and natural resource management as its research strategy, with the aim of combining tested methods of crop commodity research with well-established practices in research in natural resource management.

3. Advanced development spaces are typically asset-heavy institutions that support R&D, commercialization, technology applications, testing, product design and prototyping. With the rise in entrepreneurs in many cities in LMICs, we see an
<figure><img src="image_94.png" /><figcaption>**Fig. 1** Schematic representation of the eight archetypes of innovation hubs characterized by their physical infrastructure: asset-light to asset-heavy</figcaption></figure>

emergent variant of advanced development spaces that have less physical infra-
structure and provide informal, unscheduled activity with more open-source
knowledge. For example, Fabrication Labs is a small-scale workshop equipped
with an array of flexible computer-controlled tools.

Incubators and accelerators are the two most common archetypes found in both high-income countries (HICs) and LMICs.

4. Incubators are institutions that support entrepreneurs in developing their businesses, especially in the initial stages. An example of this is the *WeInnovation* Hub in Nigeria (Lane et al. 2019), which focuses on education, agriculture, healthcare and infrastructure. The *WeInnovation* Hub has supported more than 300 start-up teams and more than 6000 youth entrepreneurs.

5. Accelerators are programs and spaces that provide the environment, expertise, networks, and resources to take ideas to scale. They are probably the most common archetype. Here, we describe four noteworthy examples:
*Rockefeller's SME Accelerator:* The investment thesis of this accelerator covers three areas. Firstly, it brings together actors to finance small and medium enterprises (SMEs). Secondly, it facilitates stand-alone investments in making nutritious foods accessible and affordable. Thirdly, it functions as an accelerator for start-ups that have been in operation for a minimum of two years.

*World Economic Forum's Food Innovation Hubs:* The World Economic Forum (WEF) plans to launch four food innovation hubs to support food system transformation. These hubs will be locally driven and owned, both multi-stakeholder and inclusive, creating a community of practice to share learnings and build capacity (Lockyer et al. 2018).

*World Food Programme's (WFP) Innovation Accelerator:* Based in Munich, Germany, this accelerator provides WFP employees, entrepreneurs, and start-ups with funding, hands-on support, and access to WFP's global operations. In just five years, 80 projects worldwide have received support, with fourteen innovations scaling up to reach 3.7 million people (OECD 2021).

LAUNCH was constructed ten years ago in partnership with NASA, Nike, USAID, and the US State Department. The platform sources and accelerates solutions to the challenges faced by rice farmers and the institutions, governments, and companies surrounding them. LAUNCH fosters new models such as network-centered innovation and collaborative equilibrium (Results for Development 2021).

6. Innovation districts are “geographic areas where leading-edge anchor institutions and companies cluster and connect with start-ups, business incubators, and accelerators. They are also physically compact, transit-accessible, and technically wired, and offer mixed-use housing, office, and retail” (Ringel et al. 2020). Found primarily in HICs, the state of Michigan (USA) is a prominent example, in which a state-wide policy encouraged the sourcing of 20% of Michigan’s food from Michigan markets. This has stimulated the creation of 13 more food innovation districts throughout the state. Some examples of food design interventions are community gardens or fruit-bearing street trees. A well-planned innovation district can reduce transport and storage requirements and create an enabling environment for the demand and supply of safe and nutritious foods. One such example is *Sight and Life's* Nutrition Kiosk, which was conceived as a solution to the problem of delivering last-mile nutrition in the urban landscape of India. The Nutrition Kiosk uses a pushcart format that is compact and in line with the strong street-vending culture of India (Rockström et al. 2020).

7. Virtual hubs are digital platforms and communities that provide networking, training, and acceleration opportunities, transcending borders. They are constantly absorbing new information and capacities that can be accessed by other connected ‘users’ anywhere in the network. Virtual hubs consequently open up the possibility of leaner and more agile local ecosystems. A minor variant of virtual hubs is aggregation on a platform approach for advancing innovations in rural areas. Aggregation is a popular way to achieve the critical mass of consumers or producers needed for any innovation to succeed.
8. Nodes are central points in the ecosystem. Nodes typically have a regional presence, but aim for global collaboration and impact. One example is the Foodvalley in the Netherlands, which has built an active relationship strategy with regions and countries worldwide to collaborate and accelerate innovation in agri-food. The Foodvalley caters to the full range of businesses. Research programs are supported via research and academic partners.

## 3 The Future Opportunity for Food System Innovation Hubs and Their Impact on Society, Economy and the Environment

In our review, we find that innovation hubs are not a new phenomenon. Most are technology-focused. Some are yet to launch. A thorough assessment of their capacity to deliver planet-friendly, nutritious and safe foods will guide us to coordinate, collaborate and invest in building capacity in LMICs.

Food system innovation hubs are social, private or government-owned enterprises that support local entrepreneurs and practitioners in advancing productivity- and sustainability-enhancing innovations, accessing capital and knowledge through collaborations, training and building their technical and business capacity and creating an enabling ecosystem together with local government. They present a tremendous opportunity to reimagine our food systems by connecting various ecosystem actors to enable co-creation, develop linkages and alignment, and generate innovative and inclusive governance models that enable collaboration and unlock barriers to scale (Rosegrant et al. 2014). In doing so, the hubs aim to unlock investments and leverage innovations to create healthy, inclusive and resilient communities in LMICs (Fig. 2). Most of the local hubs are owned by actors within the country, while those with a multi-country reach or a global reach are often owned by more than one stakeholder. Furthermore, governments have a crucial role to play in creating an enabling environment for food system innovations.

### Economic Development

Innovation has profound effects on macro-economic environments. It accelerates economic growth and is the reason why some economies are more robust in the long term than others (Crippa et al. 2021). However, the capacity to innovate rests almost exclusively in HICs and with large companies endowed with capital, expertise, networks and resource-intensive R&D departments (Rubin et al. 2009; Searchinger et al. 2019). Shifting the locus of innovation from internal R&D teams to communities (Fig. 3) could facilitate the rapid transformation of food systems.

*Moving the locus of innovation:* Stimulating innovation calls for two knowledge-based activities: (i) generating a range of solutions to an innovation problem and (ii) selecting the appropriate solution(s) from the alternatives generated (Fig. 3). Innovation platforms can bring together communities of problem-solvers and
<figure><img src="image_95.png" /><figcaption>**Fig. 2** Food system innovation hubs stimulate economic growth, ensure health benefits for all, protect the environment, and create sustainable societies</figcaption></figure>

<figure><img src="image_96.png" /><figcaption>**Fig. 3** Engineering serendipity: the future of Innovation Platforms. (Sherrick 2020)</figcaption></figure>

expand the locus of innovation from internal to external. ‘Thought for Food’ and *Sight and Life’s* ‘Elevator Pitch Contest’ are creating such innovation platforms. Hubs can intensify such efforts.

*Purposive Financing:* Hubs must unlock innovative funding mechanisms in order to attract governments and investment funds. A few novel ones are described below.

*Governments:* Health spending is rapidly increasing, with 60% of the current budget coming from governments. In LMICs, this spending grew by a factor of 2.2 and
increased 0.6 percentage points as a share of GDP (Shukla et al. 2019). Such dramatic increases are clearly unsustainable without reforms (Sight and Life 2019). Interventions aimed at disease prevention and health improvement can cut healthcare costs dramatically while improving health outcomes. For example, healthy lifestyles in the USA, including healthy eating, could result in healthcare savings of 2.7 trillion USD per year, reducing healthcare expenditure from 20% to 7% of GDP (Springmann et al. 2018). This makes a compelling case for the US government, other nations and funding agencies to invest in innovative food solutions.

*Investment Funds:* As private sector investors and sovereign wealth funds look to create sustainable lending portfolios (Startup Scene 2021), financing healthy, resilient and carbon-neutral solutions is a compelling proposition. Moreover, creating asset classes to fund innovations in food systems can help governments to reduce spending on healthcare and help companies to adhere to their carbon commitments.

We present below three examples of investment-worthy cases:

* Vertical farming is a sustainable alternative that uses up to 90% less water and land, and 60% less fertilizer, than traditional agriculture (Swinburn et al. 2019). The farm can be located at the city's edge, reducing transportation costs and time from farm to fork, thus lowering food loss or waste. Vertical farming can also release arable land for the cultivation of cereals and legumes.

* Farmland investment: Compared to conventional asset classes, investing in farmland has generated excess returns (The Grocer 2021), is relatively less volatile (Union of Concerned Scientists 2021), is uncorrelated (United Nations Industrial Development Organization 2021), is resilient to economic cycles (OECD 2021), and represents a good hedge against inflation (van Huis and Oonincx 2017). This is likely to encourage more investment in farmland as a yielding asset and to provide fresh capital for nutritious foods.

* Insect farming is a promising and sustainable alternative to conventional protein sources. It is resource-light and planet-friendly and can recycle nutrients from food loss and waste at improved feed conversion efficiencies (Villa 2017; Wennovation Hub 2018).

Funding and investing in nutritious food is a necessity and no longer a privilege for the few. Developing nutritious foods will reduce health care expenses, provide a sustainable alternative to achieve carbon reduction goals, and provide an asset class that ticks all boxes for institutional investors while generating inclusive economic growth.

## Valuing Health

Increased availability and affordability of nutritious foods will not by itself generate change on the scale necessary to meet national and global commitments related to hunger and malnutrition. Moreover, the role of advertising in driving people towards unhealthy foods cannot be underestimated. Nudging consumers to value nutrition is therefore critical. Consumers in LMICs are ready to pay more for nutritious products
if they deem these to be valuable. Nutritious foods will need to be positioned as
foods that add value to the consumer's life. Creating such demand appears to depend
on both tangible and intangible factors. Tangible factors focus on the intervention or
product, for instance: (i) availability, affordability; (ii) nutrient content, energy
value, serving size; (iii) taste, appearance, aroma, mouthfeel, convenience. Intangi-
ble factors consider the consumer context: (i) consumer aspirations, anxieties,
expectations; (ii) culture, values, belief systems, social norms; (iii) knowledge,
perceptions, behaviors around health/nutrition. Social marketing should ensure that
the consumer is at the center of the campaign. Food system innovation hubs can
focus on amplifying the values and priorities of the communities they serve,
encouraging consumers to choose healthy, nutritious diets.

Planetary Well-Being

Global warming is a formidable challenge. The way we produce, process, and
package food contributes to more than one-third of global GHG emissions (Béné
et al. 2019). Innovations are needed to rapidly lower GHGs, such as unlocking
barriers to scaling the (bio)fortification of staple foods, reducing food loss and waste,
effecting better management of marine fisheries, aggregating smallholder livestock
farmers to improve productivity, and increasing supply chain efficiencies.

The effects of global warming are most keenly felt in LMICs. These regions have also seen less widespread fortification of their local food staples than HICs. (Bio) fortification could therefore be an effective intervention against both micronutrient deficiencies and the climate change shocks experienced by food systems. Closer to the consumer, solar-energy-based innovative techniques such as solar dryers or solar storage for perishables can preserve food quality and prevent waste (Union of Concerned Scientists 2021). These techniques can alleviate global warming, because solar energy generates up to 90% fewer GHG emissions than natural gas and coal (Willett et al. 2019).

Targeted investment and technology transfer from HICs to LMICs will be crucial in advancing and adapting product innovations such as new food enzymes and insect protein, business model innovations for solar technologies and improved livestock management. To that end, food system innovation hubs in Africa and Asia can accelerate this process. These hubs will share both capital goods and knowledge resources with partners in LMICs, allowing them to access innovations vital to (bio) fortifying local diets and strengthening fragile food systems.

Inclusive Societies

Innovation can help alleviate social exclusion and inequalities in the food system by providing more personal, predictive and preventive nutritious products and services that improve human health. Additionally, inclusive innovations help reduce inequalities by making existing goods and services cheaper and more accessible. A food system transformation would ensure social inclusion for all food system actors, especially women, smallholders and young people. The WEF describes three key actions: link smallholders and SMEs to finance and markets; empower women; and engage youths.
*Link smallholders & SMEs to finance and markets:* This involves elevating the position of smallholders and SMEs in value chains through access to financial services and market and asset information. We need to see more companies across many sectors developing new business models with the potential to help close the rural and agricultural finance gap affecting smallholder farmers and agri-SMEs.

*Empower women:* Women make up 43% (World Bank Group 2021) of the agricultural workforce in LMICs, yet less than 20% (World Economic Forum 2021) of the landowners are women. With more equitable agricultural policies towards women, more than 100—150 million (World Bank Group 2021) people could be lifted out of poverty.

For any innovation to truly have an impact on women's empowerment, it needs to have a gender-transformative approach from its very inception. This refers to an approach that explicitly engages women and men to examine, question, and change institutions and norms that reinforce gender inequalities and, through that process, to achieve both economic growth and gender equality (World Food Programme Innovation Accelerator 2020).

*Engage youths:* The average age of farmers exceeds 60 years in most geographies, and farming is unattractive to most young people (World Health Organization 2021). The younger generation has the potential to combine the introduction of new technologies with learning from traditional methods to solve the food system's biggest challenges. Many organizations, such as the CGIAR, also believe that innovation will help make agriculture more attractive to young people.

To spark social change, hubs can design food systems in a more deliberate manner, with innovations targeted at each of the levers of social change. This can be done through a combination of an inclusive design lens and purposive financing.

# 4 Concluding Remarks

Not only are food systems complex, each is also unique to the geography and culture it is supposed to nourish. Therefore, a one-size-fits-all solution does not exist, and the approaches used by HICs cannot be expected to work in the same way for LMICs. Our aspiration is that the transformation of underperforming food systems lies in innovation hubs.

As next steps, with country ownership, diverse actors in the food system will collaborate and connect with existing models in a few LMICs, such as India, Rwanda and Nigeria, and then build cohesive food system innovation hubs for scale and sustainability. Operating in a variety of different locations, these hubs will be able to mold themselves to the needs of their specific nations and communities by engaging directly with their people, culture, entrepreneurial talent, and
unique climate. This will be achieved by focusing on three key actions: Inspire! Invest! Innovate!

### Inspire!

Hubs can encourage outstanding food and technology companies to expand into LMICs, with the goal of growing market interest, aligning with a range of investors, and developing and testing new products.

### Invest!

Hubs can facilitate investment in local companies that have the potential to scale, as well as in technology transfer, nutrition, food safety, and consumer studies to prove market viability and identify latent demand for nutritious foods.

### Innovate!

Hubs stimulate innovation throughout the value chain in a manner tailored to LMIC markets and draw additional investment into scaling up and innovating new technologies. This will be especially impactful to the SMEs and start-ups that dominate food production in these markets today. These SMEs also face unique constraints compared to their developed-nation peers.

Food system innovation hubs are bold initiatives that will accelerate innovation, streamline processes, support nature-positive, biodiverse agriculture, build sustainable supply chains, and create a consumer pull for healthy foods to better nourish the nations and communities they serve.

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# A Whole Earth Approach to Nature-Positive Food: Biodiversity and Agriculture

Fabrice A. J. DeClerck, Izabella Koziell, Tim Benton, Lucas A. Garibaldi, Claire Kremen, Martine Maron, Cristina Rumbaitis Del Rio, Aman Sidhu, Jonathan Wirths, Michael Clark, Chris Dickens, Natalia Estrada Carmona, Alexander K. Fremier, Sarah K. Jones, Colin K. Khoury, Rattan Lal, Michael Obersteiner, Roseline Remans, Adrien Rusch, Lisa A. Schulte, Jeremy Simmonds, Lindsay C. Stringer, Christopher Weber, and Leigh Winowiecki

## What Evidence Is There?

Healthy diets require dietary diversity, which requires greater crop diversity and agricultural biodiversity supporting production. Enhancing production of more diverse foods can be a win-win solution for both improved nutrition and bio-diversity [High Agreement, Robust Evidence].

F. A. J. DeClerck (✉) · A. Sidhu · N. E. Carmona · S. K. Jones · C. K. Khoury · R. Remans
Alliance of Bioversity and CIAT, CGIAR, Montpellier, France
e-mail: f.declerck@cgiar.org

I. Koziell

The International Centre for Integrated Mountain Development (ICIMOD), Lalitpur, Nepal

T. Benton

Chatham House, London, UK

L. A. Garibaldi

Universidad Nacional de Rio Negro, Bariloche, Argentina

C. Kremen

University of British Columbia, Vancouver, BC, Canada

M. Maron

University of Queensland, Brisbane, QLD, Australia

C. R. Del Rio

Global Commission on Adaptation, World Resources Institute, Washington, DC, USA

J. Wirths

CGIAR Research Program on Water Land and Ecosystems, Colombo, Sri Lanka

M. Clark

Nuffield Department of Population Health and Department of Zoology, University of Oxford,
Oxford, UK
It is possible to produce healthy diets for 10 billion people and halt the loss of biodiversity, securing its contribution to climate regulation and other planetary boundaries, despite significant challenges and trade-offs in several regions of the world, especially in developing economies [High Agreement, Medium Evidence].

Agriculture currently occupies 40% of the global land surface. At least 10–20% of semi-natural habitat per km² is needed to ensure ecosystem functions, notably, pollination, biological pest control and climate regulation, and to prevent soil erosion, nutrient loss and water contamination. Today, between 18–33% of agricultural lands have insufficient biodiversity to provide those services, an unacceptable risk for food security.

Agriculture thus needs a multipronged approach. This requires a shift towards regenerative production systems that deliver more diversified diets, coupled with strict conservation of intact habitats. Diversification strategies within fields, between fields and across landscapes are often regenerative, synergistic and multipurpose, and can bolster ecosystem functions within resilient agricultural production systems. Regenerative agricultural practices can generate additional critical ecosystem services by maintaining biodiversity in agricultural lands. At scale, these practices offer the potential to sequester 4.3–6.9 Gt CO₂e year⁻¹ year [Medium Agreement, Medium Evidence], retain > 30% environmental flows in major water to

C. Dickens
International Water Management Institute, Colombo, Sri Lanka

A. K. Fremier
Washington State University, Pullman, WA, USA

R. Lal
Member of the Scientific Group of the UN Food Systems Summit 2021, Ohio State University, Columbus, OH, USA

M. Obersteiner
Environmental Change Institute, University of Oxford, Oxford, UK

A. Rusch
l'institut national de recherche pour l'agriculture (INRAE), Villenave d'Ornon, France

L. A. Schulte
Natural Resource Ecology and Management, Iowa State University, Ames, IA, USA

J. Simmonds
University of Queensland, Brisbane, QLD, Australia

L. C. Stringer
Department of Environment and Geography, University of York, York, UK

C. Weber
Global Climate and Energy, WWF, Washington, DC, USA

L. Winowiecki
World Agroforestry Center, CGIAR, Nairobi, Kenya
basins [High Agreement, Limited Evidence], create 12–17 M km² of habitat for biodiversity [High Agreement, High Evidence] and increase connectivity for biodiversity [High Agreement, Limited Evidence]. There is no evidence that diversified production systems compromise food security – many agricultural diversification practices provide multiple complementary benefits [High Agreement, High Evidence].

Halting the expansion of agriculture into intact nature is necessary to achieve zero net loss of biodiversity and secure the critical Earth system functions that nature provides. Ecosystems covering half of the global land surface are currently intact, although these are largely within desert, boreal and tundra biomes. Halting extinction loss will require the retention of most remaining intact ecosystems across ice-free areas. **Regulating regional water cycles and achieving the Paris Climate Agreement (including climate mitigation targets) while halting biodiversity loss requires retaining at least 50% intact nature [Medium Agreement, Robust Evidence].**

Global goals, whether the SDGs, the Paris Climate Agreement, or the Convention on Biological Diversity, have repeatedly emphasized the urgent and critical need to halt emissions and accelerate carbon sequestration opportunities. Investing in context-specific research and development (R&D) aligned with global goals while building local capabilities and capacities is critical. While global models remain helpful in setting pathways and understanding the urgency and ambition needed, they need to be complemented with demand-driven R&D for farmer and pastoralist communities that provides them with flexibility and adaptive capacity without compromising their livelihoods.

In light of the vulnerabilities to climate and environmental change in LMICs and increases in all forms of malnutrition, including rapid transitions to unhealthy diets, there is a need for a much greater investment in diversified farming systems that meet societal goals, with increased resilience to climate and environmental change. While society still hopes to achieve climate stability, the impacts of climate change and environmental degradation are manifesting and should be anticipated to persist and worsen for several decades. Farming systems must be designed to be resilient to anticipate change, while simultaneously contributing to building back better: sinking GHGs, producing foods that contribute to the dietary health of local and regional communities, and regenerating environmental goods. Diversified farming systems are a critical strategy for adapting to anticipated change and mitigating impacts while building back better. Investing in nature-positive or circular production systems, which can prevent waste and leakage while supporting reuse, regenerative agroecological systems, complex rotations and mixed farming are “no regrets” investment options.

Investment in food policy is also urgently needed. All too often, the onus of profitability is placed on farmers and farming systems to drive important improvements in efficiency, but at environmental, social and climate costs that are becoming increasingly evident. Investment in a better understanding of how food policy, markets and supply chains enable regenerative and diversified systems to be profitable is urgently needed. This includes greater research on and investment in market
systems and value chains, but also agricultural tools and technologies that reduce the drudgery of diversified production and increase labor efficiencies in particular.

In light of the vast environmental footprint of agriculture, the broader food system must be a key part of the solution to the intertwined challenges of biodiversity loss, climate change and human health. Siloed visions of agricultural systems being independent of the natural world and somehow exonerated from environmental responsibilities are no longer compatible with global goals on food and nutritional security, climate security, environmental security and livelihood security. **Thus, the first step is for policymakers to adopt a new conceptual framing that recognizes that all parts of food systems need to work together as a whole if they are to deliver diets that are high quality and sustainable. This demands thinking about 'food system productivity,' rather than agricultural productivity,⁵ and requires all sectors of government to break out of their own conceptual silos and institutional structures.**

In considering the relationship between agriculture and biodiversity, several key areas for investment emerge: (i) closing the gap between the current composition of crop production and consumption to supply healthy diets at the local, regional and global scales in line with SDG2 and SDG3; (ii) transitioning to managing agricultural systems as ecological systems (agroecosystems); (iii) greater inclusion and recognition of farmers as key actors, with women, youths and indigenous farmers bringing unique knowledge systems and capabilities to bear in food production.

Food security should not be prioritized above other critical goals: nutritional, climate, environmental and livelihood security. Treating these areas solely as inevitable trade-offs fails to recognize important areas of synergy. Making the transition to food production systems that actively take account of and are synergized with biodiversity goals will require significant transitions in the policy landscape. Agriculture needs to be more strongly integrated into global agreements and policies on environment and health. Given that almost 20% of the global dietary energy supply is derived from imported foodstuffs, trade policy also needs to take better account of its impact, creating greater space for diversification of commodities, supporting the conservation of intact ecosystems, and including a consideration of environmental goods and services.

Current agricultural investments and practices often overlook the important potential for increasing ecosystem services that agroecosystems can provide (Wood et al. 2018), with an estimated 7% of innovation spending explicitly targeting environmental outcomes (CoSAI 2021). Farmers and farming communities can produce public goods (e.g., climate mitigation, soil water-holding capacity, water quality improvement), but promoting these public good functions has been consistently underexplored and under-resourced, even though they are also necessary for creating sustainable and resilient production systems. Recognizing that farmers and farmlands can produce these benefits in addition to quality food presents an opportunity for revitalizing rural communities by repurposing public funds for public goods and services. Diversification strategies can be applied in a range of contexts and would benefit from investment in technologies, tools, markets and incentives
that increase and improve employment opportunities, reduce the drudgery of food production and provide greater autonomy to producers.

During the next decade, priority approaches to diversify production systems should target:

* Urgent investments in undervalued crops and cropping systems, notably, underproduced crops that underpin dietary health and indigenous cropping and knowledge systems;

* Greater investment in tools, technologies and enabling environments that amplify and/or complement biodiversity's contribution to agriculture, rather than seeking to replace it;

* Repurposing policies and public and private agriculture funds to support farmers producing public goods, including the production of healthy foods, carbon capture, clean water and habitat for biodiversity.

**A coordinated, transformational adjustment of policies, incentives, regulations and other public sector instruments is needed to make healthy and sustainable food affordable and available for all and enable farmers and farming communities to gain greater recognition, reward and payments for actions that produce healthy foods or environmental benefits.**

Achieving food, nutrition, climate and environmental goals can occur if a policy framework is developed that takes a whole system perspective. This means valuing not just the amount of production, but production of healthy foods with low or regenerative environmental impacts. **This perspective necessarily incorporates reducing food waste, encouraging good eating habits low on the food chain, and providing access to a diversity of nutritious foods for low-income communities globally [High Agreement, Robust Evidence].**

# 1 Introduction

It is widely recognized that a major transformation of food systems is urgently needed if we are to achieve food and nutrition security globally, while also meeting global climate, biodiversity and health targets. What foods people eat, how and where it is produced, as well as how much is wasted and lost, have a significant impact on human and planetary health, including 11 million premature deaths, over 30% of global greenhouse gas (GHG) emissions, 70% of freshwater use and 80% of land conversion driving biodiversity loss. Paradoxically, while agriculture is currently the largest single source of environmental degradation and biodiversity loss, it is also likely to be the biggest victim of this degradation – the conversion of natural ecosystems into croplands and pastures, coupled with the impacts of agricultural pollution, severely threaten vital ecosystem services that underpin agriculture itself (Rockström et al. 2020).
**Agroecology**, as an ecological science, focuses on the contribution of **biodiversity** to enhancing the generation of ecosystem services to and from agriculture with the aim of **regenerating** these services. Diversification, agro-ecological, or regenerative agricultural practices are overlapping and include a diversity of management options from fields to landscapes (Source: Report Authors).

FAO and the HLP Report #14 (FAO-HLPE 2019) on “Agroecological and other innovative approaches” suggests a concise set of 13 agroecological principles related to: recycling; reducing the use of inputs; soil health; animal health and welfare; biodiversity; synergy (managing interactions); economic diversification; co-creation of knowledge (embracing local knowledge and global science); social values and diets; fairness; connectivity; land and natural resource governance; and participation.

2021 signals a pivotal year for the agricultural community. Major events such as the United Nations Food Systems Summit (UNFSS), the UNFCCC COP26, the UNCBD COP15, and the launch of the UN Decade of Ecosystem Restoration offer a real chance to make a step change towards the necessary transformation of our food systems – so they can become more sustainable and equitable and deliver affordable, healthy and nutritious food for all. Ensuring that there is a clear pathway for addressing biodiversity in all this, as well as highlighting its inextricable links to agriculture, is essential, given growing evidence that food system interventions have the potential to become the single largest solution space for both human and planetary health (Rockström et al. 2020).

## 1.1 Biodiversity Is Inextricably Linked to Food and Agriculture

Covering approximately 40% of the global land surface, agricultural ecosystems (including rangelands) comprise the world's largest terrestrial ecosystem, albeit a highly modified and heterogenous one. Biodiversity in agricultural ecosystems, as in natural ecosystems, is highly threatened, and this has very real consequences for the resilience and sustainability of both the production of food and environmental goods and services generated on agricultural lands and in water. The reduction of biodiversity in agriculture diminishes the ecosystem functions that contribute to local, regional and, when scaled, global processes. To ensure environmental and climate security by 2030, a transition is necessary toward treating agricultural lands as ecosystems, or as 'agroecosystems,' and greater investment in research, practices, technologies and incentives that reward the efforts of farmers just as much for the environmental services they produce as for the foods they produce.
Which and how much of the diversity of available foods we eat, and in what quantities, plays a key role in human health. Yet today, nearly half of the world's population struggles to access or afford either enough food or food that is healthy. Global progress against SDG2 - Zero Hunger - has stalled over the last few years, with current estimates showing that nearly 9 percent (690 million) of the world's population go hungry - up by 10 million people in 1 year and by nearly 60 million in 5 years (FAO I, UNICEF, WFP, and WHO 2020). Global food supply also falls alarmingly short of providing a low health-risk diet: nearly 2 billion struggle with hunger and malnutrition; another 2 billion struggle with diseases related to overconsumption (Global Panel on Agriculture and Food Systems for Nutrition 2020).

Producing healthy diets sustainably is dependent on biodiversity. Decades of research demonstrate that 'sharing space' for biodiversity on agricultural lands is logical and cost-effective for many reasons. The most notable example is our increasing dependence on pollinators to produce the foods that underpin healthy diets. Other examples of agriculture's dependence on biodiversity include: its roles in pest and disease regulation, in building resilience to shocks through crop and intra-species diversity, and in protecting the water cycle and maintaining soil health. However, investments in the kinds of agricultural practices that will build on and enhance these kinds of biodiversity benefits are severely lacking, including in modernizing and time-saving technologies that can increase biodiversity's contribution to production.

Tackling the global-scale challenges of stabilizing global climate, regulating regional water cycles and halting the extinction crisis is dependent on sparing sufficient intact nature from conversion across all biomes. Avoiding any further loss of intact nature is vital, particularly by halting ongoing conversion of land to agriculture, as called for by the Convention on Biological Diversity (CBD) Target 1, "ensuring that all land and sea areas globally are under integrated biodiversity-inclusive spatial planning addressing land- and sea-use change, retaining existing intact and wilderness areas." Achieving these goals requires active contributions from agriculture, starting with the recognition that environmental and climate security are equally non-transgressible goals, along with food and nutritional security. Increasing the productivity of agricultural lands, shifting to nature-positive practices, reducing food waste and loss, and fostering more sustainable diets are four ways in which food systems contribute to CBD conservation targets.

## 1.2 Reconfigure Biodiversity in Agriculture to Meet Food, Nutrition, Climate and Water Security Targets

Over the last decade, multiple global reviews, commissions and academic papers have argued for more sustainable and healthy food, farming and agriculture. Promoting biodiversity in diets, in farms and fields, and in intact nature makes essential contributions to these goals. International policy frameworks that support this
change include the Paris Agreement (UNFCCC), the United Nations Convention to Combat Desertification (UNCCD), the CBD and the SDGs.

In response, bold biodiversity targets to halt the loss of area and intactness of
nature and securing nature's contributions to people are being set by the CBD in
2021. Achieving these targets is a prerequisite for food, nutrition, climate and water
security, in addition to halting the ongoing extinction crisis. According to the Global
Biodiversity Outlook 5, we have failed to meet the 2020 Aichi Biodiversity targets
(Díaz et al. 2020; Diversity 2020). This failure points to the need for an urgent
rethink and transformation of the relationships among food, agriculture and biodi-
versity (Rockström et al. 2020; Leclère et al. 2020) if we are to succeed in reaching
the 2030 targets.

1.3 *Shifting from Crop Productivity to Systemic Productivity*

While food production has increased over recent decades, this trend masks an
underlying decline in ecosystem services that underpin production (Brauman et al.
2020), including pest and disease regulation, pollination and soil fertility. This rise in
productivity similarly masks an alarming decline in dietary health across countries
with different income statuses. The focus on crop productivity has fueled a false
dichotomy between conservation and production that may have critical conse-
quences for environmental and climate stability. This approach will ultimately also
have negative effects on future food production and distribution. Transforming the
objective outcomes of agriculture to encompass environmental and human health
objectives is a first, and necessary, step in realigning food across multiple global
goals. This requires refocusing food from yields per unit input to the food system's
overall productivity and efficiency, or the number of people that can be fed healthy
diets sustainably per unit input (Benton and Bailey 2019; Remans et al. 2014;
DeFries et al. 2015).

1.4 Critical Actions for Reconciling Agriculture
and Biodiversity

There is considerable evidence available about *what* needs to change in the food and agriculture system to enable nutritional, climate, environmental and livelihood security, and that innovative solutions can emerge when these goals are considered as equally non-transgressible. There is similarly substantial biophysical evidence that food and agriculture can provide healthy diets while contributing to environmental restoration and regeneration. **But there is still insufficient evidence indicating and understanding how to make the necessary social, political, economic and agronomic transformations urgently.** Much of the challenge lies in the siloed
nature of policy and innovation, as well as entrenched political economies of food. Recognizing the role that agriculture plays within the Earth system, as an ecosystem; considering the dietary health impacts of food; and recognizing and utilizing the dependencies of agriculture on biodiversity for agroecosystem services suggests the need for agricultural systems that are radically different from those we have today.

In this review, we have attempted to provide the best available evidence of agriculture's relationships with biodiversity. This spans many dimensions of agriculture and biodiversity, including:

* The diversity of food in our diets and calls for production systems to increase that diversity as a contribution to public health. Evidence indicates that there is ample scope to increase the diversity of foods produced in order to improve dietary health, with concomitant benefits for agricultural biodiversity.

* The dependency of food production for healthy diets on in-field and on-farm biodiversity, focusing on five core contributions: (i) genetic diversity of seeds and breeds, (ii) soil fertility, (iii) water, (iv) pollination, and (v) pest control and the risks of technologies and practices that replace, rather than amplify, these contributions.

* The role that in-field, on-farm, and around-farm biodiversity plays in securing non-food-related ecosystem services from agriculture, notably, climate mitigation, regulation of local and regional water fluxes and water quality.

* Halting the expansion of agriculture into intact nature to achieve zero net loss of biodiversity and secure the critical Earth system functions that nature provides.

We have not covered livelihood security here, although we find no evidence that better integration of biodiversity in agriculture reduces the opportunities to create more meaningful and remunerative livelihoods in agriculture. There is recent and growing evidence, however, that small and medium fields and farms are better able to integrate biodiversity without compromising yield (Ricciardi et al. 2021).

We present five critical challenges to agriculture in relation to biodiversity that, borrowing from the Science Based Targets Network (SBTN), suggests that this interaction can be conceived as an AR³T 'mitigation classification,' with targets aligned to the forthcoming CBD Kunming objectives (Fig. 1):

* **Avoid** continued land expansion into intact nature to secure nature's essential contribution to climate mitigation, aiming for 30% protected and > 50 intact.

* **Restore** intact nature where possible, prioritizing those areas that have been degraded, have high climate mitigation or have biodiversity conservation potential in line with no net loss as of 2020, restoration in 2030, and full recovery by 2050, contributing to biodiversity conservation, climate mitigation, and regional hydrological flow regulation.

* **Reduce** the impacts of agriculture on biodiversity, notably by halting the losses of nutrients, biocides, and other pollutants to air, soil and water.

* **Regenerate** the ecosystem services provided by biodiversity in all agricultural lands everywhere, retaining, at *minimum*, 10% habitat per km² within agriculture. We note that 20% is a much lower risk boundary.
<figure><img src="image_99.png" /><figcaption>**Fig. 1** Bold biodiversity targets are required to halt the loss of biodiversity and to secure bio-diversity's contributions to Earth system and ecosystem processes (Maron et al. 2018). Several studies (Willett et al. 2019; Maron et al. 2018; Newbold et al. 2016; Dinerstein et al. 2017; DeClerck et al. In Review), using distinct methodologies, find that approximately half the Earth's land surface remains intact, making 'half intact' the equivalent of a no-net-loss target (CBD Goal A, Target 1). We define intactness here as a measure of biodiversity status measured as the relative abundance of originally present species or level of human pressures. Combined actions to avoid loss, restore intact nature, reduce impacts of human activities on nature, regenerate ecosystem service production through nature-positive production, and transform agricultural policies and actions are needed to maintain a safe environmental space for humanity (Rockström et al. 2020, 2021). (Figure adapted from Maron et al. 2018)</figcaption></figure>

* Transform the food system by creating the policy instruments, demand and incentives for food production systems that leverage biodiversity's capacity to contribute to climate, environmental, food and nutritional securities (Willett et al. 2019; Rockström et al. 2009; Steffen et al. 2015).

## 2 Healthy Diets Require Dietary Diversity

### Take-Home Messages

* Lack of dietary diversity is a primary cause of diet-related disease and mortality.

* Shifting to increased consumption of fruits, nuts, vegetables and whole grains and healthy consumption of a diversity of meats could avert 11 million premature deaths per year.

* Shifting to healthy, plant-rich diets could avert per capita GHG emissions from crop and livestock production by 32% from 2009 to 2050, and lead to a 20% decrease in the land needed to meet consumption demand, in line with the CBD goal of no net loss of nature by 2050.