Abstract
The 1972 Meadows report, ‘the limits to growth’, predicted a global socio-economic tipping point during the twenty-first century. Now supported by 50 years of empirical evidence, this work is a tribute to systems thinking and an invitation to take the current environmental crisis for what it is: neither a transition nor a bifurcation, but an inversion. For instance, we used matter (e.g., fossil fuel) to save time; we will use time to preserve matter (e.g., bioeconomy). We were exploiting ecosystems to fuel production; production will feed ecosystems. We centralised to optimise; we will decentralise to support resilience. In plant science, this new context calls for new research on plant complexity (e.g., multiscale robustness and benefits of variability), also extending to new scientific approaches (e.g., participatory research, art and science). Taking this turn reverses many paradigms and becomes a new responsibility for plant scientists as the world becomes increasingly turbulent.
Keywords
circular bioeconomyresilience
Type Classics Information DOI: https://doi.org/10.1017/qpb.2023.2 [Opens in a new window] Creative Commons This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work. Copyright © The Author(s), 2023. Published by Cambridge University Press in association with The John Innes Centre
In 2022, Quantitative Plant Biology has showcased new questions in plant science, such as solid versus liquid signalling (van Schijndel et al., Reference van Schijndel, Snoek and ten Tusscher2022) or the new role of threonine in skotomorphogenesis (Tabeta et al., Reference Tabeta, Higashi, Okazaki, Toyooka, Wakazaki, Sato, Saito, Hirai and Ferjani2022). New quantitative tools were introduced, from non-coding long RNAs identification and classification (Nithin et al., Reference Nithin, Mukherjee, Basak and Bahadur2022) up to ecosystem natural capital accounting in local territories (Argüello et al., Reference Argüello, Weber and Negrutiu2022). Several articles took a step back on plant science, with new evolutionary views, for instance, on shoot apical meristems (Wu et al., Reference Wu, Yan, Liu, Zhang and Zhou2022), while others explored its future, notably with the rise of transdisciplinary approaches such as citizen science (Receveur et al., Reference Receveur, Poulet, Dalmas, Gonçalves and Vernay2022) and art & science (Bonneval, Reference Bonneval2022). Quantitative Plant Biology is also a forum for the plant science community to promote systems thinking and explore the complexity behind plant physiology and development (Autran et al., Reference Autran, Bassel, Chae, Ezer, Ferjani, Fleck, Hamant, Hartmann, Jiao and Johnston2021). This extends to the ‘how’ and ‘why’ we do research on plants.
In particular, with the rise of social networks and the focus on most recent publications, we, as a community, take the risk of falling into the trap of immediacy, the fuel that promotes (fast) overly reductionistic thinking instead of (slow) systems thinking. Quantitative Plant Biology is thus opening a new format to contribute to slow science: in the ‘classics’ format, you will not read the latest discovery, but instead dig into an article, published more than 20 years ago and which is still seminal in the field. Call it a tranquil resistance to fast fashion in science. I am happy to say that more than ten world leaders in plant science have already agreed to write such a piece in 2023.
Here, I take the liberty of opening this new format with a 50-year-old computational model and corresponding book, the limits to growth (Meadows et al., Reference Meadows, Randers, Meadows and Behrens1972). World3 is the first computational model of the world, and this already is enough to make it a landmark in the history of science. Many models have followed, the most recent one being Earth4all, with a deeper exploration of socio-economical inequalities (Dixson-Declève et al., Reference Dixson-Declève, Gaffney, Ghosh, Randers, Rockström and Stoknes2022). Why should such work be relevant to plant science? The key trigger of the 1972 study was the threat of a shortage of essential resources. In other words, by pointing out the unescapable limit on non-renewables, the model highlights the need to slow down our extraction to give us enough time to switch to circular bioeconomy. This is a call to reconsider our main, and almost only, renewable resource: plants.
The World3 model provides two main messages. A trivial one, first: on a finite planet, one cannot continue to live under the conceptual framework of infinite growth. The second conclusion is much more disturbing and is crystallised in a date: unless a true revolution happens, the business-as-usual model predicts a socio-economic tipping point before 2050 (Figure 1). This shocking news is why the book sold millions and was translated into 35 languages almost immediately. However, with the oil crisis in 1973, this conclusion was actively attacked, buried, and finely forgotten. Until the turn of the century where World3 was re-examined in the light of empirical data accumulated over 30 years, and the conclusion was unchanged: despite all the media attention on sustainable development, we are following World3 scenario #1 (standard run), that is, the business-as-usual route (Figure 1, Meadows et al., Reference Meadows, Randers and Meadows2009; Turner, Reference Turner2012). Further studies have confirmed this trend, warning about upcoming tipping points for the climate (Steffen et al., Reference Steffen, Rockström, Richardson, Lenton, Folke, Liverman, Summerhayes, Barnosky, Cornell and Crucifix2018) and for ecosystems (Barnosky et al., Reference Barnosky, Hadly, Bascompte, Berlow, Brown, Fortelius, Getz, Harte, Hastings and Marquet2012), further locking humanity on that trajectory. For intensive agriculture, this means that we would have around 20 harvests before the global food system faces at least one of its physical limits: water availability, soil sustainability, phosphate stock, extreme climate events, oil and energy supply.
Fig. 1. Lessons from the 1972 Meadows report for plant scientists: systems thinking for resilience. (a) Standard run from the 1972 report (dotted line), revisited with empirical data until 2000 (plain line), and predicting a socio-economic tipping point before 2050 (Adapted from Turner, Reference Turner2012). (b) New quantitative plant biology questions and framework in agroecology, building on complexity and fuelling resilience (adapted from FAO and HLPE, 2019; Nicholls & Altieri, Reference Nicholls and Altieri2016).
One could resist this conclusion arguing that we have made much progress in agronomical and economic productivity and that the ecological transition is in progress. The very fact that we are following the business-as-usual scenario means, to say the least, that this is denial: we have not really deviated from the 1972 basic prediction. In fact, such a disappointing outcome was also predicted in the Meadows report and should be revisited today, notably to question some of the proposed scientific solutions to the environmental crisis.
Should we extract more resources (e.g., rare metals through deep sea mining) to prolong our current socio-economic model, including intensive agriculture? According to World3 scenario #2 ‘unlimited resources’, this would only increase the production of pollution without affecting the existence of a tipping point before 2050. Thus, should we also promote cleaner technologies? Yes, of course, but let us not be naïve: this would only delay the tipping point by a few years or decades, because reduced pollution also promotes the exhaustion of arable land to support a growing population, as illustrated in World3 scenario #3 ‘unlimited resources with controlled pollutions’. Should we thus add increased agricultural productivity to face these challenges? As shown in World3 scenario #4 ‘unlimited resources with controlled pollutions and increased agricultural productivity’, this would promote global pollution (despite the existence of cleaner technologies), without affecting the trajectory. Now in the 2020s, we can experience the predicted turbulence of the business-as-usual scenario in our daily life: mega-fires, mega-flooding, heat waves and heat domes, and shortage in resources with the associated social and geopolitical unrest. What can plant science do about it?
In the worst-case scenario, plant scientists would ignore the Meadows scenarios and put forward reductionistic solutions overlooking known key parameters in the bigger picture. This includes believing that an increase in agricultural productivity is a satisfactory goal to preserve food availability and ecosystem services. As shown all over the world, Norman Borlaug’s land-sparing theory is not verified: higher intensification has not reduced the land surface area devoted to agriculture to preserve other ecosystems. This is due to at least two factors: a rebound effect (increased productivity generates new needs, leading to more resource consumption in the end (Hamant, Reference Hamant2020)) and desertification (because intensive agriculture provides short-term benefits but kills soils and ecosystems in the long term, at least in its current form with ploughing, fertilisers and pesticides). In fact, soil degradation is already perceived as a major threat to crop production in certain countries, like Kenya (Moore, Reference Moore2016). As noted by FAO, ‘past agricultural performance is not indicative of future returns’ (FAO, 2016). United Nations special rapporteur on the right to food Olivier de Shutter is blunter: ‘our food systems are making people sick’.
One key responsibility of plant scientists is to resist the attractive trajectory of efficiency in agriculture in an isolated framework. This means that we will have to set our research questions in the framework of slower and more complex route of resilience in agriculture, that is, agroecology (FAO and HLPE, 2019). Several scenarios show that such sustainable agriculture can feed the world (Couturier et al., Reference Couturier, Charru, Doublet and Pointereau2016; Pretty & Hine, Reference Pretty and Hine2001). This involves hardcore quantitative plant biology, extending the complexity to genetic diversity, genetic and environment interactions, and agronomical practices. What would such quantitative plant science look like in the future?
The revolution in plant science is not a cosmetic one. It is not a sustainable development add-on or even a transition. With systems thinking in mind, one can see the emergence of a true inversion, a third way, matching the socio-economic tipping point predicted by World3 (Hamant, Reference Hamant2022). Here are five axes where such inversion happens.
First, the drive for more efficiency will die out because of its counterproductivity. Instead, plant science will focus on socio-ecological resilience, that is, the ability to persist, to adapt and to transform in a fluctuating environment (Folke et al., Reference Folke, Carpenter, Walker, Scheffer, Chapin and Rockström2010; Hamant, Reference Hamant2022). This is a total revolution in plant science as the focus will shift away from yield increase and optimisation (only relevant to a stable, controlled, environment), to the mechanisms supporting robustness and adaptability (relevant to a fluctuating environment). For instance, this involves analysing how time can tune regulatory networks (Calderwood et al., Reference Calderwood, Hepworth, Woodhouse, Bilham, Jones, Tudor, Ali, Dean, Wells and Irwin2021), how incoherence generates stability (Creff et al., Reference Creff, Ali, Bied, Bayle, Ingram and Landrein2023; Joanito et al., Reference Joanito, Chu, Wu and Hsu2018), how local variability generates global reproducibility (Roeder, Reference Roeder2021) or how delays support adaptability (Vidal et al., Reference Vidal, Araus, Lu, Parry, Green, Coruzzi and Gutierrez2010).
Second, plant scientists will increasingly question and depart from a socio-economic context that fuels the exploitation of ecosystems to increase agricultural production. Beyond systems thinking, this will happen because arable lands and ecosystem services are the most precious parameters for our viability on Earth, and their value and protection will continue to rise. Plant scientists will instead ask how agronomical production can feed ecosystems. This notably involves understanding agroecological practices, from varietal mixtures increasing drought tolerance and pathogen resistance (Barot et al., Reference Barot, Allard, Cantarel, Enjalbert, Gauffreteau, Goldringer, Lata, Le Roux, Niboyet and Porcher2017), to permaculture maintaining soils alive, a basic research which is not incompatible with cutting-edge quantitative technologies, for example, on microbiome (Toju et al., Reference Toju, Peay, Yamamichi, Narisawa, Hiruma, Naito, Fukuda, Ushio, Nakaoka and Onoda2018).
Third, plant science projects will no longer take part of fragile global food systems made of only five main seed companies worldwide and producing carbon-heavy and unhealthy ultra-processed foods (whether plant- or animal-based). Instead, plant scientists will get closer to local farmers through citizen science, for example, with participatory plant breeding (Ceccarelli & Grando, Reference Ceccarelli and Grando2020), and design local and robust strategies to face a turbulent century. This involves basic research on the open book of heterogeneous situated knowledge.
Fourth, plant science will no longer support projects where non-renewable resources (e.g., oil or metals) are used to increase productivity (e.g., in precision agriculture); instead, plant scientists will explore ways in which time can be used to preserve resources (bioeconomy). This shift might even extend to plant-based materials to build next-generation digital hardware (e.g., Ghanem et al., Reference Ghanem, Khoryati, Behrou, Khanolkar, Raetz, Allein, Boechler and Dehoux2021). In other words, plant scientists will shift from a world of large extractions and poor interactions, to a world of few extraction and rich interactions. This involves systems biology, circular bioeconomy and the development of (slower) biobased material production, as well as science and society projects with local stakeholders (notably to assess and balance available resources and essential needs).
Last, plant science will no longer support competition as a fuel for discovery, simply because in a time of shortage of resources, competition is counterproductive! Instead, cooperation will increasingly become the norm, and a much richer way to produce knowledge. This shift is already happening with the rise of interdisciplinary plant science. Interestingly, plants show us the way: in forests, trees switch from competition to cooperation when resources become scarce (Choler et al., Reference Choler, Michalet and Callaway2001).
Needless to say, this global revolution in plant science must also be accompanied by a new ethics in science publishing and sharing. With a community-based editorial board, a not-for-profit publisher (Cambridge University Press) and partner scientific institution (John Innes Centre), and a fully open-access framework, Quantitative Plant Biology takes its part and invites everyone to contribute to an engaging and stimulating future plant science where basic research meets global challenges, notably through Meadows’s inspiration on systems thinking.
Conflicts of Interest
The author is also the editor-in-chief of Quantitative Plant Biology, which explains the editorial tone of this article.
References
Argüello, J., Weber, J.-L., & Negrutiu, I. (2022). Ecosystem natural capital accounting: The landscape approach at a territorial watershed scale. Quantitative Plant Biology, 3, e24.CrossRefGoogle Scholar
Autran, D., Bassel, G. W., Chae, E., Ezer, D., Ferjani, A., Fleck, C., Hamant, O., Hartmann, F. P., Jiao, Y., Johnston, I. G., et al. (2021). What is quantitative plant biology? Quantitative Plant Biology, 2, e10.CrossRefGoogle ScholarPubMed
Barnosky, A. D., Hadly, E. A., Bascompte, J., Berlow, E. L., Brown, J. H., Fortelius, M., Getz, W. M., Harte, J., Hastings, A., Marquet, P. A., et al. (2012). Approaching a state shift in Earth’s biosphere. Nature, 486, 52–58.CrossRefGoogle ScholarPubMed
Barot, S., Allard, V., Cantarel, A., Enjalbert, J., Gauffreteau, A., Goldringer, I., Lata, J.-C., Le Roux, X., Niboyet, A., & Porcher, E. (2017). Designing mixtures of varieties for multifunctional agriculture with the help of ecology. A review. Agronomy for Sustainable Development, 37, 13.CrossRefGoogle Scholar
Bonneval, K. (2022). Translators to weave with the non-humans. Quantitative Plant Biology, 3, e17.CrossRefGoogle ScholarPubMed
Calderwood, A., Hepworth, J., Woodhouse, S., Bilham, L., Jones, D. M., Tudor, E., Ali, M., Dean, C., Wells, R., Irwin, J. A., et al. (2021). Comparative transcriptomics reveals desynchronisation of gene expression during the floral transition between Arabidopsis and Brassica rapa cultivars. Quantitative Plant Biology, 2, e4.CrossRefGoogle ScholarPubMed
Ceccarelli, S., & Grando, S. (2020). Participatory plant breeding: Who did it, who does it and where? Experimental Agriculture, 56, 1–11.CrossRefGoogle Scholar
Choler, P., Michalet, R., & Callaway, R. M. (2001). Facilitation and competition on gradients in alpine plant communities. Ecology, 82, 3295–3308.CrossRefGoogle Scholar
Couturier, C., Charru, M., Doublet, S., & Pointereau, P. (2016). The Afterres 2050 scenario - 2016 version. Solagro association with support from ADEME, Fondation Charles Léopold Mayer pour la progrès de l’Homme, French regions Centre Val de Loire, Ile-de-France, Picardie, and Rhône Alpes. https://afterres2050.solagro.org/wp-content/uploads/2015/11/solagro_afterres2050_version2016.pdf Google Scholar
Creff, A., Ali, O., Bied, C., Bayle, V., Ingram, G., & Landrein, B. (2023). Evidence that endosperm turgor pressure both promotes and restricts seed growth and size. Nature Communications, 14, 67.CrossRefGoogle ScholarPubMed
Dixson-Declève, S., Gaffney, O., Ghosh, J., Randers, J., Rockström, J., & Stoknes, P. E. (2022). Earth for all: A survival guide for humanity: A report to the Club of Rome (2022), fifty years after the limits of growth (1972). New Society Publishers. ISBN-13 : 978-0865719866Google Scholar
FAO. (2016). Save and grow in practice maize rice wheat. FAO, https://www.fao.org/3/i5318e/i5318e.pdf Google Scholar
FAO and HLPE. (2019). Agroecological and other innovative approaches for sustainable agriculture and food systems that enhance food security and nutrition. HLPE https://www.fao.org/3/ca5602en/ca5602en.pdf Google Scholar
Folke, C., Carpenter, S. R., Walker, B., Scheffer, M., Chapin, T., & Rockström, J. (2010). Resilience thinking: Integrating resilience, adaptability and transformability. Ecology and Society, 15, 20.CrossRefGoogle Scholar
Ghanem, M. A., Khoryati, L., Behrou, R., Khanolkar, A., Raetz, S., Allein, F., Boechler, N., & Dehoux, T. (2021). Growing phenotype-controlled phononic materials from plant cells scaffolds. Applied Materials Today, 22, 100934.CrossRefGoogle Scholar
Hamant, O. (2020). Plant scientists can’t ignore Jevons paradox anymore. Nature Plants, 6, 720–722.CrossRefGoogle ScholarPubMed
Hamant, O. (2022). La troisième voie du vivant. Odile Jacob.Google Scholar
Joanito, I., Chu, J.-W., Wu, S.-H., & Hsu, C.-P. (2018). An incoherent feed-forward loop switches the Arabidopsis clock rapidly between two hysteretic states. Scientific Reports, 8, 13944.CrossRefGoogle ScholarPubMed
Meadows, D. H., Randers, J., & Meadows, D. L. (2009). The limits to growth: The 30-year update. Earthscan.Google Scholar
Meadows, D. H., Randers, J., Meadows, D. L., & Behrens, W. W. (1972). The limits to growth: A report for the Club of Rome’s project on the predicament of mankind. Universe Books.Google Scholar
Moore, H. (2016). Can agroecology feed the world and save the planet?. The Guardian.Google Scholar
Nicholls, C., & Altieri, M. (2016). Agroecology: Principles for the conversion and redesign of farming systems. Journal of Ecosystem and Ecography, 01(s5).Google Scholar
Nithin, C., Mukherjee, S., Basak, J., & Bahadur, R. P. (2022). NCodR: A multi-class support vector machine classification to distinguish non-coding RNAs in Viridiplantae. Quantitative Plant Biology, 3, e23.CrossRefGoogle ScholarPubMed
Pretty, J., & Hine, R. (2001). Reducing food poverty with sustainable agriculture: A summary of new evidence. Final Report from the “SAFE-World” project (University of Essex) commissioned by UK Department for International Development, Bread for the World, and Greenpeace (Germany). https://www.iatp.org/sites/default/files/Reducing_Food_Poverty_with_Sustainable_Agricul.pdfGoogle Scholar
Receveur, A., Poulet, L., Dalmas, B., Gonçalves, B., & Vernay, A. (2022). Citizen science: How to extend reciprocal benefits from the project community to the broader socio-ecological system. Quantitative Plant Biology, 3, e20.CrossRefGoogle Scholar
Roeder, A. H. K. (2021). Arabidopsis sepals: A model system for the emergent process of morphogenesis. Quantitative Plant Biology, 2, e14.CrossRefGoogle Scholar
Steffen, W., Rockström, J., Richardson, K., Lenton, T. M., Folke, C., Liverman, D., Summerhayes, C. P., Barnosky, A. D., Cornell, S. E., Crucifix, M., et al. (2018). Trajectories of the earth system in the Anthropocene. Proceedings of the National Academy of Sciences, 115, 8252–8259.CrossRefGoogle ScholarPubMed
Tabeta, H., Higashi, Y., Okazaki, Y., Toyooka, K., Wakazaki, M., Sato, M., Saito, K., Hirai, M. Y., & Ferjani, A. (2022). Skotomorphogenesis exploits threonine to promote hypocotyl elongation. Quantitative Plant Biology, 3, e26.CrossRefGoogle ScholarPubMed
Toju, H., Peay, K. G., Yamamichi, M., Narisawa, K., Hiruma, K., Naito, K., Fukuda, S., Ushio, M., Nakaoka, S., Onoda, Y., et al. (2018). Core microbiomes for sustainable agroecosystems. Nature Plants, 4, 247–257.CrossRefGoogle ScholarPubMed
Turner, G. M. (2012). On the cusp of global collapse? Updated comparison of the limits to growth with historical data. GAIA - Ecological Perspectives for Science and Society, 21, 116–124.CrossRefGoogle Scholar
van Schijndel, L., Snoek, B. L., & ten Tusscher, K. (2022). Embodiment in distributed information processing: ‘Solid’ plants versus ‘liquid’ ant colonies. Quantitative Plant Biology, 3, e27.CrossRefGoogle ScholarPubMed
Vidal, E. A., Araus, V., Lu, C., Parry, G., Green, P. J., Coruzzi, G. M., & Gutierrez, R. A. (2010). Nitrate-responsive miR393/AFB3 regulatory module controls root system architecture in Arabidopsis thaliana. Proceedings of the National Academy of Sciences, 107, 4477–4482.CrossRefGoogle ScholarPubMed
