How do we go about increasing agricultural crop yields? As long as human populations are increasing, this is the primary challenge we face in agriculture. We must do this without threatening our ability to produce food in the future, and, if possible, without expansion of agricultural land (see graph below).
One idea promoted by ecologists, agroecologists, and some organic farming proponents is to use polycultures instead of monocultures. Although polycultures have their place in some systems, I believe that monocultures are better suited for annual cereal crop agriculture, the source of a majority of our food energy.
What is a monoculture? I ask because there is some confusion on this; even Wikipedia had it wrong for a while. Here is how monocultures and polycultures fit into diversity in both space and time:
A monoculture is a field planted to one species – there is no time variable. When the same species is planted year-after-year, it is not a monoculture, but a continuous monoculture, or monocropping. With corn, this would be “continuous corn.” A field that is planted to a monoculture of a different crop each year, such as wheat – corn – beans, is in a crop rotation if the sequence cycles (from beans back to wheat), or just a dynamic crop sequence if there is no determined cycle. A polyculture is two or more species intermingled in the same space. One way to view a crop rotation is as a polyculture over time.
The ecological theory behind polycultures is that increased biodiversity will increase productivity when compared to monocultures; the biodiversity-productivity relationship. The idea is that there will be complimentary, or synergistic effects, rather than competition between the species in the mixture, which will result in increased yields.
Several large, long-term experiments have been trying to determine the nature of the biodiversity-productivity relationship, including the often cited Cedar Creek plots in Minnesota (Tilman, 2014). Since the early 1990s, hundreds of such experiments have been carried out around the world. Recently, studies using meta-analysis have summarized the large amount of data generated from these experiments over the years to give us a better picture of the general conclusions.
Meta-analysis is a statistical method that allows researchers to combine and analyze data from many different studies. While the technique has been used in other fields, such as medicine, for 20 years or more, its use in agriculture is more recent (see overview here). The strength of meta-analysis is that it allows us to take a cumulative view of research and get a general sense of what it is telling us.
With regard to the biodiversity-productivity question, a meta-analysis by Cardinale et al. (2011) gives some insight into what we might expect from polycultures in agriculture. This study, an update of a 2006 effort, analyzed data of 192 peer-reviewed papers in its summary of 574 independent comparisons of species diversity to monocultures. The authors then set out to determine the answers to the critical questions on this issue.
The most important question posed in regards to agriculture, is “do diverse communities out perform their most efficient or productive species?” However, a little background is needed to understand the details behind this question.
When a polyculture yields more than a monoculture, it is called overyielding. This is not as simple as it sounds, and so various indices have been proposed to allow standard comparisons of polyculture and monoculture yields. Garnier et al. (1997), in their paper, A problem for biodiversity-productivity studies: how to compare the productivity of multispecific plant mixtures to that of monocultures?, found that the conclusions of these experiments depends on which index of overyielding is used.
The paper presents three indices used to determine overyielding. One, called the land equivalent ratio (LER), is calculated for a polyculture based on the relative yields of all the species present. A similar index compares the yield (biomass or harvested portion) of mixtures to the average of the monoculture yields of the species included in the polyculture. The final index compares the yield of the polyculture with the most productive monoculture. When any of these indices is greater than 1, overyielding is indicated. However, according to Garnier et al., this is deceiving. It turns out that the three indices are equal (for the same experiment) only when all the monoculture yields are equal. When monoculture yields differ, the first two indices are always greater than the third; that is, the first two may indicate overyielding for an experiment while the third does not; opposing conclusions can be drawn depending on which index is used. Which, then, is the best indicator of overyielding by a polyculture?
Garnier et al. argue, and I agree, that for a polyculture to be better than a monoculture, it must yield better than the best monoculture (Trenbath had the same conclusion in 1974), because otherwise a wise farmer wanting to grow the species involved would plant them as monocultures in separate fields and not a difficult-to-manage polyculture. So, for agriculture, only the last index, based on a comparison with the best monoculture is relevant. When overyielding is indicated by this index, it is termed transgressive overyielding, because a polyculture’s yield must transgress, or go beyond the yield of the best monoculture. (Perhaps using LER is more appropriate for answering some ecological questions, but since yield is essential in agriculture, transgressive overyielding is the relevant indicator of the value of polycultures.)
Back to Cardinale et al., what does their meta-analysis say about transgressive overyielding? They found the hypothesis that diverse polycultures exhibit transgressive overyielding is not supported, a conclusion in which they had high confidence. The same goes for the hypothesis that diverse polycultures capture more nutrients than their most efficient species. Agreeing with an earlier review of agronomic research by Trenbath (1974), their analysis found very little evidence to support transgressive overyielding by polycultures.
Why not? Some of the results can be explained by a “rule of logic” presented in the Garnier paper (from Crawley, 1983); if “one species is less productive than the other, then replacing a more productive individual by a less productive one is bound to reduce yield”. That is, unless there is some complimentary effect, some synergy between the species, replacing the better species with a lesser one just dilutes the productivity of the former, and reduces yield per area. Without complimentary effects, transgressive overyielding is unlikely.
There is one exception. Transgressive overyielding is often found when legume crops are mixed with non-legume crops, especially grass crops (corn, wheat, rice), in soils with low nitrogen levels. Here, the nitrogen from the legumes, and possibly other beneficial effects of the mix, often combine to produce transgressive overyielding. This is the best known example of the complimentary effects of polycultures. However, the effect disappears in soils with nitrogen levels sufficient for high crop yields.
What are the implications of all this for agriculture?
While polycultures may have a place in systems that more resemble natural ecosystems (e.g. grasslands and forests, where perennials dominate), we should recognize the benefits of monocultures in annual crop agriculture. The first, as has been confirmed, is higher yields – this is important for feeding people, but also for limiting the expansion of agriculture into presently wild lands. Of course there may be other benefits to biodiversity beside productivity, but those will have to wait for another post.
Second, we can rotate monoculture crops to create diversity in time, rather than in space as with polycultures. Crop rotation works for many different reasons, and should be used to provide many of the benefits that those promoting polycultures desire. Rotation of monocultures (including cover crops) disrupts pests, helps recycle nutrients, adds nitrogen (if legumes are used), shifts soil biology, and benefits yields of all the crops in the rotation. When rotation is not used, the resulting decrease in yield cannot be made up for by management, nor breeding, nor pesticides; not even the usually impressive effects of additional fertilizer can match a good crop rotation. Diverse rotations of monocultures are easier to manage than polycultures, in planting, nutrient management, weed management, and harvest, and also allow a large percentage of our population to pursue non-agricultural careers. Given the research results and the practical benefits, let us give up the polyculture strategy for annual cropping agriculture and instead, promote and improve the time-proven benefits of monoculture rotations.
Cardinale, B. J., Matulich, K. L., Hooper, D. U., Byrnes, J. E., Duffy, E., Gamfeldt, L., … Gonzalez, A. (2011). The functional role of producer diversity in ecosystems. American Journal of Botany, 98(3), 572–592.
Crawley M. J. (1983). – Herbivory. The Dynamics of Animal-Plant Interactions. Blackwell Scientific Publications, Oxford.
Garnier, E., Navas, M.-L., Austin, M. P., Lilley, J. M., & Gifford, R. M. (1997). A problem for biodiversity-productivity studies: how to compare the productivity of multispecific plant mixtures to that of monocultures? Acta Oecologica, 18(6), 657–670.
Tilman, D., Isbell, F., & Cowles, J. M. (2014). Biodiversity and Ecosystem Functioning. Annual Review of Ecology, Evolution, and Systematics, 45(1), 471.
Trenbath B R (1974). Biomass productivity of mixtures. Adv. Agron. 26, 177-210.