Tequila, bats, and agave farmers: towards an understanding of the right incentives to protect genetic diversity

Genetic diversity in agricultural crops can act as a 'natural insurance' against, for example, pest infestations or changes in climate; it can also lead to agricultural improvements (Simpson 2005). Nonetheless, a focus on short-run productivity, a demand for product homogeneity, and other market considerations, have led to the genetic erosion of many crops (Esquinas-Alcázar 2005), resulting in an increased risk of exposure to pathogens (Vurro et al 2010), and fewer opportunities for crops to continuously adapt in response to changing climatic conditions (Dyer et al 2014). As the cases of cassava (Vurro et al 2010) and banana (Butler 2013) show, the commercial production of crops with low levels of genetic diversity is very susceptible to being severely affected by plant pathogens. Blue agave (Agave tequilana Weber blue variety)—used in Mexico to produce tequila—is not the exception. Commercial farming has resulted in the genetic erosion of blue agave (Gil Vega et al 2001, Vargas-Ponce et al 2009, Ruiz Mondragon et al 2022), whereas the low levels of diversity have increased its exposure to pests and diseases and have limited the possibilities for artificial selection of beneficial characteristics that can improve production under climate change problems (Solís-Aguilar et al 2001, Eguiarte and González 2007, Flores López et al 2016).

Tequila has a designation of origin by which it can only be produced with the blue agave grown in certain regions of Mexico. Most producers of blue agave follow a technique of asexual reproduction that has prevailed in the tequila industry for several decades (Trejo-Salazar et al 2016). Agave plants are prevented from flowering, otherwise, all the sugar will go to the nectar in the flowers, and the plant will no longer be useful for producing tequila. The reproduction of agave is then based on clonal sprouts from a small pool of plants that are removed and resown. Unsurprisingly, this intensive technique of reproduction has been detrimental to genetic diversity (Gil Vega et al 2001, Vargas-Ponce et al 2009, Ruiz Mondragon et al 2022). The commercial farming of blue agave has an additional unintended negative side effect: harming bat populations. Agave's sexual reproduction is carried out by several kinds of pollinators (Trejo-Salazar et al 2015), the bats of the genus Leptonycteris, commonly known as magueyero bats, are the main blue agave pollinators (López-Hoffman et al 2010). Other species of bats, like Choeronycteris mexicana, Glossophaga sp., and Anoura sp., are also important pollinators of agave plants. Without flowers from agave plants, pollinators bats lose a crucial food source.

In this study, we elicit farmer's willingness to participate in a hypothetical program that can improve genetic diversity and generate more foraging resources for bats. More specifically, we elicit agave producers' willingness to let some of their plants bloom in exchange of monetary and non-monetary benefits. The hypothetical program that we use in our experimental setting is based on the bat friendly program ⁵ , by which tequila (and mezcal) producers can receive a hologram to put in their bottles to signal they follow environmentally friendly practices. Producers need to show that they have left some of their plants bloom to be part of the program and receive the hologram. Although the program has not been in operation long enough to evaluate its actual effect on genetic diversity (Ruiz Mondragon et al 2022), it has already raised industry's awareness of the need for increasing the genetic diversity of blue agave by allowing its inflorescence and hence pollination by bats (Trejo-Salazar et al 2016). Arguably, the current situation in which the commercial production of agave is contributing to put bat populations at risk, could be changed to one in which protecting bats can be a factor that increases the resilience of the tequila industry by increasing agave diversity. Similar programs for other agave-based spirits (like mezcal and bacanora ⁶ ) have also been implemented (Minardi 2020, Bat Conservation International 2023). It is worth mentioning that these kinds of programs are not without risks. For example, allowing sexual reproduction could result in morphological changes to the crop, which could compromise its denomination of origin. ⁷

Making producers and consumers aware of the link between tequila, or similar agave-based spirits, and the future of bats, is a step in the right direction towards a production system that is environmentally friendly and more resilient (Lear 2020, Bat Conservation International 2023). Nevertheless, for this voluntary system to work, consumers must be willing to pay a higher price for the product. Meanwhile, the agave producers need to be properly compensated for the losses they incur by letting some of their plant bloom. The situation is further complicated by the fact that plants lost for tequila production represent an immediate direct cost to the agave producer, while the potential benefits, in terms of higher genetic diversity and healthier bat populations, are public benefits to be obtained in the future. Moreover, it is important to note that while the bat friendly project can serve as a direct incentive for tequila producers, not all agave producers are tequila producers. A significant portion of agave farmers solely cultivate and sell agave to tequila houses without participating directly in tequila production. Consequently, these producers do not receive a direct incentive from the bat friendly hologram program, thereby creating a potential gap in adopting bat-friendly practices within the industry. For this reason, we focus our hypothetical program on agave producers and their willingness to adopt bat-friendly practices in exchange for private benefits. The information obtained with this analysis can help policymakers, producers, NGOs, and other industry participants, to design effective strategies that could lead to the genetic conservation of blue agave and the protection of magueyero bats and other bat-pollinators of agave.

Data

Methods

In choice experiments, a stated preferences technique, respondents are asked to choose their preferred alternative among a set of mutually exclusive hypothetical options. A set of attributes characterizes each alternative. With the inclusion of a cost or payment mechanism for each alternative, marginal utility estimates can then be converted into willingness-to-pay estimates for changes in the levels of these attributes. Choice experiments assume that when a person is confronted with a pair of mutually exclusive alternatives, their choice can be explained by a process of utility maximization (Champ et al 2017). Each alternative is assumed to have a certain level of utility known to the interviewee, but unobservable to the researcher. This can be formalized in a model where the utility (${U}_{{ij}}$) that the individual $i$ derives from the choice of the alternative $j$ can be expressed as the sum of a systematic component (${V}_{{ij}}$) and a random component (${\epsilon }_{{ij}}$):

$$\begin{eqnarray}&&{U}_{{ij}}={V}_{{ij}}\left({X}_{j}\right)+{\epsilon }_{{ij}},\end{eqnarray} \tag{ 1 }$$

where ${X}_{j}$ is a vector of attributes associated with the alternative $j.$ From the set of alternatives $J,$ individual $i$ chooses the alternative $h$ that maximizes their utility, so that the utility from $h$ is strictly greater than that from any other alternative $j\in J.$ The probability ${P}_{{ih}}$ of this choice can be expressed as:

$$\begin{eqnarray}&&{P}_{{ih}}=P\left[\left({V}_{{ih}}+{\epsilon }_{{ih}}\gt {V}_{{ij}}+{\epsilon }_{{ij}}\right){\rm{;}}\forall j\in J\right]\end{eqnarray} \tag{ 2 }$$

Choice experiments provide estimates of the indirect utility function; this allows us to use the coefficients estimated by the econometric model to calculate the marginal willingness to pay (MWTP) for a change in the level of any attribute $k$ (Champ et al 2017). Narjes and Lippert (2016) have used this method to estimate the valuation that farmers in Thailand have for the pollination services that bees provide. Here, we use it to explore if agave farmers might be willing to participate in programs aimed to increase the genetic diversity of their crop while benefiting a different pollinator, bats. That is, although we do not elicit the valuation that farmers have for pollinators (farmers are assumed to receive no direct utility from the existence of the bats), the hypothetical programs that we presented to the farmers are expected to have a positive effect on the population of bats.

We constructed different hypothetical alternatives for the choice experiment; all of them require the farmer to invest a given amount of agave plants to participate in the hypothetical program. This investment represents the number of plants the agave producers are required to let flower in exchange for receiving the program. The levels of this investment were based on what has been proposed by the bat-friendly program. In particular, Trejo Salazar et al (2016) argue that allowing 5% of each agave hectare to flower could be a key food source for magueyero bats, while also increasing the genetic diversity of blue agave. ⁸ In the choice experiment, we used four different investment levels, 150, 90, 60 and 30, plants per hectare, which correspond to 5%, 3%, 2%, and 1% of an hectare planted with 3,000 blue agave plants, which is close to the number of plants per hectare in a typical plot. Since the cost associated with selecting an alternative other than the status quo is measured in the number of plants that the farmer will need to leave untouched for sexual reproduction, all the MWTP results that we report in the next section are measured in number of blue agave plants that a farmer is willing to sacrifice in exchange of the respective attribute.

The hypothetical programs presented to the farmers had three attributes, a change in yield, a monetary incentive, and a non-monetary incentive. The change in yield is meant to capture the benefit of higher genetic diversity in terms of blue agave productivity. Given the lack of specific evidence about the magnitude of this effect, farmers were only presented with two levels of this attribute, no change in yield and a positive, but unspecified, change. The monetary incentive is a payment that represents a fraction of the cost of the plants invested (table 2). The payment per plant (500 pesos) was defined using information from a focus group with other agave farmers. Finally, some of the alternatives presented to the farmers included a non-monetary incentive, which consisted of an offer to receive training and support (e.g., greenhouses or nurseries) to make better use of the seeds harvested from the plants that were left to flower. The selection of these attributes, and their values, were defined after consultation with a group of researchers who work on issues related to the conservation of the genetic diversity of blue agave.

Table 2. Attributes of the hypothetical program used in the choice experiment.

Attribute	Levels	Description
Investment	30, 60, 90, 150	Agave plants (per ha) intended to be set apart so they can flower. This is the investment that the farmer must make to participate in the hypothetical program.
Change in yield	None, Positive	Changes in the productivity of agave harvest.
Non-monetary incentives	No, Yes	Support in the form of training, greenhouses, and other necessary supplies to make a better use of the seeds obtained from the plants invested.
Monetary incentives	0%, 20%, 50%	Percentage of plants that are paid to the agave producer in relation to the number of plants invested. Price of a palm was set at 500 pesos following actual prices at the time of the survey.

As shown in figure 1, each choice set included four attributes and three different alternatives. The first two alternatives correspond to hypothetical programs with different levels of the respective attributes, while the third alternative corresponds to the status quo. Each choice set was designed using an R package (support.CEs) with the 'mix-and-match' method. This allows for a more efficient and less overwhelming design for the interviewee (Aizaki 2012). After eliminating the sets with strictly dominant alternatives, we were left with two versions of the questionnaire, with five choice sets in each one of the versions.

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We assume that the indirect utility function that can be derived from the model presented before is linear in parameters and variables, and that the error term is distributed as a generalized extreme value. Therefore, we can use a multinomial logit model to estimate the parameters of interests and the MWTP (Haab and McConnell 2002). The alternative hypothesis for the choice experiment is that the positive values of the program's attributes will positively contribute to the individuals' utility. For example, an increase in the productivity of the crop, derived from an increase in genetic diversity, will increase utility. The latter will be reflected as a positive sign of the respective parameter in the econometric estimation.

Table 3 shows the results from the econometric estimation of the coefficients associated to each attribute (column 1). The estimated coefficients for change in yield, monetary incentives (in its two levels), and non-monetary incentives, are all positive and statistically significant. This supports the hypothesis that positive attributes generate positive effects on the utility of agave farmers. As expected, the coefficient associated with investment is negative; everything else constant, farmers are less willing to accept a program when the number of plants they need to let flower increases. Column 2 of the table shows the marginal willingness to pay that agave producers have for each one of the attributes. The estimations shown represent the number of plants that, on average, a farmer is willing to invest to receive each one of the attributes. For example, farmers are, on average, willing to let 93 plants flower in exchange for an unspecified increase in yield. Meanwhile, they are willing to invest 129 plants if they receive a monetary incentive equivalent to 20% of the value of the plants, and almost 180 if the incentive is 50%. The attribute that farmers value less (71 plants) is the non-monetary incentive. The monetary attributes are a direct and certain transfer, while the productivity increase and the non-monetary incentives were framed in the experiment as having potential but unspecified gains. Therefore, the results are compatible with the idea that individuals tend to prefer gains that are certain.

Finally, it is common for choice experiments to include an alternative specific constant (ASC), which takes the value of 1 if the individual selected one of the hypothetical programs and 0 if the status quo was selected. Including the ASC allows the econometric estimation to account for the possibility of a status quo effect, by which individuals tend to prefer the current situation to the alternatives provided. Some researchers argue that the ASC is simply a way to capture the average effect that all the factors not explicitly included in the model have in the utility, while for others, it can actually be associated with behavioral aspects, or with the utility that the status quo provides (Meyerhoff and Liebe 2009). As table 3 shows, the coefficient associated to the ASC is negative and significant, supporting a status quo effect. This is a relatively common result for research in environmental valuation (Meyerhoff and Liebe 2009). Although exploring further the reason behind this status quo effect goes beyond the objectives of this paper, we wanted to make sure that our results were not biased by the responses given by a certain group of individuals. Therefore, we excluded those interviewees that always preferred the status quo (25% of the sample) and estimated the model again after dropping these observations. As columns 3 and 4 show, although smaller in magnitude, the results remain qualitatively the same.

Our research shows that, if adequately compensated, blue agave farmers are willing to participate in a program that aims to increase the genetic diversity of blue agave, while benefiting bat populations at the same time. It is relevant to emphasize that our results show that an adequate compensation does not necessarily needs to be a full compensation in monetary terms. That is, farmers seem to be willing to let some of their plants flower even when they only receive compensation equivalent to 20% of the value of the plants. This can be partially explained by the fact that farmers do not have access to any kind of insurance that can protect them from negative price shocks, so, as some of the farmers told us, a guaranteed income transfer could be seen as some sort of insurance. It could also reflect that when farmers choose their preferred option, they consider the benefits that they will receive from the seeds obtained through the program. Farmers also show a willingness to participate in the program if they receive a non-monetary transfer or if they expect an increase in yield because of the program.

One of the limitations of this study is that we included the potential benefits of an increase in genetic diversity in a very simplistic way. In the choice experiments, we only stated that the yield would increase, but we did not provide any information about its magnitude. In addition, we did not differentiate between benefits from increased resistance to pests and diseases, and those from increased productivity due to the selection of beneficial characteristics from a bigger genetic pool. Studying the willingness to pay for both attributes separately, while providing more information about the potential magnitude of the benefits, would be very useful for informing policies. Furthermore, a program like this could lead to morphological changes that could in turn compromise the denomination of origin. This is something that needs to be explored and, if confirmed, clearly communicated to potential program participants.

Implementing a program to protect the genetic diversity of blue agave will require funding to be implemented. Given the risk that blue agave faces from pests and diseases, and potentially to changes in climate, the tequila industry could take it upon itself to voluntarily fund a program like the ones described in our choice experiments. Farmers seem to be willing to adopt them. Moreover, the industry could join efforts with the groups trying to protect the magueyero bats. If tequila consumers are willing to pay a premium for bat-friendly tequila, these additional funds could finance, at least partially, the implementation of a conservation program aimed at agave producers. Studying the consumers' willingness to pay for that kind of product is a worthy research agenda. Incidentally, in this research, we assumed that farmers derive no direct benefit from helping the bats; this could be formally tested by explicitly including an attribute related to the effect that letting some plants flower will have on the bats.

It is important to recognize that, depending on some of their characteristics, for example, the amount of land owned or income from other sources, farmers might react differently to the same conservation program. Unfortunately, the sample size of this study was too small to allow us to do any heterogeneity analysis within the agave producers. Furthermore, we did not include questions about risk aversion or discount rates. Both characteristics are relevant in a setting like ours, where some of the benefits are in terms of risk reductions in the future. Correcting these shortcomings would be very important to provide inputs that can help design a successful program targeted to the right farmers. Despite these limitations, the results of this study provide evidence to be cautiously optimistic about the possibilities of implementing a program that can increase the genetic diversity of blue agave and benefit magueyero bats.

We thank Héctor Núñez Amórtegui for his comments on previous versions of this paper. An anonymous reviewer provided valuable feedback. We also thank the Tequila Regulatory Council for allowing us to approach the blue agave producers in their offices, and especially Dr Guillermo Briceño Félix for his valuable explanation on A. tequilana genetic issues. Finally, we are particularly grateful to all the agave farmers who responded to our questionnaires and shared their knowledge about the world of blue agave.

The data that support the findings of this study are openly available at the following URL/DOI: https://github.com/LopezFeldman/agave_CE.