WEF Nexus Indicators for Livestock Systems: A Comparative Analysis in Southern Brazil

Abstract

Integrated approaches such as the WEF nexus (water–energy–food) have been key to measuring the efficiency of production systems. In southern Brazil, where extensive livestock farming and integrated agricultural systems coexist in anthropized natural grasslands, such an assessment is crucial for balancing production and conservation. This research aimed to assess the sustainability of different livestock systems in Brazil’s Pampa biome from the perspective of the WEF nexus. One hundred and twenty-one systems were analyzed and divided into extensive livestock systems (ELSs) and integrated livestock systems (ILSs). The MESMIS methodology was used to construct and measure 37 WEF nexus indicators. The data were analyzed using a raincloud diagram and compared using Student’s t-test. In terms of water, the results showed that the ELS was more sustainable in terms of the scope of production. In terms of energy, the ELS stood out in the scope of the sustainability of mechanical energy use. The ILS was superior in terms of social and associative participation in the food nexus, while the ELS stood out in terms of sustainable production management. In general, in both systems, the sustainability indices for the water nexus were optimal, but the situation was alarming for the energy and food nexus. This research contributes by applying the WEF nexus to the analysis of the sustainability of livestock systems, offering a replicable model for other natural grassland regions.

1. Introduction

The recent challenges surrounding climate change have boosted the impacts caused by soil degradation, water pollution, and biodiversity loss on individuals, economies, and livelihoods. Consequently, to guarantee humanity’s future and reduce greenhouse gas (GHG) emissions, an integrated approach that incorporates articulated actions for the water, food, and energy security of populations is necessary.

Food security, environmental degradation, and climate change are fundamental issues for agricultural production, especially in developing countries. The transition process to agricultural sustainability depends on factors covering production processes, marketing, and consumption patterns. In this context, it becomes challenging to find strategies capable of promoting agricultural and livestock production that meet the growing demand for goods and services and minimize the negative externalities of agriculture. The growing competition for land, water, and energy, coupled with overfishing, will affect our ability to produce food, as will the urgent need to reduce the impact of the food system on the environment [1,2]. In other words, agriculture today faces a double challenge: on the one hand, the urgent need to provide food for a growing population, and on the other, to achieve this in a sustainable way [3,4,5].

With this in mind, the United Nations has proposed 17 Sustainable Development Goals (SDGs) to tackle significant global challenges such as global food insecurity, the energy crisis, and water scarcity. Within this scope, food, energy, water, and carbon emissions are central elements of the SDGs [6,7,8].

Agricultural production involves several interconnected components, such as land, water resources, energy efficiency, and climate [9,10], which contribute significantly to different levels of sustainability. The term nexus is a concept encompassing a strategy that combines integrative solutions to improve land use and water resources with better management of energy resources. At the same time, it considers the urgent concern for the sustainability of global economies [11,12]. The water–energy–food framework emerges from the close interconnection of these three basic resources to analyze an agricultural system’s performance, examining its sustainability from a triple perspective: economic, environmental, and social [13,14]. From this perspective comes the nexus approach, assuming that the sustainability of the water, energy, and food triad (WEF nexus) should be the central unit of analysis [15].

Livestock systems have been the main form of economic exploitation of the natural pastures of the Pampa biome, Brazil’s southernmost biome [16]. Recent changes in land use, primarily since the expansion of soybean production in the Pampa biome region, have raised concerns about the continuity of extensive production systems and could accelerate soil degradation processes [17]. This expansion is based on agricultural export production sustained by a globalized model governed by financialization and competitiveness [18], replacing extensive livestock areas with the production of non-food commodities. In addition, these changes impact the population’s access to locally produced food, making local economies dependent on supplier markets [19]. Thus, the implications of climate change, enhanced by changes in land use, determine a process of high degradation of natural resources (water, soil, and biodiversity).

Cattle grazing has been indicated as an alternative for conserving native grassland vegetation [20]. However, some anthropogenic interventions have been advocated as an alternative to conservation. These interventions have generated what authors Viana et al. [16] called the “grassland dilemma”, i.e., the paradoxical conservation of slightly “anthropized” ecosystems. It is, therefore, essential to identify and deepen knowledge about the sustainability of this way of life and its production systems. This requires the existence and generation of indicators that reflect on the current reality and the possibilities for its sustainability in the future.

Research has already focused on modelling the WEF nexus in agricultural systems [21]. For example, Sun et al. [22] developed a model for the sustainable management of the agricultural WEF nexus in northwest China using the fuzzy fractional programming model with probability constraints (CFFP). The authors incorporated water resource use, agricultural land allocation, and electricity generation into the nexus framework in the Kaikong River basin, a water-scarce region in northwest China.

The studies by Cansino-Loeza and Ponce-Ortega [23] use a multi-objective optimization model for the design of a WEF system involving the sustainable production of water, energy, and food in areas that share economic activities through the industrial, agricultural, and livestock sectors in Mexico. Research conducted Saray et al. [24] and Radmehr et al. [25] examined the interrelationship between water, energy, food, and CO₂ emissions on a farm located in northwestern Iran. However, studies that measure and compare indicators of water, energy, and food sustainability between different livestock production systems in natural fields are lacking. Furthermore, no previous study has used nexus indicators to compare livestock production systems in Brazil. This is the background to our research question: what are the levels of water, food, and energy sustainability of different livestock production systems in the Brazilian Pampa biome?

Thus, the aim of this research was to assess the sustainability of water, energy, and food indicators of different livestock systems in southern Brazil, meeting the demand highlighted by the FAO [26] and Shah [27] to promote WEF nexus assessment strategies and methodologies.

As a hypothesis, extensive livestock systems are expected to have a higher level of sustainability in the WEF nexus. The practice of extensive livestock farming preserves soil structure conditions, as well as the biodiversity of the biome’s fauna and flora, contributing to water sustainability. The low intensity of mechanization leads to less dependence on the use of energy from fossil fuels, and production on natural grasslands benefits the production of better-quality animal protein.

The proposed study makes contributions to the field of knowledge, both by providing subsidies to the discussion on sustainable management of similar ecosystems globally and by building a methodological tool with indicators that allow a nexus assessment to be carried out in other realities.

2. Materials and Methods

2.1. Study Area and the Nexus–MESMIS Approach

The Pampa biome is characterized by grassland vegetation, notably known as the southern grasslands. Its pastoral regions extend over part of Argentina (the provinces of Buenos Aires, La Pampa, Santa Fe, Entrerríos, and Corrientes), all of Uruguay, and part (63%) of Rio Grande do Sul, Brazil [28]. In Brazil, the Pampa biome represents 2.3% of the national territory, occupying an area of approximately 19 million hectares [29].

In the Pampa biome of Brazil, two central livestock systems are exploited: (a) extensive livestock systems, characterized by the exclusive rearing of cattle on natural pasture, with a low use of external inputs, and (b) integrated livestock systems, characterized by cattle rearing integrated with grain agriculture, especially with soybean and/or rice crops [30,31,32,33]. Other variants of the extensive systems can be found, with the exploitation of livestock being more intensive in terms of external inputs (using cultivated pastures, animal supplementation, etc.).

To assess the sustainability of extensive livestock systems (ELSs) and integrated livestock systems (ILSs) in Brazil’s Pampa biome, we chose the Ibirapuitã River basin as our study area (Figure 1). The choice is justified by the fact that the basin contains a diversity of dynamics that resemble the realities of other parts of this biome: livestock systems, urban agglomeration, and intensive land use for crops [19].

The construction of sustainability indicators for the production systems studied was based on the MESMIS methodology proposed by Masera et al. [35]. This method indicates that sustainability should be measured from each socio-environmental and temporal context based on a systemic, participatory and interdisciplinary approach. To this end, adaptations were made to the MESMIS methodology, transforming the tripod of sustainability (social, economic, and environmental) into the fundamentals of the nexus approach (water, energy, and food). Interdisciplinarity and a participatory approach were guaranteed through a group of 70 extension workers and researchers from different areas of knowledge, including professionals in higher education in agriculture, scientists from research institutions, and professors from Brazilian public universities.

The construction of the indicators was conducted through six stages of the evaluation cycle proposed by MESMIS, namely: (i) determining the object of evaluation; (ii) determining the critical points; (iii) selecting the indicators; (iv) measuring and monitoring the indicators; (v) integrating the results; and (vi) conclusions and recommendations by López-Ridaura [36]. The type of production system to be studied was defined in the first stage. In the second stage, a SWOT (Strengths, Weaknesses, Opportunities, and Threats) matrix was drawn up for family livestock systems in Pampa. In the third stage, each dimension of the nexus (water, energy, and food) was discussed in working groups. The interdisciplinary approach was guaranteed through a participation group of extensionists and researchers from different areas of knowledge, totaling 70 members. In the end, each group collectively presented proposals for developing indicators within the WEF nexus. The interdisciplinary vision enriched the process, especially when assigning indicator weights, avoiding overlapping interests in disciplinary processes. Thus, the scopes and indicators for the three dimensions (water, energy, and food) were defined, totaling 37 WEF nexus indicators.

Table 1. Sustainability indicators for the water–energy–food nexus of livestock systems (ELSs and ILSs).

Dimension	Scopes	Weight	Indicators	Weight
Water	Human consumption	20	Water quantity Water quality	10 10
	Production	40	Water for production Water use efficiency Drought susceptibility	10 20 10
	Degradation	40	Existence of conservationist practices Perception of the erosive process	30 10
Energy	Electric	60	Generation Consumption Grid	20 20 20
	Thermal	20	Thermal energy use Thermal energy source	10 10
	Mechanical	20	Pumping Fossil fuel	5 15
Food	Organizational and institutional environment	20	Tradition and culture Supporting organizations Public policies Social and associative participation Cooperation in the markets Logistic and energy infrastructure Quality of life Succession/transmissibility	2 2 2 2 2 2 4 4
	Productive and technological environment	50	Genetics of animal production Feed management Dependence on external inputs Production diversification Economic management Dependence on the flow of capital Availability of labor force Cattle raiding	4 6 6 6 6 6 4 4 4 4
	Commercialization and consumption	30	Market structure and prices Commercialization chains Value addition Secondary products Self-consumption and direct sale	8 8 6 4 4

shows each WEF nexus dimension, its scope, and its indicators. The experts within the working groups assigned the indicator weights for the water, energy, and food dimensions. The assignment followed the criterion of the relative importance of each indicator in the sustainability of each dimension. These weights were then put to a group of livestock farmers to assess their empirical relevance. A detailed overview of the description, composition, and questionnaire that resulted in the measurement of each indicator can be found in the Appendix A of Viana et al. [37].

The indicators were constructed by experts and measured based on the farmers’ perceptions of each variable in the survey. In the end, the variables’ composition and respective weights in each indicator resulted in an assessment of the sustainability of the production systems studied in the Brazilian Pampa region.

2.2. Sampling and Analysis of Data from the ELS and ILS Systems

The fourth stage of the methodology involved drawing up a questionnaire to measure all the indicators. In order to create a representative sampling plan, it was necessary to obtain a minimum amount of information about the farms in the area. Due to the lack of secondary data, we conducted a pilot study with 45 livestock farms in the region. The data from this pilot study delimited the variability between farms. Based on this measure, the survey’s sampling plan was defined according to the sampling method for a finite population (Equation (1)) by Anderson et al. [38].

$$n={\displaystyle \frac{{\sigma }^2·Z^2·N}{{\epsilon }^2·\left(N-1\right)+{\sigma }^2·Z^2}}$$

(1)

where n = sample size; σ = standard deviation; Z = confidence level; N = population size; and ε = margin of error.

There are 2685 farms in the Ibirapuitã River basin [39]. A 95% confidence level was used to calculate the sample (Z = 1.96). With the data from the pilot study, it was possible to measure the standard deviation and margin of error of the sustainability indices. The energy indices showed the most significant variability, so we used these indices to calculate the sample (σ = 7.94; ε = 1.5). With these parameters, the minimum estimated sample size was 104 livestock systems.

In order to represent the heterogeneity of agricultural systems and land use in the Ibirapuitã River basin, the survey reached 121 livestock systems, which were segmented into extensive livestock systems (ELSs, n = 80) and integrated livestock systems with agriculture (ILSs, n = 41). The difference in quantity between the groups is due to the characteristics of the population itself. There is a predominance of extensive livestock farms compared to livestock farms integrated with agriculture. This scenario is changing as a result of the recent transformation of land use in the region [40]. All the systems sampled were georeferenced. Figure 2 shows a spatial view of the sample stratification in the Ibirapuitã River basin. The interviews were conducted face-to-face. Due to the long distances, it was possible to conduct a maximum of two interviews per day, each lasting an average of six hours.

The fifth stage was the integration and analysis of the results. The sustainability indices range from 0 to 100. In a specific analysis of sustainability within the dimensions (water, energy, and food), the indices were measured from the weighted composition of each indicator. Ultimately, the closer the value is to 100, the greater the sustainability attributed to the index. In this way, it was possible to create a scale of sustainability levels for the WEF nexus, as shown in Figure 3.

In all scientific disciplines, there is growing recognition of the need for more statistically robust approaches to data visualization. Plotting tools are sought that accurately and transparently convey the main aspects of statistical effects [41]. From this perspective, the raincloud diagram method emerges. A raincloud diagram is especially useful for comparing groups of data in a clear and intuitive way. It consists of three forms of analysis: (i) a density plot, which shows the shape of the data distribution; (ii) a boxplot, which represents the median, quartiles, and extreme values/outliers; and (iii) a scatter plot, which delimits the individual observations allowing for the dispersion of the data to be observed. Thus, the WEF nexus sustainability indicators were presented using raincloud diagrams.

For an inferential analysis, the 37 WEF nexus indicators were measured and compared between and within the systems’ water, energy, and food dimensions. The normality of the data was confirmed using the Shapiro–Wilk test (p > 0.05). Thus, we used Student’s t-test to compare the ELS and ILS systems, with a maximum % significance level of 5%. The software used for the statistical analysis was JASP 0.19.3.0. Finally, the sixth stage discussed the sustainability indices of extensive livestock systems and integrated livestock systems into agriculture with recent findings from the international literature.

3. Results

The presentation of the results compares the levels of sustainability between and within the water, energy, and food nexus (WEF nexus) in extensive livestock systems (ELSs) and integrated livestock systems with agriculture (ILSs) located in the Pampa region of Brazil. Figure 4 shows the dispersion, descriptive measures, and distribution of the WEF nexus sustainability indices and their scopes using a raincloud diagram. The sustainability indices of the water–energy–food nexus (WEF nexus) of the ELSs and ILSs sampled showed a distribution close to normal, favoring an inferential perspective of the results. The ELSs showed slightly higher medians than the ILSs in the water and food dimensions, except for the energy dimension. The ELSs showed sustainability indices in the WEF nexus with more homogeneous and consistent distributions than the ILSs.

Table 2. Analysis of Student’s t-test for the sustainability index for the WEF nexus of livestock systems (ELSs and ILSs) sampled in the Pampa region of Brazil.

Variables	Sustainability Index		p-Value	Coefficient of Variation (%)
	ELS	ILS		ELS	ILS
Water	88.82	86.34	0.035	6.7%	7.3%
Energy	52.56	53.18	0.730	16.6%	19.6%
Food	50.97	49.49	0.280	13.1%	15.9%

shows the results of Student’s t-test for the sustainability index of the water, energy, and food nexuses for the production systems (ELSs and ILSs). The data show that the ELSs had slightly higher indices in the water and food nexus and lower indices in the energy nexus, with a significant difference (p < 0.05) only in the water nexus.

The results of the evaluations within each nexus (water, energy, and food) are presented below. According to

Table 3. Analysis of Student’s t-test for the sustainability index for the water nexus of livestock systems (ELSs and ILSs) sampled in the Pampa region of Brazil.

Variables	Sustainability Index		p-Value	Coefficient of Variation (%)
	ELS	ILS		ELS	ILS
Human consumption	97.56	96.09	0.341	6.3%	11.2%
Production	86.90	84.32	0.089	9%	9.3%
Degradation	86.37	83.47	0.229	13.9%	16.1%

, the indices for the human consumption and degradation scopes showed no significant difference in the water nexus. However, the ELSs showed greater sustainability regarding the water for production scope (p < 0.10).

Table 4. Analysis of Student’s t-test for the sustainability index for the energy nexus of livestock systems (ELSs and ILSs) sampled in the Pampa region of Brazil.

Variables	Sustainability Index		p-Value	Coefficient of Variation (%)
	ELS	ILS		ELS	ILS
Electricity	50.65	54.37	0.160	25.7%%	27.6%
Thermal	40.00	44.39	0.199	44.3%	39.7%
Mechanical	70.87	58.41	<0.001	17.1%	34.6%

shows the sustainability indices for the energy nexus (electrical, thermal, and mechanical). The ILSs showed higher absolute indices for the electrical and thermal energy scopes. However, a significant difference between the averages was only found in the mechanical energy scope (p < 0.01), with ELSs showing greater sustainability.

Regarding the food nexus (organizational/institutional environment, production/technological environment, and marketing/consumption),

Table 5. Analysis of Student’s t-test for the sustainability index for the food nexus of livestock systems (ELSs and ILSs) sampled in the Pampa region of Brazil.

Variables	Sustainability Index		p-Value	Coefficient of Variation (%)
	ELS	ILS		ELS	ILS
Organizational and institutional environment	51.00	58.72	0.002	25.8%	20.4%
Productive and technological environment	55.85	49.80	0.001	16.2%	21%
Marketing and consumption	42.81	42.80	0.999	28.3%	40.3%

shows that there was a significant difference in the first two scopes (p < 0.01), with ILSs being higher in social and associative participation and ELSs being higher in sustainable production management.

In summary, the results show that, in the Ibirapuitã River basin of the Brazilian Pampa region, the livestock systems (ELSs and ILSs) showed different behaviors regarding the sustainability indicators, with the ELSs being superior in aspects related to the production environment, such as the use of water resources in food production, sustainable production practices and management, and the use of mechanical energy. On the other hand, the ILSs performed better in terms of the social and associative participation of production units. It should be noted that the sustainability indices of the water nexus of both systems were in an optimal situation (Figure 3). However, the sustainability indices of the energy and food nexuses of the ELSs and ILSs were in a warning situation. The results will be discussed in dialogue with the international literature.

4. Discussion

The global food system is facing an unprecedented challenge in terms of balancing the growing demand for animal products with the imperative of sustainability. In this scenario, livestock production plays a fundamental role in food security, cultural practices, and socio-economic development. The results presented here highlight the urgent need to use approaches that will enable progress in the WEF nexus sustainability measurement proposals, particularly to compare the performance of different production systems.

Sustainability in livestock systems has become a focal point in agricultural research and policy due to its multifaceted impacts on the environment, the economy, and society. Within diversified farming systems, crop–livestock integration is considered one of the most promising options for achieving sustainability goals, as demonstrated by Kirkegaard et al. [42] and Liang et al. [43], due to the environmental and economic benefits already demonstrated, as shown by Ryschawy et al. [44], Sustainable livestock systems aim to balance the need for efficient food production with environmental stewardship, economic viability, and social responsibility.

Although the literature has pointed to the strategic role of integrated systems in improving sustainability indicators and mitigating the effects of climate change, emphasizing positive effects in terms of food security [45], in the case of Brazil’s Pampa biome, the supremacy of ILSs is not evident. This leads us to reflect that the performance of a given system largely depends on its ability to adapt to the endogenous conditions of the biome and the management practices adopted. In this case, extensive cattle ranching in natural grasslands has greater synergy with the biome and more significant sustainability potential than integrated systems.

In this case, extensive livestock farming represents a valuable alternative for food production and the conservation of natural resources, since adaptive management and rotational grazing on native pastures optimize biomass production, promote and conserve soil health, preserve conditions for optimizing water resources, and minimize the need for external inputs and intensive mechanization [46,47]. In addition, according to Overbeck et al. [48], the maintenance of native biodiversity, a characteristic of extensive systems, contributes to the resilience of ecosystems and the provision of ecosystem services, such as the regulation of the hydrological cycle and the conservation of carbon in the soil.

The system of extensive livestock farming in natural grasslands has created a particular condition of resilience fundamental to the sustainability of livestock production in biomes such as the Pampa. The ability of these systems to recover from disturbances such as droughts and fires is essential for maintaining biodiversity and ecosystem services. Studies such as that by Viana et al. [16] point out that “the sustainability of livestock systems in the Pampa biome depends on maintaining the resilience of native grasslands, which are the basis of animal feed”.

This resilience, one of the factors that anchor the sustainability of production systems, results from the complexity and diversity of natural grassland ecosystems, which allow species to adapt and vegetation to recover after extreme events. When these conditions are modified by changes in land use, notably grain cultivation, this capacity is affected, and there are repercussions on the results of sustainability indices related to the typical productive aspects of agricultural systems.

From this perspective, integrated cropping and livestock systems (soybeans and cattle) are resilient to climate change in southern Brazil, according to simulation models. Although soybean productivity may be slightly lower in integrated systems compared to specialized (control) systems, total system productivity, including forage and livestock production, is higher in integrated systems [49]. That said, the importance of agricultural diversification to increase the resilience of agroecosystems to climate change is highlighted, providing additional support for assessing ongoing changes in land use in the Pampa biome.

In the scope of mechanical energy, the results show that ELSs outperformed ILSs. The literature helps us understand this difference in performance. For example, de Moraes et al. [50], when studying soil carbon stocks under different grazing intensities in the Brazilian subtropics, observed that different management practices for native grasslands imply different levels of mechanical intervention, indirectly influencing energy flows in the system. This observation suggests that even in extensive systems, management choices can lead to variations in the use of machinery and, consequently, the consumption of fossil fuels, which can translate into a lower environmental impact per unit of product.

However, the higher intensity of management in integrated systems, involving soil preparation, forage cultivation, and manure management, can imply higher mechanical energy consumption compared to extensive systems, typically characterized by fewer mechanized interventions [51].

Despite the efforts to generate clean energy technologies for use in agriculture, what still prevails in the universe surveyed is the use of fossil-fuel-powered machinery and implements. In this sense, the reduction in mechanization, which can be seen especially in ELSs, results in less demand for fossil fuels and has positive effects on soil quality and environmental quality, promoting improvements in the sustainability indices of these systems. The intrinsic variability in the systems and the focus of many studies on broader environmental impacts make it difficult to quantify these differences precisely, requiring future research.

The results also reveal differences between the livestock systems (ELSs and ILSs) regarding the organizational and institutional environment. Here, two perspectives are important for reflecting on the superiority of ILSs over ELSs. The first is that isolation is a characteristic ingrained in the way of life of cattle ranchers in the Pampa region. According to Leal [52], the gauchos of the Pampa region have historically had a profile that values autonomy and independence, which, together with the dispersion of the properties over long distances, is a determining factor in the low adherence to collective forms of organization, where the sharing of resources, decisions, and participation in meetings and joint activities are fundamental [53].

It should be added that this tendency towards individualism in livestock farming, which is echoed in the Pampa region, has also been observed in global contexts, shaped by similar challenges and cultures. As Cronon [54] points out, the figure of the American cowboy, with his “radical independence”, reflects an ingrained individualism parallel to the self-sufficiency of Australian cattle ranchers on vast properties, where isolation reinforces their autonomy. Competition for scarce resources in arid regions accentuates this characteristic, with protecting individual property taking precedence over cooperation.. However, the need to face collective challenges, such as health problems in animal production and expanding and qualifying access to markets, highlights the importance of cooperation, which, despite individualism, persists as a crucial element in global livestock farming.

The second perspective is that in contrast to extensive livestock systems, integrated (crop–livestock) systems encourage the formation of cooperation networks due to dynamics that are intrinsic to agriculture, such as the expansion of negotiating power for the joint purchase of inputs and sale of production from associative and cooperative structures [44,55,56,57]. These systems also promote the exchange of knowledge and technologies, as highlighted by Schneider [58] and Bungenstab [59], and facilitate access to credit (for input and equipment investments), as well as to public policies that support production—including technical assistance, advisory services, storage, and grain marketing. In commodity production, unlike in livestock systems, the pursuit of scale and negotiating leverage is vital for competitiveness, prompting farmers to form cooperatives to gain market access and secure better prices.

Still, on the food axis, the “productive and technological environment” dimension, in which ELSs showed superiority, brings us back to the importance of the coevolution of extensive livestock farming with the biome, primarily through the sustainable management of cattle in natural fields.

Finally, it is important to note that the alert condition in the sustainability indices for the food dimension is strongly influenced by the limitations of the “marketing and consumption” dimension for both systems (ELSs and ILSs). These dimensions share a significant part of the problems relating to infrastructure and logistics that affect access to markets. Critical points in this area include the distance from major consumer centers, precarious roads, high transport costs, low differentiation, and value addition.

5. Conclusions

This research contributes to the field by including the nexus approach in the analysis of agricultural systems’ sustainability, and it can be replicated in other realities that face a scenario of agricultural advancement over livestock systems in natural fields.

This article reveals that livestock systems (ELSs and ILSs) show different behaviors and impacts in terms of sustainability. ELSs stand out for their more efficient use of natural resources in aspects related to the production environment, such as using water resources in food production and adopting sustainable production practices and management, which minimize environmental impact. In addition, ELSs tend to use less mechanical energy, which contributes to reducing greenhouse gas emissions. On the other hand, ILSs show greater social engagement and organizational capacity, with greater participation in collective structures to support production and/or marketing. As we have already pointed out, in both systems, the sustainability indices for the water nexus are optimal, but the situation is alert for the energy and food nexuses.

Furthermore, this article makes a double contribution, both to the debate on changes in land use, especially in biomes where conventional agriculture is advancing over livestock systems in natural fields, and to aspects linked to the sustainability of production systems, given the scarcity of resources, climate change, and the environmental crisis.

The development prospects for livestock systems managed with natural pastures can be a valuable resource in combating biodiversity loss and climate change. Although some may equate livestock farming with images of large-scale agricultural systems, the types of systems we see for the most part include mixed farming systems, in which integration between crops and livestock is fundamental to soil health, semi-intensive systems, to which many producers are transitioning, and pastoral and extensive grazing systems, which are fundamental to restoring large areas of arid land and pastures.

Our findings contribute to other regions by encouraging sustainable livestock indicators that can improve soil health, increase carbon sequestration, promote ecosystem diversity, restore degraded land, support wildlife conservation, and increase agricultural resilience. Agricultural systems are increasingly contested as demand for the provision of a range of ecosystem services increases, particularly in relation to the energy, water, and climate nexus in an integrated manner. It is imperative to adopt a comprehensive and interconnected approach that considers the environment in theoretical approaches and practical implementation in livestock systems.

It is important to emphasize that scientific effort is still needed to produce studies that can, like this one, provide tools for public managers and private agents to implement actions in the agricultural sector, or in other words, to help decision-makers meet the demand for food while preserving natural resources and mitigating the impacts of climate change.