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Our study evaluated the effectiveness of using eight pathways in combination for a complete to transition from fossil fuels to renewable energy by 2050. These pathways included renewable energy development; improving energy efficiency; increasing energy conservation; carbon taxes; more equitable balancing of human wellbeing and per capita energy use; cap and trade systems; carbon capture, utilization, and storage; and nuclear power development. We used the annual ‘British Petroleum statistical review of world energy 2021’ report as our primary database. Globally, fossil fuels, renewable (primarily hydro, wind and solar), nuclear energy accounted for 83%, 12.6%, and 6.3% of the total energy consumption in 2020. To achieve zero fossil fuel use by 2050, we found that renewable energy production will need to be increased by up to 6-fold or 8-fold if energy demand is held constant at, or increased 50% from, the 2020 energy demand level. Constraining 2050 world energy demand to a 25% increase over the 2020 level, improves the probability of achieving independence from fossil fuels. Improvements in energy efficiency need to accelerate beyond the current rate of ~1.5% per year. Aggressive application of energy conservation policies involving land use and taxation could potentially reduce world energy use by 10% or more by 2050. Our meta-analysis shows that the minimum level of per capita energy consumption that would allow 8 billion people to have a ‘Decent Living Standard’ is on average ~70 GJ per capita per year, which is 93% of the 2020 global average. Developed countries in temperate climates with high vehicle-dependency needed ~120 GJ per capita year−1, whereas equatorial countries with low vehicle-dependency needed 30 GJ per capita year−1. Our meta-analyses indicated replacement of fossil fuels with renewable energy by 2050 may be possible but will require aggressive application of all eight pathways, major lifestyle changes in developed countries, and close cooperation among all countries. 

New Mexico (NM) has been identified as the state in the US that will be most adversely impacted by climate change and associated water stress. Roughly 92% of NM is rangeland, most of which is grazed by beef cattle. We calculated the blue (surface and ground) and green (precipitation) water footprints (WF) of NM beef cattle industry (cow-calf, backgrounding, and feedlot). This analysis indicated that the weighted average WF of NM beef cattle was 28,203 L/kgmeat. The majority of the WF was accounted for green water (82%; 23,063 L/kgmeat) used by rangeland forages. Blue water accounted for only 18% (5140 L/kgmeat) of the total beef WF estimate. The relative contribution of green vs. blue water varied significantly among the different phases of beef production. In cow-calf, green water accounted for 99.5% of the WF whereas blue water, accounted for 100% of beef WF during backgrounding and feedlot. Based on our estimate, NM cow-calf operations is about a third or a quarter of the blue water (m3/year) used to produce corn or wheat, and only 5% or less of the water used to produce cotton or hay. In NM, irrigation accounts for about 84% of freshwater use followed by public/domestic use of 10%. Mining, thermo-electric, livestock production, aquaculture, and industrial uses collectively account for the other 6%. 

Understanding the fluctuations in monthly and annual cattle prices plays a key role in supporting the sustainability of New Mexico’s (NM’s), United States (US), beef cattle industry under variable environmental conditions. The goal of this study was to provide an improved understanding of NM’s beef cattle production systems in terms of prices and production patterns and related drought impacts. The main objectives were to evaluate monthly and annual prices patterns for heifers and steers (cattle) and calves, the relationships between annual cattle prices and inventory and drought, and the effects of drought on ranch net return. Drought events were assessed using the Self-Calibrated Palmer Drought Severity Index (SC-PDSI). The generalized autoregressive conditional heteroscedasticity models and their exponential version were used to investigate the effects of drought and cattle supply on cattle prices, and the effects of drought on ranch net return. Spectral analysis and timeseries decomposition were used to identify the cycles of the annual price and numbers of cattle and calf. Coherence analysis was used to examine the relationships between inventory of cattle classes and drought. The results indicated that prices of cattle and calf usually drop in October through January and peak in April. The inventory of replacement heifers and steers were negatively related to cattle prices, while the inventory of calves was positively related to calf prices. Cattle and calf prices showed negative linear relationships with droughts. Annual cattle and calf prices showed 6- and 10-year cycles, while their inventory showed 6- and 8- year cycles, respectively. Our finding suggested that a rancher can still earn some net return when drought falls within the “Abnormally Dry” category of the US Drought Monitor. However, a rancher with a large herd or ranch size can endure drought more than a rancher with a medium herd or ranch size and reach the breakeven point. Specifically, the net return ($/head) is expected to increase (or decrease) by $62.29, $60.51, and $64.07 per head if the SC-PDSI increase (or decrease) by one unit in all large and medium ranch sizes, respectively. The effects of drought on ranch net return that we identified need further improvements using additional data. Due to NM’s location and the diversity of its rangeland, understanding the response of cattle prices to drought and beef cattle supply based on these findings can be used to help NM’s ranchers and those in other similar regions make informed ranch management decisions. These findings can also support the development of improved understanding of beef cattle production systems regionally. 

Accelerated climate change is a global challenge that is increasingly putting pressure on the sustainability of livestock production systems that heavily depend on rangeland ecosystems. Rangeland management practices have low potential to sequester greenhouse gases. However, mismanagement of rangelands and their conversion into ex-urban, urban, and industrial landscapes can significantly exacerbate the climate change process. Under conditions of more droughts, heat waves, and other extreme weather events, management of risks (climate, biological, financial, political) will probably be more important to the sustainability of ranching than capability to expand output of livestock products in response to rising demand due to population growth. Replacing traditional domestic livestock with a combination of highly adapted livestock and game animals valued for both hunting and meat may be the best strategy on many arid rangelands. Eventually, traditional ranching could become financially unsound across large areas if climate change is not adequately addressed. Rangeland policy, management, and research will need to be heavily focused on the climate change problem. 

In support of Food-Energy-Water Systems (FEWS) analysis to enhance its sustainability for New Mexico (NM), this study evaluated observed trends in beef cattle population in response to environmental and economic changes. The specific goal was to provide an improved understanding of the behavior of NM’s beef cattle production systems relative to precipitation, temperature, rangeland conditions, production of hay and crude oil, and prices of hay and crude oil. Historical data of all variables were available for the 1973–2017 period. The analysis was conducted using generalized autoregressive conditional heteroscedasticity models. The results indicated declining trends in beef cattle population and prices. The most important predictors of beef cattle population variation were hay production, mean annual hay prices, and mean annual temperature, whereas mean annual temperature, cattle feed sold, and crude oil production were the most important predictors for calf population that weigh under 500 lb. Prices of beef cattle showed a strong positive relationship with crude oil production, mean annual hay prices, rangeland conditions, and mean annual precipitation. However, mean annual temperature had a negative relationship with mean annual beef prices. Variation in mean annual calf prices was explained by hay production, mean annual temperature, and crude oil production. This analysis suggested that NM’s beef cattle production systems were affected mainly and directly by mean annual temperature and crude oil production, and to a lesser extent by other factors studied in this research. 

This study was conducted within the context of providing an improved understanding of New Mexico’s food, energy, water systems (FEWS) and their behavior under variable climate and socioeconomic conditions. The goal of this paper was to characterize the relationships between production and prices of some forage crops (hay, grain sorghum, and corn) that can be used as feed supplements for beef cattle production and the potential impacts from a changing climate (precipitation, temperature) and energy inputs (crude oil production and prices). The analysis was based on 60 years of data (1958–2017) using generalized autoregressive conditional heteroscedasticity models. Hay production showed a declining trend since 2000 and in 2017, it dropped by ~33% compared to that of 2000. Crude oil production (R2 = 0.83) and beef cattle population (R2 = 0.85) were negatively correlated with hay production. A moderate declining trend in mean annual hay prices was also observed. Mean annual range conditions (R2 = 0.60) was negatively correlated with mean annual hay prices, whereas mean annual crude oil prices (R2 = 0.48) showed a positive relationship. Grain sorghum production showed a consistent declining trend since 1971 and in 2017, it dropped by ~91% compared to that of 1971. Mean annual temperature (R2 = 0.58) was negatively correlated with grain sorghum production, while beef cattle population (R2 = 0.61) and range conditions (R2 = 0.51) showed positive linear relationships. Mean annual grain sorghum prices decreased since the peak of 1974 and in 2017, they dropped by ~77% compared to those of 1974. Crude oil prices (R2 = 0.72) and beef cattle population (R2 = 0.73) were positively correlated with mean annual grain sorghum prices. Corn production in 2017 dropped by ~61% compared to the peak that occurred in 1999. Crude oil production (R2 = 0.85) and beef cattle population (R2 = 0.86) were negatively correlated with corn production. Mean annual corn prices showed a declining trend since 1974 and in 2017, they dropped by ~75% compared to those of 1974. Mean annual corn prices were positively correlated with mean annual precipitation (R2 = 0.83) and negatively correlated with crude oil production (R2 = 0.84). These finding can particularly help in developing a more holistic model that integrates FEWS components to explain their response to internal (i.e., management practices) and external (i.e., environmental) stressors. Such holistic modeling can further inform the development and adoption of more sustainable production and resource use practices.