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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.
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Ranchers Adapting to Climate Variability in the Upper Colorado River Basin, Utah
In the Upper Colorado River Basin, agriculture is a major contributor to Utah’s economy, which may be stressed due to the changing climate. In this study, two data-mining techniques and interview data are used to explore how climate variability affects agricultural production and the way the farmers have been adapting their practices to these changes. In the first part of the study, we used multilinear regression and random forest regression to understand the relationship between climate and agricultural production using temperature, precipitation, water availability, hay production, and cattle herd size. The quantitative results showed weak relations among variables. In the second part of the study, we interviewed ranchers to fill the gaps in the quantitative analysis. Over the 35 years (1981–2015), the quantitative analysis shows that temperature has affected cattle and hay production more than precipitation. Among non-climatic variables, resource availability and commodity prices are the most important factors that influence year-to-year production. Farmers are well-aware of these effects and have adapted accordingly. They have changed irrigation practices, cropping patterns, and are experimenting to produce a hybrid species of cattle, that are resilient to a hotter temperature and can use a wider variety of forage.
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- Award ID(s):
- 1633756
- PAR ID:
- 10381572
- Date Published:
- Journal Name:
- Climate
- Volume:
- 8
- Issue:
- 9
- ISSN:
- 2225-1154
- Page Range / eLocation ID:
- 96
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3390/cli8090096
