|Title||Can foraging behavior of Criollo cattle help increase agricultural production and reduce environmental impacts in the arid Southwest?|
|Publication Type||Conference Paper|
|Year of Publication||2016|
|Authors||Spiegal S., Estell RE, Cibils AF, Browning DM, H. Peinetti R, James D.K, Romig KB, Gonzalez AL|
|Conference Name||Ecological Society of America|
|Publisher||Ecological Society of America|
|ARIS Log Number||329839|
The Longterm Agroecosystem Research Network (LTAR) was formed to help the nation’s agricultural systems simultaneously increase production and reduce environmental impacts. Eighteen networked sites are conducting a Common Experiment to understand the environmental and economic problems associated with “business as usual” (BAU) agricultural systems and explore hypotheses about how aspirational systems can overcome those problems. In the American Southwest, BAU comprises lightly to moderately stocked cow-calf operations, typically with Angus crossbreds (AX). AX tend to utilize the landscape unevenly. When droughts occur, they may have difficulty accessing sufficient forage, and expensive and resourceintensive supplemental feed is then required. Destocking is a typical coping strategy. We hypothesize that Raramuri Criollo (RC) cattle, which have persisted in arid, rugged conditions in Mexico for ~500 years with minimal husbandry, utilize the landscape more widely – and therefore can sustain droughts with little to no supplemental feed. Many questions must be answered about RC production systems. In 2008, we used GPS collars to compare the behavior and landscape utilization of RC and AX in a 1535-ha pasture. We tracked movements across four growing season stages with 5-minute GPS “fix” intervals. Using points correlated with foraging, we compared their average daily spatial coverage and resource selection. Preliminary spatial coverage analyses (minimum convex polygon) suggest that in the drier growing season stages, Pregreenup and Drydown, RC foraged over more ground than AX on an average daily basis. Resource selection functions (RSFs) are a general class of functions that predict the probability of use of various resources in a sampling area. Preliminary RSFs estimated using logistic regression suggest that during the drier seasonal stages, the probability that RC will select vegetation types and ecological states with dense honey mesquite is greater than the probability that AX will select those vegetation types and ecological states. Further, in the drier seasonal stages, the likelihood that RC will forage further from permanent watering points is higher than for AX. We did not collect data about direct environmental impacts or agricultural production of the two cattle types during the study; however, a cattle type that forages further from water and selects mesquite patches may help agricultural producers in the arid Southwest weather droughts with less supplemental feed. Many questions remain for the Common Experiment; however, these preliminary results suggest that an agricultural system based on RC may be more likely than "business as usual" to simultaneously increase production and reduce environmental impacts.