Final Report for SW09-054
Cattle distribution patterns and associated DNA samples from tracked cows were analyzed using High Density Single Nucleotide Polymorphism (SNP) technology. One genetic marker overlaid a gene that has been reported to be a factor in feeding behavior, appetite and locomotion, and it accounted for 25% of the phenotypic variation in use of steep slopes and high elevations. A smaller SNP panel was developed and confirmed that multiple genetic markers could explain 10% to 26% of phenotypic variation in terrain use. Associations between terrain use indices and multiple genetic markers near candidate genes clearly show that cattle grazing distribution is inherited.
1) Evaluate the extent that genetics influence cattle distribution.
1a) Determine if cattle that use rugged terrain far from water are familialy related.
1b) Determine if cattle that use gentle terrain near water are familialy related.
2) Determine if the propensity for cows to use rugged terrain can be identified from the behavior of the bull that sired it.
3) Use identification and selection of adapted cattle at cooperating ranches as a forum and demonstration to train ranchers to develop and implement site-specific grazing management practices.
A key tenant in grazing management is livestock distribution (Holechek 1988). Most of the concerns associated with livestock grazing are the result of undesirable grazing distribution rather than stocking rate (Bailey 2005). Cattle are selective and respond to abiotic and biotic factors in their decisions of where to graze (Bailey et al. 1996). Abiotic factors such as slope, elevation and distance to water constrain where cattle choose to graze. Typically cattle prefer to graze gentle slopes near water and avoid steep slopes, high elevations and areas far from water (Roath and Krueger 1982; Holechek 1988). Biotic factors associated with quantity and quality of forage affect selectivity within these abiotic constraints (Senft et al. 1987). Fortunately, dietary and distribution preferences of livestock vary greatly among individual animals.
While most cattle are bottom dwellers and graze gentle terrain near water, some cattle are hill climbers and readily travel long distances from water and utilize steep and rugged terrain (Bailey et al. 2004, 2006). Transferring grazing use to rougher terrain and areas far from water usually reduces overgrazing, protects habitat, minimizes erosion and potentially allows ranchers to sustainably increase stocking rates by using previously ungrazed forage (Bailey 2005). If the grazing intensity is kept at light levels, cattle grazing on steep slopes does not result in accelerated erosion or reduction in rangeland health (Trimble and Mendel 1995, Moir et al. 2000).
Selecting cattle that use steeper slopes, higher elevations and areas far from water (hill climbers) and/or culling cows that use gentle slopes near water (bottom dwellers) may be a cost-effective approach to improve uniformity of grazing distribution (Roath and Krueger 1982). In contrast to Mosley (2005), Bailey et al. (2006, SARE SW98-064) found that selection has the potential to improve uniformity of grazing. Riparian areas in pastures grazed by hill climbers had higher stubble heights and more uniform utilization than pastures grazed by bottom dwellers. Grazing distribution is affected by animal factors such breed (Van Waggoner et al. 2006) and environmental factors such as learning and experience (Bailey et al. 2010). However, there have been no studies to document that grazing distribution and terrain use can be inherited. This is important, since selection will be much more effective for heritable traits (Falconer 1981). Selecting bulls with superior genotypes will result in more progress than culling cows that are very undesirable. Walker (1995) argued that the only way to change the grazing habits of livestock is to work on genetics. Now, 17 years later, as a result of this project (SW09-054), we have finally completed the groundwork needed to develop tools that ranchers can use to manipulate the genetic potential of beef cattle for superior grazing distribution.
Bailey, D.W. 2005. Identification and creation of optimum habitat conditions for livestock. Rangeland Ecology & Management 58:109-118.
Bailey, D.W., J.E. Gross, E.A. Laca, L.R. Rittenhouse, M.B. Coughenour, D. M. Swift, and P.L. Sims. 1996. Mechanisms that result in large herbivore grazing distribution patterns. Journal of Range Management 49:386-400.
Bailey, D. W., M. R. Keil, and L. R. Rittenhouse. 2004. Research observation: Daily movement patterns of hill climbing and bottom dwelling cows. Journal of Range Management 57:20-28.
Bailey, D.W., H C. VanWagoner, and R. Weinmeister. 2006. Individual animal selection has the potential to improve uniformity of grazing on foothill rangeland. Rangeland Ecology & Management 59:351-358.
Bailey, D.W., M.G. Thomas, J.W. Walker, B.K. Witmore, and D. Tolleson. 2010. Effect of previous experience on grazing patterns and diet selection of Brangus cows in the Chihuahuan Desert. Rangeland Ecology & Management 63:223-232.
Falconer, D. S. 1981. Introduction to quantitative genetics. London, UK: Longman. 340 p.
Holechek, J.L. 1988. An approach for setting the stocking rate. Rangelands 10(1):10-14.
Moir, W., J. Ludwig, and R. Scholes. 2000. Soil erosion and vegetation in grasslands of the Peloncillo Mountains, New Mexico. Soil Science Society of America journal 64:1055-1067.
Mosely, J.C. 2005. Influence of social hierarchy on distribution of rangeland cattle. CRIS Hatch Project MONB00206 Report.
Roath, L.R., and W.C. Krueger. 1982. Cattle grazing and behavior on a forested range. Journal of Range Management 35:332-338.
Senft, R. L., M. B. Coughenour, D. W. Bailey, L. R. Rittenhouse, O. E. Sala, and D. M. Swift. 1987. Large herbivore foraging and ecological hierarchies. BioScience 37:789-799.
Trimble, S. W., and A. C. Mendel. 1995. The cow as a geomorphic agent—a critical review. Geomorphology 13:233-253.
VanWagoner, H.C., D.W. Bailey, D.D. Kress, D.C. Anderson, and K.C. Davis. 2006. Differences among beef sire breeds and relationships between terrain use and performance when daughters graze foothill rangelands as cows. Applied Animal Behaviour Science 97:105-121.
Cattle were tracked at seven ranches in New Mexico, Arizona and Montana. The first ranch was the Hartley Ranch in northeastern New Mexico, near Roy, NM. Terrain was rugged. Nine Angus and Angus cross heifers were randomly selected from a herd of 25 and tracked with GPS Lotek 174 3300 collars. Heifers were tracked from November 2009 to March 2010 (112 days). All heifers were raised in these pastures.
The study site was the Todd Ranch. The ranch is at the southern end of the Winchester Mountains near Willcox, Arizona. The pasture was approximately 9,065 ha and had very diverse terrain. Nineteen cows were selected from a herd of 250 mature Limousin cows and collared with GPS Lotek 174 3300 Collars. Cows were tracked during late winter to late spring of 2011.
Observations were recorded on three different occasions at the Corona Range and Livestock Research Center (CRLRC), a 11,285-ha working ranch laboratory located approximately 13 km east of the village of Corona, NM. The East Johnson and South Johnson pastures were used for this study and are located at the east end of the CRLRC. The East Johnson pasture is 1,601-ha and South Johnson is 721-ha. Terrain in this area is variable, but generally gentle with rolling hills, undulating plains, limestone sinkholes and limestone outcrops. During the summer of 2010, 17 cows of 120 Angus and Angus x Hereford cows were randomly selected and collared with GPS Lotek 174 3300 collars for tracking. Cows were tracked from May 17, 2010 to July 19, 2010 (63 days). During the same time period that cows were being tracked with GPS collars, horseback visual observations were recorded as well. In the summer of 2011, the herd consisted of 110 Angus and Angus x Hereford cross cow-calf pairs. The cows that ranked as extremes in the overall rank (HC and BD) from the 2010 visual observations were tracked from May 15, 2011 to June 24, 2011 (40 days) using GPS Lotek 174 3300 collars. Seven HC and six BD were tracked in 2011. GPS tracking was conducted during the breeding season in both 2010 and 2011. Corresponding, there were seven bulls in the pasture during 2010 and six bulls in 2011. Bulls were also collared and tracked as part of another study. All GPS collars recorded positions every 10 minutes. In 2012, 28 randomly-selected cows out of approximately 120 cows were tracked at five minute intervals for 51 days from late June to mid-August.
Observations were recorded at the Chihuahuan Desert Rangeland Research Center (CDRRC) on two occasions. The CDRRC is located approximately 37 km north of Las Cruces, New Mexico. The study was conducted in 3,990-ha pasture with only one water source in 2011. Terrain in the pasture is moderately flat with rolling hills and many arroyos at the base of small ridges. Sixteen cows were tracked for 33 days from late June to early August. In the winter of 2012/2013, 18 cows were tracked in the 3990 ha pastures used in 2011 and a second 2830 ha pasture with two water sources. Cows were tracked for 38 days in December and January.
The Thackeray Ranch is located near Havre, MT. The study pasture (Back Pasture) was 336 ha and contained rugged terrain. Nineteen cows out of 213 mature cow-calf pairs were collared with GPS Lotek 174 3300 collars and tracked from August 11, 2011 to September 4, 2011 (25 days). Positions were recorded every 10 minutes. Cows were crossbred with Simmental, Tarentaise and Hereford breeding.
The Carter Brangus Ranch located near Thatcher, AZ. Twelve Brangus cows were tracked for 75 days at 15 minute intervals from mid-October 2011 to early January 2012. The study pasture was 4184 ha with gentle and rolling terrain and five water sources.
The Evans Ranch (C Bar Ranch) is located near Silver City, NM. The study pasture was 2563 ha of mountainous terrain with two water sources. Sixteen Angus cows were randomly selected from a herd of approximately 80 cows and tracked at 10 minute intervals for 59 days from late August 2012 to late October 2012.
A Digital Elevation Model (DEM) was derived from USGS Seamless Data Warehouse (seamless.usgs.gov) for each study site and was added as a layer in ArcGIS software. Percent slope was derived from the DEM layer by using the Spatial Analyst Extension in ArcMap tools (www.esri.com). Watering point locations were added as a layer, and distance from each drinker was derived using ArcMap tools (www.esri.com). Average slope and elevation use and average distance from water were calculated for individual cows using all recorded positions during the tracking period by extracting elevation, slope and distance from water from layers in ArcMap using the Spatial Analyst Extension.
Individual cows from each ranch were ranked by an index identified as “rough” which is a “normalized average” of elevation and slope. The mean elevation of each cow was divided by average elevation use of all cows tracked at a study site (ranch) and multiplied by 100. Similarly, mean slope use of each cow was divided by the average slope use of all cows tracked at a study site and multiplied by 100. The corresponding products associated for elevation and slope for each cow were then averaged. The rough index reflects relative differences in elevation and slope use for cows tracked at the same ranch. A value of 100 indicates that the mean elevation and slope use for that cow was equivalent to the average of all tracked cows. Values less than 100 correspond to gentler and/or lower terrain use than the ranch average, and values over 100 indicate use of steeper slopes and/or higher terrain. Ratio was calculated identically, but it is a normalized average of elevation, slope and distance to water. Blood was collected from every collared cow at each ranch (see attached photo). A few drops of blood were applied to free-to-air (FTA) cards for further DNA analysis (Geneseek, www.neogene.com).
For the first 80 cows tracked from 2009 to September 2011, blood samples were collected with 6 mL vacutainer tubes coated with ethylenediaminetetra-acetic acid (EDTA; Sigma, St. Louis, MO), which prevents the blood from clotting. EDTA tubes were centrifuged and white blood cell supernatant (i.e. buffy coat) recovered using procedures described by Thomas et al. (2007). Concentration of the extracted DNA was measured using a fluorometer, while quality of DNA was evaluated by gel electrophoresis to ensure high molecular weight DNA was present and intact. DNA was extracted and genotyped on the Illumina BovineHD beadchip assay (770,000; Illumina, San Diego, CA) by GeneSeek. A total of 80 cows from the Hartley Ranch (Roy, NM), Todd Ranch (Willcox, AZ), CRLRC (Corona, NM), CDRRC (Las Cruces, NM) and Thackeray Ranch (Havre, MT) were evaluated with the the Illumina Bovine SNPHD array.
Using the results from the Illumina Bovine SNPHD array evaluated using DNA from the 80 cows identified above, genome-wide genotype to phenotype association analysis was conducted to determine if locations along the bovine chromosome (single nucleotide polymorphisms) are associated with terrain use traits. Roughly, 770,000 single nucleotide polymorphisms (SNP) equally spaced along 29 somatic chromosomes and X/Y chromosome were simultaneously evaluated. Genotyping results and phenotypes were processed and analyzed with SNP Variation Suite 7 software (SVS) from Golden Helix (Bozeman, Montana). The analysis strategy was similar to studies of Luna-Nevarez et al. (2011) and Wickramasinghe et al. (2011). Marker-trait association analysis was performed using a linear regression test under additive, dominant and recessive model assumptions. Statistical analyses were performed using the genotype association and regression modules from SVS. A similar approach was successfully used to analyze tag SNP on BTA4 associated with milk production traits (Rincon et al. 2009b) and to analyze the association of tag SNP within the bovine STAT6 gene and carcass traits in feedlot cattle (Rincon et al. 2009a). In brief, the adjusted phenotype, y, is fit to every encoded genotype under a model assumption, x, and is represented with the following equation:
y = b1x + b0 + e,
where y is the adjusted phenotype, b1x + b0 represents the model and the error term, e, expresses the random residual effect.
A smaller SNP panel was developed based on the results from the Illumina Bovine SNPHD array analyses. Fifty SNP were selected at or near loci determined to be important in the SNPHD analyses and incorporated into a new smaller, less expensive panel. For the second analyses, an additional 78 cows from the Carter Brangus Ranch, Evans Ranch, CRLRC and CDRRC were added to the 80 cows used in the first analyses. All DNA for the second, smaller panel was obtained from the samples obtained in the FTA cards and were separate DNA samples from the first analyses.
Similar to the analyses for the Illumina Bovine SNPHD panel genotype data, marker-trait association analyses were performed on the 50-SNP panel genotype data using a linear regression test assuming an additive model. All analyses were performed using the genotype association and regression modules from SNP Variation Suite (SVS7) version 7 (Golden Helix Inc., Bozeman MT) as described in Rincon et al. (2009b). The model used for the regression analysis was identical to the equation above. A P-value threshold of 0.05 was used to establish significant associations. Genotype combinations were tested to examine significantly associated markers with ratio and rough using the haplotype module. False discovery rate (FDR) was controlled according to the method of (Storey, 2002) and a cutoff for significant association values was set at FDR q-value < 0.1. Linkage disequilibrium (LD) analyses were also performed by SVS version 7 software.
Locations recorded by horseback observers from the Hartley Ranch, Thackeray Ranch and Todd Ranch were summarized similar to the GPS tracking data. The rough and ratio terrain indices were calculated for a total 109 cows (sum from the three ranches). For the Hartley and Thackeray Ranch, cows used in the analyses were observed at least seven times and at least three times at the Todd Ranch. Genotype to phenotype associations were calculated using the procedures described above.
Another analysis was conducted to evaluate the consistency of terrain use of beef cows over time. For the Hartley Ranch data, a repeated measures analysis was conducted using data from all collared heifers. Response variables were elevation, slope and distance from water averaged by week. Week was a fixed effect, and the repeated statement used heifer as the subject. Covariance between repeated records was modeled using autoregressive of order 1, compound symmetry or unstructured covariance structures (Littell et al. 1996). For the Todd Ranch data, the repeated measures analysis was identical except fixed effects were initial classification as hill climber of bottom dweller based on visual observations from horseback observers, week and the class by week interaction.
Two approaches were used to evaluate the consistency of terrain use of individual cows at both the Hartley and Todd Ranches. Weekly averages of terrain use (elevation, slope and distance to water) were used as repeated records. Covariance components obtained from the compound symmetry method were used to determine an intra-class correlation of repeated weekly averages of terrain use. The intra-class correlation was calculated by dividing the between cow component (cow) by the sum of the between cow (cow) and within cow (residual) components of variance. Using the autoregressive one method of modeling covariance model in PROC MIXED, cow was used as the subject in the repeated statement, and cow was also used as a random effect. The autoregressive procedure provided an estimate of the correlation of adjacent records. An inter-class correlation was calculated after modeling the covariance of repeated records using autoregressive one by dividing the cow component by the sum of cow and the residual.
Littell, R., G. Milliken, W. Stroup, and R. Wolfinger. 1996. SAS system for mixed models. Cary, North Carolina: SAS Institute. Inc.
Luna-Nevarez, P., G. Rincon, J. F. Medrano, D. G. Riley, C. C. Chase, Jr., S. W. Coleman, D. M. Vanleeuwen, K. L. DeAtley, A. Islas-Trejo, G. A. Silver, and M. G. Thomas. 2011. Single nucleotide polymorphisms in the growth hormone-insulin-like growth factor axis in straightbred and crossbred Angus, Brahman, and Romosinuano heifers: population genetic analyses and association of genotypes with reproductive phenotypes. Journal of Animal Science 89:926-934.
Rincon, G., E. A. Farber, C. R. Farber, J. D. Nkrumah, and J. F. Medrano. 2009a. Polymorphisms in the STAT6 gene and their association with carcass traits in feedlot cattle. Animal Genetics 40:878-882.
Rincón, G., A. Islas-Trejo, J. Casellas, E. Lipkin, M. Soller and J. F. Medrano 2009.b Fine Mapping and Association Analysis of a Quantitative Trait Locus for Milk Protein Percentage on BTA4. Journal of Dairy Science 92:758-764.
Storey, J. D. 2002. A direct approach to false discovery rates. Journal of the Royal Statistical Society: Series B (Statistical Methodology) 64:479-498.
Thomas, M., R. Enns, K. Shirley, M. Garcia, A. Garrett, and G. Silver. 2007. Associations of DNA polymorphisms in growth hormone and its transcriptional regulators with growth and carcass traits in two populations of Brangus bulls. Genetics and Molecular Research 6:222-237.
The Illumina Bovine SNPHD array evaluated approximately 770,000 genetic markers (i.e., single nucleotide polymorphisms; SNP) across the 30 bovine chromosomes. The GPS data were used to characterize use of rough terrain and areas far from water using indices based on the normalized averages of slope use, elevation use and distance to water (Ratio Index) and normalized averages of slope and elevation use (Rough Index). The Ratio Index should be more informative in extensive pastures where distance to water plays an important role in grazing distribution. The Rough Index should be more informative where steep mountainous terrain is more critical than distance to water for determining cattle grazing patterns. A chromosome region associated with these traits is known as a quantitative trait locus (QTL), and the significance is determined by the statistical association of genotypes with phenotype effects (-log10 p-value > 5). Significant QTL regions were detected on chromosomes 17 and 29 for slope and elevation (Rough Index). The variation in significance can be readily observed in a Manahattan plot (Figure 1) where values with a high negative value (-log10 p-value > 5) are significant. When these variables were combined with distance to water, QTL were detected on 11 chromosomes and a structural copy number variant was detected on chromosome 8 (Figure 2). A QTL region can span many base-pairs on a chromosome and encompass numerous genes. However, QTL analyses are a useful entry-point for identifying functional loci and potential genetic markers to help understand the genetic and physiological basis of cattle grazing distribution. One genetic marker on chromosome 29 overlaid a gene that appears to be a factor in feeding behavior, appetite and locomotion based on our physiological knowledge of its function. This location accounted for 25% of the phenotypic variation in use of steep slopes and high elevations. A variant of this gene may be useful for identifying hill climbers. The QTL on chromosome 17 accounted for 21% of the phenotypic variation in slope and elevation use (Table 1 attached). Additional QTL found on other chromosomes (Figure 3) accounted for 5 and 10% of the variation in slope and elevation use, as well as distance traveled from water (Ratio Index). These findings are very exciting, because most individual genetic markers account for only 1 or 2% of the phenotypic variation in a trait (Garrett et al., 2008; DeAtley et al., 2011; Luna-Nevarez et al., 2011).
Using the results from the Illumina Bovine SNPHD array, a smaller panel based on 50 SNP was developed and evaluated on the 80 cows tracked previously and an additional 78 cows from four ranches in Arizona and New Mexico (n=160 cows at seven ranches). Multiple genetic markers near or within the gene identified on chromosome 29 were associated with indices of terrain use and accounted for 10 to 18% of the phenotypic variation (Table 2). In addition, a marker on chromosome 4 accounted for 26% of the variation in an index based on use of steep slopes, high elevations and areas far from water. Other QTL on chromosomes 8, 12 and 17 accounted for 10 to 15% of the phenotypic variation in indices of terrain use (Table 2). Results from this evaluation of 50 selected SNP near candidate genes and QTL support the analyses from the Illumina Bovine SNPHD array. The association between indices of terrain use and multiple genetic markers near candidate genes clearly shows that grazing distribution and spatial behavior of cattle is a heritable trait.
Genotype to phenotype associations were completed for 109 cows at the CDRRC, Thackeray Ranch and Todd Ranch based on locations obtained by horseback observers. Association of multiple genetic markers and the rough and ratio terrain indices were found on chromosomes 4, 12, 17 and 29. However, only the QTL on chromosome 4 was the same as found in the Illumina Bovine HDSNP genotyping. Visual tracking data from cows other than those tracked with GPS collars supported the genotype to phenotype association found on chromosome 4. With the limited amount of visually recorded data, especially at the Todd Ranch, it is not surprising that results from this data varied from that recorded by GPS collars.
Differences in grazing patterns among individual cows were often pronounced. Figure 4 (attached) shows grazing patterns of two yearling heifers at the Hartley Ranch from November 2009 to March 2010. One heifer (cyan dots) had the favorable genotype for chromosome 29 and the other heifer (pink dots) did not. Similar differences in grazing patterns of hill climber and bottom dweller cows were observed by Bailey et al. (2004).
The consistency of terrain use at the Hartley and Todd Ranches was relatively high for elevation and moderate for slope, but it was lower for distance traveled from water. At the Hartley Ranch, the intra-class correlation of elevation use was 0.61 using the typical compound symmetry approach, but for distance to water it was only 0.18 (Table 3). Adjacent records were typically more related than other records. The intra-class correlation of elevation use at the Todd Ranch using the typical intra-class correlation method was 0.71. Adjacent records of elevation use were surprisingly less correlated (0.60) than other records (Table 3). Slope use was relatively consistent among cows with a typical intra-class correlation of 0.30. Slope use was relatively consistent during adjacent weeks at the Todd Ranch (0.30 typical intraclass correlation), and adjacent records were similarly related to non-adjacent records. Intra-class correlations (Table 3), especially for elevation use, also indicated terrain use when evaluated as weekly means was relatively consistent.
Overall terrain use by beef cattle is temporally variable and large phenotypic differences exist among individuals when grazing extensive and/or rugged rangeland pastures. There are relatively consistent grazing patterns that exist among cattle which can be used to characterize their grazing behavior (e.g. hill climbers and bottom dwellers). This suggests that cattle grazing distribution varies considerably. In addition to extremes in terrain use, most cows are in the middle of the expected normal distribution (bell) curve. By identifying and selecting cattle that utilize rugged terrain and areas far from water and culling cows that use gentle terrain near water, ranchers may be able to minimize areas of concentrated heavy grazing and perhaps sustainably increasing stocking rates.
We also found that bull grazing patterns during the breeding season were highly influenced by movements of the cow herd and estrus activity. The distance that bulls traveled each day increased about 20 days after cows were synchronized for estrus. Bulls followed the cows and the measures of their terrain use (e.g., distance from water and slope use) were similar to cows. Outside of the breeding season, bulls are typically kept together. Since there are only a small number of bulls at most ranches, the bulls typically move together. Correspondingly, tracking data from bulls during periods outside the breeding season are expected to be similar. Results from this study suggest that terrain use of bulls will not be a reliable indicator of the terrain use of their daughters.
Bailey, D. W., M. R. Keil, and L. R. Rittenhouse. 2004. Research observation: Daily movement patterns of hill climbing and bottom dwelling cows. Journal of Range Management 57:20-28.
DeAtley, K. L., G. Rincon, C. R. Farber, J. F. Medrano, P. Luna-Nevarez, R. M. Enns, D. M. VanLeeuwen, G. A. Silver, and M. G. Thomas. 2011. Genetic analyses involving microsatellite ETH10 genotypes on bovine chromosome 5 and performance trait measures in Angus- and Brahman-influenced cattle. Journal of Animal Science 89:2031-2041.
Garrett, A. J., G. Rincon, J. F. Medrano, M. A. Elzo, G. A. Silver, and M. G. Thomas. 2008. Promoter region of the bovine growth hormone receptor gene: single nucleotide polymorphism discovery in cattle and association with performance in Brangus bulls. Journal of Animal Science 86:3315-3323.
- Table 1 Assoication analysis from Illumina HDSNK
- Table 2. Assoication analysis from small 50 SNP panel
- Table 3. Intraclass correlations of weekly terrain use
- Figure 1. Manhattan plot of Rough Index
- Figure 4. Grazing patterns of hill climber and bottom dweller heifers at Harltey Ranch
- Figure 2. Manhattan plot for CNV of Rough Index
- Figure 3. Manhattan plot of Rato Index
This is the first study to conduct genotype to phenotype association studies of difficult to measure quantitative production traits that are important for rangeland sustainability. DNA was obtained from 80 beef cows that were tracked in mountainous and/or extensive rangeland pastures. The DNA was used for high density genotyping (Illumina BovineSNPHD; ~770,000 genotypes/cow) while the GPS data were used to characterize use of rough terrain and areas far from water using indices based on the normalized averages of slope use, elevation use and distance to water. Associations between genetic markers on chromosome 29, 17, 4 and others were identified. The strength of these associations was greater than typically found for QTL for other traits. A smaller and less expensive 50 SNP panel was developed for genetic markers that were important in the HDSNP analyses, including several nearby makers. The number of cattle evaluated in the second analysis (50 SNP) was doubled. The genotype to phenotype associations were detected in the second analyses similar to those found with the Illumina Bovine HDSNP panel. Although tracking data recorded by horseback observers is clearly less accurate and precise than GPS data, results from data collected from independent cows support that the genetic marker on chromosome 4 is clearly an important QTL for grazing distribution. The genotype to phenotype associations identified by candidate genes and other QTL clearly show that grazing distribution is inherited and genetic selection is very promising tool to improve distribution. This work also highlights the value of combining genomic information with accurate grazing distribution phenotypes to understand the biology of cattle foraging behavior.
The success of the smaller targeted SNP panel shows that we can potentially identify cattle with desirable and undesirable genotype for a reasonable cost. Note: this would be without the need for time consuming measures of grazing behavior or expensive GPS tracking collars. This research is the first step of a process to develop a DNA test for identifying cattle with superior genotypes for grazing distribution, and more importantly, a molecular breeding value that ranchers can use to select cattle for grazing distribution. The molecular breeding value could be used similar to Estimated Progeny Differences (EPD) that are used for cattle selection across the U.S. Cattle breeders in the western U.S. could begin to develop cattle specifically adapted to sustainably use extensive and rugged pastures (a new niche market). Workshops in Arizona showed that well over 75% of rancher participants would be willing to spend additional money on bulls with superior genotypes for grazing distribution.
Grazing distribution is a critical factor in rangeland management. Many of the issues associated with cattle grazing on both public and private lands are associated with undesirable grazing distribution patterns. This project and an earlier Western SARE-funded project show that individual cattle can have very different grazing patterns. If cattle with undesirable grazing patterns are culled and cattle with desirable grazing patterns are selected, most livestock grazing concerns can be alleviated and producers can potentially increase stocking levels while maintaining rangeland health. However, it was critical to know if a trait is heritable to before implementing a selection program. This study has established that cattle grazing distribution can be inherited. Although more data is needed to verify this study, our results suggest that the heritability for cattle use of steep slopes and high elevations is at least 25%. This level of heritability is similar to weaning weight, which producers have selected for years.
Education and Outreach
Preliminary results from this research were presented at the annual meeting of the New Mexico Section of the Society for Range Management on January 5, 2012 in Socorro, NM. Five ranchers and 20 land managers attended the meeting.
Results from this project were also presented at the Southwest Beef Symposium in Roswell, NM on January 17-18, 2012. Over 40 ranchers from New Mexico and west Texas attended the symposium.
On December 6 and 7, 2012, results from this study were highlighted at the Managed Grazing of Beef Cattle on Arizona Rangelands Workshop in Willcox and Payson, Arizona (respectively). The Willcox workshop had 24 participants (primarily ranchers) and the Payson workshop had 37 participants, and included ranchers and a few land managers from the Forest Service. The agenda for the Willcox, AZ workshop is attached (almost identical to Payson, AZ workshop). A letter from the workshop organizer, Dr. Jim Sprinkle, is attached.
Symposium at the 66th Annual Meeting of the Society for Range Management, Oklahoma City, OK entitled “Targeted Grazing: Management of Livestock Distribution,” see attached request and agenda. The first half day of this symposium (morning) was focused on this Western SARE-funded project. In the morning session, 48 people attended, and in the afternoon 80 people attended this symposium.
On May 22, 2013, we made a presentation at the “Strategic & Targeted Grazing as Vegetation Management Tools - A Symposium” in Elko, NV. Over 80 people attended (see attached agenda). There was roughly an equal split between ranchers and federal land management personnel (BLM, Forest Service and NRCS). Six of 42 respondents in a survey of participants at the symposium identified that the potential to use genetic selection to improve cattle use of rough terrain was the most important thing they learned at the symposium. This response rate was impressive considering that genetics of distribution was 1 of 13 presentations, and this potential practice requires more research and development.
Field Tours were conducted in Willcox, AZ and Silver City, NM on June 20 and 21, 2013, respectively. A flyer summarizing the activities is attached. Twenty-one people attended the Willcox tour, primarily ranchers with a few from BLM and the Forest Service. Twelve people attended the Silver City tour; two ranchers, four land management agencies and six university personnel. On June 25, 2013, we conducted a one-day workshop at the Southwestern Center for Rangeland Sustainability in Corona, NM (see attached flyer). Twenty five people attended the workshop in Corona. A handout (fact sheet) was developed for the field tours and workshop (see attached). Based on the evaluations of the June 2013 field tours and workshop, the attendees increased (P < 0.001) their overall knowledge and skills from an average initial value of 1.9 to an average ending value of 2.6, where 1 is low, 2 is medium and 3 is high.
Stephenson, M.B. and D.W. Bailey. 2014. Association patterns of visually- observed and GPS- tracked cattle grazing mountainous and extensive rangelands. In preparation for submission to Applied Animal Behaviour Science (expect to submit in May 2014).
Bailey, D.W., D. Jensen, M.G. Thomas, D. Boss, and R. Welling. 2012. Genetic and environmental influences on movement patterns of beef cattle grazing foothill rangeland. In preparation for submission to Rangeland Ecology and Management (expect to submit in March 2014).
Lipka A., Bailey D. W., Thomas M.G., Lunt S. Movement patterns of beef bulls grazing extensive rangelands during the breeding season. In preparation for submission to Applied Animal Behaviour Science. (expect to submit in January 2014).
Lunt S., Bailey D. W., Thomas M.G., Lipka A. Consistency of terrain use in beef cattle grazing rugged rangelands. In preparation for submission to Applied Animal Behaviour Science (expect to submit in November 2013).
Bailey D. W., Thomas M.G., Medrano J.F., Cánovas A., Rincon G., Lunt S., Lipka A., Stephenson M. B. Association of high density genetic markers and terrain use in beef cows grazing mountainous and extensive rangelands. In preparation for submission to Rangeland Ecology and Management (expect to submit in October 2013.
Bailey D. W., Thomas M.G., Medrano J.F., Cánovas A., Rincon G., Lunt S., Lipka A., Stephenson M. B. 2014. Association of high density genetic markers and terrain use in beef cows. Abstract from the 67th Annual Meeting of the Society for Range Management; February, 2014; Orlando, FL, USA. (submitted)
Stephenson, M.B. and D.W. Bailey. 2014. Association patterns of visually- observed and GPS- tracked cattle in the western United States. Abstract from the 67th Annual Meeting of the Society for Range Management; February, 2014; Orlando, FL, USA. (submitted)
Bailey, D. W., M. Stephenson, M. G. Thomas, J. F. Medrano, G. Rincon. 2013. Manipulation of the spatial grazing behaviour of livestock in extensive grassland systems. Proceedings of the International Grassland Congress; September 16-19, 2013; Sydney Australia (in press).
Bailey, D. W., M. Stephenson, M. G. Thomas, J. F. Medrano, G. Rincon, A. Cánovas, S. Lunt, and A. Lipka. 2013. Manipulation of the spatial grazing behaviour of cattle in extensive and mountainous rangelands. 17th International Meeting of the FAO-CIHEAM Mountain Pasture Network; June 5 – 7, 2013; Trivero, Italy. (attached)
Lunt, S. T. 2013. Modifying individual grazing distribution patterns of cows in extensive rangeland pastures through genetic selection [MS Thesis]. Las Cruces, NM: New Mexico State University. 117 p.
Bailey, D. and L. Howery. 2013. Introduction – Why worry about grazing distribution? Abstract from the 66th Annual Meeting of the Society for Range Management; February 3 - February 7, 2013; Oklahoma City, OK, USA.
Bailey, D., M. Thomas, S. Lunt and A. Lipka. 2013. Selection for cattle adapted for sustainable use of extensive rugged rangeland: Part 1 - Understanding important phenotypes. Abstract from the 66th Annual Meeting of the Society for Range Management; February 3 - February 7, 2013; Oklahoma City, OK, USA.
Thomas, M., G. Rincon, J. Medrano, and D. Bailey. 2013. Selection of cattle adapted for sustainable use of extensive rugged rangelands: Part 2 – What we can learn from the genotype. Abstract from the 66th Annual Meeting of the Society for Range Management; February 3 - February 7, 2013; Oklahoma City, OK, USA.
Bailey, D., D. Jensen, M. Thomas, D. Boss, and R. Welling. 2012. Genetic and environmental influences on movement patterns of beef cattle grazing foothill rangeland. Phoenix, AZ: 2012 Annual Meeting American Society of Animal Science. J. Animal. Sci. 90 (Suppl. 3):454.
Lipka, A., D. Bailey, S. Lunt, M. Thomas, S. Cox and R. Dunlap. 2012. Landscape use and movement patterns of beef cows and bulls during the breeding season. Abstract from the 65th Annual Meeting of the Society for Range Management; January 28 - February 2, 2012; Spokane, WA USA.
Lunt, S., D. Bailey, M. Thomas and A. Lipka. 2012. Individual grazing distribution patterns of cattle in the Winchester Mountains of southeastern Arizona. Abstract from the 65th Annual Meeting of the Society for Range Management; January 28 - February 2, 2012; Spokane, WA USA.
Bailey, D. W., M. G. Thomas, and L. D. Howery. 2011. Manipulation of cattle grazing on rangelands of the southwestern United States. Abstract of key note presentation from the 2011 Australia and New Zealand Spatially Enabled Livestock Management Symposium; September 29, 2011; Surfers Paradise, Queensland, Australia.
Bailey, D., D. Jensen, M. Thomas, D. Boss, R. Weinmeister and R. Welling. 2011. Genetic and environmental influences on distribution patterns of beef cattle grazing foothill rangeland. Abstract from the 64th Annual Meeting of the Society for Range Management; February 6-10, 2011; Billings, MT USA.
Lipka, A., D. Bailey, S. Lunt, M. Thomas, M. Russell, S. Cox and R. Dunlap. 2011. Grazing distribution patterns of beef bulls and cows during the breeding season in central New Mexico. Abstract from the 64th Annual Meeting of the Society for Range Management; February 6-10, 2011; Billings, MT USA.
Lunt, S., D. Bailey, A. Lipka, M. Thomas and M. Russell. 2011. Accuracy of cattle grazing distribution patterns recorded by horseback visual observers during the early morning. Abstract from the 64th Annual Meeting of the Society for Range Management; February 6-10, 2011; Billings, MT USA.
- Cooperator Dick Evans (center) giving presentation at Silver City NM field tour
- Poster presented at UC Davis research meeting
- Agenda for Targeted Grazing Symposium in Elko NV
- 2013 Fiedl Tours flyer
- Field tour and workshop handout & fact sheet
- Agenda for Range Nutrition Workshop in Willcox AZ in December 2012
- Thank you letter for Arizona Range Nutrition workshop Dec 2012
- Proceedings of Mountain Pastures Network meeting Turin Italy
- Flyer for Corona NM workshop
- Cooperator Tom Todd (right) and participants at field tour in Willcox AZ
Education and Outreach Outcomes
Areas needing additional study
Results from this study need to be verified with additional data. These results are very exciting. However, genomic studies typically involve measures from over 500 animals. An additional genotype to phenotype association study for grazing distribution is needed. Genetic markers identified in this study as having strong associations with indices of terrain use must have similar relationships with grazing distribution from cattle from other ranches.
If these results are verified in other herds, the next step is to develop a molecular breeding value for grazing distribution. Estimated progeny differences (EPDs) could be developed for indices for terrain use. Terrain use EPDs would provide ranchers the tool to readily rank bulls in their potential to sire daughters that would be more willing to use rough terrain and travel far from water. The ranchers could begin to integrate terrain use and grazing distribution into their cattle selection and breeding programs.