Study area description
This study was conducted at the Jornada Experimental Range (JER;
32°37’ N; 106° 40’ W), approximately 40 km north of Las Cruces,
New Mexico, USA. The JER is approximately 78,104 ha and our
experiment pasture was approximately 3,215 ha in size with an
average elevation of 1,200 m. The JER is located in the northern
portion of the Chihuahuan Desert between the Rio Grande River to
the west and the San Andres mountain range to the east, where the
climate is arid with warm summers and mild winters, and an average
of about 230 frost-free days. The average annual temperature is
16.9°C and average annual precipitation is approximately 248 mm.
Rainfall events primarily occur during the monsoon season (July
through September). Soils of the north western JER are
predominantly of the Berino-Bucklebar association (sandy) and
vegetation of the study area includes perennial grasses such as
black grama (Bouteloua eriopoda Torr.), dropseeds (Sporobolus
spp.), threeawns (Aristida spp.), tobosa (Pleuraphis mutica
Buckley), and burrograss (Schleropogon brevifolius Phil.). Shrubs
of our study area include honey mesquite (Prosopis glandulosa
Torr.), Soap-tree yucca (Yucca elata Engelm.), broom snakeweed
(Gutierrezia sarothrae [Pursh] Britton & Rusby), creosote bush
(Larrea tridentate [DC.]) and fourwing saltbush (Atriplex
canescens [Pursh] Nutt.).
Study area descriptions are provided by Spiegal et al. (2019).
Four permanent drinkers and five dirt tanks (ephemeral water
during late summer) were present in this pasture that was also
intersected by a network of dirt roads as well as six small
grazing exclosures. Most of the pasture (99.63%) was within 3.2 km
(2 mi) from a drinker-watering source, the point at which cattle
use begins to diminish (Holechek, 1991).
Animals
Animal handling protocols were approved by the New Mexico State
University Institutional Animal Care and Use Committee (Protocol
2016-019). Two cohorts of yearling steers totaling 57 Jornada
Rarámuri Criollo (JRC), Criollo × beef breed crossbreds (XC) and
Mexican Criollo (MC; examples provided in Figure 1) were monitored
over a two-and-a-halfyear period (December 2015 – January 2017)
for weight gain and grazing behavior (Table 1). Jornada Rarámuri
Criollo steers in this study were sourced from the USDA-ARS
Jornada Experimental Range purebred herd, which was imported to
the ranch from the Chiapas – Temeris region of the Copper Canyon,
México in 2005. Mexican Criollo (those not from the JER herd) used
in this study were sourced from two Mexican ranches: Rancho el
Nogal in Yeppachi, Chihuahua (cohort 1; C1) and Rancho Las Mesas
de Las Borregas in Cuauhtémoc, Chihuahua (cohort 2; C2). Genotype
history of the Mexican Criollo used in this study is unknown and
it is likely that the MC evaluated were genotypically similar to
the JRC. However, due to the difficult-to-obtain nature of the
Rarámuri Criollo from the Copper Canyon (Anderson et al., 2015)
and the fact that larger framed MC are relatively easier to
obtain, their evaluation alongside the JRC herd is of great
interest to a growing number of ranchers across the American
Southwest who are seeking to raise larger-framed Mexican Criollo
cattle.
The crossbreds available to conduct our study were Criollo ×
Waguli (cohort 1; sired by Criollo bulls on Waguli cows) and
Criollo × Brangus (cohort 2; sired by Brangus bulls on Criollo
cows) owned by two cooperating ranches: 47 Ranch, Bisbee, Arizona,
USA and Evergreen Ranching, Black Hills, South Dakota, USA. Beef
breeds used as crosses in this study differed between cohorts, but
we reasoned that their genotypic parentage was suitable for
replication because each are characterized by similar breed
development histories and 9 phenotypes. Waguli cattle were
developed by the University of Arizona by crossing a Bos indicus
based breed (Tuli) with an improved beef breed (Wagyu) in an
attempt to create an animal that exhibited both high quality
carcass and growth traits as well as heat tolerance (Garcia, 2013;
Ibrahim et al., 2008). Brangus, too, were developed, originally,
by the USDA – ARS station in Jeanerette, Louisiana by crossing a
Bos indicus based breed (Brahman) with an improved beef breed
(Angus; USDA, 1935) with the same goal of creating a heat-tolerant
and high yielding animal. Though limited, studies that have
compared Waguli to Brangus steer growth and carcass traits have
shown few breed differences between mature weights, feed to gain
ratios, dressing percentages, or other carcass merits (Garcia,
2013).
Steers were maintained on rangeland until 30 months of age to
allow animals time to mature to slaughter weight. Few differences
in major carcass grades and quality have been found in 30-month
old steers developed in intensive vs. extensive production systems
(Keane and Allen, 1998). Additionally, USDA 69 FR 1984 prohibits
use of vertebral columns or skulls of cattle older than 30 months
of age in Advanced Meat/Bone Separation Machinery (Coffey et al.,
2005).
The recommended stocking rate for our study area is 5.14 ha •
AUM-1 (USDA-NRCS 2017) and fewer than 30 steers, all weighing less
than 500 kg, were placed in our 3,215 ha experiment pasture at any
point during this experiment. Thus, our study pasture was lightly
stocked at all times. During the month prior to shipping, steers
of each cohort were placed in smaller pastures and were provided
ad libitum triticale hay.
Steers of both cohorts entered the trial with different weights
(Table 1). Crossbred steers in cohort 1 had heavier initial weighs
(312.7 ± 6.7 kg) than MC steers (299.1 ± 3.8 kg) and JRC steers
(274.2 ± 4.0 kg; Table 1). Cohort 2 JRC steers had similar weights
(233.7 ± 6.4 kg) of XC counterparts (231.4 ± 11.53 kg) and both of
these were heavier than MC steers (179.9 ± 6.7 kg) at the onset of
the study in cohort 2 (Table 1). Steers in both cohorts were
weighed individually at approximately two-month intervals to the
nearest half kilogram using a manual balance (Buffalo Scale Co.).
Steers were fasted in pens overnight prior to weighing. Steers
from C1 were shipped to the University of Arizona campus farm on
January 09, 2017 and slaughtered shortly after on January 10,
2017. No meat quality data were available for steers in this
cohort. Steers from C2 were shipped to Evergreen Ranch in Custer,
South Dakota on February 1, 2018 where they were fed western
wheat/ brome/ sweet clover grass-hay for approximately one month
before being transported to Sturgis Meats in Sturgis, SD, USA and
slaughtered on February 28, 2018. Subsequent analyses of carcass
characteristics were performed by trained South Dakota State
University personnel; C2 JRC, MC, and XC steers were analyzed for
hot and cold carcass weights (kg), cooler shrink (%), adjusted
preliminary yield grade, percent of kidney-pelvic-heart fat,
ribeye area (cm2), yield grade, and marbling score.
A subset of randomly selected JRC and XC steers within each
cohort, and season were fitted with GPS collars (Lotek 3300, Lotek
Wireless New Market Ontario, Canada) and monitored during winter
(dormant vegetation) and late summer (end of growing season; Table
1). Collar GPS receivers were configured to log geolocation data
at 5-min intervals. Grazing behavior of JRC and XC animals in both
cohorts was monitored via GPS during winter and late summer (Table
1 and Figure 4).
Data Processing
GPS data collected during four periods over the course of this
study were used to calculate 26 behavior variables including
distance traveled, path sinuosity, area explored, activity
(grazing, resting, traveling, travel: graze ratio), drinking
behavior (time at water, time near water, and drinking frequency),
and pasture use patterns (Table 2). The first two response
variables were calculated for four daily time periods (night
pre-dawn hours, daytime hours, night post sunset hours, and 24 h
[day + night]) using a Java program (GRAZEACT) tested by Sawalhah
et al. (2016; Gong et al., 2020). The Pythagorean Theorem was used
to calculate distance traveled between two subsequent GPS points.
Path sinuosity was inferred using the straightness index
(Batschelet, 1981) that reflects the ratio of the distance between
the first and last points for any time period and cumulative
distances between consecutive points for the same period. A
straightness index equal to zero indicates a highly sinuous path
whereas an index equaling one indicates a straight path
(Batschelet, 1981). The straightness index is a reliable indicator
of tortuosity of a random search path (Benhamou, 1992). GRAZEACT
was used to estimate area explored for the same four daily time
periods (24-hour, pre-dawn, daytime, post-sunset). Area explored
was calculated as a minimum convex polygon (MCP) using a convex
hull algorithm designed to encompass an individual animal’s
locations with internal angles less than 180 degrees.
Activities including resting (movement velocity < 2.34 m •
min-1), traveling (velocities > 25 m • min-1), and grazing
(velocities > 2.34 m • min-1 and < 25 m • min-1) were
extracted using parameters tested by Nyamuryekung’e et al. (2020)
that were partially adapted from Augustine et al. (2013).
Corresponding activities were assigned to each GPS point based on
its velocity and overall activity budget was calculated by
multiplying the number of GPS points classified into each activity
class by fix time interval (5 min) and converted to h x day-1. A
second Java program (GRAZEPIX) tested by Sawalhah et al. (2016)
and described by Gong et al. (2020) was utilized to evaluate
pasture use patterns. This software created a 30-m2 pixel grid
(50,841 total grid cells) of our study pasture and overlaid GPS
fix locations where animals were presumed to be grazing
(velocities ranging from 2.34 m • min-1 to 25 m • min-1) to
calculate percent of grazed pixels, pixel residence time, pixel
revisit rate (pixel visits on different days), and pixel return
interval (days between visits to the same pixel) for each animal.
Pixels grazed (%) was calculated by determining the number of
pixels grazed per animal and dividing by the sum of available
pixels. Pixel revisit rates were calculated by summing the visits
to each pixel on different days. Pixel return interval (days) was
calculated by identifying the number of times an animal revisited
a 30x30 (900-m2) pixel and calculating the number of days between
visits. Pixel residence time (minutes*visit-1) was calculated by
summing the total of 5-minute grazing GPS fixes per cell per
animal. These metrics were used to analyze pasture use pattern
differences among biotypes, and between seasons and cohorts. To
ensure consistency between sampling periods, only the first 20 d
of each trial period were used to derive the four pasture use
metrics described above.
Drinking behaviors including time at water (within 15 m from
water, h x day-1), time close to water (within 200 m from water, h
x day-1) and drinking frequency (visits x day-1 within 15-m of a
drinker) during 24-h periods were calculated using the spatial
join tool in ArcGIS 10 to merge GPS fix locations and buffered
Euclidean distances from drinkers (ESRI, Redlands, CA). Metrics
describing pasture use patterns in relation to the location of
drinkers were based on Valentine (1947) and included time spent
within 1.6 km of water (h x day-1) and time spent between 1.6 and
3.2 km of water (h x day-1) during 24-h periods and were also
calculated in ArcGIS 10 (ESRI, Redlands, CA). Pasture use was
expressed using Ivlev’s (1961) electivity Index, where negative
one = avoidance, zero = indifference, and one = selection, and
where r is the proportion of time spent in each concentrically
buffered drinker distance zone (ha) available within the pasture
(p [total ha]; Jacobs, 1974). Drinking behaviors were calculated
using all GPS fix locations.
Steer weights were recorded to the closest half kilogram and were
determined by averaging two weights recorded per steer per
weighing date. Steers were fasted overnight and the entire group
(cohort) of steers were passed through the scale twice during
morning hours on weighing days (Table 1). Average daily gains
(ADG) were calculated by subtracting the final weight prior to
shipping (30 months of age) from the initial weight (when animals
entered the study) and dividing the difference by the total number
of days in the study. Partial ADG was also calculated for
GPS-tracking periods by subtracting the final weight (from the end
of the tracking period) from the initial weight (at the beginning
of the tracking period) and dividing the difference by the total
number of days in the tracking period (approximately one month;
Table 1). Kilogramsof beef per hectare (kg*ha-1) was calculated as
the total weight gain per cohort between weigh dates divided by
the total hectares of our 3,215 ha study pasture. Steer carcass
characteristics were analyzed for C2 animals in March 2018.
Vegetation phenology is known to have strong effects on livestock
performance on rangelands (Cruz and Ganskopp, 1998). To determine
the relationship between vegetation phenology (greenness) and
animal performance, we regressed MODIS Terra 16-day composite 250
m time-series Normalized Difference Vegetation Index (NDVI)
products (MOD13Q1) against kilograms of beef per hectare. Our NDVI
products spanned the entire study period. One NDVI tile (V006) was
mosaicked and re-projected from sinusoidal projection to WGS 1984
UTM zone 13N. Each NDVI image was overlaid on our map and the mean
NDVI of 30 pixels covering the study area was used to predict
relative plant greenness per period. Kilograms of beef per hectare
produced between weighing dates (described above) was regressed
against maximum pasture NDVI for each period.
