**2. Methods**

patches ranging from <2 to 200 m in diameter. This woody species can tolerate poor soils,

Some patches of WS are desirable as thickets provide nesting habitat for ground-dwelling birds, as well as some protection for newborn calves (Charlie Totton, rancher, personal communication, June 2013). Therefore, complete elimination of WS plants in most pastures is not the ultimate management goal. But, over time, uncontrolled patches of this less palatable [3], woody groundcover can reduce plant species diversity and amounts of desirable forage; alter

Options for rangeland perennial weed control vary in implementation and effectiveness and require multiple years of maintenance. After WS removal, biomass of grasses and forbs can increase dramatically [7], although WS densities can rebound in less than a year if control measures cease [8]. Herbicides applied in June resulted in good (64%) to excellent (99%) WS control during the growing season, depending on herbicide and application rate [9, 10] with control in subsequent years ranging from none to excellent. Even with excellent control, herbicides often are more expensive than short or mid-term returns justify [11]. However, because WS occurs in patches, uniform treatment of entire pastures may not be necessary, thus reduc-

Physical techniques, based on timing, alone or combined with grazing are other options for WS management. While a single growing season of mowing did not control WS [10], two mowing events over 3 years reduced WS patch size [1], and increased succulent sprout growth, making the plant more palatable to livestock. Grazing WS patches in early season (May) or left untreated had lower WS densities the following year compared to areas grazed in August [12] or burned with late season fire [8]. Prescribed fires from mid- to late-May combined with goat (*Capra aegagrus hircus*) grazing suppressed WS plants, reduced seed production, canopy cover, and stem density [13, 14] in the NGP. However, goats are not commonly reared in the

Cattle grazing for weed control is a natural fit for NGP pastures and rangelands. However, weed management using cattle often has limited success. First and foremost, cattle are expensive to raise and replace and, depending on weed species, may result in problems with nutrition [16], reproduction, toxicity, or have other negative impacts (e.g. off flavors of meat) [2, 17]. Since cattle avoid dung-soiled pasture, selective grazing can occur when stocking rates are low or moderate [18, 19]. Thus, only the most palatable plants are grazed, leading to overgrazing desirable species, and ultimately changing the plant community [20]. In addition, cattle hooves break up sod, leaving areas vulnerable to weed invasion, which is counter-productive to control [5]. Deliberately managing and manipulating cattle stocking rate and density, grazing duration, and seasonal timing based on pasture conditions can promote weed management success [16]. Livestock can consume and/or trample plants and improve pasture nutrient condition and competitiveness of desirable plants through incorporation of manure and urine [5], often with fewer adverse effects on non-target species than herbicide applications. Grazing should occur when the weed is most palatable, vulnerable to injury, and not toxic to the animal.

Mob grazing (or nonselective grazing) using cattle has been promoted as a system to improve soil health and plant conditions [21–23]. This system attempts to mimic animal/vegetation

harsh temperatures, flooding, and drought [2].

20 Forage Groups

nutrient cycling [4]; and result in economic loss [5, 6].

ing costs and environmental impacts.

NGP for a variety of reasons [15].

#### **2.1. Study site description and treatments**

Forage utilization and WS (*Symphoricarpos occidentalis*) data were collected at two South Dakota locations, Chamberlain (southcentral SD; 43.8°N, 99.3°W) and Selby (northcentral SD; 45.3°N, 99.8°W). South Dakota, located in the NGP of the United States, has a continental climate, i.e. cold winter temperatures with snow, and moderate to warm summer temperatures. Most annual precipitation occurs in spring and summer.

At Chamberlain, forage and WS response was quantified in mob-grazed pastures (2013 and 2014), ungrazed pastures (2013) and an early (May through mid-June) rotational-grazed pasture (2014). In Selby, treatments were performed in mob-grazed (2013 and 2014), rotationalgrazed (2013), and ungrazed pastures (2014). Pasture vegetation and soil types for each site are listed in **Table 1**. Climate, grazing, and sampling information for the two-year period are provided in **Table 2**. Growing degree days (GDD; base 0°C) for the growing season (March through September) were near (±5%) the 30-yr average (1980–2010) at each year and site (**Table 2**). Precipitation (January through September) was 8% lower than their respective 30-yr averages for both sites in 2013, and 4% lower at Chamberlain and 16.5% lower at Selby, in 2014. Specific GDD and precipitation amounts for sampling dates are reported in Myer [29].

Local producers determined stocking intensity, grazing dates, and paddock size, with cattle moved in mob grazed areas after 24-hr (**Table 2**). The rotational and ungrazed treatments differed among years at the locations due to cattle needs and pasture condition. At Chamberlain


**Table 1.** Plant species and soil types at Chamberlain and Selby, SD in 2013 and 2014.

mob grazed pastures were mob grazed every-other year, so the 2013 mob grazed pasture was ungrazed in 2012, and the 2014 mob grazed pasture was ungrazed in 2013. Meanwhile, the 2013, ungrazed pasture at Chamberlain was rotationally grazed at a stocking density of 250 kg ha−<sup>1</sup> for approximately 30 days on 300 ha in 2012, and this same pasture was rotationally grazed in 2014. At Selby, both the mob grazed and rotationally grazed pastures were managed similarly in previous years as the experimental years, and the 2014 ungrazed pasture was rotationally grazed in 2013.

**2.2. Vegetative data collection**

dBoth sampling dates occured after rotational grazing

a

b

c

locations.

SD, respectively.

Rotationally grazed in 2012

Grazed in May – mid June

was recorded.

Three parallel 50-m transects were set up about 10 m apart (pre-graze measurement) immediately prior to the first sampling date (**Table 2**; **Figure 1A**) with two paddocks of each grazing treatment sampled each year (six transects) per site. Average standing forage height was measured to the nearest cm every 2.5 m along each transect, with GPS points recorded (Garmin eTrex 20, Garmin International, Inc., Olathe, KS). Every 5 m along each transect, the closest WS plant was identified, tagged with a metal loop near the plant base, and height (highest

**Table 2.** Climate, grazing information, and sampling dates for 2013 and 2014 at Chamberlain (Chamb.) and Selby, SD

30 yr average is based on 1980 to 2010 data for the nearest weather stations to the study site (Chamberlain and Hoven,

Mob Grazing Results in High Forage Utilization and Reduced Western Snowberry Size

http://dx.doi.org/10.5772/intechopen.83402

23

After grazing, or in the fall for the non-summer grazed paddocks, transects were reestablished. Average standing forage height, including WS, at each sampling point was measured again and percentage of newly trampled forage (e.g. vegetation remaining that was ≤45° from upright position) was estimated in mob-grazed paddocks only. Tagged WS plants were measured as in pre-grazing, and post-grazing condition (e.g. intact, trampled, browsed)

point from soil surface) and two perpendicular widths were measured.

Mob Grazing Results in High Forage Utilization and Reduced Western Snowberry Size http://dx.doi.org/10.5772/intechopen.83402 23


a 30 yr average is based on 1980 to 2010 data for the nearest weather stations to the study site (Chamberlain and Hoven, SD, respectively.

b Rotationally grazed in 2012

c Grazed in May – mid June

mob grazed pastures were mob grazed every-other year, so the 2013 mob grazed pasture was ungrazed in 2012, and the 2014 mob grazed pasture was ungrazed in 2013. Meanwhile, the 2013, ungrazed pasture at Chamberlain was rotationally grazed at a stocking density of

loam/clay loam

ally grazed in 2014. At Selby, both the mob grazed and rotationally grazed pastures were managed similarly in previous years as the experimental years, and the 2014 ungrazed pas-

for approximately 30 days on 300 ha in 2012, and this same pasture was rotation-

250 kg ha−<sup>1</sup>

**Soil types**

22 Forage Groups

ture was rotationally grazed in 2013.

Sansarc-Opal clay Opal-Sansarc clay

Uly silt loam Gettys clay loam

McClure silt loam Bearpaw-Gettys complex Bullcreek clay Highmore-Bearpaw silt

**Table 1.** Plant species and soil types at Chamberlain and Selby, SD in 2013 and 2014.

**Chamberlain Selby**

Common sunflower *Helianthus annuus* Musk thistle *Carduus nutans* Common ragweed *Ambrosia artemisiifolia* Bull thistle *Cirsium vulgare* Milkweed *Asclepias sp.* Green needlegrass *Nassella viridula* Needle and thread *Hesperostipa comata* Big bluestem *Andropogon gerardii* Porcupine grass *Schizachyrium scoparium* Sideoats grama *Bouteloua curtipendula* Blue grama *Bouteloua gracilis*

**Common name Scientific name Common name Scientific name** Western wheatgrass *Pascopyrum smithii* Western wheatgrass *Pascopyrum smithii* Smooth brome *Bromus inermis* Green needlegrass *Nassella viridula*

Western snowberry *Symphoricarpos occidentalis* smooth brome *Bromus inermis* red clover *Trifolium pratense* Kentucky bluegrass *Poa pratensis* Kentucky bluegrass *Poa pratensis* Scurfpea *Psoralidium sp.* dandelion *Taraxacum officinale* Sweet clover *Melilotus officinalis*

sweet clover *Melilotus officinalis* Western snowberry *Symphoricarpos occidentalis*

dBoth sampling dates occured after rotational grazing

**Table 2.** Climate, grazing information, and sampling dates for 2013 and 2014 at Chamberlain (Chamb.) and Selby, SD locations.

#### **2.2. Vegetative data collection**

Three parallel 50-m transects were set up about 10 m apart (pre-graze measurement) immediately prior to the first sampling date (**Table 2**; **Figure 1A**) with two paddocks of each grazing treatment sampled each year (six transects) per site. Average standing forage height was measured to the nearest cm every 2.5 m along each transect, with GPS points recorded (Garmin eTrex 20, Garmin International, Inc., Olathe, KS). Every 5 m along each transect, the closest WS plant was identified, tagged with a metal loop near the plant base, and height (highest point from soil surface) and two perpendicular widths were measured.

After grazing, or in the fall for the non-summer grazed paddocks, transects were reestablished. Average standing forage height, including WS, at each sampling point was measured again and percentage of newly trampled forage (e.g. vegetation remaining that was ≤45° from upright position) was estimated in mob-grazed paddocks only. Tagged WS plants were measured as in pre-grazing, and post-grazing condition (e.g. intact, trampled, browsed) was recorded.

Therefore, due to time and labor constraints, grazing stick measurements that accounted for height and percent cover were used to describe relative forage productivity and grazing impact.

Mob Grazing Results in High Forage Utilization and Reduced Western Snowberry Size

http://dx.doi.org/10.5772/intechopen.83402

25

Forage consumption = [(pre-graze biomass) – (post-graze biomass + trampled)]/(pre-graze biomass) × 100; with biomass estimated using the grazing stick method described above, and assuming the difference in standing forage was consumed by the livestock and not by insects, wildlife, or rodents [32]. Since there was no trampled forage estimate for rotational-grazed paddocks, this was only calculated for the mob-grazed treatment. Additionally, forage utilization (consumed + trampled forage) was estimated at each sampling point and was based on change in biomass (estimated using the grazing stick method), including the trampled forage. Pre- and post-grazing WS relative plant volume was estimated for each tagged plant

WS volume = height × width 1 × width 2; with height measured at the highest point on the plant from the soil surface, width 1 as the widest horizontal measure of the WS, and width 2

Matched paired one-tailed (post-graze<pre-graze) t-tests were used to compare pre- versus post-grazing WS plant volume and estimated forage biomass at each point along the transect at a significance va1lue of P ≤ 0.10. Data were combined when appropriate. Data from ungrazed pastures were examined with a one-tailed matched paired analysis test with the

Binomial analysis of WS plant volume data (yes = less volume post grazing (or in the fall for

[p ± t(0.1) sqrt (p (1 − p)/n)] (2)

was used to determine if grazing intensity treatments impacted individual WS plant volume.

based on the median WS plant size in grazed pastures and analyzed using two-tailed matched paired t-tests to determine if pre-graze volume impacted cattle interaction with plants.

respectively (**Table 3**). Stocking density was greater and individual paddock size larger in

sumed + trampled) in mob-grazed areas were similar and >90% each year. Harvest efficiency

and >6500 cm3

in 2013 and 2014,

on 2 ha). Harvest utilization (con-

)

non-summer grazed treatment); no = same or greater volume) using the equation: [33]

In addition, WS plants were separated into two volume classes (<6500 cm3

Estimated forage biomass before mob grazing was 6100 and 2840 kg ha−<sup>1</sup>

(amount consumed) was also similar and >60% each year.

on 5 ha) than 2014 (43,680 kg ha−<sup>1</sup>

Forage consumption (efficiency) percentage [31] was estimated by:

the width of the WS perpendicular to the width 1 measurement.

assumption that spring forage < fall forage.

**2.3. Data analysis**

using the equation:

**3. Results**

**3.1. Chamberlain**

2013 (67,200 kg ha−<sup>1</sup>

**Figure 1.** Pasture condition before (A) and after (B) a 24-hr mob grazing event at Chamberlain, SD.

Forage productivity can be estimated using the grazing stick method:

 Forage productivity = (average standing forage height − 10 cm) × 79 kg ha<sup>−</sup><sup>1</sup> cm<sup>−</sup><sup>1</sup> . (1)

which is the conversion value for a cool season, mixed species pasture with about 90% cover [30]. The 10 cm is subtracted from the height to account for remaining leaf and stubble after grazing. In preliminary data sets, Myer compared grazing stick method to clipping forage biomass at >40 sampling points and found these two estimates were within 15% of each other [29]. Therefore, due to time and labor constraints, grazing stick measurements that accounted for height and percent cover were used to describe relative forage productivity and grazing impact.

#### **2.3. Data analysis**

Forage consumption (efficiency) percentage [31] was estimated by:

Forage consumption = [(pre-graze biomass) – (post-graze biomass + trampled)]/(pre-graze biomass) × 100; with biomass estimated using the grazing stick method described above, and assuming the difference in standing forage was consumed by the livestock and not by insects, wildlife, or rodents [32]. Since there was no trampled forage estimate for rotational-grazed paddocks, this was only calculated for the mob-grazed treatment. Additionally, forage utilization (consumed + trampled forage) was estimated at each sampling point and was based on change in biomass (estimated using the grazing stick method), including the trampled forage. Pre- and post-grazing WS relative plant volume was estimated for each tagged plant using the equation:

WS volume = height × width 1 × width 2; with height measured at the highest point on the plant from the soil surface, width 1 as the widest horizontal measure of the WS, and width 2 the width of the WS perpendicular to the width 1 measurement.

Matched paired one-tailed (post-graze<pre-graze) t-tests were used to compare pre- versus post-grazing WS plant volume and estimated forage biomass at each point along the transect at a significance va1lue of P ≤ 0.10. Data were combined when appropriate. Data from ungrazed pastures were examined with a one-tailed matched paired analysis test with the assumption that spring forage < fall forage.

Binomial analysis of WS plant volume data (yes = less volume post grazing (or in the fall for non-summer grazed treatment); no = same or greater volume) using the equation: [33]

$$\left[\mathbf{p} \neq \mathbf{t}\_{(0,1)} \operatorname{sqrt} \left(\mathbf{p} \left(1 - \mathbf{p}\right) / \mathbf{n}\right)\right] \tag{2}$$

was used to determine if grazing intensity treatments impacted individual WS plant volume. In addition, WS plants were separated into two volume classes (<6500 cm3 and >6500 cm3 ) based on the median WS plant size in grazed pastures and analyzed using two-tailed matched paired t-tests to determine if pre-graze volume impacted cattle interaction with plants.
