Article: Soil Hydrologic Response to Number of Pastures and Stocking Density under Intensive Rotation Grazing
Authors: Warren, S.D. Blackburn, W.H. Taylor, C.A
Published: Journal of Range Management 39(6), November 1986
Research for this paper was completed during the two year period from 1983 to 1984 at the Texas Agricultural Research Station near Sonora, Texas. During this period, annual precipitation showed a mean of 155 mm below average.
The authors summarize the general research design:
Three pastures which were 16, 24, and 32 ha in size were used for this study…[and] the number of days grazing per cycle [were] proportional to the size of the pasture. For example, during a 56 day cycle the 32-a pasture was grazed for 8 days while the 24 and 16-ha pastures were grazed for 6 and 5 days, respectively. The procedure maintained a constant year-long stocking rate of 4.8 ha/AU/yr, which is approximately 1.7x the recommended moderate rate…the respective stocking densities for the 32-, 24-, and 16-ha pastures were .68, .51, and .34 ha/AU. This design effectively simulated 3 equally stocked 224-ha intensive rotational grazing systems, with the 32-, 24-, and 16-ha pastures representing 7-, 9-, and 14-pastures systems, respectively.
At these varying stock densities, a number of variables were measured and compared. The most relevant are: infiltration rates, sediment production, bare ground, litter cover, vegetation cover, litter biomass, and soil organic matter.
Few differences were found in terms of sediment production and infiltration rates, “but as a general rule, the pasture which was grazed at the highest stocking density (0.34 ha/AU) had the lowest infiltration rate…the same trend in hydrologic condition was true for sediment production.” The authors summarize the lack of a relationship between stock density and water infilitration:
Logic would dictate that if stocking density were truly affecting hydrologic condition, then the pasture stocked at either the highest or lowest density would produce the highest infilitration rate and the least amount of sediment. The pasture in best hydrologic condition would then be followed in sequence by the other 2 pastures, based on successively ascending or descending stocking density. Such was not the case in this study.
What stands out here is that the range of stock densities were fairly homogeneous when compared to the actual range of densities applied in practice. The authors create the false impression that low stock densities are being compared to high stock densities. In actual fact, low stock densities are being compared to lower stock densities. Truly high stock densities are an altogether different phenomenon.
A nice illustration of this point comes from Dan Dagget’s book Beyond the Rangeland Conflict. In the following passage, Dagget is commenting on observations from a visit to Ivan Aguirre’s La Inmaculada Ranch. Keep in mind that the stock density applied at the Aguirre ranch in the example given is .007 ha/AU; compare this to the range of .34 to .68 ha/AU applied by the researchers in the presented study. These massive differences in management are brought into focus by Dagget:
The cattle at La Inmaculada are kept in one large herd to concentrate their impact, and few ranchers concentrate impact as much as Ivan Aguirre. As we walk out into the paddock, we scuff our feet through soil that resembles what you find in a tilled garden. As a matter of fact, Ivan actually uses his herd of 3,000 cattle as tillers, grazing them for half a day in a field of fifty acres to prepare it for the planting of tepary beans and Indian corn, native plants once cultivated by indigenous peoples. The soil where we stand now…is pulverized. Cattle dung and grass litter are churned into the mix, along with limbs and twigs busted from shrubs and tress by the continuous passing of the cattle of their way to water, creating a loose mulch in some places up to six inches deep.
Rukin Jelks, who knows something about disturbance, reaches down and picks up a handful of pulverized dirt. “Do you know what would happen to this if it rained?” he asks. Massive erosion, I think, but before I can reply he continues. It’ll soak up water, lots of water, and soil around here isn’t used to being wet. When it gets wet,” he says, “it explodes with growth.”
Comparisons in management between the research in this study and the practice of Ivan Aguirre are not limited to massive differences in stock density. One of the key distinctions is the application of tools towards specific objectives. By using cattle to create mulch, Aguirre is achieving what the researchers could not: improvements in water infiltration. These descriptions are qualitative, to be sure, but this is because research has often failed to successfully apply tools and then measure the land’s response. This failure has frustrated practitioners for years. Instead of playing the blame game, researchers and practitioners alike must find common ground and build research models around innovative, solution-driven practices.
The most useful part of this article comes at the end, almost as an afterthought. The authors present a model for determining the optimal number of paddocks based on a required recovery period. They correctly argue that recovery periods are of critical importance to infiltration rates and sedimentation:
Infiltration rate is generally lower and sediment production higher following short periods of intensive grazing associated with rotational grazing system. In order to avoid long-term progressive degradation, rest periods must be of sufficient length to allow full recovery soil hydrologic condition prior to the reoccurrence of livestock impact…The potential for increasing the length of the rest period through the manipulation of the number of pastures is minimal where the number of pastures is already large.
The graph below illustrates this argument: paddock numbers should be a function of required recovery periods. The inflection points for a 28 day, 56 day, and 112 day recovery are 5, 7.5, and 12 paddocks, respectively.
Looking at the graph, one quickly notices that beyond these inflection points, increases in the number of paddocks are subject to the law of diminishing returns. That is, the inflection point designates the optimal number of paddocks based on a chosen recovery period. Beyond the inflection points, increases in paddocks will not substantially (nor economically) increase stock density or reduce grazing days per paddock. Though paddock numbers might not always be driven by recovery periods (depending on objectives), this model is worthwhile as a general rule of thumb and as a planning tool. This paper resolves some of the questions raised in a previous post.