Though widely used, Kothmann points out that AU is a supply-based measurement of forage demand. By definition, it represents 26 lbs. of dry matter intake (DMI)/day, which is supposed to represent the maintenance for one cow. But the definition doesn’t say whether that’s a 900-lb., fat, dry cow or a wrung-out, 1,500-lb. mama nursing a calf. AU accounts for neither the energy demand of specific animals nor the energy provided by specific forages.

This imprecision coupled with the challenges cited above led Kothmann to begin considering the puzzle from the opposite direction back in the 1980s. Ultimately, he developed a model for managing carrying capacity that utilizes grazing demand days (DD) as the unit of measure.

Whereas AU represents DMI regardless of forage nutrient value, DeGroff explains DD also approximates the energy requirements for gain.

As the term implies, rather than a supply-based yardstick such as AU represents, DD expresses the calories demanded by livestock – cattle and other large ruminants – for both maintenance and gain. Specifically, one DD equals 12 mega calories of intake for maintenance and gain.

Kothmann wanted more than a different yardstick, though. He wanted a way to estimate forage availability, demand and use in such a way that he could detect shortfalls further down the road rather than too late or after the fact.

Applicable to all operations

Kothmann’s answer is The Grazing Manager (TGM), a computer-based, decision-support tool that budgets forage demand against forage supply using DD as the measure.

“It allows the manager to forecast forage balance many months into the future, make timely adjustments to stock numbers, and avoid risks associated with overstocking during drought,” Kothmann explains. It empowers grazing managers to be proactive rather than reactive.

While this article is slanted toward rangeland, Kothmann emphasizes TGM can be utilized with any forage and grazing system.

“TGM was developed to capture the basic elements of the intuitive management approach used by many successful grazing managers and structure them into a quantitative dynamic grazing model,” Kothmann says.

Before your eyes start to glaze over, yes, the system requires input, but nothing more than what’s already rattling around your brain. Think here in terms of the number grazing, for how long, weights on and off pasture, etc.

The variables that must be input, all of which are observable, include:

  • Forage year,
  • Seasonal forage growth cycle,
  • Pasture production in DD,
  • Annual livestock flow,
  • Management plan for grazing, burning, haying and supplementation,
  • Actual forage growth rates (estimated by the manager) and
  • Pasture use rating (% DD used).

The software leads users through the process and contains the necessary data, such as forage growth cycle information for wherever you operate, besides doing the calculations automatically.

Much of the TGM output is graphical, too, such as a continuum between light and heavy pasture use.

“The input doesn’t have to be exact,” Kothmann says. “You say what the range or pasture should look like based on the estimates you input. If it doesn’t, then you review your estimates until TGM and your observations agree.”

DeGroff adds that, “When there is a deficit in moisture, you can put a percentage to it – above or below normal – and approximate the reduction in forage production based on the growth curve for that specific forage in your area.”

In other words, relative to current growing conditions, based on the season forage growth cycle, TGM estimates available DD for the forage year. As growing conditions change and producers input an adjustment to reflect the change, TGM adjusts available DD for the remainder of the forage year.

Such monitoring and adjusting, especially early on, is part of what is termed calibration; calibrating you and how you use the system rather than calibrating the model.

By design, TGM doesn’t tell users what they should and shouldn’t do. It’s merely a tool offering them more precise projections to use in making decisions, Kothmann and DeGroff say.