In this post Julie Kray, Agricultural Science Research Technician, USDA-ARS & Lauren Porensky, Ecologist, USDA-ARS discuss the recent paper ‘Thresholds and gradients in a semi-arid grassland: long-term grazing treatments induce slow, continuous and reversible vegetation change’
How do we strike a balance between an economically sustainable amount of grazing, and an ecologically sustainable amount? This is the central challenge in managing grazed landscapes around the world. Due in part to differences in vegetation, soil conditions, climate, and past grazing history, a grazing strategy that results in ecological damage in one place might underutilize the resources of another. In addition, the optimal balance between livestock production and resource conservation is a moving target, because each year brings different weather, and the effects of one year’s weather and management decisions often influence subsequent years.

To help producers and managers adapt to constantly changing conditions, the USDA Natural Resources Conservation Service developed state-and-transition models (STMs) for the US. These models describe, for a particular location, how vegetation changes in response to management and natural processes. But any model that simplifies real world complexity enough to be generally useful requires test runs and revisions. As STM predictions are compared to real world responses across a wide range of situations, we learn which pieces of each model do or don’t work, and this leads to improvements in both the model and the management it was built to guide.

Due to a lack of long-term data, many of the existing STMs have a similar set of shortcomings. For example, most STMs only hint at the rate of expected vegetation changes. Furthermore, it is often unclear whether changes are permanent or reversible, given a change in management. Long-term experiments are needed to build more detailed temporal dynamics into STMs, but few studies have measured grazing effects over multiple decades, or evaluated the potential for vegetation recovery with years of rest after decades of grazing.
We studied the effects of three grazing intensities imposed for 33 years on northern mixed-grass prairie near Cheyenne, Wyoming, USA. We compared pastures with no cattle grazing to others with light, moderate, and heavy stocking rates. We also returned a subset of the heavily grazed pastures to light grazing or no grazing for 8 years, to see if the effects of 25 years of heavy grazing were reversible. Based on the current STM for our area, we expected long-term heavy grazing to cause an irreversible change from a mixed cool-season and warm-season perennial grass community to one without any cool-season grasses. The loss of the taller, more productive cool-season grasses from this plant community could reduce the number of livestock it supports and place economic stress on producers.

Just as the STM predicted, 33 years of heavy grazing caused the cover of dominant cool-season grasses, western wheatgrass and needle-and-thread, to decline while cover of the dominant warm-season grass, blue grama, increased. However, the cool-season grasses did not vanish after three decades of heavy grazing, and we were surprised to find that reversing management from heavy grazing to light or no grazing allowed dominant cool-season grasses to recover. This recovery took about as long as the initial change during the first 8 years of the experiment.

Our study suggests that northern mixed-grass prairie may be more resilient to grazing than the current STM predicts, which is good news. However, it still took more than a decade for the vegetation to revert to pre-grazing conditions, which is far from a speedy recovery. From a producer’s perspective, this is a long time to wait for higher economic returns from the land, suggesting that a lower stocking rate is optimal over the long term.
For the STM, our take-home message is that, in resilient rangelands, quantifying the rates of plant community change appears to be more important than identifying permanent transformations. Adding measured rates of change (when available) to STMs will greatly improve their usefulness, and enable land managers to add well-defined grazing rest periods into their long-term plans.