Space-Age Tools For Old-School Grazing Management

By Tip Hudson, Washington State University rangeland & livestock management Extension professor

I am an early adopter. And I’m a critic of technology adoption that moves faster than our social ability to understand effects and develop ethics to guide usage. I love technology, and I love writing on paper with a pen because it helps me think better. I learned cursive in 3rd grade and I write in cursive exclusively and profusely. I use an iPhone, but my favorite apps are Merlin Bird ID (records bird calls and identifies on the fly), OnX (like a digital version of a topo map but better), and the Wall Street Journal app that lets you read a digital version of what looks like an old-school news-paper instead of the infinity scroll. One of my favorite books is Nicholas Carr’s “Glass Cage: the Social Costs of Automation”, a philosophical musing mixed with anecdotes of the good and bad of trusting human judgment and reactions to machines (Carr 2014). I wrote in a journal article a few years ago about the need for direct human engagement with our physical environment and with fellow humans (Hudson 2020). This was in defense of both the use of recorded conversation (The Art of Range Podcast) for achieving broad, context-specific conservation goals as well as the importance of thinking deeply and resisting the urge to outsource thinking about natural resources management to machines. And I find myself in agreement with Nicholas Carr that the best tools (Greek techne) are those that enhance uniquely human ways of understanding and engaging with the biological/geophysical world. I don’t trust so-called intelligence that is artificial. This seems like an oxymoron.

One of the oldest human-managed uses of the physical world is animal husbandry. This has always been a fascinating, complex combination of scientific understanding of natural resources and animals and the contextual application of that knowledge, which builds on itself in the doing. This is why we call it an art. It’s an art in the sense that one practices medicine or practices law. You don’t really know the thing until you begin doing it, applying it, getting steered in your doing by the unforgiving nature of Nature. And there’s something about caring for sentient creatures that are dependent on us that is good for our psyches. 

We have some technological advancements now that help to understand natural ecosystems that add significant value to human efforts to steward, to husband (in the old sense) land and animals well. Truly sustainable grazing of rangeland and ‘tame’ pastures has always required ensuring forage consumption by domesticated herbivores does not exceed some harvest level of forage supply such that naturally-occurring forage is able to stabilize soil, support water cycling, and reproduce itself in sufficient kinds and quantities that it persists over time in a way that supports ecosystem goods and services other than provisioning meat and fiber from livestock. On large, heterogeneous landscapes with dozens or hundreds of soil types, landscape positions, plant communities, each of them affected by slope and aspect, this forage supply has been difficult to characterize accurately, particularly in terms of forage quantity. This is why many grazing permits, leases, and private grazing plans are based on (I’m serious) 1958 soil survey data. This is a little too old-school even for me. 

We need good data. Forage supply is finite. It is variable across space. And it is variable over time. On-the-ground sampling methods can measure with some precision, and statistically definable accuracy, forage biomass . . . on a particular soil type . . . at a particular elevation . . . with a particular plant community . . . in 1975. Forage production at the spot I’m standing on was different last year and will be different than that next year. We encounter a significant problem of scale when we attempt to extrapolate sampling on a few square meters to tens of thousands of hectares (Sayre et al. 2017; Sayre 2017). That extrapolation is inaccurate and risky. And that’s before we add animal terrain use to the stocking rate equation. Overallocating forage quantity, resulting in an imbalance of forage demand to forage supply, doesn’t just lead to inadequate plant residual in grazing areas and potential soil loss, habitat value loss, soil compaction, macroinvertebrate decline, etc., but also to declining forage quality received by grazing animals as they are obligated to consume less preferred plants or portions of plants with more structural carbohydrates, leading to other kinds of production loss and poor animal husbandry. 

 Tens of thousands of hectares is the scale of real-world management. Thanks to the space age, we now have quite accurate remote-sensed above-ground herbaceous biomass estimates that can be used for developing grazing plans based on more realistic forage production values. Data on range production now exist that can be manipulated by geographic information systems to calculate accessible forage, a subset of total forage, for a given landscape (Reeves et al. 2014; 2021). In a recent article in the Land journal by Reeves, et al (and present author): “we describe a decision support model aimed at estimating grazing capacity for managed herbivory in a public land management setting using spatially explicit data describing vegetation production, lifeform distribution, water points, and topography.” The paper describes grazing planning on federal lands, but the approach used is the functionality we have developed into an online grazing decision support tool at www.stock-smart.com (Reeves et al. 2025; Hudson et al. 2021). 

StockSmart is a free, online decision support tool developed by Washington State University, the University of Arizona, and the US Forest Service Rocky Mountain Research Station. It calculates stocking rates using remotely-sensed forage production data for every quarter of an acre for the last 40 years, providing much more information than previous datasets on how that forage production varies across geographic space and from year to year. StockSmart also allows the user to define their animals’ terrain use with some key parameters, especially how steep a slope their livestock will traverse, and how far from water they will disperse. These values are used in a background calculation that assigns a forage availability factor to every 30m x 30m pixel. Comparison of this terrain use model to actual animal distribution measured by GIS has demonstrated good accuracy, >80% correlation between predicted and actual distribution. 

StockSmart allows you to explore scenarios, such as how the amount of forage and stocking rate might change if you invest in new water developments or fencing. You can calculate forage quantity and stocking rate across an entire ranch or federal grazing allotment or at the individual pasture scale, and all of that together. 

Space does not permit describing all the space-age features of StockSmart here, but more information is available about the data, how calculations are handled, and how to use the program, at https://www.stock-smart.com/, https://csanr.wsu.edu/sustainable-grazing-starts-with-good-forage-production-data/, and https://research.fs.usda.gov/rmrs/products/dataandtools/stocksmart.

References

Carr, Nicholas G. 2014. The Glass Cage: Automation and Us. First edition. WWNorton & Company.

Hudson, Tipton D. 2020. “Conversation as an Education Medium for the Age of Distraction - the ‘Art of Range’ Podcast.” Rangelands 42 (1): 9–16. https://doi.org/10.1016/j.rala.2020.01.005.

Hudson, Tipton D., Matthew C. Reeves, Sonia A. Hall, Georgine G. Yorgey, and J. Shannon Neibergs. 2021. “Big Landscapes Meet Big Data: Informing Grazing Management in a Variable and Changing World.” Rangelands 43 (1): 17–28. https://doi.org/10.1016/j.rala.2020.10.006.

Reeves, Matthew C., Brice B. Hanberry, Hailey Wilmer, Nicole E. Kaplan, and William K. Lauenroth. 2021. “An Assessment of Production Trends on the Great Plains from 1984 to 2017.” Rangeland Ecology & Management 78 (September): 165–79. https://doi.org/10.1016/j.rama.2020.01.011.

Reeves, Matthew C., Adam L. Moreno, Karen E. Bagne, and Steven W. Running. 2014. “Estimating Climate Change Effects on Net Primary Production of Rangelands in the United States.” Climatic Change 126 (3–4): 429–42. https://doi.org/10.1007/s10584-014-1235-8.

Reeves, Matthew C., Joseph Swisher, Michael Krebs, et al. 2025. “Data-Driven Decision Support to Guide Sustainable Grazing Management.” Land 14 (1): 1. https://doi.org/10.3390/land14010140.

Sayre, Nathan F. 2017. The Politics of Scale: A History of Rangeland Science. University of Chicago Press.

Sayre, Nathan F., Diana K. Davis, Brandon Bestelmeyer, and Jeb C. Williamson. 2017. “Rangelands: Where Anthromes Meet Their Limits.” Land 6 (2): 31. https://doi.org/10.3390/land6020031.