Building #agduino

I’ve talked to a few folks in the arduino for agriculture space over the past few days or so. There is a lot going in the arena, and after having looked at just some of what’s happening, it is absolutely the Wild West for in the Internet of ag-things. There’s a lot of potential applications, and there are a lot of creative and smart people going in different directions. This type of diversity is healthy for the future prospects of low-cost automated agricultural applications using microcontrollers.

Some conclusions:

  • The hardware piece is the easier part, but there’s still a lot of code to be written to make this stuff work seamlessly with phones, existing database architecture, and desktop applications.
  • Different people are approaching this differently, with the challenge being paying the bills and generating cash flow. Some are purely comitted to open source, others are using a hybrid model with software as a service for montetization, while others still are a completely closed system. Likely these serve large industrial producers.
  • There is a general sense that the future of agriculture, in part at least, is small, microintensive production units, e.g. aquaponics in basements.
  • The opportunities to integrate existing digital and analog electronics into the new Internet is mind-boggling, and just getting started.
  • The groups working in this space are fragmented! We need to work on building a small but committed community of people who are regularly communicating online.

If you are interested in being a part of an emerging community of like-minded people comitted to arduino for ag, then please let me know.  Contact me via email or twitter.  Or tweet #agduino.

@Indi_food Asks a Question

@Indi_food asked me the following question:

Just imagine the gains if flood irrigation changed to drip feeding that only initiated when soil moisture reached xx and evaporation levels went below xx. Is this the kind of thing that arduino can be programmed to do?

Yes! That’s exactly the type of thing arduino could do. Let’s flesh that scenario out more:

Agroduino is hooked into set of pressurized drip irrigation lines running to raised bed vegetables. The vegetables species and varieties are chosen to be drought tolerant (great in a place like New Mexico). A set of sensors are reading soil moisture and growing conditions. Data is sent to a mysql cloud database, then fed out over the internet to a hand-held Android device. Android reads data stream, then alerts you when conditions drop below certain thresholds. The producer monitors closely. A number of factors are taken into consideration:

  • Available water, either stored or via irrigation
  • Irrigation schedule (important in places where water is shared)
  • Drought tolerance of the plants
  • Growth stage (need more water after pollination in tomatoes and squash, for example, but not too much to avoid blossom end rot)
  • Economic value of crop (some beds may have high value crops, other lower value crops; some may have greater investment put into them)

If the conditions are right, the producer can control how much water the plants receive with precision, all from the handheld device.

The granularity of control really makes it worthwhile. The difficulty right now is the immaturity of the hardware/software stacks. As a producer, you shouldn’t have to learn ac/dc circuits to be able to benefit from this type of system. You don’t have to learn this to use a computer, or a cellphone, why should you for these devices? They should be plug and play with existing digital electronics hardware/software stacks that we are using now. But they are not. Not yet. So the ROI isn’t there yet for a standard producer, many of whom are struggling to keep their heads above water. We’re in the stage right now where people were with home computers 40 years ago…really wonky and geeky, not yet mainstream. Same could be said for 3D printing. But it will go fast, fast now, because we’re all connected and writing open source code and we can produce open hardware dirt cheap in China.

After having been in this space for a long time, I am acutely aware that sustainable agriculture is one of the most promising and underfunded initiatives underway around the world. And because most people who are undertaking it are landless and poor, or land rich and cash poor, there is little actual resource available to invest in acquiring land, much less improving it.

So we have to find another way. We have to accept that the land base we are going to be managing, for the foreseeable future, is going to be small, small, small except for the few rich folks who are into organic and/or support it because it’s the right thing to do. They are the minority. So how much food can we produce on an acre? 10 acres? 100? We need to feed millions in small spaces. That’s not easy, or probably possible, but if we have a shot at it, then we’ll have to use every technological tool at our disposal.

Is agroduino real?

image

I got an arduino, an arduino sensor shield, a solid-state relay, a set of climatological sensors, a bluetooth dongle, and an Android phone. Would it be possible to build an all-in-one agricultural management box that can be easily prototyped and deployed in the field? Or how about an entire network of them, a series of field-deployed small devices that collect data from the field, and then send the data a to a cloud server running open source agricultural record-keeping software. Then send the data to an open source permaculture simulation engine. And while we’re at it, how about adding a series of electric relays, servomotors, electric pumps and solenoid valves to manage greenhouse structures, aquaponics tanks, and irrigation systems. Could I build such a thing? Will you help me?

In Wake of Drought, Cows Eating Gummy Worms

English: brightly-coloured sprinkles.

(Photo credit: Wikipedia)

Corn crops were decimated by a severe drought last summer, pushing prices to a precipitous high. So farmers have had to get creative about what they feed their cattle. Some common solutions: chocolate bars, rainbow sprinkles, gummy worms, and, yes, cookies.

I hope these cattlemen realize that there’s plenty of corn in gummy worms and rainbow sprinkles.  This a clever stop-gap measure, but certainly not sustainable.

When Corn Costs Soar, Let Cows Eat Cake (Wired Magazine)

Economic Collapse in Greece Leads to Deforestation

Tens of thousands of trees have disappeared from parks and woodlands this winter across Greece, authorities said, in a worsening problem that has had tragic consequences as the crisis-hit country’s impoverished residents, too broke to pay for electricity or fuel, turn to fireplaces and wood stoves for heat.

Wood was humanity’s primary source of energy for thousands of years, and still is an critical source of energy in “developing” nations. Expect wood, and hence deforestation stories, to regain its importance in the global energy economy. And start planting trees.

Greeks Raid Forests in Search of Wood to Heat Homes

What is the Agrocollapse?

I stumbled on the term “agrocollapse” in fairly typical fashion.  Collapse is a concept drawing a lot of attention and discussion these days…and just as we’ve built out a lot of words by putting the word “agro” in front of them (agroforestry, agroindustry, etc.), agrocollapse seemed like a compelling and worthwhile concept.

What really set me forward on the concept, however, was when I attended a sustainable agriculture conference in November of 2012.  As is often the case at these events, many familiar faces and old hands were in attendance.  The topic was “How to Feed 9 Billion”.  The agenda was surprisingly tame: soil ecology, improved grazing management, plant breeding, fruit tree production, and the like.  Few of the presenters addressed the really tough questions, like What happens to sustainable ag as fossil fuel depletion continues?  Why aren’t we feeding 100 million people using these techniques now, instead of talking about 9 billion?  How can we really do any of the things we’re talking about on the scale we’re imagining when most of the land is in the hands of the top 1%?  None of these questions were on the agenda.  After all, we wouldn’t want to make people think too hard, and we certainly wouldn’t want to make anyone uncomfortable.

The one presenter who did address the issue of land reform was from Latin America; of course, the circumstance would require a latino to feel culturally comfortable with the topic, as land reform has been a powerful revolutionary force in Latin America for at least 100 years.  For him, the topic is not so taboo as it is here in the United States.

As the conference progressed, I began in private conversations to press people about my concerns.  Why aren’t we talking about these things?  After all of our technical achievements over the years, why aren’t we providing for a greater portion of the nation’s food supply?  Do we really believe that we’ll just gradually win, because our way is better, and we will just replace industrial agriculture with sustainable agriculture, the same way one replaces an old pair of shoes with a new pair?  Inevitably, the response that I got was generally the same: sooner or later, the industrial agricultural model is going to collapse.  And be replaced by what?  By us, who barely have the man-power and the land to feed 30 million people?  And what will happen to our movement as the beating heart of our country’s food supply implodes?  Will we even have the fuel to get our products to market?  Are we preparing ourselves for the collapse of the industrial food system, so that our own systems have the resilience to continue during the collapse of the industrial model and beyond?

These questions, I came to realize, are the questions of the agrocollapse.  It is frightening and alarming that the general public is not grappling with the great dilemmas of our time; it is downright Apocalyptic that even the sustainable agriculture community is not able to do so.

My own construction of agrocollapse is multi-faceted: it is a set of scenarios for thinking about the future, a series of data points from the present to improve our understanding, and perhaps most importantly, it is a developing set of strategies for thriving under difficult circumstances.

But it is also a process underway in the real world, one that runs parallel to the slow and step-wise decline of industrial civilization as it slides down the slope of energy descent.  Agrocollapse is not a simultaneous global catastrophe, and it is certainly not something that occurs in isolation from the many other social, economic, political, and natural forces that shape our world.  It is driven by financial collapse, peak oil, climate change, war, and social revolution; therefore, much like climate change and peak oil, it impacts different groups differently at different times.

Some may benefit, at least temporarily, from its effects.  Just as oil companies benefit from price spikes associated with peak production, and hedge funds benefit from rampant speculation and volatility in collapsing financial markets, so too do industrial agricultural producers benefit from high commodity prices resulting from similar phenomena.  Others may be devastated by its effects, like the rancher or pastoralist who is is forced to cull and destock the herd as a result of climate disruption and drought.

The pace of agrocollapse, and collapse in general, will be tempered by global connectivity and massive investments in maintaining the status quo; many have argued that the former is a vulnerability of the current system, but in fact global connectivity has acted as a buffer against localized collapse.  After a catastrophic earthquake in Haiti, aid poured into the country, unevenly and marred by bungling and corruption, to be sure, but the flow of resources certainly helped to mitigate the worst effects of the disaster.  The case is similar around the world: a desert community imports fossil fuels to run electric pumps during years of drought (Phoenix), refugees of seasonal floods are provided with tents, food, and medicine (Staten Island).  Manufactured goods, energy, and human resources move around the world at amazing speeds and with incredible efficiency; thus the pace of collapse is slow and uneven, straining our resources, which spurs our descent, but never quite resulting in immediate and global Armageddon.

The questions of the agrocollapse will be the main theme of this blog moving forward.  If we think, and plan, and prepare, perhaps we will preserve the vital elements of permaculture, and some critical manufactured technologies, so that our children and grandchildren will inherit a world that is livable and comfortable, and their society will be one that is aware of our history and the greatest elements of our cultural legacy.  This is our task.

Organic v. Conventional: The Yield Debate

Recently the journal Nature published an article of some significance.  The article is a meta-analysis entitled “Comparing the yields of organic and conventional agriculture”, and was written by Verena Seufert, Navin Ramankutty, and Jonathan Foley.   Meta-analysis is a useful and increasingly common research method employed by scientists.  When conducting meta-analysis researchers aggregate dozens and sometimes hundreds of different published research studies to discern broader patterns in the area of study.  This approach is becomingly increasingly common in the fields of medicine, climate research, and ecology, to name a few.

Summary

What follows is a cliff-notes, bullet point summary of the research results.   According to the study, “Overall, organic yields are 25% lower than conventional…”, however “organic performance varies widely over crop types and species.”

  • Yields of organic fruits and oilseed crops show a small (-3% and -11% respectively), but not statistically significant, difference to conventional crops
  • Organic cereals and vegetables have significantly lower yields than conventional crops (-26% and -33% respectively)

Yield performance varies widely not just based on the crop being produced, but also based on the agro-ecological and socioeconomic conditions under which that crop is produced.

  • Organic crops perform better on weak-acidic to weak-alkaline soils (pH between 5.5 and 8.0), possibly related to phosphorous being less available under acidic or alkaline conditions.
  • Organic performance is -35% under irrigated conditions, but only -17% under rain-fed conditions.
  • In developed countries organic performance is, on average, -20% whereas in developing countries it is -43%.

In summary, “Organic agriculture performs better under certain agroecological conditions – for example organic legumes or perennials, on weak-acidic or weak-alkaline soils, in rainfed conditions, achieve yields that are only 5% lower than conventional yields.”

Management also plays a critical role:

  • Having applied best management practices show better organic performance…organic yields thus depend more on knowledge and good management practices than conventional yields.
  • Organic yields are low in the first years after conversion and gradually increase over time, owing to improvements in soil fertility and management skills.

The improved management associated with organic agriculture also contributes to farm resilience, which can make a tremendous difference in relation to climate-related risk.  As the paper notes: “Soils managed with organic methods have shown better water holding capacity and water infiltration rates and have produced higher yields than conventional systems under drought conditions and excessive rainfall.”

Analysis

Some articles on the Internet have used this research to question the future viability of organic agriculture.  In particular, Time magazine’s “Ecocentric” blog published a post with the title “Why Organic Agriculture May Not Be So Sustainable.”  The article alludes to a criticism of organic agriculture cited by the Nature researchers: “Critics argue that organic agriculture may have lower yields and would therefore need more land to produce the same amount of food as conventional farms, resulting in more widespread deforestation and biodiversity loss, and thus undermining the environmental benefits of organic practices.”

What I found significant about the Nature article was not, however, the fact that organic yields are overall lower, but in fact how closely comparable those yields are under relatively difficult circumstances.  As the researchers note, “Organic systems may rival conventional yields in some cases…”  Consider the following facts:

  • Most agricultural subsidies are structured to favor large agribusiness, hence putting small-scale organic producers at an economic disadvantage, thereby negatively affecting capital inflows and technological innovation
  • 50 years of research at US land-grant institutions have focused on conventional, chemically-intensive agriculture.  In fact, the US has fallen behind countries like Austria, Switzerland, and Germany in leading-edge research in organic agriculture, adding another structural advantage for conventional agriculture.
  • The research did not distinguish between industrial and small-scale organics.  The former is characterized by scale, efficiency, and mechanization, allowing more land to be worked per unit of labor.  The latter is characterized by high-yield polycultures where more labor and management is required per unit of land, but overall farm yields can be much higher.

In this context, the comparison of organic to conventional becomes much more favorable and impressive, and illustrates that organics could indeed compete with, and perhaps could surpass conventional agriculture under the appropriate circumstances.

From a yield perspective, perhaps the real disadvantage to the organic producers, and the single most important factor accounting for the -25% differential, is the prohibition of nitrogen fertilizers.  Indeed, as the authors note: “Organic systems appear to be N limited, whereas conventional systems are not.  N availability has been found to be a major yield-limiting factor in many organic systems.”   The prohibition of chemical fertilizers in organic systems is understandable, considering the irresponsible and ecologically disastrous problems of nitrogen saturation and aquatic eutrophication (Google both for more information).

My attitude towards chemical fertilizers is more nuanced.  Surely saturating soils with NPK mixtures through chemical injections and sprays is unwise, but not being able to responsibly apply small to moderate amounts of chemical fertilizers in the appropriate context is a big setback for the sustainable agriculture movement.  And while nuanced views won’t change the mandates of organic labeling, I certainly think we should be rethinking our attitude towards chemical fertilizers in general.  If organic labeling had allowed for judicious and limited use of nitrogen fertilizer, perhaps the -25% differential would be much less, or even non-existent.  Additionally, nitrogen fertilizer can be produced sustainably from hydro or wind power (see freedomfertilizer.com).

Closing the yield gap between organic and conventional agriculture is a big challenge.  As we have seen, lower yields in organic agricultural systems are primarily a function of human management, structural problems, and socioeconomic constraints.  The challenges on the production side, while significant, could be easily surmounted given sufficient attention and resources.  One factor that is sure to contribute to further success is the continued education of farmers and ranchers.

Correlation and Causality: Science in Crisis?

Holistic Management practitioners have long known that reductionism makes for poor land management.  When one relies too heavily on a search for single causes of a problem, or has a myopic perspective on farm/ranch priorities, this can lead to financial ruin.  They also know that the ecosystems which they steward are complex; these complex systems respond to management decisions in novel and unanticipated ways, leading to constant surprises for land managers with decades of experience in the field.

This appreciation has been a source of tension with the research community.  Indeed, ecological research is fraught with challenges, many of them socio-economic in nature (like the difficulty in securing long-term funding), and others methodological or philosophical.

Ecological research, perhaps more so than any other field of biological inquiry, relies heavily on statistical correlation to ferret-out the complex and hidden relationships within natural systems.  The controlled conditions of the laboratory are of limited use in a field where natural relationships are the primary focus of study.

A recent article in Wired magazine challenges readers with the provocative title “Trials and Errors: Why Science Is Failing Us”.  While this article deals mostly with the difficulties pharmaceutical researchers are now encountering in the design of new medicines, as I read it I could not help but be reminded of the similar difficulties ecological researchers face when attempting to understand the intricacies of managed natural systems.  The following passage from the article elucidates the nature of these challenges:

The good news is that, in the centuries since Hume, scientists have… continued to discover new cause-and-effect relationships at a blistering pace. This success is largely a tribute to the power of statistical correlation, which has allowed researchers to pirouette around the problem of causation. Though scientists constantly remind themselves that mere correlation is not causation, if a correlation is clear and consistent, then they typically assume a cause has been found—that there really is some invisible association between the measurements.

Researchers have developed an impressive system for testing these correlations. For the most part, they rely on an abstract measure known as statistical significance… This test defines a “significant” result as any data point that would be produced by chance less than 5 percent of the time. While a significant result is no guarantee of truth, it’s widely seen as an important indicator of good data, a clue that the correlation is not a coincidence.

But here’s the bad news: The reliance on correlations has entered an age of diminishing returns. At least two major factors contribute to this trend. First, all of the easy causes have been found, which means that scientists are now forced to search for ever-subtler correlations, mining that mountain of facts for the tiniest of associations. Is that a new cause? Or just a statistical mistake? The line is getting finer; science is getting harder. Second—and this is the biggy—searching for correlations is a terrible way of dealing with the primary subject of much modern research: those complex networks at the center of life. While correlations help us track the relationship between independent measurements, such as the link between smoking and cancer, they are much less effective at making sense of systems in which the variables cannot be isolated. Such situations require that we understand every interaction before we can reliably understand any of them. Given the byzantine nature of biology, this can often be a daunting hurdle, requiring that researchers map not only the complete cholesterol pathway but also the ways in which it is plugged into other pathways.

Correlation is not casuality, and the search for correlations is now in a spiral of diminishing returns as complexity threatens to overwhelm our quaint and contrived mathematical models.  But what does this all mean for land managers?  After all, most folks are busy with the day to day realities of cattle prices, conception rates, harvesting schedules, and farm repairs.  Should land managers give up on science altogether and rely solely on observation?

Not so fast.  Let’s remember, science is a set of tools, and statistical correlation is a sub-set of tools within the broader framework.  While reducing natural relationships to a set of statistical correlations may seem a poor substitute for perfect understanding, it remains one of the most powerful tools we have to enhance our comprehension of the natural world.  Research is not a substitute for observation in the field, nor can we ever expect to have perfect knowledge of the systems which we manage.  We are imperfect beings with limited knowledge in a complex world.  A little humility is never a bad thing.

Thus the emphasis on holistic thinking.  The best we can hope for is adapt our management to new thinking and new information as we receive it.  Understanding the limitations of research gives us a useful lens through which we can view and analyze the results of scientific studies.  We must recognize that our decisions may have unintended consequences, and we must be vigilant to this possibility.  Our use of monitoring and feedback loops builds this recognition into the management process.  And although statistical correlation is a tool with limitations, it is still a powerful one that requires substantial data gathering to be effective, so work with scientists to gather as much data as you can where and when possible.  And remember that skepticism is always a healthy and worthwhile position to take when evaluating the results of any study, most particularly and especially when that study confirms your own human biases and beliefs.

Control What You Spend

A great quote from my interview with Holistic Management practitioner Walt Davis.   Another interview with Walt is in the pipeline, so stay tuned. Thanks to the blog dig this / dig that for the transcription:

“I was putting more money at risk every year than the potential for profit justified. Any time that you have to come out of pocket with cash in an agricultural situation–almost any situation I can think of but in agriculture it’s particularly true because we have control of such a small portion of the factors that affect us–we can’t control the market, we can’t control the weather, we can’t control the political situation–the one thing that we can control is what we spend.”

“Modern agriculture is maybe 60 years old–I saw the first nitrogen fertilizer I remember in 1950, maybe 1951… modern agriculture all goes back to nitrogen fertilizer. During that time of modern agriculture we have degraded our soils, we have degraded our food chain, or our people, and we have degraded the financial and mental health of our producers.”

“The better job I did of conforming to what the prevaling wisdom said was good management the worse shape I got in financially. I didn’t get back into good shape financially until I realized that it’s all out there. All you have to do is tailor your management to your environment, and substite management for money.”

Fukuoka sensei, is this Zen farming?

English: Masanobu Fukuoka throwing the first s...

Image via Wikipedia

A wonderful excerpt from the series about Masanobu Fukuoka on the Agroinnovations Podcast.  Thanks to the Astromen blog for the transcription.

People would ask: So tell us, Fukuoka sensei…is this Zen farming? He would say, No, no, no, it’s got nothing to do with religion, it’s just farming. It’s just farming. It’s a timeless understanding, and if I were to call it Zen farming, then right away you would take my farming and put it into your Zen file, and then that would be a way you could say, Oh I understand it because I can compartmentalize this whole thing and call it Zen. That would be playing into the need of our human intellect to try to understand things, and by doing that, gain control somehow.

[Fukuoka] didn’t want to do that, so he said: No, no, all I’m doing here is farming. But when you’re a farmer then you’re out in nature, and you see all of these wonderful dramas and these things of beauty, and you hear the wind blowing through the trees and so forth, and the farmer has many opportunites to break through and see God directly.

To him, the religions were an unnecessary structure that people have created to try to understand. And understanding is not part of this at all. If you really wanted to set him off, you would just say, Don’t you think people can understand nature? And he would say, People can’t really, truly understand anything.

Related articles

Check out this article from the Huffington Post on the Zen of Pruning.

Socialist or Entrepreneur?

The plain red flag is often used at socialist ...

Image via Wikipedia

A reviewer on iTunes had this to say about the Agroinnovations Podcast:

Unfortunately, it seems almost every episode is tainted with devotion to the man-made global warming myth and often socialistic economic theory. There is a lot of self-defeating philosophy in that if the government control the host and guests espouse were implemented then they wouldn’t be allowed to do the agricultural innovations they promote.  This is the kind of podcast you’ll get when the host is a socialist trying to be entrepreneurial.

What do you think?  Is the Agroinnovations Podcast socialist propaganda posing as entrepreneurship?

Shipping Containers as Farms? (Updated)

Intermodal shipping containers on a railway fl...After reading an article on Treehugger, I just learned about a Kickstarter Project that is attempting to modify “recycled shipping containers with the tools to grow fruits and vegetables in an urban environment.”  These shipping containers are to be fitted with hydroponic technologies and, presumably, electric lighting to provide plants with “solar” energy.

Shipping containers have several advantages that make them well suited to agricultural modification:

  • Containers are standard in their measurements, making them well suited to small scale manufacturing for modification
  • Containers can be moved fairly easily using existing water, rail, and road networks.  Even as fossil fuels become scarce, moving containers over fairly short distances will probably be feasible.
  • Containers can be fitted with a number of renewable, regenerative technologies that can move through a community as required

So while I agree with the basic premise of this project, I’m not sure I agree with the tactical implementation.  Why fit shipping containers with relatively expensive lighting technologies for producing vegetables?  The sun does a much better job for much cheaper; the energy yield for the vegetables is probably a thermodynamic loss.

Instead, why not modify the container to act as a mobile agro-industrial unit?  Dorn Cox of Greenstart has the jump on this, as he is currently installing open source biodiesel generators into an old Coca-Cola trailer.  The biodiesel generators are designed to process sunflower oil produced from his no-till organic sunflower crop.  Since Dorn doesn’t use the equipment year round, there’s plenty of machine down-time to warrant a technology share with neighboring farms.  The shipping container could also be fitted with additional regenerative open source technologies, like the open source Rodale crop roller.

The permacultural concept of guilds becomes useful here, as shipping containers could be dedicated modules (or guilds) for ecosystem regeneration: an aquaponics module for producing breeding fish; a mushroom lab for producing mycelium spawn; an apiculture module for building and deploying hives; and as mentioned above, a liquid fuel/no-till module for producing energy.

Centralizing shipping container modifications into an semi-industrial process will allow for rapid deployment of “seed” technologies that can be moved across the globe with the urgency that is commensurate with our current human crisis.

And check out this article, again via Treehuger, about growing shrimp in the desert.  Feeding the voracious 24-7 shrimp appetite of Las Vegas is probably not a good use for this tech, but overall the idea may make more sense than vegetable production, as the protein conversion efficiency of aquaculture is many times greater than a feedlot.

Update:

I found some good additional information after publishing this.  Apparently, lead paint is a problem in shipping containers…which may be very difficult and/or expensive to remediate.

Additionally, these things are hot and difficult to ventilate, which probably isn’t a huge problem in New Hampshire, but more problematic in Haiti or New Mexico.

Treehugger has really covered this issue over the years.  See the link below for a summary of this coverage:

http://www.treehugger.com/sustainable-product-design/the-shipping-container-scene-in-2010.html

And the National Young Farmer’s Coalition has a report back from a FarmHack event on Dorn Cox’s farm in New Hampshire.

Epigenetics, Allergies, and Microbiology

Image courtesy ddpavumba

New research is transforming our understanding of the relationships between micro-organisms, epigenetics, the human gut, and allergies. An excerpt from a new article on the website of the scientific journal Nature sums up the crux of this dynamic:

“These [micro-organisms] are flipping switches,” says Sarkis Mazmanian, a microbiologist at the California Institute of Technology in Pasadena. If these beneficial microbes fail to colonize our guts early in life, or if they succumb to a course of antibiotics, then switches don’t get flipped and the immune system can become hypersensitive, attacking harmless microbes and other substances such as pollen, pet dander or shellfish.

The greatest frontier in science is biological.  We must proceed with enthusiasm and with ethics.  A great article by my friend Cassandra Willyard.  Nice work.  Read it below.

Microbiome: Gut reaction

Turkey Tractors

© Mr.Bojangles from BackyardChickens.com

Happy Thanksgiving. Hope everyone is taking the time to be thankful for family, friends, and food.

Chickens aren’t the only poultry species suitable for rotational grazing via enclosed “tractors”.  Turkeys seem to do just fine as well.  So, in the spirit of Turkey day, I thought I’d share some innovative things that other agriculturalists are doing with turkey tractors.

Have a look at the YouTube video below, courtesy of bean444444. Also, check out the forum post below to learn more about people’s experiences with turkey tractors via the Backyard Chickens Form.

Turkey Tractors

Pesticide Use Breeds Aphids

According to research comparing conventional triticale production to organic production, “…the preventative application of insecticides against aphids does not produce any advantages even though it consumes a lot of time and money.”  This is because:

  1. “insecticides indiscriminately kill off beneficial animals that feed on the aphids”
  2. “[researchers] detected three times as many natural enemies of aphids and five times fewer aphids in the organic fields than in the conventional fields”

Fewer aphids in organic crop fields

New Agroinnovations.com Site

Welcome to the new, redesigned site Agroinnovations.com.  Several months after having a server crash, which caused many of the original urls for the podcast page to break, I’ve finally gotten around to fixing the site.  You’ll notice that all of the podcast urls are now working.  Not all have been given redirects that will allow old links to bring users to content, but that will be coming soon.

The site is now simplified, with two main sections: blog and podcast.  The blog contains a few hundred posts that I’ve written over the past 5 years or so, while the podcast has all 128 episodes that have been created to date.

With the launch of the new site, I’ll be blogging more frequently, and will get back to podcasting in the very near future.  I doubt I will be able to release a new episode once a week.  Look to the blog for information and opinions on permaculture and organic/sustainable agriculture.  I plan to update it frequently, so check back soon.

Holistic Planned Grazing Improves Soil Moisture

Article: Effect of grazing on soil-water content in semiarid rangelands of southeast Idaho

Authors: Weber, K.T. Gokhale, B.S.

Published: Journal of Arid Environments 75 (2011) 464-470

This article is a first for the Holistic Management community in a number of regards.  It is one of the first peer-reviewed journal articles to show a link between animal impact and increased soil moisture.  It is one of the first to specifically use (simulated) holistic planned grazing as an experimental treatment.  It is also one of the first studies to apply a suite of technological innovations, like GIS, GPS, and soil moisture probes, towards monitoring the effects of holistic planned grazing over the medium term.

The paper articulates the research goal:

The goal of this study was to determine if soil-water content is affected by land management decision (e.g. grazing and rest), within the semiarid sagebrush-steppe rangelands of southeast Idaho.  Specifically, this study sought to experimentally determine if a positive relationship exists between soil-water content and litter cover and if land use treatments can be used to beneficially manipulate litter cover.

The experimental design involved the division of a largely homogenous (ie topography, soils, climate) experimental grazing range into three fenced treatments.  The first was simulated holistic planned grazing (SHPG), “where cattle grazed at high density (66 AU/11 ha) for a short period of time (6 days) during the first week of June each year.”  Under the second treatment, rest rotation (RESTROT), “cattle grazed at low density (300 AU/ 1467 ha) for long periods of time (30 days) during the month of May each year.”  Recovery days for these two treatments were 359 days and 335 days, respectively.  The final treatment was total rest (TREST), “where no livestock grazing has occurred since June 2005.”

A number of ecological indicators were monitored through the course of the study.  Soil moisture was recorded using thirty-six Decagon ECH20 capacitance sensors buried at a depth of 100 mm; 12 probes were installed for each of the three treatments.  Vegetation variables measured were percent shrub, grass, litter and bare ground, and biomass was also measured via clipping and weighing.

After data collection, a number of statistical tests were run on the data.  First, the comparative results of percent litter cover:

Comparisons of percent litter cover revealed significant differences among all three treatments beginning in 2007 but no difference prior to this time.  Pair-wise comparison showed significantly higher litter cover in the SHPG pasture compared to the RESTROT pasture in both 2007 and 2008, as well as higher litter cover in the SHPG pasture relative to than found in the TREST pasture in 2007.

 A similar pattern emerged from the data set for soil moisture:

Comparisons of daily %VWC [percent volumetric-water content] among treatment pastures indicate a significant difference when all treatments were compared at once.  Pair-wise comparisons indicated %VWC was significantly higher in the SHPG pasture compared to the RESTROT and TREST pastures in 2006, 2007, and 2008.  No difference in %VWC was found between the RESTROT and TREST pastures in either 2006 and 2007 although %VWC was higher in the RESTROT pasture in 2008.

Do environmental factors alone account for these changes in soil moisture?  The authors explain that although “%VWC differs annually, it is differentially variable by pasture, suggesting both an environmental and a treatment influence.”

This study provides strong experimental evidence to support the effects of planned grazing and animal impact long applied by holistic management practitioners.  Specifically, this study validates the use of animal impact to control the arrangement of residual biomass in relation to the soil surface.   The authors summarize some of the physical and biological mechanisms at play:

  • Litter improves soil nutrients and structure while reducing erosion
  • Litter reduces soil surface temperature, which lowers surface evaporation and “impedes the volatilization of soil carbon, thereby reducing greenhouse gas emissions”
  • Grazed pastures have higher levels of organic matter particles in the soil, probably caused by increases in biological decomposition when litter is put in contact with the soil surface

The authors provide further insight:

 The changes observed in the SHPG treatment pasture appear to be the result of several interactive affects [sic] (high-intensity/short-duration grazing, animal impact, and increase litter cover) that produced a positive feedback cycle which may ultimately improve the condition and sustainability of these rangelands.

 And:

 Indeed, the different grazing treatments may have altered the porosity and organic matter of the soil within each treatment pasture through differential production and decomposition of litter, thereby offering a likely explanation of how these soils were able to retain more water throughout the growing season.

While these final thoughts are conjecture on the part of the authors, it certainly would fortify their argument if soil organic matter had been measured, analyzed, and reported with the same rigor of soil moisture.  Future replications of this study should include such measurements.

After many years, some research evidence is emerging that now supports many of the experiential lessons learned by farmer and ranchers.  One question arises: Why is this evidence emerging now, after many years of debate and inconclusive research?  A principle reason is the fact that Dr. Weber understands the principles embodied in Holistic Management and planned grazing, and has applied them in his experimental design.  To date, few research designs have taken this approach.  Another potential reason is our growing technological capacity to collect and analyze data.  GIS/GPS technology allows us to randomize data collection points; digital soil moisture probes allow for the creation of very large, accurate data sets with relative ease; and statistical analysis software gives a single researcher the power to analyze massive amounts of data in very short time periods.  With these new tools, which continue to grow and develop, monitoring and research should continue to experience major upgrades in the coming years, and should provide us with deeper insights into the functioning of grassland ecosystems and their ecological responses to management decisions.

The Decline in Fruit and Vegetable Nutrient Densities

Article: Declining Fruit and Vegetable Nutrient Composition: What is the Evidence?

Author: Davis, D.R.

Publication: HortScience Vol. 44(1) February 2009

We often hear claims that minerals in both our food supply and our soil have been declining for the past several decades.  Soils poor in minerals are a consequence of poor land stewardship, the argument goes, and as a result the quantities of vitamins and minerals in our food have also declined.  What research evidence exists to support this argument?

The article cited above is one of the few peer-reviewed articles that directly address this topic.  This article “summarizes three kinds of evidence pointing toward declines during the last 50 to 100 years in the concentration of some nutrients in vegetables and perhaps also fruits available in the United States and the United Kingdom.”

The first type of evidence presented deals with the “dilution effect” of synthetic fertilizers.  Research trials have compared mineral content of fertilized plants and unfertilized plants, concluding: “…fertilized plants contained larger amounts of minerals than the unfertilized plants, but these amounts were sufficiently diluted by the increased dry matter that all mineral concentrations declined, except for P.”

Comparisons of historical measurements are another type of evidence presented.  Statistical comparisons of older data (50 to 70 years) with current data reveal a similar trend of decline:

The strongest evidence for declines occurs for minerals in vegetables, especially calcium and copper (Cu), with median declines of ~17% and 80%…The one study that considered protein and vitamins found apparent median declines in 43 garden crops (nearly all vegetables) amounting to 6% for protein and 15% to 28% for three of the five vitamins studied.

Similar studies show statistically significant declines in potassium, manganese, zinc, copper, magnesium, calcium, phosphorous, and iron.

Data analysis reveals, however, that these trends are not necessarily well explained by soil mineral depletion.  Natural variability between cultivars may be responsible for declines in nutrient densities.   The author compares four side-by-side studies in order to test this hypothesis.  He concludes that these studies:

 show uniformly inverse associations between yield and nutrient concentrations for every nutrient studied so far (other than carbohydrate) – two minerals in broccoli; six minerals in wheat, plus protein, oil; and three amino acids in maize.  These four studies suggest to me that genetic dilution effects may be common when selective breeding successfully increases crop yields.

The author explains the apparent reason for these consistent declines in mineral and nutrient concentrations:

In fruits, vegetables, and grains, usually 80% to 90% of the dry weight yield is carbohydrate.  Thus, when breeders select for high yield, they are, in effect, selecting mostly for high carbohydrate with no assurance that dozens of other nutrients and thousands of phytochemicals will all increase in proportion to yield.  Thus, genetic dilution effects seem unsurprising.

Davis’ explanation for declines in food nutrient densities is certainly plausible, and supported by the evidence.  While current available data does little to support the hypothesis that declines in soil minerals are causing the decline in food quality, more research is required in this area to ascertain the true nature of the relationship between land management and nutrient densities in food.  The research of Dr. Kristine Jones on the pasture cropping techniques of Colin Seis indicate massive changes in soil mineral content associated with a shift to pasture cropping; the effect that these changes may have on our food supply is still poorly understood.

What is clear, however, is that plant breeding programs have had the unintended consequence of reducing our food quality; this evidence highlights yet another reason why our agricultural biodiversity is such an important resource for the future of food production.

Phenological Grazing Planning (Part II)

As noted in a previous post, the further development of collaborative monitoring tools for plant phenology will be critical to developing the concept of phenological grazing planning.  Implementing a phenology monitoring program is the first step in phenological grazing planning, but it is not necessary to have many years of data to incorporate these concepts into your planning.  Many land managers are often aware of the annual cycles of the principle species on the landscape; taking the time to think through and write down these key moments in species lifecycles can help in the planning process.

Mapping your landscape is also an important part of this process.  Species composition is determined by variable landscape features, like soil type and elevation.  Understanding the relative abundance of a species or a plant community will help you to understand what plants exist where, and as a result you will know which species life cycle patterns you must give the greatest attention on a per paddock basis.

Additionally, phenological grazing planning requires an understanding of how grasses and other plants grow.  While individual plants do not move through space, they do move through time.  As they do so, plants undergo changes in structure, palatability, and sensitivity to grazing.  Presented below is a review of some of the key phases in a grass plant’s growth and development.  This analysis is not comprehensive, but it will provide a strong basis for thinking about these concepts.

C3 or C4?

The differences between C3 and C4 plants are primarily metabolic, related to the different enzymes used in the photosynthetic apparatus of the plant.  For our purposes, it is enough to say the C3 grasses tend to be cool season plants, and C4 grasses are generally warm season grasses.  Some common C3 plants are wheatgrass, needlegrass, bromegrass, and bluegrass.  Cool season grasses initiate growth in the early spring, when soil temperatures reach a minimum of 40 degrees F.

These cool-season grasses produce high-quality forage early in the growing season. However, they do not grow during the hot periods in midsummer, and often become semi-dormant. They may grow again in the fall as temperatures cool and late summer precipitation replenishes soil moisture. Thus, there may be two growing periods for these grasses: early spring and late summer or fall. 1

Common C4 grass species include blue grama, buffalograss, and bluestems.  These grasses grow in a temperature range between 70 and 95 degrees F, although soil temperatures can be between 60 and 65 degrees F.  C4 grasses are more effective at using soil moisture, especially under droughty conditions.  In general, they are less palatable to grazers than cool season grasses.  As Trlica notes:

…because C3 grasses often enter the reproductive period at about the time that C4 grasses begin growth, livestock normally seek out this new growth from warm-season species. New foliage is always more digestible than more mature foliage, whether it be from a C3 or C4 species.2

The Phases of Growth

There are several identifiable stages of grass growth: seedling germination/establishment, vegetative stage, the “boot” stage, the reproductive stage, and the dormant stage.  Cereal producers have used more detailed tools for agronomic purposes.  One such example is the Zadocks scale.  For our purposes, the five stages listed above should be sufficient, and will be given consideration below.

Seedling Germination and Establishment

Seed germination occurs under proper environmental conditions, and is highly species specific.  Some species will only germinate when soil moisture and soil temperatures have reached a critical threshold; other species require fire, insects, or passage through an animal’s digestive tract to germinate properly.  Know your species, and take good notes of what you see in the field.

When planning your grazing, remember the following:

The most critical period in the life of a grass seedling is when the primary roots begin to die and the secondary roots may not have developed enough to properly feed the shoot. This period is particularly critical if soil moisture in the surface few inches of soil is limited and no subsoil moisture is present.3

Vegetative Growth

Plants enter the vegetative growth stage immediately after coming out of dormancy in the spring, or in the case of seedlings shortly after the development of secondary roots.  Range scientist L.L. Manske has written concisely about the vegetative growth stage of grass plants, with specific reference to the effects of grazing.  Below is an excerpt from his writings detailing key aspects of vegetative grass growth:

… the grass shoot’s production of three to three and a half new leaves during the growing season is important. When the shoot reaches the third-leaf stage, the apical meristem begins to produce flower buds rather than leaf buds, although formed leaf buds continue to grow and develop. Defoliation of leaf material before the shoot has reached this stage can disrupt the formation of leaf buds and leaves for the shoot, weaken the plant and diminish the plant’s ability to produce herbage.

Most native cool-season grasses reach the third-leaf stage around early June, and most native warm-season grasses follow in about two weeks. On strategies that begin grazing before the third-leaf stage, such as early spring grazing started in mid May, 45 to 60 percent of the potential herbage biomass will not be produced.

Defoliation of the shoot that has reached the third-leaf stage can stimulate the natural biological processes grass plants have developed in response to grazing. These processes include stimulation of vegetative reproduction, the growth of new tillers from the grazed shoot’s axillary buds. Properly timed grazing that removes only a small  portion of the leaf activates beneficial processes that can result in a 30 to 45 percent increase in herbage production.

Implementing grazing management strategies that start after the third-leaf stage and coordinate rotation grazing periods with grass growth stages can activate beneficial plant processes that result in increased herbage production and in turn reduce pasture and forage costs…4

The “Boot” Stage

The “Boot” stage of grass growth is the transitional stage from vegetative to reproductive growth.  This growth stage is initiated by changes in day length, and the transition is controlled by plant physiology and hormone releases.  According to Manske, “The first external sign of flower stalk development is the swelling of the sheath that encloses the flower head.”5

Annual seed production is not always required to maintain range health, often because grasses can reproduce via tillering, or in the case of sod grasses via underground rhizomes.  Since the forage quality and productivity of grass plants is much higher under vegetative growth, land managers might often prefer to graze plants after the third leaf stage and before the boot stage, thereby maintaining the grass community in a vegetative state.  As Trlica notes:

… a reproductive tiller may remain vegetative if the growing point (terminal [or apical] meristem) is removed by grazing. Vegetative growth, therefore, is favored by some grazing, which reduces the number of seedheads produced and may stimulate the formation of new tillers.

Manske provides insights on how phenological data can be used to plan grazing in relation to the boot stage: “Most cool-season plants enter the reproductive stage before June 21, the longest day of the year, and most warm-season plants enter the reproductive stage after June 21.

Reproductive Stage

Sometimes seed production is necessary, especially when a stand is in need of newly established seedlings.  Some land managers actually manage a stand to produce a seed crop, which is harvested and sold on the market.

Planned grazing can be used to steer the successional trajectory of a particular paddock or pasture.  In this context, timed grazing and controlled utilization may allow the manager to inhibit seed production of some plant species.  Subsequently, grazing animals can be removed from the area to allow seed production of desirable species.  This process can also be applied in reverse, depending on the plant species and their flowering times.  This approach requires good data on plant phenology, hence our previous emphasis on establishing monitoring protocols and collaborative databases.  For more information on managing successional trajectories, please see our video on Holistic Weed Management.

The Dormant Stage

Plants begin to prepare for dormancy during the growing season.  Carbohydrates accumulate in roots and crowns.  These sequestered resources are used for respiration during winter dormancy and then again for the first flush of green growth once growing conditions resume.

Phenological grazing planning is an implicit principle embodied in the concept of planned grazing.  It is our attempt here to offer tools and ideas for making this concept explicit in our thinking and planning processes.  The idea is based on three principles: phenology monitoring, understanding the grass life cycle, and planned grazing.  Hopefully, readers will find these concepts useful, and will apply them in their management process.  HMI will continue to explore these concepts in greater detail.  Ultimately, we aim to provide our community with useful tools for applying these concepts in practice.

1Trlica, M.J. Grass Growth and Response to Grazing. No. 6. 108. Range: Natural Resources Series. Colorado State University.  Online at: http://www.ext.colostate.edu/pubs/natres/06108.html

2Ibid.

3Stichler, C. Grass Growth and Development.  Texas Cooperative Extension.  Available online: http://publications.tamu.edu/publications/Forages/scs-2002-22a.pdf

4Manske, L.L. Kraus, A.M. Jirik, T.C. Manipulating Grass Plant Growth Can Enhance Forage Production. North Dakota State University. Available online: http://www.chaps2000.com/bin/ccs2r2.pdf

5Ibid.

Phenological Grazing Planning

According to Wikipedia1, “phenology is the study of periodic plant and animal life cycle events and how these are influenced by seasonal and inter-annual variations in climate.”  The discipline of phenology is often attributed to the great naturalist and author Aldo Leopold.  In fact, phenology is an ancient science that human beings have studied and applied for millennia.

Phenological phenomenon are expressed in the annual cycles of nature: a bear emerging from hibernation, a spring ephemeral blooming in the forest, or a grass seedling germinating and establishing itself with the assistance of summer rains.  Phenology is proving a critical science in studying the effects and pace of climate change around the globe.  Understanding phenology, moreover, is a critical part of land management, and grazing planning is no exception.

To date, attempts at phenological grazing planning have been subtle or poorly documented.  It is imperative that we improve our existing planning tools; this can be achieved by monitoring ecosystem phenology, and by incorporating phenological data into the grazing planning process.

Monitoring is the first critical element of phenological grazing planning.  Phenology is highly place specific, factors like elevation, latitude, seasonal variation, and species composition will affect annual ecosystem cycles.  Many groups have felt the need to develop a landscape-scale, collaborative phenological monitoring protocol and database.

This need has led to the USA National Phenology Network.  They have developed data collection sheets, documentation on collecting field data, and a collaborative web-based interface to enter and retrieve data from across North America.

Learning how to use and expand upon these kinds of tools will be critical for the continued development and refinement of planned grazing.  In 2011, HMI will be looking to build a stronger relationships between our community and organizations like the USA National Phenology Network.  We will encourage the use of these monitoring tools via outreach and education, and also explore ways to integrate these tools within the framework of holistic planned grazing.

In my next post, I will explore some of the possibilities that phenological grazing planning offers to the land manager.

1http://en.wikipedia.org/wiki/Phenology

Species Composition Changes in Response to Grazing

Article: Quantitative effects of grazing on vegetation and soils over a global range of environment

Authors: Milchunas, D.G. and Lauenroth, W.K.

Published: Ecological Monographs, 63(4). 1993. pp. 327-366

This is the second post dealing directly with the article under consideration.  For methodological details, please see the previous post.  We have seen the relationship between ecosystem productivity and grazing; there exists a strong and statistically significant relationship between aboveground net primary productivity (ANPP) and evolutionary history of an ecosystem.

Yet changes in ANPP occur over the medium term; changes in species composition can occur over shorter time periods:  “…we may consider species composition a fast, ANPP an intermediate, and soil nutrient pool a slow response variable.”

Thus, in the context of the multivariate regression models developed for this study, species composition was analyzed to answer the question: “Are there ecosystem-environmental and grazing variables that explain the variability in responses of dominant species to grazing?”  Changes in species composition were measured using dissimilarity values that ranged “from 0 (no differences between ungrazed and grazed sites) to 1 (completely different ungrazed and grazed sites).”

Regression analysis from the available data revealed strong and statistically significant relationships for several key variables:

Precipitation alone explained 24% of the variation in species dissimilarity between ungrazed and grazed sites. Variables entering the model restricted to only grasslands were again ANPP, consumption, and evolutionary history of grazing. ANPP alone explained 40% of the grasslands variance compared to 54% for the entire model. Although level of consumption was consistently both significant and a large contributor to R2, the number of years of protection did not significantly enter into any of the above models.  Increasing values of all independent variables led to larger differences in species composition between grazed and ungrazed sites.

What emerges is a portrait of those environmental and management variables that are most sensitive to species composition when sites are grazed or ungrazed:

The first three models (all communities, grasslands-plus-shrub- lands, and grasslands alone) consistently produced a sensitivity ranking of ANPP > evolutionary history of grazing > consumption, with ANPP increasing in effect on species dissimilarity as community types were narrowed.

A bullet point summary of the implications of these results is provided below:

  • Grazing has a greater effect on species composition in humid (highly productive) environments, partly because plant canopies are taller and thus have a greater structural effect due to grazing
  • Environments with a longer evolutionary history of grazing exhibit greater differences in plant communities when grazed
  • Sites with higher consumption (i.e. utilization) of available biomass by grazing animals showed greater changes in species composition when grazed versus ungrazed

In addition to general changes in species composition, the authors analyzed changes in absolute abundance of the single most dominant species.  Their results were as follows:

Changes in absolute abundance of the single most dominant species with grazing was most strongly related to evolutionary history of grazing in the all-communities model, and, together with consumption, precipitation, low temperature, and years of protection, explained approximately half of the variation.  Similar to the models for species dissimilarity, a majority of the explained variance could be attributed to ecosystem-environmental variables rather than intensity (consumption) or duration (years of protection) of grazing.

Species dominance reacted somewhat differently to grazing than overall species composition, especially when factoring in evolutionary history.  The dominant species tended to change more dramatically when evolutionary history was short:

Increases in the dominant species occurred under conditions of low consumption-short evolutionary history, and large decreases occurred under conditions of high consumption-short evolutionary history regardless of the level of ANPP. Sensitivity to differences in ANPP or consumption were relatively small when evolutionary history was long.  Under conditions of short evolutionary history, changes in the other variables had large influence on the dominant species compared with relatively small influence at long evolutionary history

In addition to just looking at the single most dominant species, the authors also looked at the two most dominant species.  These results were also interesting:

For a total of 274 sites, 126 sites (46%) displayed decreases in both of the most abundant species with grazing, 125 sites (46%) displayed one species decreasing and the other increasing, and 23 sites (8%) displayed increases in both species. The single most dominant species decreased in 68% of the sites that had one of the two most abundant species decreasing and the other increasing.  Less than 1% of grassland sites displayed increases in both dominants compared with 9% of shrubland sites, suggesting dominants in the two types of communities may be responding differently to grazing.

Changes in species composition may or may not occur under grazing pressure, but changes in plant growth form and canopy are frequently observed, where there is “…selection for low-growing, prostrate growth forms…”.  Existing species may simply change their growth form, or this can result via an actual change in species composition.  While often considered a grazing avoidance mechanism, this also creates nutrient dense grazing lawns that can increase the grazing efficiency of ungulates.

Although species composition can change over a relatively short time frame in response to grazing, this may not translate into an increase or decrease in primary productivity:

Primary productivity does not necessarily change when species composition changes, and can increase or decrease depending upon the replacement species, life-history traits, and the manner in which the continuing grazing pressure or stress affects water and light resources and nutrient cycling rates.

The response of shrublands to grazing is given some attention throughout this article.  In part, the authors are attempting to address the perception that shrub invasions increase with grazing.

Average consumption for shrubland sites and other sites combined was greater than in grassland sites, although aboveground net primary production (ANPP) was generally lower in shrublands or other sites compared with grasslands.  Grazing of areas with a shrub component is commonly reported to lead to increased dominance by shrubs and the conversion of grasslands to less-desirable shrublands.  Why then are we grazing shrublands at a relatively greater intensity than grasslands?

Changes in the dominant species in shrub ecosystems were also evaluated, again attempting to detect a discernable relationship between grazing and increased shrub prevalence:

On average, species dissimilarity of grazed vs. ungrazed shrublands was less than for grasslands, and increases in dominants in grazed areas were 9 times more likely in shrublands compared with grasslands.  This would suggest that shrublands are inherently more sensitive to grazing, but environmental conditions and ecosystem attributes of shrublands are those under which relatively less impact of grazing occur.

Careful monitoring of both management variables and changes in species composition could help to ameliorate shrub recruitment and successional changes as shrub-susceptible ecotypes are grazed.  In addition, more attention must be paid to utilization levels in shrub landscapes; reductions in utilization may reduce shrub invasion.  The use of GIS technology can help to identify areas on the landscape where shrubs are just beginning to invade.

The Effects of Grazing on Ecosystem Productivity

Article: Quantitative effects of grazing on vegetation and soils over a global range of environment

Authors: Milchunas, D.G. and Lauenroth, W.K.

Published: Ecological Monographs, 63(4). 1993. pp. 327-366

We have given significant consideration to Samuel McNaughton’s grazing optimization hypothesis.  Essentially, McNaughton argues that grazing can in fact improve ecosystem productivity through compensatory plant responses and other biotic and abiotic factors associated with the effects of grazing animals.  He provides compelling evidence to support these claims.

However, most of his research is specific to the African Serengeti.  As noted by the authors of the article under consideration, “no quantitative evaluations of the long-term effects of grazing on ANPP (aboveground net primary production) have been made across ecosystems.”  Therefore, the objectives of their research “…were to use quantitative techniques to compare the impacts of grazing on plant communities in relation to various grazing, abiotic, and ecosystem variables.”  The authors go on to name the variables with which they were most concerned:

Specifically, community variables included plant species composition, abundance of dominant species, aboveground net primary production (ANPP), root biomass, and soil carbon and nitrogen of grazed and ungrazed sites. We asked how these depended upon grazing variables such as level of consumption (intensity) and years of protection from grazing (duration), and upon ecosystem-environmental variables such as mean annual precipitation, high and low temperatures, latitude, ANPP, and evolutionary history of grazing. We then asked whether relationships differed among grasslands, shrublands, forests, deserts, and high-elevation sites.

In order to perform such a comprehensive and global analysis, they searched and compiled information from the scientific literature to create a large data set for statistical analysis.  The authors elaborate:

Approximately 500 potential articles were surveyed, with 97 articles representing 276 data sets obtained for analyses. The criteria for selection were that (1) ungrazed controls were compared with grazing treatments, (2) grazing was yearlong or during some part of the growing season, but not only during winter in temperate locations, and (3) species abundances and years of treatment, plus either above- ground net primary production (ANPP) of ungrazed treatment (or peak standing crop) or grazing intensity (either as a percentage of ANPP or as a stocking rate with ANPP) were provided or could be obtained from the authors. Other data compiled included precipitation, mean low and high temperatures for the coldest and warmest months, range of the annual low-high temperatures, ANPP of grazed plant communities, and latitude of the site. Belowground data most commonly reported were root mass, total soil N, and soil organic matter or carbon.

In regards to the nature of the included studies, the authors provide this information:

Some of the studies used in the analyses were from systems with native grazers where populations are not regulated by humans, some were from sites where grazing by domestic livestock was “uncontrolled” or “free- grazing” or represented “overgrazed” situations, but most were studies of controlled levels of grazing by domestic livestock.

To determine a key variable in their statistical models, they turned to their colleagues in the scientific community:

…sixteen scientists with several different areas of expertise and from various parts of the world were asked to categorize the sites according to evolutionary history of grazing, and to rank the certainty of their estimates.  The individuals were asked to rank each study site either 1, 2, 3, or 4 for least to greatest evolutionary history of grazing, and to rank their estimate either 1, 2, 3, or 4 for low to high certainty.

Statistical analysis performed on the data relied heavily on the use of multivariate regression models.  Various iterations were performed on different statistical models. Models that had poor explanatory power were not included in the results; models using independent and dependent variables with strong relationships were included in the results and discussion of the paper.  Since stronger relationships were found in grassland and shrubland communities (which tend to have a longer evolutionary history of grazing), separate “regressions were run for all community classes combined, grasslands-plus-shrublands, grasslands, and shrublands when sufficient data were available.”  The statistical models developed are given consideration below.

Aboveground Net Primary Productivity

The response of ecosystem productivity to grazing is a controversial topic that has been under debate for decades.  This paper provides strong evidence that grazing can increase or decrease ecosystem productivity.  The authors describe the measurement method for ANPP:

In the majority of cases ANPP was estimated as peak standing crop in ungrazed treatment and in temporarily caged grazed treatment; compensatory growth due to current-year defoliation is not accounted for. [emphasis added]

The summarized results of the regression analysis are provided below:

Most of the differences between ANPP of grazed vs. ungrazed plant communities were negative. However, the statistical models for grasslands-plus-shrublands or for grasslands alone predicted positive ANPP responses to grazing in some situations. For the entire data set, 17% of the cases had positive values for the effects of grazing on ANPP and these were generally low levels of consumption and few years of treatment.

The authors elaborate on those conditions where grazing tends to induce a positive productive response:

Conditions under which grazing was more likely to increase or have no or small effect on ANPP were long evolutionary history and low productivity, regardless of the number of years of grazing treatment or the levels of consumption within a range generally not considered abusive “overgrazing.”

In other words, grasslands and shrublands seem to benefit from moderate grazing, while mountains, deserts, and forests are less likely to see an improved productive response due to grazing.

When analyzing below-ground productivity, even across ecotypes, this argument becomes even more compelling:

Whereas the effect of grazing on ANPP averaged -23%, the effect on root mass averaged + 20%. Further, positive effects of grazing on root mass occurred in 61% of the sites where grazing had negative effects on ANPP and in 62% of sites where differences in ANPP were negative, positive, or not known. [And] negative impacts of grazing on aboveground production were accompanied by as many positive as negative responses belowground. The general perception of decreased plant production with grazing may not be as great when viewed at the level of the whole plant

Another critical data point makes this argument more persuasive.  As we have seen in previous articles, compensatory growth due to herbivory can be a powerful force driving greater ecosystem productivity.  Yet, as mentioned previously, this study did not account for compensatory growth due to defoliation in measures of ANPP.

Of critical importance is the concept that evolutionary history may be a key driver affecting ecosystem response to herbivory and defoliation.  The presented data show a very strong relationship between evolutionary history of grazing and ANPP; sites with a long evolutionary history of grazing show greater resilience and in general respond more favorable to herbivory.  As the authors point out, “the predominance of ecosystem-environmental variables rather than grazing variables in sensitivity analyses suggests that where we graze may be more important than how we graze.”

The authors address a critical point of weakness in their “meta-analysis” approach:

Our approach entailed combining studies that used different methods, grazing systems, and animals, and varied in topography or weather during the year(s) of study, etc. The studies also spanned a range of strong to weak experimental designs and degrees of accuracy in estimating variables such as aboveground net primary production (ANPP) or consumption.

Also of significance is the fact that most of these studies represent systems under management either by scientists or field managers.  In most cases, the natural cyclic patterns of grassland ecology so thoroughly described by McNaughton are not in effect; the critical factor of human management may in fact be the principle phenomenon driving “noise” in the research data.  Yet, as the authors note, the “general directions indicated by the relationships and the relative influence of variables in the statistical models” on the whole seem acceptable, especially when tempered by thoughtful analysis.

In my next post, I will present the research results from this paper dealing with changes in species composition, and the relative impact of grazing on shrubland ecosystems.

The Natural Cycles of Grazing Ungulates

Article: Ecology of a Grazing Ecosystem: The Serengeti

Authors: McNaughton, S.J.

Journal: Ecological Monographs, 55(3) 1985, pp. 259-294

In previous posts, we have analyzed research dealing with spatial heterogeneity on the landscape.  Sometimes spatial heterogeneity is a desirable management objective, and can be achieved through management, such as rotating fire annually through paddocks or through grazing planning.

But spatial heterogeneity is also a natural result of a landscape that is edaphically, climatologically, and topographically variable.  These natural differences occur both through time and space.  In many instances, human managers have failed to grasp this most fundamental of natural principles at a landscape scale.

S.J. McNaughton’s research shows that animal behavior in unmanaged grassland ecosystems is often a response to spatial and temporal heterogeneity.  During their annul migration, wildebeest and other grazers are constantly reacting to uneven precipitation patterns across a climatologically stochastic landscape:

Large wildebeest and gazelle herds arrived on the Serengeti Plains within 3 days of the first significant rainfall and remained there as long as precipitation promoted grass growth.  They kept the vegetation in a grazing lawn throughout the season so that leaf tissue was almost all that was available.

Natural cycles determine the movements of migratory mega-herds on a landscape scale:

…nomadic herds move at the beginning of the dry season to grasslands that have sustained low grazing intensities during the wet season.  Large herds enter those mid-grasslands at their peak biomasses, graze them heavily, then move onward.

Those familiar with the Serengeti mega-herd migrations are aware that animals move from the high precipitation north and into the brittle southern plains during the rainy season.  These mega-herds move in a clockwise migratory pattern from north to south and back north again over a 6 to 8 month period, giving birth to and rearing their young in the process.  Video evidence shows animals are highly sensitive to precipitation patterns, and as note above, will follow rainfall in search of green swards.

These descriptions may give one the impression that precipitation patterns are merely uneven over large geographic distances as climate regimes change with latitude and topography.  While this is true, it does not paint a complete picture of what is actually happening.  Precipitation patterns are also uneven at relatively short distances, creating spatial and temporal heterogeneity at macro and micro scales; animals seem to have built-in behavioral mechanisms to deal with these random natural phenomenon.  As McNaughton observed:

The lack of correlation between productivity patterns of three stands on the Serengeti Plains separated by distances of 4-10 km emphasizes the low predictability of productivity pulses.  Productivity ranged up to a maximum of 40 g/m2/d in such pulses, so the food potentially available to ungulates can be substantial, but its occurrence in space and time is highly variable.  The ability of grazers to track such productivity pulses was documented by a close relationship between gazelle density and primary production over the duration of such a pulse.

Population densities in time and space are determined by precipitation, and ultimately by primary productivity:

When primary productivity increased due to showers, the gazelle population increased; when green biomass decline between showers, the population decreased.  Localized areas of higher primary productivity, therefore, act as grazing foci.

Holistic Management is based on premises gleaned from careful observation of nature.  But we must not forget that our managed ecosystems are inherently artificial.  Fencing, vaccinations, domestic livestock, submersible pumps, these are all technological innovations that are common place on most ranches.  In our haste to privatize land and commodify its output, we may have inadvertently inhibited the ecological forces responsible for maintaining healthy grasslands.  One unintended consequence is our inhibition of the natural migratory behavior of grazing ungulates.  In North America, bison herds exhibited similar behaviors to the mega-herds of the Serengeti:

Historical accounts of the American bison suggest that they were fully as mobile as the Serengeti migratory fauna.  Rapid movements, sometimes over large distances, are a characteristic behavioral pattern of undomesticated animals that evolved in grassland ecosystems.

Even at small scales, our inhibition of natural animal behavior may have consequences for the health of the land:

Deterioration of agricultural grazing lands may be less a consequence of stocking density than of the reduced responsiveness of a confined fauna to the temporal and spatial dynamics of grassland ecosystems.

While we may never fully restore these grassland ecosystems, we have available to us the tools we need to more accurately mimic the natural processes that maintain healthy grasslands within the socioeconomic context of modern ranching.  Some guidelines can help us improve our planning based on grassland ecology.  First, precipitation is critical to grassland productivity.  Every drop of rain must be conserved through enhanced management.  Animal impact can break soil crusts and the keyline plow can improve water infiltration for maximum conservation.

Regardless of soil condition, precipitation is inherently uneven across the landscape, especially in brittle environments.  The larger the management unit is in size, the more likely one is to encounter uneven precipitation patterns from one year to the next.  Grazing planning can be used to mimic the natural behavior of grazing animals, creating grazing foci in areas of high precipitation and permitting deferred recovery of temporally arid zones.  This type of planning may also improve animal performance.

As our understanding of these processes evolves, it may become possible to build landscape level grazing corridors that more accurately mimic natural grassland migrations.  Mega-herds with multiple owners may move through these corridors via negotiated arrangements with landowners as grass farming becomes a separate but complimentary profession to animal husbandry.  Currently, this possibility is wishful thinking considering our current socio-economic and cultural context; however, with time, both economics and biology may trump culture, and people may begin to realize the benefits of restoring these natural cycles.

Utilization and Multi-Species Grazing in the African Serengeti

Article: Ecology of a Grazing Ecosystem: The Serengeti

Authors: McNaughton, S.J.

Journal: Ecological Monographs, 55(3) 1985, pp. 259-294

McNaughton’s research also sheds light on the proportions of utilization and the effects of multiple ungulate species harvesting biomass from the same resource base.  As we have noted repeatedly on this blog, utilization is a key factor that determines the spatial geometry, nutrient cycles, and successional trajectory of grassland ecosystems.  In light of what McNaughton’s research has shown us about natural cycles in unmanaged grazing ecosystems, the question arises: What utilization patterns are observed in nature?

McNaughton provides utilization estimates through a variety of statistical tools:

…estimating consumption by comparing peak biomass inside fences and terminal biomasses outside fences would have led to the conclusion that 92% of aboveground production was consumed…the annual average consumption as a proportion of actual primary production in Serengeti grasslands exceeded .5 at 19 of the 28 study sites; some exceeded that value by a substantial margin.  The most lightly grazed Serengeti site, with 17% of aboveground primary productivity consumed by herbivores, was well above the values from most terrestrial ecosystems.  The maximum proportion consumed was .94.

And:

Similar estimates for the Serengeti region would indicate that consumption averaged 92% of aboveground production.  A more realistic estimate is the ratio of consumption to actual net productivity, which averaged .66 with a median of .71.

Clearly there is significant variability in utilization patterns, with extraordinarily high values at some spots and relatively low values at others.  The average and mean may mask this variability.  Deriving a utilization rule of thumb from this data is not necessarily recommended.  However, what is apparent is that animals are selecting for high utilization in some areas and lower utilization in others.  Animal behavior in response to a changing environment is a strong factor that drives uneven utilization on the landscape.  This will be addressed in a subsequent post.

Grazing ungulates in the African Serengeti also prefer green forage; migratory patterns on a vast, unfenced landscape allow animals to graze green forage almost exclusively: “green forage made up a relatively constant proportion of consumption.  [Approximately] 80% over a broad range of green forage on offer.”  In modern-day ranching operations, hay is usually shipped in from irrigated pastures or distant biomes to simulate similar feeding behavior.

One must remember that in ecological terms, the Serengeti is a multi-dimensional system.  Grazing herds are not monotypic; that is, a variety of grazing ungulates coexist on the landscape, each one seeking advantage through different feeding strategies.  McNaughton notes this in his observation of the synergies between zebra (an equine species) and wildebeest (a ruminant species):

The appearance of the sward changed substantially during the grazing succession.  Prior to wildebeest passage, the grassland had little apparent structural differentiation.  After they passed, ungrazed patches stood out as tall clumps.  That structure facilitated zebra foraging in a way heretofore undescribed, as I observed zebras walking from tall patch to tall patch to feed.  Grazing by zebras had a leveling effect on the vegetation, and the regrowth following their passage produced a structurally homogenous grazing lawn of high biomass concentration.

These interactions also shed light on how utilization occurs over time and space in a multi-species environment.  As McNaughton observed:

During their passage through the stand, wildebeest consumed 156 g/m2, 76% of the initial standing crop, in a few hours.  The zebra herd subsequently consumed 21 g/m2, or 44% of the remaining forage.  Overall, the two grazers consumed 87% of the initial standing crop in a 4-d period.  To the extent that there is excess soil moisture, such stands will regrow after grazing.

The following table, taken directly from the referenced article, displays the extent to which multi-species environments are subjected to different grazing pressures in the course of a year.

A study of this table reveals seasonal changes in grazing preferences for each species.  It also shows that nature has filled various niches with the preferential feeding behavior of different species, thereby allowing for a more complete trophic food web and full-spectrum utilization of available biomass resources.

McNaughton’s observations force us to reevaluate our own approach to land management, raising some difficult questions in the process.  Can we simulate natural ecosystem processes through the use of multi-species herds?  Does multi-species grazing in a ranching environment result in a more effective utilization of available biomass resources?  Will multi-species grazing increase the nutrient density of the grassland, creating a dense and nutrient rich “grazing lawn”?  And can human ingenuity be used to apply similar grazing patterns that are based on nature’s model?

Plant Productivity and Compensatory Growth

Article: Ecology of a Grazing Ecosystem: The Serengeti

Authors: McNaughton, S.J.

Journal: Ecological Monographs, 55(3) 1985, pp. 259-294

As noted, the relationships between grazers, grasses, and other biota are complex and highly connected.  The research of Samuel J. McNaughton has provided a treasure trove of empirical insights, both observational and statistical, into these relationships.  This post explores the relationships between plant productivity and grazing as described by McNaughton.

Using his traditional approach of observation and data collection, McNaughton presents a rigorous statistical analysis of a variety of factors in the paper cited above.  The research presented was

…designed to obtain information on vegetation dynamics, the nature of plant-herbivore relations, and ecosystem processes in Earth’s last, vast unmanaged grazing ecosystem [the Serengeti] constituting a natural ecological unit.

A principle part of his analysis was evaluating the factors that measurably affect ecosystem productivity.  Naturally, productivity had a strong relationship to annual precipitation:

Productivity of control plots was linearly related to annual rainfall….this relationship explained [approximately] 48% of the variance; inclusion of hilltop and lowland stands from the regional sites reduce the correlation substantially (r = .416) and there were three evident outlier stands at high rainfalls.

McNaughton also presents evidence consistent with his hypothesis that grazing can increase grassland productivity:

The stimulation of aboveground productivity due to grazing was maximum at intermediate grazing intensities… for midslope and flatland grasslands…

The following figure, taken directly from the referenced article, illustrates nicely the ability of grazing animals to maximize productivity at intermediate grazing intensities:

Also noted is the fact that grazing intensity and plant compensatory mechanisms may be the driving forces determining productivity:

Due to the partial ability of grazing to override the rainfall dependence of plant productivity, [annual primary productivity] was controlled more by mean annual grazing intensity than by annual rainfall [and]…grazers tended to override rather than merely amplify patterns of intrinsic vegetation productivity.

Compensatory growth in response to herbivory was also measured and “…on average, only [approximately] 60% of the forage consumed by herbivores was replaced by compensatory plant growth within the same year.”

Although covered in a previous post, it is worthwhile to reiterate some of the mechanisms responsible for these rather impressive compensatory responses:

Reductions in plant competition in grasslands maintained in a short grazing lawn, and competitive release due to canopy opening in taller vegetation, also may be important.  By maintaining an open canopy, conserving soil moisture, and recycling nutrients that would become immobilized in senescent plant tissues, grazing may alleviate the intensity of both intraplant and interplant competition.

Yet plant compensatory growth responses to grazing induced defoliation do not necessarily indicate symbiosis or mutualism:

… compensatory growth of the grasslands did not compensate completely for removal by herbivores, and the grasses have evolved levels of silicification, an antiherbivore defense, more pronounced than have been recorded in any other ecosystem.  Thus it is improper to conclude that grazing is strictly advantageous to the plants.  Highly interactive organisms can be interdependent, as are a parasite with a reduced virulence and a host with increased resistance, without being mutualistic.

In nature, grazing is a self-limiting phenomenon driven by successional dynamics and changes in the species composition of the plant community:

The invasion of heavily grazed grasslands by other species that are more grazing tolerant or avoidant (due to low palatability) than previous species, commonly referred to as a consequence of “overgrazing”, indicates that there are limits to which a flora con tolerate defoliation and other grazing effects.  That consequence of grazing represents a natural negative feedback at the community level that will tend to restore a moderate level of grazing in the system.

Land managers observe similar changes when land deterioration and species composition change as a result of poor management decisions, which often force destocking.  So while grazing at optimum levels can in fact increase overall productivity, ecosystem constraints will limit grazing in both managed and unmanaged grasslands.

Grazing ungulates, plant biomass concentrations, and nutrient cycling

The evolutionary ecologist S.J. McNaughton is well-known as a strong advocate of the grazing optimization hypothesis.  Essentially, this hypothesis is summarized as follows:

…grazing benefits many grasses and other plants in grassland ecosystems… moderate grazing promotes the productivity of many grasslands above the levels that prevail in the absence of grazing. {footnote} Grasses and Grazers, Science and Management. McNaughton, S.J. 1993. Ecological Applications, 3(1) pp. 17-201

Through the years, McNaughton’s research has been empirically thorough and statistically rigorous.  His general methodological approach has also been simple and straightforward.  Through the use of fencing exclosures in the still wild grassland ecosystem of Serengeti National Park, he has been able to measure and compare the effects of grazing on vegetation, soil, water, and nutrient cycling.  The African Serengeti is home to 3 million head of over 25 species of herbivorous ungulates, and is one of the last remaining wild grassland ecosystems in the world.  Therefore, McNaughton’s research provides key insights into the natural functioning of grassland ecosystems in the absence of massive human interventions like fencing and domestic livestock.

In one of his research papers, McNaughton explores the idea that

…gregariousness in grazing animals may increase foraging efficiency by modifying vegetation structure to increase food yield per bite to the individual grazer in a herd. {footnote} Grazing Lawns: Animals in herds, plant form, and coevolution.  McNaughton, S.J. 1984.  The American Naturalist, Vol. 124. No. 6 pp. 863-886.2

In this research, he compares biomass concentration data from exclosures and the natural surrounding grasslands.  His measurements reveal that biomass concentration “was consistently higher outside exclosures (0.44 mg/cc) than inside them (.34 mg/cc)”.  And “the maximum biomass concentration of grazed vegetation was achieved only when the canopy height was arrested at very short statures, i.e., in grazing lawns.” 3

These research results have implications for both land managers and ecologists:

…low plant biomass concentrations, even if total standing crop is high, can result in forage consumption rates insufficient to meet herbivore energy and nutritional requirements, leading to declining herbivore condition amid high plant biomasses.  Below a bite size of about 0.3 g, a cow-sized animal is food limited…cow bite size will fall below that level at plant biomass concentrations below 0.8 mg/cc. 4

As noted above, what is required to maintain high biomass concentrations are “large dense animal aggregations [that] create and maintain vegetation of high biomass concentration and quality…”  Moreover, “individual grazers obtain a foraging advantage by membership in a herd because of the greater forage yield per bite from grazing lawns compared with lightly grazed vegetation.” 5

In this case, biomass concentration was measured as the weight per volume of green forage (milligrams per cubic centimeter).  McNaughton’s research demonstrates that biomass concentration could in fact be used as a key measure of grazing efficiency as a function of plant productivity; as a rule of thumb, biomass concentrations at 0.8 mg/cc and above could be considered optimal for superior animal performance.

Other similar research conducted by McNaughton demonstrates the importance that large animal herds have for nutrient cycling.  Through the course of 20 years of observation, he noticed that animals tend to concentrate in some areas and not in others.  To test the hypothesis that soil nutrients are higher at areas of animal concentration, McNaughton extracted soil cores at these sites and paired them with similar sites where animal concentrations are not common.  In terms of Nitrogen (N) results were noteworthy:

…the net N mineralization rate in soils supporting dense resident animal populations was over twice that of areas where animals are uncommon…[and grazing] leads to increased leaf N concentration and therefore to litter of greater decomposability.  In addition, urination enriches soil with N from urea, leading to a burst of organic matter mineralization that produces greater available mineral N in the soil than is added as urea.  {footnote} Promotion of the Cycling of Diet-Enhancing Nutrients by African Grazers. McNaughton, S.J. Banyikwa, F.F. McNaughton, M.M. 1997. Science Vol 278.6

Similarly noteworthy were the results for sodium (Na) concentrations.

Standing stocks of extractable Na concentrations were universally, and substantially, higher in soils of animal concentration areas…[and] grazing increased the Na supply from Serengeti soils by an order of magnitude. 7

Sodium is an essential element for animals but required at best in very small concentrations by plants.

Also, “Serengeti grazers tangibly accelerate the mineralization of two minerals of considerable importance in animal nutrition.”  This means that “habitat deterioration is not an inescapable consequence of increased density of organisms.”  On the contrary, in some cases it would seem that dense animal herds are in fact responsible for maintaining resilient and productive grassland ecosystems.

Other research by McNaughton provides further insight into the nature of biological organisms as the lynch pin for nutrient cycling in grassland ecosystems.  McNaughton has observed that “freshly deposited dung was more likely to be adjacent to other fresh dung with an active dung beetle fauna than to older dung.” 8 McNaughton, S.J. 1985. Ecology of a Grazing Ecosystem: The Serengeti. Ecological Monographs, 55(3) 1985, pp. 259-2949  While the mechanisms for this are not well understood, it seems that grazing ungulates deliberately deposit their dung in areas where it will be quickly recycled by localized dung beetle populations.

Finally, McNaughton recognizes the role of grazing ungulates as nutrient recyclers in their own right:

…a major contributor to the stimulatory effect of grazing on growth of the Serengeti grasslands likely is nutrient recycling through dung and urine, emphasizing the importance of large grazing mammals in the dynamics of grassland ecosystems.9

In summary, ecosystems that in which grazers, grasses, and other biota have coevolved are enmeshed in a complex and interrelated web of symbiosis and mutualism; understanding the dynamics of these relationships will help land managers to more effectively mimic the natural processes at work in these ecosystems.

1Grasses and Grazers, Science and Management. McNaughton, S.J. 1993. Ecological Applications, 3(1) pp. 17-202.

2Grazing Lawns: Animals in herds, plant form, and coevolution.  McNaughton, S.J. 1984.  The American Naturalist, Vol. 124. No. 6 pp. 863-886.

3Ibid.

4Ibid.

5Ibid.

6Promotion of the Cycling of Diet-Enhancing Nutrients by African Grazers. McNaughton, S.J. Banyikwa, F.F. McNaughton, M.M. 1997. Science Vol 278.

7Ibid.

8McNaughton, S.J. 1985. Ecology of a Grazing Ecosystem: The Serengeti. Ecological Monographs, 55(3) 1985, pp. 259-294

9Ibid.

The Grazing Optimization Hypothesis

Article: Compensatory plant growth as a response to hervibory

Author: McNaughton, S.J.

Journal: Oikos 40: 329-336 1983

The relationship between grasses and grazers is a complex one influenced by a number of biotic and abiotic factors.  Some researchers and theorists have argued that grazing, on the whole, has a negative influence on plant biomass as a result of repeated defoliation.

Advocates of the grazing optimization hypothesis have argued for the opposite.  One of the most prolific and well respected proponents of this hypothesis is behavioral ecologist S.J. McNaughton.  He summarizes a principle tenet of the grazing optimization hypothesis thusly:

Providing there is an intervening period of growth, removal of vegetative tissues to a certain proportion of their initial level is rarely translated into a commensurate proportional reduction in the final yield of those or other plant tissues.

McNaughton does not base this assertion on simple conjecture, but on a wide body of empirical evidence, both from his own research and the research of others.  Here are some excerpts from the research literature that support his claims:

…a 50% defoliation at the 2nd-4th leaf stage [in radishes] resulted in only an 8% reduction in final leaf area and that a 100% defoliation at this stage resulted in only a 42% reduction in final leaf area.

And:

In an experiment in which cattle were stocked on Cynodon spp. at 7.5, 10, and 15 animals per hectare over a two year period, maximum yield of both forage and animal biomass occurred at the intermediate animal density.

Plant responses to herbivory and defoliation are certainly species specific, as some species have developed stronger compensatory mechanisms in the face of constant evolutionary pressure.

Additionally, plant responses may depend “on plant developmental stage at the time of defoliation.”   Research on the effect of the Colorado potato beetle (Leptinotarsa decemlineata) on tuber yields demonstrates this fact:

…tuber yield is unaffected when defoliation occurs between the fourth and sixth week of growth.  Prior to and after this, there are escape windows in time, and even defoliation levels approaching 100% have little effect of final yield.

Likewise, the defoliation of soybean had less effect on the yields of seed,

if it occurred during vegetative stages of growth than if it occurred during seed filling…Removal of half the foliage during vegetative stages reduced yield only about 10%, and 100% defoliation resulted in a yield reduction of less than 40%.

According to McNaughton, the mechanisms responsible for plant compensatory growth as a response to herbivory are manifold:

  • Cytokinins promote cell division and the activation of meristems, promoting tillering in grasses as a response to herbivory
  • Prevention of shading of leaves lower in the canopy can extend the lifetime of productive tissue
  • Increased root-shoot ratio can improve plant water status
  • Reduction of the transpiration surface conserves soil moisture and extends the growing season
  • Reduced competition for substrates between reproductive tissues leads to larger seed size and nutrient content
  • Hormones present in animal saliva may promote plant growth
  • Associations between herbivores and mycorrhizae improve plant nutrient uptake

Finally, McNaughton concludes:

I do not contend that herbivory maximizes plant fitness, but that plants have the capacity to compensate for herbivory and may, at low levels of herbivory, overcompensate for damage so that fitness may be increased.

Grazing Systems, Exclosures, Increasers, and Decreasers

Article: The Vegetative Response under Various Grazing Management Systems in the Edwards Plateau of Texas

Authors: Reardon, Patrick O.; Merrill, Leo B.

Published:  Journal of Range Management (1976), Volume 29 (3)

This article describes a twenty year study conducted in the Edwards Plateau of Texas.  The study compared the vegetative response of five different grazing management schemes.  The five schemes were as follows:

(1)   Pasture that was ungrazed by livestock or white-tailed deer (exclosure)

(2)   Pasture grazed by deer only

(3)   Pasture lightly grazed at 16 AU/Section

(4)   Pasture heavily grazed at 48 AU/Section

(5)   4 deferred rotation pastures at 32 or 43 AU/Section

The research was determined by weighing clippings from each section in grams.  The plant material was divided into four groups: decreasers—plants that decrease under excessive grazing pressures; increasers—plants that increase when decreasers decrease because of excessive grazing; Weeds were not classified as desirable or undesirable; and dry organic matter to include all dead grass, weeds, tree leaves, and manure.

After the twenty year study, several conclusions were reached.  First, they take a look at the decreaser plants.  The enclosures both had a lower yield of decreaser plants than the deferred pasture.  This tells us that these plants need some grazing in order to flourish.   Also, the heavily grazed pasture had significantly less decreaser plants.

The increaser plants were highest in the lightly grazed pasture.  The lightly grazed pasture, the deferred pasture and the livestock exclosure were all pretty high and significantly higher than the other two pastures, which showed little difference between the two of them.

The weeds and forbs varied very little among all five pastures.  However the weeds found on the heavily grazed section were the lowest number and also were very low quality weeds.  They were about 90% bitterweed (a poisonous plant).  The rotation pasture was found to have the highest quality weeds.  The conclusion was made that the reason for this is because there were no deer on the heavily grazed pasture and at least 10 AU/Section of deer on the rotation pasture.  This indicates the rotation pastures were actually grazed at a higher rate than the heavily grazed pasture while still producing higher yields of plants and of much higher quality which means a higher net profit per acre.

Finally, dry organic matter was highest on the rotation pastures.  The deer-livestock enclosure had only a little more litter than the heavy grazed pasture.  They noted this could be from a lack of stimulation in the land.  There was nearly twice as much litter in the rotation pasture compared to the total enclosure and the heavily grazed pasture; the other pastures did not show many differences.

Total organic matter—all four plant types combined were also shown here.  The rotation system had more than the others, and the heavily grazed system was the lowest.  Also noted is the heavy grazed pasture and the deer-livestock enclosure are nearly the same.

The authors draw two conclusions from this twenty year study.  First, is that the ungrazed area needs to be considered before using it to compare for research.  Vegetation may actually deteriorate and decrease after an extended period of deferment (i.e. total rest).  The second conclusion they draw is that the use of a grazing management system in this area, allows the development of a highly productive vegetation complex and also the maintenance and improvement of the livestock and wildlife habitat.

Interesting about this article is that it shows clear evidence that some sort of deferred grazing (rest-rotation) is much more effective than heavy grazing and more effective than light grazing also.  However the light grazing was done at 16 AU/Section and the deferred grazing at up to 43 AU/Section (excluding wildlife in both).  According to the data, more profit could be made and higher density of vegetation using a deferred grazing method.   Much of the information in this study corroborates lessons learned in Holistic Management over the past 25 years.

I included the table below which shows the results.  Numbers in a row followed by the same letter are not significantly different at the 5% level as determined by a Duncan’s multiple range test.

Dan Dagget: An Audio-Visual Presentation

Below is a series of videos featuring author, environmentalist, journalist, and ecosystem restorer Dan Dagget. In this series Dan shares with us a series of slides showing the on the ground techniques of active ecosystem restorers. Featured is a discussion of goals vs. issues, cattle as a tool to restore mine tailing sites, the damage to land caused by rest and preservation, strategies for conserving endangered species, and a critique of environmentalism as driven by politics instead of results on the ground.

A follow-up audio interview is available on in Episode #109 of the Agroinnovations Podcast.