Monday, December 14, 2015

The Kirtland’s Warbler: An Endangered Michigan Songbird

Maggie Dollar, Youth and Education Intern, Thumb Land Conservancy

Bill Collins, Executive Director

Back in the summer when biology professor Carrie Dollar helped the TLC get its first student interns from Saint Clair County Community College, she told us that her daughter, Maggie, was also interested in helping the TLC. She wanted to write some nature articles for the TLC, and we were happy to accept her offer. Maggie is an exceptional writer, especially considering that she’s only in the eighth grade at Parcell’s Middle School in Grosse Pointe where she is taking all honors courses and participates in a journal club. Maggie is not only a writer, but plays the cello and is on her school’s robotics team. She aspires to become a paleontologist or archaeologist because of her interest in history.

We hope we will see more of Maggie’s writing. Her first article is about the Kirtland’s Warbler, a migratory bird that breeds in northern Michigan, and seems to be recently expanding its territory. As do many warblers, likely a few Kirtland’s pass through the Thumb on their way to and from their winter range in the Bahamas, but sightings in our region have been extremely rare and it’s thought they largely make their migratory journeys as non-stop flights. Regardless, with so few Kirtland’s Warblers, every one counts and so if the Thumb provides habitat for the odd bird that occasionally stops in our area, all the better. Also, what we learn about a species that may not normally inhabit our region can provide insight into species that do. Instead of focusing on boundaries and limits, one thing nature teaches us is how connected everything is.

The Kirtland’s Warbler: An Endangered Michigan Songbird
By Maggie Dollar

The Kirtland's warbler, or Jack Pine warbler, is a songbird that only nests on the ground near young jack pine trees, mostly in the northern part of Michigan’s Lower Peninsula. In the fall, they migrate south to their wintering grounds in the Bahamas. The bird is about the size of a large robin, from five and a half to six inches (fourteen to fifteen centimeters). Its back is grey with black marks and its stomach is a bright yellow.

Female Kirtland's Warbler
"Kirtland's Warbler - female" by Dominic Sherony - Kirtland's Warbler female.
Licensed under CC BY-SA 2.0 via Commons -

Male Kirtland's Warbler
Photograph by Ron Austing.
Olson, J. A. 2002. Special animal abstract for Dendroica kirtlandii (Kirtland’s warbler).
Michigan Natural Features Inventory, Lansing, Michigan. 5 pages.

The Kirtland's warbler is one of the rarest members of the wood warbler bird family. The only places it currently nests are mainly in Michigan, and a few locations in Wisconsin and the province of Ontario. The first Kirtland’s warbler in North America was identified in 1851 from a specimen collected on Dr. Jared Kirtland’s farm near Cleveland, Ohio. Biologists did not learn where it nested until 1903 when they found a warbler nest in a jack pine forest in northern Michigan. Today, Kirtland’s warbler sightings are rare, mostly because they face two main threats: lack of crucial young jack pine forest habitat and the parasitic brown-headed cowbird.

Kirtland's Warbler county occurrences in Michigan
Michigan Natural Features Inventory. 2007. Rare Species Explorer (Web Application).
Available online at [Accessed Dec 14, 2015]

Many people do not realize that birds can also be parasites! The parasitic cowbird is a major threat to Kirtland’s warblers. A female cowbird will lay its own eggs in the nest of another bird, such as a Kirtland’s warbler. The cowbird egg hatches before the warbler eggs, getting a head start on growth. The young cowbird is bigger and able to claim more food than the warbler nestlings, and the cowbird may even push the baby warblers out of the nest!

Another factor that endangers the Kirtland’s warbler is its selective nature about where they nest and the fact that they do not like to share their nesting area with other warblers. The Kirtland’s warbler requires about thirty to forty acres for nesting and raising their young, which has become a problem, as there are not enough dense areas of young jack pine.

Kirtland's Warbler habitat - Young Jack Pine in northern Michigan
Olson, J. A. 2002. Special animal abstract for Dendroica kirtlandii (Kirtland’s warbler).
Michigan Natural Features Inventory, Lansing, Michigan. 5 pages.

Realizing the Kirtland's warbler was in danger of becoming extinct, forest managers set aside special areas for them. In these special Kirtland's warbler management areas, forest managers try to imitate what once happened naturally that allowed young jack pines to prosper. Oddly enough, forest fire prevention has led to the decline in young jack pine forest. Sometimes carefully managed fires are set purposefully in small areas of old jack pine in order to clear the way for young jack pine. In other areas, forest managers harvest some of the old jack pine trees, replanting the areas with jack pine seedlings. At least 1,200 seedlings are planted in each acre to create good nesting conditions. Essentially, good management of the bird is rooted in jack pine management.

The requirements for nesting and the cowbird parasite have caused a dramatic decline in Kirtland’s warbler population and has led to the listing the species as “endangered” since 1967.

Kirtland's Warbler occurrences in Michigan counties
Michigan Natural Features Inventory. 2007. Rare Species Explorer (Web Application).
Available online at [Accessed Dec 14, 2015]

If you are interested in seeing the Kirtland’s warbler, the Huron-Manistee National Forest hosts Kirtland’s warbler guided tours. The best time to visit is May. For more information on the tour visit the U.S. Fish and Wildlife website at:

Sunday, December 13, 2015

Claude Shannon and Norbert Wiener

Bill Collins, Executive Director, Thumb Land Conservancy

Once in a while, I decide to read about something I haven’t before. Could be just about anything. Yes, I am one of those people that will occasionally read through a dictionary. I’ve learned quite a bit by doing that. I realize there’s a lot of knowledge out there in books and other print that will probably never make it to the web, but I’m still amazed by the internet. I try not to take it for granted. There are some days that the choices feel too overwhelming, or I just don’t care for anything new, even the weather. But most of the time, I’m still fascinated by the opportunity to go almost anywhere, into almost any subject, with one search on a browser. Life is just too short though.

So, while writing the previous blog article about plant ecology and monitoring the Michigan Road Preserve, I decided to look up Shannon of the Shannon-Wiener Species Diversity Index. I really wasn’t expecting much, like maybe some abstract of a university ecology paper or mention of someone that worked for the US Fish and Wildlife Service, or something like that. Ha ha. Boy was I wrong.

Claude Shannon
The first thing I read was that Shannon was Claude Elwood Shannon, born in Petoskey, Michigan in 1916, the same year as my grandfather, and he grew up in Gaylord, Michigan of all places. That was completely unexpected. But the rest of his story is far more fascinating. Together with the story of Norbert Wiener, this little tangent led to some of that rare historical treasure that I sometimes dig up. But now, knowing about these two men, I feel a little stupid for not having known about them a long time ago.

Gaylord and Petoskey, Michigan, in the northern Lower Peninsula.
As a boy, Shannon was inspired by Thomas Edison, who grew up in Port Huron, Michigan as many of us Michiganders know, my home town. Shannon was a young tinkerer just like Edison, and later he even found out they were distantly related. Shannon studied electrical engineering at the University of Michigan. Then he went off to the Massachusetts Institute of Technology where he ended up working with an analog computer called the “Differential Analyzer”. Conceived in the 1920’s by MIT Dean of Engineering, Vannevar Bush, the Differential Analyzer was built and working by 1931. It was a mechanical computer, the only electrical parts being the motors that drove the gears. Preparing it to work with one equation and obtaining an answer could take almost a week. As a work-study student, Shannon helped visiting scientists set up the analyzer by adjusting mechanical linkages to correspond to their mathematical equations.

Claude Elwood Shannon. Wikipedia:

Shannon was intrigued by the operation of the many relay switches of the Differential Analyzer and enjoyed watching them work. Multiple relay switches were either on or off at a given time, and this reminded him of symbolic logic he studied back at the University of Michigan, a binary logic in which statements are either true or false, essentially on or off. Shannon made the connection between the relay switches and the potential to create mechanical and electronic logic. Apparently, this had not occurred to anyone before. Vannevar Bush suggested that Shannon study the operation of the Differential Analyzer relay circuits for his Master’s Thesis. In 1937, Shannon wrote what is described in many references as possibly the most important Master’s Thesis of the Twentieth Century, A Symbolic Analysis of Relay and Switching Circuits, describing how Boolean algebra and binary arithmetic could be used with electrical relays to solve mathematical problems. He demonstrated how such binary circuits could perform complex mathematical functions such as “if the number X equals the number Y, then do operation A.” As an illustration of this, he showed how relay switches could be arranged to create an electronic lock that opened only if a series of buttons was pressed in a certain order. Shannon’s conclusions in his 1937 thesis became the basis of modern computers and all digital technology since. The operation of a machine utilizing an internal program not only led to the development of the computer that you are most likely reading this article on right now, but also initiated the field of artificial intelligence. Shannon once said that he had more fun doing this work than anything else in his life.

Vannevar Bush with his differential analyzer. Bush’s Analog Solution. Computer History museum:

Claude Shannon. DaTuOpinion:
At a few points while reading about Shannon, I was wondering when he made a switch to ecology and what motivated him. Was it because he grew up in Gaylord, surrounded by forest, lakes and the northern Michigan wilderness? I was thinking back on my history. I had three years of electronics at Port Huron Northern High School taught by the great and ever-entertaining Paul Johnson. As I recall, it was a 2-hour class every day. My plan was, encouraged by Mr. Johnson, to study electrical engineering at Michigan Technological University up in Houghton, Michigan. Not only was MTU considered a leading university for electrical engineering, but I loved the Upper Peninsula. Eventually, my interest in nature and the environment led me to study natural resources and ecology at Michigan State University. Probably should have stuck with electronics. Anyway, turns out that development of the Shannon-Wiener Diversity Index had nothing to do with ecology.

In 1941, Shannon was hired by Bell Laboratories where he worked on automated anti-aircraft firing controls and cryptography, both of which became critical as the US entered World War II. In 1943, he had some association with the famous British cryptanologist and mathematician Alan Turning, who, a few years earlier, had broken the Naval Enigma machine used by the Nazi’s. From about this time, Shannon became more involved with cryptography and communication theory. His interest in transmitting and receiving information steadily grew as he realized that perfect, undistorted information transmission was theoretically possible using the digital technology that he developed a few years earlier. He wrote to his MIT graduate advisor, Vannevar Bush, “Off and on, I have been working on an analysis of some of the fundamental properties of general systems for the transmission of intelligence, including telephony, radio, television, telegraphy, etc.”. I think he actually meant that “Off and on” as a joke. In his spare time, while at Bell Laboratories, he continued to work on the mathematics of his digital information ideas, but according to several sources, he kept it mostly to himself and no one realized what he was doing. Shannon said he was motivated simply by curiosity and that publication was a “painful” process. I got that idea while at MSU, which is partly why I never went on to earn a graduate degree. I mean, back in the mid 1980’s they barely had reliable word processing programs. Publishing in the 1940’s had to be very difficult.

Claude Shannon with Theseus the intelligent electronic mouse.

But finally, in 1948, Shannon once again published a ground-breaking article, A Mathematical Theory of Communication in the July and October issues of the Bell System Technical Journal. Before this paper, there was apparently no concept of unifying all forms of communication into digital format, including radio, television, audio, visual, data, and so on. Equally as important, Shannon demonstrated that perfect transmission or communication was possible, within limits, regardless of the amount of background noise or distortion, or how faint the signal. Shannon’s “fundamental theorem” of information theory, as he called it, surprised even him. Before this, it seemed that signal noise would always be a problem. Again, this was a huge leap forward in thinking that enabled more technological advances than I care to list here, not the least of which is space exploration. Obviously, his work is a foundation of the internet as well, without which, again, you would likely not be reading this article.

Claude Shannon. Virtual Panorama. The Universe Of Information At Your Service:
What became the equation for the Shannon-Wiener Diversity Index was originally developed as a way to quantify the entropy or uncertainty of information in groups of text for the purpose of deciphering messages and codes, and to facilitate transmission and reception of data according to Shannon’s ideas of information theory. The more different letters or other data characters there are in a line of text or other group of characters, and the more equal their proportional abundance, the more difficult it is to correctly predict the next characters in a sequence. The Shannon entropy equation quantified the uncertainty of each new character.

The Shannon-Wiener Diversity Index, or entropy, equation.

Someone, I don’t know who yet, later got the idea this same equation could be a useful measure of species diversity in a given sampling area. The same concept applies to species or any other group of assorted things as lines of data characters. In a given group of species, the more different species there are, and the more even or proportional their abundance, the more diverse the group is and the harder it would be to predict which species you might encounter in the sampling area. For example, if there were only a few species and abundance was skewed toward one or two species, you could easily predict which species would be encountered most of the time. If there are many species with fairly equal abundance, it would be much more difficult to predict what species would be encountered and this would be described as a very diverse community. There have since been more refined equations developed, but the Shannon-Wiener Index essentially gets at what species diversity is.

Reading about Shannon was one surprise after another. Throughout his life, Shannon was drawn to physical activities that required dexterity and coordination. He was a gymnast in college, a juggler, and rode a unicycle. His wife, Betty, said he liked “circus things”. She bought him a unicycle one Christmas, which he mastered within a few days. He is famous for riding his unicycle down the hallways of Bell Laboratories while juggling, which I read they subsequently banned after Shannon was gone. He felt this kind of activity helped his intellectual work. In 1973, he even co-founded the Unicycling Society of America. Well, I used to ride a skateboard and I can juggle. As of a few years ago, I’m still (barely) able to juggle and pass 6 objects, such as plastic fruit, with one of my old roommates from MSU. But I've always had a hard time with mathematics, so maybe I need to try a unicycle.

Claude Shannon:

Shannon loved to build complex and odd machines. It might even be more correct to say that he worked professionally on the side. He was quoted in a 1987 OMNI magazine article, which I used to read, “I was always interested in building things with funny motions”. This goes back to his youth in Gaylord, Michigan, where most boys were probably more interested in hunting and fishing, but instead, he was busy building model planes, radios, a radio-controlled model boat, and a telegraph. So, at the University of Michigan in 1932, he said he had no hesitation about majoring in electrical engineering. The many unique things he built throughout his life included: rocket-powered flying discs; a motorized pogo stick; a flame-throwing trumpet; the “THROBAC” or “THrifty ROman-numerical BAckward-looking Computer” which calculated and displayed Roman numerals; the “Ultimate Machine”, a box with a switch on the side that when switched on would activate an arm to reach out from a lid on the box, switch itself off, and return inside the box; a mechanical version of W.C. Fields that could juggle; a machine that could solve the Rubik’s Cube; one of the first computer chess programs; and his famous mechanical mouse “Theseus” that learned how to navigate mazes with the help of telephone relay circuits. Shannon’s “ultimate machine” recreations have been popular in internet videos in recent years. He used to keep his, the original, on his desk at work. You can also watch video of his mouse “Theseus” in action with a detailed explanation provided by Shannon while he was working for Bell Laboratories. He also co-invented a wearable computer that he used while playing roulette in Las Vegas. By this point, he had gotten into game theory, which allowed him to do very well in the casinos and the stock market.

Shannon’s approach to his work was out of genuine curiosity and fascination with the complexities of the world, with a spirit of fun and playfulness. In later years, he witnessed what he felt was a lot of misinterpretation and hype regarding information theory, and he largely withdrew from public, wanting to avoid what he perceived as undue celebrity. He continued his pursuits for many years, but eventually was afflicted with Alzheimer’s disease and died in Medford, Massachusetts in 2001.

There are a few videos on YouTube with Claude Shannon and some of his creations.

Claude Shannon Demonstrates Machine Learning. In Their Own Words:

Claude Shannon Juggling:

Claude Shannon - Ultimate Machine - Leave Me Alone Box - um 1952:
A replication of Shannon's "ultimate machine".

Norbert Wiener
So who was Wiener? Norbert Wiener, the man credited with co-developing the Shannon-Wiener Diversity Index, was a boy genius from Columbia, Missouri of Polish, German, and Jewish ancestry. His father, a professor of Slavic languages at Harvard, was determined that his son should be a prominent scholar and home-schooled Norbert until he was 9. He graduated from high school at 11, earned a Bachelor’s degree in mathematics at 14, and a PhD in mathematics from Harvard at the age of 18. In 1914, he went off to Cambridge University in England and the University of Goettingen in Germany to study philosophy, logic, and mathematics. Wiener seemed to be interested in all kinds of things. He even studied zoology. At the outbreak of World War I, he returned to the US and taught philosophy at Harvard. He then worked as an engineer for General Electric, and wrote for the Encyclopedia Americana.

Young student Norbert Wiener. Polymath Matematica e ist:

Wiener had a strong sense of social justice and often acted on his convictions. He was briefly a journalist for the Boston Herald, where he wrote an article about the poor working conditions of mill workers in Lawrence, Massachusetts. He got fired from the paper because he refused to write favorable articles about a politician they wanted to promote. Although he was a pacifist, and perhaps driven by his experience of studying in England and Germany in 1914, he tried to enlist in the military a few times to help the US effort in World War I, but was rejected due to his poor eyesight. For a short time, in the summer of 1918, Wiener worked for the military privately with other mathematicians on ballistics at the Aberdeen Proving Ground in Maryland, but he still felt he should serve as a soldier, just as any other common man. He tried to enlist again and was finally admitted into the Army in 1918, but the war ended shortly after and he was discharged.

In 1919, Wiener started teaching mathematics at the Massachusetts Institute of Technology. While remaining with MIT, in 1926, he returned to Cambridge and the University of Goettingen as a Guggenheim Scholar where he had studied when he was 20. There, he worked on things like Brownian motion, the Fourier integral, Dirichlet's problem, harmonic analysis, and the Tauberian theorems. He became a professor at MIT in 1931, and worked there the remainder of his career. He said MIT gave him “… the encouragement to work and the freedom to think" in contrast to Harvard. Wiener became quite famous at MIT and enabled them to put together a research team that explored all kinds of things, including cybernetics, cognitive science, neuropsychology, and the mathematics and biophysics of the nervous system. Members of this MIT research group later made significant contributions to computer science and artificial intelligence. It seems there was just no limit to what some of these guys could do.

Young Norbert Wiener. Norbert Wiener Portraits:

It should be noted that Wiener was known for a diverse collection of mathematical notions that bear his name, including the Wiener process, the Wiener equation, the Wiener measure used to represent Brownian motion, the Wiener filter used to minimize noise in signals, and the abstract Wiener space, to name a few. Well, I’m not intimidated. I hypothesized and proved the existence of The Antelopean Surface as early as 1977. Wiener was attracted to quantum mechanics, collaborating with some of the leading researchers on relativistic quantum theory, the fifth dimension, unification of gravity and electromagnetism, and a theory of statistical hidden variables using differential space. Although I have a pretty good foundation in physics, I wish I could honestly say that I have a grasp on all that.

Professor Wiener in the MIT classroom with the tricycle cart.
Norbert Wiener, father of cybernetics and prophet forgotten:
Throughout his academic career, Wiener participated in many international gatherings and collaborated with academics across the world, especially several French mathematicians. Perhaps influenced by his father, Wiener was interested in foreign languages and preferred to exchange ideas with his collaborators in their native language. At least 16 of his articles are in French, five in German, and one in Spanish. He said, "One cannot understand a nation without knowing its language". He spent a year in China where he learned Mandarin. He spent a few years working in Mexico City, which had an important influence on his ideas about cybernetics. He continued to spend a lot of time in France, and in his later years lectured in the Netherlands, Italy, India, and Japan. He was a strong advocate for automation as a means of improving living conditions, and was very influential on the government of India in the 1950’s. All indications are that he truly had an international outlook on the world, and likely had a strong sense of being a citizen of the world, which unfortunately, sometimes brought him into conflict with the powers that be. Wiener was especially criticized for sharing ideas with researchers in the Soviet Union, which resulted in suspicions about him during the Cold War. After World War II, he became quite openly critical of political interference with research and the militarization of science, and especially of nuclear weapons. The January 1947 issue of The Atlantic Monthly featured his article, A Scientist Rebels, in which he urged scientists to consider the ethical implications of their work.

Norbert Wiener and Baidyanath swami at ISI, 1954 (Credits Indian Statistical Institute [ISI], Kolkata). Thinking Machines in the Physical World. IEEE 2016 Conference on Norbert Wiener in the 21st Century:

Norbert Wiener and Mrs Mahalanobis (2) at ISI, 954 (Credits Indian Statistical Institute [ISI], Kolkata). Thinking Machines in the Physical World. IEEE 2016 Conference on Norbert Wiener in the 21st Century:

Page of letter to his sister Bertha. Wiener Autograph Image:
Wiener seems to have always been a maverick in his own unimposing way, investigating and writing about the limitations of mathematical thinking early in his career, even as he was studying the depths of mathematics. Aspects of philosophy and a sense of social morality underlay much of his investigations, including cybernetics. In his last book, God & Golem, Inc., A Comment on Certain Points where Cybernetics Impinges on Religion, Wiener discusses the confrontation of technology and ethics, and the responsibilities of religion and politics.

As in his youth, Wiener’s interests remained broad throughout his life, including mathematics and the sciences of course, but also philosophy, literature, and fine arts. He wrote two short stories, a novel, and his autobiography in two parts, Ex-Prodigy: My Childhood and Youth in 1953, and I Am a Mathematician in 1956. He was described as being meditative, appreciating his personal solitude, which his wife helped protect from too many outside pressures. He enjoyed life in the country and spent his summers in “Tamarack Cottage” in South Tamworth, New Hampshire, often at a black board in the attic. Despite the many demands of his career, he was described as generous and once said, "I want to be the master of nobody". Wiener died in Stockholm, Sweden at the age of 69 in 1964.

Dr Norbert Wiener (credit Life Magazine) 
Enroque de ciencia. Norbert Wiener, un hombre despistado:

Unfortunately, I couldn't find any video featuring the actual Norbert Wiener, but there are a few videos about him that are interesting.

Norbert Wiener Today (1981):
This video is very well done. An actor portrayal of Wiener begins at 9:00. I was wondering why a guy from Missouri had a slightly British accent, but I supposed it could be a New England university thing.

Norbert Wiener:
This video is a little strange but has some good information.

Documental Norbert Wiener: 
This video is in Spanish, but you can set the subtitles to English and get a rough idea of what is said.

During his work with automation of anti-aircraft guns for the military in World War II, Norbert Wiener began developing what became cybernetics and information theory. Independently, Claude Shannon was also developing his ideas and is widely considered the father of information theory, the basis for all of our modern digital technology. As a student at MIT, Shannon met up with Wiener who was on the MIT faculty. This is apparently the basis of Shannon co-crediting Wiener with his development of his equation for entropy, which was eventually used for species diversity. Both Shannon and Wiener were known for being generous in crediting others for contributions to their ideas and work.

So, the short of it is, all of this was quite unexpected when I set out to read about the creators of an equation for species diversity. Some of the top minds in history are responsible for this little formula that I use. I can't help but project myself as I read about people, which maybe all of us do. Based on what little I know of each man on a personal level, I feel more of a kinship with Wiener, while I'd love to have the agile and upbeat mind of Shannon.

It appears Norbert Wiener was an ecologist after all.

As impressed as I am with Shannon and Wiener, after having read about them through several different sources, I have become a little more skeptical of solely crediting individual scientists with major accomplishments and labeling this man or that, “the father of” whatever. Sorry ladies, but it seems rarely in science have I read about “the mother of”. Clearly, certain people are responsible for major breakthroughs, but if you dig a little deeper you will often find how much they were influenced by someone else. There is the recurring phenomenon of two individuals, completely isolated from each other, hitting upon the same idea or discovery at about the same time, as though they are two particles in quantum entanglement. But, then there are those relationships that are obvious, where one person very clearly built upon the foundation created by someone else. So, not to take away from the impressive and fascinating achievements of Shannon and Wiener, but as I write, I constantly feel like maybe I should be reading more about the work of 10 or 15 other people who are mentioned in passing.

Saturday, December 12, 2015

Basic Plant Ecology and Monitoring the Michigan Road Preserve

Bill Collins, Executive Director, Thumb Land Conservancy 

For 5 years, the TLC has monitored and managed 51 acres of forest and shrub swamp on the Michigan Road Preserve in Port Huron Township for Saint Clair County and a private developer. The preserve is located along the east side of Michigan Road, north of Dove Road and south of the Canadian National Railway tracks. It is a small remnant of the northern forest and shrub swamp that once covered most of the Port Huron area. This northern forest complex is an expanse of forested lakeplain swamp, periodically interrupted by upland sand ridges deposited thousands of years ago by higher waters of the early Great Lakes. The Michigan Road Preserve was protected by two conservation easements as wetland mitigation for two projects permitted by the Michigan Department of Environmental Quality. The MDEQ requires long-term monitoring and management on all wetland mitigation sites, usually by a third-party steward such as a land conservancy. For more details, refer back to the 2015 March 17 blog article, Michigan Road Preserve Stewardship:

Vegetation Monitoring
A routine part of monitoring natural areas is collecting vegetation data to record the existing or baseline conditions. All plant species are identified and inventoried to determine the type and quality of natural community present, and to detect changes in the vegetation over time due to natural and human impacts. In Michigan, the usual impacts include the spread of invasive plant species, plant diseases and pests, over-grazing by deer, forest clearing and fragmentation, surface and ground water drainage, off-road vehicle incursions, and refuse dumping, among other things. The vegetation may also change in response to deliberate management actions by the preserve steward intended to improve the natural area, such as weeding, mowing, controlled burning, and herbicide application for invasive weed control and habitat improvement. A preserve may be seeded and planted with certain native species to improve or enhance the plant community or forest stand. Having baseline data allows the land steward to evaluate the effectiveness of their management activities.

2014 Spring burn in the northwest of the Michigan Road Preserve.
Vegetation can also change naturally through plant succession and shifts in species dominance. The classic example of plant succession in Michigan is forest progression from old-field, to wooded shrub thicket, to “pioneer” woodland, to young “second-growth” forest, to mature and old-growth forest. Unfortunately, we are not seeing much succession in this direction these days. It’s the opposite, as woodlands are cleared for farming and development. Natural succession can also be cyclical in some plant communities, for example, progressing from open wetland, to conifer swamp, to dense tree cover which favors mosses, to increasing moss-induced soil acidity which causes tree mortality, back to open wetland again, and so on. A land manager may want to document these natural changes in vegetation to better understand the plant community and to manage for particular species, among other reasons. All of the potential impacts, management actions, and natural changes that occur in preserves make the collection of baseline data a good idea for many stewardship purposes.

Diagram of general forest succession in North America.
Vegetation can be described simply by general observation, more thoroughly with searches for particular species, or in great detail utilizing sampling plots positioned on transects or located randomly. It all depends on the purpose of the observation. For a basic description of the plant community, general observation of dominant species may be sufficient. For plant inventories to determine the general quality of the natural community or to find rare species, meander searching is usually sufficient. For meaningful analysis of disturbance impacts or effectiveness of management actions, sampling plots are usually necessary. There are other methods that don’t require plots, such as linear transects where vegetation intersecting the line is measured, but plots are probably most often used.

Sampling Plots
Sampling plots, or quadrats, are usually small square or round frames of wood, plastic, or other material laid on the ground to define a sampling area. Larger plots are simply marked by stakes, flags, or ribbons. Plots vary in size from a few square feet for small plants to several hundred for shrubs and a few thousand for trees. For the sake of mobility, often having to trudge and carry equipment through thick growth, instead of a frame plot, I just use a piece of string marked at 1-meter intervals to 3 meters. With one end looped around a small stake, I walk the string around in a circle while observing the vegetation within the 1, 2, and 3-meter radii. This effectively provides me with 3, 12, and 27-square meter round sampling plots by carrying just a string and a stake or small pole. For larger sampling areas, I carry a measuring tape or a longer pre-marked string, and ribbon.

A typical square sampling plot or quadrat.
Species-Area Curve
A basic concern in measuring vegetation is whether the sampling areas are large enough to obtain representative samples. Too small, and the sampling area may exclude species that are important and the results will be skewed. A larger sampling area is better, but too large and it wastes time and effort without added benefits to the study. Usually, the idea is not to include every plant species in the sampling area, but enough to show basic trends. Knowing if sampling sizes are adequate is accomplished by producing a species-area curve, a graph of the number of species per sampling size. As the sampling size is increased from zero, the number of new species within the sampling area initially increases. This makes sense. The bigger the sampling area, the more species. The graph is an upward curve as new species are encountered. But this holds true only to a point. Keep increasing the sample size and normally, the number of new species starts to taper off, and likewise, the slope of the graph curve starts to flatten out. No matter how much the sampling area is enlarged, there are only so many new species that can be added. This is assuming that the sampling area does not cross over into a different type of plant community where completely different species occur. An example of this might be a sampling area within a swamp forest where the species are mostly wetland forest species. If the sampling crosses over onto an adjacent upland ridge, there would be several upland species added and the species-area curve would begin to slope up again.

A species-area curve for a 1-meter radius circular plot of 3 square meters. To ensure the 1-meter radius was large enough to obtain a representative sample, species numbers were counted out to a 2-meter radius and a 3-meter radius. The curve clearly shows a decrease in the slope, or the rate of addition of new species after the 1-meter radius, or sampling area of 3 square meters, where 7 species were found. Only 3 more species were added to the 2-meter radius, and only 2 more in to 3-meter radius.
There are two ways to vary sampling size in order to obtain representative samples of the vegetation, although they are essentially the same because they both simply increase or decrease the total sampling area. One way is to increase the size of each sampling plot until the species-area curve flattens out for each plot. For my work in Michigan, I have found that a sampling plot of 3 square meters, or a 1-meter radius circle, has almost always been sufficient to sample herbaceous plants, the mostly non-woody ground layer of vegetation. I use this 1-meter radius plot most often because I am usually sampling in open, non-forested and non-shrubby wetlands constructed as wetland mitigation. These wetlands have been developing from bare ground for only a few years, so trees and shrubs have not established to any great extent yet. Besides individual plot size, the other way to vary the sampling size is to add or subtract the total number of plots. In this case, obtaining a representative sample at each individual plot may not be so much a concern as getting a representative sample of the whole landscape or natural community. If you were to graph the number of species per number of sampling plots, you would find the same species-area relationship described earlier. The slope of the curve rises initially, and then begins to flatten out at the point where fewer species are added with each new sampling plot. I think it could be argued that it’s important to use both a large enough sampling plot to obtain representative samples at each location, and also use enough plots to obtain a representative sample of the whole natural area, but I can imagine some applications where this might not be necessary.

The graph above shows species-area curves for 9 sampling plots on a mitigation site in Macomb County over the course of 4 years. This is not the best of curves, but it generally shows the sweet spot is somewhere around 4 or 5 plots to obtain representative sampling of the community. That’s the point at which the curve slopes mostly decrease and flatten out, remaining fairly constant after the 6th plot. To be safe, I’d want to have more than 5 plots, and that’s partly why I stuck with 9 for this site
Island Biogeography
You might be getting the idea by now that basic ecology is mathematics, and you would be correct. This was a little surprising to me in college, but like many things, measurement and data analysis are required to draw certain conclusions. I first got a taste of this mathematical approach to ecology when studying the theory of island, or insular, biogeography in a graduate world biogeography course taught by Dr. Peter Murphy at Michigan State University. I sometimes wondered if Dr. Murphy led the life of a gothic musician at night. But anyway, island biogeography was developed in the 1960’s by ecologists Robert H. MacArthur and Edward O. Wilson to understand and explain species richness on islands and other isolated ecosystems. E. O. Wilson went on to become quite a well-known ecologist and author in later years, specializing in the study of ants. In reading a little about his life, I see that we share the experience of having taught nature at Boy Scout summer camp in our youth. The basis of island biogeography theory is species richness, or total number of species on an island, resulting from species immigration and extinction, which are functions of island size and degree of isolation, among other factors. As you might guess, smaller and more isolated islands, those more distant from other islands and mainland which serve as species sources, have less species. Landscape, habitat diversity, geographic history, length of isolation, ocean currents, chance, and other factors are all influences, but in the purest sense, island size and degree of isolation are primary determinants. So basically, island biogeography is founded on measuring land size and counting species, and then graphing the results. As simple as it is, this theory eventually led to a kind of revolution in conservation. The same ideas of size and isolation can be applied to other situations, such as isolated nature reserves, fragmented forest patches, mountains, isolated bodies of water, and so on. Concern for maintaining species richness in smaller, fragmented natural areas, eventually led to the recognition of the significance of natural corridors to allow species migration between natural areas.

A diagram showing the theoretical migration of species from a mainland (bottom) to islands of varying size and distance from the mainland. Assuming an even movement of species away from the mainland, it’s fairly easy to see how larger and closer islands would receive a larger proportional input of species to replenish those going extinct.
A graphic representation of island biogeography. The bottom axis of the graph shows the total number of species, increasing from left to right, on islands of varying distances from a mainland and of varying sizes. The blue curves beginning on the left represent the rate of immigration to islands close to the mainland (top curve) and far from the mainland (bottom curve). The overall rate of immigration is higher for close islands than far ones, and for both, the rate is initially higher toward the left as species move onto an island with few species present, but declines toward the right as more and more species occupy the island which becomes more crowded and harder to colonize. The red curves beginning on the right represent the rate of species extinction on small islands (top curve) and large islands (bottom curve). The overall rate of extinction is higher for small islands than large islands, and for both, the rate is initially higher toward the right with more species on an island competing with each other and more to lose, but declines toward the left as there are less species in competition with each other and less to lose. Projecting down from the intersection of these four curves gives the expected theoretical number of species on islands, of varying distance and size, that are stabilized, or where the rates of immigration and extinction are in equilibrium. A small island far from the mainland is expected to have the least species (A). A large island close to the mainland is expected to have the most species (D). A close small island (B) and a far large island (C) are expected to have species totals somewhere between the extremes.
Another early recollection I have of mathematical application in ecology is ordination, which was introduced to me by my botany teacher and friend at Michigan State University, Dr. Brian Palik. As I got to know Brian, he shared his research work with me in forest ecology. In particular, Brian was investigating the response of forest to different levels and regimes of disturbance. He has since worked for the US Forest Service for many years, studying and designing alternative tree harvest methods, among other things, for the sake of maintaining more natural forest communities. Although Brian was first studying with Dr. Peter Murphy, he didn’t seem to have Goth tendencies. But I must say, having access to his raw data, seeing the basic framework of his research, while at the same time, understanding the larger construct of his conclusions, was somewhat Bauhausian for me. Ordination, also known as gradient analysis, is a mathematical way of representing data clusters, where objects of similar value are located nearer each other numerically and graphically than objects of less similar value. It is a way of looking at objects characterized by multiple variables, particularly useful in ecology and other natural sciences, to investigate relationships that are not otherwise clearly evident. As my friend Brian said, “Ordination is cool” and I’m sure he’d still say that. An example of the application of ordination is the investigation of plant species distribution across a natural area in relation to multiple factors documented at each sampling point such as soil density, wetness, slope, elevation, soil pH, particular soil nutrients, and so on. Ordination sorts through all of those parameters, showing species distribution in relation to all of these factors in one graphic, making it easier for researchers to see relationships they might not otherwise. I have not made use of ordination in my work simply because it hasn’t been necessary, but I understand it and appreciate its power. I would like to use it someday in certain natural areas I have studied just to see if it reveals any new insights.

Dr. Brian Palik explains his research activities for the US Forest Service in Minnesota, where they are trying to prepare for the expected invasion of the Emerald Ash Borer as the climate warms. Right now, the pest is largely excluded from northern Minnesota due to extremely cold winters, but the winters are expected to become warmer. They are looking at what happens to the forest community and what tree species will dominate in the absence of Black Ash, and how they might replace Black Ash with some other tree species currently of a more southerly range. West Central Tribune, Willmar, Minnesota, 2015 March 08, Dan Kraker:
Ordination graph showing the relationship of various forest communities to several different parameters, including slope, elevation, density, topographical situation, pH, drainage, calcium, magnesium, nitrogen, basal area, organic matter, cation exchange capacity, carbon : nitrogen ratio, stand age, and solid rock.
Density, Cover, and Frequency
The most basic measurements in plant ecology are density, cover, and frequency. These are simple tools of the plant ecologist, just like a hammer and saw to a carpenter, used to construct much more complex views of a plant community. Density is the total number of individuals of a particular species in a given area. Counting plants is usually easy, but sometimes deciding what constitutes a single plant is another story. In the many cases where individual plants are not so obvious as a single tree, such as clusters of shrubs or clumps of grasses or mosses, it is often necessary to count stems or devise some alternate measure of density. Being consistent is more important than being technically precise about the absolute exact number of individuals. Cover is the area of land or water occupied by a particular plant species. There are many variations of this measurement, which is most often visually estimated, and volume can even be used. While determining the cover of a single tree might seem like a simple notion, unless basal trunk area is used, it may be necessary to decide if the crown will be considered a single two-dimensional area, or a multi-layered three-dimensional mass. In the first case, percent cover will be a maximum of 100%, and in the second case, percent cover can be well over 100%. Frequency is the number of occurrences of a particular species across multiple sampling areas. In other words, it is just a measure of how repetitive the species is across the sampled landscape. While a certain plant species may be quite dense and cover a large portion of one sampling area, it may be in low numbers or absent from the rest of the sampling area, and this is important to know for the purpose of characterizing the plant community as a whole. So, the spatial quantities that are the basis of plant ecology are how many, how large, and how consistent. These quantities can then be used in many different ways to further evaluate vegetative communities.

An example of Density (D), Cover (C), and Frequency (F) measurements of a single species across 5 sampling plots or quadrats.
One of the most useful measurements I use as a professional wetland ecologist is Importance value. As the name implies, Importance is a measure of which species are most important spatially in the plant community. Generally, those species of most spatial importance make the community what it is. Importance combines density, cover, and frequency to produce a number that more precisely depicts the spatial significance of a species than density, cover, or frequency alone. By themselves, these singular measurements leave one with the question, “Which species are spatially more important in the landscape; the few big ones that cover a large area, or the smaller but more numerous ones?” Importance values combine density and cover to provide an answer better than one parameter alone. Further, Importance answers the question, “Is a species that dominates only one part of the landscape as significant as a species that doesn’t dominate any area but is distributed across the entire landscape?” Frequency of distribution is combined with density and cover to produce a number in Importance that quite roundly represents the spatial significance of species. In actuality, it may turn out that some unseen fungus is the most important species in the landscape from an allelopathic perspective, but from a macro-spatial perspective, Importance provides a comprehensive measure.

Which plant species are more important in the community; the few large or the many small?
I use Importance most in evaluating the development of mitigation wetland. In this work, we want to know whether wetland plant species are establishing, and to what extent. We also want to know if invasive weeds are present and how extensive they are. Just listing the plant species present doesn’t give a complete picture because it provides no quantities. Percent cover would be closest to indicating how extensive species are in most cases, but for larger plants, especially shrubs and trees, the number or density is also important. Plant species are inventoried in sampling plots located at regular intervals along transects across the mitigation wetland. Species-area curves are produced to ensure that the plots are large enough. Importance values are calculated for all plant species found in the plots. These values are then multiplied by the wetland indicator value or wetland coefficient of each species. Regional Wetland Indicators and Coefficients have been published for most plants in North America by the United States Fish and Wildlife Service in the National List of Plant Species That Occur in Wetlands, and for Michigan in the Michigan Plants Database. Every plant species in North America is assigned a wetland coefficient, ranging from -5 for obligate wetland species, to +5 for upland species. These indicators or coefficients are estimates of the probability of occurrence in wetland for each species, ranging from 0 to 100%. The products of Importance for each species and the corresponding wetland coefficient are added up and divided by the number of species to produce an average wetland coefficient value or Prevailing Wetland Coefficient for each plot. If there are enough plots and they are distributed across the mitigation area so that results aren’t skewed, this provides a very clear picture of the wetland status of the site. And one of the best things about it is that it doesn’t rely on my opinion. It’s purely numbers and closer to the truth than just visual estimation alone. Importance does rely on visual estimation of plant cover in each plot. It could be measured in various ways, but it would be unnecessarily time consuming. Fortunately, in my first full-time job after college, I was employed as an asbestos technician by Testing Engineers and Consultants in Lansing. There, I spent most of my time looking through a polarized light microscope at building material samples trying to detect whether asbestos was present, and if so how much. After looking at hundreds and then thousands of samples, we got very good at visually estimating percentages of various materials within that small round spot in the microscope, not unlike a sampling plot.

First page of the Michigan Plants Database.
In each sampling plot, Cover (C%) is visually estimated as a percentage of the total plot area covered by each plant species, whether herb, shrub, sapling, or tree. Relative Cover (RC%) is the cover of a particular species as a percentage of total plant cover in a plot. Density (D) is determined by counting the total number of individual plants of each species in a plot, normally determined by the total number of plant stems. For those plant species with a very high density or complex morphology, the number of individuals is often estimated based on cover. Relative Density (RD%) is the density of a particular species as a percent of total plant density in a plot. Frequency (F%) is the percentage of total plots that contain at least one individual of a particular species. Relative Frequency (RF%) is the frequency of one species as a percentage of total plant frequency in a plot. Importance (I) is a measure of spatial dominance of a particular species and is calculated for each species as the sum of Relative Cover, Relative Density, and Relative Frequency (I = RC% + RD% + RF%). The Importance value for any species ranges between 0 and 300 as it is the sum of three numbers, each being a maximum of 100.

Corresponding Wetland Coefficients, Regional Wetland Indicators, and probability of species occurrence in wetland. These coefficients or indicators are assigned to almost every plant species in North America. They can vary according to different regions where the same species may thrive within slightly different conditions.  
Table showing Importance value and Prevailing Wetland Coefficient data for species in a 1-meter sampling radius. The first column (left) after the species name is Percent Cover (C%), followed by Relative Cover (RC%), Density (D), Relative Density (RD%), Frequency (F), Relative Frequency (RF%), Importance (I), Wetland Indicator Coefficient (WI), and the product of Importance multiplied by the Wetland Indicator Coefficient (IWI). These IWI values are then summed up and divided by the number of species in the sampling plot to give the average or Prevailing Wetland Coefficient of the area. The last column at the far right is data used to calculate Diversity.  
Species diversity is a quality that provides some insight into the condition of a natural area. High native plant diversity is mostly good and usually indicates a relative lack of human impact and health of the ecosystem. High native diversity can mean that species recruitment and retention has been relatively unhindered by human disturbance. It can also mean that natural processes, such as low-intensity fire, have continued as in the prehistoric landscape. However, it is important to note that not all native plant communities are naturally diverse. Bogs for example, are usually not highly diverse plant communities. The highly acidic, low-nutrient, and saturated peat soils exclude many species, except those that are specially adapted to grow in such conditions. Bogs certainly are unique and worthy of protection for many reasons, but plant diversity is typically not high on the list. Other communities that are usually not highly diverse include muskeg, boreal forest, and dry northern forest. Generally, vegetation of northern latitudes is less diverse than that of southern latitudes, with the tropics of equatorial latitudes generally being the most diverse areas of the world. Every plant community and region is ecologically important for many reasons, including the unique array of native species that are supported. A plowed farm field left fallow for a few years may actually have higher diversity than some native woodland. But the average fallow field is full of very common species, many of which are alien weeds or even invasive species. Old-field habitat can have good natural value, perhaps for uncommon insects or grassland birds, but the southern Michigan landscape was once about 95% forested, and is now only about 10 to 15% forested. A forest has so much more natural value than old-field in the context of today’s highly impacted world that it doesn’t even make sense to begin comparing the two based on diversity. As with many things, one aspect alone, like diversity, doesn’t account for all of the values associated with a natural area. The world is much more complex. So, you need to be careful how you use some measurements. Knowledge of native plant communities and ecosystem context is always required to qualify your conclusions.

There are many ways to calculate diversity. The method I have used for years is the Shannon-Wiener Diversity Index. Species are inventoried in each sampling plot and the following equation is applied:
In the equation above, H’ = the Shannon-Weiner Diversity Index, i = 1 individual species, s = the total number of species in the sample, pi = the proportion of all individual plants in the quadrat which are of a particular species, and ln pi = the natural logarithm of the proportion of all individual plants in the quadrat which are of a particular species.
While the equation may look a little complicated, it accounts for two primary aspects of species diversity. First, it uses species richness, or the total number of species in the sample. Second, it calculates how evenly distributed the species are in terms of total number of each. For example, there may be 3 species in the sampling area, and all 3 species are equal in total number or density, say 100 each, for 300 individuals total. But in another example, there may be 3 species of which 298 are all one species, and each of the other two species only has one individual in the sampling area. In this latter case, the sample is really not as diverse as the first example. Both are equally species rich, with 3 species in each sample, but the distribution is far more even in the first sample. In the second sample, the ecologist making the measurements could step on two plants and wipe out two-thirds of the species.

Floristic Quality Index
A relatively new calculation on the plant ecology scene that I use frequently is the Floristic Quality Index, which basically provides a comparison of the present vegetation to what would be expected a few centuries ago, before it was drastically altered by European settlers. While all natural areas were not pristine, before European settlement, there was a much higher prevalence of native species associated with prehistoric plant communities. I like using the Floristic Quality Index calculation, and it’s always interesting to see how sites rate. I suppose the equation has been around a long time, but it wasn’t until someone assigned what are called “coefficients of conservatism” for each species that it became useful to plant ecology. As far as I know, that happened only about 15 years ago for Michigan flora. I saw it years earlier for Illinois flora, and finally, Floristic Quality Assessment for Michigan was developed in partnership with those that created it for Illinois.

A Floristic Quality Index (FQI) is calculated for a particular plant community based on the assignment of a coefficient of conservatism (C) to each plant species occurring within the community. C values range from 0 to 10 and represent an estimated probability that a species would occur in a plant community relatively unaltered from what is thought to have existed prior to major human disruption; in the prehistoric landscape of pre-European settlement Michigan. The lower the C value, the less a plant species is considered associated with remnant presettlement communities, and the higher the C value, the more a plant is restricted to presettlement remnants. A mean coefficient of conservatism (č) is derived from a comprehensive list of plant species on a particular site. This is done by summing all of the coefficients of conservatism (C values) of an inventory of plants and dividing by the total number of plant species (n), yielding an average or the mean coefficient of conservatism (č = SC/n). The č is then multiplied by the square root of the total number of plant species (√n) to yield the FQI:

FQI = č√n = (SC/n)√n

For Michigan, FQI values greater than 35 are considered to indicate that a specified natural area is floristically important from a statewide perspective. An area with an FQI value less than 20 is generally considered to have minimal significance from a plant quality perspective. Values near 50 indicate natural areas that are near pristine. The FQI procedure is not limited to sampling plots, but relies on a complete plant species inventory across an entire plant community. It can be used on a plot basis to compare the relative FQI of each sampling area, but with the understanding that the true FQI value of the community is not represented in each plot.

The FQI or Floristic Quality Assessment (FQA) procedure for Michigan was co-developed by a few people I’ve had association with. Back in 1987 and 88, just finished with Michigan State University, I did some contract work with the Michigan Department of Natural Resources, Wildlife Division which was actually used by the Michigan Natural Features Inventory. I was hired by Sue Crispin to write species abstracts, or summaries, for a few rare Great Lakes shoreline plants, including Pitcher’s Thistle and Houghton’s Goldenrod. Through this work I became acquainted with Mike Penskar, the lead botanist for the MNFI. In the years since, we have had some communication regarding plant species like Michigan Endangered Painted Trillium and most recently, Michigan Special Concern Broad-leaved Puccoon that I found near the new Lake Huron water intake facility for the Genesee County waterline.

Anton "Tony" Reznicek, the Carex man, has been a Curator, now Assistant Director, of the University of Michigan Herbarium for years, and one of the nicest persons you can hope to encounter in academia. Another botanist that I communicate with once in a while and have run into at a few meetings. I guess I first heard of Tony in the late 1980’s when I read some material from the Michigan Nature Association. The MNA was often criticized for protecting very small preserves which were not likely to be sustainable in the long-term. Tony made the statement that actually, many plant colonies can survive in small natural areas for a very long time, and so for the sake of certain rare plants, a small preserve can be justified, at least temporarily. I think this is why MNA had what they called “sanctuaries”, their normal larger preserves, and also smaller areas they called “plant preserves”. My opinion is that any natural area is worth protecting. Sure, there are priorities based on significance and money and availability of the land, but apart from that, I don’t write-off any part of nature. It was in discussions with Tony that I first realized the interesting patterns and significance of post-glacial migrations of plant species in North America. This has since led to my concern about obscuring these ancient traces of plant migration by modern human movement of non-endemic genotypes all over the place for landscaping, wetland mitigation, forest restoration and other uses. For example, a plant species from Illinois will not necessarily be genetically identical to the same species in Michigan. My opinion is that there are differences even over a much shorter distance, and that aesthetically, we should try to maintain local populations as much as possible. At the very least, discussions of species variations, or varieties, included in many plant guides, are gradually becoming obsolete as we will no longer be able to determine whether a certain variation occurred naturally, or was introduced through nursery stock from who knows where. Another thing about Tony, he worked with the late Dr. Ed Voss for years to produce the internet version of Michigan Flora which is very useful and available on-line at:

Tony Reznicek. University of Michigan Herbarium:
There is another co-developer of the FQI I am acquainted with. I have run into his botanical consulting work several times when a significant natural area is being carved up and destroyed for development. I’ll just say that I find it ironic that some botanists can discover so many rare species, but when they’re a hired gun, they seem to lose that skill. But this is a topic for another article, or book as I’ve had in mind.

Michigan Road Preserve In 2015
So finally I get to the end of my article about vegetation monitoring, with all of my tangents from the subject matter. If you’ve read this far, you may have forgotten that I started by discussing the TLC stewardship of the Michigan Road Preserve in Saint Clair County. And so you may be wondering how the preserve is doing, as measured by all of this highly advanced mathematics. Oh, fair to midland.

OK. The preserve hasn’t changed significantly since the TLC started monitoring in 2011. It is still an important part of one of the largest remaining fragments of northern forest complex in Saint Clair County. Characteristic of the Port Huron area, southern swamp forest and northern shrub swamp cover low and wet Wainola-Deford fine sands, and northern forest covers upland ridges of Rousseau fine sands. The vegetation is typical of that occurring on relatively undisturbed land in the Port Huron area, largely a second-growth forest community reestablished in the past century after much of the forest was cleared for timber. Despite extensive clearing, the forest has retained many species from before European settlement. The vegetation is composed of a blend of northern and southern species that meet here in a mixing zone of northern and southern flora, being located at a southern extension of Michigan’s Transition or Tension Zone along the Lake Huron coast.

Wetland in the northwest of the preserve showing extensive tip-up mounds and potential habitat for Michigan Endangered Painted Trillium.

Paper Birch on upland sand ridge on the east of the preserve. 

Eastern White Pine and Paper Birch in the east-central part of the preserve.
There are few recent human impacts on the preserve. It appears that only a few deer hunters use the preserve, and are actually doing the native vegetation a service by reducing the grazing of these destructive herbivores. There are no trails, due in part to the isolation of the preserve between Michigan Road, the North Branch of the Bunce Creek, the Canadian National Railway, and extensive forest to the east and south. Because wetland is so extensive in this area, there are few nearby residences, which is another factor in the lack of disturbance.

Invasive plant species are the biggest problem for the preserve, as with many natural areas in southern Michigan. Glossy Buckthorn – Frangula alnus is widespread across the preserve, throughout the swamp forest and shrub swamp. It is dominant in the understory of about half of the preserve and is, by far, the greatest management concern at this point. But the Glossy Buckthorn invasion in this area, southwest of Port Huron, has been happening for a long time. For some reason, Glossy Buckthorn became widespread in the Dove Road area many years ago. Eliminating Glossy Buckthorn from these areas will also be a long-term effort. Reed - Phragmites australis and Narrow-leaved Cat-tail - Typha angustifolia are widespread in the open shrub swamp of the preserve. They are detrimental to the native vegetation in that they exclude native species that would otherwise occupy the shrub swamp. However, aggressive attempts to eliminate these invasive weeds could make the situation worse. It appears that Speckled Alder is gradually out-competing Reed and Narrow-leaved Cat-tail in these areas. Burning or herbicide applications might serve to suppress the Speckled Alder growth more than the invasive weeds. So, the TLC has taken a cautious approach to this area. For one thing, these weeds aren’t spreading because they require open areas with near full sunlight. The Speckled Alder is slowly filling-in and shading it out and the shrub swamp is surrounded by forest. Another problem is that Reed is thick along the north preserve boundary, on the CN Railway property. So we would need to also control Reed on the CN property to keep it from moving back into the preserve.

A tangle of Speckled Alder, Chokeberry, and Glossy Buckthorn in the shrub swamp portion of the preserve. 
The most severe impact to the Michigan Road Preserve, just shortly after the TLC began monitoring the site in 2011, was the clearing of land along the west side for improvements to Michigan Road and construction of the new bridge over the CN Railway. But, it was partly because of this impact to regulated wetland that the MDEQ required preservation of the adjacent land as mitigation. This demonstrates the double-edged sword of mitigation. Preserving these large natural areas is great, but it requires destruction. While the clearing was not on the preserve, the boundaries of the “preserve” are arbitrary, and no natural area exists in a vacuum. Forest clearing on the adjacent land west, amounting to roughly a 100-foot wide swath of forest being eliminated, has already adversely affected the preserve by extending edge impacts roughly an additional 100 feet into the west side. Negative impacts include increased growth of invasive Glossy Buckthorn, extension eastward of edge-forest species leading to the displacement of higher quality interior forest species, slightly increased wind-throw of mature trees, and degradation of the forest habitat for woodland birds by decreasing the size. Most remaining forest tracts in the region are already very small and highly fragmented. Forest quality is very dependent on maintaining relatively large, non-fragmented tracts that are less susceptible to invasion of edge and weed species. Large non-fragmented forests are better able to maintain interior forest species, remnants of prehistoric populations that thrived prior to European settlement 150 to 200 years ago. The loss of forest on along the west side of the preserve makes it that much less sustainable in the long term. With less forest, full sunlight extends further into the remaining forest, favoring weedy edge species over the remnant native flora. It appears that Glossy Buckthorn has especially responded to the increased light, having the greatest density and new growth along the west boundary of the preserve. Wind-throw of mature trees from prevailing west winds will extend slightly further into the preserve. Interior forest birds such as Wood Thrush are particularly vulnerable to nest invasion and territorial displacement by non-forest birds such as Cowbirds and other common birds that thrive in highly fragmented woodlands.

View north along the west side of the preserve of cleared land along Michigan Road that was forested before 2011. The Michigan Road bridge crossing of the CN Railway in the left background.
Increased Glossy Buckthorn growth along the west side of the preserve. Michigan Road in the background.

TLC Interns
2015 was the first year that the TLC had the help of student interns in monitoring the Michigan Road Preserve. Read more about our interns at:

TLC Intern Jeff Hansen recording vegetation data on the Michigan Road Preserve in Port Huron Township, Saint Clair County.
TLC Interns Nicole Barth and Jeff Hansen observing vegetation within sampling plot on the Michigan Road Preserve in Port Huron Township, Saint Clair County.
MDEQ Monitoring Requirements
In case you are wondering exactly what are the monitoring requirements of the MDEQ for a wetland mitigation preserve, here they are, listed below as they appear in the wetland permits:

The permittee shall monitor the mitigation area approved for preservation credit for a minimum of five (5) years. The following information should be collected and provided in the monitoring reports:

  • Provide a written evaluation on the success of the long term management plan goals and recommendations.
  • Sample vegetation in plots located along transects shown in the plan once between July 15 and August 31 with an approach approved by the MDEQ. Transects should occur along areas targeted in the long-term management plan for enhancement or corrective actions.
  • Provide annual photographic documentation of the mitigation area approved for preservation credit from permanent photo stations located within the mitigation wetland. At a minimum photo stations shall be located at both ends of each transect. Photos must be labeled with the location, date photographed, and direction.
  • Provide a written summary of data from previous monitoring periods and a discussion of changes or trends based on all monitoring results.
  • The mean percent cover of invasive species including, but not limited to, Phragmites australis (Common Reed), Lythrum salicaria (Purple Loosestrife), and Phalaris arundinacea (Reed Canary Grass) shall in combination be limited to no more than ten (10) percent within each wetland type. Invasive species shall not dominate the vegetation in any extensive area of the mitigation wetland.
  • If the mean percent cover of invasive species is more than ten (10) percent within any wetland type or if there are extensive areas of the mitigation wetland in which an invasive species is one of the dominant plant species, the permittee shall submit an evaluation of the problem to the MDEQ. If the permittee determines that it is infeasible to reduce the cover of invasive species to meet the above performance standard, the permittee must submit an assessment of the problem, a control plan, and the projected percent cover that can be achieved for review by the MDEQ. Based on this information, the MDEQ may approve an alternative invasive species standard. Any alternative invasive species standard must be approved in writing by the MDEQ.
  • Provide a written summary of all problem areas that have been identified in meeting goals and objectives of the management plan and potential corrective measures to address them.
  • A monitoring report, which compiles and summarizes all data collected during the monitoring period, shall be submitted annually by the permittee. Monitoring reports shall cover the period of January 1 through December 31 and be submitted to the MDEQ prior to January 31 of the following year. A qualified individual able to identify vegetation to genus and species must conduct the wetland monitoring. The MDEQ reserves the right to reject reports with substandard monitoring data. If the MDEQ determines that the restoration and management goals have not been met, the MDEQ may require subsequent annual monitoring until final approval from the MDEQ can be granted.

Sampling Plots
A total of nine sampling quadrats, or plots, Q-1 through Q-9, were established along an east-west transect across the north part of the Michigan Road Preserve in 2011. The vegetation was inventoried in each plot to provide baseline data for long-term monitoring. Herbaceous vegetation was sampled within each 3-meter radius, shrubs and tree saplings (diameter less than 3 inches) within a 5-meter radius, and mature trees (diameter greater than or equal to 3 inches) within a 9-meter radius. These plots have been checked every year since to determine if there have been any significant changes in the vegetation. No significant changes have been found, beyond the natural growth of shrubs that have increased shade in parts of the swamp forest and across the shrub swamp.

Sampling plots or quadrats, Q-1 through Q-9, on the north side of the preserve.

Species-Area Curves
Species-area curves were produced for each sampling plot to verify that the size was adequate to obtain representative samples of species occurrence, vegetative cover, and plant density. In all cases, the sampling sizes were sufficient as indicated by the species-area curves for both individual and collective quadrats.

2014 species-area curve for all plots on the preserve. This curve doesn't flatten-out well because of the variety of conditions and resulting habitats across the preserve, but generally, it appears by the 6th or 7th plot, a representative sample has been obtained.

Species-area curves for shrubs and trees in plots Q-1 through Q-3. Three plots are adequate. The slight rise in species at Q-3 is due to new species encountered in the sampling area on an upland sand ridge, versus the swamp forest in Q-1 and Q-2. 

Importance Values
Based on Cover, Density, and Frequency, Importance values were calculated for plant species in each sampling plot. The following table is a list of the top dominant species, in descending order, on the Michigan Road Preserve, observed from 2011 through 2015.

Dominant plant species on the north side of the preserve.

Prevailing Wetland Coefficients
Importance values were combined with Wetland Coefficients for each species inventoried in the sampling plots to determine the Prevailing Wetland Coefficient for each sampling plot. There have been only very slight variations in the values listed in the table below. Prevailing Wetland Coefficients range from a low of -3.6 (Facultative Wetland) to a high of 2.4 (Facultative Upland +). The average Prevailing Wetland Coefficient for the north part of the preserve is almost right in the middle between wetland and upland, -0.7 (Facultative), corresponding to a plant community of moderate wetness.

Prevailing Wetland Coefficients on the north side of the preserve.

Species Diversity
Shannon-Wiener Diversity indices were calculated for the vegetation inventoried in each sampling plot. There have been only very slight variations in the values listed in the table below. The Shannon-Wiener Diversity indices across the north part of the preserve range from a low of 1.17 to a high of 2.68, with an average value of 2.01. These are moderate values as common and relatively undisturbed native forested wetlands in southeast Michigan typically have values in the 2.0 to 3.5 range. The generally low diversity of the north part of the preserve probably reflects the dominance of several species as opposed to a lack of species richness. However, species richness is somewhat lacking and remains a concern for long-term quality and sustainability.

Shannon-Wiener Diversity Indicies on the north side of the preserve.

Floristic Quality Index
From 2011 through 2014, the Michigan Road Preserve has consistently had an FQI value of 26.7, which places it in the middle of the “moderate to good” spectrum, on a scale of 0 to 50, as described earlier. With the discovery of a few new species in 2015, the FQI has raised slightly to 28.3. The preserve has a higher FQI than average natural areas remaining in Michigan, but floristically, is not significant on a statewide basis by the FQI standard. But it is not entirely the individual plant species that make the preserve a valuable natural area. The unique assemblage of species, sand ridge and depression landscape, sand soils, range of hydrology, wetland content, forest cover, and wildlife values, among other aspects, make this an important natural area. The combination of all these features indicate a relatively intact, native natural area retaining many important natural functions and likely to support rare or uncommon species. With further species surveys, the FQI is very likely to rise.

Buttonbush - Cephalanthus occidentalis found on the preserve in 2015. This species has a Coefficient of Conservatism of 7 (out of 10 being the highest), so the addition helped raise the Floristic Quality Index. Buttonbush is in the same plant family as coffee.
A unique aspect of the vegetation on the Michigan Road Preserve is the northern flora represented by Red Maple, Paper Birch, Black Ash, Speckled Alder, Nannyberry, Black Chokeberry, Low Sweet Blueberry, Wintergreen, Bunchberry, Dwarf Raspberry, Bracken Fern, Wild Sarsaparilla, Starflower, and Marsh Saint John’s-wort. While these species occur throughout Michigan, their distribution is generally concentrated north of Michigan’s Transition Zone. Their widespread occurrence on the preserve indicates a northern plant community somewhat disjunct from its usual location north of the Transition Zone. This is characteristic of the flora in the Port Huron area, influenced by the cooler growing season and extensive sand soils near Lake Huron. Historic fire disturbance may also have been another important factor in maintaining the northern flora. At the same time, the occurrence of southern species enhances the diversity of these areas. Distinctly southern species on the preserve include Black Oak, Juneberry, and Smooth Highbush Blueberry. This unique blend of northern and southern flora in Saint Clair County, particularly the Port Huron area, was described about 100 years ago by noted Port Huron botanist Charles K. Dodge.

Bunchberry (white flower) and Fringed Polygala (violet flowers) on the preserve.
Most of the large oaks on the upland sand ridges of the preserve key out to Northern Pin Oak - Quercus ellipsoidalis according to dominant characteristics of the acorns, buds, and leaves. However, in Michigan Flora, Part II, Voss considers Northern Pin Oak to be a northern small-fruited variation of Scarlet Oak - Quercus coccinea, likely part of a single complex of oak species according to the work of William R. Overlease in 1977. Voss suggests that hybrids between what are considered Northern Pin Oak and Black Oak may be called Quercus x palaeolithicola, which is inclusive of Scarlet Oak and Black Oak hybrids. Some of the oaks on the preserve appear to share characteristics of Black, Northern Pin, and Scarlet Oak species. The unique character of what appear to be hybrid populations of Scarlet Oak and Black Oak particular to eastern Saint Clair County has been noted by other botanists. Such trees were noted on uplands preserved along with wetland on the Super Kmart property in Port Huron Township, about 1 mile northeast of the preserve.

What appear to be Northern Pin and Black Oak hybrids on a sand ridge on the preserve, shown after the 2015 spring burn of the area.  
A few patches of Marsh Saint John’s-wort - Triadenum fraseri occur in the shrub swamp of the preserve. This is a northern species not often encountered in Saint Clair County, but more common in northern Michigan. Marsh Saint John’s-wort is indicative of wet sandy soils, occurring in alder thickets, such as this shrub swamp, but also bogs and sedge meadows, suggesting it may be remnant of a more open, fire-maintained community.

Controlled Burn
On 2015 May 01, the TLC conducted its second controlled burn on the Michigan Road Preserve. For details, refer back to:

This year we were able to burn on our own, without fire department supervision. One purpose of the burning is to kill invasive Glossy Buckthorn – Rhamnus frangula, recently renamed as Frangula alnus, a small tree or shrub native to Eurasia and North Africa. It was introduced to North America about 200 years ago, first as an ornamental hedge plant, and later as a planting for wildlife and other conservation uses. Like so many other shrubs brought to North America for these purposes, including Common Privet, Tartarian Honeysuckle, and Autumn-olive, Glossy Buckthorn became highly invasive, especially in open forests and shrub swamps. It forms very dense shrub thickets that shade-out and displace nearly every other plant species that once grew in the same area. It appears that the burning has been somewhat effective at killing Glossy Buckthorn seedlings and small saplings, but this will be a multiple-year endeavor.

2015 spring burn on the preserve.
Another purpose of burning is to encourage fire-tolerant vegetation that likely dominated this landscape prior to European settlement, before fires were suppressed. Accomplishing this should increase native woodland species abundance and replicate the vegetation structure that existed until about 200 years ago. Some of the fire-dependent species that occur now on the higher sandy soils of the Michigan Road Preserve include Black Oak and Northern Pin Oak hybrids, Black Cherry, Paper Birch, Low Sweet Blueberry, Bracken Fern, Wintergreen, Bunchberry, Fringed Polygala, Canada Mayflower, and others.

Stewardship Issues
Presently, the most critical stewardship concern on the Michigan Road Preserve is the widespread occurrence of Glossy Buckthorn. It is not likely to ever be completely eradicated from the general area without radical intervention. It may be controlled enough on the preserve so that it does not dominate the understory and completely displace native species. The hard part about buckthorn control is that it requires a lot of manual labor, pulling, cutting, and applying herbicide. This means a lot of volunteers are needed, or a lot of money to pay removal crews. And it’s delicate work because you need to sort out the buckthorn from native tree and shrub saplings, which isn’t always easy. The TLC has contacted Scout troops and a few local schools for volunteers, but with little response. So, if you are interested in helping, please contact the TLC or the Saint Clair County Drain Commissioner.