Faunal Force

Provincalism

                                   

 

 

  “Have you lived here all of your life?”

  “No, not yet.”

I’ve lived in Virginia most of my 75 years. Maybe I’m provincial for I am influenced by my environment in Virginia. Virginia does not have high rank in many lists of desirable characteristics, accomplishments, strengths, and desirable human conditions. It’s OK, but that word may be a pseudonym for “provincial.” There are political forces here that influence education and the people around me. There are abundant people in poverty. Tax bases for the State as well as communities are limited. Turn-over rates in employment and thus ideas and innovations are low. 

Central Appalachia is not a happy place, in song, dance, art, or ideas. It is a place to survive, to keep on keeping on. Lynchburg, in the Piedmont, where I grew up was a black racist and white snobbish place, out-competed by Roanoke, and without a vision. It and its surrounding communities was a provincial small province of Virginia. I had every right to be provincial.

Television changed some of that. It let the light in. The differences became clear, beyond what could be taught in a few hours of schooling (about 5000 hours is my wager). The differences between what we had and what others had were shown to us on the monitor. Some of us were “dissonant,” troubled by the difference between the present and the possible. Others, poor and powerless, knew well how to survive. There is no entitlement; life just is. It is a waste of time to think about the impossible. People live what they have or are given. Some inherit more than others. That is the way it is.

I went to Oregon in 1952 and saw Douglas fir trees. Each tree, an enormous thing, had more wood in it than any acre of forest I had seen in Virginia. Engineers were hired to move these complex masses out of the forests. Conditions for growth are very different in different parts of the world. 

I went to Idaho in 1965. I had come from mountains and I had lectured and pleaded with landowners to try to stop erosion from their slopes. My Virginia hills were millions of years old, well-rounded, eroded away Himalayan-sized mountains. They eroded badly in some areas but in Idaho I saw young mountains from shifting lands and volcanoes and they eroded whole sides of them, carved deep valleys, and left deep house-covering “earthen fans.” Erosion was out of scale; day-log events moving the same amount of earth as year-long processes back home. The effects, amounts, residuals were unimaginable. They had to be seen on site.

I went to China in 1991 and saw what was meant by a “human population explosion” and “tables of human density data.” One night I asked a conductor on a train speeding through the countryside of Northern China, “Do you like your job?”

My translator told me that the man could not comprehend my question. He had a job. That in itself was a good condition. In those years there were no alternatives. Any job is your lot in life. You live what is; what is given.

With Blair Jones, Charles Smart, and others I developed for Virginia a statewide geographic information system before such things were called a GIS. It changed the scale of my thought from a state map on the wall or a fold-up in the glove compartment of the car to map cells or picture elements (pixels) of about 27 acres each. In my computer I “knew” 50-100 factors about each cell in Virginia, all 1,013,902 of them. I was no longer thinking about my back yard, the town, the county … but about the best place for a power corridor … one among the thousands of possibilities between two designated points … and then “what if one of the proposed points (for delivery) was changed?”

I have a pottery chard on my desk from a sand dune in Nigeria, 1990, a dune half covering and engulfing the home of a family. The desert was on the move. Deserts, once forests, were now on the move in China too. I met the person in charge of stopping them. He would fail, for he did not have the time, money, or staff for the necessary action. Areas in the US are now becoming deserts … and climatic warming speeds the process.

Maybe I’m “provincial” because of where I have lived and maybe thoughts are not fashionable or off-centered.  I doubt if I’m called “self centered.” I know I’m not as well educated as I would like to be and I’m hardly sophisticated. I’ll not try for the latter and continue work at the former. Or maybe I cannot comprehend the question: Just what does it mean to be provincial today in a globalizing world?

Bugs at Night

There’s not much technology on the surface of a task of trapping insects. Whole books are written on the many devised ways to do so for scientific study …and to remove pests.

I used seven ways to estimate insect population sizes before and after an aerial spray application of Malathion insecticide. Those were to sample the insects likely present during the daytime.

Some insects are not active during the day and cannot be sampled by sweep nets, molasses traps, sticky-board traps, extraction from soil, etc. I needed to sample at the center of two woodland areas at night, then to repeat the sampling when one area had been sprayed, then to make the comparisons.

I purchased a light trap, one with a “black-light” or ultra-violet-fluorescing bulb. It was large and bulky and I needed a power source in the center of the forest. I had to build a carrying box, find large wheels suitable for easily rolling over limbs and logs in the forest, find a “converter” to change DC to AC current from the 12 volt auto batteries, and then go and sit in the silence of the forest alone in the purple of the night watching insects hit the baffles and fall into the poison at the base.

These were nights of reflection about sampling errors, about adequate sample size and about whether “a little knowledge may be better than none” … unless the sample is too small. On these nights I discovered yet-un-named insects and surrendered to my doubts that I could understand and model a system with things in it about which I (or anyone else) knew nothing and had met for the first time.

I did not catch enough mosquitoes. They were concentrating on me. I was especially concerned about their attacks for I had taken a class in Medical Entomology from Dr. Carl Venard at The Ohio State University. There seemed to be danger in every buzz.  I caught beautiful moths … and I was sorry for their loss. I caught many adults of the “inch-worms,” the forest leaf eaters also called “millers.”

Of course there were differences in insects caught before and after the spray, but the differences were confounded by extreme differences in numbers trapped between areas, between years, between nights … just another expensive study confirming ecological variability and raising doubts about whether the much-touted “comprehensive knowledge of the functional ecosystem” can be achieved.

Fog Drip

I’ve written about the cloud and even though many people speak of “cloud computing,”  Fingar in his Dot.Cloud  book described the cloud as having both a computer dimension as well as a profound business dimension. It refers to new computer and Internet influences on  marketing, advertising, collaboration among enterprises, internal corporate structure, and a shift of emphasis to serving the customer. It, like real clouds, can be hazy at the edges, moving, and ever-changing. It is a concept that might creep into the windows of  state and federal natural resource agencies, but I doubt it. It ought to.

I’ve mentioned fog drip in several posts one  related to a new form of watershed management.

There’s a new addition to the Encyclopedia of Earth that include “canopy drip.”

Canopy drip – the water from rainfall or snowfall that falls along the edge of a tree or plant canopy, common in coniferous vegetation. On the ground, canopy drip creates areas with higher moisture content that are located in a narrow band at the edge of the plant canopy.

I’m fascinated by fog drip. I first saw its parents on a winter walk, 1956, at Mountain Lake, Virginia, within a hoarfrost-covered hardwood forest.  I later learned that conifers “comb” moisture from moving low clouds and fog and it drips from their needles. Leafy trees do the same and the moisture is directed as stem flow or drops to the ground. This is moisture not recorded in rain gages! It is precipitation that changes the water budget of areas. In areas where there are typically 40-50 inches of annual rain, it may add an additional unaccounted 10 – 12 inches … further explaining the variability in ecosystem studies.

In two adjacent forested areas, one from which trees were just harvested, one will receive 12 inches less than the un-harvested area; it will have less soil moisture and absorb more of peak rainfalls than the other, have less runoff (but perhaps more…depending on the storm intensity).  Whether the ground is frozen or not  determines the effect of melting hoar frost. It’s a fascinating, complex world out there. It needs to be modeled to help understand it and predict its future states … and then prepare for some of them.

Rational Sloppiness

We don't know everything that we need to know about wild animals, human values and human behavior in relation to animals, or about faunal spaces, all of which are changing. With 3000 large animals to master and at least 100 topics of interest about each animal in at least 50 significantly different areas of the world, we need only 15,000,000 studies. We've done 10 thousand in the past 200 years. At a silly minimum of $10,000 average for each study, the resources needed are not available ... and never will be! ... even in the next 200 years with the entire budget of the US Fish and Wildlife Service devoted only to studies which will not happen. It seems irrational to continue to act as if an impossible act is possible. We need an alternative. Rational sloppiness is the name of such an alternative and it includes, simultaneously:

1. Using statistical levels of confidence of about 0.15 (not 0.05) as seems to be required in agricultural publications and widely adopted by Wildlife Society editors as the mark of good research.
2. Using expert system theory and its technology.
3. Using and concentrating studies on the upper and lower limits of statistical range, not the mean, mode, or variance.
4. Using native expert knowledge gained by interviews (especially of ranges).
5. Using the results of retirement interviews and agency-expert interviews.
6. Using computer models (simulations).
7. Using dynamic planning models, improving units within such systems.
8. Developing coordinated database-building projects.
9. Developing and using group statistical services.
10. Developing Internet data and information sources.
11. Developing optimization programs, then using sensitivity analyses as the grounds for research fund allocations and for planning strategically selected project topics.
12. Improving use of volunteers in planned projects.
13. Using GIS to generalize about the conditions suitable for population occurrence and abundance and about human uses of areas over time.
14. Re-organizing animal and plant taxonomy along genetic and functional lines, relinquishing the hold of anatomy and structure on the patterns of study now in force.
15. Producing and then continuing to revise within models a set of principles and generalizations about populations, faunal space, and resource users.

We need to loosen the hold of the ultra-precise and ultra-confidence now required in labs for the real work to be done in the variable outdoors where every alpha unit is unique and essential levels of accuracy as well as confidence are closer to 0.15 than 0.05.

We need to become more rational about the limits of our time, skillful people, and funds and to relinquish a lab model of gaining knowledge for a system of studies that is diverse, chaotic, and responsive to sequential changes at sites affected by conditions in nearby sites.

We need to adopt an attitude of gaining tentative goodness of knowledge ... with feedback.

Predator Management Revisited

Predator management is a topic in the gray zone among public values, hunting and trapping, integrated vertebrate pest damage management, and population management. It is a controversial practice and may, in some situation, have undesirable secondary effects that are worse than the initial reason for initiating control. When predators or their populations are out of control they may affect recovery of species that are threatened or endangered. Predator control is expensive. If started, typically it must be continued. It is only recommended when:

• it is not likely to involve an endangered species,
• costs and losses of predation are measured,
• real (not likely to change due to chance)
• significant to the land owner, and
• the costs are substantially less than the perceived losses.

A predator is an animal that kills or eats other live animals. An omnivore eats animals and plants and so may be a predator. The difference between predators and other animals is that they eat  animals in which a person has direct interest. When there is no direct interest, it is probably best to observe nature for there "things eat other things" regularly.

The modern manager is attempting to control damage, not injury.

When large numbers of an animal are needed or are to be produced, then losses need to be reduced ... and predator control is one such way. It must be continuous and viewed as a direct cost of operation. If done irregularly, it can result in great, usually undesirable fluctuations in both predators as well as prey.

The Fundamentals

Mortality is an expression of a loss rate. Natural mortality in wildlife populations is a numerical rate. It is one of the major dimensions of population dynamics. Deaths of animals result from many factors: starvation, disease, accidents, energy loss in severe weather, perhaps "old age" (but other factors like loss of vigor, senescence, and effects of poison and disease operate) ... and  of course there is predation. Predators are only one of many elements, (no matter how conspicuous) that influence population abundance. When a population of interest (e.g., a game animal) is part of a community and well established there, conventional predator control efforts will not increase that significant population. It is influenced by many factors of the environment and even though predation pressures may be lifted, the population will soon encounter other factors that limit abundance.

Predator action is believed to be, in most natural systems, mortality that is compensatory. This means, generally, that if predators do not kill animals, something else will kill them or they will die and the effect of the loss in the ecosystem will be about the same. Some biologists claim that predators remove the sick and old in a prey population. Predators are probably not very particular and seize any opportunity to take an animal. The more likely effect of predation is that when a prey animal is removed, the remaining food and other resources can be used by the remaining animals (i.e., more food per prey animal that remains in the system).

The story of predation is mixed and confusing because the predators as well as prey differ in their behavior, habitat requirements, and their reproductive rates (thus recovery rates). That foxes prey on mice does not elicit nearly the concern as that which is produced by their preying on rabbits. Some omnivores are predators as some time. It is useful to discuss the role of a species identified in a particular situation as predaceous, not a general class of behavior, and to discuss the probability of real, financial, measured losses resulting from such behavior.

When animal populations are not natural, i.e., when they suddenly (within a few years) have reduced feeding areas or when they nest in unusual places, then predation can cut into a population. (It is no longer "compensatory" but "additive.") Under such conditions when predators are attracted to such areas or reproduce and achieve unusual densities, then predator suppression (after suppression of effects (as by fencing)) may be used. Such direct predator population reduction has been effective in reducing losses to waterfowl and to endangered species where their populations, due to human involvement, are high. Again "prey determine predators" is the general rule. (There may be exceptions.) Sadly, from a financial viewpoint, most control efforts are costly and must be maintained and diversified for the suppression to continue. Reducing predator population effects is a cost of land use elsewhere that has typically produced the high prey populations.

Very intensive predator control using a variety of methods (including poisons) can reduce predators. Prey populations will respond, but that response is small and it is rare that unconventional, diverse, sustained predator population reduction is attempted. The costs are very high. One of the fundamental concepts of predator management is that in natural populations, prey determines the number of predators, not the converse statement. A general rule: the number of predators present is the population response to a food supply, one with more energy taken in than energy lost or required to prey upon and process animals taken. Net energy rules in the domain of the predator population. Rarely do predators seriously reduce a wild population with high quality faunal space ("good cover") or habitat conditions.

Sample Recommendations for a Specific Area/Population  

The plan is to monitor predator and prey populations. When predator populations increase substantially (more than 50% from previous 3-year mean) and the effects of that change seem to reduce our ability to increase the system performance index, then and only then will control efforts be discussed and a cost-effective program possibly implemented. We seek balanced populations of predators and prey with both contributing to the desired index value. Excessive numbers of each may be "natural" but losses to many objectives (animal disease, economic stability, recreation sitings, safety, etc.) require action that results in the desired balance. The "desired balance" is difficult to decide and that is why quantified objectives are used and so carefully developed within The Trevey.

A program to suppress predator effects is to be implemented. Often predators prey on house cats and dogs, on penned poultry, and on animals on the range or pastures. The effect is the problem, secondarily the animal. We encourage as a first and almost final strategy the improved husbandry of all livestock including care, confinement, rotating feeding and watering areas, human presence, use of protection dogs, fencing, health maintenance, insurance, and rapid complete disposal of sick or dead animals.

We consider studying the general management practices outlined for animals. Most are provided to increase populations. We rethink each as it might apply to reducing the predator(s) with which we are involved. The reverse of the recommendations may be the action needed.

Then, and only then, do we recommend careful in-depth discussions of effective suppression of effects. Note, we have not yet mentioned killing predators. If a predator takes $500 worth of livestock, is it worth $600 to control it? We first argue for reducing expected financial loss. This is an economic expression, the product of (1) the probable value of a unit (e.g., a bushel), (2) the probable units produced, (3) the probable proportion of loss of (2) due to animals, and (4) the probable price per unit. Is loss of a fawn deer in an area that is highly over-crowded with deer a loss that needs to be stopped? We suggest that is not the case.

We seek first to suppress conspicuous effects, then suppress expected net present discounted financial loss, then reduce unnatural situations such as animal feedlots, watering areas, and human constrained migration routes, then to prevent such occurrences.

Managing populations of mice or other small rodents, a prey base, is what is needed to meet the needs of some wild animal populations (called predators) such as the hawks, owls, foxes, and cats. Many predators are as prized as game animals and some are endangered. Thus they need all of the skills of managers once devoted to increasing populations of game species (most of which were plant-eaters). It now seems that predator management (to increase them) depends more on prey management than habitat management, though both are intertwined. Many carnivore populations have the ability to recover rapidly.

Our plan is to analyze objectives, express evident effects, suppress effects cost effectively, analyze residual effects, then use predator suppression where needed. In some cases a single animal or pair may be causing dissatisfaction. These will be removed, live trapped where feasible, and placed in an appropriate area. Usually there are no suitable areas; populations are at capacity, behavioral disruptions may occur in the population into which the extra animals are placed and and create problems for other people. Otherwise the animal will be dispatched humanely. Significant change (as stated above) in perceived effects; not necessarily animal abundance, will be an emphasis.

Like other animals, predators are a function of their habitat. Often conditions for them can be reduced. After this, cost-effective populations suppression will be carried out. Trained suppression agents will be used. Humane treatment will be emphasized.

Multiple-predator species will be the first assumption that will be made until observations determine an alternative. That the predator populations are larger than evident will also be a typical first assumption. Seasonal shifts in home range and movement will be expected. Home-range overlap of individuals is expected.

No bounties will be used due to persistent fraud and ineffectiveness experienced, widespread, with this practice. It is well known that bounties are not effective and should not be tried.

Repellents (chemical) as well as guard animals (dogs,llamas, donkeys, etc.) may be considered.

A long term view (more than 50 years) will be used.

Scent post studies and road-side observations will be used to establish population trends (for comparisons with perceived predation rates).

A protect-the-predators project exists and Wildlife Damage Review is an anti-federal predator-control organization (PO Box 85218, Tuscon, AZ 85754).

Re-Visiting Statistical "Range"

Range has several definitions found in statistics books. It may be the highest and lowest numbers observed for a set of observations or a single number which is the lower number subtracted from the higher number. Some texts describe it as this difference plus one. It is too simple, it seem, for high-powered computers and software that can do so much. It is too unstable for people who want the average and some expression of variability. In range however, we may be able to find the answers to some of the animal and plant questions that are of great interest to all of us.

I live with the premise that the mean, the arithmetic mean, may never occur. I count animals and I invariably get statistics with fractional animals. Knowing that none exist is not the point. I take the average of 4 animals observed and 6 observed and get 5...and a group of 5 has never been observed! The same occurs for almost every set of observations made by ecologists or economists. Perhaps the mean is not the number I want or need for certain decisions. That the mean may not exist is a premise that begets caution and a new (at least alternative) view of data.

Most ecologists, at least naturalists, like to know the biggest, the tallest, the fastest...anything. Zero is commonplace in ecology so the range becomes the same as the value of the maximum. When means and standard deviations are used, these statistics may hide such extremes. They may hide them because the selection of the number of standard deviations only brackets a limited number beyond the mean. "The mean plus or minus 2 standard deviations" means that even if the population is well described by the bell shaped curve, only about 68 percent of the values observed and like to be observed are included within the stated limits. The extremes are there, part of the computations, but ignored or dropped in the statement about the population. In my observations, most ecological populations are not normally- or bell-shaped and thus normal statistical thought (that about "bells") can be very misleading. The range, usually the maximum value, but both lower and upper limits, are needed to conceive of the shape of the skewed distribution. A return to thinking about and using the range may be useful.

When I try to reduce sample sizes to reduce costs (since budgets have become mystical), then I reduce my requirements for confidence (from 5 to 15 %), the acceptable inaccuracy from 5 to 10 %, and then I look at the variance (the third major factor in most sample-size determination equations). I recall that the range, not the sample size, is the controlling factor in making that estimate. The variance is often difficult (and expensive) to get. (To do so justifies all of those pot-boiler studies, preliminary works, and seed-money requests.) The range for normal populations is about 6 standard deviations and the variance is merely the square of the standard deviation. We can make progress (not as well as with a lot of money) at low cost by using what range tells us in the context of some reasonable assumptions about sampling to inform managerial work in a highly variable field (with few penalties for being wrong.)

I usually imagine that there are three dominant independent variables affecting almost any wildlife variable of interest -- habitat, population, or people. If I plot those three variables as axes of a box, and mark off the range of each, then I can imagine the topic of interest, the dependent variable floating around, driven by changes, but always within the box. The dominant factor box gives me a feeling of control, of understanding. It limits my chances for being wrong; it suggests new questions and ways to perceive the complex world of work.

In analyses of streams and rivers, the maximum flood height is reported and often expressions of the 10-, 50-, or 100-year flood crest are used. This value results from cumulative observations over time. People measure the height of the flood and then, year after year, measure the height...but only plot the height of the water if it exceeds the highest water on record. They are clearly interested in the range, the highest that the stream will ever flood...for safety, etc. Most rivers and streams now have such records. A logarithm, a log-log graph, or a simple exponential function readily approximates the graph with time as the independent variable (such as in species-area curves now often used by ecologists). I suspect we do not have such records for many animals (either weight or population sizes), for the biomass of plants, or for the biomass of communities. By judicious use of records (and with the same software that is used for determining this curve for stream crest estimates) we could estimate the maximum weight of warbler X, or elk Y. Ecosystems, by some theory, are energy maximizers. Why then, should most of our observations be of the mean and its deviations? Why shouldn't we evaluate the difference from the estimated maximum (or minimum, which for most animals and plants is zero)? Cannot the same curves with ranges be used to estimate the maximum and minimum temperatures for GIS map pixels? For fish weights? For hours of lake fishing? For miles of recreational hiking? For estimating extreme ranges that are used in GIS systems to screen and clean data. There are few things in the environments in which I live that have values less than zero. There are few that have infinitely great values. In the field, I wish to deny the facile assumptions of sophomore math and return to estimating the real limits. When I make decisions in the wildlands, I want to see what would happen if likely, extremely great, and extremely small events occurred. By working with ranges, using them in maps and simulators (often with the uniform or flat distribution), or in combinations of these, I can reduce my risks and generally improve my decisions.

In GIS work, I think each of three unusual artificial layers will be found to be useful as independent variables for making an estimate or prediction of an occurrence of ecological variables. These three are the maximum value (or proportion) in a 9-cell window, the minimum value in the window, and the difference (the range). When doing landscape-scale work such as comparing watersheds or viewscapes, I want a map layer with the range in each polygon or map cell.

The range sounds too gross to most field analysts straight out of school. They have never worked with the GIS! Map the range with slope, aspect, elevation, boundaries, landform, roads, lakes, and lake zones. The complexity, the noise, and the unfathomable relations in a map of so many factors when combined will suggest that any discrimination that the range makes possible will be very welcome. Perhaps the GIS experts can help field people see that range itself is the factor of importance to be estimated as related to locators of elevation, latitude, and longitude and that such discrimination opens new vistas for understanding the worlds of wild plants and animals and the people who use them.

Basic Fern

Herman J. Heikkenen died in October, 2008. He had many ideas and many unusual observations and hypotheses.

I wish that I had made the one about ferns that he shared with me. It is so like him; so precise. I am not sure what to do with this observation. Neither did he. It might have been made by someone else but it flowed out in conversation on one of our field trips.

“Have you ever seen a Christmas fern (Polystichum acrostichoides Michx. Schott) with a blemish on any frond? Have you ever seen one with a disease or an insect “bite"?  He asked.

Ferns are believed to be among the oldest living plants. They have weathered storms, diverse epidemics, and hordes of insect and other creatures over a thousand thousand years and here they are … clear and shiny in the back yard. All of the other plants have spots, chunks removed. Rarely the fern. This plant has to contain the mother of all insecticides, fungicides, and molluscicides.

 

I have never seen damage on ferns from snails and slugs. The deer rarely eat the adult fronds. Several fern species have had historical medicinal use in removing tape worms.

Someday someone will study the plant, isolate the resistant and repellent substance(s), attribute the discovery to “biomimicry” and claim it a victory in the “green” or organic gardening wars.

Foggy Cloud

Professors have to name their ideas so that they can teach them … titles in lectures and handouts. Students learn subject matter over four or more years and develop a pattern. They learn in named categories. Business people, graduates, think in named categories … as they have been taught. Things, even obscure ones, have to have names.

I once dreamed of simulating massive ecological/environmental/land management/river basin/ socio-economic systems and integrating with them with optimization units (1965). I didn’t know what to call all of that together. It didn’t matter. The computers then were too small for such thought. Now I have a computer on my desk linked to servers. It is large enough. The demand for such systems has now diminished but in my view the needs and computer capabilities have increased.

There’s a parallel. There’s a thing out there somewhere being discussed by many people that’s a high-technology thing with some “stuffness.” There are collectively software and servers, the Internet, and hardware all working away and likely to be working differently soon. There are advances coming that are likely to be important to information technology people, businesses, to the defense department, and to new global-energy-economic-economic-esthetic-enforcement interacting “thingies.” No one knows what to call all of this which is working together.  It has been growing and changing, sometimes smaller, sometimes more expansive. It is being described in great detail for individual important functions, generalized for its effects on society and the globe. It is  both technological and computer-intensive change as well  social change because some leaders  think that technology and the Internet, so developed, will change the way companies are structured. Teams will dominate, companies become collaborative, and major emphases will be turned from the corporation to serving the customer. The changes in speed and knowledge-bases will change the whole business model and thus staffing, leadership, funding, and strategic developments will occur …computer aided. It is a different, large, changing, impossible-to-define thing, and will likely to remain so (like discussing “globalization” or “love.”). There is no “standards group” for the immediate future.Nuances and add-ons come at the square of the definitions.

It has to be called something, given a name category, for naming was what graduates were taught. It’s been called “cloud.” It’s a file label.  It’s a flag under which papers, conferences, and small discussion groups may meet so they we all may begin to comprehend the coming advantages … and risks. It’s a name for a lot of small changes coming together, becoming interactive, and many more for the near future. The changes will likely be notable in businesses work, the projects within the Internet, the software support to businesses and their conglomerates, payments, and the analytics available on customers and suppliers. But it needs to include and embody what people in the above activity do now.

What’s all this “cloud talk?”  Narasimhan mentioned emotional and conflicting ideas about its meaning.I talked briefly of the cloud  in Handshake 2.0after reading Fingar’s Dot.Cloud book.

It’s about an idea that escaped the computer inner sanctum and rested above businesses, diverse technology, and futurism. It’s a picture of a glance into the probable socio-economic world rebuilt and continually reshaped at all levels by computers and the Internet.

The world of environmental relationships of all types just has to mix into the cloud, to participate, utilize the technology, learn the social system gains, and present the ecological and human gains and losses in the increasing involvement of the public in land use decisions.

Behavior of Wolves

In a recent seminar on Science, poverty and lion conservation in Africa, Dr. Craig Packer described the notable differences in lion behavior toward herders with spears and those without them. I took his comments as supportive of the observation that other animals may pass along behaviors and that wolves also learn and somehow pass along knowledge that people with guns are to be avoided (as was the case in early US history). That now may no longer be the case as a new population of re-introduced wolves in the USA increases. See notes of Will Graves in his 2007 book Wolves in Russia: Anxiety Through the Ages, Detselig Enterprises Ltd, Calgary, Alberta, Canada, 222p. (Will N. Graves, 900 Hillen Dr., Millersville, MD 21108)

Insights into Streams from Their "Order"

One way to understand stream is to analyze their order. See attached figure. Where two first-order streams join, the stream becomes a second-order stream. A first-order stream is a headwater stream and may be dry most of the year. It can be considered as starting on the surface of the ground as a small indentation in the land at a ridge or any upland. It is where an extremely large rainfall will start to collect water. On a USGSTopo map it will be nothing more than a dip in a contour line near the top of the ridge. This is different from many mapping systems (and will show higher order streams on our maps than those of many other analysts who usually use only blue-line streams identified on 1:24,000 scale maps). A stream remains at anorder, no matter how many more first-order streams flow into it. When two second-order streams flow together, then the stream becomes a third-order stream. This pattern of description may continue to an ocean. The largest rivers are ninth- and tenth-order streams. (One estimate is that the Mississippi is a 13th order stream).

The interest in stream order is long-standing. Mathematicians, hydrologists, and ecologists have been interested in the pattern and have found the following relationships:

As stream order increases (in general and with few exceptions)...

1. Stream width increases
2.  Stream surface area increases
3.  Stream depth increases
4.  Percent of the channel subsurface that is rubble increases
5. Percent of the channel subsurface that is gravel decreases
6. Channel elevation decreases
7.  Channel gradient decreases
8.  Percent of the channel in "pools" decreases
9.  Number of fish species (species richness) increases
10.  Similarity of community structure increases
11.  Similarity of animal assemblages increases
12.  Temperature increases
13.  Dissolved oxygen decreases
14.  Usually pH increases (depending on site)
15.  Carbon dioxide level decreases
16.  Level of carbonates decreases
17.  Bicarbonate alkalinity increases
18.  Turbidity fluctuation increases
19.  Turbidity, itself, decreases
20.  Conductivity increases
21.  Production-to-respiration ratio increases
22.  Physio-chemical stability increases

I'll add factors to the list and relations indicated as more knowledge is gained. (I'll welcome advice about these generalizations.) Some of the above items are correlated; some seem like common sense; some are mirror images of others. One effort herein is to suggest how much we already know (or can learn) from simple observations. Perhaps such observations can improve decisions, help understanding, and reduce risks for the landowner and manager. Besides, 22 findings from one measure from a map seems like a productive measure. It suggests payoffs ahead for unifying knowledge.