A unit of Lasting Forests evolving since March 30, 1999
A Total Forest Management Plan and Wildland Management Decision Support System
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A Consequence Table

One action rarely has only one result. In a harvest, timber profits may be gained ... but game and recreational profits may be lost. The results of not knowing almost all of the major consequences of an act can lead to poor decisions, even by very logical and conscientious people.

In addition to the simple numbers presented, a composite "score" is used to aid decision making even though the individual components and their scores are listed. Typically there are positive and negative changes in animals and plants whenever any change is made in an ecosystem or management area. The Composite Consequence index, the CC, presents a special version of net results. It presents "the bottom line." in much the same way that a Goss Domestic Product unifies many factors of an economy.

A set of indexes are "weighted" or assigned estimates of their relative importance, then averaged. These indices tend to reflect Primary Objectives. Weights are assigned by the owner or management team members and they reflect their best current estimate of the owner's or local public's feeling about the importance of each. (Later, if funds for expensive surveys become available, and analyses justify the effort, citizens or experts may be surveyed to get these weights.)

The indices are as follows. Many are classical, traditional concepts of biodiversity used by some scientists, students of diversity, or managers. There are many such concepts. This large number is part of the problem of attempting to achieve it. "Biodiversity" means at least 20 different things. It means several things to the same person. The CC has been created in response to genuine desires and the real objective of many people. The index merely attempts to approximate (not measure precisely) that interest and concern as it may be achieved on this managed area.

By studying alternative actions or before-and-after situations, differences in biodiversity and other structural and dynamic aspects of the wildland system may be observed. As an example of the way to process the number of the index, an action that lowers the biodiversity score may not be bad if many other weighted objectives are achieved simultaneously. Similarly, a score may be lowered on one forest Aarea, and increased on another area of the same forest to result in an improved biodiversity score for the total area. The score will change over the years even if no other forces are at work due to changes in the age and composition of forest stands. These are all dimensions of the CC that need to be in the mind of the people who actually use it. The many components of the index are described next. These components are system performance measures for the area which is viewed as a management system.

Component 1 - Total Faunal Richness

In most discussions of biodiversity, the desire for abundant species is implied. This is called richness and where N is the number of species, then richness, R, is (N-1) (since an area with only one species is not rich) and the rate of change in richness is)

r = N/(R+1)

where N is the number of species present at some time after R has been evaluated and decided as the standard. (For example, R may be the total from the State information system for the county(s) in which the management area is located.)

Herein we use 10 separate analyses, one for each major animal group, one for all animals, and one for all flowering plants. We hasten to add that we have not included insects, crustaceans, mosses, mushrooms, lichen, and several other forms, and these need to be added to the analyses as expertise and funds become available. It is regrettable that we seek to comprehend, discuss, and manage whole ecosystems and cannot even list all of the parts of the ecosystem comprising the management area. This, however, is not a unique condition.

The size of N may increase or decrease due to study. Similarly, study can reveal misidentifications that can change the number (there being no change in the field). We assume here that a positive increase in the number, N, will be viewed as good. Thus

D₁ = [1.0 + ((N_t - N)/(R+ 1))] x 100

For example, where there are 200 species present and 2 are added (discovered) due to research in the area, then where R, the area standard, is 199, then

D₁ = [1.0 + ((202-200)/(199+ 1))] x 100 = 101.

No change results in a score of 100, a desirable and satisfactory condition. Additional creatures "add points." There may be years when no changes are made. The value of N is always taken at some stated standard time. It should only be taken as standard when a good comprehensive analysis has been made since a limited survey could result in a very large D₁ for many years to come.Regional data bases can be used for standards. The computation of D₁ above is for all animals. Each faunal category is analyzed similarly

D₂ - Birds
D₃ - Mammals
D₄ - Fish
D₅ - Salamanders
D₆ - Toads and frogs
D₇ - Turtles
D₈- Lizards
D₉ - Snakes

Component 10 - Plant Richness Total plant species (including trees) are treated as above.

Component 11 - Tree Species Richness A subset of Component 10.

Component 12 - Shrub Species Richness A subset of Component 10.

Component 13 - Forbs and Grasses Richness A subset of Component 10.

Component 14 - Threatened. Endangered. and Rare Species Index The list of threatened and endangered species of the area should not increase and perhaps can decrease. These species are included within the count for D₁. The score for this condition is

D₁₄ = [1.0 - ((n - N)/N)] x 100

where N is the number of threatened and endangered species at the standard (or current) year and n is the count as some specified future date.

For example, if the number was 5 in 1990 and it is now 6, then the score would be

D₁₄= [1.0 - ((6-5)/S)] x 100 = 80.

No change results in a score of 100. When species are removed from the list (for whatever reason), the score increases and may exceed 100 (e.g., when there were once 5 and there are now 4, the score is 125).

Component 15 - "Species Undetermined" Status Index The identical analyses are performed on species in the "species undeterinined" classification, a peculiar category suggesting uncertainty about the status of species and real risk of loss.

D₁₅ = [1.0 - (n* - N)/N)] x 100

where the numbers are those animals in the classification currently established by the state or other agency.

Component 16 - The Restoration Index

A statement might be made: "There appear to have been - species lost within this area during the regional settlement period (beginning 384 years bp)." Perhaps they can be restored. The restoration index is

D₁₆ = [1.0 - ((X - n)/X)] x 100

where X is the number of species lost and n is the number of species restored. For example, where there have been 6 species lost (e.g., the woodland buffalo, passenger pigeon, wolf, mountain lion, etc.), and there are none (n = 0) restored, then

D₁₆= [1.0 - ((6-0)16)] x 100 = 0

Recall that one goal of biodiversity advocates is restoration.

Component 17 - The Stand-Type Index - Region Base

Maximum diversity would imply that every stand was of a different forest type. (A forest "type" is a characteristic group of trees dominated by one or two species. These are described by the Society of American Foresters.) For example, there are 33 types that occur within the Jefferson National Forest. Because of limited size of most management areas, and limited ecological conditions, only a few of these types are likely to be present. A percentage of these types is thus considered, thus the Forest-base index to type diversity is

D₁₇ = (t/T) x 100

where t is the number of types in the managed area and T is the total number of types that occur in the region. When there are 36 types in the region and 30 in the management area, then

D₁₇ = (30/36) x 100 = 83.

Component 18 - The Stand-Type Index - Area Base

An index of the proportion of land area in each type is computed by

D₁₈ = [1.0 - (p_t*)²] x 100

summed over all types , where p_t* is the proportion of the area in each type. An example is shown in Component 19.

Component 19 - The Stand-Type Index - III - Stand Base

An index to type dominance is used. If all stands are of one type, the index is 0. The index is grounded in the Simpson index (1949) and is here

D₁₈ = [1.0 - (p_t)²] x 100

where there are n types, p_t is the proportion of the stands in each type, and summation is over all types.

If there were 3 types:

Types	Proportion	(pt)2
1	0.36	0.129
2	0.24	0.058
3	0.40	0.160 Sum = 0.347

Thus,

D₁₉ = (1.0 - 0.347) x 100 = 65.

Component 20 - The Stand Size Index

Stands, the smallest similar unit of land, all of one type, and usually treated similary, vary from large to small throughout the area. They should vary in size to provide the diversity of conditions suitable for many animals and plants. Managed areas for small ownerships are too small for an index to be of great value, but they may be of use in some analyses. Herein, the distribution desired is said to be poissonal (i.e., the mean of the sizes should approximate the variance and many observers say "randomly distributed".) The scoring device is

D₂₀ = [1.0 -ABS ((variance - mean)/mean)] x 100

where ABS mean "absolute value." If there is no difference in the mean and variance, then D₂₀ = 100.

Component 21-22 - The Stand Age Index

Different life forms are associated with ages of forest stands. Many are strongly related to stands with a predominance of old (60+) trees. In mixed-age hardwood stands influenced by previous harvests, fires, and storms, the predominant age is difficult to determine. Stands with a low stem count and high basal area are typically old-age stands.

The age index analysis has 2 parts, one for older-aged stands, the other for the distribution of the younger-aged stands.

Older-aged Stands

D₂₁ = (1.0 - ABS(area in older-age stands -(0.33 x Total Stand Area)) x 100) / (0.33Total Stand Area)

The younger-age stands are assumed to be distributed as the negative log or the reversed-J distribution widely recognized within forestry. The analysis is based on area of all stands of less than 60 years. To extent that the actual distribution fits (R² analyses) the reversed-J distribution, a score for D₂₂ of 0 to 100 is assigned.

D₂₂ = (1.0 - (Actual Distribution - Hypothesized Distribution) x 100) / (Hypothesized Distribution)

These scores are weighted, added, and averaged to produce the CC index. It is computed as:

CC = ( D_i W_i)/ W_i)

where, in this case, summation is over all components (i) of the concept of biodiversity.

We have developed the above approach:

1. to be inclusive;
2. to allow expert knowledge about the goodness or relevance of each index to be expressed and;
3. to provide a means to help thoughtful people to evaluate past or proposed changes on the land.

Other components of the index, CC will be included as developed.

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This Web site is maintained by R. H. Giles, Jr.
Last revision January 17, 2000.