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of an Alternative Wildlife Resource Management

Unique Nearness Sequences and the Zone of Influence: Faunal Spaces for the Modern Manager

Robert H. Giles, Jr., Professor Emeritus, Department of Fisheries and Wildlife Sciences, Virginia Polytechnic Institute and State University, Blacksburg, VA 1993

Abstract: Wildlife managers see limitations to conventional watershed-based planning and management decision-making. Computer capabilities now allow alternatives in habitat analysis and management to be considered. For the future, we suggest that a concept of unique nearness sequences will be useful in faunal system management. The concept is grounded in the following: (1) every spot (1 m²) in the field is unique; (2) every spot is related to adjacent or nearby phenomena; and (3) every spot changes with reasonably predictive sequences over time. Models of the ecology, energetics, esthetics, and economics of each site provide the basis for goal-seeking systems for regions, states, and provinces. Such systems when developed with dynamic report preparation, become planning systems and decision-aiding systems, making static plans passe.

Because of growing concern about the many meanings of once-familiar and agreed-upon words used by participants in conferences such as this, we wish to build a brief conceptual structure. We wish to be understood and not misunderstood. We do not have time to describe why we reject certain alternatives or to list support for our brief paper. We start by limiting wildlife to fauna, only those macroscopic. and only those for which at least two methods are known by which the population can be influenced by managers. Thus this paper is only about manageable macrnfauna, both terrestrial and aquatic.

Next, we use faunal space in a way implied by Hutchinson (19 ) who described the ecological hyperspace. We think that the word "habitat" was once useful, and still is useful in some groups. We suggest that it can be replaced by a multidimensional view that includes the familiar variables of area, forage, stem and plant density, exposed soil, foliage layers and their density, and many others of the "surround" of the individual animal. There are already enough variables named to convince anyone that an animal is a function of, influenced by many variables, thus lives in a multidimensional space. We think the physical and biotic elements of habitat are important and have been stressed. We wish to emphasize, however, that an animal is also a function of the presence of another animal, examples being wolves in a pack contra the singular wolf or singular fox kit compared to a litter of four. We also wish to emphasize that a manager of a migratory animal, short-distance (e.g., deer moving over 2 farm ownerships) or long-distance migrants (e.g., the neo-tropical migrants), are very much a function of several unique sets of physical and biotic factors including the population itself (i.e., the surrounding flock with which it migrates). An animal and a population is a function of past environments (e.g., calcium availability 3 years ago) and past populations (within which we include predators in the same way we tally stems or bunches of grass). In summary, we no longer think "habitat" is theoretically or practically useful and argue for use of the concept of n-dimensional faunal space.

Next, we suggest that, at least at a minimum, wildlife workers study the three dimensional physical space within which populations live. Some are almost A exclusively upper canopy feeders; others live mostly in the top 7 cm of soil. The relevant faunal space is a volume deep into the ground and high above the vegetation canopy. Ignoring plant roots is as silly (unwise) for the habitat analyst as ignoring the volume within which many of the prey-base of the macrofauna live.

We have observed the species-area curve relations developed by many workers, i.e., the relationship of

S=cA^z

where S is the number of species on an island, a proportionality constant, A the area and z a rate phenomenon. We suspect that the variance reported in values of z may be related to the faunal volume and area edge available to animals, not to map area. Fagan et al. (19 ) found strong habitat differences within an area influenced species numbers. Giles (1978, in prep.) has described the "tunnel" at land use edges, a rectilinear volume with length, width, height, and quality --a measure correlated with and called by some "edge effect."

As we have studied these actual, three-dimensional volumes and conceptual volumes, we have become aware that every spot on the land of Earth may be unique. We realize there are about 1.52 x 10¹⁴ m² of land on Earth. If we postulate a mere 200 soil types, 8 aspects, 6 land forms, 6 slope classes or categories, 20 elevation classes, 20 rainfall classes, 150 land use classes, we have more than enough unique classes into which to fit potentially every square meter. Of course there will be duplicates; but of course we have listed only 9 discriminating variables. We suspect there are at least 50. (There are 1.12 x 10¹⁵ classes available if we use 50 variables each having only 2 conditions, not 150 ( as shown above.) These numbers are mere arithmetic to ma~e two simple points. One, is that each spot on Earth (we think a meter is as far as we need to go) is potentially unique. To group"spots" causes loss of information about sites. Point 2, computer capability now exists to handle all such spots. We no longer need the summary statistic! We no longer need to group and classify. The computer has changed all of that. We may want to compare things with old groupings and some people may want or insist upon "big pictures" and "bottom lines" but we are now of the view that every spot, every square meter, every subunit of a wild faunal management system should be viewed as unique.

A particular consequence of this view is that we must reject our personal long-held view that the watershed is an appropriate planning and descriptive unit. It is a unit; it can be good for some purposes, but it is not longer the best or most desirable unit. Watershed analysts have long known about the non-replicatability of watershed studies. Each is unique. There is over-aggregation within such a unit. A high point in a watershed does not have the same characteristics as a low point. A southern aspect has few of the hydrologic properties of a northern aspect. We believe each unit, each "finite element" of a watershed needs to be treated separately. The cell size is important, of course, and a function of many factors (those typical in any land use sampling design). We think watershed planning is an improvement over other types of planning but managers should not be trapped by it before engaging the land cell or volume.

If it is not possible for a person to accept such a view, then surely every volume having a meter-base must be unique!

Before we venture any further, let us suggest the implication of this simple view of how habitats can be analyzed, evaluated, and managed for the future. We do not go into detail, only suggest that

1. We can utilize the power of geographic information systems.
2. We need not over-aggregate data to discover our test statistics are so low and variances so high that we can explain or predict nothing from our studies.
3. We can stratify our sampling reducing costs by several orders of magnitude.
4. We can begin to see where animals really live and the things to which they really respond without the noise produced by our classification system.
5. We can collect separate data for each spot, then use it in multiple studies contra single studies based on unique classification schemes.
6. We can make separate map analyses for any species, or group, or either over time. Williamson ( ) presented the concept of dynamic mapping of ecological interests.

Contiguity

Faunal system managers understand edges better than anyone except those who work with tile. Evident in the field, is that plants in each spot of the land (whatever the scale, hectare to meter) are related to the factors in the spot (hereinafter called the map "cell" but meaning the total column, the volume above and below the mapped land surface). They also know that they are related to the moisture and erosiion from the cell that is at a higher elevation, the wind temperature from the side, the pollution creeping uphill (Giles ). What is measured in ecology classes "in the quadrat" is a scant image of the operational factors for a plant or animal. (It is a small wonder that explanatory equations using conventional within~cell observations have yielded the explanatory-descriptive power that they have!) The within-cell factors pale in influence to nearby cell factors and to differences in sequences of events within cells.

We have observed from our first geographic information system work in 1969 (Fales 1969) and that in 19 (Hoar ) that overlay mapping such as advocated by McHarg ( ) is useful. We observed "weights" included in such systems (as if adding several maps of one factor) were useful. We have worked with exclusion mapping with Boolean limits, suggesting where a species could not occur because conditions were limiting or unsuitable. These were a type of model but we have seen and done cell-specific modeling. By this we mean developing a computer program with non-linear equations and conditional statements that take many mapped data sets as inputs and create a new map of some phenomenon (e.g., probable soil erosion from a cell, suitability of the cell for an animal species, probable game harvest, or probable recreational sightings).

We are of the view that, at least for future maps, every cell adjacent to each map cell should be examined and factors operative from the edge cells should modify the interior-cell condition. In practice, the computer selects a cell, studies all contiguous cells, re-computes, then moves to the next cell in sequence and repeats the study... usually for thousands of cells. The result is a cell having a factor (like presence of water or species x) or being adjacent to a cell with the named factor.We think contiguity analyses can shed new light on within-cell phenomena. Evident outside-cell phenomena of interest are roadway pollution, animal territory, riparian influence (Giles and Nielsen ( ), livestock influence, and human noise.

Nearness Add 2-3-4 cell groups idea.

Figure 1. Map cell B is contiguous to cell C but whether call A is contiguous to all C (or, if so, should its data be treated in the same way as that of cell B) has been a problem in some analyses.

Cell contiguity, by definition, means map cells touching each other. Whether A in Fig. 1A is touching cell C in the same way that cell B touches is an important question for the analyst, but we think it too detailed for now. We are advocating an evolutionary step, not perfection (as might exist if mapping were done with small hexagons). Contiguity is one condition along a nearness continuum. Touching is maximum nearness; the minimum is probably approximately half the circumference of the Earth. The relevant distance is probably several hundred miles, perhaps the distance of a long ungulate migration or flights by pairs of bird breeding or in over-wintering sites. We are of the view that each map cell is also a function of or potential support for phenomena in other cells, more or less near.

We once worked on direct solar radiation (Lawrence ) to a surface cell but, now seek to study that radiationas it may be influenced by intermediate mountains. The solar radiation received by the plants in a cell is not only a function of its date and latitude but by topography kilometers away.

Figure 2. Not contiguity but nearness to a feature may be an important factor to be mapped, cell by cell. Off-site or out-of-cell factors may be more influential in explaining the variance in some mappable factor than within-cell factors usually analyzed.

The radiation directly influences plant survival growth: even sugar content of mast, thus food quality. If future managers are serious about computing forage-based populations, they will include nearby, out-of-cell phenomena (Figure 2, the influence of factors in Z on C) in their analyses.

The literature on "landscape ecology" has grown rapidly. We applaud only its practical contribution to faunal systems management which is that manageable wild macrofauna in a spatial volume are a function of things contiguous and things far away, things on nearness sequences. Managers remember that permutations of things are all possible sequences of combinations of things and is computed as n! Where n is 20, then the permutations are 2.4 x 10¹⁸. In faunal systems work for over 70 years people have discussed patchiness, interspersion, fragmentation, and edge relations, all of which are correlated. All are expression of why one cell is better or worse than another for a species. It is better (or not) due to its surroundings, things outside the cell, and some are strongly related the more near the cell; others conditional (if present, then the animal can exist); and some negatively related (e.g., pollution emitting sources, nesting sites). We are of the view that nearby out-side-the-cell phenomena observations may explain more of the variance within animal populations (as of typical interest) than carefully, costly made within-cell, site observations.

Cumulative

Figure 3. All conditions in cells surrounding C may be accumulated and made a new mappable factor for cell C, then the computer instructed to move to cell D to repeat the operation (and similarly for all cells; the "roving-window" concept).

When a map cell is seen as the topic of interest, however tentative the interest (because thousands more are likely to be examined for any faunal resource management system), then factors above or below the traditional mappable area can be seen to come into play from aggregate soil-layer influences to forest strata, to pollutants or radiation limiting components of the atmospheric layers. More clearly evident (Fig. 3) is the possibility of creating new maps, expressions of the actual or potential cumulative effects of nearby cells. Most modern geographic information systems have "nearness-to" functions. Used with raster (cell) data, these functions with additive operators can produce maps of, for example, animal center-of-activity cells with estimated available forage in surrounding cells.

Landscape ecology measures (Forman and Godron 19 ) tend to take on relevance to faunal systems when a map cell (the hypervolume discussed above) is seen as the topic of interest. Outside-cell conditions can be analyzed as contiguous, cumulative, or distant i.e., at various places on a continuum. Faunal space is analyzed and some cases evaluated, i.e., characterized for its value (at least relative value) to a species or taxon being managed. We suggest that neither analysis nor evaluation be done without there being a role for such evaluation within a planning system.

A planning system is a dynamic computer system for producing reports. Once called "plans", those reports are now conceived as being newspapers, used but discarded tomorrow. Plans, these "dusty books on the shelf", are no longer relevant now that computer capabilities exist for word processing, mapping, analyses, expert systems, and multimedia presentations from CD-ROMs. The faunal space analyses, we believe, should emerge from clear needs within the planning system design. Specific information is denoted as needed. Field observers collect the data, analysts work on it and entries are made to the system. Because all parts of a well-designed system are tightly linked (as if itself is an ecosystem), then any change may cause changes throughout the system. A report today may differ from that tomorrow in any (or all) parts of the system, not just some numerical changes in a table or a change in a few map cells in one of 25 maps in a document.

The planning system is based, as we currently are designing one, the interactive economics, ecologic, esthetic, and energetic components. The key ecologic components are atmosphere, hydrosphere, lithosphere, and biosphere. The overriding paradigm is that of "general systems theory". The more we work with and study the planning system, the more we realize it can (and we think "should") become the core of the faunal system agency or company, the central theme or organizing pattern. We think that people's needs and wants are achieved in space, the same places where wild animals live. To understand them both, requires detailed analyses and then use of these analyses to create a sequence of actions needed to achieve optimum conditions. Faunal resource systems include maps, but that is merely a way to depict a place or space where a resource exists. A resource is a four-factor entity -- valued energy (or matter), time, space, and variety (Watt 19 Odum ). Planning systems that include the elements we have listed can serve faunal resource management systems well in the future.

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Last revision April 3, 2001.